Environmental Science and Technology

Environmental Science and Technology (2014) Volume 1

Edited by

George A. Sorial Jihua Hong ISBN 978-0976885368

Library of Congress Cataloging-in-Publication Data Environmental Science and Technology 2014 Vol. 1 Proceedings from the 7th International Conference on Environmental Science and Technology, held on June 9-13, 2014 in Houston, Texas, USA Includes bibliographical references

ISBN: 978-0976885368 I. Sorial, George A. II. Hong, Jihua III. International Conference on Environmental Science and Technology (7th : 2014 : Houston : Texas)

Printed in the United States of America Copyright © 2014 American Science Press. All rights reserved. This document, or parts thereof, may not be reproduced in any form without the written permission of the American Science Press. Requests for permission or further information should be addressed to the American Science Press, 9720 Town Park Dr. Ste. 18, Houston, TX 77036, USA Email: [email protected] Website: www.AASci.org/conference/env ISBN 978-0976885368 © 2014 American Science Press

Environmental Science and Technology (2014)

Volume 1

Edited by

George A. Sorial Jihua Hong

American Science Press, Houston, USA

Environmental Science & Technology 2014 Vol. 1

TABLE OF CONTENTS INTRODUCTION George A. Sorial and Jihua Hong …………………………………………………………....

1

PLENARY SESSION

Aerobic Sludge Granulation: Current Perspectives, Advances and the Way Forward. Kuan-Yeow Show, Duu-Jong Lee, Yan Yuegen, and Joo-Hwa Tay ……………………..………….…..………… Hydraulic Fracturing, Water Conservation and Environmental Protection. Davis L. Ford ……..….

4 10

Global Climate Change -The Quantifiable Sustainability Challenge. Frank Princiotta ……………

11

Development of a PV-Powered Electrochemical Wastewater Treatment System. Michael R. Hoffmann, Kangwoo Cho, Clement Cid, and Qu Yan ………………………….…………....… Evolving Conceptual Model of Natural Attenuation of Groundwater Plumes. Charles J. Newell and David T. Adamson …………………………………………………………………………………..

12 13

WATER POLLUTION AND WATER QUALITY Rivers, Lakes and Estuary Systems New Findings on Sources of Orthophosphate in Upper Malibu Creek Watershed: A Geologic Source Primarily? Barry Hibbs, Kathleen Kuepper, and Yola Wong K …………………………….……… Evaluation on Eco-security of Water Resources and Regulating & Control Mode of Environmental Planning for Lake Basin --- A Case of Taping Lake, Anhui Province, China. Xiangrong Wang… Key Issues for River Regulation: An Illustration from Dianchi Inflowing Rivers in China. Baoxue Zhou, Ke Huang, JinHua Li, Jing Bai, ZhuJing Jin, FengLe Yang. ……………………………..

15 16 17

Watershed Management Trace Element Mobilization by Oxidation via Anthropogenic Nitrate in Southern California Watershed. Yola Wong K, Barry J. Hibbs ………………………………………………………. Sustainable or Green Water Management Practices by South African Mining Companies. Mbofho Stanley Liphadzi & Andre Vermaak ……………………………………………………………………

18 19

Water Resources and Assessment Crude Palm Oil Production: Environmental Impacts Assessment of Freshwater Consumption Using LCA Approach. Zainura Zainon Noor, Noor Salehan M. Sabli, Che Hafizan Che Ahmad ……. The ART In-Well Technologies, Re-Engineering Existing Remedies to Reduce Time, Costs & Risks. Mohamed Odah …………………………………………………………………………………..………. Environmental Risk Assessment of Caffeine in Parana’s Rivers (Brazil). Maiara C. Perussolo, Isadora Terumi Saruhashi, Pauline Lais Nasatto, Andréa Fernandes, Eliane Carvalho de Vasconcelos, and Cíntia Mara Ribas de Oliveira. …………………………………………………… Progress on the Research of Flood Routing under the Effect of Seepage in Seasonal Streams. Wu Guizhi , Li ningning and Wu Zhouhu …………………………………………………………………..

i

20 21 22 23

Environmental Science & Technology 2014 Vol. 1 Mass Fluxes of Urban Micropollutants and Integrated Modelling of the River – Groundwater – Interaction in the City of Halle/Germany. Frido Reinstorf, Sebastian Leschik, Andreas Musolff2, Gerhard Strauch, Karsten Osenbrueck and Mario Schirmer....................................................... Improving Implementation Capacities of Cities by sharing best practices in Urban Water Cycle Services. Kees van Leeuwen ......................................................................................................... Sustainability of Water Resources of Ho Chi Minh City, Vietnam. N.C. Woo, Minh T. Ngo, Jae M. Lee ............................................................................................................................................... Assessment of Groundwater Recharge Using Water-Table Fluctuation Method and Water Balance Model. Sasmita Sahoo, Madan K. Jha .......................................................................................... Evaporation Reduction Based Design of Water Ponds surface Areas Using Palm Frond. Ibrahim Elsebaie ........................................................................................................................................ Hydraulic Fracturing: A Look at Efficiency and the Environmental Effects of Fracking. Emily C Jackson and David E Dismukes. ..................................................................................................

24 25 26 27 35 42

Groundwater Correlations between Chlorinated Aliphatic Hydrocarbons and Environmental Variables in a Contaminated Groundwater in Shanghai, China. Lu Qiang, Li Hui, Lin Kuang Fei, and Liu Yong Di .................................................................................................................................................. Remediation of Acidic Groundwater Using a Sodium Bicarbonate Injection System, Christina Brown, Paul Marotta, David Wall, Teresa Jordan, and Christina DeJarlais …………………….. A Comparative Study of Enhanced Bioremediation Techniques for a BTEX Compound (Toluene) in Contaminated Groundwater. B.K Yadav, Shreejita Basu, Anuj Mathur and Shashi Mathur……. Interactions of Arsenic Desorption and Indigenous Bacterial Activity in Shallow Groundwater System. Zuoming Xie, Guangming Ouyang, Xiaoyan Sun, Dong Yang, Yanxin Wang …………. Optimization of Fluoride Removal from Aluminium Smelter Contaminated Ground Water. Scott Sleap, Brett Turner, Kristian. KrabbenhØft and Scott Sloan ……………………………………….. A Pilot Scale Permeable Reactive Barrier for the Treatment of Spent Potliner Contaminated Ground Water. Brett Turner, Scott Sleap, Kristian. KrabbenhØft and Scott Sloan ………………………… Residues of Veterinary Antibiotics in Environmental Waters in Central Jianghan Plain, China. Tong Lei, Wang Yanxin, Liu Hui, Li Minjing ........................................................................................ Prediction of County-level Contamination Exceeding Rate from Groundwater Sampling Data through Intelligent Data Dependent Modeling. Qing Li, Fengxiang Qiao, Lei Yu …………….. Exploring the Influence of Dissolved Organic Matter on Phosphorus Mobility in Groundwater. Christine A. Rumsey, Darwin L. Sorensen, David K. Stevens, Joan E. McLean ……………….. An Analysis of Groundwater Chemistry of Hot Springs in the Soutpansberg Basin in South Africa. Ayanda Shabalala, A.P.K. Nyabeze and Zuko Mankayi. …………………………………………….

47 48 49 55 56 57 58 59 65 66

Non-point Sources Atmospheric Reactive Nitrogen Deposition onto Coastal Regions of China. Xiaosheng Luo and Xuejun Liu ……………………........................................................................................................ Nutrient Load Predictions in Streams using LS-SVM and Wavelet-ANN. Raj Mohan Singh ……..

67 68

Wastewater Discharge Management The Study of Destructive Effects of Wastewater Caused by the Activities of leather Manufacturing Factories in Tehran. Shobeiri Seyed Mohammad, Kavei Behrouz, Shotorbani Azarmir Marjan, Alireza Bassiri, Nazari Batoul ...................................................................................................... ii

77

Environmental Science & Technology 2014 Vol. 1 Theoretical Analysis of Pollutant-Mixing Zone for Rivers with Variant Lateral Diffusion Coefficient. Zhou-hu Wu, Wen Wu ............................................................................................................... Effect of Textile Effluent on Germination and Growth of Gram. Monika Chandel, Tank Shantilal K..

78 83

In-Situ Measurement and Monitoring Monitoring of Cyanotoxin and T&O Compound Producing Cyanobacteria in Drinking Water Reservoirs using qPCR Method. Tsair-Fuh Lin, Yi-Ting Chiu, Hung-Kai Yen A Novel Flow-cell for in situ Spectrophotometric Detection of Contaminants in Water Samples. Emanuele Reggiani, Richard Bellerby, Kai Sørensen A Microfluidic Colorimetric Analyser for pH in Water. John Cleary, Deirdre Cogan, Thomas Phelan, Kamil Jankowski, Dermot Diamond

88 89 90

Drinking Water Sustaining Safe Drinking Water Supply in Developing Countries: Lebanon Case Study. Mey Jurdi.. Biological Desalination of Seawater Using Marin Microalga Scenedesmus sp. and Chlorella vulgaris. E. Sahle-Demessie, Ashraf Aly Hassan, Amy Zhao……………………………………….. Analysis for Atmospheric Water for Drinking. Qing XIA and Shu GENG ……………………………. Source Water Protection for Drinking Water Production: A European River Memorandum. Peter G Stoks and Ina Brüning .................................................................................................................. Community Water Supply and Treatment Project in Cameroon: Chlorinator Design and Development. Kristen Chorney and Sam Miller........................................................................... Vulnerability Assessment of Small Community Water Systems in Puerto Rico. Adaíl AliceaMartínez, Rafael A. Rios ...............................................................................................................

91 92 93 94 95 96

Water Quality Assessment/Management An Independent Investigation into the Physico-Chemical Purification Capacity of Gravity Fed Home Water Treatment Devices Supplied in South Africa. Cherie Ann Kruger, Tobias George Barnard, Natasha Hodgkinson and Cathleen Bartie ................................................................... Improving Surface Water Quality of Agricultural Watershed using Planned Intervention Microwatershed Approach. Durga D. Poudel. ............................................................................ An Analytical Model for Pollutant Transport in the Rosetta Branch of the Nile River, Egypt. Mohamed Mostafa and Robert W. Peters. ................................................................................... Polychlorinated Biphenyls (PCBs) in Industrial and Municipal Effluents: Concentrations, Congener Profiles, and Partitioning onto Particulates. Aparna Balasubramani, Hanadi S. Rifai, and Nathan L. Howell. .................................................................................................................................... Characteristics of Optimization Problems for Coastal Ground Water Management. Karen Ricciardi Quantifying E. coli Discharge from Onsite Sewage Facilities in the Dickinson Bayou Watershed, Texas. Derek Morrison, Clyde Munster, R. Karthikeyan, John Jacob……………………………. Impact of Soil Type on the Salt Accumulation Due To Recycled Water Irrigation. Muhammad Muhitur Rahman, Dharma Hagare, Basant Maheshwari and Peter Dillon……………………….. Diversity of Aquatic Flora in Relation to Water Quality in Kolleru Lake, Andhra Pradesh, India. P. Brahmaji Rao ............................................................................................................................... Heavy Metal Analysis in Catchment and Fish Communities of Mista-Ali Tin Mine Lake, MiddleBelt Nigeria. Jatau-Emeagha, G. L, Wade, J.W.W and Ufodike, E.B.C …………………………… Study on Water Quality Variation during Rainfall Runoff Evolution Process in a City Residential District. Huaien Li, Jiake Li and Zengchao Liu. ......................................................................... iii

97 98 99 100 106 107 108 109 110 119

Environmental Science & Technology 2014 Vol. 1 Low Cost Autonomous Sensing Platforms for the Direct Determination of Nutrients in Water. Deirdre Cogan B, John Cleary, Kamil Jankowski, Dermot Diamond, Mark Bowkett ………….. QUAL2K Water Quality Analysis and Source Locations Identification: A Case Study of North Buffalo Stream. Jenberu Feyyisa, Shoou-Yuh Chang ………………………………………………. Technical, Financial and Administrative Capacity Evaluations and Improvement of Small Community Water Systems in Puerto Rico. Adaíl Alicea-Martínez, Rafael A. Rios ……………..

120 127 128

Nitrogen-Phosphorus Wastewater Treatment / Sludge Treatment Simultaneous Removal of Ammonia and Nitrate by Electrolytic Decomposition as Tertiary Wastewater Treatment. Jing Ding, Qingliang Zhao, Wei Li, and Kun Wang. …………………… Enhancement of Anammox Biomass Activity with External Electric Field Application. Sen Qiao, Xin Yin, Jiti Zhou, Yingjun Cheng ................................................................................................ Anaerobic Oxidation of Ammonium Coupled to Electricity Production in a Microbial Electrolysis Cell. Bo Qu and Bin Fan. ............................................................................................................ Effect of Bamboo Biochar on Fertility and Nutrient Leaching of a Sandy Pear Orchard Soil in Southeast China. Lou Liping, George A.Sorial ...........................................................................

134 140 146 147

Sludge Treatment Changes of Bacterial Community Diversity in Oxic-Settling-Anaerobic (OSA) Activated Sludge Process. Lianpeng Sun, Jinxin Tan, Xiaoyu Yu, and Lili Chen…………………………………….. Identification and Characterization of Dye Degrader Microbes in Microbial Granular Sludge Treating Synthetic Textile Wastewater. K. Muda, A. Aris, M.R.Salim, Z. Ibrahim, M.Z Nawahwi. Compost Bioremediation of Oil Sludge by Using Different Manures under Laboratory Conditions. Ubani O., Atagana H. I. and Thantsha M. S. …………………………………………………………. Identification and Characterization of Oil Sludge Degrading Bacteria Isolated from Compost Ubani O., Atagana H. I. and Thantsha M. S. and Adeleke R. ............................................................... Effect of Acid Treatment on Sewage Sludge Derived Carbons for Catalytic Wet Peroxide Oxidation. Yang Yu, Huangzhao Wei, Yamin Wang, Li Yu, Wentian Jiang, Songbo He, Chenglin Sun…….. Appraisal of Certain Anaerobic Digestion Studies. Ram Pal Singh and P. Pal ………………………

148 155 156 157 158 159

Municipal Wastewater Biotreatment Applying Static Magnetic Field on Physical Properties of Activated Sludge: Optimization through Response Surface Methodology. Nur Syamimi Zaidi, Khalida Muda and Johan Sohaili……….. Life Cycle Assessment of a Municipal Wastewater Treatment Plant- A Case Study in Kinmen, Taiwan. Huan-Yu Shiu and Pei-Te Chiueh. ................................................................................ Evaluation of Bacteria and Metals in Sewage Dump Site in Jos-Nigeria. Yakubu, Juliet M, Agarry, Olaitan O ..................................................................................................................................... The Effect of EPS on Mixed Liquor Characteristics and Membrane Fouling in UCT¬MBR Process. Qiongyuan Dong, Xiaonan Feng, Tao Tao, Lin Chen, Junhong Zhou and Guohong Yang…… An Approach for Selection of Wastewater Treatment Units using Analytical Hierarchy Process. Nekram Rawal, A.K.Sachan ......................................................................................................... Structure and Function of Dominant Microbial Community in Enhanced Aerobic Granular Sludge Process. Liang Zhu, Xiangyang Xu, Xin Dai, Jiaheng Zhou ………………………………………… Industrial Wastewater Biotreatment

iv

167 173 174 175 181 187

Environmental Science & Technology 2014 Vol. 1 Biogenic Manganese Oxide Generation and Mn(II) Removal by Manganese Oxidizing Bacteria using Response Surface Methodology. Narsi R. Bishnoi and Shalu. ……………………………… Reduction of Vinasse Soybean Pollution Using Different Strains of the Genus Cupriavidus Necator. Elizabeth dos Santos Costa Alexandre, Luiz Gustavo Lacerda, Marco Aurélio da Silva Carvalho Filho ............................................................................................................................................. The Application of Nitrification-Denitrification Process to Enhance Treatment Efficiency in Livestock Wastewater. B. S. Lee, S. S. Ton ................................................................................ Refinery Wastewater Treatment: A Challenge towards Zero Liquid Discharge. Farid Benyahia…… Examining Process Wastewater Treatment and Grey Water Footprint of Biofuel Produced via Fast Pyrolysis and Hydrotreating. May Wu .......................................................................................... Isolation of a Lysinibacillus Strain B1-CDA Showing Potentials for Arsenic Bioremediation. Aminur Rahman, Noor Nahar, Jana Jass, and Abul Mandal………………………………………………… Effects of Zinc on Germination, Seedling Growth and Nutrient Contact of Rauvolfia Serpentine. Milvee K. Vyas, Kailash Patel, Parimal Patel …………………………………………………………

188 194 195 200 201 202 203

Adsorption/Desorption for Wastewater Treatment Synthesis and Characterization of Cu(II) Imprinted Nanoparticles Based on Polyethyleneimine for Selective Recognition of Copper. Jin jia，Shengji Luan, and Aihua Wu. ……………………… Adsorption of Pb(II) on Nanoscale Iron-Oxide Doped Granular Activated Carbon. Zhihua Xu, Daofang Zhang and Weifang Chen …………………………………………………………………… Synthesis and Characterization of High Ordered Mesoporous Carbon (OMC) Using Polyacrylamide for Resorcinol Removal. Wan Shou, Hanlong Ren, Zhong Ren and Dianel Dianchen Gang…. Adsorption of Phenol onto Low Cost Adsorbent: Optimization of Adsorption Process Parameters Ramakant S. Ingole and Dilip H. Lataye …………………………………………………………….. Removal of Diclofenac Sodium and Carbamazepine from Water by Regenerable Granular Carbon Nanotubes/Alumina Adsorbents. Shubo Deng, Haoran Wei, Bin Wang, Jun Huang, Gang Yu … Fluoride Biosorption with Modified Eichhornia crassipes and Typha Elephantina. Suvendu Manna, Prosenjit Saha, Debasis Roy, Basudam Adhikari, Ramkrishna Sen……………………………… Removal of Chromium (VI) by Ethyl Cellulose Treated with Polyaniline. Bin Qiu, Zhanhu Guo, Cuixia Xu, Suying Wei ………………………………………………………………………………….. Synthesis and Structure Characterization of Modified Ordered Mesoporous Carbons for Total Organic Carbon (TOC) Model Compound (Resorcinol) Removal. Hanlong Ren, Wan Shou, Chong Ren and Dianel Dianchen Gang ………………………………………………………………. Characterization and Absorption Behavior of Ammonia and Methylene Blue by Biochar Derived from Common Reed. Lun Lu, Fengmin Li, and Zhi Liang. ………………………………………… Adsorption of Nicotine on Magnetically Separable Ordered Mesoporous Carbons in Aqueous Solution. Hsin-Yu Lin, Ya-hsuan Liou, and Pei-Te Chiueh. ……………………………………… Cleaning Metal Contaminated Water Using Pyrolyzed Banana Peels. Bluyé Demessie, E. SahleDemessie, George A. Sorial ……………………………………………………………………………. Ion Exchange/Adsorption/Desorption To Recover Nutrients from Conventional and Segregated Streams of Domestic Wastewater for Further Use as Fertilizer. Bilsen Beler Baykal …………… Elucidating the Role of Phenolics in the Effectiveness of DOM Adsorption on Activated Carbon. Liang Yan and George. A. Sorial ………………………………………………………………………. Removal of Fluoride from Water Using Chemically Modified Jute. Basudam Adhikari, Suvendu Manna, Prosenjit Saha, Debasis Roy…………………………………………………………………… Effect of Effluent Organic Matter on Organic Micropollutants Sorption onto Activated Carbon. Caroline Soares-Pereira, Romain Mailler, Adèle Bressy, Emilie Caupos, Lila Boudahmane, Mohamed Saad, Jonhy Gasperi, Vincent Rocher, Gilles Varrault …………………………… v

206 207 213 219 225 226 227 228 233 234 235 236 242 243 249

Environmental Science & Technology 2014 Vol. 1 Removal of Emerging Micropollutants from WWTP Discharges: Is Activated Carbon Adsorption Suitable for Wastewater Application? Romain Mailler, Johnny Gasperi, Yves Coquet, Cécile Cren-Olivé, Nathalie Cartiser, Sifax Zedek, Steven Deshayes, Adèle Bressy, Emilie Caupos, Régis Moilleron, Ghassan Chebbo and Vincent Rocher. ………………………………………… Biosorption of Heavy Metals from Aqueous Solution by Bacteria Staphylococcus aureus & Bacillus spp. Patel Ritixa, Tank Shantilal……………………………………………………………………….. Adsorption of Uranium, Strontium and Cesium in Radioactive Waste by Modified Attapulgite. Jie Yang, Na Guo, Jingsheng Wang, Haiyang Chen………………………………………………………

250 251 255

Physico-chemical Wastewater Treatment Bioinspired Gradient-structure Fibers for Water Collection at Micro- and Nano-level. Yongmei Zheng………………………………………………………………………………………………………... Advanced Oxidation Methods-Fenton Process for Dye Removal in Textile Wastewater. Macid Nurbas and Burak Dindas ……………………………………………………………………………… Unconventional Oil Contaminated Industrial Effluent Treatment by Catalyzed Hydrogen Peroxide and Sodium Persulfate. Niina Dulova, Eneliis Kattel, Marika Viisimaa, Anna Goi, Deniss Klauson, Marina Trapido, Alar Saluste, and Taavo Tenno. ……………………………………… Efficient Dechlorination of 2,4-Dichlorophenol in An Aqueous Media Using a Pd/TiO2NTs/Ti Cathode. Jiangkun Du and Jianguo Bao……………………………………………………………… Treatability of Aqueous Alcohol Ethoxylates Solution by Electrocoagulation and Coagulation. Çisem Ecer, Işık Kabdaşlı, Olcay Tünay, Tuğba Ölmez Hancı. …………………………………… Removal of Chromium Cr(VI) From Wastewater Using Saudi Activated Bentonite. Saad AlShahrani ………………………………………………………………………………………………….. Chromium(VI) Removal by a Fe-Mn Binary Oxide with and without H2O2. Si-Hyun Do and YongJae Kwon………………………………………………………………………………………………… Electrochemical Advanced Oxidation Process for Optimal Decontamination of Phenolic Wastewater Containing Inorganic Species. Nuhu Dalhat Muazu, Gulraiz Khan1 and Nabil Jarrah ……………………………………………………………………………………………………….

260 261 262 269 279 280 281 282

Reactions and Degradation of Wastewater Contaminants Continuous Treatments of Estrogens through Polymerization and Regeneration of Electrolytic Cells. Vo Huu Cong, Sota Iwaya and Yutaka Sakakibara ………………………………………………….. Assessment of Cometabolic Biodegradation Potential of Diclofenac in The Presence of Acetate under Anaerobic Conditions. Sevgi Sari, Emel Topuz, Egemen Aydin, Didem Okutman Tas…..

283 290

Nanotechnology Applications Graphene-Hapten-Based Nanosensor for Ultrasensitive Detection of Bisphenol A with an Optofluidic Biosensing Platform. Feng Long, Hanchang Shi. ………………..…………………… Effect of Freshwater Relevant Conditions on the Agglomeration of Titanium Dioxide Nanoparticles, Emel TOPUZ, Laura SIGG and Ilhan TALINLI……………………………………………………… Using Persulfate Activated by an Emplaced Zone of Iron Nanoparticles to Treat a Trichloroethylene Source Zone. Mohammed A. Al-Shamsi, Neil R. Thomson………………………………………… Mathematical Simulation of Nano Sized Aluminum Phages to Purify Water. V.K. Katiyar and Rohit Agarwal………………………………………………………………………………………………….. Interaction of Bacterial Biofilms with Engineered Nanoparticles, Hengye Jing, George Sorial, Ashraf Aly Hassan, E. Sahle Demessie, and Christina Bennett-Stamper. ………………………………… vi

291 292 293 294 295

Environmental Science & Technology 2014 Vol. 1 Evaluating Stability and Structural Changes of Nanocomposites and Developing Methods to Evaluate the Release of Nanoparticles. Amy Zhao, E. Sahle-Demessie, Heidi Grecsek ………… Preparation of a Novel Magnetic Nanoparticle Adsorbent and Its Adsorption Behavior of Arsenic in Groundwater. Shuqiong Kong, Yanxin Wang, Qinhong Hu and Abass K. Olusegun…………….. Surface Chemistry of Iron-Impregnated Mineral Oxides and Catalytic Activity for Oxidation of Aqueous Contaminants. Yue Li , Weile Yan. ………………………………………………………….. Electrocatalytic Characteristics of Hybrid MWCNTs and GNPs with Different Surface Morphology. Yanping Cui, Yu Zhu, Yaohui Wang, Yanyan Qin…………………………………………………….. Visible-Light Responsive Photocatalytic Fuel Cell Based for Simultaneous Wastewater Treatment and Electricity Generation. Baoxue Zhou, Jing Bai, JInhua Li and Suqin Jiang………………..

296 297 298 299 303

Water Purification Technologies Low Grade Heat: An Underused Energy Source for Desalination Using Membrane Distillation. Farid Benyahia. ……………………………………………………………………………………….….

304

AIR POLLUTION AND AIR QUALITY CONTROL Aerosol Performance of Aerosol Sampling Inlet from Aircraft Platform. Baoqing Wang, Shu Yao, Zebei Wang, Ronghui Chen, and Yangyang Li, Zhuoru Wang. …………………………………………

306

Air Quality Assessment Application of Factal Analysis to Assess of Air Pollutant Emission Rates in Opencast Coal MinesAn Innovative Approach. Mrinal K.Ghose…………………………………………………………… PLS-Path Model Analysis for Understanding the Cause-Effect Relationship of Ground Level Ozone Concentration. A. K. Gorai, F. Tuluri, and P. B. Tchounwou…………………………………….. Intra-urban Spatial and Temporal Comparison of Fine and Quasi-Ultrafine Particles in Houston TX. Yuncan Guo, Masoud Afshar, and Inkyu Han………………………………………………………. Non-Parametric Regionalized Model Performance Evaluation of PM2.5 Chemical Transport Models. Jeanette Reyes and Marc Serre. ……………………………………………………………. On-line Measurement of Aerosol from Desulfurization Flue Gas Based on Aerosol Mass Spectrometry. Pan Danping, Guo Yanpeng, Bao Jingjing, Yang Linjun………………………. Metabolic Characteristics and Community Diversities of Airborne Microbes at Different Functional Regions in Qingdao in Winter. WU Dengdeng, and SONG Zhiwe. ……………………………. Source Identification of Atmospheric Particulate Matter Using Radiocarbon and Molecular Source Markers. Hyun-Min Hwang, Bruce Buchholz, Thomas Young …………………………………… Air Pollutant Watch List of Texas – Port Arthur Example. Tara Capobianco, Ross Jones, and Darrell McCant……………………………………………………………………………………………………. Atmospheric Pollution in a North African City: The Ceuta Paradigma. S. Garcia Dos Santos, R. Fernández Patier, M.A. Sintes Puertas, A. Aguirre Alfaro, J. Alonso Herreros and S. Guevara Hernández, R. Benarroch Benarroch and J.M. Cantón Gálvez, Saul García ………………… Occupational Exposure to Chemicals in Nail Salons. Tasneem Islam, Margaret Back, Katherine Chin, Morgan Dashko, Alisa Feinswog, Aliza Heeren, Ben Krause, Molly Pearlman, Maia Rodriguez-Semp, Madeline Rosenberg, Emily Scharf, Shanlai Shangguan, Emily Weisfeld, Brett Aronson, Joseph Allen, Matt Fragala, Theodore Myatt, James Stewart, Laura Goldin………. Source Apportionment of Indoor PM2.5 at Santiago, Chile. Héctor Jorquera and Francisco Barraza. vii

312 313 314 315 316 317 318 319 320

321 322

Environmental Science & Technology 2014 Vol. 1 Atmospheric Carcinogenic Polycyclic Aromatic Hydrocarbons in Houston, TX, USA: Pine Needles as Passive Samplers. Sharmila Bhandari, Hyun-Min Hwang……………………………………… Effectiveness of Low Emission Zones: Analysis of the Changes in Fine Dust Concentrations (PM10) in 19 German Cities. Peter Morfeld, David.A. Groneberg, and Michael Spallek…………………. A Comparative Study of Economic Evaluation Methods on PM2.5 Health Impact. Hao Yin, Linyu Xu………………………………………………………………………………………………………….. Impacts of Vehicle to Infrastructure Communication Technologies on Vehicle Emissions. Qing Li, Fengxiang Qiao, Lei Yu ………………………………………………………………………………… A GIS-Based Spatial Analysis of Air Pollution in Nanning. Bo Wei, Fengxiang Qiao, Zhihu Huang, Juan Ma, Lei Yu …………………………………………………………………………………………. Vehicle Emission Analysis at Restaurant Drive-Through Facilities with Different Configurations. Keziah Hill, Mehdi Azimi, Fengxiang Qiao, and Lei Yu. …………………………………………… Prediction of Pollutant Concentration through the Consolidation of Multiple. Air Dispersion Models Using a Superensemble. Shoou-Yuh Chang and Frank Gronwald ………………………………. Effects of Quarry Operation Processes to Air Quality in Istanbul Cebeci Zone According to PM10 Emissions, Kadir Alp, İsmail TORÖZ , Edip Avşar, Ezgi Erdoğan, Banu Özlem, İlker Akmırza… Scenario Modeling as A Tool for Multi-Pollutant Policy Development in California. Joshua Cunningham, Nicole Dolney…………………………………………………………………………… The Use of Locally Manufactured Activated Carbon Filters for Indoor Air Quality Improvement. Abdullah M. Al-Qahtani, Waleed H. Al- Rwaily, Jamal Al-Radaideh …………………………

323 324 325 326 333 339 345 346 353 354

Transport of Pollutants Source Apportionment of Selected Heavy Metals in Aerosol Samples Collected from Sebele, Botswana. Alfred S. Likuku, Gilbert K. Gaboutloeloe and Khumoetsile B. Mmolawa………….. Study on an Ozone Episode over the Pearl River Delta, China. Jin SHEN, Hao CHEN, XueSong WANG, JinFeng LI, Wei LV, YuanHang ZHANG, Luan Yuan, Liuju ZHONG …………………..

355 356

Waste Gas Control Techniques Styrene Degradation by Biotrickling Filters with Single and Mixed Packings. Ailing Ren, Huanhuan He, Bin Guo and Xi Lv…………………………………………………………………………………… Treatment of Mixture of n-Hexane, Benzene, and Methanol in an Integrated Scheme of Cyclic Adsorption/ Desorption Beds and Trickle Bed Air Biofilter. Abderrahman Zehraoui and George A. Sorial…………………………………………………………………………………………………… Removal of Chloroform as a Model Trihalomethane in the Presence of Co Metabolite and / or Surfactant by Using Anaerobic Biotrickling Filter, Bineyam Mezgebe, George Sorial, E. Sahle Demessie and Ashraf Aly Hassan. …………………………………………………………………….

373 380 381

Air Pollutant Monitoring Wrestling with Fenceline Fugitives: Nuisance Air Monitoring. Ben Bolton, John Siler, and Rick Bolton……………………………………………………………………………………………………. Characterization of PM2.5-bound Nitrated and Oxygenated PAHs in Diesel Exhaust Particles. Meiling Hou, Jianjun LI, Wanglai Cen, Huaqiang Yin, Yangjun Wang ………………………… Daily and Seasonal Variations of Volatile Organic Compounds and Carbonyls in the Atmosphere of Monterrey, Mexico. H. Lizette Menchaca and Alberto Mendoza………………………………… Characteristics of Greenhouse Gas Emission in the Yellow River Delta Wetland. Qingfeng Chen, Junjian Ma, Hongyan Yang and Wenguo Dong…………………………………………………….. viii

382 383 384 385

Environmental Science & Technology 2014 Vol. 1 A Monitoring Study on Fine and Coarse Particulate Matter at Construction Sites. Harmonie A. Hawley, James Miller, and Brian O’Dell. ………………………………………………………….. 2012 Air Quality in Alberta Oil Sands Community of Fort McKay versus Canadian Urban Locations. Warren Kindzierski and Md. Aynul Bari. …………………………………………………………….. Development of Vehicle Emission Database for Air Quality Analyses. Po-Hsien Kuo, Fengxiang Qiao, Lei Yu ………………………………………………………………………………………………. Vehicle Emission Estimation while Picking up Passengers at Airport Terminals. Larry Hill, Fengxiang Qiao, Keziah Hill, Lei Yu …………………………………………………………………... Effective Approaches for Public Communication of Air Quality Results from Two Environmental Dredging Projects. Scott Manchester and Matt Traister ……………………………………………..

386 392 393 398 403

Hazardous Gas Biofiltration / Catalysts for Reducing Emission Methane Slip Emission Treatment by Pt/Pd/Al2O3 Washcoated Monolith with Spatial Concentration Measurements. Gregory Bugosh, Vencon Easterling, and Michael Harold………………………. Predicting SO2 Oxidation over a Pt/Al2O3 Diesel Oxidation Catalyst. Tayebeh Hamzehlouyan, Chaitanya S. Sampara, and William S. Epling ……………………………………………………….. Why Silver/Mesoporous Silica Catalyst is Unique for CO and HCHO Catalytic Oxidation Elimination? Zhenping Qu, Dan Chen and Xiaodong Zhang……………………………………..

404 405 406

Fuel Gas DeSOx, DeNOx, and Metal Removal The SO2 Removal Method of a Sulfuric Acid Process Exhausts Gas. Jianjun LI, Huaqiang YIN, Xin LI……………………………………………………………………………………………………………

407

Air Pollution Prevention and Management Charactering Air Pollutant Effects Caused by Extra Commuting Time due to Housing Price Factor. Ling Liu, Fengxiang Qiao, Lei Yu ………………………………………………………………………

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Noise Modelling of Road Traffic Noise during Journeys in Mumbai Metropolitan Region, India. Vishal Konbattulwar, Saurav Jain, and Nagendra R. Velaga* ……………………………………………..

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GLOBAL WARMING AND CLIMATE CHANGE Global Warming and Its Impacts Adaptation of Agricultural Sector to the Impacts of Climate Change in Saudi Arabia: Reallocation of Irrigation Water among the Comparative Advantage Crops. Ahmed M. Alabdulkader; Fawzi S. Awad; and Ahmed I. Al-Amoud …………………………………..………………………………….. Adaptation of Field Crops to Climate Changes Impact. Tawfik M.M., Thalooth A.T., E. M. Abd El Lateef, B. B. Mekki, Amany , A. Bahr and Magda , H. Mohamed ………………………………….. Influence of ENSO on Rainfall, Streamflow and Vegetation in Pranhita Catchment, India. Rajashree Vinod Bothale, Yashwant B. Katpatal …………………………………..…………………………… Performance Comparison of Methods for Temporal Precipitation Downscaling in Urban Area: the Kunming Case. Hua Bai, Siyu Zeng, Xin Dong, and Jining Chen ………………………………… ix

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Environmental Science & Technology 2014 Vol. 1 Better To Save A MW Rather To Generate A MW. Mehboob Alam Khan, Asif Hussain Siddiqui, Abdul Fawad …………………………………..………………………………………………………….

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Carbon Discharge Reduction The Interactions of Rock with CO2 and Brine under CO2 Sequestration Conditions. Y. Soong, L. Zhang, B. H. Howard, S. W. Hedges, R. Warzinski, R. Dilmore, D. J. Soeder, R. T. McClendon, M. L. Gray, I. Haljasmaa and D. Crandall ………………………………………………………….. Bioremediation and Biotransformation of CO2 Using Biocatalyst. Bhagat Chintan, Tank Shantilal K, Bhasar Sunilkumar, Dudhagara Pravin ………………………………………………………………. Space Distribution of Carbon Emissions in China. Mi Hong, Zhang Tiantian, Zhou Wei ………….

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INTRODUCTION The Seventh International Conference on Environmental Science and Technology 2014 was held in Houston, Texas, USA, June 9-13, 2014. The Program included 16 sections, containing 60 sessions with approximately 600 platform and poster presentations. This conference series strives to provide a platform for an extremely diverse group of environmental topics for engineers and scientists from around the world. Authors of the presentations accepted for the program were invited to submit their papers to the Conference Organizing Committee. More than 120 papers were received and then reviewed by the editors, session chairs, and the members of the Scientific/Technical Committee of the conference. Those papers and abstracts accepted for publication were assembled into two volumes. Sections are arranged basically according to their order listed in the original program except the sessions entitled Land (Soil, Waste Solid) Pollution and Remediation. This exception was made to balance the length of the two volumes. The conference also consisted of having a plenary session with four speakers from different universities at the United States and other countries. Environmental Science and Technology 2014 (Volome 1) contains the following sections: • Plenary Presentation • Water Pollution and Water Quality Control • Air Pollution and Air Quality Control • Global Warming and Climate Change Sections included in Environmental Science and Technology 2014 (Volume 2) are as follows: • Land (Soil, Waste Solid) Pollution and Remediation • Ecosystem Assessment and Restoration • Bio-Assessment and Toxicology • Wetlands and Sediments • Metals (Distribution, Removal, Remediation, Speciation, and Phytoremediation) • Chlorinated and Other Persistent Organic Compounds • Modeling • GIS for Environmental Assessment, Database, and Remote Sensing Applications • Environmental Analysis and Measurements • Society and the Environment • Environmental Planning and Management

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Environmental Science & Technology 2014 Vol. 1 • Renewable Energy Development We would like to especially thank the session chairs who were instrumental in the success of the conference. The Conference was sponsored and organized by the American Academy of Sciences, with financial contributions from the co-sponsors and supporting organizations. The papers in these proceedings represent the authors’ results and opinions. No sponsors, cosponsors, participating organizations or editors should be construed as endorsing any specific contents or conclusions in the proceedings.

George A. Sorial, Ph.D. University of Cincinnati

Jihua Hong, Ph. D. American Academy of Sciences

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PLENARY PRESENTATION

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AEROBIC SLUDGE GRANULATION: CURRENT PERSPECTIVES, ADVANCES AND THE WAY FORWARD Kuan-Yeow Show1, Duu-Jong Lee2, Yan Yuegen3, and Joo-Hwa Tay4 1 Puritek Environmental Technology Institute, Nanjing, China 2 National Taiwan University, Taipei, Taiwan 3 Puritek (Nanjing) Co., Ltd, Nanjing, China 4 University of Calgary, Calgary, Alberta, Canada ABSTRACT: Aerobic granulation was developed as a novel approach to agglomerating loose biomass into dense and compact biogranules. Compared with conventional biological flocs, aerobic granules are characterized by well defined shape and compact build up, superior biomass retention, enhanced microbial functions, and resilient to toxicity and shock loading. Their unique features lead to a promising prospect in overcoming the problem of biomass washout often encountered in activated sludge processes, thus offering a new dimension for wastewater treatment. This paper provides a review of current development in aerobic granulation. Factors affecting granulation such as seed sludge, type of substrate and organic loading, and mode of reactor operation are delineated. Maintaining granule structural stability is a major challenge of aerobic granulation. This paper also outlines approaches to addressing granule disintegration and stability for practical applications of aerobic granulation. Challenges and future work of aerobic granulation are also discussed.

INTRODUCTION Granulation is a self-immobilization phenomenon in which fluffy biological solids agglomerate as dense and compact granular sludge under controlled conditions. Aerobic granules possess superior characteristics such as distinct shape and structure, high settling velocities and biomass accumulation, and its ability to withstand high organic loadings (Tay et al., 2001). Because of its unique features, application of aerobic granulation is perceived as one of the promising technologies since it was developed in the 90s. Aerobic granulation has been investigated in various laboratory-scale bioreactors (Ho et al., 2010). Extensive work on granule characterization, factors affecting granulation, response of granules to various environmental and operating conditions, and granulation mechanisms has been documented. There is, however, limited study of pilot- or full-scale aerobic granular sludge systems. For practical industrial applications, continuous-flow reactors are preferred over sequential batch reactors (SBRs) for lower installation cost as well as simpler reactor operation, maintenance and control. However, it appears that maintaining granule of adequate structural stability poses a major challenge for full-scale operation. A study had revealed that aerobic granules developed in a continuous-flow reactor would disintegrate faster than those in a sequencing batch reactor (SBR) (Chen et al., 2009). On the other hand, it appeared that stable granule structure can only be sustained for a limited time in an SBR (Li et al., 2007). This paper presents a review on recent development in aerobic granulation. Factors affecting granulation and approaches to addressing granule stability are discussed. Challenges and future work of aerobic granulation are also outlined. FACTORS AFFECTING GRANULATION 4


Seed Sludge. Activated sludge has been used as seed in most aerobic granulation studies. Aerobic granules can also be cultivated by seeding completely autotrophic nitrifying microorganisms in SBR (Zhang et al., 2010). Different microbial community in seed sludge exhibited different agglomeration abilities arising from variation of physico-chemical characteristics (Bos et al., 1999) which can be associated with microbial strain, hydrophilic or hydrophobic nature, or it can be a result of certain extracellular polymeric substances (EPS) activities (Martienssen et al., 2001). The greater number of hydrophobic microbial community in the seed could result in faster aerobic granulation with excellent settleability (Wilen et al., 2007). Single culture aerobic granules using separate isolates from a phenol-fed aerobic granule had been successfully cultivated (Adav et al., 2008a). The isolates presented high phenol-degrading and high autoaggregation capabilities. Conversely, isolates with low auto-aggregation capability failed to develop into single-culture granules. Aerobic granules were cultivated using single culture Corynebacerium sp. DJ1 with high auto-flocculating and high phenol-degrading capabilities (Ho et al., 2010). The cultivated granules were subsequently used to degrade phenol at concentrations greater than 2500 mgl-1 with good efficiency. Substrate and Loading. Various types of substrate were used to cultivate aerobic granules. These included glucose, acetate, phenol, starch, ethanol, molasses, sucrose and other synthetic wastewaters (Adav and Lee, 2008). Inorganic carbon source dominated by nitrifying bacteria was used to cultivate aerobic granules (Tay et al., 2002; Tsuneda et al., 2003). Granules were cultivated from activated sludge using nitrobenzene as sole carbon and nitrogen sources (Wang and Zhou, 2010). The type of substrate dictates the diversity and dominancy of the bacterial species, granule surface, and structure (Liu and Tay, 2004). Aerobic granules have been cultivated with OLRs ranging from 2.5 to 15.0 kg chemical oxygen demand (COD) m-3d-1 (Moy et al., 2002; Liu et al., 2003). High organic loading enhanced biogas production causing higher upflow liquid velocity serving as a selection pressure for granulation (Hulshoff Pol et al., 1988). It was reported that optimal OLR for granulation was 2.52 kg COD m-3d-1 (Kim et al., 2008). While it had been found that granulation cannot be accomplished at OLRs less than 2 kg m-3d-1 (Tay et al., 2004), granules were successfully cultivated at OLRs of 1.05–1.68 kg COD m-3d-1 (Wang et al., 2009) over a cultivation period of a year. A long granule cultivation time of over 400 days using SBR fed with municipal wastewater with low OLR was recorded (Liu et al., 2010). Mode of Operation. It appears that aerobic granules had been successfully cultivated only in sequencing batch reactor (SBR). Settling time and exchange ratio of liquid volumes at the end of each SBR cycle serve as a selection pressure to remove non-granular biomass. Short cycle time results in short hydraulic retention time (HRT) favoring rapid granulation (Liu et al., 2007). Granules cultivated at 1.5 h cycle time showed the largest size, while those cultivated at 4h cycle exhibited the densest structure. Short settling time washes away poorly settling solids and retains only well settling granules (Hu et al., 2005). A shift in microbial community for granules cultivated at different settling times was noted (Adav et al., 2009). Short settling time leads to washout of non-flocculated strains, and the flocculated strains can be enriched in granules without competition from non-flocculated strains being washout. It had been hypothesized that periodic starvation in SBR increases cell surface hydrophobicity, which in turn facilitates aerobic granulation (Liu et al., 2004). Conversely, starvation may be detrimental to surface hydrophobicity (Castellanos et al., 2000) while starvation cycle is not a prerequisite for aerobic granulation (Liu et al., 2007; Liu and Tay, 2008). Environmental Factors. It appears that dissolved oxygen (DO) in the liquid is not a dictating factor for aerobic granulation, as granules can be developed at DO levels as low as 0.7-1.0 mgl-1 (Peng et al., 1999) to as high as 2–6 mgl−1 (Tsuneda et al., 2003). While most aerobic granulation work was carried out at 20– 25 ºC, granulation was reported in a SBR operated at 8ºC. The granules cultivated were in irregular shape with excessive growth of filamentous microbes, causing severe biomass washout and unstable operation (de Kreuk et al., 2005). The pH of reactor liquid has a profound impact on the microbial growth. Fungi would become prolific at low pH and may play a role in the initial granulation (Williams and Reyes, 2006). 5

Environmental Science & Technology 2014 Vol. 1 It has been observed that granulation at a pH of 4.0 was dominated by fungus with granule size approaching as large as 7 mm. At a higher pH of 8.0, granulation was dominated by bacteria with granule size reduced to 4.8 mm (Yang et al., 2008). GRANULE STABILITY Deterioration in granule stability over time is a common issue of aerobic granulation for full-scale operation. Studies have shown that aerobic granules would disintegrate after prolonged operation (Lee et al., 2010). Overgrowth of filamentous bacteria can lead to fluffy and loose granules that are unstable and can be easily washed out of the reactor. Liu and Liu (2006) showed that overgrowth of filamentous microorganisms can lead to reactor failure when the DO was low. It has been shown that strong shear force caused by intense aeration would also provide sufficient oxygen to suppress filament growth (Adav et al., 2007). Zheng et al. (2006) noted that at a high OLR of 6.0 kg COD m−3 d−1, granules grew larger with remarkable filamentous growth but gradually deteriorate in stability. Granules became unstable at high OLRs of up to 8 kg/m3-d (Tay et al., 2004). When granules grow oversize to such an extent that its radius is larger than the oxygen transfer limit, anaerobic conditions could develop within the granule. Inherent anaerobic metabolites such as fatty acids and biogas can weaken the granule internal structure resulting in disintegration of granules (Zheng et al., 2006). It was reported that rupture of mature granules is attributable to clogging of pores and channels in granules, hence hindering nutrients intake by the microbes (Lemaire et al., 2008). Moreover, mineral complexes associated to granule EPS matrix would dissolved at low pHs causing damages to the granule. It was observed that granule became unstable during an extended idling period under high storage temperature (Tay et al., 2004). A high storage temperature in the absence of substrate supply can lead to endogenous respiration and a rapid disintegration of the granules. It has been reported that EPS constituting proteins, polysaccharides, humic acids, and lipids secreted by bacteria help to initiate aerobic granulation process (Liu et al., 2004). It was hypothesized that EPS bridge bacterial cells and other particulates into an aggregate forming the precursor of a granule (Liu et al., 2004). Non-soluble beta-polysaccharides form the outer shell of aerobic granules to withstand shear (Wang et al., 2005). On the contrary, a non-cellular protein core in aerobic granules provides mechanical stability to the granule (Zhang et al., 2007). Granule structure is supported by a network composed principally of β-polysaccharides as the backbone for embedment of proteins, lipids, α-polysaccharides, and cells, and hydrolysis of β-polysaccharides caused disintegration (Zhang et al., 2007). In essence, enrichment of certain EPS enhanced microbial granulation and granule stability. CHALLENGES AND FUTURE WORK Maintaining granule with adequate structural integrity is one major challenge that hinders practical application of aerobic granulation. Current bottleneck of aerobic granulation development highlights the need for further research in granule stability for full-scale operation. There is a need to explore ways or techniques in developing granules with sustainable integrity. A few strategies were proposed to enhance granule stability for practical operation. It has been established that applying an appropriate OLR is essential to control granule stability (Li et al., 2010). Li et al. (2010) proposed that operating at high OLRs (>2.0 kg COD m-3d-1) is an effective strategy to control fungal bloom and maintain granule stability. Conversely, granules subject to high OLRs may disintegrate (Moy et al., 2002; Zheng et al., 2006; Liu and Liu, 2006; Adav et al., 2008b). Overgrowth of filamentous microorganisms could result in granule disintegration when the DO is inadequate especially operating at high OLRs (Liu and Liu, 2006). Granules may grow oversize at high OLRs, and DO may not be diffused into the internal matrix due to limitation of mass transfer. This would create an anaerobic environment beyond the DO diffusion limit extending into the granule core (Zheng et al., 2006). The subsequent anaerobic metabolites such as volatile fatty acids and biogas including the toxic hydrogen sulfide may damage the granule structure leading to disintegration. Instead of allowing fast6

Environmental Science & Technology 2014 Vol. 1 growing filamentous microbes to thrive in the culture, promoting slow-growing organisms such as phosphate or glycogen accumulating bacteria could enhance granule stability at low oxygen saturation (20%) (de Kreuk et al., 2004). Other slow-growing microbes such as the denitrifiers would thrive with nitrate or nitrite supplement, which could penetrate into the granule core. In essence, granule structure can be strengthened by promoting heterotrophic growth within the granule. Studies revealed that addition of Ca2+ ions accelerated aerobic granulation (Jiang et al., 2003), and bacterial alginate reacted with calcium ions principally contributed to stability of aerobic granules (Lin et al., 2008). Accelerated formation of granules with larger size and denser interior was reported in reactor dosed with 10 mgl-1 Mg2+ (Li et al., 2009) and 100 mg Ca2+ l-1 in the feed (Jiang et al., 2003). A technological know-how for cultivating granules of adequate structural stability for storage has been described for the first time (Lee et al., (2010). It appears that the drying did not cause notable impact on the granules in terms of morphology and functionality. The granules were recuperated after being dried for 21 days. It was reported that COD removal of the dried granules upon recuperation was not affected by the drying. The removal efficiency was comparable with active fresh granules without subjecting to drying. The finding may suggest the use of drying as a novel treatment of granule for storage purpose. The novel drying technique of aerobic granules would allow convenient storage and handling of granules for use as inoculums for rapid startup and as granule supplement to enhance treatment. Further research is needed to ascertain other impact of the drying such as settleability, density, surface hydrophobicity, specific oxygen uptake, strength and ECP content of granule. To further explore the potential of aerobic granulation, the following studies are proposed: (1) Enrichment and distribution of certain EPS components in promoting granulation and maintaining granule stability. Using CLSM coupled with specific florochromes, spatial distribution of proteins, α-, β-polysaccharides, and lipids within the granule can be examined for a better understanding on granule internal structure and stability. (2) As most research work on aerobic granulation has been based on SBR sequencing operating mode, aerobic granulation in continuous operating mode need to be established. Continuous operation of reactor is advantageous over batch or sequencing mode for efficient full scale operation. (3) Coupling granulation technology with other treatment systems, for example MBR to complement benefits from both processes. Cultivation of aerobic granules with genetically engineered microbial species with multiple targeted genes for removing multiple toxicants by single transformed bacterium. Treatment capacities of aerobic granulation system can be easily adjusted to accommodate varying loading rates, wastewater composition, and treatment goals by bioaugmentation with genetically engineered granules. (4) Use of drying as a treatment of granule needs to be explored to ascertain stability of aerobic granules and other impact of the treatment. Novel treatment of granules would allow convenient storage and handling for use as inoculums and as granule supplement to enhance treatment of existing systems. CONCLUSIONS Aerobic granulation evolves as a promising technique for high strength and/or toxic wastewater treatment. Stability of aerobic granules for practical applications remains a major challenge that has yet to be resolved. There is a need to explore ways or techniques in developing granules with sustainable integrity. Strategies for generating a more stable granule including selection of slow-growing microorganisms, inhibiting the activity of anaerobic bacteria, along with strengthening the core of the granule were heartening, while findings of granule cultivated with durable stability in a continuous-flow reactor, and granule storage with drying technique are encouraging. The novel drying technique of aerobic granules would allow convenient storage and handling of granules for use as inoculums and as granule supplement. Further research is needed to ascertain other impact of the drying, and to ascertain stability of granules in pilot- and full-scale long-term operation and storage. REFERENCES 7


Adav, S. S., D. J. Lee and J. Y. La. 2007. “Effects of aeration intensity on formation of phenol-fed aerobic granules and extracellular polymeric substances.” Appl Microbiol Biotechnol 77:175–182. Adav, S. S. and D. J. Lee. 2008. “Extraction of extracellular polymeric substances from aerobic granule with compact interior structure.” J Hazard Mater 154:1120–1126. Adav, S. S., D. J. Lee and J. Y. La. 2008a. “Intergenetic coaggregation of strains isolated from phenoldegrading aerobic granules.” Appl. Microbiol. Biotechnol 79:65-661. Adav, S. S., D. J. Lee, K. Y. Show and J. H. Tay. 2008b. “Aerobic granular sludge: recent advances.” Biotechnol Adv 26:411–423. Adav, S. S., D. J. Lee and J. Y. La. 2009. “Aerobic granulation in sequencing batch reactors at different settling times.” Bioresource Technol 100:5359–5361. Bos, R., H. C. van de Mei, and H. J. Busscher. 1999. “Physico-chemistry of initial microbial adhesive interactions - its mechanisms and methods for study.” FEMS Microbiol Rev 23:179–230. Castellanos, T., F. Ascencio, and Y. Bashan. 2000. “Starvation-induced changes in the cell surface of Azospirillum lipoferum.” FEMS Microbiol Ecol 33:1–9. Chen, Y. C., C. J. Lin, H. L. Chen, S. Y. Fu, and H. Y. Zhan. 2009. “Cultivation of biogranules in a continuous flow reactor at low dissolved oxygen.” Water Air Soil Pollut Focus 9:213–221. de Kreuk, M. K., and M. C. M. van Loosdrecht. 2004. “Selection of slow growing organisms as a means for improving aerobic granular sludge stability.” Water Sci Technol 49:9–17. de Kreuk, M.K., B. S. McSwain, S., Bathe, S. T. L. Tay, Schwarzenbeck and P. A. Wilderer. 2005. “Discussion outcomes.” In (Ed.), Aerobic Granular Sludge. Water and Environmental Management Series, pp.165–169. IWA Publishing, Munich. Ho, K. L., Y. Y. Chen, B. Lin and D. J. Lee. 2010. “Degrading high-strength phenol using aerobic granular sludge.” Appl Microbiol Biotechnol 85:2009-2015. Hu, L., J. Wang, X. Wen and Y. Qian. 2005. “The formation and characteristics of aerobic granules in sequencing batch reactor (SBR) by seeding anaerobic granules.” Process Biochem 40:5–11. Hulshoff Pol L. W., K. Heijnekamp and G. Lettinga. 1988. “The selection pressure as a driving force behind the granulation of anaerobic sludge.” In G. Lettinga, A. J. B. Zehnder, J. T. .C Grotenhuis and Pol L. W. Hulshoff (Eds.), Granular anaerobic sludge: microbiology and technology, pp.153–161. Kluwer, Wageningen. Jiang, H. L., J. H. Tay, Y. Liu and S. T. L. Tay. 2003. “Ca2+ augmentation for enhancement of aerobically grown microbial granules in sludge blanket reactors.” Biotechnol Lett 25:95-99. Kim, I. S., S. M. Kim and A. Jang. 2008. “Characterization of aerobic granules by microbial density at different COD loading rates.” Bioresource Technol 99:18–25. Lee, D. J., Y. Y. Chen, K. Y. Show, C. G. Whiteley and J. H. Tay. 2010. “Advances in aerobic granule gormation and granule stability in the course of storage and reactor operation.” Biotechnol Adv 28:919934. Lemaire, R., R. I. Webb and Z. G. Yuan. 2008. “Micro-scale observations of the structure of aerobic microbial granules used for the treatment of nutrient-rich industrial wastewater.’’ ISME 2:528-541. Li, J., K. Garny, T. Neu, M. He, C. Lindenblatt and H. Horn. 2007. „Comparison of some characteristics of aerobic granules and sludge flocs from sequencing batch reactors.” Water Sci Technol 55:403-11. Li, X. M., Q. Q. Liu, Q. Yang, L. Guo, G. M. Zeng, J. M. Hu and W. Zheng. 2009. “Enhanced aerobic sludge granulation in sequencing batch reactor by Mg2+ augmentation.” Bioresource Technol 100:6467. Li, A. J., T. Zhang and X. Y. Li. 2010. “Fate of aerobic bacterial granules with fungal contamination under different organic loading conditions.” Chemosphere 78:500–509. Lin, Y. M., L. Wang, Z. M. Chi and X. Y. Liu. 2008. “Bacterial alginate role in aerobic granular bioparticles formation and settleability improvement.” Separation Sci Technol 43:1642–1652.

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Environmental Science & Technology 2014 Vol. 1 Liu, Q. S., J. H. Tay and Y. Liu. 2003. “Substrate concentration-independent aerobic granulation in sequential aerobic sludge blanket reactor.” Environ Technol 24:1235–1243. Liu, Y. and J. H. Tay. 2004. “State of the art of biogranulation technology for wastewater treatment.” Biotechnol Adv 22:533–563. Liu, Y., S. Y. Yang, J. H. Tay, Q. S. Liu, L. Qin and Y. Li. 2004. “Cell hydrophobicity is a triggering force of biogranulation.” Enzyme Microb Technol 34:371–379. Liu, Y. and Q. S. Liu. 2006. “Causes and control of filamentous growth in aerobic granular sludge sequencing batch reactors.” Biotechnol Adv 24:115–127. Liu, Y. Q, W. W. Wu, J. H. Tay and J. L. Wang. 2007. “Starvation is not a prerequisite for the formation of aerobic granules.” Appl Microbiol Biotechnol 76;211–216. Liu, Y. Q. and J. H. Tay. 2008. “Infuence of starvation time on formation and stability of aerobic granules in sequencing batch reactors.” Bioresource Technol 99:980–985. Liu, Y. Q., B. Y. P. Moy, Y. H. Kong and J. H. Tay. 2010. “Formation, physical characteristics and microbial community structure of aerobic granules in a pilot-scale sequencing batch reactor for real wastewater treatment.” Enzyme and microbial Technology 46:520–525. Martienssen, M., M. Reichel and U. Kohlweyer. 2001. “Surface properties of bacteria from different wastewater treatment plants.” Acta Biotechnol 21:207-225. Moy, B. Y. P., J. H. Tay, S. K. Toh, Y. Liu and S. T. L. Tay. 2002. “High organic loading influences the physical characteristics of aerobic sludge granules.” Lett Appl Microbiol 34:407–412. Peng, D., N. Bernet, J. P. Delgenes and R. Moletta. 1999. “Aerobic granular sludge - a case report.” Water Res 33:890–893. Tay, J. H., Q. S. Liu and Y. Liu. 2001. “The effects of shear force on the formation, structure and metabolism of aerobic granules.” Appl Microbiol Biotechnol 57:227–233. Tay, J. H., S. F. Yang and Y. Liu. 2002. “Hydraulic selection pressure-induced nitrifying granulation in sequencing batch reactors.” Appl Microbiol Biotechnol 59:332–337. Tay, J. H., S. Pan, Y. X. He and S. T. L. Tay. 2004. “Effect of organic loading rate on aerobic granulation: Part II. Characteristics of aerobic granules.” J Environ Eng 130:1102-1109. Tsuneda, S., T. Nagano, T. Hoshino, Y. Ejiri, N. Noda and A. Hirata. 2003. “Characterization of nitrifying granules produced in an aerobic upflow fluidized bed reactor.” Water Res 37:4965–4973. Wang, F., F. Yang, X. W. Zhang, Y. Liu, H. Zhang and J. Zhou. 2005. “Effects of cycle time on properties of aerobic granules in sequencing batch airlift reactors.” World J Microbiol Biotechnol 21:1379–1384. Wang, S. G., L. H. Gai, L. J. Zhao, M. H. Fan, W. X. Gong, B. Y. Gao and Y. Ma. 2009. “Aerobic granules for low-strength wastewater treatment: formation, structure, and microbial community.” Chem Technol Biotechnol 84:1015–1020. Wang, D. Z. and L. X. Zhou. 2010. “Cultivation of aerobic granular sludge and characterization of nitrobenzene-degrading.” Huanjing Kexue 31:147–152. Wilen, B. M., M. Onuki, M. Hermansson, D. Lumle and T. Mino. 2007. “Microbial community structure in activated sludge floc analysed by fluorescence in situ hybridization and its relation to floc stability.” Water Res 42:2300-2308. Williams, J. C. and F. L. Reyes. 2006. “Microbial community structure of activated sludge during aerobic granulation in an annular gap bioreactor.” Water Sci Technol 54:139–146. Yang, S.F., W. Y. Li and H. Q. Yu. 2008. “Formation and characterisation of fungal and bacterial granules under different feeding alkalinity and pH conditions.” Process Biochem 43:8–14. Zhang, L. L., X. X. Feng, N. W. Zhu and J. M. Chen. 2007. “Role of extracellular protein in the formation and stability of aerobic granules.” Enzymes Microb Technol 41:551–557. Zhang, Z. J., W. W. Wu and J. L. Wang. 2010. “Granulation of completely autotrophic nitrifying sludge in sequencing batch reactor.” Huanjing Kexue 31:140–146. Zheng, Y. M., H. Q. Yu, S. J. Liu and X. Z. Liu. 2006. “Formation and instability of aerobic granules under high organic loading conditions.” Chemosphere 63:1791-1800. 9


HYDRAULIC FRACTURING, WATER CONSERVATION AND ENVIRONMENTAL PROTECTION Davis L. Ford (University of Texas Austin, Davis L. Ford & Associates, Austin, Texas 78746, USA) The discovery of enormous amounts of energy reserves, mostly proven, which are in “tight” shale and sandstone formations, both oil and gas, is transforming the United States to be totally independent of foreign fossil energy. Our import energy has dropped from over 60% to less than 30% in the past few years, dramatically enhancing our GDP. Recently, the United States has passed Russia and Saudi Arabia in fossil fuel production. Currently, over 90% of U.S. energy demand depends on fossil fuel. Subsidies for “green energy” are now under review. While wind and solar energy are increasing in selected areas, biofuels and particularly ethanol, because of their huge water demand, are becoming less popular and cost effective. Natural gas is the least cost option for new power generation in most areas, and has a minimal greenhouse gas footprint. The fundamentals of this enhanced oil and gas extraction will be outlined in this presentation, with major emphasis on the associated water issues. It is imperative that the use of fresh water in the fracking process be reduced or eliminated through conservation and cost effective reuse of flowback and produced water generated in this process. The reuse technologies such as reverse osmosis, electrocoagulation, and related desal technologies generally are in place, but reduced costs per volume is essential in the overall enhanced oil and gas economics as well as the preservation of fresh water sources for human and crop irrigation uses. Although the fracking process normally occurs in depths of 8,000 feet or more below the surface, drinking water quality can be adversely affected by poor surface casing and/or imperfect cementing, as well as surface contamination from tank storage of fuel and trucking activities (spills and leaks)

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GLOBAL CLIMATE CHANGE -THE QUANTIFIABLE SUSTAINABILITY CHALLENGE Frank Princiotta (USEPA-National Risk Management Research Laboratory, Durham, NC 27711, USA) Humanity is on an unsustainable trajectory; developmental pressures, spawned by an increasing demand for resource intensive goods, foods and services, are altering the planet in ways that threaten the long-term well being of humans and other species. The presentation provides an updated analysis of the emission reductions needed to constrain this warming, and the energy technologies needed to achieve these emission reductions. Transparent modeling tools and the most recent literature are used, to quantify the challenge posed by climate change and potential technological remedies. The presentation examines forces driving CO2 emissions, how different emission trajectories could affect warming this century, a summary of mitigation options, and R&D priorities. Major focus is on the power generation and mobile source sectors both globally & for the United States, assuming a target of 50% Carbon Dioxide (CO2) emission reductions (from 2007) by 2050. The current generation of energy generation and end use technologies are capable of achieving less than half of the emission reduction needed for a serious CO2 mitigation program. New technologies will have to be developed and deployed at a rapid rate, especially for the power generation and transportation sectors. A discussion of the adequacy of the current global efforts to develop & demonstrate such technologies is also discussed.

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Development of a PV-Powered Electrochemical Wastewater Treatment System Michael R. Hoffmann, Kangwoo Cho, Clement Cid, and Qu Yan (Environmental Science & Engineering, California Institute of Technology, Pasadena, California 91125, USA) We have developed a transportable prototype wastewater treatment system designed for the treatment of raw domestic wastewater, human urine, human feces, and synthetic human waste analogues. After several hours of PV-powered electrochemical treatment, the turbid, black-water influent can be clarified with the elimination of the suspended particles along with the reduction or total elimination of the chemical oxygen demand (COD), total enteric coliform disinfection via in situ reactive chlorine species generation, and the elimination of measurable protein after 3 to 4 hours of PV-powered treatment. Our advanced prototype incorporates additional features such as a residual sludge handling unit, a hydrogen purification and filter system, a closed water reuse system, and microbial fuels cells. We have packaged our second-generation prototypes into modified shipping containers that are ready for field-testing in remote locations that lack traditional urban infrastructure. The electrochemical treatment units employ bismuth oxide doped titanium dioxide (BiOx/TiO2) electrode arrays with underlying layers of sequential nano-particulate coatings of IrO2, Ta2O5, SnO2, and Bi2O3. A robust kinetic model, which assumes a chemical reaction limited regime, is used to investigate the role of various redox reactions mediated by Cl- ion oxidation to chlorine and by hydroxyl radical generated at the electrode surfaces. Under current densities (J) higher than 200 A m–2, the oxidative elimination of the chemical oxygen demand (COD) and ammonium ion can be modeled using experimentally-determined pseudo first-order rate constants and current efficiencies In combination with a microbial fuel cell pretreatment step, the human urine and feces is processed. The COD, protein, and color are eliminated within 4 hours of continuous treatment. The treated water is then recycled for reuse. In the laboratory, we investigated the electrochemical treatment of real domestic wastewater coupled with simultaneous production of molecular H2 as useful by-product. The electrolysis cells employ multi-layer semiconductor anodes with electro-active bismuth-doped TiO2 functionalities and stainless steel cathodes. DC-powered Laboratory-scale electrolysis experiments were performed under static anodic potentials (+2.2 or +3.0 V NHE) using domestic wastewater samples, with added chloride ion in variable concentrations. A 95% reduction in chemical oxygen demand (COD) and ammonium ion were achieved within 6 hours. In addition, we experimentally determined a decreasing overall reactivity of reactive chlorine species towards COD with an increasing chloride ion concentration under chlorine radicals (Cl∙, Cl2–∙) generation at +3.0 V NHE. The current efficiency for COD removal was 12% with the lowest specific energy consumption of 96 kWh kgCOD–1 at the cell voltage of near 4 V in 50 mM chloride. The current efficiency and energy efficiency for H2 generation were calculated to range from 34 to 84% and 14 to 26%, respectively. The hydrogen comprised 35 to 60% by volume of evolved gases. The efficacy of our electrolysis cell was further demonstrated by a 20 L prototype reactor totally powered by a photovoltaic (PV) panel, which was shown to eliminate COD and total coliform bacteria in less than 4 hours of treatment.

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EVOLVING CONCEPTUAL MODEL OF NATURAL ATTENUATION OF GROUNDWATER PLUMES Charles Newell and David T. Adamson (GSI Environmental Inc., Houston, Texas, USA) Natural attenuation of contaminants that comprise groundwater plumes has evolved considerably since its origin in the 1980s. Up to 1994, there natural attenuation was described using terms such as “natural assimilation,” “natural biodegradation,” “intrinsic remediation,” and largely focused on aerobic biodegradation of hydrocarbon compounds such as benzene and other petroleum-related aromatics. Then in 1994 the U.S. Air Force issued a ground-breaking Draft Protocol for evaluating natural attenuation of fuel hydrocarbons, and in 1998 a Technical Protocol for Evaluating Natural Attenuation of Chlorinated Solvents in Ground Water was issued by the US Environmental Protection Agency. Both of these highutilized, highly-cited technical protocols had two things in common: • Recommended use of up to three lines of evidence: i) Documented loss of contaminants at the field scale, ii) Contaminant and geochemical analytical data, and ii) Direct microbiological evidence; • Emphasis on a few key naturally occurring biodegradation reactions in the plume downgradient of the source (direct oxidation reaction with naturally occurring electron receptors for fuel hydrocarbons, reductive dechlorination with naturally occurring electron donors for chlorinated solvents. By the mid-2000s these protocols had been applied extensively around the world, and formed the basis for managing contaminated groundwater plumes at hundreds of sites. In the past 10 years, however, there has been important new thinking about why, how, and where MNA is applied. Key new developments include: • Application to new contaminants such as fuel oxygenates, metals, radionuclides, dioxane and other emerging contaminants, and to new settings such as LNAPL and chlorinated solvent source zones; • Better appreciation of new attenuation processes including biogeochemical transformation of chlorinated solvents, natural source zone depletion; • Revisions to our understanding and reliance on mechanical dispersion, and a new understanding of when DNAPL is present in chlorinated solvent source zones and when matrix diffusion alone may be sustaining plumes; • New measurement tools such as more powerful compound specific isotope analyses and molecular biological tools; • New tools for evaluating MNA, including new analytical models such as U.S. EPA’s REMChlor model, mass flux based dilution calculations, and matrix diffusion models; • A growing recognition that long term and lengthy restoration processes may be inevitable (Leeson et al., 2013; ITRC, 2011) and that “Transition Assessments” may be needed to determine when to transition from active treatment to long-term, more passive treatment such as MNA (National Research Council, 2012). These developments paint a picture where the useful, but narrow original conceptual model of MNA (a single biodegradation reaction in the groundwater plume is evaluated) is being replaced by a broader, more powerful MNA conceptual model that includes dilution at exposure points, long-term storage in low permeability zones, and a diverse assortment of degradation reactions that is applied to a wide variety of contaminants, problems, and management roles.

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WATER POLLUTION AND WATER QUALITY CONTROL

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NEW FINDINGS ON SOURCES OF ORTHOPHOSPHATE IN UPPER MALIBU CREEK WATERSHED: A GEOLOGIC SOURCE PRIMARILY? Barry J. Hibbs, Kathleen Kuepper, and Yola Wong K (California State University, Los Angeles, CA, USA) Recent studies have suggested dissolution of geologic strata by percolating groundwater is the most important source of orthophosphate during dry weather flow conditions (2 weeks after any rain event) in Upper Malibu Creek Watershed of Southern California. The earliest concepts on nutrient levels in the watershed, which were somewhat anecdotal, pointed to urban runoff as the principal source of orthophosphate in residential and commercially developed parts of the watershed. More recently, it has been established that baseflow is a principal source of dry weather stream flow in many parts of the watershed. The observation that creeks are fed to a significant extent by groundwater, and that orthophosphate is elevated in the creeks along the upper watershed corridor (where Monterey/Modelo Miocene marine strata are the main source rocks feeding baseflow into the creeks and streams) led some investigators to conclude that the phospatic member of Monterey/Modelo strata is the source of elevated orthophosphate. Concentrations in surface water in Upper Malibu Creek Watershed are typically in the range of 0.4 to 1.0 mg/L dissolved orthophosphate. To test the hypothesis of geologic origins of phosphate in the upper watershed, we undertook extensive studies to evaluate geologic and other sources. Our studies included extensive sampling of stream water, shallow groundwater, dry weather urban runoff, and hyporheic zone water. Water samples were analyzed for nutrients, standard inorganic constituents, and stables isotopes of oxygen, hydrogen, sulfur, and nitrogen. Our findings indicate that groundwater sourced directly from Monterey/Modelo strata contains less than 0.3 mg/L dissolved orthophosphate in more than 95% of groundwater samples, while urban runoff sourced from both tap and reclaimed water sources contains 0.2 to 9 mg/L dissolved orthophosphate. Mass balance analysis demonstrably points to the fraction of urban runoff (10 to 40%) to be an additive source of orthophosphate that at least doubles the concentration in the developed parts of the watershed. Orthophosphate loading from dry weather urban runoff blends with baseflow and undergoes complex processes in stream riffles and pools, and especially within the hyporheic zone, to both remove and release orthophosphate into pore water and stream water. The hyporheic zone processes seem to favor release of sorbed orthophosphate due to abundant organic matter that creates semi-oxic redox conditions and reactions in interstitial spaces to mobilize orthophosphate while competing for clay sorption sites. Our studies indicate that hyporheic zone processes and urban runoff are more important source of orthophosphate than loading from baseflow from the Monterey/Modelo strata proper.

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EVALUATION ON ECO-SECURITY OF WATER RESOURCES AND REGULATING & CONTROL MODE OF ENVIRONMENTAL PLANNING FOR LAKE BASIN --- A CASE OF TAPING LAKE, ANHUI PROVINCE, CHINA Xiangrong Wang (Fudan University, Shanghai 200433, China) Under the guidance of 'source-flow-sink' of ecological theory, the eco-security evaluation and regulating & control mode for environmental planning of water resource in Lake basin were carried out in this paper from the research of water system, wetland and vegetation system, farmland system, point and non-point source pollution, geological disaster and ecological sensitivity using the coupling evaluation methodology of EF-ES model and 3S (RS, GIS and GPS) techniques within 1770 km2 of Taiping Lake Basin, Anhui Province, China. The SWOT conditions of main resource and eco-environmental issues were identified for the study of environmental capacity, eco-vulnerability and carrying capacity as well as ecosystem service function in both lake body and lakeshore area. The environmental planning and management strategies of regulating and control mode for water resource were put forward. This paper aims to study the methodology of ecosecurity evolution and regulating & control mode of environmental protection planning for water resources of whole lake basin, and explore for a benign circulation mechanism of economico- socio development and environmental protection by taking Taiping Lake Basin as an example.

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KEY ISSUES FOR RIVER REGULATION: AN ILLUSTRATION FROM DIANCHI INFLOWING RIVERS IN CHINA Ke Huang, JinHua Li, ZhuJing Jin, FengLe Yang, BaoXue Zhou (School of Environmental Science and Engineering, Shanghai Jiao Tong University, No. 800 Dongchuan Rd, Shanghai, China) An effective approach for river regulation (RR) should be seen as a chance for development and improvement of social and environmental conditions in surrounding areas. However, there is currently no good way to control severe polluted rivers, especially to those in developing areas with large population and low technological level. This paper tried to provide a useful guideline for other polluted rivers regulation. In the context, three key issues for RR based on the regulation work of eutrophicated Dianchi inflowing rivers (DIRs) were illustrated. The first key issue is execution of river management, which was the most important for the area with low productivity. An effective responsibility system for the leaders in charge of the DIRs is necessary to improve inefficient execution. Furthermore, another key issue is to raise sufficient funds by strengthening market operation, thus introducing many financing channels for engineering-based treatment. As the third key issue, comprehensive engineering including ecological engineering also plays a very important role in pollution reduction and ecological remediation. After more than six years of practicing in DIRs, related regulation work gets better results. Ecology environment of DIRs has been improved obviously; the amount of pollutants from the DIRs to the DL decreased by 10%, and the comprehensive pollution index of major DIRs decreased by 56%.

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TRACE ELEMENT MOBILIZATION BY OXIDATION VIA ANTHROPOGENIC NITRATE IN SOUTHERN CALIFORNIA WATERSHED Yola Wong K and Dr. Barry Hibbs (California State University, Los Angeles, CA, USA) A comparative study of two creeks (having similar land use practices and geology) in Malibu Creek Watershed in Southern California investigated the variability of nitrate (NO3--N) and toxic trace element (selenium, Se) concentrations. The study area’s geological framework is unique, containing selenium enriched strata facilitating geochemical reactions resulting in possible selenium oxidation and mobilization in shallow groundwater that feeds into the creeks as baseflow. Previous studies demonstrated a positive correlation of nitrate to selenium in the shallow groundwater and surface water of the creeks, creating toxicity concerns to terrestrial aquatic species. One major tributary, Las Virgenes Creek, has nitrate concentrations of 2 to 8 mg/L NO3--N and 10 to 50 ug/L dissolved Se, exceeding the MCLs for freshwater species. The neighboring tributary, Medea Creek, has generally low nitrate concentrations < 1 mg/L NO3-N, and does not have high oxidizing potential for selenium, resulting in less than 5 to 10 ug/L dissolved Se in surface water and groundwater. These conditions apply during normal and dry years. Wet weather and dry weather impacts the Malibu Creek watershed water quality concentrations. In very wet years, the groundwater baseflow is so much higher that there appears to be temporarily very high selenium due to recent recharge waters having very high dissolved oxygen leading to rapid oxidation of selenium in rocks. In addition, water tables rise during extremely wet years into strata that are normally not saturated, facilitating leaching of selenium directly into groundwater. In dry weather, dissolved oxygen is consumed quickly because of the more sluggish groundwater flow regime that exists. There is limited oxidation potential, except where anthropogenic nitrate is high in particular creeks. We hypothesize that selenium is oxidized by elevated nitrate in shallow groundwater flowing through Monterey/Modelo formation adjacent to Las Virgenes Creek, the only creek in Malibu Creek Watershed that is known for relatively high nitrate. Shallow groundwater sampling of springs and seeps that flow into Medea Creek and Las Virgenes Creek feasibly confirms our hypothesis through water quality testing. Analysis of hydrogen and oxygen stable isotopes, nitrate isotopes, selenium, and other redox-sensitive species in surface water and groundwater demonstrate creek characteristics, sources of water feeding into the creeks, anthropogenic source(s) of nitrate and selenium concentrations in the watershed. Laboratory batch studies are underway to determine the efficacy of nitrate oxidizing selenium contained in Monterey/Modelo strata. These hydrogeological investigations in can assist water agencies improve water quality and the Malibu Creek Watershed habitat for aquatic species.

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SUSTAINABLE OR GREEN WATER MANAGEMENT PRACTICES BY SOUTH AFRICAN MINING COMPANIES Mbofho Stanley Liphadzi1 & Andre Vermaak2 (1. Water Research Commission, Private Bag X03, Gezina, 0031, South Africa; 2. School of Business and Leadership, University of South Africa, Midrand, Johannesburg, South Africa) Sustainable and green water management practices are aimed at facilitating environmental, social and economic performance of the company. The assumption is that there is no business or company that can attain long term growth and sustainability if it degrades the environment, violate human rights, or fails to make profit. However, green practices are mostly focused on promoting environmental sustainability as a platform for use to enhance social and economic sustainable performances. Sustainable or green water management practices adopted by the mining industry includes those prescribed by the Global Reporting Initiatives (GRI) and the International Council on Mining and Metals (ICMM) geared towards addressing Water Use (reduce use, recycle &reuse), Pollution Reduction and Prevention, Reclamation & Rehabilitation, and Planning. The objectives of the study were to investigate which sustainable or green water management practices are used by the selected mining companies; to identify factors (or main drivers) that determine the kind of water management practices that the selected mining companies use in mining operations; to determine if currently used water management practices of the mining company are sustainable / green, and to identify gaps or areas that mining companies can improve on to enhance their environmental sustainability. Mining companies with activities associated with toxic mine water production were identified and included in the study. While the study showed that a suit of sustainable water management initiatives are used by the mines, there are still more strategic action needed for the mining sector to be sustainable.

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CRUDE PALM OIL PRODUCTION: ENVIRONMENTAL IMPACTS ASSESSMENT OF FRESHWATER CONSUMPTION USING LCA APPROACH Zainura Zainon Noor, Noor Salehan M. Sabli and Che Hafizan Che Ahmad (Universiti Teknologi Malaysia, Skudai, Johor, MALAYSIA) Freshwater use and its consumption have emerged as areas of high environmental concern. The problems surrounding the management of this vital resource have stimulated public awareness, especially in the last decade. However, water use and related impacts are still widely excluded from Life Cycle Assessment (LCA) methodologies, which aim at measuring and assessing the environmentally relevant emissions and resources consumed, over the entire life cycle of a product or service: the supply chain, the product assembly, the use and disposal phase or recycling (ISO 14044). LCA is increasingly applied and required by industry, authorities and consumers to make sustainability decisions. One main reason of neglecting water has been the absence of comprehensive impact assessment methods associated with freshwater use. The Malaysian oil palm industry is a very important industry since it contributes immensely to the nation’s economy. The industry is asked again and again to prove the sustainability of their products. Sustainability is no longer an option because it will be the primary driver of economic development in the long-term. Sustainability has to be part of the oil palm industry’s business strategy. Just as how carbon footprint or GHG emissions are playing such an important role in the oil palm industry, the next thing the world is moving into is water footprint. In view of the imminent need for the oil palm industry to be accountable for its water consumption, it is very crucial to first quantify the water footprint of the industry and identify areas of high water intensity despite the fact that Malaysia is n. The next step will be to reduce the water consumption as much as possible. In this manner, the oil palm industry will remain competitive and sustainable in the global market. The main objectives of the study are to identify the areas of high water consumption and the potential environmental impacts associated with them. This study embarked on a cradle-to-gate water footprint of the production of crude palm oil (CPO). It was found that milling process consumed the highest amount of water and the production of significant amount of palm oil mill effluent (POME) from the milling process and may lead to environmental degradations. Nonetheless, certain measures can be taken up to minimize the water consumption as well as mitigate the potential environmental impacts. Even though the study for now covers up to the palm oil mill, in the near future, it will be further expanded to also cover right up till the production of palm biodiesel and other downstream products.

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THE ART IN-WELL TECHNOLOGIES, RE-ENGINEERING EXISTING REMEDIES TO REDUCE TIME, COSTS & RISKS Mohamed Odah (Accelerated Remediation Technologies, Inc Overland Park, Kansas 66212, USA) Building on the multiple remediation concepts combined within the ART Technologies, ART has engineered an alternative to traditional air sparging and soil vapor extraction (AS/SVE) remedial systems. This patent-pending alternative utilizes similar processes as traditional AS/SVE, but is applied differently. The ART AS/SVE well consists of two screens separated by a solid section. The lower screen is positioned near the bottom of contamination. The upper screen intersects the water table. An innovative, specially designed packer will be strategically positioned in the solid riser portion, between the two screen zones, to force injected air to exit the well via the lower screen. The vapors are captured through the upper screen along with additional vapors captured from the vadose zone, thus reducing or eliminating vapor intrusions issues. In addition to reduced drilling cost, savings also include reduced trenching and piping installations and maintenance activities. Traditional AS/SVE methods may cause uncontrolled air sparging into the formation that is difficult to recapture allowing possible expansion of plume boundaries and vapor intrusion into nearby structures. However, the ART AS/SVE well utilizes one below grade structure to achieve greater control of component processes as well as decreased costs due to initial construction and long term operation and maintenance. The ART AS/SVE design allows for a more controlled recapture of the sparged air as the vapor extraction component is included within the same sub-grade structure. Furthermore, the ART Innovative AS/SVE allows for the addition of amendments to the subsurface through the sparging screen if it becomes necessary.

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ENVIRONMENTAL RISK ASSESSMENT OF CAFFEINE IN PARANA’S RIVERS (BRAZIL) Maiara C. Perussolo, Pauline Lais Nasatto, Isadora Terumi Saruhashi*, Andréa Fernandes, Eliane Carvalho de Vasconcelos, Cíntia Mara Ribas de Oliveira (Universidade Positivo, Curitiba, PR, Brazil) The presence of pharmaceuticals in the environment has been intensively researched, and the risk posed by these substances has been still considered as an important issue to assess the aquatic organisms exposure. Caffeine can be found in pharmaceuticals and foods and it has been reported as a continuous pollution tracer in the aquatic environment. Environmental risk assessment of caffeine shows interesting scenarios concerning anthropogenic inputs to the aquatic environment, mainly in developing countries, in which many people have no basic sanitation. The herein study analyzed the environmental risk of caffeine in some rivers in Alto Iguaçu Basin (Paraná State – Brazil). The risk quotient (RQ) was calculated using the ratio between the measured environmental concentrations (MEC) of some stations in the basin and the aquatic organisms measured low effect concentrations (LEC). The average concentrations ranged from 6.8 ng/L to 608 µg/L. High environmental risk situations were identified for most of the stations (RQ ≥ 1). The highest quotients were found to the stations into the Barigui river, which may be related to the anthropogenic activities in the area. The presence of caffeine in Paraná’s rivers from the Alto Iguaçu Basin showed the significant impacts from irregular domestic wastewater discharges.

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PROGRESS ON THE RESEARCH OF FLOOD ROUTING UNDER THE EFFECT OF SEEPAGE IN SEASONAL STREAMS Wu Guizhi *, Li ningning and Wu Zhouhu (Qingdao Technological University ,Qingdao, Shandong Province, China) Flood is one of the major natural disasters in the world. The simulation on stream flood routing has realistic significance in order for flood control and prevention. Seasonal seepage in streams causes obvious damages in arid or semiarid areas, which affects the flood flow and process.The study on the effect of seepage on seasonal flood routing can provide scientific methods and basis for flood forecast, prevention and control, and comprehensive utilization of water resources of seasonal rivers.It describes the main results of domestic and foreign researchers about the effect of seasonal seepage on flooding routing. Moreover, it analyzes the progress of domestic studies in China and discusses the trend of development.

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MASS FLUXES OF URBAN MICROPOLLUTANTS AND INTEGRATED MODELLING OF THE RIVER – GROUNDWATER – INTERACTION IN THE CITY OF HALLE/GERMANY FRIDO REINSTORF1, Sebastian Leschik2, Andreas Musolff2, Gerhard Strauch2, Karsten Osenbrueck3 and Mario Schirmer4 1 ( University of Applied Sciences Magdeburg-Stendal, Department of Water and Waste Management, Breitscheidstrasse 2, 39114 Magdeburg, Germany; 2,3Helmholtz Centre for Environmental Research – UFZ, Permoserstrasse 15, 04318 Leipzig, Germany; 4EAWAG, Swiss Federal Institute of Aquatic Science and Technology, Department Environmental Toxicology, Ueberlandstrasse 133, 8600 Duebendorf, Switzerland) The urban aquatic environment is increasingly polluted by low concentrated but high eco-toxic compounds as pharmaceuticals, fragrances and endocrine disruptors. These so-called xenobiotics are emitted into the surface and subsurface waters by outlets of waste water treatment plants and/or by seeping processes of waste water. This contamination could have a long-time impact on the urban ecosystem and on human health. Within an interdisciplinary project on risk assessment of water pollution, we work on the identification of water and substance fluxes in urban areas. The objective is an integrated modelling tool for the description of transport of substances in the urban environment. Transport processes of interest are related to surface water, groundwater and the groundwater – surface water interaction zone. In a first attempt we used a flow model concept with in- and output and surface water transport represented by the city of Halle, Germany, and the river Saale. The river Saale acts as surface water system collecting lateral inputs along the city traverse. Using indicators for xenobiotic impacts on water resources such as Bisphenol A and t-Nonylphenol, Carbamacepine, Galaxolide and Tonalide investigations of the pathways and the behaviour of the substances in the environment have been carried out. In the city of Halle, concentrations of the indicators at a magnitude of ng/L to g/L were found in rivers and in groundwater. A balance of water and substance fluxes in the rivers was built up for the city as a whole. The calculation of the loads shows increasing values of the investigated indicators over the distance of the city passage. The understanding of the interaction between groundwater and surface water is important to quantify the exchange of substances between the two hydrological compartments. In order to investigate this, a transient hydrodynamic river reach model of the Saale River and a groundwater flow model of the area connected to the reach were built up and coupled. Using this model, the inter-compartmental transport of the indicator Carbamacepine that exfiltrated from the Saale River into the groundwater was simulated over a time period of one year.

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IMPROVING IMPLEMENTATION CAPACITIES OF CITIES BY SHARING BEST PRACTICES IN URBAN WATER CYCLE SERVICES C.J. Van Leeuwen (KWR Watercycle Research Institute, P.O. Box 1072, 3430 BB Nieuwegein, The Netherlands) The European Innovation Partnership on Water (EIP Water) is one of five European Innovation Partnerships which aim is to promote innovation that contributes to solving social challenges, enhances Europe's competitiveness and creates employment and economic growth. EIPs help to pool expertise and resources by bringing together public and private actors at EU, national and regional levels. The overall objective of the EIP Water is to support and facilitate the development and implementation of innovative solutions to deal with the many water related challenges Europe and the World are facing, as well as to promote economic growth by bringing such solutions to the market in Europe and further afield. “City Blueprints” is one of nine initial EIP Water AG’s which have been selected from a total of 64 proposals submitted in 2013 (http://www.eip-water.eu/working-groups/city-blueprints-improvingimplementation-capacities-cities-and-regions). The “City Blueprints” for Water is a baseline assessment of the sustainability of water management in a city (or other dominantly urban region). The result allows a city to quickly understand how advanced it is in sustainable management of its urban water cycle services (UWCS) and to compare its status with other leading cities. City Blueprints” is also an opportunity to take part in a new and innovative programme to improve city-level water steward-ship, in the spirit of smart and sustainable cities. The basic output is a simple radar chart. The paper highlights the assessments done in 25 cities in the world. The advantages and limitations of the approach will be discussed, as well as the next steps that are needed to solve the challenges in (1) water safety, (2) water scarcity and (3) water governance in cities around the world.

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SUSTAINABILITY OF WATER RESOURCES OF HO CHI MINH CITY, VIETNAM Minh T. Ngo, Jae M. Lee, Nam C. Woo (Yonsei University, Seoul, Korea) As a fresh-water source, groundwater is a critical element of sustainable development of coastal areas. This study identifies the causes of saline-water intrusion into the main water-supplying aquifer, the Upper Pliocene aquifer (n22), of the Ho Chi Minh City. Hydrogeochemistry, isotope signatures and water-level data indicated that saline-water intrusion be induced by groundwater over-exploitation from the aquifer to meet the increased water demand from population growth and expansion of industrial complexes. During the period of 2004–2009, the saline boundary had moved inland with the farthest distance being about 3.2 km. The ratios of Br:Cl and δ2H and δ18O values of the samples indicated that the salinization of groundwater resulted mainly from mixing with seawater over a long period. Calculation results of the groundwater sustainability indicators (GWSIs) show that groundwater resources of the study area face a significant risk for its sustainable development, and thus, management strategies for the coastal aquifer should be implemented urgently.

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ASSESSMENT OF GROUNDWATER RECHARGE USING WATER-TABLE FLUCTUATION METHOD AND WATER-BALANCE MODEL Sasmita Sahoo and Madan K. Jha (Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India) ABSTRACT: Accurate quantification of groundwater recharge is essential for sustainable management and protection of valuable groundwater resources. The main objective of this study is to determine and compare the spatial distribution of groundwater recharge using two methods: (a) water-table fluctuation (WTF) method and (b) water-balance method using Visual HELP model. In water-table fluctuation method, the site-specific recharge was computed at 13 observation wells using specific yield and water-level data. In water-balance approach, the Visual HELP model was used to estimate site-specific groundwater recharge at 8 selected sites considering soil characteristics, land cover and weather data as inputs to the model. The point estimates of recharge obtained by both the methods were then subjected to geostatistical modeling to determine the spatial distribution of groundwater recharge in the study area. Comparison of results from the above two methods indicated that the mean annual recharge for the 11-year period range from 55.1 to 348 mm/year and from 196.6 to 326.1 mm/year for WTF method and Visual HELP model, respectively. Thus, the WTF method shows a high range of spatial variability as compared to Visual HELP model. However, the most of the groundwater recharge in the study area was found to occur during the monsoon season. Based on the findings of this study, it can be inferred that comparison of multiple methods is imperative for determining the range of pragmatic recharge in a study area. Moreover, the results presented in this paper is useful for future studies of groundwater recharge and water management planning as well as construction and calibration of groundwater flow simulation models. INTRODUCTION In order to meet demand for freshwater, there has been indiscriminate exploitation of groundwater resources. If pumping exceeds the total amount of recharge, groundwater mining occurs and the aquifer becomes no longer sustainable (Sophocleous, 2005). Since recharge is a key parameter in groundwater resources, a reliable estimate of recharge is essential in order to develop a sustainable management scheme for protection of this vital resource. The key to the successful estimation of groundwater recharge lies in the utilization of a variety of independent methods. It is difficult to estimate groundwater recharge reliably by one method because of uncertainties and assumptions associated with different methods, which could eventually have detrimental impacts on resource management decisions. For this reason, it is strongly recommended that recharge should be estimated using multiple methods to increase reliability of recharge estimates (Healy and Cook, 2002; Misstear et al., 2009). They have demonstrated that recharge estimates can widely vary depending on the estimation technique employed. The different methods available for recharge estimation include lysimeters, chemical tracing, Darcian approach, water-balance method, water-table fluctuation method, numerical modeling with groundwater flow models, infiltration models, hydrograph separation method, isotopes method. The choice of methods will depend on the spatial and temporal scale of investigation, the characteristics of the aquifer, the mechanism sought for understanding, the availability of data of adequate quantity and quality, and the spatial and temporal resolution of the results (Flint et al., 2002; Heppner et al., 2007). Water- balance methods used for recharge estimation are based on the fact that water entry should be equal to the amount discharged plus or minus the variation in the volume of water that is stored. Water-balance methods have several advantages like availability of data, their straightforward implementation and relatively low cost, and their applicability to all types of recharge and aquifer media (Sophocleous, 1991; Rivard et al., 2008). On the other hand, the water-table fluctuation method (WTF) method assumes groundwater rises in 27

Environmental Science & Technology 2014 Vol. 1 an unconfined aquifer as a result of recharge reaching the groundwater level and it is one of the most widely used techniques for estimating net recharge rates (Healy and Cook, 2002). The main objectives of this paper are to present the application of two important methods, namely water-table fluctuation (WTF) method and water-balance model using Visual HELP to estimate sitespecific groundwater recharge and then to determine its spatial distribution by interpolating the point estimates of recharge using geostatistical modeling and GIS. MATERIALS AND METHODS Study Area Description. The Kushabhadra-Bhargavi Interbasin of Mahanadi delta, Odisha, India (Figure 1) was selected as a study area for quantifying groundwater recharge. It is located between 19° 49' 04'' N to 20° 18' 45'' N latitude and 85° 54' 47'' E to 86° 03' 26'' E longitude. The two major rivers, namely Kushabhadra and Bhargavi River form the eastern and western boundaries of the study area, respectively. The topography of the area is almost flat with the elevation varying from 0 to 26 m MSL and it encompasses an area of 620 km2. The climate of the area is classified as tropical monsoon climate and wet. The average annual rainfall is about 1470 mm and mostly occurs during south-west and north-east monsoon season from mid-June to end of October. The mean monthly temperature ranges from 29 to 46 °C and the mean monthly humidity varies from 41 to 86%, while the mean monthly wind speed varies from 2.6 to 26 km/h. The study area is mostly occupied by the laterite and alluvium geologic formation which contribute to the essential source of groundwater in the basin. The major aquifers present in the study area consist of fine sand, medium sand, coarse sand and coarse sand with pebbles; the medium to coarse sand being the predominant formation.

FIGURE 1. Map of the study area with location of sites selected for recharge estimation. Data Collection. The daily rainfall data of six rainfall stations in the study area were collected for 21 years (1990-2010) from the Department of Agriculture, Puri, Odisha. The groundwater-level data of 13 28

Environmental Science & Technology 2014 Vol. 1 observation wells (wells tapping uppermost unconfined aquifer) were collected for 15 years (1997-2011) from the Central Groundwater Board (CGWB) and Groundwater Survey and Investigation (GWS&I), Bhubaneswar, Odisha. The lithological data of the study area were collected from the Odisha Lift Irrigation Corporation (OLIC), Bhubaneswar, Odisha. The meteorological data such as relative humidity, wind speed, duration of sunshine hours, maximum and minimum air temperature have been collected for 2000-2010 period at Bhubaneswar and Puri stations from India Meteorological Department, Pune. Methods Investigated for Groundwater Recharge Estimation. Two methods have been selected to estimate groundwater recharge in the study area: (1) the water-table fluctuation method, and (2) waterbalance approach using Visual HELP model. These methods have been selected based on the availability of data and the hydrogeological setting of the study area. A brief description of these two methods is presented below. Water-Table Fluctuation Method. The water table fluctuation (WTF) technique is mainly applied to shallow water tables (unconfined aquifers) that display sharp water level rises and declines (Healy and Cook, 2002; Scanlon et al., 2002). It is based on the principle that rises in groundwater levels in unconfined aquifers are due to recharge water reaching at the water table. The net recharge is calculated as (Healy and Cook, 2002):

R = ∆SGW = S y

dh ∆h = Sy dt ∆t

(1)

Where, R = groundwater recharge, ∆SGW = groundwater storage variation, Sy = specific yield, h = water level and t = time. In this study, the net groundwater recharge was computed at 13 observation wells for 11 years (2000-2010) using Eqn. (1). Specific yield values obtained from pumping test data analysis were used for estimating net recharge. Visual HELP Water-Balance Model. Visual HELP was developed by the U.S. Army Waterways Experiment Station to compute the water balance of landfills (Schroeder et al., 1994). It is a “quasi-twodimen-sional” model that routes rainfall falling on the land to components of evapotranspiration, runoff, storage, and vertical infiltration (recharge) for a layered soil column (Schroeder, et al., 1994). The expression used for estimating groundwater recharge by HELP model (based on the conservation of mass principle) as follows: R = P - (ET +R +ΔS)

(2)

Where, R = recharge; P = precipitation; ET = evapotranspiration ; R = direct runoff ; and ΔS = change in storage. In this study, water-balance equation (Eqn. 2) was applied by Visual HELP model and site-specific groundwater recharge was estimated at 8 selected sites for the period 2000-2010. Mean annual groundwater recharge was calculated from rainfall under the influence of soil properties, solar radiation, air temperature, wind speed, and vegetative properties. Therefore, input data used by the model in this study were monthly precipitation, monthly temperature, average wind speed, relative humidity, solar radiations, soil properties, and land cover. The spatial distribution of land use/land cover in the study area comprises of six major land use/land cover categories namely, agricultural land, dense forest, degraded forest, wasteland, settlements, and rivers and water bodies. The depth and formation of the soil profile at each of the 8 sites were obtained from the detailed stratigraphy analysis. The soil classes found in the study area are: silty loam, clayey loam, coarse sand, very fine sand and sandy loam. The soil properties of the selected sites in the study area were obtained from Water Technology Centre for Eastern Region Bulletin (Singh et al., 2002). Moreover, the 29

Environmental Science & Technology 2014 Vol. 1 runoff calculated from the SCS curve number was used by Visual HELP model, while evapotranspiration was calculated from Penman–Monteith equation. Spatial Prediction of Groundwater Recharge. The spatio-temporal variability of the recharge is of great importance for water management applications (Scanlon et al., 2002) can successfully be obtained by combining the recharge estimation technique with the Geographic Information System (Sophocleous, 1991). In this study, the point estimates of net recharge (mean annual recharge) by both WTF technique and Visual HELP model were interpolated using geostatistical modeling and GIS in order to determine the spatial distribution of groundwater recharge over the study area. RESULTS AND DISCUSSION Results of Groundwater Recharge Estimation by WTF Method and Visual HELP Model. The annual variation of recharge estimated by WTF method at 13 observation wells for 11-year period (2000-2010) is presented in Figs. 2(a,b). It is evident from this figure that maximum amount of recharge is obtained at site O-1 for the year 2006 and 2004 [Fig. 2(a)], whereas lowest amount of recharge is obtained at Site O-20 for the year 2007 [Fig. 2(b)]. Figure 3 shows the annual variation of recharge estimated by Visual HELP model at 8 sites for 11-year period (2000-2010). Clearly, maximum amount of recharge is found at Puri Sadar in the year 2000 and 2001 due to highest rainfall in these years, while Gop-II has lowest amount of recharge in the year 2002 and 2006 due to scanty rainfall. Thus, it can be inferred that groundwater recharge responds well to the rainfall events.

FIGURE 2(a,b). Annual variation of recharge (WTF method) at 13 observation wells for 2000-2010 periods. Moreover, the mean annual recharge for the 13 observation wells as estimated by WTF method is shown in Figure 4(a) together with error bars of standard errors. It is apparent from Figure 4(a) that the maximum recharge occurs at Site O-1 during 11 years, while little groundwater recharge occurred at Site O-20. Further, the variation in recharge over 11 years is highest at Site O-1 followed by O-2, O-7 and O19, while O-8 shows smaller amount of variation in recharge over 11-year periods. On the other hand, for the Visual HELP model [Figure 4(b)], the variation in recharge is highest at Puri Sadar, followed by Satyabadi and the remaining six sites shows almost equal variation of recharge over 2000-2010 periods.

30


FIGURE 3. Annual variation of recharge (Visual HELP model) at 8 sites for 2000-2010 periods.

FIGURE 4. Variation of Mean Annual Recharge estimated by (a) WTF method (b) Visual HELP model.

31


.

FIGURE 5. Spatial distribution of mean annual recharge by: (a) WTF method and (b) Visual HELP model. 32

Environmental Science & Technology 2014 Vol. 1 Spatial Distribution of Groundwater Recharge. The mean annual groundwater recharge in the study area estimated by WTF method varies from 55.1 to 348 mm/yr as observed from Figure 5(a). It is apparent from this figure that a net recharge rate of 87.7-120.2 mm/yr is predominant in the study area, followed by 282.9348 mm/yr found in the northern portion of the study area. Moreover, the recharge estimates from WTF shows a wide range of variability of recharge over the study area. However, recharge estimates from Visual HELP model indicates less variability in recharge distribution (196.6-326.1 mm/yr) over the study area as compared to WTF method, as shown in Figure 5(b). Further, the majority of the north-west portion and some parts of the central portion have the highest estimate of groundwater recharge from the water-balance model, i.e., 297.4-326.1 mm/yr CONCLUSIONS In this study, groundwater recharge has been estimated by using two methods, viz., water-table fluctuation (WTF) method and Visual HELP water-balance model considering both site-specific and spatially distributed groundwater recharge. In WTF method, the site-specific recharge was computed at 13 observation wells for 11 years (2000-2010), whereas in water-balance approach, the Visual HELP model was used to estimate the point estimate of groundwater recharge at 8 selected sites for 11 years (2000-2010). Then, spatial distributions of groundwater recharge are determined by interpolating the point estimates of recharge in GIS environment. Comparison of results from the above two methods indicated that the estimates of mean annual recharge for the 11-year period range from 55.1 to 348 mm/year and from 196.6 to 326.1 mm/year for WTF method and Visual HELP model, respectively. Thus, the WTF method shows a high range of spatial variability as compared to Visual HELP model. However, the most of the groundwater recharge in the study area was found to occur during the monsoon season. The techniques used in this study are easy to implement, widely available and do not require complex hydrogeologic modeling. Moreover, the results presented in this paper, can also provide input to the construction and calibration of groundwater flow simulation models, which is essential for sustainable management of groundwater resources. ACKNOWLEDGEMENTS The authors are very grateful to the Department of Agriculture, Puri, Odisha, Central Groundwater Board (CGWB), Groundwater Survey and Investigation (GWS&I), Bhubaneswar, Odisha, and India Meteorological Department, Pune for providing necessary data for the present study. REFERENCES Flint, A. L., L. E. Flint, and E. M. Kwicklis. 2002. “Estimating recharge at Yucca Mountain, Nevada, USA: comparison of methods.” Hydrogeology Journal. 10(1): 180-204. Healy, R. W., and P. G. Cook. 2002. “Using groundwater levels to estimate recharge.” Hydrogeology Journal. 10: 91-109. Heppner, C. S., J. R. Nimmo, G. J. Folmar, W. J. Gburek, and D. W. Risser. 2007. “Multiple-methods investigation of recharge at a humid region fractured rock site, Pennsylvania, USA.” Hydrogeology Journal. 15: 915-927. Misstear, B. D. R., L. Brown, and P. M. Johnston. 2009. “Estimation of groundwater recharge in a major sand and gravel aquifer in Ireland using multiple approaches.” Hydrogeology Journal. 17: 693-706. Rivard, C., Y. Michaud, R. Lefebvre, C. Deblonde, and A. Rivera. 2008. “Characterization of a regional aquifer system in the Maritimes Basin, eastern Canada.” Water Resources Management. 22: 1649-1675. Scanlon, B. R., R. W. Healy, and P. G. Cook. 2002. “Choosing appropriate techniques for quantifying groundwater recharge.” Hydrogeology Journal. 10(1): 18-39 Schroeder, P. R., C. M. Lloyd, and P. A. Zappi. 1994. The Hydrologic Evaluation of Landfill Performance (HELP) Model. User’s guide for version 3. Interagency Agreement No. DW21931425.

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Environmental Science & Technology 2014 Vol. 1 Singh, R., D. K. Kundu, and H. N. Verma. 2002. Hydro-physical Characteristics of Orissa Soils and their Water Management Implications. Research Bulletin No. 12, Water Technology Centre for Eastern Region, (Indian Council of Agricultural Research), Bhubaneswar, Orissa, 751023, India. Sophocleous, M.A. 1991. “Combination the soil water balance and water-level fluctuation methods to estimate natural groundwater recharge: Practical aspects.” Journal of Hydrology. 124: 229-241. Sophocleous, M.A. 2005. “Groundwater recharge and sustainability in the High Plains aquifer in Kansas, USA.” Hydrogeology Journal. 13(2): 351-365.

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EVAPORATION REDUCTION BASED DESIGN OF WATER PONDS SURFACE 1072 AREAS USING PALM FRONDS Ibrahim H. Elsebaie (Civil Engineering Department, College of Engineering, King Saud University, Saudi Arabia; [email protected].) ABSTRACT: The limited water supply and the increased future demand necessitate the importance of optimum use of water resources which might be obtained through reduction of water losses. The reduction of evaporation losses has recently received increasing attention because of the increase in water demand and the decrease in water availability. Therefore, the aim of this research is to use a new technique that can save evaporation water losses as a non-conventional water resource. To know the efficiency of this technique (Palm Fronds cover) in our arid zones, an experimental setup consisted of four pans with two different cross sections (rectangular and square). The setup included also study the effect of the shape and the cover pattern on the rate of the evaporation losses. The daily observations during 41 days reduced the losses by evaporation and the rates of reduction of the evaporation are remarkable and are more than 45 % for the half covered compared to the open pan. And the strips covered reduce the evaporation compared to the open pan by more than 60%. It could be concluded from the research that water evaporation can be reduced and controlled using environmentally safe techniques. Keywords: Evaporation, Palm Fronds, arid zones, water resources.

INTRODUCTION Water is the most precious natural resource in the world, especially in Saudi Arabia with arid climate and limited resources of surface water. Management of water by reducing the evaporation rates will optimize the amount of water that may perhaps support the ever-growing domestic, agricultural, and industrial demands. Evaporation losses from small reservoirs affect their water storage efficiency. Evaporation from open water bodies such as wetlands, reservoirs and lakes often represents the largest loss in their local hydrological budget, yet its quantification still continues to be a theoretical and practical challenge in surface hydrology. Limited renewable water resources characterize the Kingdom of Saudi Arabia, due to its geographical location and climatic conditions. In fact, renewable water resources of the kingdom are significantly less as compared to non–renewable water resources due to low annual precipitation and therefore, require greater attention for development and management for long-term utilization. Considering the importance of optimal utilization of renewable water resources, therefore, the government was constructing dams on some of the valleys in order to benefit from the establishment of such dams. But one of the challenges of water management in arid regions is to reduce the huge amount of water loss through evaporation from water surfaces of dam reservoirs and lakes due to extremely high evaporation rates. Saudi Arabia Experiences high evaporation rate with an annual rate ranges between 2500 to 3000 mm. on the other hand, rainfall annual rate ranges from 100 to 150 mm, which shows the need for water conservation though evaporation reduction techniques. One way of evaporation rate reduction might be activated by designing ponds surface areas which give the minimum evaporation . 35

Environmental Science & Technology 2014 Vol. 1 Many materials, either chemicals or physical covers, were developed to reduce evaporation from open water surfaces. Those materials are designed to suit certain climatic conditions. some are economically feasible but may have negative environmental impacts. There has been an increased focus on evaporation control techniques which can be applied to water storage due to severe drought conditions in many parts of the world (Anonymous, 2003). In a similar study Barnes (1993) found that monolayer is potentially most effective in conditions where the rate of evaporation is high. Cooley (1983) carried out a study to determine the effect of long-term exposure on the evaporation reduction efficiency of five floating cover materials. He has shown that evaporation reduction efficiencies ranged from 36% to about 84% depending on cover type. Palm tree is considered to be one of the most important commercial crops widely distributed across the Saudi Arabia capable of withstanding extremely hot weather conditions of the arid region (Al-Juruf et al., 1988). The number of trees in the Kingdom is estimated to be over 21 million. These trees are estimated to yield about 210,000 tons of fronds (Al Gassim Dates Factory, 2011). The study by Alvarez et al. (2006) on different types of shading meshes reveals that the shading of pan induced a significant decrease of the daily evaporation rate, ranging from 50% for the aluminized screen to near 80% for the coloured-polyethylene meshes. Craig et al. (2007) observed that the use of physical cover was able to reduce evaporation substantially, they suggested that these types of covers would be more effective with small reservoirs (less than 10 ha in size). However the physical covers can also be used for large reservoirs but it could be uneconomical. The study by Ikweiri et al. (2008) conducted study beside the Omar Muktar reservoir to test the effect of the monolayer technique to reduce the evaporation in comparison to the cost of the local water that are lost by evaporation. Recent study done by Al-Hassoun et al. (2009) on impounding reservoirs found that the average reduction in evaporation using the floating cover made up of palm leaves was 63% for the fully covered pool while for the half covered pool it was 26% only. Another study by Al-Hassoun et al. (2011) on effectiveness of using palm fronds in reducing water evaporation showed that evaporation reduction from the fully covered pool was about 55%, while that from the half covered pool was about 26%. Also in their study, water quality analysis showed that fronds have no serious effect on water quality. Shamshad and AlShaikh (2013) conducted study on the Use of palm fronds as shaded cover for evaporation reduction to improve water storage efficiency. They observed that the average reduction in evaporation in the covered pan (with single layer of cover) was about 47% as compared to the evaporation from the open pan. However, the average reduction in evaporation in the covered pan (with double layer of cover) was about 58% as compared to the evaporation from the open pan. Present study proposes the use of Palm fronds as strips covered and half covered for the reduction of evaporation from the open water surface. MATERIALS AND METHODS Experimental Setup. The study deals with the effect of surface area, shape and the cover pattern on evaporation reduction. For this purpose, two different surface areas (rectangular and square) are tested. Two different configuration pattern for the cover were used, one of them half covered by palm fronds and the other configuration use strips. These configurations were made for the four tanks. Details of these tanks are given in Table (1). The material used for cover was locally available palm fronds which are a massive agriculture waste and environmental friendly by-product in Saudi Arabia, one of the strip is shown in Fig. (1). Shaded cover reduces the energy available for evaporation; reduces wind action over the water surface and traps humid air under the cover, all factors that contribute to evaporation.

36

Environmental Science & Technology 2014 Vol. 1 Data Collection. A large amount of data were collected during the study period (42 days), but only the most important data and results have been presented herein. These data include measurement of water levels in tanks, evaporation depths and some meteorological data (i.e temperature, Humidity and wind speed), as well as some other data were recorded (i.e water conductivity, Dissolved oxygen (DO)). One example of the recorded data for the square tank with strips cover were summarized and presented in Table (2) Table (1). Tested surface area Tank shape Area (m2)

Tank No 1 2 3 4

Rectangle (strips covered) Rectangle (Half covered) Square (strips covered) Square (Half covered)

Dimensions (L x W x D)

1

0.67x1.5x0.5

1

0.67x1.5x0.5

0.5

0.707x0.707x0.5

0.5

0.707x0.707x0.5

Strip sample Figure 1: One of the strip used for square tank Evaporation was measured by measuring changes in water level in the tank. This was done manually with point gauge. The data were recorded at 9:30 am and 2:00 pm every other day. The amount of evaporation is a function of temperature, humidity, wind and other ambient conditions. In order to relate evaporation to wind current or expected conditions, data of continuous ambient temperature as well as the amount of water passed with evaporation were recorded with the help of a nearby weather station. Water was added into the tanks to substitute the evaporation when water level in the tank was dropped to 20 cm. RESULTS AND DISCUSSION

37

Environmental Science & Technology 2014 Vol. 1 The experimental observations revealed that the evaporation rate was directly affected by the ambient temperature as the rate of evaporation was higher during the day time (when ambient temperature was higher) while it was less or minimum in the evening and night. Figs. (2 and 3) represent the overall percentage reduction in evaporation using strips layer of palm fronds as cover compared to the one without cover for the rectangular ad square tanks. It was observed that the average reduction in evaporation in the covered rectangular tank (with strip layer of cover) were about 60% and 66% for rectangular and square respectively when compared to the evaporation from the open tanks (same dimensions). Table (2). Recorded data for square tank with strips cover Time (days)

Evaporation depth (CM)

after rain

DO (MG\L)

water Conductivity (ms\cm)

temperature

air temperature ( max )

air temperature ( min )

air temperature ( Avg )

Humidity(max)

Humidity(Min)

Humidity (Avg)

Wind Speed (km\h)

0

0

7.53

1072

26.9

31

16

23.5

42

19

29

4

2

0.9

7.22

1068

25.7

30

16

23

59

14

37

11

5

1.7

7.08

1060

25

30

14

22

51

12

31

6

6.77

1073

21.7

30

15

22.5

48

12

30

7

3.76

1094

17.3

22

14

18

94

59

80

13

6

3

11

1.5

after rain

13

2

4.22

1062

18.2

23

18

20.5

94

64

84

6

17

0.4

6.55

1055

19

23

9

16

88

11

54

3

18

1

6.83

1065

20.4

26

9

17.5

87

10

50

1

20

1.9

7.02

1099

22.6

29

11

20

82

7

40

5

4

6.92

1164

14.8

25

10

17.5

88

18

58

8

27

4.8

6.88

1189

19.9

29

10

19.5

76

5

38

4

31

6.6

7.19

1260

20.6

27

13

20

94

20

62

5

32

6.8

7.04

1275

20.4

28

13

20.5

94

8

52

5

34

8

7.16

1332

14.7

17

8

12.5

59

29

44

12

39

9.8

7.21

1428

8.8

12

4

8

65

16

43

15

40

9.5

7.51

1411

10.5

16

7

11.5

76

17

45

7

41

10.3

7.64

1465

11.7

17

6

11.5

57

12

31

6


25

after rain after rain

50 45 40 35 30 25 20 15 10 5 0 1

11

21

31

41

51

time (days) In the period from 7 Nov to 18 Dec Rectangle with strips coverd Rectangle without cover

Figure 2: Comparison between rectangle tank with strips cover and without cover

.

Figs. (4 and 5) show Comparison of evaporation depth for the different patterns for the four the two tanks. The results showed that in case of rectangular shape, the strips covered reduced the evaporation by 38

Environmental Science & Technology 2014 Vol. 1 23 % more compared to the half covered. But in case of square shape, the strips covered reduced the evaporation by 19 % more compared to the half covered In comparison with recent study done by Shamshad and AlShaikh (2013), where the evaporation daily avg. = 9.5±0.11 mm (open pan) on same month (March). The half covered rectangle reduce the evaporation compared to the open pan by 50%, and the strips covered rectangle reduce the evaporation compared to the open pan by 61%. The half covered square reduce the evaporation compared to the open pan by 60%, and the strips covered square reduce the evaporation compared to the open pan by 67%. In comparison with recent study done by Shamshad and AlShaikh (2013), where the evaporation daily avg. = 7±0.17 mm (open pan) on same month (November). The strips covered rectangle reduce the evaporation compared to the open pan by 57%. The strips covered square tank reduce the evaporation compared to the open pan by 64%. 50


45

Square with strips coverd

40 35 30 25 20 15 10 5 0 1

11

21

31

41

51

time (days) In the period from 7 Nov to 18 Dec

Evaporation depth (cm)

Figure 3: Comparison between square tank with strips cover and without cover 12 10 8 6 4 2 0 0

48

96

144

192

240

288

336

384

432

480

528

Time (hours) rectangle half covered

rectangle strips covered

Figure 4: Comparison of evaporation depth for the rectangle tank

39

576

evaporation depth (cm)

Environmental Science & Technology 2014 Vol. 1 9 8 7 6 5 4 3 2 1 0 0

48

96

144

192

240

288

336

384

432

480

528

576

Time (hours) square half covered

square strips covered

Figure 5: Comparison of evaporation depth for the square tank

CONCLUSIONS The daily observations during 41 days reduced the losses by evaporation and the rates of reduction of the evaporation are remarkable and are more than 45 % for the half covered compared to the open pan. It was observed that the average reduction in evaporation in the covered rectangular tank (with strip layer of cover) were about 60% and 66% for rectangular and square respectively when compared to the evaporation from the open tanks (same dimensions). This is approximately 15% higher as compared to percentage evaporation reduction by use of half layer cover. Significant results obtained in comparison the results of this study to the study done by Shamshad and AlShaikh (2013) in two months. The strips covered reduce the evaporation by about 57% and 64% for rectangular and square tanks respectively when compared to the open pan. Palm tree is considered to be one of the most important commercial crops and is widely distributed across the country. Palm fronds and leaves are considered as disposed waste after pruning. Therefore, it is recommended to use palm fronds as cover for open water surfaces to reduce evaporation as it is a good use of disposed waste, is environmental friendly and is capable of withstanding extremely hot weather conditions of the arid region. ACKNOWLEDGEMENT The research was carried out at the Department of Civil Engineering, College of Engineering, King Saud University, Riyadh, KSA. REFERENCES Al Gassim Dates Factory . Al-Hassoun, S.A., Mohammed, T.A., Nurdin, J., 2009. Evaporation reduction from impounding reservoirs in arid areas using palm leaves. J. Eng. Appl. Sci. 4, 247–250. Al-Hassoun, S.A., AlShaikh, A.A., Al Rehaili, A.M., Misbahuddin, M., 2011. Effectiveness of using palm fronds in reducing water evaporation. Can. J. Civil Eng. 38 (10), 1170–1174, 10.1139/l11-071. 40

Environmental Science & Technology 2014 Vol. 1 Al-Juruf, R.S., Ahmed, F.A., Alam, I.A., 1988. Development of heat insulating material using date palm leaves. J. Therm. Insulation 11, 158–159. Alvarez, M.V., Baille, A., Molina-Martinez, J.M., Gonzalez-Real, M.M., 2006. Efficiency of shading materials in reducing evaporation from free water surfaces. J. Agric. Water Manag. 84, 229–239. Anonymous, 2003. Department of Natural Resources and Mines. Methods for Reducing Evaporation from Storages Used for Urban Water Supplies, Final Report, 41/12219/67346. Barnes, G.T., 1993. Optimum conditions for evaporation control by monolayers. J. Hydrol. 145, 165–173. Cooley, K.R., 1983. Evaporation reduction: summary of long-term tank studies. J. Irrig. Drainage Div. ASCE 109, 89–98. Craig, I., Aravinthan, V., Joseph, P., Baili, C., Beswick, A., 2007. Evaporation, seepage and water quality management in storage dams: a review of research methods. J. Environ. Health 7, 84–97. Ikweiri, F.S., Gabril, H., Jahawi, M., Almatrdi, Y., 2008. Evaluating the evaporation water loss from the Omar Muktar open water reservoir. In: Twelfth International Water Technology Conference, IWTC, Alexandria, Egypt, pp. 893–899. Shamshad Alam and Abdulmohsen A. AlShaikh, 2013. Use of palm fronds as shaded cover for evaporation reduction to improve water storage efficiency. Journal of King Saud University – Engineering Sciences, 25, 55–58.

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HYDRAULIC FRACTURING: A LOOK AT EFFICIENCY AND THE ENVIRONMENTAL EFFECTS OF FRACKING Emily C. Jackson and David E. Dismukes (Louisiana State University, Baton Rouge) ABSTRACT: The use of hydraulic fracturing techniques in unconventional oil and gas development has resulted in an energy revolution that is dramatically changing the outlook for U.S. energy supplies and prices. Yet, with these new developments come a number of concerns regarding the environmental and human health effects that can be a negative consequence of these new hydrocarbon extraction techniques. The three most cited concerns are those associated with air emissions from onsite combustion, large levels of water use, and the possible intrusion of fluids and chemicals into surface and groundwater from hydraulic fracturing activities. This research provides well-specific estimates of major air emissions, water use, and the chemical composition and usage levels for the Haynesville shale utilizing operator-specific data reported to the Louisiana Department of Natural Resources as well as voluntary reports on water use included in the industry-supported Frac Focus on-line database. This research provides a three-component inventory of major air pollutants, water use and chemical use over the rapid Haynesville shale development period from 2007-2013. The annual inventory is then compared to other statewide and local air emissions, water use and chemical discharges and finds that while Haynesville-related uses and discharges are generally small relative to statewide data, local impacts can differ and warrant closer monitoring. This research also shows some positive environmental “learning-by-doing” effects: that is, operators are becoming more efficient at their water use, air emissions, and chemical uses as they drill more wells and garner more experience in the emerging play. Those operators with greater levels of experience (i.e., those that drill more wells) are relatively more efficient at reducing some, but not all, of the environmental impact of their activities than those operators drilling fewer wells. INTRODUCTION Hydrocarbons are typically located in geologic formations that are commonly classified as being “conventional” or “unconventional” in nature. Conventional hydrocarbons are those typically extracted from soft, relatively porous and permeable rock formations from vertically-drilled wells of varying depths. Unconventional hydrocarbons, however, come from a variety of differing geologic formations that includes various types of sands and shales. Unconventional hydrocarbon development from shale plays also tend to utilize a form of high pressure, artificial stimulation, known as “hydraulic fracturing” that utilizes water, chemicals, and various propants (typically silica) to extract natural gas from shale formations found thousands of feet below earth’s surface (Comen, 2012). This additional form of stimulation is necessary since these unconventional resources are typically located in formations where the porosity is smaller, and/or tighter, than those found in conventional reservoirs. As of 2009, 50 percent of all U.S. natural gas production originated from unconventional reservoirs and is expected to increase to 60 percent by 2035 (EPA, 2004). This energy revolution is now starting to migrate into areas known to hold a form of “shale crude oil” that is also prolific in nature, and leading to a possible scenario where the U.S. could be energy independent by the end of the decade (Smith, 2013). An unconventional well goes through a number of development phases. First, an appropriate site must be selected. Site preparation represents the second phase of the development process where roads to a drilling site are installed, pads are constructed, supporting equipment and buildings are moved on-site, and prepared for the next critical phase: drilling. The drilling component of a typical unconventional shale well has both a vertical and horizontal phase. The vertical phase is comprised with drilling a well that looks similar to “conventional” wells to a depth at which the thick layer of shale has been identified through geological surveys and analyses. This vertical segment usually ranges at depths of between 8,000 to 16,000 feet. The well then transitions to a horizontal segment that can span a distance of between 4,000 to 6,000 feet. The horizontal well segment runs parallel with the formation adding additional well exposure in order 42

Environmental Science & Technology 2014 Vol. 1 to recover a greater amount of hydrocarbons. The well (vertical and horizontal segments) is completed by inserting and cementing various protective casings that help to secure the well, maintain its integrity, and to prevent fluids/gas leaching into the surrounding sub-surface. Hydraulic fracturing begins after the well is drilled and cased and utilizes millions of gallons of usually fresh water, often pumped from a nearby source, and stored on site for future use over a fracturing process that usually spans a few weeks (EPA, 2004). Several chemicals, often referred to as “fracturing fluids,” are added to the water. The chemical composition of the fluids vary by region but can often include hydrochloric acid, ethylene glycol, ammonium persulfate, citric acid, and even diesel, benzene, and arsenic (Coman, 2012) and are used for a variety of reasons that range from reducing pipe corrosion and fouling, to assisting in the fracturing process (Loris, 2012). A “proping” agent, usually coated silica (sand), is added to the fracturing fluid solution and used primarily to help keep the fractures made in the shale formation open. The fracturing fluid solution is mixed at a 90:9:1 ratio of water: sand: chemicals, respectively (Coman, 2012). This solution is then injected down into the well at extremely high pressures that forces the shale formation to crack, allowing the sand to maneuver into the cracks and keep them open, releasing the natural gas back to the surface. The length of the fracturing process is a function of the number of “cycles” that are actual fractured, where each cycle is a function of the horizontal length of the well: the longer the horizontal portion of the well, the greater the number of cycles that can be fractured. While the number of cycles will vary depending upon the geologic formation and the operator, a typical horizontal well will utilize about 12 cycles, requiring a fracturing process that runs from between 2 to 30 days. The process of fracturing uses drills, chemicals, heavy equipment, water, and many other things that do not naturally belong in the area raising considerably environmental concerns, the most important of which are typically associated with water use and the potential for chemical/fluid migration into ground water aquifers. Air pollution is also an important environmental concern given the wide range of combustion and compression activities that occur at a typical unconventional drilling and production site. Other environmental factors such as quality of life around fracking sites, seismic activity, and health of the workers are important but not at the forefront of fracturing issues. DATA AND METHODS The Haynesville shale region is the study area for this research. The Haynesville share is comprised of about 9,000 square miles in Louisiana and Texas and is considered a major natural gas producing shale play in the United States (Mauck 2013). The play was formed from deposits dating back to about 150 million years ago during the Upper Jurassic age when water covering the region receded and sediments were deposited ultimately leading to the development of the formation (Environ, 2013). The Haynesville Shale, has an average thickness of between 200 to 300 feet, is located about two miles below the Earth’s surface, and is estimated to have technically recoverable resources of 251 trillion cubic feet (TCF) of natural gas (Geology.com, 2013). Unconventional well-specific data for the Haynesville shale was collected from multiple sources for the time period of its most recent active development (2007-2013). The Louisiana Department of Natural Resources (LDNR) supports an online database (called “SONRIS”) that includes information such as: true vertical depth (TVD); measured depth (MD); lateral length; well status (active, inactive, etc.); as well as spud and completion dates (LDNR, 2013). Fracturing stages were not reported directly by LDNR but were estimated assuming one stage for every 328 feet of lateral section (Roy, et al., 2013). Thus, an estimated lateral length (TVD less MD) divided by 328 provides an estimated number of fracturing stages per well. Water and chemical use data was obtained from the online chemical disclosure registry, Frac Focus, for each year in which such information was available (FracFocus.com, 2013). Since information for all wells was not available, Monte Carlo-based simulation methods were used to estimate water and chemical use where such information was missing. Total water use per well was estimated using a two-step process where (1) well-specific water use statistics were matched to wells in the SONRIS data set for 819 reported wells and (2) water use for the remaining 1,487 active wells, with no water use reported, was estimated using the known range from the reported water use statistics. Chemical use data was similarly generated, first by matching the known chemical use statistics to those in the SONRIS data set, then the proportion of

43

Environmental Science & Technology 2014 Vol. 1 wells that used the chemical was found and extrapolated to all Haynesville wells and finally, using the known concentration reported, estimates were simulated for the 707 wells with no report. Air emission estimations were developed using similar equations such as those presented by Roy et al. (2013) and Environ (2013). These equations were developed for two specific activities: one for drilling activities and the second for fracturing activities. In addition, two other sets of equations were developed to estimate air emissions from heavy duty truck traffic and completion venting. The primary air pollutants associated with drilling and fracturing activities are NOX, CO, VOC, PM, SOX, CO2, and CH4. ESTIMATED RESULTS AND DISCUSSION Water Use Results The summary results in Table 1 show that estimated water use per well increases throughout the period of investigation until about 2012 when drilling activity decreased in reaction to the dramatic reduction in natural gas prices. Table 1: Haynesville Shale Water Use per Well Water use increases prior to 2012 are a Standard function of both increased drilling activity and Year Average Minimum Maximum Deviation longer lateral lengths used in the wells that --------------------------- Gallons --------------------------were drilled during this period. For instance, 2007 3,691,802 2,231,004 5,019,403 1,145,206 drilling activity increased by 1,883 percent 2008 3,460,253 625,464 5,592,848 1,207,282 between 2007 to 2011 (the peak drilling year). 2009 3,564,946 1,517,919 6,590,304 1,174,089 Lateral lengths increased by 73 percent over 2010 4,054,394 478,513 11,868,486 1,509,802 the same time period. 2011 5,463,441 367,290 34,258,678 2,383,943 The drop in per-well water use from 2012 4,976,308 510,384 14,365,376 2,648,553 2011 indicates the possibility of operator learning-by-doing effects. Reduced per-well water use could indicate that operators are becoming more efficient at using water in drilling related activities as the scope of their basin-specific experience expands. Although all companies were found to increase their water usage throughout the years on a per well basis, the bigger companies increased their use at a much slower rate than smaller companies. Figure 1 shows local water use for hydraulic fracturing activities compared to other water uses within the local parishes in which Haynesville activity has been concentrated. Estimates provided here show that three parishes (each of which are relatively small) have estimated hydro-fracturing-related water uses that far exceed local municipal or industrial use. 6 Total Water Use

Billion Gallons

5

Fracturing

4 3 2 1 0

Figure 1: Local Parish Hydro-fracturing Water Use Relative to Other Local Uses (million gallons). On a total state-wide basis, water use for fracturing was relatively low ranking about 8th among all major Louisiana industries. Fracturing-related water uses were 0.05 percent of power-generation related water uses (for cooling purposes). However, there is a big difference between the water use for power generation purposes and fracturing: fossil fueled power generation-related water use is returned to the system, whereas water used for fracturing is permanently disposed and not re-injected into the system.

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Environmental Science & Technology 2014 Vol. 1 Chemical Use Results. Estimated chemical uses focused on three relative potent chemicals that can be included in fracturing fluids and include hydrochloric acid (HCl), phenol, and quaternary ammonium salts (quats). Table 2 provides the descriptive statistics for each chemical type as well as its usage frequency (in probability terms). For instance, 34.4 percent of the wells in the Haynesville shale either reported, or were estimated to have used HCl in their drilling fluids over the 2007-2013 time period. These concentrations can also be transformed into gallons used for each fracturing job. This research estimated that, on average, a well using HCl used 12,489 gallons of the chemical, a well using phenol used 5,219 gallons, and a well using quats used 1,220 gallons. While it is true that these chemicals can become highly diluted in a fracturing application given their mixture with about 5.6 million gallons of water, their toxicity and ability to degrade the Table 2: Chemical Concentrations (Gallons) and Usage Probability environment is still relatively high. Standard Chemical Average Minimum Maximum Probability Phenol and quats are labeled in EPA’s Deviation toxicity category 1 and 3, respectively, -------------------------- Gallons ------------------------making them a potential threat to HCL 0.206 0.001 0.417 0.119 34.400 human health and becoming highly Phenol 0.086 0.003 0.181 0.049 8.000 toxic in the aquatic environment. Quats

0.020

0.000

0.040

0.012

7.500

Table 3: Estimated Drilling-Related Air Emissions (Tons per Well) Drilling 2007 2008 2009 2010 2011 2012 2013

NOX 11.50 10.58 9.73 9.95 10.03 9.77 9.89

CO 6.23 5.73 5.27 5.39 5.43 5.29 5.35

VOC 0.72 0.66 0.61 0.62 0.63 0.61 0.62

PM 0.359 0.331 0.304 0.311 0.313 0.305 0.309

SO X

CO2

CH4

0.019 0.018 0.016 0.017 0.017 0.016 0.017

2.78 2.56 2.35 2.40 2.42 2.36 2.39

0.0017 0.0016 0.0014 0.0015 0.0015 0.0014 0.0015

Air Emission Results. Air emissions were calculated for all wells drilled and completed in the Haynesville Shale from 2007 to October 2013. Well specific, or shale specific, data was used when available, otherwise simulation results were entered and emission estimations were developed.

Table 3 shows estimated drilling emissions on a tons per well basis. The emissions show a slight drop from 2007/2008 to 2009/2010 and then rise again in 2011, followed by a drop in the next two years. Table 4 shows that 2011 is Table 4: Estimated Hydro-Fracturing-Related Air Emissions (Ton per Well) also the same year in which perFracturing NOX CO VOC PM CH4 well emission rates are their 2007 0.0620 0.0388 0.0101 0.0042 0.0038 highest during the 2007-2013. The 2008 0.0574 0.0359 0.0093 0.0039 0.0035 per-well emissions peak in this 2009 0.0600 0.0375 0.0097 0.0040 0.0037 2010 0.0616 0.0385 0.0100 0.0042 0.0038 year is attributable to the fact that 2011 0.0632 0.0395 0.0103 0.0043 0.0039 (1) drilling was at its highest level 2012 0.0646 0.0404 0.0105 0.0044 0.0039 in terms of both the number of 2013 0.0654 0.0409 0.0106 0.0044 0.0040 wells drilled in that year, but also (2) there were a large number of both small and large companies drilling wells in that peak year (2011). The implications this has for measuring the efficiency of air emissions will be discussed in the later section of this paper. Table 5 Table 5: Comparative Emissions, Drilling v. Fracturing (Per Well Basis) summarizes the per well Activity NOx CO VOC PM SOx CO2 CH4 air emission rates per Drilling 10.03 5.432 0.63 0.313 0.017 2.42 0.001 pollutant type indicating drilling related Fracturing 0.085 0.053 0.014 0.006 NA NA 0.005 the activities clearly drive overall air emissions relative to hydraulic fracturing. Thus, from air emissions perspective, there is not a considerable amount of difference between the air emissions associated with conventional activities and unconventional activities, holding total drilling depth constant. Air emissions were compared to other major industries in the State. The pollutant of major concern in these comparisons would be that for NOx where unconventional drilling activities, given their scale and scope, were found to rival those of chemical and allied product manufacturing in Louisiana. Some air 45

Environmental Science & Technology 2014 Vol. 1 emission efficiencies, or “learning by doing” impacts, are indicated in the results. Those companies drilling a larger number of unconventional wells appear to emit fewer pollutants (on a per well basis) during the fracturing stage of well development. Only the fracturing stage was looked at because that was the only stage where per well, and thus per company, data was available. CONCLUSIONS This research is unique since it uses a more accurate range or well-specific parameters for the environmental impacts of unconventional oil and gas activities. This is also the first attempt at estimating a broader range of environmental impacts that include air emissions, water use, and adverse chemical uses. The empirical results indicate that the Haynesville Shale is a major emitter of air pollutants but at levels considerably lower than other major industries in Louisiana. While unconventional hydro-fracturing activities use a considerable amount of water, this use is moderate at the state-wide level. However, for three of the smaller parishes investigated in this research, this increased water use has been considerable and warrants continued observation. The chemicals used in fracturing should be handled with care because of the amount used and the relative toxicity to the environment and humans of each chemical. It is shown that the Haynesville Shale has become more efficient in unconventional drilling activities by decreasing drilling time, increasing lateral lengths and stages to recover more resources. Though still of concern, environmental effects have lessened from big companies because they have decreased their air emissions and slowed their water use per well over time. ACKNOWLEDGEMENTS The authors wish to acknowledge and thank the LSU Center for Energy Studies at LSU for the financial support for this research. The authors also thank Siddhartha Narra for his technical assistance in several parts of this project. REFERENCES Coman, Hannah. "Balancing the Need For Energy And Clean Water: The Case For Applying Strict Liability In Hydraulic Fracturing Suits." Boston College Environmental Affairs Law Review 39.1 (2012): 131160. Academic Search Complete. Web. 26 Nov. 2012. Environ. “Emissions from Natural Gas Exploration and Production Activity in the Haynesville Shale.” Environ. January 2013. Geology.com. “Haynesville Shale: News, Map, Video, Lease and Royalty Information.” Geology.com. Web. 2 Oct. 2013. . Loris, Nicolas. “Hydraulic Fracturing: Critical for Energy Production, Jobs, and Economic Growth.” 28 Aug. 2012. The Heritage Foundation. Web. 12 Feb. 2013. . Mauck, Keith. “What is the Haynesville Shale?” GoHaynesvilleShale.com. Web. 2 Oct. 2013. . Roy, Anirban A. Adams, Peter J. & Robinson, Allen L. “Air Pollution Emissions from the Development, Production, and Processing of Marcellus Shale Natural Gas.” Journal of the Air & Waste Management Association, 2013, Vol 64(1), 19-37, DOI: 10.1080/10962247.2013.826 151. Smith, Grant. “U.S. to Be Top Oil Producer by 2015 on Shale, IEA Says.” Bloomberg, 12 Nov. 2013. Web. 7 April 7, 2014. < http://www.bloomberg.com/news>. U.S. Environmental Protection Agency. “EPA Hydraulic Fracturing of Coalbed Methane Reservoirs Study.” 2004. Web. 26 Oct. 2012. . U.S. Department Of Energy. “Shale Gas Glossary.” United States Department of Energy. Web. 2 Oct. 2013. http://energy.gov/sites/prod/files/2013/04/f0/shale_gas_glossary.pdf.

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CORRELATIONS BETWEEN CHLORINATED ALIPHATIC HYDROCARBONS AND ENVIRONMENTAL VARIABLES IN A CONTAMINATED GROUNDWATER IN SHANGHAI, CHINA Lu Qiang*, Li Hui, Lin Kuang Fei, and Liu Yong Di (East China University of Science and Technology, Shanghai, China) With the development of manufacturing in China's Yangtze River Delta, processing enterprises has exposed a large number of enterprise-situ soil and groundwater contamination incidents during the process when industry layout adjusted and moved out subsequently land transferred and re-circulated. Chlorinated aliphatic hydrocarbons (CHs) as a cleaning solvent in manufacturing plants widely contaminated soil and groundwater due to its extensive usage and inappropriate disposal practices. Natural attenuation reactions of anaerobic aquifers contaminated with CHs always take place and it has become a research hotspot. This study focused on correlations between CHs and Environmental variables in a shallow groundwater contaminated by 1,1,1-Trichloroethane (1,1,1-TCA) in Shanghai, to characterize the natural attenuation law of CHs. Site data from monitoring wells are presented and analyzed. The results showed that less chlorinated products including 1,1-dichloroethane (1,1-DCA), 1,1-dichloroethene (1,1-DCE), chloroethane (CA), and vinyl chloride (VC) were found, CA and VC were accumulated. The plumes distribution of contaminated groundwater covered an area about 5,000 m2 and located in the 4-8 m clay bed underground, including about 50 m3 dense non-aqueous phase liquid (DNAPL). Heatmap of multifactorial analysis for CHs and environmental variables showed that it was a significant negative correlation (P90% fluoride removal can be attained with the added benefit of removing the coffee coloured taint from the SPL contaminated groundwater. Changes in the porosity of the calcite barrier were also examined using cores obtained by injection of resin into a 100mm diameter tube inserted into the calcite barrier before and after testing. Results indicate that after 28 days and 26,000L of leachate there was no significant change in the porosity of the calcite barrier.

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RESIDUES OF VETERINARY ANTIBIOTICS IN ENVIRONMENTAL WATERS IN CENTRAL JIANGHAN PLAIN, CHINA Tong Lei, Wang Yanxin, Liu Hui, Li Minjing (School of Environmental Studies, China University of Geosciences, Wuhan, China) Antibiotics have been widely used in livestock industries since the early 1990s in China. Despite the positive effects, the overuse of antibiotics in livestock feed leads to high concentrations of antibiotics and their metabolites in the waste. Therefore, these drugs and their metabolites can eventually enter ground and surface waters following the common practice of applying manure to agricultural fields. In the present study, the occurrence of antibiotics in surface water and groundwater in a vulnerable aquifer was investigated. The study area locates in the central part of Jianghan Plain, Hubei, China (near Yangtze River, southwestern part of Wuhan city). Low, flat and crisscrossed by rivers and lakes, Jianghan Plain is famous of its agriculture in animal husbandry, fishery and planting industry. The Yangtze River and other located rivers recharge and discharge into groundwater because the hydraulic head of the confined aquifer is equivalent to the surface water. A total of 25 groundwater and 9 surface water samples were collected from Shahu County, Jianghan Plain. Surface waters were collected as a grab sample from near fishponds and main rivers, including East Wuhu Lake, Tongshun River, Kuige River and Lvfeng River, which flowed across the town. Groundwater samples were sucked from hand tube wells. The in situ filtration (0.45 μm) was adopted after sampling and antibiotics were measured immediately by solid-phase extraction and Liquid chromatography tandem mass spectrometry. Nineteen antibiotics belong to four groups, sulfonamides (SMs), fluoroqinolones (FQs), tetracyclines (TCs) and macrolides (MLs) were all detected at least once in surface water and groundwater in study area. For each compound appeared in different sample sites, it obviously that surface water has been polluted heavier than groundwater. Chlorotetracycline, doxycycline and enrofloxacin were the three antibiotics with high concentrations and high relevance ratios in two kinds of water samples. Frequency of detection as high as 100% was found in most macrolide compounds, interestingly, the detected concentrations of which were less than 5 ng/L. High frequency of detection represents widespread use of these compounds in fish ponds or animal husbandry near the main rivers in Shahu County. Antibiotics concentrations in groundwater were highly variable across wells. The differences in residue levels and detection frequency for antibiotics mentioned above could be attributed to variations in dosage levels of animals and metabolic characteristics in the environment.

58


PREDICTION OF COUNTY-LEVEL NEW CONTAMINATION CASES FROM HISTORIC GROUNDWATER CONTAMINATION CASES THROUGH DATA DEPENDENT MODELING Qing Li, Fengxiang Qiao, and Yu Lei (Texas Southern University, Houston, Texas, USA) ABSTRACT: Groundwater is one of the most important natural resources associated with the environment, public health, welfare, and long-term economic growth. Billions of populations rely on the groundwater for their daily activities. However, thousands of contamination cases have been documented in many groundwater reports. The primary contaminants are artificial products such as gasoline and diesel. To protect the important water resource, a series of efforts have been exerted including enforcement and remedial actions. Every year, the Texas Groundwater Protection Committee (TGPC) publishes a “Join Groundwater Monitoring and Contamination Report” described historic and new contamination cases in each county, which is an important data source for the prediction and design of prevention strategies. In this paper, a data dependent modeling (DDM) approach is proposed to predict the county-level new contamination cases (NCC). A case study with contamination information from Harris County in Texas was conducted to illustrate the modeling and prediction process with promising results. The one-step prediction error is 1.5%, while the two-step error is 12.1%. The established model is applicable for the use at county-level, state level, and even country level, while the prediction results could be a kind of reference during decision-making process. INTRODUCTION According to the Environmental Protection Agency (EPA), 97 percent of the rural population depends on groundwater for drinking in Unite States, and 40 percent of people living in United States use groundwater in their daily life for drinking, cooking, cleaning, irrigation, and other types of activities (Moody, 2014). Groundwater has been considered as the safest fresh water resource. However, the groundwater is confronting depletion and contamination has been threatening its supplies (Konikow, 2013). As a matter of fact, except the saltwater intrusion, contamination is more likely to occur in natural recharge process for groundwater. Specifically, in rainwater harvesting, many pollutants may be brought into groundwater by penetration with surface water and eventually deteriorate its quality. The pollutants mainly are the artificial products, such as gasoline, oil, road salts, and chemicals, with which they will pose enormous health effects. For instance, people may suffer from diseases such as hepatitis and dysentery through drinking contaminated groundwater from septic tank waste, and they may be poised by toxins that leached into well water supplies. Other long term effects such as certain types of cancer may be resulted from the exposure to the contaminated groundwater. Many efforts have been made to protect the groundwater resources from deterioration, including enforcement and remedial action. Nevertheless, there are still many new groundwater contamination cases recorded every year. Furthermore, groundwater remediation is a complicated and a time-consuming work due to its location, in soil pore spaces, and in the fractures of rock formations. Prevention is always better than cure, while prediction is essential for preventive strategies. There are many methodologies dedicated to the prediction of specific contamination in groundwater for protection purpose. For instance, Hossain et al. (2013) developed the arsenic contamination risk map using a combination of classification tree and Geographic Information System (GIS) technology. United States Geological Survey (USGS) scientists developed a methodology based on the age of oil and gas wells, the type of soil, the distance from wetlands and streams, and the density of the wells in the area to predict the likelihood of contamination. However, less research has been conducted on the relationship between the historical contamination cases and new cases that potentially take place in groundwater in the near future. This calls for a novel method to predict the new contamination cases in a region. RESEARCH OBJECTIVES

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Environmental Science & Technology 2014 Vol. 1 This study intends to develop a data dependent model (DDM) to predict the number of new contamination cases (NCC) at county-levels. The base data are the existing contamination cases from the Texas Commission on Environmental Quality (TCEW) in annual Join Groundwater Monitoring and Contamination Reports (JGMCR). The proposed model is tested by a case study in Harris County, USA. THE SOURCE DATA The Texas Groundwater Protection Committee (TGPC) services to bridge gaps between existing state groundwater programs, and to optimize water-quality protection by improving coordination among agencies involved in groundwater activities. The TGPC publishes Annual JGMCR based on the activities of ten coordinated organizations, including the Texas Commission on Environmental Quality (TCEQ), the Texas Water Development Board (TWDB), the Railroad Commission of Texas (RCT), and the Department of State Health Services (DSHS). The report provides the annual status of groundwater monitoring associated with the regulatory, planning, and administrative programs of state agencies and local groundwater conservation districts. Also, it reports the annual status of documented groundwater contamination reasonably suspected of having been caused by activities under the jurisdiction of those programs. Specifically each year, in the table of groundwater contamination case descriptions, there are eleven columns including the information on county, division, indication of new case, file name, file number, case location, contamination description, date occurred, enforcement status, data quality, and section number. They are reported by the Texas Natural Resource Conservation Commission. These tables reveal that the main contaminations in groundwater are solvent, gasoline, volatile organic compounds (VOCs), and related petroleum products. What’s more, the tables also demonstrate the progress of enforcement and remedial action for existing individual case, and conformed new contamination cases (NCC) occurred each year. This is a primary data source to build up the suitable prediction mechanism for NCC. DATA DEPEDENT MODELING OF CONTAMINATION NEW CASES Mathematical Representation. In order to better understand how the NCC various each year, and to better model such variation for prediction purpose, a mathematical notation system for NCC observation is , ,…, is used to denote the number of successively observed defined. A discrete series = NCC in a region (e.g., a county in Texas), where i represents the year observed, n is the total number of observations that is also the number of years covered, and is observed at a uniform sampling interval (e.g., once a year). The series is called a time series since all samples are collected chronically. As it might be very difficult to physically describe all factors that may affect the series , one feasibly way to model such series is to seek for a suitable model to capture the autocorrelations between those successive observations. The data dependent modeling procedure is capable of simulating and predicting a stationary time series (Pandit, 1991; Qiao and Yang, 1998; Qiao, 2010). The Data Dependent Model. One traditional data dependent model is the famous ARMA(n, m) model (Pandit, 1991), where AR(n) is the auto-regression of n observed data, and MA(m) represents the moving average with order m. The expanded expression of the ARMA(n, m) model is in Equation 1. =∅

+∅

+ ⋯+ ∅

+

−

+

+ ⋯+

(1)

In Equation (1), is the NCC at year t, means the NCC at ith year before year t, while is a sequence of uncorrelated variables or shocks, following an independent normal distribution: ~ 0, . ∅ and are the coefficients of and that can be calibrated from observed data sets. All terms on the right hand side of equation (1) are related to auto-regression, while all terms are related to moving average. ! " and # " using algorithms such as the ForwardThe coefficients ∅ and can be calibrated as ∅ Backward algorithm (FB), the Least Squares algorithm (LS), the Yule-Walker algorithm (YW), the Burg's 60

Environmental Science & Technology 2014 Vol. 1 algorithm (BURG), and the geometric lattice method (GL) (Pandit and Wu, 1983). With the calibrated coefficients, the NCC number at year t can be estimated as: ! # =∅

! +∅

! + ⋯+ ∅

−#

+#

+ ⋯+ #

$

(2)

where, = − # , n and m are orders of auto-regression and moving average parts, respectively, while the prediction error % at step t is . If multiple ARMA models are involved, the goodness of models can be examined through indexes such as the Akaikes Final Prediction Error (FPE). FPE = ) ∗ 1 + 2 ∗ -/

(3)

where ) is a loss function, d is the number of estimated parameters, and N is the number of estimation data samples. The detailed FPE calculation can be found in Pandit and Wu (1983) and Pandit (1991). Modeling Steps. By definition, a stationary time series should come from a stationary stochastic process, where the mean is constant and can be assumed as zero without loss of generality (Pandit and Wu, 1983). However, there is no any evidence that the observed NCC series is a stationary one. There could be deterministic trend(s) mixed inside the series. Therefore, the observed NCC series could be decomposed into two parts. One part represents the mean of the series, accounting for the non-stationary trend by one or multiple deterministic functions. The second part is a stochastic part with zero mean so that it can be modeled by a data dependent scheme. This yields out three corresponding modeling steps. Step one: to ascertain the trend(s) of observed series by using curve fitting methods (such as Sine/Cosine, exponential, power, logarithmic, linear, and polynomial functions), and calculate the residual series after curve fittings. Step two: to employ the data dependent approach and construct an ARMA(n, m) model by employing the residual series from step one, and predict the values for next one or more step(s). For this research, the next step means the next year. Step three: to re-construct the predicted values by combining the estimation(s) from trend(s) and the prediction from ARMA(n, m) model. CASE STUDY Case Selection. This paper uses the NCC from Harris County in Texas to illustrate the proposed prediction procedure. The groundwater in Texas accounts for 60 % of all water used for domestic, municipal, industrial, and agricultural purposes, while 28% of drinking water is from groundwater, serving over millions of Texans (TGPC, 2013). Based on the 2010 census, Harris County is the most populous county in Texas and the third in the U.S. (Mackun et al., 2011). Besides, there are numerous petroleum industries in this county, resulting in a large amount of groundwater contaminations. Identifying Deterministic Trends. The NCC data from year 1997 through 2012 were carefully retrieved from the JGMCR (TGPC, 1998-2013) and are potted in Figure 1. The solid line is the observed NCC for Harris County and the dashed line is the curve fitting using a Cosine function, representing a periodical variation of contaminations and even the behind production and economics in the region. There are two peeks occurring in years 1997 and 2008, and the fitted Cosine function can be written as in Equation (4). NCC123 = 58.5 ∗ COS 2π/: ∗ ; − 1997

+ 142

(4)

where, t is the year of analysis, and T = 11 years is the oscillation cycle in year. By removing the Cosine trend from the observed NCC series, the residuals are plotted as the solid line in Figure 2. It contains a decreasing trend that can be fitted by a Logarithm function in Equation (5) and is also the dotted line in Figure 2. NCC?@A = −43.04 ∗ LN t − 1997 + 73.977

(5) 61


The new residual subtracting the Logarithm function with zero mean is plotted in Figure 2 as the dash line and is denoted as Residual0, which is the series for data dependent modeling. 350 NCC Data 300

COS-fitting

CNC Numbers

250 200 150 100 50 0 1997

1999

2001

2003

2005

2007

2009

2011

Year

FIGURE 1. The observed NCC solid line and the fitted Cosine (COS) dash line for Harris County. 150 Residual

Residual0

Logarithmic

CNC Residuals

100

50

0

-50

-100 1997

1999

2001

2003

2005 Year

2007

2009

2011

FIGURE 2. The further curve fitting using a Logarithm function and the resulted residuals. Data Dependent Modeling of Residuals. After removing two deterministic trends (Cosine and Logarithm,) several ARMA (n, m) models were constructed from the series residual0: ARMA(1, 0), ARMA (0, 1), ARMA(2, 0), ARMA (1, 1), ARMA (0, 2), ARMA (2, 1), ARMA (0, 3), ARMA (2, 2), and ARMA(0, 4). Figure 3 lists the FPEs of all ARMA models, where ARMA (0, 4) is spotted with the lowest FPE and can also be denoted as MA(4). 9000 8000 7000

FPE

6000 5000 4000 3000 2000 1000 0 1, 0

0, 1

2, 0

1, 1 0, 2 2, 1 ARMA (n, m)

0, 3

2,2

0, 4

FIGURE 3. Comparison of different data dependent models via FPE values. The predicted value E with calibrated parameters can be calculated using Equation (6).

E = − 0.2327

F

− 0.08476

F

− 0.2246

F H

62

+ 0.8756

F I

(6)

Environmental Science & Technology 2014 Vol. 1 With the information of the first 14 years (1997-2010) for modeling, the predictions for years 2011 and 2012 of the constructed MA (4) model (as is shown as the dashed line in Figure 4) are very close to the residual0 series from observed ones (the solid line in Figure 4). Prediction Errors. By recovering the two trends for both Cosine trend and the Logarithm trend, the one step prediction of NCC in year 2011 is 66 (vs. the observed NCC 65) with a relative error of 1.5%. The two step prediction of NCC for year 2012 is 111 (vs. the observed one 99) with a relative error of 12.1%. 100 80

Residual0

60

ARMA(0, 4) prediction

Residual0

40 20 0 -20 -40 -60 -80 1997

2002

2007

2012

Year

FIGURE 4. Comparison between predicted (years 2011 and 2012) and residual0 series. Computer Program. Most of the above modeling and prediction procedures are implemented through a self-coded program in computer language MATLAB, while the “Statistics” and “Economics” toolboxes were used durin programming. By feeding different input data, the compiled program is capable of modeling and predicting NCC numbers and other similar variables at different levels. Discussion. The observed NCC can be decomposed into three parts. First, the Cosine trend NCC123 in Figure 1 and Equation (4) could be a reflection of the economics and production cycle of 11 years with four stages, which could be expansion, crisis, recession, and recovery. This fits to the Juglar cycle in economics with an investment cycle of 7 to 11 years identified by Juglar (1862). Within the Juglar cycle, one can observe oscillations of investments into fixed capital. A recent research employing spectral analysis confirmed the presence of Juglar cycles in world Gross domestic product (GDP) dynamics (Korotayev and Tsirel, 2010). Second, the Logarithm value NCC?@A in Figure 2 and Equation (5) represents a decreasing trend of NCC due to the implication of possible innovative technologies and/or more strict government policies in environmental protection. This is a part leading to the decreasing of contamination from groundwater, and the trend of decreasing since late 2010s is not as strong as that in late 1990s. Third, the stochastic part E is represented by the MA(4) model in Equation (6). This part senses the residual non-deterministic trends and grasps the dependency of successive data series, so as to increase the precision of forecasting. The total prediction should combine the estimates from all three parts from Equations (4)(6). CONCLUSION In this paper, a data dependent approach is proposed to model and predict the county-level contamination new cases in Texas. Deterministic trends are firstly removed, followed by a modeling procedure to ascertain the best fit ARMA model. A case study on 16 years’ NCC numbers in Harris County was conducted and the one step prediction error was only 1.5% (actually only one more case predicted). However, the two step prediction error increased to 12.1%. With more years’ NCC observations accumulated, the prediction errors could be even smaller. While the proposed approach was tested using information from Harris County of Texas, the fundamental method could be employed in other counties, states, and even countries. With the prediction from such method, relevant stakeholders, agencies, and government could be able to propose and implement suitable countermeasures in advance so as to mitigate the negative impacts of those contaminations on groundwater. 63


ACKNOWLEDGEMENTS Supports for this research by the U.S. National Tier 1 University Transportation Center (UTC) TranLIVE and the U.S. National Science Foundation (NSF) CREST #1137732 are gratefully acknowledged. REFERENCES Environmental Protection Agency (EPA). 1984. Ground-Water Protection Strategy. Washington, D.C. Hossain. M. and P. Mongkut. 2013, “Groundwater Arsenic Contamination Risk Prediction Using GIS and Classification Tree Method” Elsevier, Engineering Geology, volume 156, April 2013, pages 37-45. Juglar. C. 1862. Des Crises Commerciales et Leur Retour Periodique En France, En Angleterre, et aux Etats-Unis. Paris: Guillaumin. (French). Konikow, L.F. 2013. Groundwater Depletion in the United States (1900−2008). U.S. Geological Survey Scientific Investigations Report. 2013−5079, 63 p. Korotayev, A. V., and Tsirel, S. V. 2010. “A Spectral Analysis of World GDP Dynamics: Kondratieff Waves, Kuznets Swings, Juglar and Kitchin Cycles in Global Economic Development, and the 2008– 2009 Economic Crisis.” Structure and Dynamics. Vol.4. #1. P.3-57. Mackun. P and S. Wilson. 2011. Population Distribution and Change: 2000 and 2010. 2010 Census Briefs Moody. D. W. 2014. Environmental Protection Agency (EPA). “#3: Sources and Extent of Groundwater Contamination”, Groundwater and public policy leaflet series. http://dnr.wi.gov/topic/Groundwater/documents/pubs/gwcntsrcs.pdf. Date accessed: April 29, 2014. Pandit, S. M. 1991. Modal and Spectrum Analysis: Data Dependent Systems in State Space. Pandit, S. M. and S.M. Wu. 1983. Time Series and System Analysis with Applications, John Willey and Sons, Inc. New York, NY. Qiao, F. 2010. Intelligent Data Dependent Modeling of Traffic Flow: Solving Problems in Traffic Flow Classification, Simulation, and Control. ISBN-10: 3-8383-2906-6. Publisher: Lap Lambert Academic Publishing. 244 pages. Qiao, F. and H. Yang. 1998. “A Dynamic Data System Approach to Simulate Freeway Traffic Flow.” Postproceedings of the 8th World Conference on Transportation Research, Antwerp, Belgium, July 12-17. Texas Groundwater Protection Committee (TGPC). 1998-2013. Join Groundwater Monitoring and Contamination Report 1997-2012. Texas Groundwater Protection Committee (TGPC). n.d. “Groundwater Facts & References” file:///D:/University/ICEST_2014/groundwater/TGPC_GW_Facts_References.pdf. Date accessed: April 29, 2014

64


EXPLORING THE INFLUENCE OF DISSOLVED ORGANIC MATTER ON PHOSPHORUS MOBILITY IN GROUNDWATER Christine A. Rumsey, Darwin L. Sorensen, David K. Stevens, and Joan E. McLean (Utah Water Research Laboratory, Logan, UT, USA) Phosphorus (P) concentrations in the shallow, unconfined aquifer at Pineview Reservoir, Utah indicate increased phosphorus transport is occurring in groundwater. Because of known septic system influence in shallow groundwater, a set of sorption experiments was completed to determine whether the presence of dissolved organic matter (DOM) influences P sorption and increases P mobility. A P only and a P + DOM isotherm were completed for two types of aquifer sediments. Initial P concentrations of 0, 1, 2, 5, 7, and 10 mg PO4-P/L were chosen to simulate environmentally relevant conditions. For the P + DOM isotherm, 15 mg C/L was spiked into the DOM artificial groundwater solution. Aquifer sediments were collected from two locations around the reservoir to be used in sorption experiments. Sediments represented coarse-grained and fine-grained sediments. Artificial groundwater was prepared to match the principal cation and anion concentrations of groundwater at the two sampling locations. DOM used in sorption experiments was obtained by concentrating DOM from groundwater at the two sample sites using reverse osmosis and dialysis. Dialyzed DOM concentrates were characterized using DOC, UV/visible absorption spectrum, proteins, sugars, and fatty acid concentration. Results suggest that at the environmentally relevant levels of P and DOM used in experiments, DOM did not create a notable effect on P sorptive behavior. Final DOM was composed of relatively large biomolecules and had a more aromatic, hydrophobic, and humic nature than the original groundwater. These larger molecular weight molecules, including sugars and proteins, had a minimal effect on P sorption. Factors such as saturated sorption sites and the effects of historic septic system loading are more likely the reasons soluble P is present in the shallow unconfined aquifer at PVR.

65


AN ANALYSIS OF GROUNDWATER CHEMISTRY OF HOT SPRINGS IN THE SOUTPANSBERG BASIN IN SOUTH AFRICA Ayanda Shabalala*, A.P.K. Nyabeze and Zuko Mankayi (Council for Geoscience, Pretoria, Gauteng, RSA) Groundwater aquifer and water chemistry of hot springs were investigated to understand the geothermal potential of the Soutpansberg Basin. Water sampling was carried out at five hot springs namely Tshipise, Dopeni, Mphephu, Sagole and Siloam. Water quality parameters were measured in situ using portable, multi-sensor meters. Cations were analyzed using inductively coupled plasma optical emission spectrometry (ICP-OES) and anions by ion chromatography (IC). The hot springs were found to be enriched in sodium, bicarbonate and chlorine with very low concentrations of other element species. The chemical composition of Tshipise, Sagole and Siloam thermal springs indicates the same source of origin of Na-Cl-HCO3 waters, typical of deep circulating groundwater. Chemical analysis of the ground water revealed that the water does not have any indication of pollution. High temperatures of 59.4, 51.2 and 46.0 ◦C were recorded at Siloam, Tshipise and Dopeni hot springs respectively. The relatively high temperature and the deep groundwater circulation are factors that support the geothermal potential of the Soutpansberg Basin.

66


ATMOSPHERIC REACTIVE NITROGEN DEPOSITION ONTO COASTAL REGIONS IN CHINA Xiaosheng Luo and Xuejun Liu* (China Agricultural University, Beijing, China) With the increasing reactive nitrogen (Nr) creation and emissions, more and more Nr enter into the coasting sea by nitrogen deposition and lead to eutrophication of the coasting ocean and harmful alga bloom in the ocean occurred frequently. To determine the present conditions of atmospheric Nr deposition in coasting sea of China, six coasting sampling sites were selected to monitor Nr concentrations in air and precipitation as well as their dry and wet deposition in 2011. Atmospheric concentrations of NH3, HNO3, NO2, pNH4+, and pNO3- were 1.97-4.88, 0.46-1.22, 3.03-7.09, 2.24-4.90, 1.13-2.63 µg N m-3 at Dalian, Changdao, Linshandao, Fenghua, Fuzhou and Zhanjiang sampling sites, respectively. NO3--N and NH4+-N concentrations ranged from 0.46 to 1.67 mg N L-1 and 0.47 to 1.31 mg N L-1 in rain samples at the six sampling sites, respectively. Dry N deposition was 13.0-34.1 kg N ha-1 yr-1 and total N deposition was 27.255.6 kg N ha-1 yr-1 at the six coastal sampling sites. Average N dry deposition account for 55.8% of the total deposition, and NH3 and NO2 contribute 67.1% for the total dry deposition. Applying the half N deposition rate in this study for the four Seas (Bohai Sea, Yellow China Sea, East China Sea and South China Sea) around China, the total N wet and dry deposition can amount to 6.2 Tg N yr-1, reflecting a huge environmental nutrient input onto the ocean.

67


NUTRIENT LOAD PREDICTIONS IN STREAMS USING LS-SVM AND WAVELET-ANN Raj Mohan Singh (Department of Civil Engineering, Motilal Nehru National Institute of Technology, Allahabad-211004, INDIA; E-mail: [email protected]; [email protected]) ABSTRACT: Rise in nutrients concentrations have been a persistent problem in streams rivers throughout the world. Estimates of nutrient fluxes are necessity as well as challenges for water quality management. The observation of nutrient loads (of nitrogen and/or phosphorous) from watershed into river or stream system is not straight forward but complex function of hydrology, geology, and land use of the region. There are statistical approaches to predict the nutrients loads in rivers. Development of models based on temporal observations may improve understanding the underlying hydrological processes complex phenomena of nutrient concentrations in river. Present work utilized temporal patterns extracted from temporal observations of monthly flow data and nitrogen loads using wavelet theory. Performance results show that time series least square support vector results are comparatively better than ANN model results for predicting the monthly nutrient load. Model efficiency on testing data set is 32 percent for WaveletANN model whereas 35 percent for LS-SVM (least square support vector machine) when only one input (discharge) is used. Keywords. Wavelet-ANN, Time series modeling, Wavelet transforms, Nutrients, Nitrogen, load prediction.

INTRODUCTION Rivers have been central to the growth of societies throughout recorded history. Their fertile floodplains produced, and continue to produce, high yields from agricultural crops. The rivers yielded high harvests of fish, and river ecologists have learned that fish production, too, is linked to the productive floodplain [Junk et al., 1989]. Both nitrogen and phosphorus have complex cycles that are mediated by physical, chemical, and biotic processes in the water and in the soil [Brady and Weil, 2008].These processes are modulated by temperature and water conditions. Therefore, nitrogen and phosphorus cycles are expected to be affected by the timing of floodplain inundation. Excessive addition of nutrients, usually nitrogen and phosphorus (N and P), to natural water is usually refers as eutrophication [Jorgenson and Richardson, 1996]. Rise in nutrient concentrations can result in locally high algal, phytoplankton, and macrophyte biomass that have negative impacts on aquatic habitat and biota. Additionally, the transport of these nutrients can lead to degradation of downstream water bodies, such as lakes, reservoirs, and estuaries [USEPA, 2000]. Noteworthy examples of problems associated with elevated nutrient concentrations vary from eutrophication of lakes and reservoirs to hypoxia (low concentrations or absence of dissolved oxygen) [Saad et al., 2002]. Nutrient enrichment results in the excessive growth of plants including phytoplankton in surface waters. In recent years, eutrophication has been recognized as an important issue for environmental concern. It becomes one of the most serious water pollution problems (Lee and Arega, 1999; Su and Dong, 1999). Eutrophication can stimulate rapid algal growth, resulting in massive algal glooms. High biomass during algal blooms may initiate significant ecological problems and cause harmful effects in the biota of the region (Scholten et al., 2005). Some typical problems include anoxia condition of the water, change in biocommunity and food-web, deterioration of the water quality and adversary effects on the recreational use of the water. Anoxia or hypoxia induced by algal blooms would cause declines in fishery production, major changes in species composition, and distortions of sex ratio of some fish (Shang et al., 2006). In the water supply source the organic matter excreted from algae cannot be effectively removed by enhanced coagulation and filtration, and hence it is difficult to control the formation of disinfection by-products in drinking water (Cheng and Chi, 2003). 68

Environmental Science & Technology 2014 Vol. 1 The gradual accumulation of water quality data records over the past few decades has increased the value of these data for examining long-term trends. However, on many major rivers of different countries, infrequent sampling of most pollutants makes flux estimates and their analysis difficult. The present work utilized the monthly data for the Idaho River to estimate the nitrogen loads using Wavelet ANN conjunction model. Transport of nutrient into river or streams is complex function of hydrology of the region and land use patterns in a given river or stream basin which are difficult to quantify accurately. Development of models based on temporal observations may improve understanding the underlying hydrological processes in such complex phenomena. Recently, artificial neural network (ANN) as a non-linear inter-extrapolator is extensively used by hydrologists (Nourani et al., 2009). ANNs may not be able to cope with nonstationary data if preprocessing of the input and/or output data is not performed. Therefore, in this study, a new combined model was developed for monthly nitrogen load prediction based on wavelet decomposition and ANN techniques. The aim of combining the wavelet and ANN models is to improve the accuracy of nutrient load prediction. Present work utilized temporal patterns extracted from temporal observations of monthly nutrient load series using wavelet theory. These patterns are then utilized by an artificial neural network (ANN). The wavelet-ANN conjunction model is then utilized to predict the monthly nitrogen load in a stream. The application of the proposed methodology is illustrated with real data pertaining to Indian River system. ARTIFICIAL NEURAL NETWORK The ANN is a broad term covering a large variety of network architecture, the most common of which is a multilayer perceptron feedforwrd network with back propagation algorithm [Rumelhart et al., 1986]. There is no definite formula that can be used to calculate the number of hidden layer(s) and number of nodes in the hidden layer(s) before the training starts, and usually determined by trial-and-error experimentation. The back propagation algorithm is used for training of the feed forward multi-layer perceptron using gradient descent (Bishop, 1995; Singh et al., 2004). Present paper utilized LevenbergMarquardt (LM) backpropagation algorithm to optimize the weights and biases in the network. LM algorithm is more powerful and faster than the conventional gradient descent technique (Hagan and Menhaj, 1994; Kisi, 2007). Basics and details of ANN are available in literature (Haykin, 1994). LEAST SQUARES SUPPORT VECTOR MACHINE (LSSVM) Support vector machine (SVM) is based on statistical learning theory as proposed by Vapnik and Chervonenkis (1971) and discussed in detail by Vapnik (1995). It is a Kernel-based technique available in the field of machine learning (Cortes and Vapnik, 1995). It is one of the most sophisticated nonparametric machine learning approach available with various applications and many different configurations (Burges, 1998) depending upon the kernel and optimization method used. SVM has been applied successfully to time series prediction as seen in the works of Tay and Cao (2001), Thiessen and Van Brakel (2003) and Misra et al. (2009). Some of the application of SVM have also been carried out in hydrological and water resources planning (Wang et al., 2009; Asefa et al., 2006; Lin et al., 2006; Dibike et al., 2001; Liong and Sivapragasam, 2002; Yu et al., 2006). The standard SVM is solved using quadratic programming methods. However, this method is often time consuming and has a high computational burden because of the required constrained optimization programming. Least squares support vector machines (LSSVM), as a modification of SVM was introduced by Suykens and Vandewalle (1999) and Suykens et al. (2002). LSSVM is a simplified form of SVM that uses equality constraints instead of inequality constraints and adopts the least squares linear system as its loss function, which is computationally attractive. Besides that, it also has good convergence and high precision (Samsudin et al. 2011). Hence, this method is easier to use than quadratic programming solvers in SVM method. Extensive empirical studies (Wang and Hu, 2005) have shown that LSSVM is comparable to SVM in terms of generalization performance. This LS-SVM formulation modifies Vapnik’s SVM (Vapnik, 1995) at two points. First, LS-SVM takes equality constraints instead of inequality constraints. Second, the error variable ei was introduced in the sense of least-square minimization. These error variables play similar role as the slack variables in SVM formulation such that relatively small errors can be tolerated (Suykens et al. 2002). The major advantage of LSSVM is that it is computationally very cheap besides having the important 69

Environmental Science & Technology 2014 Vol. 1 properties of the SVM. LSSVM has been successfully applied in diverse fields (Afshin et al., 2007; Lin et al., 2005; Sun and Guo, 2005; Gestel et al., 2001). However, application of LSSVM in the water resource filed is limited (Yunrong and Liangzhong, 2009; Samsudin et al. 2011; Bhagwat and Maity, 2013 etc). The LSSVM is a new technique for regression. In this technique, the predictor is trained by using a set of time series historic values as inputs and a single output as the target value. The first step would be to (xi is the input vector; di is the desired value and n is consider a given training set of n data points , data size). SVM approximates the function in the following form J = KL +M (1)

Where L is the high dimensional feature space which is mapped from the input space x. Values of w and b are estimated by minimizing the regularized risk function in the feature space with a squared loss (Suykens et al., 2002): S NOP Q K, % = K R K + ∑ U % (2) Subject to the equality constraints: V = KL +M+% (3) where γ is the regularization constant parameter; and ei is error vector for xi in optimizing the trade-off between minimizing the training errors and minimizing the model’s complexity. The solution is obtained after constructing the Lagrange: ) K, M, %, ∝ = Q K, % − ∑ U ∝ K R L

+M+% −V

(4)

With Lagrange multipliers αi, the conditions for optimality are obtained by partially differentiating with respect to w, b, ei and αi,:

XY X\

XY XZ

XY X]^

=0→K=∑U ∝ L

=0→∑U ∝ =0

(6)

= 0 →∝ = _% XY X∝^

(5)

(7)

= 0 → KRL

+M+% −V =0

(8)

From the set of Equations (5)–(8), w and e can be eliminated and finally, the estimated values of b and αi can be obtained by solving the linear system. Replacing w in Equation (1) from Equation (5), the kernel trick may be applied as follows using Mercer’s condition (Mercer, 1909; Vapnik, 1995; Courant and Hilbert, 1953): R à , b c = L .L b (9) Here, the kernel trick means a way to map the observations to an inner product space, without actually computing the mapping and it is expected that the observations will have a meaningful linear structure in that inner product space. This finally leads to the following LSSVM model for function estimation: Vd = ∑ U e à , b c + M (10)

where αi, b are the solution to the linear system. Any function that satisfies Mercer’s condition can be used as the kernel function. K(xi , xj ) is defined as the kernel function. The value of the kernel is equal to the 70

Environmental Science & Technology 2014 Vol. 1 inner product of two vectors Xi and Xj in the feature space L and L b that is, à , b c = L × L b . The structure of a LSSVM is shown in Fig. 1. Generally speaking, there is no general guiding principle for choosing a kernel function (Li et al., 2010). The widespread use of kernel functions includes radial basis function (RBF), linear, sigmoid and polynomial ones. For these four kernel functions, in general, the RBF kernel function is a reasonable first choice (Liu et al., 2009). This kernel function nonlinearly maps samples (data patterns) into a higherdimensional space. So, unlike the linear kernel, it can handle the case when the relation between class labels and attributes is nonlinear. The second reason is that the RBF kernel function has a less number of hyperparameters which influences the complexity of model selection. Finally, the RBF kernel has fewer numerical difficulties (Caydas¸ and Ekici, 2012; Avci, 2012; Comak and Arslan, 2012). In comparison with some other feasible kernel functions, the radial basis function (RBF) is more compact and is able to shorten the computational training process and improve the generalization performance of LS-SVM, a feature of great importance in designing a model (Suykens and Vandewalle 1999). Aksornsingchai and Srinilta (2011) studied support vector machine with polynomial kernel and with radial basis function (RBF) kernel and found that RBF is more accurate for statistical downscaling. Also, many studies have demonstrated the favourable performance of the RBF (Choy and Chan 2003; Dibike et al. 2001; Han and Cluckie 2004; Liong and Sivapragasam 2002; Yu and Liong 2007). Therefore, the RBF kernel function is employed in this study. The RBF kernel function can be expressed as: ` , = exp jk ‖ − ‖ (11) where is the kernel function parameter of the RBF kernel. The symbol ‖m‖ is the norm of the vector V and thus, ‖ − ‖ is basically the Euclidean distance between the vectors x and xi. In the context of nitrogen prediction, xi is the new vector of time series inputs (flow and/or total nitrogen concentration), based on which total nitrogen load prediction (Vd ) is made. Values of yi (observed) and Vdn (predicted) are compared to assess the model performance. Details of Methodology are presented in Fig. 1.

Fig.1. Schematic of support vectors methodology WAVELET ANALYSIS Wavelet analysis allows the use of long-time intervals for low frequency information and shorter intervals for high frequency information. Wavelet analysis is capable of revealing aspects of original data like trends, breakdown points, and discontinuities that other signal analysis techniques might miss. Furthermore, it can often compress or denoise a signal. Basics of wavelets are available in literature (Daubechies, 1998; Kang and Lin, 2007; Mallat, 1998). Discrete wavelet transform (DWT) 71

Environmental Science & Technology 2014 Vol. 1 operates two sets of function (scaling and wavelets) viewed as high-pass and low-pass filters (Fig. 2). The original time series are passed through high-pass and low-pass filters and separated at different scales. The time series is decomposed into one comprising its trend the approximation and one comprising the high frequencies and the fast events (the detail). In the present study, the detail coefficients (D) and approximation (A) subtime series are obtained using MATLAB wavelet tool box (MATLAB, 2004).

Fig. 2. Decompositions of time series data into DWT components

WAVELET-ANN CONJUNCTION MODEL FOR NITROGEN NUTRIENTS Wavelet-ANN conjunction model utilized wavelet decomposed coefficients ob-tained from wavelet analysis to the ANN technique for daily sediment load prediction as shown in Fig.3.

Fig.3. Wavelet-ANN conjunction Model for Nitrogen Nutrients First, the measured daily time series, Q (discharge) (m3/s) and/or N(Nitrogen nutrients, NO2 +NO3) (mg/l) were decomposed into smulti-frequency time series comprising of details (low scale, high frequency) - Qd1(t); Qd2(t);…; Qdi(t) for discharge and Nd1(t); Nd2(t);…; Ndi(t); and approximate (high scale, low frequency) – QA(t) for discharge and NA(t) by DWT. The representation di presents the level ‘i’ decomposed details time series and ‘A’ denotes approxi-mation time series. The decomposed Q(t) and N(t) time series were utilized as in-puts to the ANN model and the original time series of observed nutrient load at the next step N(t+1) is output to the Wavelet-ANN model (Fig. 3). Model Evaluation Criteria. The performances of the developed models are evaluated based on some performance indices in both training and testing set. Varieties of performance evaluation criteria are available which could be used for evaluation and inter comparison of different models. Following four performance indices represented as correlation coefficient (R), root mean square error (RMSE), model efficiency (Nash–Sutcliffe Coefficient, MENash) [Nash and Sutcliffe, 1970], and Index of agreement (IOA) are selected in this study based on relevance to the evaluation process.

R=

RMSE =

n ∑ ( Xai − i =1

Xai )( Xpi − Xpi )

n 2 n ∑ ( Xai − Xai ) ∑ ( Xpi − i =1 i =1

(12)

Xpi) 2

1 n ( ∑ ( Xai − Xpi ) 2 ) n i =1

(13)

72


n 2 ∑ ( Xai − X pi ) i = 1 ME Nash ( E ) = 1.0 − n 2 ∑ ( X ai − Xai) i =1 n 2 ∑ ( Xai − X pi ) i = 1 IOA = 1.0 − n 2 ∑ ( X ai − Xai ) + ( X pi − Xpi ) i =1

[

(14)

(15)

]

where Xai and Xpi are measured and computed values of atrazine concentration values in streams; Xai and Xpi are average values of Xai and Xpi values respectively; i represents index number and n is the total number of years of measurement. Application LS-SVM and Wavelet-ANN Conjunction Model. The developed models require uninterrupted time series data pertaining to flow and Nitrogen load at a gauging station for calibration and verification periods. The data derived from the Iowa River at the Wapello, IA site (USGS Station Number 05465500; basin area (sq mi): 12,499; latitude: 41°10′48′′; longitude: 091°10′57′′) were employed to train and test all the models developed in this study. The monthly time series of Q and N (NO2 +NO3) for this station were downloaded from the USGS web server (http://toxics.usgs.gov/pubs/of-20071080/sub_basins/IOWAWAPE. Monthly. xls). Monthly data from October 1978 to September 1997 (20 yrs) and the data from October 1997 to September 2005 (8 years) were used as training and testing sets, respectively. RESULTS AND DISCUSSIONS One of the most important steps in developing a satisfactory forecasting model such as ANN and LSSVM models is the selection of the input variables. In this study, the nine input structures which having various input variables are trained and tested by LSSVM and ANN. For LS-SVM and Wavelet-ANN conjunction models are implemented on MATLAB platform. For developing the time series LS-SVM models, three input conditions are considered- first, when flow data is input Three time series After loading the data, hyper-parameters gamma and sigma squared are tuned. Final values of parameters obtained are The function values and corresponding parameters values are shown in Table-. After 10 iterations, back propagation ANN training algorithm is implemented for obtaining the optimal ANN architecture with the internal parameters as: number of epoch=1000; momentum coefficient=0.8. Table 1. Training and testing errors for WANN conjunction model and TANN Models (Trainlm) WANN 1 2-2-1 W-LS-SVM T-LS-SVM TANN 1 1-2-1

Training /Testing Training Testing Training Testing Training Testing Training Testing

R

Performance statistics RMSE E

IOA

0.671 0.578 0.746 0.598 0.549 0.486 0.556 0.498

4.6E+03 5.4E+03 4.2E+03 5.34E+03 5.2E+03 5.8E+03 5.2E+03 5.8E+03

0.777 0.700 0.8381 0.7311 0.669 0.579 0.669 0.596

0.450 0.326 0.5568 0.3466 0.301 0.23 0.309 0.238

In addition, optimum combinations of transfer functions in the hidden and output layer are obtained with ‘trainlm’ function for Levenberg- Marquardt (LM). Performance of Wavelet–ANN (WANN) conjunction model is compared with actual time series (without wavelet decomposition) ANN model (TANN). Two WANN models, WANN 1 and WANN 2 are developed. WANN-1 model has two inputs (wavelet decomposition-approximation and details coefficients of discharge data at time t by wavelet transform DWT Haar wavelet level 1). The output for WANN 1 model is Nitrogen concentration in the river 73

Environmental Science & Technology 2014 Vol. 1 at time t+1. Two TANN models, TANN 1 and TANN 2, are also developed. TANN 1 model has one in-put i.e. actual discharge at time t and one output (nitrogen load at time t+1. The TANN 2 model has two inputs i.e. both actual discharge and nitrogen load at time t. The output is same as TANN 1 model. Thus, output of all the models is same. Two LS-SVM models are developed: one having input-output similar to TANN and second having input-output similar to WANN. Experimentation with varying number of hidden nodes and training algorithm are performed. The error statistics of best performing WANN and TANN models in training and testing are shown in Table 1. LS-SVM with time series (T-Ls-SVM) out performs the time series ANN whereas wavelet When both discharge and sediment data are employed in nitrogen prediction, results improve LS-SVM (W-LS-SVM) out performs the wavelet ANN modelthe considerably. WANN2 model (4-3-1) outperforms TANN2 (2-21) as evident from performance statistics presented in Table 1. CONCLUSIONS The study presents the general framework for evaluating nutrients load in a river system. Methodology for wavelet-ANN conjunction model for nitrogen load prediction in rivers is demonstrated through illustrative real monthly discharge and nitrogen concentration data. The values of statistical performance evaluation criteria indicate the WANN time series model is able to simulate the complex nitrogen transport event in rivers. Wavelet decomposition improved the results considerably. Model efficiency on testing data set is 32 percent for Wavelet-ANN model whereas 35 percent for LS-SVM (least square support vector machine) when only one input (discharge) is used. Multi levels of wavelet decomposition may further improve the testing results.

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Environmental Science & Technology 2014 Vol. 1 Shang E.H.H. Yu R.M.K. and Wu R.S.S. (2006) Hypoxia Affects Sex Differentiation and Development, Leading to a Male-Dominated Population in Zebrafish (Danio rerio) Environmental Science and Technology, 40, 3118-3122. Singh, R.M, Datta, B., Jain, A. (2004). Identification of unknown groundwater pollution sources using artificial neural networks, Journal of Water Resources Planning and Management, ASCE, 130(6), 506514. Su J.L. and Dong L.X. (1999) Application of Numerical Models in Marine Pollution Research in China. Marine Pollution Bulletin, 39, 1-12, 73-79. Sun, G. and Guo, W. (2005). Robust mobile geo-location algorithm based on LSSVM, IEEE T. Veh. Technol., 54(2), 1037–1041. Suykens, J. A. K. and Vandewalle, J. (1999). Least squares support vector machine classifiers, Neural Process. Lett, 9(2), 293–300. Suykens, J. A. K., Van Gestel, T., De Brabanter, J., De Moor, B., and Vandewalle, J. 2002). Least squares support vector machines, World Scientific, Singapore. Tay, F. and Cao, L. (2001): Application of support vector machines in financial time series forecasting, Omega Int. J. Manage. Sci., 29(4), 309–317. Thiessen, U. and Van Brakel, R. (2003). Using support vector machines for time series prediction, Chemometr. Intell. Lab., 69, 35–49. U. C aydas¸ and S. Ekici, “Support vector machines models for surface roughness prediction in CNC turning of AISI 304 austenitic stainless steel,” Journal of Intelligent Manufacturing, vol. 23, pp. 639–650, 2012. USEPA (U.S. Environmental Protection Agency), 2000. Nutrient Criteria Technical Guidance Manual— Lakes and Reservoirs: Office of Water, Office of Science and Technology, EPA-822-B-00-001., Washington, D.C. Vapnik, V. N. (1995): The Nature of Statistical Learning Theory. New York: Springer-Verlag. Vapnik, W. N., and Chervonenkis, A. Y. 1971, On the uniform convergence of relative frequencies of events to their probabilities. Theory of Probability and its Applications. Vol.17, pp.264-280. Wang, H. and Hu, D. (2005). Comparison of SVM and LS-SVM for Regression, IEEE, 279–283. Wang, W. C., Chau, K. W., Cheng, C. T., and Qiu, L. (2009). A Comparison of Performance of Several Artificial Intelligence Methods for Forecasting Monthly Discharge Time Series, J. Hydrol., 374, 294– 306. Wang, W., Gelder, V. P., and Vrijling, J. K. (2006). Forecasting daily stream flow using hybrid ANN models, J. Hydrol., 324, 383–399. Yu, P. S., Chen, S. T., and Chang, I. F. (2006). Support vector regression for real-time flood stage forecasting, J. Hydrol., 328(3–4), 704–716. Yu, X., and Liong, S.-Y. (2007). “Forecasting of hydrologic time series with ridge regression in feature space.” J. Hydrol., 332(3–4), 290–302. doi: 10.1016/j.jhydrol.2006.07.003.

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THE STUDY OF DESTRUCTIVE EFFECTS OF WASTEWATER CAUSED BY THE ACTIVITIES OF LEATHER MANUFACTURING FACTORIES IN TEHRAN Shobeiri Seyed Mohammad1, Kavei Behrouz2, Shotorbani Azarmir Marjan3, Alireza Bassiri4, Nazari Batoul5 Department of Environmental Education, Payame Noor University, P.O.Box: 19395-4697, Tehran, Iran. 2 Department of Statistics, Sanjesh Organization, Tehran, Iran. 3 Department of Environmental Education, Payame Noor University, P.O.Box: 19395-4697, Tehran, Iran. 4 Department of Environmental Education, Payame Noor University, P.O.Box: 19395-4697, Tehran, Iran. 5 Department of Medical Sciences, University of Ahvaz, Iran. 1

Considering the fact that water is the single most important and vital element, and there is no replacement for it and having access to a desired amount and quality is of essence, the conservation of water quality and quantity has to be of the utmost priority. With the rise of the development trends and the formation of industrial development plans in developing countries, the state of the environment in such countries have started to raise concerns. Unfortunately, along with the gradual depletion of the size of available water resources, various types of pollution add to the existing problems within water resources. Different industries produce different types of pollution with their wastewater whose entry to the environment without refinement could cause irreparable damages. One of the major industries emitting industrial wastewater is leather industry. This industry gives off wastewater which is also used for its additives. The parts and wastes of the skin itself contain a lot of pollutants like high BOD5, intense color, soluble salt, chemicals and high PH. Thus, leather industry wastewater needs to undergo a careful and meticulous refinement for the fact that it contains three types of physical, chemical and biological pollution so that the damage inflicted upon the environment would subside. The most effective step to protect the environment is to assess people’s performance and behavior to achieve basic principles of sustainable living; a sustainable development that depends on sustaining the earth would not be possible unless a sustainable economy, a sustainable society and a sustainable utilization are realized. The present study aimed to help improve the conditions and function of refineries by studying destructive effects of wastewater caused by the activities of leather manufacturing factories in Tehran, by evaluating the competency of the managers in this industry and by proposing solutions to problems so that an important step to achieving a sustainable development is taken. For this purpose, with objective observation using a checklist, existing methods will be weighed. Regrettably, the performance of leather industry refineries in Tehran is not favorable and it is not near standards and there is no refining carried out practically. The best solution considering the current status is to follow methods that help decrease the creation of wastewater until refineries are operational. Also, with optimal management, the consumption of substances like chromium, which causes the most damage to the environment in this regard, should be cut down so less of this substance enters wastewater networks and the environment.

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THEORETICAL ANALYSIS OF POLLUTANT-MIXING ZONE FOR RIVERS WITH VARIANT LATERAL DIFFUSION COEFFICIENT Zhou-Hu Wu (Qingdao Technological University, Qingdao, Shandong, P. R. China) Wen Wu (Queen's University. Kingston, Ontario, Canada) ABSTRACT: For point constant source in straight-bank wide open channel, analytical solution for the pollutant concentration distribution under variant lateral diffusion coefficient condition was obtained by solving simplified two-dimensional transport equation, in which the advection in longitudinal direction and the diffusion in lateral direction had been taken into consideration. The calculation method for pollutant mixing zone was investigated. Theoretical formulas for the maximum length, maximum width and the corresponding longitudinal coordinate of the maximum width of the pollutant mixing zone had been deduced, as well as its area and the contour-curve formulas of its outer boundary. Further discussion had focused on the effects of variant lateral diffusion coefficient on the morphology of the pollutant mixing zone. INTRODUCTION Generally speaking, wastewater discharged from industrial, municipal or other resources cannot meet the environmental quality standards. It causes the formation of dilution/diffusion zone of pollutants where their concentration exceeds the environmental quality standards, so called pollutant mixing zone. ZHANG YL, et al. (1993) concludes that when the wastewater quality exceeds the environmental quality standards, pollutant mixing zone is acceptable as long as its area keeps relatively small. One of the pollutant mixing zone technical procedure manuals (drafts), for instance, was proposed by Idaho Department of Environmental Quality in 2008. It includes the mixing zone rules, mixing zone approval process, monitoring, incomplete versus complete mixing, mixing zone determinations and water quality modeling etc (Idaho Department of Environmental Quality, 2008). WU Z H, et al (2009, 2011) developed an analytical pollutant mixing zone calculation method for constant lateral diffusion coefficient cases such as wide, rectangular and straight rivers. The analytical formula for geometric scales and mixing zone area were then obtained based. The formula clearly showed the constitutive relations between the affecting factors. Moreover, it also led to a standard curve formula describing the boundary of the pollutant mixing zone. The results were proved by the data of the simultaneous monitoring of both the water environment and the hydrology/water quality pollution load carried out by Huang Z L, et al. (2006) in the Three Gorges of the Yangtze River in China, before the dam and reservoir were built. The predicted pollutant mixing zone boundary curve agreed very well with the measured fields near the discharging exit of the Fuling Phosphate Fertilizer Factory. Discrepancy, however, appeared in predicting the pollutant mixing zone near the municipal sewage outfall of Huangshaxi City by the Yangtze River. The difference was due to the variant lateral diffusion coefficient during the transport of pollutant near Huangshaxi City municipal sewage outfall, rather than the constant assumption used in the method: the shallows on the shore near the outfall, as where the beginning of the diffusion happened, were dominant by small-scale vortices which resulted in smaller diffusion coefficient; as the diffusion cloud moved further from the bank and became bigger, the affects of larger-scale vortices were enhanced thus the diffusion coefficient became larger correspondingly. In this paper, we developed an analytical method for pollutant mixing zone calculation for variant lateral diffusion under constant point source riverbank discharging condition. The simplified twodimensional advection-diffusion transport equation is solved to give the analytical solution of pollutant concentration fields. The solving procedures have been explored. The results provide analytical formula for geometric scales and mixing zone area, as well as the standard curve equation for the boundary of pollutant mixing zone. The impact of variant lateral diffusion coefficient on pollutant mixing zone morphology was analyzed.

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PRINCIPLES AND METHODS Turbulence consists of vortices of various scales. Generally speaking, the large-scale vortices play the major role in the transport of momentum, mass and heat (XIA ZH.1982). The longer the pollutants being discharged from the outfall, the further they get diffused, which causes them more likely to be transported by the large-scale vortices in the main stream. Therefore, by assuming the river lateral diffusion coefficient being proportion to the diffusion distance x, the variant lateral diffusion coefficient can be written as follows (FISCHER H B, et al. 1979): α (1) E y ( x) = γ y x in which γy and αy are positive constants. Put the formula (1) into the simplified two-dimensional advection-diffusion equation, we have: y

U

2 ∂C α ∂ C =γ yx y ∂x ∂y 2

(2)

arrange formula (2) to get: γ y ∂ 2C ∂C = (1+α y ) 1 + α y ∂y 2 ∂x

U

(3)

let X = x (1+α ) , E = γ y (1 + α y ) , thence Formula (3) transforms into: y

U

∂C ∂ 2C =E 2 ∂X ∂y

(4)

According to FISCHER H B, et al. (1979), under the condition of the constant point source, the analytical solution of Formula (4) is: C ( X , y) =

m H πEUX

exp(−

Uy 2 ) 4 EX

(5)

put X, E into Formula (5) and simplified it to get: C ( x, y ) =

m H πU

1+α y

γ yx

(1+α y )

exp( −

(1 + α y )Uy 2 4γ y x

(1+α y )

)

(6)

in which x is the longitudinal direction along the river flow oriented from the sewage outfall; y is lateral direction perpendicular to x, pointing to the opposite shore of the outfall; m is discharge intensity with dimension [M/T]; U is the mean flow velocity in the mixing zone with dimension [L/T]; H is mean depth of mixing zone with dimension [L]. Formula (6) indicates that the lateral concentration of pollutants discharged from the river bank has semi-normal distribution. The maximum concentration near the bank (Cm) decays as the - (1 + α y ) 2 -th power of distance x and the concentration distribution variance is σ y 2 = 2γ y x (1+α ) [U (1 + α y )] . Assuming the summation of the background concentration (Cb) and the concentration allowed to increase caused by the pollutant discharge (Cd) is the standard concentration (Cs) in the water environmental function zone, we have Cd = Cs − Cb . Then the iso-concentration contour of Cd surrounding the region indicates the pollutant mixing zone. From Formula (6) we can deduce the formula for iso-concentration contours as the outer boundary of the pollutant mixing zone as: 1+ α y (1 + α y )Uy 2 m (7) Cd = exp(− ) (1+α ) (1+α ) H πU γ y x y 4γ y x y y

Let y=0 in Formula (7), theoretical formula for the maximum length of pollutant mixing zone is: 1 + α y m 2 /(1+α y ) (8) Ls = ( ) πUγ y HCd taking derivative of each term in both sides of formula (7) and let dy dx = 0 , we obtained the theoretical formula of the maximum width of pollutant mixing zone and its longitudinal coordinate:

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bs =

2γ y Ls

(1+α y )

(1 + α y )eU

=

−1 /(1+α y ) 2 m , Lc = Ls e πe HUCd

(9)

−1 Thus the positive constant (αy) in the variant lateral diffusion coefficient is α y = ln (Ls Lc ) −1. It can be determined onsite by the ratio of the corresponding coordinates of the maximum length and width of the pollutant mixing zone measured at the bank. Put Formula (8) and (9) into Formula (7), the contourcurve formula of the pollutant mixing zone outer boundary is obtained as follows:

x (1+α ) x (1+α ) y x (1+α ) x (1+α ) ( ) 2 = −e( ) y ln( ) y , or y = bs − e( ) y ln( ) y bs Ls Ls Ls Ls

(10)

Take definite integral of Formula (10) in x direction in the range of [0, Ls], formula for the area of the pollutant mixing zone is: S=

∫

Ls

0

bs − e (

x (1+α y ) x (1+α ) ) ln( ) y dx Ls Ls

(11)

substitute the variables as x L s = ζ and then η = ζ (3+α y ) 2 , simplify formula (11) and noticed 1 −1 ∫0 ln(η )dη = π 2 in table of integrals, the theoretical formula for pollutant mixing zone area will be: πe 2(1 + α y ) πe 2(1 + α y ) (12) S= Lsbs = µLsbs , µ = 3+αy 3+α y 3+αy 3+αy here μ is area coefficient that only decreases monotonically with the increasing of αy. The lateral diffusion coefficient will be a constant when αy=0. The maximum area coefficient μ = 0.795 is exactly the same as the results of WU Z H, et al. (2009) for constant lateral diffusion coefficient cases. RESULTS AND DISCUSSION It can be known from Formula (10) that the shape of pollutant mixing zone outer boundary as defined by the standard dimensionless iso-concentration curve is only determined by αy . The lateral diffusion coefficient is constant when αy=0. The corresponding longitudinal coordinate of the maximum width is Lc=Ls/e=0.368Ls. The standard curve equation and the calculated conditions are consistent with the results of WU Z H, et al. (2011). When αy =0.443, the corresponding longitudinal coordinate of the maximum width is Lc=0.50Ls. The widest section is in the middle of the pollutant mixing zone. When αy>0.443, the corresponding longitudinal coordinate of the maximum width is Lc=(0.50～1.0)Ls. The widest section is between the middle section and the end section. Plots of the dimensionless curve of pollutant mixing zone by riverbank discharge are shown in Figure 1 for αy=0, 0.5, 1, 2. Dimensionless lateral coordinate y /b s

1 0.8 αy=0 αy=0.5 αy=1 αy=2

0.6 0.4 0.2 0 0

0.2 0.4 0.6 0.8 Dimensionless longitudinal coordinate x /L s

1

FIGURE 1 Dimensionless curves show the shape of pollutant mixing zone by riverbank discharge

As can be seen from Figure 1, the shape of riverbank discharge pollutant mixing zone is semielliptical. When αy = 0, the shape is blunt near the outfall while gradually becoming sharper downstream. As αy increases, the region near the outfall becomes sharper while the downstream end gets blunter. Studies have shown that with the increase of the constant αy of variable lateral diffusion coefficient, the location of 80

Environmental Science & Technology 2014 Vol. 1 the maximum width of pollutant mixing zone moves downstream along the longitudinal coordinate Ls/e. This finding consists with our assumption that the further the diffusion distance, the greater the chances of pollutants got transported by large-scale vortices, thus the larger the lateral diffusion coefficient. The length-width ratio of the pollutant mixing zone by riverbank discharge can be described by the ratio between the maximum length and the maximum width of the pollutant mixing zone. The ratio can be obtained from formula (9): (1 + α y )eULs e(1 + α y ) Ls (13) bs

=

2γ y Ls

αy

=

2

Pe

α here E L = γ y Ls is the characteristic lateral diffusion coefficients. Pe = ULs E Ls is the Peclet number physically represents the ratio of the longitudinal advection and the lateral diffusion of materials. Formula (13) shows that the length-width ratio of the pollutant mixing zone by bank discharge is proportional to (Pe)1/2. When the longitudinal advection effect is stronger than the lateral diffusion, the length-width ratio of the pollutant mixing zone is larger. Thus the pollutant mixing zone presents a long and narrow shape. WU Z H, et al.(2011) observed the pollutant mixing zone in the outfall’s by one starchy factory in Guangfu river. Using the theory obtained above, αy=0 and the lateral diffusion coefficient Ey=constant γy=0.27 m2/s, the pollutant mixing zone of this starch factory can be described by the standard curve equation based on formula (10) as follows: 2  y x  x (14)   = −e ln   5 32  32  HUANG Z L, et al. (2006) provided the concentration filled contours of NH3-N measured in Yangtze River at Huangshaxi outfall in dry season (shown in figure 2) The measured maximum length, maximum width and its corresponding longitudinal coordinate of pollutant mixing zone are given in Table 1 for concentration of NH3-N being 0.33, 0.40 and 0.50mg/L. y

s

FIGURE 2 Concentration filled contours of NH3-N measured in Huangshaxi outfall during dry season. Outer boundaries predicted by this study are also plotted. TABLE 1 Sewage pollutant mixing zone characteristic parameters and lateral diffusion coefficient of Huangshaxi outfall Iso-concentration Max. length Max. width Longitudinal Area S/m2 ELs/(m2s-1) Items Value Ls/m bs/m coordinate Lc/m ----0.33 269.7 120.0 204.8 Measured 0.40 204.8 75.0 126.5 ----values 0.50 112.7 45.3 73.0 ----0.33 271.4 116.7 186.6 21193.3 136.6 Theoretical 0.40 196.7 75.0 135.3 9871.5 74.7 fitted values 0.50 112.7 43.4 77.5 3272.9 30.3

The mean flow velocity is 0.75, 0.72 and 0.50 m/s for NH3-N=0.33, 0.40 and 0.50mg/L respectively, calculated based on the measured cross-section velocity distribution in sewage mixing zone of Huangshaxi. Using the theoretical formula obtained above, the calculation formula for the variant lateral diffusion coefficients of the Huangshaxi outfall when αy=1.67, γy=0.0114 is (in metric units): α (15) E y = γ y x y = 0.0114x 1.67 81

Environmental Science & Technology 2014 Vol. 1 Put αy=1.67 into Formula (10), we can obtain the standard curve equation of the outer boundary of the pollutant-mixing zone of Huangshaxi outfall shown in Figure 2 as filled contours. y x x (16) ( ) 2 = − e( ) 2.67 ln( ) 2.67 bs Ls Ls Ls and bs here are fitted values for the maximum length and maximum width. The theoretical curves of three pollutant mixing zones boundaries predicted by Formula (16) are also shown in Figure 2. CONCLUSIONS (1) We proposed the analytical solution of the simplified two-dimensional transport equation for the pollutant concentration distribution in riverbank discharge cases under variant lateral diffusion coefficient condition. The theoretical formulas for the maximum length, maximum width and its corresponding longitudinal coordinate, as well as the area of the pollutant mixing zone are obtained. (2) Shape of the pollutant mixing zone in the riverbank discharging cases only depends on the constant αy defining the variant lateral diffusion coefficients. The lateral diffusion coefficient is constant when αy=0. The standard curve equation in dimensionless form of the pollutant mixing zone’s outer boundary we deduced has simple form and is convenient and practical. (3) The length-width ratio of the pollutant mixing zone in riverbank discharge is proportional to (Pe)1/2. The larger the Peclet number is, the longer and narrower the pollutant mixing zone is. ACKNOWLEDGEMENTS This research is supported by the National Natural Science Foundation of China (51379097). REFERENCES FISCHER H B, IMBERGER J, LIST E J, et al. 1979. Mixing in inland and coastal waters. Academic Press, New York, NY. HUANG Zhen-li, LI Yu-liang, CHEN Yong-can, et al. 2006. Water quality prediction and water environmental carrying capacity calculation for Three Gorges reservoir. China Water Resources and Hydropower Press, 168-177, Beijing, China. Idaho Department of Environmental Quality. 2008. Mixing Zone Technical Procedures Manual (DRAFT). Idaho Department of Environmental Quality, Boise, USA. WU Zhou-hu, JIA Hong-yu. 2009. Analytic method for pollutant mixing zone in river. Advances in Water Science, 20(4): 544-548. (in Chinese). WU Zhou-hu, WU Wen, WU Gui-zhi. 2011. Calculation Method of Lateral and Vertical Diffusion Coefficients in Wide Straight Rivers and Reservoirs. Journal of Computers, 6(6):1102-1109. XIA Zhen-huan. 1982. Turbulence mechanics. Hydraulic Engineering Department of Tsinghua University, Beijing, China. ZHANG Yong-liang, LI Yu-liang. 1993. A guide to analytical solution of pollutant mixing zone. Ocean Press, Beijing, China.

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EFFECT OF TEXTILE EFFLUENT ON GERMINATION AND GROWTH OF GRAMS Monika Chandel, S.K. Tank (Department of Biosciences, Veer Narmad South Gujarat University, Surat, Gujarat, India) ABSTRACT: Surat is located at 21.17 N latitude and 72.8300 E longitude. There are more than 500 textile industries involved in dyeing and printing in Surat city which generates lot of effluent. The textile industry waste is one of the most toxic and pollute water resources. Not only the amount of water which is being used by the textile industry gets polluted but also the effluent which is fed into the water bodies pollutes the surface water. The present study focuses on the dreadful effects of textile waste water on germination and growth of Chickpea. The different concentration of effluent was taken [20%, 40%, 60%, 80%] and seeds were grown. In lower concentration the germination ratio and growth are relatively higher than the control, but gradual decrease in the germination of seeds, seedling growth with increase in effluent concentration was observed. The best germination and seedling growth was observed in 20% concentration with growth promoting effect, and significantly better than control. The effect on root and shoot length were observed and on the overall growth along with secondary root emergence and branches. Thus the textile mill effluent can be safely used for irrigation purposes with proper treatment and dilution at 20%. Key Words. Textile Effluent, Grams, Growth , Germination, Toxicity. INTRODUCTION Increasing pollution of natural waters with waste effluents arising from various industries has become serious problem in Surat, as textile industrial growth and development have been on the increase. In Gujarat diamond and textile industry represent an important economic sector. Surat is located at 21.17 N latitude and 72.8300 E longitude. There are more than 500 textile industries involved in dyeing and printing in Surat city which generates lot of effluent. Due to the nature of its operations which requires large amount of water, most of the waste generated ends up in the nearby Pandesara khadi (water stream) thereby altering its natural state as regard quality. Industrial effluents are undesired by-products of economic development and technological advancement. When such wastes are improperly discharged off, they imperil human health and the surrounding environment. Effluents from textile industries are complex mixtures of chemicals varying in quantity and quality. These industries generate both organic and inorganic waste mixed with waste waters from the production process, which leads to change in both biological and chemical parameters of the receiving water bodies. Now the industries are well developed and a large number of small textile processing units are scattered all over the country. Wet processes like bleaching, dyeing and screen printing are being carried out by these industries. Textile processes requires large volumes of fresh water after the cloth processing operations. The wastewater volume varies from mill to mill. The combined wastewater volume from Indian textile mills lies in the range of 86 to 247 liters with an average 172 liter per kg of cloth produced. Their effluents constitute a major part of the total industrial effluents in India. On an industrial scale the effluents resulting from the dyeing and printing operations of textile mills are managed through primary or secondary wastewater treatment. Whatever the pollution source may be, soils can act as a sink of heavy metals but three main kinds of ecological risks are associated to this fact are: • the loss of productivity in the soil compartment, • the pollution of ground-water due to metal leaching, and • the accumulation of pollutants in food-chain, with effects on vegetation and animals, including humans In India, the abundance of soils with low organic matter content, favours the use of industrial wastewaters containing organic matter as an organic amendment and nutrient supply to soil. Although the benefits of wastewater use in irrigation are numerous but precautions should be taken to avoid short and long-term environmental risks related. Earlier studies have shown that the effect of an industrial effluent 83

Environmental Science & Technology 2014 Vol. 1 vary from crop to crop. So it is essential to study the effect of industrial effluents on individual crops before their use in agricultural fields. MATERIALS AND METHODS Sample Collection and Treatment. Water sample were collected from textile industry in Surat city from Pandesara region, into clean plastic containers. The water sample was immediately evaluated in its crude natural state for physiochemical variables. Seeds of chickpea were obtained and used for study. Seeds were planted on loam soil in pots. The soil was kept moist by adding water when necessary. Seeds Treatment. Chickpea seeds were subjected to sterilization before planting so that they become free of any fungal infection. They were sterilized with 0.01% solution of mercury chloride for 1 minute and then washed under running tap water for 2 to 3 minutes and then with distill water twice for 3minutes.Seedlings were then soaked in different concentration of textile effluent 0%, 20%, 40%, 60% and 80% respectively for 24 hours. These seedlings were then transferred to pots containing similar concentrations of effluent. They were allowed to grow for 15 days after germination to enable them attain an appreciable height range of 15 to 20 cm. Five germplasm were taken for study and each individual were observed for germination. The effluent water sample were provided as and when necessary but equally to all germplasm in all the concentration and control plants received equal amount of water devoid of effluent. At the end of the treatment period, plants were harvested and various parameters were evaluated. All analyses were replicated 4 times unless otherwise stated. Root Growth Determination. Uprooted plants were thoroughly washed with clean water and the main root length was measured. Also, root architecture was visually examined. Dry Weight Determination. Harvested plants were washed thoroughly in a running tap water to remove soil particles. After rinsing with distilled water, they were placed in labeled paper bags and oven dried at 80°C for 72 hours. The dried samples were weighed using a digital top loading weighing balance to determine the dry weight. Growth inhibition was measured in relation to the control mean: % inhibition = 100 × 1- ‫ ג‬treated ‫ ג‬control RESULTS Physicochemical Characteristics of the Water Sample. The results of the physicochemical variables of the water sample are as shown in Table 1 together with the limit values accepted by the regulatory authority. The water samples Fe and Pb levels were found to be higher than the reference standards, hence violating the discharge limits. Growth. The effects of the treated textile effluent on the root growth of chickpea are shown in Photo1, Figure 1 and Figure 2. The root growth of Grams was markedly affected by the textile treated effluent. At the end of the experiment period, the control plants showed a primary root length of 110 mm while the treated plants had a mean value of 70mm, a difference that was significant. There was marked difference in the root architecture between the control plants and those that received treated effluents. The roots of control plants appeared thicker with more numerous lateral roots compared to the treated plants. The dry weight data clearly showed that treated effluent had significant inhibitory effect on Grams as treated plants accumulated less biomass compared to the control plants. The treated effluent caused 57% growth inhibition in 40% effluent (Wins et al., 2010) relative to the control plants. It was observed that in 20% effluent seeds 84

Environmental Science & Technology 2014 Vol. 1 showed delay in germination but after few days there was sudden increase in germination (Panaskar et al., 2011) and also in growth. Seeds germinated in 100% effluents but did not survive for longer period (Garg et al., 2008). TABLE 1. Characteristics of the water sample from Pandesara Khadi polluted with treated effluent from a textile industry compared with WHO standards S/N 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.

Parameters

Mean levels detected

Temperature Colour pH Total solids Total Suspended Solid Total Dissolved Solid Aluminium Cadmium Chromium Copper Iron Lead Nickel Zinc

CONTROL 0% EFFLUENT

29°C Reddish Brown 6.7 3810 mg/l 2240 mg/l 1570 mg/l 0.20 mg/l 0.196 mg/l 0.181 mg/l 0.113 mg/l 37.266 mg/l 2.13 mg/l 0.869 mg/l 0.248 mg/l

20 % EFFLUENT

WHO standards 7 to 8.5 1500 mg/l 1mg/l 0.005mg/l 0.05mg/l 1mg/l 0.3mg/l 0.1mg/l 0.1mg/l 5.0mg/l

40 % EFFLUENT

PHOTO 1. Control and Experimental Samples

DISCUSSION The present study demonstrate that treated textile effluent water sample affected growth and biomass and also photosynthetic pigments and also many other biochemical reactions occurring in seedlings during germination process. The results imply that treated textile effluent cause biotoxicity on organisms. These effects could be the result of high salt content and heavy metals in the treated textile effluent. For clarification the textile effluent was analyzed for various physicochemical parameters and was found that it contains high concentrations of Fe and Pb and the total solid content was far above the recommended standards. These studies are of immense importance because these waters are used for agricultural and 85

Environmental Science & Technology 2014 Vol. 1 domestic purposes. The study proves that the treated textile effluent which is directly fed into water streams is not safe for use in agriculture and other household domestic purposes.

140 120

Length (mm)

100 80

Control

60

20%effluent

40 40%effluent

20 0 2 day 4day 6day 8day 10day 12day 14day Days

FIGURE 1. Graph showing Root length Vs. Number of days

300

Length (mm)

250 200 150

Control

100

20%effluent

50

40%effluent

0 2day 4day 6day 8day 10day 12day 14day Days

FIGURE 2. Graph showing Shoot Length Vs. Number of days

No. of seeds germinated

6 5 4

Control

3

20% Effluent 40%Effluent

2

60%Effluent 1

80%Effluent

0 1day

2day

3day

4day

5day

No. of Days

FIGURE 3. Graph showing No. of Seed Germination Vs No. of Days 86


CONCLUSION The data obtained from this study indicated that the treated effluents from the textile industry as they are directly discharged into the water stream contain toxic compounds. These compounds contaminate the surface water, thereby making it unfit for irrigation and drinking. Therefore proper treatment of effluent water and enforcement of pollution control by the regulatory authority on the discharge of textile waste water into water streams should be done. The ecological and human health safety of continual discharge of this textile effluents into water streams are undoubtedly under threat. The present study focuses on treatment of textile wastewater and properly treated water in particular concentration can be used for irrigation purpose (Hali R., et al., 2012) and would be helpful to farmers in a country like India were it could solve 50% of the irrigation problems. REFERENCES Garg V., K., Kaushik P. 2008. “Influence Of Textile Mill Wastewater Irrigation On The Growth Of Sorghum Cultivars.”Applied Ecology and Environment Research 6(2): 1-12. Panaskar D., B., and Pawar R., S. 2011. “Effect Of Textile Mill Effluent On Growth Of Vigna Unguiculata And Pisum Sativum Seedlings.” Indian Journal of Science and Technology 4(2): 266-272. Wins A., Murugan M. 2010. “Effect Of Textile Mill Effluent On Growth And Germination Of Black GramVigna mungo (l.) Hepper.” International Journal of Pharma and Biosciences 1(1): 1-7. Hali R., Malaviya P., Sharma N. 2012. “Impact Of Dyeing Industry Effluent On Germination And Grwth Of Pea (Pisum sativum).” Journal of Environmental Biology 33:1075-1078.

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MONITORING OF CYANOTOXIN AND T&O COMPOUND PRODUCING CYANOBACTERIA IN DRINKING WATER RESERVOIRS USING QPCR METHOD Y.-T. Chiu, S.-L. Lin, Tsair-Fuh Lin* (National Cheng Kung University, Tainan City, Taiwan), H.-.K. Yen (Meiho University, Pingdong, Taiwan) Cyanobacteria are a group of microorganisms present in many drinking water sources around the world. As some of the microorganisms are producers of cyanotoxins, such as microcystins (MCY) and cylindrospermopsin (CYN), and taste and odor (T&O) compounds, such as 2-methylisoborneol (2-MIB) and trans-1,10-dimethyl-trans-9-decalol (geosmin), presence of toxin- and odorant-producing cyanobacteria may pose additional health risk and aesthetic issues for people. Therefore, quantification of cyanotoxins, T&O compounds and the producing species in water sources is necessary for proper management of drinking supplies. Conventionally, microscopy, gas chromatograph, and liquid chromatograph are employed to determine the producing species, T&O compounds, and cyanotoxins, respectively. However, these methods require experienced personnel, sophisticated instrumentation, and/or long turn-around time. Compared to the conventional methods, bio-molecular methods, such as quantitative polymerase chain reaction (qPCR), may provide the information of functional gene concentrations of targeted cyanobacterial metabolites in short time, offering additional information and time for the management of water supplies. In this study, a qPCR based method was developed for the quantification of MCY, CYN, geosmin and 2-MIB producing cyanobacteria present in drinking water sources in Taiwan. Primer and probe sets were first designed and tested with isolated cyanobacteria species, including producers and non-producers of the targeted metabolites. The designed primer/probe sets were proved to be able to quantify producers of the targeted cyanotoxins and T&O compounds in fortified natural water. Then, the method was applied in quantifying the toxin- and odorant-producing species in 38 drinking water reservoirs in Taiwan. The qPCR data obtained in the reservoir samples were compared with cyanotoxins and T&O compound concentrations measured with the conventional methods. Good correlations between the concentrations of the producers and corresponding toxins or T&O compounds were obtained. The results indicate that the qPCR based approach may offer a quick and specific detection method for the monitoring of cyanotoxin and T&O compound producing cyanobacteria in water sources.

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A Novel Flow-cell for in situ Spectrophotometric Detection of Contaminants in Water Samples Emanuele Reggiani, Richard Bellerby, Kai Sørensen (Norwegian institute for water reasearch, NIVA, Norway) A flow-cell for automated water sampling and spectrophotometric analysis has been designed and fabricated. The PTFA flowcell features 8ml sampling volume, up to 80mm light-path, possibility to feed the cuvette with two different light sources. A set of reagents may be injected and stirring is possible through an embedded magnetic flea. Temperature of the sample is continuosly monitored by a mini glassencapsulated thermistor, and can be adjusted by a miniature silicon heating pad. Water inlet and outlet are protected against backflow through low-pressure stop-valves. The cuvette features also fittings for PMMA fiber optic sensors that will be developed in the future. The cuvette has been tested in a fully unattended mode supported by custom electronics during seawater pH monitoring campaigns, aiming to early detect, with extreme precision, very small changes in ocean biogeochemistry in proximity of CO2 storage sites.

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A MICROFLUIDIC COLORIMETRIC ANALYSER FOR PH IN WATER John Cleary, Deirdre Cogan, Thomas Phelan, Kamil Jankowski and Dermot Diamond (Dublin City University, Dublin, Ireland) This paper describes the latest stage in the development of a microfluidic platform for autonomous monitoring of environmental water quality. The current project focusses on developing and integrating colorimetric methods for pH and in order to provide a low cost, autonomous monitoring system for this important water quality parameter. pH measures the acidity or basicity of water. Most aquatic animals are adapted to a range of 6.5–8.0 (close to neutral, pH 7.0). Low pH can also allow toxic substances such as ammonia to become more available for uptake by aquatic plants and animals, greatly increasing their effective toxicity. pH is commonly measured in industrial and municipal wastewaters as well as in monitoring of drinking water, of surface waters such as rivers and lakes, and in many industrial processes. The pH analyser which has been developed can be deployed in online or autonomous modes, and utilises a combination of microfluidic technology, colorimetric reagent chemistry, LED and photodiodebased optical detection systems; and wireless communications. pH is measured using a mixture of colorimetric pH indicators, optimised to give a response over the pH range 4.0–10.0, which covers the range of pH values commonly encountered in monitoring of surface waters, drinking water and many wastewaters. Dual LED light sources and a single photodiode detector are used to measure light absorbance at appropriate wavelengths (430 and 570 nm). Results from laboratory and field testing of the pH analyser will be presented.

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SUSTAINING SAFE DRINKING WATER SUPPLY IN DEVELOPING COUNTRIES: LEBANON CASE STUDY Mey Jurdi (American University of Beirut, Beirut Lebanon) Sami Ramia (American University of Beirut) Samira Korfali (Lebanese American University, Beirut, Lebanon), Rola Ajib, Sara Chehab and Aya Issa (American University of Beirut) The provision of sustainable access to safe drinking water and improved sanitation is one of the time bounded targets of the Millennium Development Goal 7 that aims through the Water for Life Decade (20052015) to cut in half the proportion of people without sustainable access to safe drinking water and improved sanitation. On March 2012, at the 6th World Water Forum, the UN Water announced that the water supply target to reduce by half the global population with no access to improved water sources has been met; still the major challenge for developing countries remains ensuring that sustainable quantities (Basic Water Requirements) are accessible and determining the quality and safety of the water supplies. In Lebanon achieving this goal is not mostly challenged by the coverage of the piped water distribution network, but by the quality and sustainability of the provided service. The intermittent distribution of the piped water supply, the deficient quality and quality monitoring and quality control leads to lack of trust in the provided service and impacts domestic water use. This consequently results in heavy dependence on complementary water sources (private wells, water springs, bottled water, vended water and cistern water) of unsafe and mostly undetermined water quality. Results of the study emphasize that the provision of sustainable access to safe domestic water supply is challenged by the type and quality of the provided service; the intermittent distribution of the piped water supply, the prevailing quality and quality control measures, deficient quality monitoring, nonexistent water safety plans and the lack of trust that leads to heavy dependence on unsafe complementary water sources. Results also reflect on wide variability in the quality of piped water supplies that vary in physical, chemical and microbiological quality and reflect mostly on exposure to major sources of pollution specifically sewage, leachate of solid waste dump sites, agriculture run off and industrial solid waste and wastewater effluents. Additionally, the condition of water reservoirs and distribution networks contributes to the water contamination profile mainly due to the corrosion of the old poorly maintained networks and the resulting sewage infiltration. As such, the management of the quality of water supply is a challenging task in the absence of sufficient technical and financial resources. What is more important is the will to commit to this process under the prevailing administrative bureaucratic system. Still, insuring the quality and safety of the water supply is a must and all efforts should be channeled to achieve this objective.

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BIOLOGICAL DESALINATION OF SEAWATER USING MARIN MICROALGA Scenedesmus sp. and Chlorella vulgaris E. Sahle-Demessie, Ashraf Aly Hassan, Amy Zhao (U.S. EPA, Office of Research and Development, NRMRL, 26 W. Martin Luther King Drive, Cincinnati, OH 45268, UA) With the increasing water demand and the scarcity of renewable natural water resources, desalination of seawater has become essential in providing water requirements especially in dry regions. Seawater desalination technology requires a large amount of energy which is typically generated from fossil fuels. The combustion of fossil fuels emits greenhouse gases and, is implicated in climate change. However, there are various types of algae or macrophytes which sequester the salts in their bodies and remove them from solution. Biological mechanisms to remove sodium chloride (NaCl) from seawater using halophytes algae are investigated. Various halophyte micro or macro-algae are screened and selected based on the degree of salt tolerance, transportation rates, biomass production, nutrient requirements, ease of propagation and lipid yield of the biomass. Two types of algae namely; Scenedesmus sp. and Chlorella vulgaris have proven this concept and showed salt removal up to 30%. Salts are accumulated within the cell for the species of Chlorella autotrophica as part of the osmoregulatory physiology of the cells. Removal of salinity was observed based on conductivity measurements in both species and all media types. Growth was examined under different salt types, salt concentrations and nutrient types. The effect of environmental conditions (including salinity) on chemical and physical cell-wall properties were analyzed and optimum condition were develop a controllable cell-aggregation protocol to facilitate rapid removal of the halophytes from the desalted water.

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ANALYSIS FOR ATMOSPHERIC WATER FOR DRINKING Qing XIA and Shu GENG (School of Environment and Energy, Peking University, China) Condensed atmospheric water could be used as drinking water resource. Atmospheric water samples were collected in six different areas of Shenzhen, China: industrial area, commercial area, road, residential area, green land, and school. Following chemistry of atmospheric water were investigated: electrical conductivity (EC), pH, six anions (F−, Cl−, NO2−, NO3−, SO42−, PO43−), five cations (Na+, NH4+, K+, Mg2+, Ca2+), total organic carbon (TOC), total bacterial count, and nine trace metals (Cr, Mn, Ni, Cu, Zn, As, Se, Cd, Pb). Results of quality analyses met drinking water standards in China, and European Commission, except NO2− and total bacterial count. After filtration treatment, all indicators for water quality were better than drinking water standards and even tap water. The potential of using atmospheric moisture as drinking water resource will be discussed in this presentation.

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SOURCE WATER PROTECTION FOR DRINKING WATER PRODUCTION: A EUROPEAN RIVER MEMORANDUM Peter G. Stoks1 and Ina Brüning2 (1. Association of Rhine Water works RIWA, Groenendael 6, 3439 LV Nieuwegein, The Netherlands; 2. International Association of Water works in the Rhine Basin IAWR, Himmelgeister Landstrasse 1, 40589 Düsseldorf, Germany) From the seventies of last century the waterworks along the Rhine river in Europe (International Association of Waterworks in the Rhine basin, IAWR) have been active in the improvement of the Rhine water quality. The ultimate goal has always been a source water quality that allows the production of perfect drinking water using simple treatment only. This view has also been adopted by the International Rhine Commission ICPR. Already in 1973 IAWR published a Rhine Memorandum stating quality demands that would help reach that goal. Interestingly, those very demands were subsequently used by the European Union as the basis of a Directive on the abstraction of surface water for dinking water production (75/440/EC). Several updates of this memorandum were published over the years. In 2008 other associations of water works, along the Danube and the Meuse, also endorsed the underlying philosophy and the memorandum was broadened to the Danube-, Meuse- and Rhine Memorandum. The Commissioner of DG Environment in the EU, when confronted with this memorandum suggested to include more European rivers used for drinking water production and in 2013 the European River Memorandum was published, representing over 170 utilities in 17 European countries, with well over 115 million consumers. The most important aspects of this memorandum are quality objectives for not otherwise regulated variables as groups, and demands and suggestions to (political) decision makers on the achievement of the desired water quality based on the preautionary approach. A distinction is made between pollutants that show biological activity (such as, e.g. pharmaceuticals or biocides) as well as pollutants for which such information is not currently available (such as many metabolites and degradation products) and other pollutants. The former type of pollutants should not exceed 0.1 ug/L in the source waters, the latter group should not exceed 1 ug/L. A motivation based on scientific criteria for these demands and objectives is also given. The ICPR has recently reconfirmed its former statement that the Rhine should, ultimately, allow drinking water production using simple treatment and in the Netherlands some of the approaches stated in this memorandum have already been incorporated into legislation.

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COMMUNITY WATER SUPPLY AND TREATMENT PROJECT IN CAMEROON: CHLORINATOR DESIGN AND DEVELOPMENT Kristen Chorney* and Sam Miller** (Wilkes University, Wilkes-Barre, PA, USA) During May 2013, a team from Wilkes University and the University of Pennsylvania’s chapter of Engineers Without Borders visited The Ngyen-Mbo and Bome Spring Distribution System. This system supplies drinking water to the people of the Bome Valley in the Northwestern region in Cameroon. Years of neglect left the water contaminated with sediment and pathogenic microorganisms contributing to health problems in the surrounding area. The team of students and local workers did maintenance on the system to clean it and water testing was conducted. Based on the results of these tests, a water treatment system was chosen to improve the quality of the water. This system is the CTI 8 Chlorinator. At Wilkes University, a model of the chlorinator was built and tested. Aqua Chem® chlorine tablets were used as the source for chlorine. The chlorinator was tested at different flow rates and a new chlorine tablet was used during each trial. These tablets were weighed before and after testing to obtain a dissolving rate of the tablet. The flow rates were 2.4 gal/min, 0.92 gal/min, and 0.72 gal/min. Results indicate that larger flowrates hinder dissolution of chlorine in the chlorinator as it provides lesser reaction time. It was concluded that when the flow rate is too high (greater than 2.4 gal/min) there is not enough time for the chlorine to properly dissolve in the chlorinator. During moderate to slow flow rates, the residual chlorine concentrations fluctuated, but were generally at safe levels. Initial results indicate that the designed chlorinator has the potential to offer a practical solution to providing potable water in many of the underdeveloped communities across the globe. Results and a discussion of the study will be presented in detail in the poster.

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VULNERABILITY ASSESSMENT OF SMALL COMMUNITY WATER SYSTEMS IN PUERTO RICO Adaíl Alicea-Martínez, Rafael A. Rios (University of Puerto Rico, Río Piedras Campus, San Juan, Puerto Rico, USA) In Puerto Rico, about 3% of the population (about 125,000 persons) gets its drinking water from approximately 250 small community water systems. This community water systems began their life in the 1950’s in the rural parts of the island because there was no public aqueducts in these remote and mountainous parts. These aqueducts were very simple and rudimentary in design but at the present time have fairly advanced methods of distribution, storage and treatment (disinfection) but the topographical conditions remain basically the same. The remote location of these aqueducts together with the threat of hurricanes, tropical storms and earthquakes characteristic of Puerto Rico’s location in the Caribbean requires a vulnerability assessment of these systems to minimize damage in the eventuality of these and other events such as terrorism acts. The objective of this study was to assess both the vulnerability (probability of damage) and criticality (if damage occurs, what is its impact on functionality) of 40 community water systems using a methodology, developed by the authors specific for these systems. The purpose of the study was to determine the degree of vulnerability and what can be done to minimize it in the event of a natural or man made disaster. An emergency response plan was developed for each system. A scale from 0 (very low risk) to 30 points (very high risk) was used for both vulnerability and criticality. The results showed that the majority of the systems had high risk value for vulnerability and criticality. However, an analysis of the results showed that the methodology failed to take into account factors such as economic means of the community and its members, number of persons served and the management capabilities of the system which may have flawed the absolute value of the criticality and vulnerability of each individual system.

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AN INDEPENDENT INVESTIGATION INTO THE PHYSICO-CHEMICAL PURIFICATION CAPACITY OF GRAVITY FED HOME WATER TREATMENT DEVICES SUPPLIED IN SOUTH AFRICA Cherie Ann Kruger, Tobias George Barnard* and Natasha Hodgkinson (Water and Health Research Centre, University of Johannesburg, Doornfontein, South Africa), Cathleen Bartie (Immunology, NHLS, Constitution Hill, South Africa) Recent outbreaks of cholera and other waterborne diseases in Southern Africa have resulted in a public perception that tap water is not safe for drinking purposes (Lang, 2007). As a result, the use of gravity fed (jug and counter top) home water treatment devices (HWTDs) in the domestic and occupational setting is increasing rapidly (Ahammed and Meera, 2010; Kaiser, 2010). Most of these devices are sold over the counter and consumers buy these products in good faith on the basis of claims of their efficiency made during marketing and advertising campaigns, and with the expectation that the device will remove 90-100% of all harmful microorganisms (Berney et al., 2008; Varbanets et al., 2009). However, very often the claims made in the manufactures brochures are not substantiated by independent research (Fengyi et al., 2009). Thus a need existed for an independent exploratory study to evaluate a representative number of gravity fed HWTDs sold in South Africa against the claims that are made by their manufacturers and in sales brochures. This was done by sourcing a representative number of gravity fed HWTDs currently available on the market and testing them independently with physico-chemical (free chlorine, conductivity, pH, turbidity, TDS and particulate size exclusion) water contaminant testing listed in the “South African National Standards” (SANS) 241:2006 (Drinking Water) to the certification standards recommended by the United States of America, National Sanitation Foundation (NSF). A general pattern of results was observed within this study as the gravity fed HWTDs potentially did improve the water quality in terms of free chlorine removal, but in terms of conductivity, pH, turbidity, TDS and particulate size exclusion the devices tested performed rather poorly, reporting on average a less than 10% removal efficiency rate. The conclusive findings from this study suggest that gravity fed HWTDs sold in South Africa cannot adequately treat water to a level deemed safe for human consumption and requires further investigation.

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IMPROVING SURFACE WATER QUALITY OF AGRICULTURAL WATERSHED USING PLANNED INTERVENTION MICROWATERSHED APPROACH Durga D. Poudel* (University of Louisiana at Lafayette, Louisiana, USA) Nonpoint source pollution and water quality impairment is a major environmental problem worldwide. Most research studies on nonpoint source pollution are either at the field plot level or in a larger watershed level. Often water quality monitoring studies are done at a large watershed, and results are generalized. The Texas Institute for Applied Environmental Research (TiAER) at Tarleton State University, Texas, has developed the Planned Intervention Microwatershed Approach (PIMA) for addressing agricultural nonpoint source pollution. The TiAER defines a microwatershed as an area within a watershed, incorporating anywhere from 3,000 to 20,000 acres, with identifiable hydrologic boundaries. According to TiAER, by dealing with small areas, watershed coordinators can reduce landuse variables and more readily identify the sources of pollutant loads. In order to design and implement a microwatershed project in southwestern Louisiana, Vermilion Soil and Water Conservation District led an initiative for building cooperative partnership with landowners and homeowners, Louisiana Department of Agriculture and Forestry, USDA Natural Resource Conservation Service, Acadiana RC&D, Louisiana Department of Environmental Quality, Louisiana State University AgCenter, Louisiana Cooperative Extension Service, TiAER, University of Louisiana at Lafayette, USDA Farm Service Agency, Coulee Baton Gravity Drainage District, Vermilion Parish Police Jury, Gulf of Mexico Program, local agricultural enterprises and businesses, and Louisiana Department of Natural Resources. A plan for voluntary application of various conservation measures and Best Management Practices (BMPs) on the land by landowners and homeowners in addressing water quality problem of Coulee Baton Microwatershed was developed. As a part of the large-scale plan, a water quality monitoring study to assess surface water quality and to identify factors associated with the variability of surface water quality was launched in the Coulee Baton Microwatershed. Seven water quality monitoring sites were identified in the mcirowatershed. Field installation for monitoring included the installation of 6712 ISCO samplers, 4230 ISCO Bubble Flow Meters, 674 ISCO Rain Gauges with tipping bucket, solar panel, and battery. Water samples were collected for 66 rain events from September 24, 2009 to August 9, 2011. Laboratory determinations of water samples included TSS, BOD5, NO3-N, NO2-N, SRP, TP, TKN, Cl, Fl, SO4, and fecal coliform. Field measurements included the determination of temperature, DO, turbidity, conductivity, and pH using YSI Sonde. Dissolved oxygen level ranged between 1.2 mg/L to 14.1 mg/L, BOD5 level ranged between 2 mg/L to 40.1 mg/L, TS concentration ranged between 35 mg/L to 5,719 mg/L , and TDS concentration ranged between 56 mg/L to 4,356 mg/L. Turbidity values for the Coulee Baton microwatershed ranged between 4.23 NTU to 1,864.1 NTU. Fecal coliform count ranged between 400 MPN/100 mL to as high as 17 million MPN/100 mL. However, fecal coliform counts were reduced dramatically following the implementation of septic system installation project by Acadiana RC&D in the microwatershed. These results clearly indicate that there are heavy fluxes of pollutants in the microwatershed which are obviously related to landuse types and agricultural practices. Principal component and factor analyses resulted in sediments, dissolved substances, nutrients, temperature, and fecal matters as the major factors associated with surface water quality variability in this microwatershed. Watershed managers and researchers can utilize PIMA for developing a highly coordinated, multidisciplinary, and participatory water quality monitoring projects and BMPs implementation programs to improve surface water quality of agricultural watersheds.

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AN ANALYTICAL MODEL FOR POLLUTANTS TRANSPORT IN THE ROSETTA BRANCH OF THE NILE RIVER, EGYPT Mohamed Mostafa* and Robert W. Peters (University of Alabama at Birmingham, AL, USA) This research is being performed on the Rosetta branch of the Nile River, Egypt. The Rosetta branch receives pollution loadings from domestic, industrial, and agricultural activities which are located along its path. The primary objective of this research project is to develop an analytical model of Rosetta branch pollution using MATLAB software. This model can be used to predict water quality and assess the downstream distance affected by pollutant releases. Additionally, this model is considered a reliable tool for water quality management in affected areas. Water samples were collected along the Rosetta Branch, and from drains discharging into the Rosetta Branch to compare actual values with experimentally obtained. Water samples were analyzed for different parameters which include biochemical oxygen demand (BOD), chemical oxygen demand (COD), pH, total organic carbon (TOC), total dissolved solids (TDS), total suspended solids (TSS), dissolved oxygen (D.O.), and temperature. The main sources of pollution were studied to identify the most appropriate ways to reduce pollution and improve water quality in the Rosetta branch. El-Rahawy drain is the main source of pollution along the Rosetta branch, where it receives water from the Abu-Rawash and Zenen wastewater treatment plants (WWTPs). Wastewater from El-Rahawy drain contains an average COD concentration of about 270 mg/L and an average D.O. concentration of about 1.45 mg/L. The Abu-Rawash WWTP receives sewage exceeding the absorptive capacity of the plant. Therefore, excess sewage is discharged directly to ElRahawy drain without even primary treatment, which leads to increase water pollution in the Rosetta branch. This research addressed an attempt to improve Abu-Rawash WWTP effluent water quality by using aluminum chloride (AlCl3) with injections of carbon dioxide (CO2). Jar tests were performed to estimate the coagulant dosage required to reach acceptable treatment. Application of 0.6 mg/L of aluminum chloride with injection of CO2 reduced the COD concentration at El-Rahawy drain from 270.0 mg/L to 112.0 mg/L. Another approach involves discharging 780,000m3 of water daily from the Al-Buhairi Water Canal (flows perpendicular to El-Rahawy drain and parallel to the Rosetta branch) to El-Rahawy drain reduced the COD concentration at El-Rahawy drain from 112.0 mg/L to 80.0 mg/L and increased the D.O. concentration from 1.45 mg/L to 3.20 mg/L, which in turn will lead to improved water quality in the Rosetta branch.

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POLYCHLORINATED BIPHENYLS (PCBs) IN INDUSTRIAL AND MUNICIPAL EFFLUENTS: CONCENTRATIONS, CONGENER PROFILES, AND PARTITIONING ONTO PARTICULATES Aparna Balasubramani and Hanadi S. Rifai (University of Houston, Houston, TX, USA) Nathan L. Howell (West Texas A&M University, Canyon, TX, USA) ABSTRACT: The Houston Ship Channel (HSC) is one of the nation’s largest and most active ports with shipping, petrochemical facilities and refineries, along with other industrial activities that have historically used polychlorinated biphenyls (PCBs). Municipal and industrial wastewater discharges from these industries are presumed to be a source of PCBs into natural water systems. This study examined wastewater effluent samples that were collected from 16 different locations in the Houston area in the summer of 2009 to describe the magnitude and specificity of this source to the Galveston Bay Estuary. All 209 PCB congeners were quantified using high resolution gas chromatography/high resolution mass spectrometry (HRGC/HRMS) using the USEPA method 1668A. Various analyses examined the distributions of all 209 PCB congeners and homologs, the differences between the industrial and municipal effluents, and the distribution of PCBs between the dissolved and suspended phases. This study is the first to quantify all 209 PCB congeners in wastewater effluents in Houston, Texas and the results presented stress the need for a more rigorous approach for managing total PCBs since partitioning within the water column affects the truly dissolved concentration that is bioavailable to biota and organisms in the Channel. INTRODUCTION Polychlorinated biphenyls (PCBs) belong to the class of persistent organic pollutants (POPs) and are widely present in the environment. Due to their persistence, PCBs are found in almost all water bodies, which makes these compounds both an environmental concern and a human health concern (Breivik et al. 2004). Major sources of organic pollutants in the environment include aerial deposition, surface runoff, domestic and industrial wastewater effluents (Stevens et al. 2003). Previous studies (Barrick 1982, Eganhouse and Kaplan 1982, Shannon et al. 1977) have confirmed that another significant source of toxic contaminants like PCBs in the environment is treated effluents discharged from both wastewater treatment plants and industries. Characterization of PCBs from both industrial and municipal facilities has been described in a few studies in the literature, with the earliest being done in the Canadian lower Great Lakes by Shannon et al. (1977), in which they found that 66% removal of PCBs was observed in the secondary treatment of wastewater, and that the removal was mainly due to the settling of PCBs in sludge. Blanchard et al. (2004), Guo et al. (2009), and Pereira and Kuch (2005) have examined the distribution of a limited number of congeners and homologs in sewage sludge that was obtained from various urban and industrial wastewater treatment plants. Though various studies (Durell and Lizotte 1998, Rodenburg et al. 2011, Vogelsang et al. 2006) have addressed the presence of PCBs in wastewater effluents, there exists many data gaps with respect to the nature and character of PCBs being discharged into natural water systems. Hence, identifying these data gaps and determining the nature and character of PCBs discharged from this point source is very critical. In order to address the aforementioned gapl, this study characterized the concentrations and distribution of all 209 PCB congeners in effluents from 16 wastewater treatment plants and industrial facilities that discharge into the Houston Ship Channel (HSC) in Texas. The main objectives of monitoring the effluents were to determine the concentrations of all the 209 PCB congeners and homologs, and assess the differences in the congener signatures between the different types of effluents. The study also determined the distribution of PCBs between the dissolved and suspended phases and analyzed how organic carbon affected the partitioning of PCBs between the two phases. MATERIALS AND METHODS The samples were taken directly from six industries (I1, I2, I3, I4, I5, and I6), six municipal wastewater treatment plants (WWTP1, WWTP2, WWTP3, WWTP4, WWTP5, and WWTP6), two 100

Environmental Science & Technology 2014 Vol. 1 industrial wastewater treatment plants (O3, and O4), one refuse system (O1), and one special warehousing facility (O2), as close to the discharge point into the receiving stream as possible, (see FIGURE 2). The 16 outfalls were selected from a total of 26 potential PCB point source dischargers into the HSC based on their proximity to the HSC and PCB hot spots in water, sediment, or fish; nature of receiving stream; type of industry; the known history of spill events within the facility; and the rate of discharge relative to the receiving waters.

FIGURE 2. Location of the sampled effluent outfalls. High volume sampling was used to collect the samples whereby 200 liters of water for each sample was pumped through a pre-cleaned glass fiber filter containing a 1 µm filter then through a XAD2 resin contained in a stainless steel column. The mass retained on the filter was considered to be the suspended fraction, and the mass collected on the XAD2 resin was treated as the dissolved fraction. Also, for each of the samples, a separate grab sample was collected and analyzed for total suspended solids (TSS), dissolved organic carbon (DOC), and total organic carbon (TOC). All 209 PCB congeners were quantified using high resolution gas chromatography/high resolution mass spectrometry (HRGC/HRMS) using USEPA method 1668A (USEPA 1999). Each of the 17 samples (16 parent samples + 1 duplicate) consisted of 164 PCB analytes and hence, a large amount of data was generated, sorted, summed, visualized and statistically analyzed using Microsoft Excel 2007. RESULTS AND DISCUSSION PCB Congener Patterns. The number of detects obtained in both dissolved and suspended phases in the various effluents, percent detection, and congeners that exhibited maximum concentrations at each of the effluent outfalls is presented in TABLE 1. It can be observed from TABLE 1 that 12 out of the 17 effluent 101

Environmental Science & Technology 2014 Vol. 1 outfalls had greater than 50% detection in the dissolved matrix whereas only 7 out of the 17 effluent outfalls had greater than 50% detection in the suspended matrix. The congener PCB-008 was among the highest three congeners in 14 of the dissolved effluent samples whereas PCB-129/128/163 exhibited the highest concentration in 14 of the suspended effluent samples. TABLE 1. Number of detects and the three congeners that showed the maximum concentrations in the dissolved and suspended phases for all effluents. Facility

Number of detects Suspended Dissolved phase phase (>1µm)

%Detects Suspended Dissolved phase phase (>1µm)

Three highest concentration PCB analytes Dissolved phase

I1 I2

116 74

102 23

71 45

62 14

110/115, 52, 95 8, 4, 1

I3

77

83

47

51

11, 8, 44/47/65

I4

87

108

53

66

1, 8, 3

I5

99

84

60

51

4, 8, 11

I6

87

97

53

59

8, 4, 15

WWTP1

88

28

54

17

11, 4, 8

WWTP1-DUP WWTP2

85 64

29 2

52 39

18 1

8, 4, 11 4, 8, 1

WWTP3

103

72

63

44

11, 52, 20/28

WWTP4

61

40

37

24

11, 20/28, 31

WWTP5

106

66

65

40

11, 8, 18/30

WWTP6

83

47

51

29

8, 4, 11

O1

107

100

65

61

8, 4, 18/30

O2

114

101

70

62

8, 4, 18/30

O3

73

29

45

18

8, 4, 1

O4

89

62

54

38

4, 8, 11

Suspended phase (>1µm) 110/115, 129/138/163, 90/101/113 15, 209, 8 129/138/163, 110/115, 118 129/138/163, 153/168, 180/193 44/47/65, 61/70/74/76, 52 129/138/163, 110/115, 153/168 129/138/163, 153/168, 90/101/113 129/138/163, 90/101/113, 110/115 209 (all other NDs) 129/138/163, 11, 110/115 11, 129/138/163, 153/168 129/138/163, 153/168, 147/149 153/168, 129/138/163, 147/149 129/138/163, 153/168, 180/193 129/138/163, 61/70/74/76, 153/168 129/138/163, 90/101/113, 209 129/138/163, 147/149, 153/168

Total PCBs (∑209) and Homolog Concentrations. It can be seen from FIGURE 3 that the total PCB (∑209) concentration in the dissolved medium ranged from 1.01 ng/L to 8.12 ng/L whereas it ranged between 2.03 ng/L and 31.19 ng/L in the suspended medium. It was noted that the concentrations were relatively constant in industrial effluents whereas more variable in the municipal and other effluents in both the dissolved and suspended media. While municipal wastewater treatment plants did not have the highest concentration of total PCBs, they were the largest contributors to natural water systems because of the relatively larger volume of effluents discharged on a daily basis. PCB homolog concentrations at all the effluent outfalls were also analyzed to see if they followed any pattern like the total PCB (∑209) concentrations. It was observed that relatively high concentrations were exhibited by lower chlorinated homologs (mono-CBs through hexa-CBs) with dichlorobiphenyls exhibiting the highest concentration at most of the effluent outfalls. An interesting observation was that at one of the industrial wastewater treatment plant (O4) nonachlorobiphenyls peaked higher than octa-CBs and deca-CBs, which was different 102

Environmental Science & Technology 2014 Vol. 1 from what had been observed in a previous study (Guo et al. 2009), and this could be attributed to the fact that maybe the source and transport of PCBs into this wastewater treatment plant was different from the rest of the facilities.

FIGURE 3. Total PCBs (∑209) concentration at each of the effluent outfalls in the dissolved and suspended phase. (Non-detects = ½ MDL).

FIGURE 4. Suspended fraction in water at all the effluent outfalls plotted against log Kow obtained from 103

Environmental Science & Technology 2014 Vol. 1 Hawker and Connell (1988) for the detected concentrations in the suspended and dissolved phases. The distribution of TSS and TOC is also shown. Suspended Fraction Vs log Kow and Partitioning onto Particulates. The suspended fraction was calculated only for the detected concentrations in all the 17 effluent outfalls, by dividing the suspended concentration by the sum of dissolved and suspended concentration of the same congener. The suspended fraction values ranged from 0.0011 to 0.979 across the effluents, as seen in FIGURE 4. Although, as expected, the higher the log Kow, the higher the suspended fraction, it was observed that suspended fractions varied widely depending on the TSS and TOC concentrations at the outfalls (see FIGURE 4). High suspended fractions observed at the municipal wastewater treatment plants were due to the high TSS concentrations at these facilities, whereas high suspended fractions were noticed in the petrochemical industries when the TSS and TOC concentration at that outfall was similar. The major conclusion derived from this analysis was that though log Kow was a good indicator of the partitioning of PCBs, it alone was not sufficient to understand the partitioning of PCBs since it did not give any information about the level of TOC and/or TSS or the type of effluent stream, water quality indicators that determine the extent to which specific congeners are present predominantly in the dissolved or suspended phase. Hence, based on these results, the need for a detailed understanding of the role played by TSS and the various fractions of carbon in effluent outfalls to control the contamination of POPs in natural water systems is deemed to be critical. CONCLUSIONS Apart from being the first study to quantify all 209 PCB congeners in wastewater effluents in Houston, Texas, other interesting observations can be made. It was observed that total PCBs (∑209) concentrations in the suspended medium were four times higher than the total PCB (∑209) concentrations seen in the dissolved medium, and the difference in the concentrations seen at various plants confirmed that treatment levels affected the PCBs in dissolved and suspended media very differently. This difference could be because of the variable sourcing of PCBs in the influent or the actual treatment processes within the plants or the chemical make-up of the effluent (organic carbon fractions, TSS). It was also observed that lower chlorinated congeners dominated the homolog concentrations, with dichlorobiphenyls exhibiting the highest concentration at most of the outfalls. Lastly, it was noticed that suspended fractions of PCBs, for the same congener, varied widely amongst the different effluent outfalls, and the log Kow was not the only deciding factor for the suspended fraction and that other parameters like TSS, TOC, DOC, and POC played a very important role in the partitioning of PCBs. Hence, the results that were obtained from this study stress the importance for development of a more rigorous approach that includes understanding of the chemical make-up of effluent waters and their organic carbon fractions, because controlling total PCBs from a water quality standpoint alone is not sufficient to predict the impact of PCBs on biota in natural water systems. ACKNOWLEDGMENTS This research was funded by the Texas Commission on Environmental Quality (TCEQ), and the United Stated Environmental Protection Agency (USEPA). Their support is gratefully acknowledged. REFERENCES Barrick, R. C. (1982). "Flux of aliphatic and polycyclic aromatic-hydrocarbons to Central Puget Sound from Seatlle (Westpoint) primary sewage effluent." Environmental Science & Technology 16(10): 682-692. Blanchard, M., M. J. Teil, D. Ollivon, L. Legenti and M. Chevreuil (2004). "Polycyclic aromatic hydrocarbons and polychlorobiphenyls in wastewaters and sewage sludges from the Paris area (France)." Environmental Research 95(2): 184-197. Breivik, K., R. Alcock, Y.-F. Li, R. E. Bailey, H. Fiedler and J. M. Pacyna (2004). "Primary sources of selected POPs: regional and global scale emission inventories." Environmental Pollution 128: 3-16. Durell, G. S. and R. D. Lizotte (1998). "PCB Levels at 26 New York City and New Jersey WPCPs That Discharge to the New York/New Jersey Harbor Estuary." Environmental Science & Technology 32(8): 1022-1031. 104

Environmental Science & Technology 2014 Vol. 1 Eganhouse, R. P. and I. R. Kaplan (1982). "Extractable organic-matter in municipal wastewaters. 2. Hydrocarbons-molecular characterization." Environmental Science & Technology 16(9): 541-551. Guo, L., B. Zhang, K. Xiao, Q. H. Zhang and M. H. Zheng (2009). "Levels and distributions of polychlorinated biphenyls in sewage sludge of urban wastewater treatment plants." Journal of Environmental Sciences-China 21(4): 468-473. Hawker, D. W. and D. W. Connell (1988). "Octanol water partition-coefficients of polychlorinated biphenyl congeners." Environmental Science & Technology 22(4): 382-387. Pereira, M. D. and B. Kuch (2005). "Heavy metals, PCDD/F and PCB in sewage sludge samples from two wastewater treatment facilities in Rio de Janeiro State, Brazil." Chemosphere 60(7): 844-853. Rodenburg, L. A., S. Du, B. Xiao and D. E. Fennell (2011). "Source apportionment of polychlorinated biphenyls in the New York/New Jersey Harbor." Chemosphere 83(6): 792-798. Shannon, E. E., F. J. Ludwig and I. Valdmanis (1977). "Polychlorinated biphenyls (PCBs) in municipal wastewater: An assessment of the problem in the Canadian lower Great Lakes, Project No. 73-3-8." Environment Canada, Environmental Protection Service Research Program for the Abatement of Municipal Pollution within the Provisions of the Canada-Ontario Agreement on the Great Lakes Water Quality. Stevens, J. L., G. L. Northcott, G. A. Stern, G. T. Tomy and K. C. Jones (2003). "PAHs, PCBs, PCNs, organochlorine pesticides, synthetic musks, and polychlorinated n-alkanes in UK sewage sludge: Survey results and implications." Environmental Science & Technology 37(3): 462-467. USEPA (1999). "Method 1668, Revision A: Chlorinated Biphenyl Congeners in Water, Soil, Sediment, and Tissue by HRGC/HRMS." Washington, D.C: USEPA National Office: 133. Vogelsang, C., M. Grung, T. G. Jantsch, K. E. Tollefsen and H. Liltved (2006). "Occurrence and removal of selected organic micropollutants at mechanical, chemical and advanced wastewater treatment plants in Norway." Water Research 40(19): 3559-3570.

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CHARACTERISTICS OF OPTIMIZATION PROBLEMS FOR COASTAL GROUND WATER MANAGEMENT Karen Ricciardi (University of Massachusetts Boston, Boston, Massachusetts, USA) This research reveals the characteristics of optimization problems applied to coastal ground water management used as a source of fresh water. Coastal ground water aquifers generally consist of fresh water underlain by salt water. When this fresh water is extracted from the aquifer, the salt water is often drawn into the fresh water zone. If the salt water is drawn into the well, then the well is contaminated and can no longer be utilized as a source of fresh water. The movement of the fresh water- salt water interface in response to ground water extraction can be predicted using mathematical models that are solved using computationally intensive algorithms. In this research the ground water flow model MODFLOW coupled with the principles of the Ghyben-Herzberg approach are used to model the fresh water- salt water interface in a hypothetical model. This approach models the interface as a sharp front, and provides a conservative estimate of the interface response to ground water pumping. While this response is conservative, the nonlinear effects of the response are consistent with more complex models, and it is for this reason that this approach provides a means by which the characteristics of an optimization problem for coastal aquifer management can be analyzed. An optimization problem is formulated that examines the minimum risk of salt water intrusion into active pumping wells that supply a fixed amount of fresh water from a coastal aquifer. The management decisions in this problem include assigning pumping rates at available well locations throughout the aquifer. To analyze this optimization problem, a large number of management designs are randomly generated. For each design, the ground water model is used to predict the response of the aquifer to the design. Along with the pumping rates assigned to each well, the risk of salt water intrusion is recorded. The risk is quantified by the predicted proximity of the salt water interface to the well. Low risk designs are analyzed using a clustering algorithm to differentiate designs according to well activation. Each cluster is then analyzed using statistical measures. The results of this analysis reveal characteristics of the objective function that are particular challenges to solving optimization problems using traditional algorithms. This optimization problem is challenged with the presence of multiple locally optimal solutions that approximate piecewise linear features that are non-differentiable close to the local solutions. These results of this analysis are two-fold. By examining the solution space of the optimization problem in the proposed manner, for this problem a wide range of low risk management solutions for coastal aquifer management is revealed. These solutions are variable in the number of wells, the quantities of pumping from the wells and the location of the wells in the management design. If the globally optimal solution is desired, this research reveals characteristics of the objective function that are useful for predetermining the derivative free optimization algorithm and the parameters of that algorithm that will determine the global optimal in an efficient manner.

106


QUANTIFYING E. coli DISCHARGE FROM ONSITE SEWAGE FACILITIES IN THE DICKINSON BAYOU WATERSHED, TEXAS Derek Morrison1, Clyde Munster1, R. Karthikeyan1, John Jacob2 ( Texas A&M University, Department of Biological and Agricultural Engineering, College Station, TX 77843, USA; 2Texas A&M University, Texas Sea Grant, 1250 Bay Area Blvd., Suite C, Houston, TX 770058, USA) 1

Since 1996, the bacteria levels in Dickinson Bayou have been considerably higher than the state limit of 126 bacteria / 100 mL for recreational waters. One hypothesis is that failing onsite sewage facilities (OSSFs) in the nearby residential areas are causing an increase of E. coli concentrations in Dickinson Bayou. Three water quality monitoring stations were installed in Dickinson Bayou to quantify E. coli in surface runoff. There are two types of OSSFs in the watershed; aerobic and anaerobic systems. Aerobic systems disperse the treated effluent by spraying the surface of the soil while anaerobic systems discharge untreated effluent into the soil from gravel drainage trenches. This project will determine if either of the two types of OSSFs is contributing to the elevated E. coli concentrations in Dickinson Bayou. Two of the monitoring sites were placed in a neighborhood that uses OSSFs. The third monitoring station was a control site placed in a neighborhood that is connected to a municipal wastewater treatment plant with no OSSFs. Each monitoring site is equipped with a flow meter and an automatic sampler. Rainfall – runoff relationships were established for each monitoring station. Water quality samples were obtained during runoff events at each monitoring station and analyzed for E. coli concentrations. Runoff events were characterized as either wet, average, or dry antecedent moisture conditions. The rainfall-runoff relationships and the E. coli concentrations in the runoff will be presented in this presentation.

107


IMPACT OF SOIL TYPE ON THE SALT ACCUMULATION DUE TO RECYCLED WATER IRRIGATION Muhammad Muhitur Rahman*, Dharma Hagare and Basant Maheshwari (University of Western Sydney, Penrith, NSW, Australia) Peter Dillon (CSIRO Land and Water, Glen Osmond, SA, Australia) In the recent years, recycled (reclaimed) water is increasingly being used for irrigating open, sports and agriculture fields. Salt accumulation study due to reclaimed water irrigation in urban open spaces is a new area compared to wastewater irrigation. Reclaimed water has more acceptability to use in irrigation compared to untreated wastewater. However, the current, but limited, literature suggests that there is an increased risk of salt accumulation in the vadose zone of the soil, which is irrigated with recycled water. This is due to the presence of high levels of salt in the recycled water as compared to that of town water supply. In this study, a laboratory column study was carried out to investigate the accumulation of salt in the vadose zone due to continuous application of recycled water over a period of 100 days. Two types of soil samples having the irrigation history of 9 and 18 years were collected from paddocks located in Hawkesbury Water Reuse Scheme (HWRS), Australia. Salt mass balance from the column study showed that the total cumulative leached salt mass was less than that was applied. Thus indicating an increasing pattern of salt mass stored in soil profile. Impact of soil type on salt accumulation at 0.2 m depth below the soil surface was evident. It was observed that loamy sand soil had higher accumulation (about 10%) of salt compared to the loam soil. Salt accumulation in both the soils was monitored in terms of bulk electrical conductivity by a dielectric sensor. However, bulk electrical conductivity was observed to depend on volumetric water content. Therefore, an equation was developed to convert bulk electrical conductivity to soil water electrical conductivity using the data that is specific to soil type. Soil water electrical conductivity is widely used as the means to express soil salinity. The equation predicted the soil water electrical conductivity in loamy sand soil with 98% and in loam soil with 88% efficiency. The result from this experiment will assist in developing the salt management strategies for these paddocks, which may be applied for other fields which are irrigated with recycled water.

108


DIVERSITY OF AQUATIC FLORA IN RELATION TO WATER QUALITY IN KOLLERU LAKE, ANDHRA PRADESH, INDIA P. Brahmaji Rao (Acharya Nagarjuna University, Andhra Pradesh, India) Kolleru Lake is the largest natural fresh water lake in India. Ramsar Convention was the first to identify the lake in coastal Andhra Pradesh as a wetland. It is located between two major deltas of river Godavari on the east and Krishna on the west. The lake (Long 810 - 40’ to 800 – 20’ East, Lat 170 – 25’ to 160 – 28’ north) has an area of 954 Sq. Kms.. The present study is aimed to reveal the aquatic flora of Kolleru Lake and nature of water quality depends on presence of diversity of aquatic flora at different field stations. Methods of study based on important value index (IVI) of aquatic flora as a indicator to know the nature of water either fresh or brackish. Aquatic floral analysis to identify the species status, dominance and diversity variations among 17 field stations. Methods used to compute the frequency, dominance and abundance. Based on values Important Value Index (IVI) was calculated. Highest IVI value for aquatic flora is Eichornia (76.7) at seventeen field stations, Atapaka and minimum IVI for the species is Nymphaea (3.6) at third filed station Prathikollalanka. plant species present or absent at field station was varied based on water quality. Observations on Eichornia which is present in all field stations except in 12th field station known as Upputeru Bridge. At Upputeru the Eichornia was not observed, because the outflow of the Kolleru lake water leads to Bay of Bengal, there it may be slight variation in the fresh water becoming brackish water. The observed reason of pharagmitis is absent at three field stations was due to undisturbed continuous water flow.

109


DIVERSITY OF AQUATIC FLORA IN RELATION TO WATER QUALITY IN KOLLERU LAKE, ANDHRA PRADESH, INDIA P. Brahmaji Rao Department of Environmental Sciences, Acharya Nagarjuna University, Guntur, Andhra Pradesh, India ABSTRACT: Kolleru Lake is the largest natural fresh water lake in India. Ramsar Convention was the first to identify the lake in coastal Andhra Pradesh as a wetland. It is located between two major deltas of river Godavari on the east and Krishna on the west. The lake (Long 810 - 40’ to 800 – 20’ East, Lat 170 – 25’ to 160 – 28’ north) has an area of 954 Sq. Km. The present study is aimed to reveal the aquatic flora of Kolleru Lake and nature of water quality depends on presence of diversity of aquatic flora at different field stations. Methods of study based on important value index (IVI) of aquatic flora as an indicator to know the nature of water either fresh or brackish. Aquatic floral analyses were conducted to identify the species status, dominance and diversity variations among 17 field stations. Methods used to compute the frequency, dominance and abundance. Based on values Important Value Index (IVI) was calculated. Highest IVI value for aquatic flora is Eichornia (76.7) at seventeen field stations, Atapaka and minimum IVI for the species is Nymphaea (3.6) at third filed station Prathikollalanka. Plant species present or absent at field station was varied based on water quality. Observations on Eichornia which is present in all field stations except in 12th field station known as Upputeru Bridge. At Upputeru the Eichornia was not observed, because the outflow of the Kolleru lake water leads to Bay of Bengal, there it may be slight variation in the fresh water becoming brackish water. The observed reason of pharagmitis is absent at three field stations was due to undisturbed continuous water flow. INTRODUCTION The catchment area of the Kolleru lake is 4763 sq. km At 3 MSL to + 10 MSL. The lake is directly fed by two seasonal rivulets Budameru and Tammileru (East and West branches) besides Ramileru and Gunderu and 30 inflowing channels and drains. Upputeru in the south- eastern end of the lake is the only natural outlet draining the lake waters at Perentalakanuma into the Bay of Bengal after traversing 50 Km. Several studied were carried out in different wetland of India. The aquatic vegetation of Kolleru Lake was studied by Seshavatharam et. al., (1982). Floristic environment of Lake Kolleru, Seshagirirao et.al., (1987), the vegetation in Kolleru was studied by Venkateswarlu (1993). Limnology and primary productivity of the plankton community of Niland Lake, Kashmir was studied by Khan and Zutshi (1980). A comparative study of plankton population of some typical water bodies of Jammu and Kasmir studied by Kaul et. al., (1978). An integrated ecological approach of the lake Kolleru Development Authourity by Mangapathirao (1987), Annon (1987). MATERIAL AND METHODS The main objective of this study was to find out the abundance of the macrophytes at selected stations in the lake in relation to the ambient water quality and aquatic flora nature. Pilot studies have shown that the lake supports a variety of hydrophytes which can be categorised as the emergent plants (Scirpus, Typha, Phragmites, Eclipta); Submerged forms (Vallisneria, Ottelia, Hydrilla, Chara, Nitella); Free floating forms (Salvinia, Eichornia, Pistia) etc. Cluster analysis (Bray Curtis) was done to identify ecological groups by using the software tool “PAST”. Clusters were developed in two way method for both aquatic flora and water quality parameters (Macfadyen and Ford, 1984). Vegetation analysis has been done by lying transects / quadrates of selective sizes (10 m x 10 m) in the study area. Raunkiaer (1934) indicates the number of sampling units. The numbers of plants present in each transect / quadrates were counted. Plant materials collected during sampling are identified with the help of standard herbaria of the Botanical Survey of India and Gamble volumes of the Department of Botany, Acharya Nagarjuna University, Guntur. Finally, the Frequency, density, Relative frequency, Relative 110

Environmental Science & Technology 2014 Vol. 1 density of each plant were calculated. At each station 5 transects / quadrates were laid down in an area of two square kilometres and the frequency, of each plant were calculated.

RESULTS AND DISCUSSIONS The study carried out to estimate the aquatic flora in and around Kolleru lake were observed and identified 17 plant species from 17 field stations (Table 1). Species dominance of aquatic flora based on IVI values among the field stations were estimated (Table 2). Species-Wise Distribution Pattern of Aquatic Flora Present among Field Stations are analysed (Table 3) and station wise status of flora and degree of maturity of plant community is established based on the percent frequency of all the species (Table 4). FIGURE 1. Study area of Lake Kolleru First field station is MONDUKODU which is having 90 cm depth and having significant geographical and ecological features. Thus each field station was described in study area and tabulated. In this station 6 species of aquatic flora. Among the six species, the dominant species are Eichornia and Phragmites with a maximum IVI value of 44.44. The lowest IVI value 5.40 was exhibited by Alternanthera, Nymphaea. The highest MIV 100 was observed in Eichornia, Ipomea and Phragmites and the lowest MIV 40. Second field station is GUDIWAKA LANKA, having a depth of 85 cms. Among aquatic flora, 8 species of each were observed. Of the 8 species of aquatic flora, maximum IVI value was exhibited by Eichornia 33.9 and minimum was shown by Alternanthera 5.48. The highest MIV was exhibited by Eichornia, Ipomea and Vallisneria (100) and the minimum was shown by Alternanthera and Ottelia (40). Third field station observed is PRATHIKOLLA LANKA which is having a depth of 110 cms. In this station, 9 species of aquatic flora species were observed and identified. The analysis was done as, among 9 species, the dominant one is Hydrilla with a maximum IVI value of 29.47, and lowest IVI value was noticed with Nymphaea (3.6). The highest MIV 100 was observed in Eichornia, Vallisneria, Salvinia, Chara and Hydrilla. The lowest MIV 40 was noticed in Nymphaea. CHETTUNNAPADU is the fourth field station had 6 Species of aquatic flora were identified and its depth is 55 cms. Of the six aquatic species, Eichornia is dominant with a maximum IVI value of 47.46. The Lowest IVI Value was noticed with Ottelia (8.64) .The highest MIV 100 was observed in Eichornia, Ipomea and Nitella. The lowest MIV 40 was observed in Ottelia. The fifth selected location is PEDAYADLAGADI. It depth is 70 cms .One can view the beauty of the lake to a certain extent from this location.8 Species of aquatic flora were observed in this location. Of the 8 species of aquatic flora, Eichormia is having the maximum IVI value of 39.20. The highest MIV 100 was observed in Eichornia, Ipomea and Nitella. The lowest IVI value 4.80, lowest MIV 40 was observed in Nymphaea. KOVVADALANKA is the sixth field station, having a depth of 45 cms. 6 Species of aquatic flora were observed. Of the 6 species, Pistia is dominant having the maximum IVI value of 45.58. The highest MIV 100 was noticed in Eichornia, Ipomea and Pistia and the lowest MIV 40 was observed in Nitella. The Seventh field station is DEVICHINTAPADU. Maximum depth (130 cms) was observed here. 4 species of aquatic flora were observed. Of the 4 species of aquatic flora, Eichormia is dominant having maximum IVI value i.e., 54.78.Phragmites is having the lowest IVI value i.e. 23.19.The highest MIV 100 was observed in Eichormia and Pistia. The lowest MIV 40 was noticed in Vallisneria. VEGILAMALLI is the eighth field station. Its depth is 85 cms. 4 Species of aquatic flora were observed. Of the 4 species of aquatic flora, Eichornia is dominant having maximum IVI value 63.00, and highest MIV 100, Nitella is having the lowest IVI value 17.00, and lowest MIV (40). The ninth field station is CHATAKAYA. It depth was 100 cms.8 Species of aquatic flora were observed. Of the 8 species in the aquatic flora, Salvinia is dominant having the maximum IVI value of 44.21, and highest MIV 100. The minimum IVI value 8.95 and lowest MIV 40 were exhibited by Scirpus, Ottelia, 111

Environmental Science & Technology 2014 Vol. 1 and Typha. BHUJABALAPATNAM was the tenth field station. The depth was 80 cms. 7 Species of aquatic flora were observed. Of the 7 species, Eichornia is dominant, exhibited a maximum IVI value of 42.42, highest relative frequency 30. The minimum IVI value 10.30 and lowest MIV 40 were observed in Nymphaea and scirpus. The highest MIV 100 was noticed in Eichornia and Salvinia. KOLLETIKOTA was the eleventh field station which has a depth of 100 cms. 8 species of aquatic flora were observed. Of the 8 species of aquatic flora, Nitella is dominant having the maximum IVI value 44.21, and the minimum IVI value 6.05, were observed in Typha. The highest MIV 100 was obtained in Nitella and the lowest 60 was noticed in Ottellia, Typha and Eclipta. UPPUTERU BRIDGE was the twelfth station. It has a depth of 50 cms. 6 species of aquatic flora were observed. Of the 6 species of aquatic flora, the maximum IVI value was exhibited by Ipomea (36.00). The Minimum IVI value (13.14) was exhibited by Vallisneria (13.14) and Potamogeton. The highest MIV 100 was noticed in Ipomea and Alternanthera and the lowest value 60 was observed in Ottelia, Vallisneria, Potamogeton, Ecilipta and Typha. SIDDHAPURAM is thirteenth station. It has a depth of 55 cms.4 Species of aquatic flora were observed. Of the 4 species of aquatic flora, the maximum IVI value (89.58) was shown by Salvinia. The minimum IVI Value 6.05 was exhibited by Typha. The highest MIV 100 was observed in Eichornia, Ipomea, Salvinia and Typha. ADAVIKOLANU is the fourteenth field station. It has depth is 45 cms. 5 Species of aquatic flora were observed. Of the 5 species of aquatic flora, Phragmites is dominant having, the maximum IVI value 49.23.The minimum IVI value 15.73, was shown by Ipomea and Pistia. The highest MIV 100 was shown by Eichornia and Salvinia. The minimum MIV 60 was noticed in Ipomea, Chara and Pistia. THOKALAPALLI is the fifteenth Station. It has a depth of 40 cms. 6 Species of aquatic flora were observed. Pistia is dominant having the maximum IVI value 44.0. The minimum IVI value 9.71 was shown by Alternanthera, Nitella. The Highest MIV 100 was observed in Eichornia and Pistia. The lowest MIV 20 was noticed in Alternanthera. CHINAYADLAGADI is the sixteenth station. It has a depth of 70 cms. 6 Species of aquatic flora were observed. Of the 6 species of aquatic flora, Eichornia is dominant having the maximum IVI 36.13. The minimum IVI 14.84 was shown by Ipomea and Nymphaea. The highest MIV 100 was observed in Eichornia and Typha. The lowest MIV 60 was noticed in Ipomea, Nymphaea and Hydrilla. The seventeenth station in ATAPAKA. It has a depth of 120 cms. 3 species of aquatic flora were observed. Eichornia is dominant exhibited the maximum IVI 76.67. The other two species Ipomea, Eclipta exhibited minimum IVI value 42.50 (Ipomea). Eclipta and minimum MIV 40 were noticed in Ipomha. Table 1. Systematic position of the species present in Kolleru lake S.No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Family Pontederiaceae Convolvuloceae Gentianaceae Amaranthaceae Nymphaeacebily Cyperaceae Hydrocharitaceae Characeae Hydrocharitaceae Salviniaceae Araceae Nymphaeaceae Potamogetonaceae Asteraceae Typhaceae Poaceae Hydrocharitaceae

Name of the Species Eichornia crassipes Ipomea aquatica Nymphoides indicum Alternanthera sessilis Nymphaea nouchali Scirpus cernuus Ottelia alismoides Chara connivens Vallisneria spiralis Salvinia aurticulata Pistia stratiotes Nitella Sps. Potamogeton nodosus Eclitpa alba Typha angustata Phragmites karka Hydrilla verticillata 112

Vernacular name Gurrapu Decca Thulakada Nymphoides Ponnagantikura Kaluva Fairy lights Duck lettuce Nir Veneki Convergent stone wort Navvaru nachu/Tape grass Pilli adugu Budaga tamara Stone wort Long leaf pond weed Guntagalagara Jambu Kikkisa Nachu


0

0

0

0

0

0

0

0

0

0

44.4

0

0

0

11

0

18.1

0

0

0

0

0

12.4

27.1

0

Prathikollalanka

18

0

0

0

3.6

6.5

14.5

14.7

22.1

22.1

0

0

0

0

0

12.2

29.5

Chettunnapadu

48

36

18

0

0

0

8.6

0

0

0

0

23.7

0

0

0

9.8

0

Pedayadlagadi

39

25

9.2

0

4.8

0

5.2

0

0

19.2

0

0

0

0

7.2

23.2

0

Kovvadalanka

36

36

0

0

10.7

0

0

0

0

0

45.6

7.9

0

0

0

7

0

Devichintapadu

55

0

0

0

0

0

0

0

29.6

0

0

40

0

0

0

23.2

0

Vegilamalli

63

0

0

0

24

0

0

0

0

44.2

0

17

0

0

0

33.3

0

Chatakaya

16

16

0

0

0

8.9

8.9

0

0

0

28.2

0

0

0

8.9

17.5

0

Bhujabalapatnam

42

19

14

0

10.3

10.3

0

0

17.6

0

0

0

0

0

0

30.3

0

Kolletikota

13

11

0

0

0

0

10.1

0

0

0

0

44.2

0

8.1

6.1

28.4

14.2

Uppeteru Bridge

0

36

0

28

0

0

17.5

0

13.1

0

0

0

13.1

0

0

30.9

0

Siddhapuram

23

20

0

0

0

0

0

0

0

53.3

0

0

0

0

0

37.1

0

Adavikolanu

33

16

0

0

0

0

0

23.6

0

0

15.7

0

0

0

0

49.2

0

Thokalapalli

40

21

0

9.7

0

0

21.9

0

0

0

44

9.7

0

0

0

0

0

Chinayadlgadi

36

15

0

23.4

14.8

0

0

0

0

0

0

0

0

0

27.1

0

29.7

Atapaka

77

43

0

0

0

0

0

0

0

0

0

0

0

42.5

0

0

0

Nitella Sps.

Pistia stratiotes

Vallisneria spiralis

Chara connivens

Table 3. Species-Wise Distribution Pattern of Aquatic Flora Present among Field Stations in Kolleru Lake S. No.

Name of the Plant Species

1

2

3

4

5

6

7

8

9

10

11

12

13

14 15

16

17

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Eichornia Ipomea Nymphoides Alternanthere Nymphaea Scirpus Ottelia Chara Vallisneria Salvinia Pistia Nitella Potamogeton Eclitpa Typha Phragmites

+ + + + + +

+ + + + + + + +

+ + + + + + + +

+ + + + + +

+ + + + + + + +

+ + + + + +

+ + + +

+ + + +

+ + + + + + + +

+ + + + + + +

+ + + + + + +

+ + + + + +

+ + + +

+ + + + +

+ + + + + + -

+ + + + + -

+ + + -

17

Hydrilla Total

6

8

+ 9

6

8

6

4

4

8

7

+ 8

6

4

5

6

+ 6

3

113

Hydrilla verticillata

5.4

5.5

Phragmites karka

5.4

9.9

Typha angustata

Nymphaea nouchali

9.7

27

Eclitpa alba

Alternanthera sessilis

33

34

Salvinia aurticulata

Nymphoides indicum

44

Gudiwakalanka

Ottelia alismoides

Ipomea aquatica

Field Station Mondukodu

Scirpus cernuus

Eichornia crassipes

Potamogeton nodosus

Table 2. Species dominance of Aquatic flora based on IVI values among the field stations in Kolleru Lake


Species vs Field Station Eichornia Ipomea Nymphoides Alternanthere Nymphaea Scirpus Ottelia Chara Vallisneria Salvinia Pistia Nitella Potamogeton Eclitpa Typha Phragmites Hydrilla

Total MIV

Table 4. Maturity Index Values (MIV) of aquatic flora present among field stations in Kolleru lake Frequency % 1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

100 100 60

100 100 60

100 0 0

100 100 60

100 100 60

100 100 0

100 0 0

100 0 0

60 60 0

100 60 60

80 80 0

0 100 0

100 100 0

100 60 0

100 80 0

100 60 0

60 40 0

40 40 0

40 0 0

0 40 60

0 0 0

0 40 0

0 60 0

0 0 0

0 60 0

0 0 40

0 40 40

0 0 0

100 0 0

0 0 0

0 0 0

40 0 0

80 60 0

80 60 0

0 0 0

40 0 100

60 100 100

40 0 0

60 0 0

0 0 0

0 0 40

0 0 0

40 0 0

0 0 80

60 0 0

60 0 60

0 0 0

0 60 0

60 0 0

0 0 0

0 0 0

0

0

100

0

80

0

0

0

100

100

0

0

100

100

0

0

0

0

0

0

0

0

100

100

0

60

60

0

0

0

60

100

0

0

0

0

0

100

100

40

60

40

0

0

100

0

0

0

40

0

0

0 0 0 100

0 0 60 0

0 0 0 0

0 0 0 0

0 0 60 0

0 0 0 0

0 0 0 0

0 0 0 0

0 0 40 0

0 0 0 0

0 60 60 0

60 0 0 0

0 0 0 0

0 0 0 0

0 0 0 0

0 0 100 0

0 40 0 0

0

0

100

0

0

0

0

0

0

0

100

0

0

0

0

60

0

440

500

660

400

600

400

300

200

400

540

540

380

300

380

420

460

280

73

71

83

80

75

80

75

67

57

68

77

76

100

76

70

77

56

Physico- chemical analysis: Water quality of Kolleru lake was analyzed based on parameters like pH, temperature, conductivity, turbidity, total solvents, BOD, COD, alkalinity etc (Table 5). The readings of such parameters help us to determine the condition of the lake compared to the standard values of the parameters. The readings of these parameters of the water sample were indicate that almost all the points got the above standard level value which indicates that the water quality is in deterioration stage. COD is also very high which could be attributed to the influx of untreated or partially treated sewage water.

FIGURE 2. Graph showing Alkalinity, Chlorides and Hardness among 17 field stations

The depth of the lake ranges from 45cm to 130cm, the pH value ranges from 7.5 to 8.2, Conductivity value ranges from 456 to 710 and Turbidity ranges from 11 to 22. Whereas the remaining parameters i.e. DO, BOD and COD concentration levels vary among the 17 field stations was shown in the figure 1. 114

Environmental Science & Technology 2014 Vol. 1 Similarly the relation between alkalinity, hardness and Chloride concentrations are predominantly correlated among the field stations were shown in the figure 2. The Phosphate and Nitrate concentrations more or less equal to all field stations whereas Sulphates are drastically ranging from one field station to another (figure 3). The similar studies on nutrient path way of Lake Kolleru ecosystem was described by Mangapathirao K (1987).

FIGURE 3. Graph showing Phosphates, Nitrates and Sulphate concentrations among 17 field stations

29.5 0 0 17.7 0 12.2 0 0 22.1 14.5 22.1 3.6 0 14.7 6.5 0 0

Hydrilla Typha A lternanthera Eicho rnia Ipo mea P hragmites Nitella Nympho ides Vallisneria Ottelia Salvinia Nymphaea P istia Chara Scirpus P o tamo geto n Eclitpa

3Prathiko

0 0 28 0 36 30.9 0 0 13.1 17.5 0 0 0 0 0 13.1 0

12Uppeter

29.7 27.1 23.4 36.1 14.8 0 0 0 0 0 0 14.8 0 0 0 0 0

16Chinaya

0 0 0 76.7 42.5 0 0 0 0 0 0 0 0 0 0 0 42.5

17Atapaka

14.2 6.1 0 13.4 11.4 28.4 44.2 0 0 10.1 0 0 0 0 0 0 8.1

11Kolleti

0 0 0 54.8 0 23.2 40 0 29.6 0 0 0 0 0 0 0 0

7Devichin

0 8.9 0 16.1 16.1 17.5 0 0 0 8.9 0 0 28.2 0 8.9 0 0

9Chatakay

0 0 9.7 40 20.7 0 9.7 0 0 21.9 0 0 44 0 0 0 0

15Thokala

0 0 0 35.8 35.8 7 7.9 0 0 0 0 10.7 45.6 0 0 0 0

6Kovvadal

0 0 0 23.3 20 37.1 0 0 0 0 53.3 0 0 0 0 0 0

13Siddhap

0 0 0 63 0 33.3 17 0 0 0 44.2 24 0 0 0 0 0

8Vegilama

0 0 0 33.3 15.7 49.2 0 0 0 0 0 0 15.7 23.6 0 0 0

14Adaviko

0 7.2 0 39.2 25.2 23.2 0 9.2 0 5.2 19.2 4.8 0 0 0 0 0

5Pedayadl

0 12.4 5.5 33.9 27.1 27.1 0 9.9 18.1 11 0 0 0 0 0 0 0

2Gudiwaka

0 0 5.4 44.4 33.3 44.4 0 9.7 0 0 0 5.4 0 0 0 0 0

1Mondukod

0 0 0 42.4 18.6 30.3 0 13.9 17.6 0 0 10.3 0 0 10.3 0 0

10Bhujaba

4Chettunn

0 0 0 47.5 35.6 9.8 23.7 18.2 0 8.6 0 0 0 0 0 0 0

FIGURE 4. Cluster analysis (Bray –Curtis Two way analysis) among 17 Field stations based on IVI value of aquatic flora 115


Depth

55

85

70

45

100

100

80

45

50

55

40

70

120

110

85

130

112

142

175

184

143

197

186

186

164

153

132

116

175

214

213

232 243

CHLORIDE

437 354 445 324 434 537 476 423 398 387 437 365 243 235

SULP HATE

256 276 414

327 365 389 412 312

532 302 345 324 316

COD

542 476 523 235 321 298 276

B OD

423 465 436 498 487 476 543 514

334 354 367 387 397 368 454 416

412

90

394 521 494 245 278 289 427 456 527 547 478 284 357 567 632 623 384

A LKA LINITY

325 426 524 578 435 654 623 643 487 465 367 365 547 723 689 713

HARDNESS

563 567 612

632 497 512

670 680 700 710

843

CONDUCTIVITY

423 385 543 476 532 578 523 456 643 621 598

670 670 650 650 680 660 670 690 670 650 710

T.D.S

700 700

1.25 1.26 1.56 1.82 1.42 1.67 1.32 1.65 1.89 1.76 1.58 1.48 1.43 1.76 1.43 1.1

1.24

P HOSP HA TE

3.2

3.3

3.3

3.4

3.5

3.7

3.6

4

3.9

3.8

4.1

4

4.1

3.1

3.2

3.1

3.1

DO

7.6

7.7

7.7

7.5

7.5

7.5

7.6

7.6

7.7

7.7

7.6

7.5

7.5

7.8

8.2

7.8

7.6

pH

32

37

36

32

43

34

41

27

25

32

31

27

58

28

26

34

35

NITRA TE

19

20

21

22

18

18

11

14

20

17

19

20

19

16

22

22

21

TURBIDITY

1Mondukod

7Devichin

2G udiwaka

3Prathiko

17Atapaka

16Chinaya

15Thokala

13Siddhap

12Uppeter

14Adaviko

10Bhujaba

11Kolleti

9Chatakay

6Kovvadal

5Pedayadl

8Vegilama

FIGURE 5. Cluster analysis (Bray–Curtis Two way analysis) among 17 Field stations based on water quality

pH

T.D.S

TURBIDITY

CONDUCTIVITY

DO

BOD

COD

ALKALINITY

CHLORIDE

HARDNESS

PHOSPHATE

NITRATE

SULPHATE

Mondukodu Gudiwakalanka Prathikollalanka Chettunnapadu Pedayadlagadi Kovvadalanka Devichintapadu Vegilamalli Chatakaya Bhujabalapatnam Kolletikota Uppeteru Bridge Siddhapuram Adavikolanu Thokalapalli Chinayadlgadi Atapaka

Depth (Cm)

Table 5: Physico-Chemical analysis of water among field stations in Kolleru lake

Field Station

4Chettunn

Concentrations

90 85 110 55 70 45 130 85 100 80 100 50 55 45 40 70 120

7.6 8.2 7.8 7.6 7.7 7.5 7.8 7.7 7.5 7.6 7.5 7.7 7.7 7.6 7.6 7.5 7.5

700 710 650 670 700 710 700 680 670 650 670 680 660 650 670 690 670

21 22 16 19 21 22 22 20 18 11 18 20 17 14 19 20 19

598 643 456 563 612 632 621 567 497 423 512 543 476 385 532 578 523

3.1 3.2 3.1 3.2 3.3 3.4 3.1 3.3 3.5 3.6 3.7 3.9 3.8 4 4.1 4 4.1

276 321 235 312 354 367 298 334 387 368 397 416 412 454 542 476 523

316 345 302 327 389 412 324 365 423 436 465 487 476 498 543 514 532

384 632 567 394 494 245 623 521 278 427 289 527 547 456 478 284 357

243 213 214 112 175 184 232 142 143 186 197 164 153 186 132 116 175

843 689 723 325 524 578 713 426 435 623 654 487 465 643 367 365 547

1.24 1.43 1.76 1.25 1.56 1.82 1.1 1.26 1.42 1.32 1.67 1.89 1.76 1.65 1.58 1.48 1.43

35 26 28 32 36 32 34 37 43 41 34 25 32 27 31 27 58

235 365 437 256 414 437 243 276 354 324 445 537 476 434 423 398 387

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Environmental Science & Technology 2014 Vol. 1 The present study results of IVI values of aquatic flora and water quality concentrations among 17 field stations ware given in the tables. The relation between water quality and aquatic flora were drawn by the statistical approach – Bray – Curtis cluster analysis method by using PAST software. The similarity among aquatic flora in Thokalapally and Kovadalanka, Pedayadlagadi and Gudiwakalanka, Bhujabalapatnam and Mondukodu. The variance is high in Prathikollalanka (figure 4). Similarly water quality analysis concentrations were also statistically worked out. The results indicates that Thokalapally and Kovadalanka, Siddhapuram and Vegilamalli, Pedayadlagadi and Gudiwakalanka, Bhujabalapatnam and Mondukodu. The only one field station i.e. Vegilamalli is having high IVI value consisting the more number of species among all field stations (figure 5). CONCLUSION Floral analyses were conducted to identify the species status, dominance and diversity variations among 17 field stations. Methods used to compute the frequency, dominance and abundance. Based on values Important Value Index (IVI) was calculated. Highest IVI value for aquatic flora is Eichornia (76.7) at seventeen field stations, Atapaka and minimum IVI for the species is Nymphaea (3.6) at third filed station Prathikollalanka. Species presence or absent at each field station were compared among all stations by Maturity Index Value (MIV) was evolved. Present study findings revealed distribution of plant species present or absent at field station was varied based on water quality. Observations on Eichornia which is present in all field stations except in 12th field station known as Upputeru Bridge. At Upputeru the Eichornia was not observed, because the outflow of the Kolleru lake water leads to Bay of Bengal, there it may be slight variation in the fresh water becoming brackish water. The observed reason of pharagmitis is absent at three field stations was due to undisturbed continuous water flow. ACKNOWLEDGMENTS: My deep sense of gratitude to Prof K.V. Rao, Vice Chancellor, Acharya Nagarjuna University, Guntur for permitting to do the research work and encouragement in my career. I also thank to A.P. Forest Department for providing logistic support. REFERENCES Amyan Macfadyen, E. D. Ford (1984). Advances in Ecological Research, Volume 14 Academic Press, 245 pp. Annon. 1987. Master plan for Kolleru Lake Development, An integrated Ecological approach. Office of the Kolleru Lake Development, Kaikalur, 1987, 255pp. Kaul, V. 1977. Limnological Survey of Kashmir lakes with reference to trophic status and conservation Int. J.Ecol. Environ. Sci. 3: 29-44. Kaul, V., D.N. Fotedar, A.K. Pandit and C.L. Trisal 1978. A comparative study of plankton population of some typical fresh water bodies of Jammu and Kashmir State. Environ. Physiol. Ecol. Plants. 249-269. Khan, M.A. and D.P. Zutshi 1980. Contributions to High Altitude Limnology of the Himalayan system. I. Limnology and primary productivity of the plankton community of Niland Lake. Kashmir. Hydrobiologia 75(2): 103-112. Mangapathi Rao, K. 1987. Master Plan for Kolleru lake development - An integrated ecological approach. Office of the Kolleru lake development authority, Kaikaluru, Government of Andhra Pradesh. Mangapathi Rao, K. 1987. The nutrient path way in Kolleru lake ecosystem. Proc National seminal on aquatic biology. Andhra University, Waltair. Raunkiaer, C. 1934. The life forms of plants and statistical geography. Claredon, Oxford, pp.632. Seshavataram. V.B.S.M. Dutt and P.Venu.1982. .An ecological study of the vegetation of Kolleru lake. Bulletin Botanical survey of India. 24(11-4): 70-75pp. Seshavataram.V. and P. Venu.1981. Some observations on the ecology of Kolleru lake. International J. Ecol. Enuviron. Sci. 7: 35-44pp. Seshavatharam.V. and Venu. P. 1982. Ecological Studies of the Vegetations of Kolleru Lake. Bull. Botanical Survey of India 24(1-4): 70–75. 117

Environmental Science & Technology 2014 Vol. 1 Venkateswarlu V (1993) Floristic Environment of Lake Kolleru, Kolleru Lake - Environmental Status (Past and Present), EM International publishers, 87pp.

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STUDY ON WATER QUALITY VARIATION DURING RAINFALL RUNOFF EVOLUTION PROCESS IN A CITY RESIDENTIAL DISTRICT Huaien Li*, Jiake Li and Zengchao Liu (State Key Laboratory of Eco-Hydraulic Engineering in Shaanxi, Xi'an University of Technology, Xi’an, Shaanxi, China) In order to investigate the water quality variation and pollution characteristics of runoff during rainfall runoff evolution process, water quality of undisturbed rain, roof runoff, road and outlet runoff for 6 events were monitored in 2011 in a residential district in Xi’an city, Shaanxi, China. The results showed that: 1) the water quality of undisturbed rain was better than that of roof runoff and outlet runoff, and the water quality of road runoff was worst; 2) road runoff were seriously polluted with a higher average concentration for COD, ammonia nitrogen and TN; 3) the pollution of rainfall runoff has first flush effect in a certain degree, the concentrations of pollutants such as SS, COD and TN in the initial stage were higher than the later in a rainfall runoff process; 4) the larger the number of antecedent dry days for rainfall event, the higher concentration of pollutants in runoff; and 5) the grass strip between building and road can partly reduce the concentration of pollutant such as COD and TN.

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LOW COST AUTONOMOUS SENSING PLATFORMS FOR THE DIRECT DETERMINATION OF NUTRIENTS IN WATER Deirdre Cogan, John Cleary, Kamil Jankowski and Dermot Diamond (Dublin City University, Glasnevin, Dublin 9, Ireland) Mark Bowkett (T.E. Laboratories, Tullow, Carlow, Ireland) ABSRACT: There is a growing need for low cost, remote sensing systems which can be deployed in situ in sufficiently large numbers to ensure that data on key water quality parameters is readily available. The challenges facing this ideal of monitoring include the cost of these platforms and the inability to “deploy and forget” due to limited long term stability and maintenance requirements. Microfluidic technology has great potential as a solution to the increasing demand for environmental monitoring, by producing autonomous chemical sensing platforms at a price level that creates a significant impact on the existing market. The development of sensing platforms for ammonia and nitrate in water and wastewater are being investigated. Our approach is to combine microfluidics with simplified colorimetric chemical assays; low cost LED/photodiode-based optical detection systems; and wireless communications. In order to drive down the cost of these devices, it is vital to keep the fluidic handling requirement as simple as possible, as multistage methods are expensive to implement as well as being less reliable in long-term deployments. Colorimetric methods for nitrate and ammonia have been modified eliminating several steps previously associated with the methods to facilitate their implementation into an autonomous platform, resulting in a rapid and simple measurement procedure.

INTRODUCTION Environmental sensors have great potential as a solution to the increasing demand for environmental monitoring.(Diamond, 2004) Presently, the challenges facing this ideal of environmental monitoring include the cost of these platforms and the inability to “deploy and forget” due to limited long term stability and automated platform maintenance requirements. The objective of this research is to produce a self-sustaining platform at a price level that creates a significant impact on the existing market. This will lead to the development of compact autonomous instruments for in situ continuous monitoring of remote locations over long deployable lifetimes (Cleary et al., 2010). The focus will be on critical factors like miniaturisation of the device and minimisation of the reagent consumption. Developing this class of environmental monitoring technology will require a multidisciplinary approach involving electronics, wireless communications, environmental science, engineering and materials science with microfluidics playing a key role. Currently, monitoring for nutrients in our waters such as nitrate and ammonia is based on in situ manual sampling followed by laboratory analysis using standard laboratory instrumental and/or wet chemical methods. This results in the infrequent monitoring of water at a fewer number of locations than is desirable, as it is time consuming, expensive, non-scalable and requires skilled personnel. Despite the enormous activity both into sensor networks and into the development of improved chemical sensors over the past decade, there has been virtually no penetration of chemical sensing platforms into widely distributed sensor network deployments, although the key challenges have been repeatedly emphasised (Diamond, 2004). Approaches to water quality monitoring of nutrient levels like nitrate and ammonia have been the subject of much research over many years. However these well-established laboratory methods are making little progression into practical adoption for autonomous field based instruments. Cost is a major factor of this, as reagent based analysers can cost up to €15,000 per unit (Microlab autonomous phosphate analyser retails at ca. €20K per unit, including vat, in Ireland, Micro Mac1000 costing ca. €18,000; autonomous instruments from YSI, and HACH are similarly priced), mainly due to the need to incorporate expensive fluidic handling components, like pumps and valves, which can represent approximately 60% of the total component cost. The clear message from these numbers is that chemical sensors and biosensors do not meet the specifications for large-scale deployments, due to price, performance and reliability issues. 120

Environmental Science & Technology 2014 Vol. 1 Therefore, in order to drive down the cost of ownership of these devices, it is imperative to keep the fluidic handling requirement as simple as possible, as complex, multistage approaches are correspondingly challenging and expensive to implement due to a high purchase price, as well as being less reliable in longterm deployments due to high maintenance costs. This research therefore, focuses on the simplifying the colorimetric methods of nitrate and ammonia for simple, inexpensive and reliable integration into sensing platforms. NITRATE DETECTION The first use of a direct nitrate analyser using chromotropic acid has been developed (Cogan et al., 2013). A simplified chromotropic acid method eliminating several steps previously associated with this method is employed in the platform. In a sulphuric acid medium, chromotropic acid reacts with nitrate ions and produces a characteristic yellow colour associated with an absorbance band in the visible region (λmax = 430 nm). The modified method allows for nitrate determination over the linear range 0.9 – 80 mg/L nitrate with a limit of detection of 0.73 µg/L nitrate. Validation was achieved by analysing water samples from various sources including groundwater, trade effluent and drinking water by the modified method and by ion chromatography. The method was implemented on a flow analysis platform shown in figure 1 incorporating a low cost paired emitter-detector diode (PEDD) as the optical detector. An excellent correlation coefficient of 0.993 was obtained between the modified method and ion chromatography. The modified chromotropic acid method represents a rapid, simple, low cost technique for the direct determination of nitrate in water.

FIGURE 5. Nitrate Analyser and PEDD Detection System. (1) Reagent storage (2) Sample storage (3) Peristaltic micro pumps containing Santropene® tubing (4) Waste storage (5) Tygon® tubing (6) PEDD flow cell (7) Mixing junction (8) Wixel microcontroller with breakout board containing wireless serial link and data logger (9) Glass flow cell (10) Detector LED at 630 nm (11) Emitter LED at 430 nm (12) Waste line (Tygon tubing). Nitrate sensors currently on the market predominantly use direct UV spectrophotometric screening, electrodes, or the cadmium reduction method, which in turn can be quite costly and/or prove difficult to implement due to the relatively intricate procedures involved, probability of interferences present and the limited detection ranges associated with various methods. There is therefore a major appeal to integrate this simple, direct method for the determination of nitrate into an autonomous platform. An area of concern that has been emphasized with this method is the use of 96% sulphuric acid (ca. 18 M) that must be present in the chromotropic acid reagent for effective formation of the nitrate complex. The strongly acidic environment drastically constrains the materials that can be used to store and move the reagent in the fluidic system. It is therefore of major interest to ensure the reliability and robustness of the materials used within the sensing platform. The materials such as the Tygon tubing used within the previous flow analysis platform had a shelf life of approximately two weeks of extensive use as the chemical compatibility was quite poor and resulted in a melting and discolouration effect. 121

Environmental Science & Technology 2014 Vol. 1 As a result an extensive study of over one year was performed on the chemical compatibility of the sulphuric acid and chromotropic acid reagent with various materials. Although this may seem relatively trivial, the managing and understanding of the fluidic components is key in realising a fully reliable deployable platform. The results are shown in table 1 and figure 2. TABLE 1. Chemical Compatibility Results.

Material

Compatibility

Polypropylene Polyurethane PTFE (Teflon) PVC (Polyvinyl chloride) Silicone Tygon® Tygon® Fuel(Lubricant) Tubing Neoprene Santoprene® Viton®

Severe effect Severe effect Excellent Severe effect Severe effect Severe effect Severe effect Severe effect Severe effect Excellent

FIGURE 2. Effects of ~98 % Sulphuric acid and chromotropic acid complex on various materials

FIGURE 3(A). Calibration curve from 0–80 mg/L NO3- and chromotropic acid complex. The standard deviations as represented as error bars (n=3). FIGURE 3(B). Field deployable platform for the detection of nitrate using chromotropic acid (1) robust and waterproof housing; (2) reagent and standard storage bags; (3) 12 V battery; (4) optical detection enclosure; (5) peristaltic pumps containing Viton Tubing. Viton® tubing is a brand of synthetic rubber and fluoropolymer elastomer from DuPont Performance Elastomers L.L.C. showing excellent resistivity to the chromotropic acid reagent. Subsequently, Viton tubing was incorporated into the peristaltic micro pump (Series 100, Williamson Manufacturing Company Ltd) previously used in the flow analysis platform, and set to continuously deliver 122

Environmental Science & Technology 2014 Vol. 1 sample and reagent via the Viton tubing over a one month period. Following the successful performance of the one month trial, the pump delivered reagent and sample to the mixing junction where the coloured complex formed passed through the PEDD detection system (O’ Toole et al., 2005) in a modified glass flow cell (Brand Ltd Cat. No.7477 15) for a period of 37 days. A calibration plot (figure 3A) was obtained and shown below using nitrate standards up to 80 mg/L NO3-. These results shown are significant as the extremely high content and aggressive nature of the sulphuric acid is no longer an issue for a field deployable platform. Although the chemistry has been previously optimised and validated in a previous study, this study on the chemical compatibility with plastics is noteworthy and will allow for the reliable integration into an autonomous platform shown in figure 3(B). AMMONIA DETECTION It is now evident that in order to maintain and acquire a reliable, reproducible and robust sensing platform, the fluidic handling strategies must remain as simple as possible. For the determination of ammonia, the Berthelot method was employed. In this method, an intensely blue coloured compound, indophenol, is formed in the presence of ammonia, hypochlorite and phenol catalysed by sodium nitroprusside. The most utilised variation of the Berthelot method incorporates a three step reagent process with the addition sequence and reaction time of the variants of this method playing an important role in the colour formation (Daridon et al., 2001). This method could prove problematic to implement in a low-cost fluidic monitoring platform due to the multiple stages involved. It was therefore imperative to simplify the Berthelot method to allow for easy integration into an autonomous platform while maintaining satisfactory analytical results. Phenol was replaced with sodium salicylate due to the high toxicity and reactivity of phenol. In a sodium hydroxide medium, the Berthelot reagent reacts with ammonium ions (NH4+) to produce a characteristic green colour (λmax at 660 nm arising from the use of salicylate rather than phenol). Recent studies simplified this to a two-stage reagent reaction sequence for the determination of ammonia in air. (Bianchi et al., 2012) This method was further developed for the determination of ammonia in water by employing a reagent pre-mix stage immediately prior to addition of the sample at a 1:1 v/v reagent to sample ratio. Reagent 1 (R1) contains 6.906g of sodium salicylate and 0.225g of sodium nitroprusside in 250 ml of 0.5 mol l-1 sodium hydroxide solution while reagent 2 (R2) contains 7.5 ml of sodium hypochlorite (10-15 % available chlorine, used as received, Sigma-Aldrich 425044), 7.5 ml of 1 mol l-1 sodium hydroxide in 250 ml volumetric flask with deionised water. Both reagents were protected from direct sunlight by storing under amber coloured glass.

FIGURE 4(A). Schematic of the analyser and microfluidic chip. FIGURE 4(B). Calibration curve using the ammonia microfluidic chip from 0-12 mg/L NH4+ Berthelot complex. The standard deviations are represented as error bars (n=3). This approach is necessary as the complete reagent mixture (R1+R2) is not stable, and must be freshly generated in-situ in order to obtain reproducible and accurate results. Following the optimisation of the measurement parameters, a validation process was implemented using 6 samples from various environmental sources. The samples were split, and parallel assays independently performed at the T.E. Laboratory site. The modified Berthelot method was performed and compared to reference measurements 123

Environmental Science & Technology 2014 Vol. 1 obtained using ion chromatography where an excellent correlation coefficient was obtained between the modified Berthelot method and ion chromatography. Figure 4(A) is a schematic of the microfluidic chip and illustration of the operating platform that was designed for the modified Berthelot reaction, showing the basic design and operation. The fluidic system comprises of sample intake, filtering unit, storage units for standards, reagents and waste and pumping system (comprising of pumps and valves) which controls the transport and mixing of the sample, standards and reagent; microfluidic detector chip; and waste storage. The pumping system comprises of 4 syringe pumps and check valves which were designed and built in-house and stepper motors with a total component cost of €74.00. This fluidic system controls the syringe plungers are used to deliver the sample and reagent via Tygon® tubing (I.D. 4.6 mm, Sigma Aldrich, Ireland) to the microfluidic mixing and detection chip. The optical detection system consists of a 660 nm LED (light emitting diode) with a photodiode detector which enables an absorbance reading to be carried out on the ammonia/Berthelot complex. The control and data layer consists of a microcontroller (MSP430, Texas Instruments) which controls the operation of the pumping system and optical detector, a micro-SD card (COM-08163, Sparkfun Electronics) for data storage; and a Wixel (WRL-10665, Sparkfun Electronics) for wireless communication using 2.4 GHz Radio. Power is provided by a 12 V, 4 Ah lead acid battery for autonomous operation, or by a mains power adapter for online operation. Reagents R1 and R2 are pumped into the reagent mixing channel in the microfluidic chip in a 1:1 v/v R1 to R2 ratio and the resulting mixture delivered to the sample mixing channel at a 1:1 v/v sample to reagent ratio and then pumped into the detector chip. The microfluidic chip shown in figure 4(A) was designed and built in-house, which is fabricated from UV-bonded layers of PMMA (poly methyl-methacrylate) into which a 0.5 mm channel has been formed by micro-milling. One side of the channel is adjacent to a mirrored surface. The 660 nm LED is oriented so that the light emitted is directed across the microfluidic channel, and reflected by the mirrored surface back across the channel to the photodiode, which converts the light intensity into a corresponding ADC value. The optical pathlength through the sample is effectively doubled so that the absorbance signal is increased in accordance with Beer’s law (Equation 1) without needing to increase the physical pathlength or affecting the sample volume. Beer’s law states that: A = ƐcL

(1)

Where A is absorbance, Ɛ is the extinction coefficient of the absorbing species, c is concentration, and L is pathlength. The method gave a linear response to ammonia concentrations up to 12 mg L-1 NH4+ after which the absorbance plateaus shown in figure 4(B). SIMPLIFIED COLORIMETRIC METHODS Although the colorimetric methods for the determination of ammonia and nitrate have been modified for the purpose of integrating into an autonomous platform, the methods also show great potential as rapid, simple and reliable lab bench methods. A study was conducted in the University of Sao Paulo (USP), Pirassununga, Brazil where case studies are on-going in the areas of nutrient detection in various water bodies such as waste water treatment plants, aquaculture aquariums and freshwater systems. The campus location was found to be ideal for monitoring such nutrients with these simple and rapid methods in the areas of waste water treatment, aquaculture studies and agriculture science, all of which require daily water quality monitoring. The monitoring was primarily focussed on an anaerobic-aerobic fixed bed bioreactor designed in USP that treats waste water effluent from a dairy farm located on campus. The bioreactor is part of an on-going long term study within USP and the manual monitoring of nutrients such as nitrate and ammonia play a crucial role in determining the overall performance of the bioreactor. Most of the routine water quality monitoring is currently carried out using HACH reagents and instrumentation (HACH DR 2800 spectrophotometer). Although this allows for easy and rapid determination of nutrients in water, discrepancies can arise as certain methods (including nitrate determination) can be sensitive to different mixing techniques and concentrations ranges associated with some of the HACH methods can be quite limited. As the chromotropic acid and the modified Berthelot method are based on standard methods and show excellent correlation with ion chromatography, the 124

Environmental Science & Technology 2014 Vol. 1 chromotropic acid method and the Berthelot method were compared daily to the on-going measurements achieved by USP, results for the nitrate and ammonia levels are shown in table 2. Various discrepancies can be found between the different methods mainly due to the limited ranges that the HACH methods offer but also due to the errors/inconsistencies in mixing the HACH reagents with sample that may vary from person to person. As a result, these methods will now be continued for water quality monitoring within the USP campus on a regular basis. TABLE 2. Comparison of results from anaerobic-aerobic fixed bed bioreactor. Bioreactor Nitrate

Ammonia

HACH Chromotropic Handheld Sample Run HACH DR 2800 Acid Method colorimeter DR 900 59.22 73.21 70 1 70.88 45.5 43.877 2 2.5 6.54 8.1 3 25.69 26.2 8 4 0.5 0.66 0.5 5

Sample Run

Nesslerization

Modified Berthelot Method

1 2 3 4

Out of Range 6.8 19.24 0.13

21.689 10.03 31.72 10.5

HACH Handheld colorimeter DR 900 Out of Range 12.8 6.99 16

CONCLUSION The long-term deployment of chemical analysers is hindered by the lack of robust and reliable chemical sensing platforms. While much research is focused on the development of prototype sensors work must be achieved in transcending this research into the real analytical world. The progress in automated flow injection analysis (FIA) systems is prohibited by large sample volumes which results in high consumption of reagents and standards. The focus has now turned to microfluidics for the miniaturisation of these analytical techniques.(Marle & Greenway, 2005) Through the miniaturisation of these devices and keeping the fluidic design as simple as possible, the overall reliability of the systems can be improved while reducing cost. The major focus is on real deployments with these modified approaches for in situ environmental monitoring. The emphasis will be on the real issues related to the analytical approach and sampling within environmental waters and in particular, keeping the sensor platform operating autonomously over time. ACKNOWLEDGEMENTS The authors wish to thank the QUESTOR Centre (grant code DCU9/11/14) and Enterprise Ireland (grant code IP/2011/0103). REFERENCES Bianchi, F., Dommen, J., Mathot, S., & Baltensperger, U. (2012). "On-line determination of ammonia at low pptv mixing ratios in the CLOUD chamber." Atmospheric Measurement Techniques, 5(7), 17191725. doi:10.5194/amt-5-1719-2012 Cleary, J., Maher, D., Slater, C., & Diamond, D. (2010). "In situ monitoring of environmental water quality using an autonomous microfluidic sensor." Paper presented at the Sensors Applications Symposium (SAS), 2010 IEEE, 36-40. Cogan, D., Cleary, J., Phelan, T., McNamara, E., Bowkett, M., & Diamond, D. (2013). "Integrated flow analysis platform for the direct detection of nitrate in water using a simplified chromotropic acid method." Analytical Methods, 5(18), 4798-4804. doi:10.1039/C3AY41098F Daridon, A., Sequeira, M., Pennarun-Thomas, G., Dirac, H., Krog, J. P., Gravesen, P. de Rooij, N. F. (2001)."Chemical sensing using an integrated microfluidic system based on the berthelot reaction." Sensors and Actuators B: Chemical, 76(1-3), 235-243. doi:10.1016/S0925-4005(01)00573-1

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Environmental Science & Technology 2014 Vol. 1 Diamond, D. (2004). "Internet-scale sensing. Analytical Chemistry," 76(15), 278A-286A. doi:10.1021/ac041598m Marle, L., & Greenway, G. M. (2005). "Microfluidic devices for environmental monitoring." TrAC Trends in Analytical Chemistry, 24(9), 795-802. doi:http://dx.doi.org/10.1016/j.trac.2005.08.003 O’ Toole, M., Lau, K. T., & Diamond, D. (2005). "Photometric detection in flow analysis systems using integrated PEDDs." Talanta, 66(5), 1340-1344. doi:10.1016/j.talanta.2005.01.054

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QUAL2K WATER QUALITY ANALYSIS AND SOURCE LOCATIONS IDENTIFICATION: A CASE STUDY OF NORTH BUFFALO STREAM Jenberu Feyyisa, Shoou-Yuh Chang, Samuel Massie (North Carolina Agricultural and Technical State University, Greensboro North Carolina, 27401, USA) City waters are suffering from waste release that grows at an alarming rate. QUAL2K is a framework that helps simulate the water quality of streams and rivers. It approximates complex physical, chemical and biological processes of streams and rivers through a simplified representation. By considering the stream as one-dimensional, steady-state and non-uniform flow, QUAL2K calculates water quality kinetics for the stream/river under consideration. It involves setting up of model components; reaches, elements, hydraulic and kinetic parameters, initial conditions for hydrodynamic and water quality simulation. This model is used to simulate one of the impaired waters of North Carolina, North Buffalo stream against its designated purpose (aquatic life propagation). The 20.5 kilometer of North Buffalo stream channel was divided into six (6) reaches and one hundred and four (104) elements each with 200 m. Before modeling water quality, hydraulic parameters of the stream reaches were simulated and predicted for two different flow seasons of the year, summer and winter. Based upon the calibrated stream channel hydraulic parameters, we obtained good agreement between calibration of August 2, 2007 and prediction for January 4, 2007 with their respective measurements. The model approximates waste load locations for the selected critical flow condition and also indicates DO condition along the stream reaches and segments.

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TECHNICAL, FINANCIAL AND ADMINISTRATIVE CAPACITY EVALUATIONS AND IMPROVEMENT OF SMALL COMMUNITY WATER SYSTEMS IN PUERTO RICO Adaíl Alicea-Martínez, Rafael A. Rios (University of Puerto Rico Río Piedras, Environmental Sciences Department, San Juan, Puerto Rico, USA) ABSTRACT: In Puerto Rico, 3% of the population gets its drinking water from approximately 250 small community water systems, that are managed by the communities but still have to fully comply with the Safe Drinking Water Act and state regulations. This study had a duration of two years and its objective was the evaluation of 48 community water systems in Puerto Rico with a Capacity Development Form (CDF) which measures their technical, administrative and financial capacity and combines it into a total capacity rating. There was an initial and final evaluation to measure changes in capacity once the needs where identified at the beginning and a circuit rider program was implemented. A scale from 0 to 100% was used to measure each capacity. It was found that on average the aqueducts had a total capacity of 47% at the beginning, but at the end they improved on the three categories. The level of improvement varied with factors like the level of commitment of the community leader with the aqueduct, the economic means of the community and the education of its members. These factors, which are numerically intangible because they have to do with environmental justice more that with numbers, were not assessed by the CDF.

INTRODUCTION Water conservation is important for drinking, food confection, and recreational uses because it is a limited source and is essential to life. Water quality can be compromised because of infectious agents, toxics and other hazardous compounds (WHO, 2010a). The World Health Organization (2013) established that for 2011 around 768 million people used unimproved sources of drinking water and 83% of the population without access to better sources of water lived on rural areas. People from rural areas get their drinking water from small community water systems that are managed by operators who typically are members of the community and lack training in the system. (WHO, 2010b).The United States Environmental Protection Agency (USEPA) has established that 300.2 million people in the United States obtain their potable water from 52,873,000 community water systems (USEPA, 2010). In Puerto Rico, 3% of the population obtains potable water from small community water systems and 97% from the Puerto Rico Aqueducts and Sewer Authority (PRASA) (DOH, 2008). PRASA, which is the only entity in the United States that serves practically a whole state, is a public corporation created on 1945, (“Ley de Acueductos y Alcantarillados de Puerto Rico” Act Num. 40, May 1, 1945, as amended) whose purpose is to provide an adequate drinking water service to the people of Puerto Rico (PRASA, 2014). However, the other 3% of the population has been excluded because the construction and operation of PRASA aqueducts in distant and rural areas was not economically feasible. In the 1950’s people from the rural areas who lacked access to potable water decided to do by themselves the construction of community water systems to get drinking water (Marti, et al., 2004). A community water system is defined as a water system on rural areas operated by the residents of the community (DOH, 2008) commonly known in Puerto Rico as Non-Puerto Rico Aqueducts and Sewer Authority (Non-PRASA). Typically a NonPRASA system is composed of a source of water, a storage tank and a distribution line (Figure 1). At the present time, there are approximately 250 Non-PRASA systems that provide potable water to approximately 125, 000 persons. These systems have evolved and improved over time depending on the population and the resources of the community. They vary from one another, some of them with more than one source of water and storage tanks, with disinfection processes and others with more than one distribution line (Figure 2). There have been significant efforts to develop drinking water quality standards and better infrastructure for public potable water systems, but there are still public health risks related to poor water quality. Specifically, small rural aqueducts are more vulnerable to water related illnesses than public water systems (WHO, 2010a). However, although some of them have improved, because of the increase on 128

Environmental Science & Technology 2014 Vol. 1 population due to the immigration from urban to rural areas and the increase on federal and state regulations, the Non-PRASA systems are confronting problems, specifically on complying with the Safe Drinking Water Act (SDWA) (Martí, et. al., 2004).

FIGURE 1. Photos of Water Source (Well), Storage Tank and Distribution Line.

FIGURE 2. Aerial Photo of a Community Water System (Non-PRASA System) in Barranquitas, Puerto Rico including five water sources (four underground and one superficial), f our storage tanks and a community office. In 1996, Congress amended the SDWA with the purpose of assisting the states and the public water systems to provide safe drinking water. The 1996 amendments established a program that encouraged the strengthening of technical, administrative and financial capacity of water systems for the purpose of 129

Environmental Science & Technology 2014 Vol. 1 providing safe drinking water (USEPA, 2012a). The U.S. Environmental Protection Agency (2012b) states that a capacity development program in small community water systems provides a framework in which both the governmental agencies and the small aqueducts work in collaboration with one another to have the tools necessary for the systems to achieve the needed capacity and comply with SDWA regulations. This study had a duration of two years. The objective was to evaluate 48 community water systems using a capacity development evaluation form at the beginning and at the end of the study. The purpose was to measure if there was an improvement on the three capacities after a circuit rider program was implemented and an action plan was developed with the community’s inputs. MATERIALS AND METHODS We used a Capacity Development Evaluation Form developed by the Department of Health, Potable Water Division of Puerto Rico, to perform the evaluation of 48 community water systems around the island (Figure 3). We performed two evaluations, one at the beginning of the project and another at the end. We wanted to measure their technical, administrative and financial capacity to determine the status of the aqueducts at the beginning of the study. A scale from 0 to 100% was used to determine each capacity and a total capacity for the aqueducts. The technical capacity is the physical and operational ability of a system to meet the regulatory requirements for drinking water, the administrative capacity is the system's ability to conduct its administrative matters so that the system can achieve and maintain compliance and the financial capacity is the system's ability to acquire and maintain sufficient financial or economic resources to enable it to achieve and maintain compliance with the Safe Drinking Water (DOH, 2010) (Figure 4). The Capacity Development Evaluation form includes questions related to the following areas: infrastructure, system operation, sampling, reports, organization system, embedding system, budget procedure, budget and income.

FIGURE 3. Municipalities (shaded) in which the capacity evaluation was performed on 48 Community Water Systems. During the two year period, a Circuit Riders Program was implemented by the Department of Health, Potable Water Division, in which trained personnel routinely visited the aqueducts to help them improve their systems. At the end of the study we wanted to measure if there was a change on the three capacities. All the evaluations were provided to the managers or leaders of the aqueducts. After the first evaluations were performed an action plan was designed for each system individually. In this way, the community played an active role in the prioritization of the necessities that had to be addressed to make the system comply, with the periodic assistance of technical personnel. RESULTS The results were based on the technical, administrative and financial capacity of the systems. We calculated an average for the 48 community water systems for the first evaluation and the final evaluation, after implementing the Circuit Riders Program and developed an action plan for each community. The first 130

Environmental Science & Technology 2014 Vol. 1 evaluation on technical capacity presented an average of 59.25%, while at the end the average was 70.95%, showing an increase of 11.70%. The administrative capacity presented an average of 40.86% at the beginning, while at the end the value was 58.81%, showing an increase of 17.95%. The financial capacity was 39.47% for the initial evaluation whereas the final evaluation presented an average of 42.90% with an increase of 3.43%. Figure 5 shows the average capacity per area at the beginning and at the end of the two year period for the 48 community water systems.

Percentage (%)

FIGURE 4: Technical, Administrative (Managerial) and Financial Capacity Development Process.

100 90 80 70 60 50 40 30 20 10 0

Beginning of Study

End of Study

Technical Capacity Average

59.25

70.95

Beginning of Study

End of Study

Administrative Capacity 40.86

58.81

Beginning of Study

End of Study

Financial Capacity 39.47

42.9

FIGURE 5. Technical, Administrative and Financial Capacity Average at the Beginning and at the End of the Study for 48 Community Water Systems in Puerto Rico. After each capacity rating was calculated for each community, we calculated a total capacity for each community. Then, we determined an average for the 48 communities for the total capacity values. At the beginning of the study the average for total capacity was 46.66% but after giving advise and routine 131

Environmental Science & Technology 2014 Vol. 1 visits to the managers of the aqueducts, we obtained a value of 57.69% in the final evaluation with an increase of 11.03% in total capacity (Figure 6). 100 90 80 70 60

Percentage (%)

50 40 30 20 10 0

Beginning of Study

End of Study Total Capacity

Average

46.66

57.69

FIGURE 6. Total Capacity Average for 48 Community Water Systems in Puerto Rico. DISCUSSION AND CONCLUSIONS It is hoped that each aqueduct will get a value near 100% for each capacity and a total capacity value. As the system is closer to 100%, we can say that the aqueduct is complying with state and federal regulations. After completing the evaluations and getting information from the leaders on the community and the aqueducts, we gathered informal data in addition to the one included on the Capacity Development Form. We concluded that there are several factors that could be affecting the final results of the evaluation but has nothing to do with the water quality of the small water system. The Capacity Development Form included questions related as to the legal titles of the land on with the source of water and/or storage tanks were constructed. The construction of the aqueducts started in the 1950's and land owners donated the land (without legal documents) to the community to build their systems. At the present time, it is almost impossible to find those persons or their family that could complete the legal documents to donate the land to the community. Another example is related to the need for a certified operator for the systems. The state and federal regulations establish that the aqueducts must have a certified operator managing their systems. To get the certification, it is required that the person must have 15 college credits on sciences or mathematics, even if they pass the test. Many of the leaders of the aqueducts only have a high school education at most. So, it is difficult to get the leaders to accomplish that requirement. There are some of them that passed the certified operator test but the governmental agencies did not give them the certification because they do not have the college credits, even when they have the knowledge and skills necessary to work with the aqueduct safely and maintain a high standard of water treatment. These are just two examples of several questions that made the aqueducts score low on capacity but had nothing to do with the water quality. The Capacity Evaluation Form has no room to take into consideration aspects like the ones mentioned above but that affect the final capacity. There should be a revision of the Capacity Form to include aspects specific for these community water systems. These aspects have more to do with environmental justice than with numbers and will affect the final results, producing figures far from the reality of each community. ACKNOWLEDGMENTS This research was supported by NSF IGERT Grant # 0801577. We would like to thank the Department of Health, Potable Water Division and the communities that allowed us access to their systems. 132


REFERENCES Department of Health of Puerto Rico. 2008. “Informe Anual de Violaciones Sistemas Públicos de Agua Potable Puerto Rico 2008”. Retrieved on January 26, 2014 from http://www.salud.gov.pr/Informacion/ Documents/InformeAnualdeviloacionesAguaPotable2008.pdf Department of Health of Puerto Rico. 2010. “Desarrollo de Capacidad: Manual Dirigido a Sistemas Comunales Pequeños de Agua Potable para Desarrollar y Mantener Capacidad Técnica, Financiera y Administrativa”. “Ley de Acueductos y Alcantarillados de Puerto Rico” Act Num. 40 from May 1, 1945, as amended. “Maps of 78 Municipalities of Puerto Rico”. Retrieved on March 26, 2014, from, http://mapsof.net/map/map-of-the-78-municipalities-of-puerto-rico. Martí, J. A., R.E. Renta and C. Velázquez. 2004. “Actualización del Inventario: Sistemas de Acueductos Independientes en Puerto Rico (Non-PRASA)”. Retrieved on February 1, 2014, from http://www.bvsde.paho.org/bvsAIDIS/PuertoRico29/martir.pdf Puerto Rico Aqueduct and Sewer Authority. 2014. “Nuestra Autoridad”. Retrieved on February 26, 2014, from http://www.acueductospr.com/NUESTRAAUTORIDAD/vision.htm U.S. Environmental Protection Agency. 2010. Fiscal Year 2010 Drinking Water and Ground Water Statistics. Report EPA 817K11001. U.S. Environmental Protection Agency. 2012a. The Safe Drinking Water Act Amendments of 1996. http://water.epa.gov/lawsregs/guidance/sdwa/theme.cfm U.S. Environmental Protection Agency. 2012b. What is Capacity Development? http://water.epa.gov/type/drink/pws/smallsystems/basicinformation.cfm#what_is_capacity_developme nt World Health Organization, Water sanitation and health. 2010a. Small community water supply management. Retrieved on December 8, 2013, from http://www.who.int/water_sanitation_health/ dwq/smallcommunity/en/index.html World Health Organization 2010b. Small and Safe: Investing in small community water supplies will reduce waterborne disease outbreaks and overall costs. Retrieved on February 5, 2014, from http://www.who.int/water_sanitation_health/ WHS_WWD2010_small_systems_2010_4_en.pdf?ua=1 World Health Organization. 2013. Progress on sanitation and drinking-water - 2013 update. Retrieved on April 26, 2014, from http://apps.who.int/iris/bitstream/10665/81245/1/9789241505390_eng.pdf

133


SIMULTANEOUS REMOVAL OF AMMONIA AND NITRATE BY ELECTROLYTIC DECOMPOSITION AS TERTIARY TREATMENT Jing Ding, Wei Li, Qingliang Zhao, Kun Wang and Junqiu Jiang (Harbin Institute of Technology, Harbin, Heilongjiang Province, China) ABSTRACT: To mitigate eutrophication risk caused by nitrogen species left in domestic wastewater effluent, nutrient compounds that are not removed after biological treatment should be eliminated by a tertiary treatment. In this paper, a divided electrochemical cell with cation membrane was developed for simultaneous anodic ammonia oxidation and cathodic nitrate reduction. The performance of electrochemical process with different chloride ion concentration was investigated. A mathematical model developed from the variations of parameters results was presented, and fits the experimental ammonia removal results well. Chloride exerted the strong influence on the oxidation rate of ammonia and the presence of free chlorine showed indirect oxidation mechanism was predominant in anodic compartment. The influence of chloride on nitrate reduction rate was less than that on ammonia removal. Nitrate reduction was fitted to pseudo-first order equation with the values of kinetic constants (0.11-0.84 L/Ah) obtained. The main product of electrolytic decomposition was nitrogen gas, since the total nitrogen in wastewater decreased due to a high removal of 74%. These results clearly showed the potential of this electrochemical system to serve as a tertiary wastewater treatment for simultaneous removal of ammonia and nitrate. INTRODUCTION Aqueous nitrogen species left in domestic wastewater effluent are one of the nutrient sources in environmental nature water (Pernet-Coudrier et al., 2012). In some specific area, nutrient species still need to be further removed and the concentration needs to go to a lower level to mitigate eutrophication risk to the environment. The residual ammonia in the domestic effluent could be further removed or decomposed by treatments such as activated carbon adsorption, breakpoint chlorination, ion exchange, electrochemical oxidation and so on (Xiao et al., 2009). Electrochemical process has been the focus by many researchers as its advantages of high efficiency, no sludge operation, small area occupied and relatively low cost (Li et al., 2009; Souza-Garcia et al., 2009; Fan et al., 2013). Previous studies have attempted to investigate the feasibility of anodic ammonia oxidation (Panizza and Cerisola, 2004; Vanlangendonck et al., 2005; Kapałka et al., 2010; Gendel and Lahav, 2012) or cathodic nitrate reduction (Szpyrkowicz et al., 2006; Mattarozzia et al., 2013; Dortsiou et al., 2013) separately, and the combined performance of cathodic reduction for nitrate and anodic oxidation for ammonia and nitrite to improve the selectivity from nitrate to nitrogen and the efficiency of electrochemical denitrification. (Reyter et al., 2010; Fan et al., 2013). However, rare information is available about the combination of anodic and cathodic decomposition for simultaneous removal of both ammonia and nitrate in wastewater. Thus, the objective of this study was to investigate the capability of total nitrogen (TN) elimination in the two-chamber electrolysis system separated by cation membrane. The influence of chloride ion for ammonia and nitrate removal was also revealed so as to obtain the removal mechanism and kinetic. MATERIALS AND METHODS Batch experiments were performed in a laboratory scale. The electrochemical reactor was constructed with Ru-Ir-Sn/Ti anode and graphite felt cathode by Pyrex glass (60mm×60mm). The reactor was comprised anodic and cathodic chamber which were pressed up onto either side of a cation membrane. The simulated effluent was stored in a glass vessel and continuously recirculated in anodic and cathodic chamber by two peristaltic pumps. The synthetic solution was prepared with NaCl, (NH4)2SO4 and NaNO3. Electrolysis process was carried out at constant current density and ambient temperature. Samples were taken after fixed time interval, but the decrease in pollutant concentration as well as the evolution of other parameters in the following section was represented against the specific electrical charge (Q), which is calculated according to electrolysis time and current density. It could represent a means of comparing the efficiency of the process at different scales, regardless of current density applied. 134

Environmental Science & Technology 2014 Vol. 1 Ammonia, nitrate, nitrite, TN, chloride and free chlorine were analyzed for the samples collected. Ammonia was measured by Nessler reagent spectrophotometry. Nitrate, nitrite and chloride ions were measured by ion chromatography (Dionex ICS3000) with a Dionex Ion Pac AS11-HC 4×250 mm Anion Exchange column, using KOH as eluent at 1 mL/min. TN was quantified by carbon analyzer (Shimadzu TOC-VCPN). Free chlorine was measured with the N, N-diethylp-phenylenediamine (DPD) ferrous titrimetric method. RESULTS AND DISCUSSION Ammonia Oxidation. In order to investigate ammonia oxidation rate, 10 experiments were carried out, the design and results of which are described in Table1, and the model based on 1stOpt software developed from the experimental results is expressed as in Eq.(1). The results indicated that ammonia removal rate was positively influenced by the chloride ion, as the free chlorine, including Cl2, HOCl and OCl- which was generated around the anode and dependent on chloride concentration. Conversely, the increase of initial ammonia concentration had negative effect on ammonia removal. This result was in accordance with the previous studies which had reported ammonia oxidation rate (k) primarily depends on the parameters of current density, chloride concentration and ammonia concentration (Vanlangendonck et al., 2005). Indirect oxidation by free chlorine was the main mechanism for ammonia removal, simplified as reaction Eqs. (2-4) (Kapałka et al., 2010). Ammonia removal rate in this study was calculated with increased Q, which was regardless of the variation of current density. +

NH 4 −1.389 Cl - 0.65 k = 0.677 × ( ) ×( ) 14 35.5

R2=0.9976

（1）

Where Cl- represented the chloride concentration (mg/L-Cl), and NH4+ was the initial ammonia concentration (mg/L-N).

2Cl-→Cl2 +2 eCl2 +H2O→HOCl+ Cl-+H+ 2NH4++3HOCl→N2 +3H2O +5H+ +3Cl-

（ 2）（ 3）（ 4）

In the domestic effluent, nitrate was left with ammonia after biological nitrification and denitrification. The investigation of ammonia electrooxidation in the presence of nitrate was essential. Fig.1 showed the comparison of experimental results and model estimations for ammonia oxidation when ammonia and nitrate simultaneously exists in the system. The result of model simulation in Eq.(1) coincided with the experiment and shown similar patterns for the ammonia removal when Cl- was 450 and 990 mg/L. A larger deviation of removal tendency was indicated in Fig.1 when Cl- was 90mg/L, which was attributed to the existence of nitrate in the system. TABLE 1. Ammonia oxidation rate obtained in the design of experiments with variable parameters 1 2 3 4 5 6 7 8 9 10

Cl-(mg/L-Cl) 200 40 80 200 300 400 200 800 200 2000

NH4+(mg/L-N) 10 20 20 20 20 20 40 40 100 100

135

Ammonia oxidation rate(k, mg/Ah) 33.292 6.414 13.962 27.52 33.818 38.21 20.54 46.228 12.34 64.34


1 Experiment-90mg/L Cl Experiment-450mg/L Cl Experiment-990mg/L Cl Model-90mg/L Cl Model-450mg/L Cl Model-990mg/L Cl

+ 0

0.8

+

NH4 /NH4

0.6 0.4 0.2 0 0

0.5

1 Q（Ah/L）

1.5

2

FIGURE 1. Experimental and model estimation for ammonia removal as Q increased with the change of chloride (Initial Ammonia: 20mg/L-N; Initial Nitrate: 20mg/L-N) The presence of free chlorine in anodic chamber with different concentration chloride ions was shown in Fig.2. Free chlorine was maintained at less than 3mg/L with chloride 90mg/L. At chloride 450mg/L, the amount of free chlorine was lower than 10mg/L, followed by linear increasing with Q after 0.5Ah/L, when ammonia had been removed totally. Similar increase trend of free chlorine was also found in chloride 990mg/L. This verified indirect oxidation was predominant mechanism in anodic compartment, and the produced chlorine reacted with ammonia rapidly. Electric charge would be used to continuously produce free chlorine, and then free chlorine was enriched without ammonia in the system according to the Eq. (3-4).

（

Free Chlorine (mg/L-Cl)

80

60

90mg/L Cl 450mg/L Cl 990mg/L Cl 3 y = 40.944x - 6.1032

40

R = 0.9909

2

y = 38.58x - 15.112 2

R = 0.9776

20

0 0

0.5

1 Q（Ah/L）

1.5

2

FIGURE 2. Free chlorine generation in the solution as a function of chloride Nitrate Reduction. Fig.3 presented the nitrate reduction as the function of chloride concentration with or without ammonia in the system. Kinetic estimation according to pseudo first order kinetic model, as expressed in Eq.(5), was also shown in Fig.3 and the results of simulation was given in Table.2. The kinetic constant varied from 0.11 to 0.84 L/Ah. Szpyrkowicz reported that nitrate reduction process in the cathodic chamber followed the Eqs. (5-7) (Szpyrkowicz et al., 2006). Ammonia in the electrolysis system seemed to exert negative influence to nitrate reduction, due to the Eq.(7). Less influence of chloride was found on nitrate reduction than ammonia oxidation, attributed to different reaction mechanisms.

136


−

（NO3 ）t - ln = kt − （NO3 ）0

(5) 1

0.9

-

-

NO 3 /NO 3 0

0.8 0.7 450mg/L Cl 990mg/L Cl 90mg/L Cl 90mg/L CL no ammnoina

0.6 0.5 0.4 0

0.5

1

1.5 2 Q（Ah/L）

2.5

3

3.5

FIGURE 3. Experimental and kinetic estimation for nitrate reduction as Q increased with the change of chloride (Initial Nitrate: 20mg/L-N) NO3-+H2O+2e-→NO2- +2OHNO3-+5H2O+6e-→NH3 +7OHNO3-+2H2O+5e-→1/2N2 +6OH-

(6) (7) (8)

TABLE 2. Nitrate reduction constant with the variation of chloride and ammonia Cl-(mg/L-Cl)

NO3-(mg/L-N)

NH4+(mg/L-N)

k(L/Ah)

R2

1

90

20

20

0.2675

0.9495

2

450

20

20

0.1106

0.9441

3

990

20

20

0.1228

0.9786

4

90

20

0

0.8356

0.9648

1 90mg/L Cl 450mg/L Cl

0.8

TN/TN0

990mg/L Cl 0.6 0.4 0.2 0 0

0.5

1

1.5 2 Q（Ah/L）

2.5

3

3.5

FIGURE 4. The elimination of TN as Q increased with the change of chloride 137

Environmental Science & Technology 2014 Vol. 1 Total Nitrogen Removal. It was noticed that nitrate reduction in cathodic chamber may cause the derivation of ammonia and nitrite, as shown in Eqs. (6-7). Therefore, TN concentration was essential to be determined to inspect the conversion of nitrogen species in aqueous phase to nitrogen gas. Fig.4 presented TN removal as Q increased with different chloride concentration, and the results indicated that the conversion from ammonia and nitrate to nitrogen gas in this system was efficient, with the highest TN removal of 74% at the end of experiment. The efficiency of TN removal increased with chloride concentration, due to the positive effect of chloride to ammonia removal. CONCLUSIONS This study demonstrated that chloride had positive influence on ammonia removal in anodic chamber, as the ammonia was oxidized by an indirect mechanism via free chlorine. The removal model satisfactorily fitted the experimental results when chloride concentration was 450 and 990mg/L. The occurrence and increase of free chlorine as Q increased verified the rapid reaction of ammonia and chlorine. Nitrate reduction in the cathodic chamber followed pseudo first order kinetic, with the kinetic constant varied from 0.11 to 0.84 L/Ah. 74% removal efficiency of TN was achieved in the system, which provided the feasibility of the system on the conversion of the different nitrogen species to nitrogen gas. ACKNOWLEDGEMENTS This research was funded by Project 51121062 (National Creative Research Groups) supported by National Nature Science Foundation of China, the National Critical Scientific and Technological Project of Water Pollution Control and Management (2012ZX07201003-002). REFERENCES Pernet Coudrier, B., W.X. Qi, H.J. Liu, B. Müller and M. Berg, 2012. “Sources and pathways of nutrients in the semi-arid region of beijing-tianjin, China”. Environ. Sci. Technol., 46 (10):5294-5301.

Xiao, S.H., J.H. Qu, X. Zhao, H.J. Liu, D.J. Wan, 2009. “Electrochemical process combined with UV light irradiation for synergistic degradation of ammonia in chloride-containing solutions”. Water Res., 43(5),1432-1440. Li, M., C.P. Feng and Z.Y. Zhang, 2009. “Efficient electrochemical reduction of nitrate to nitrogen using Ti/IrO2–Pt anode and different cathodes”. Electrochim. Acta, 54:4600-4606. Souza-Garcia, J., E.A. Ticianelli, V. Climent and J.M. Feliu, 2009. “Nitrate reduction on Pt single crystals with Pd multilayer”. Electrochim. Acta, 54(7): 2094-2101. Fan, N., Z. Li, L. Zhao, N. Wu and T. Zhou, 2013. “Electrochemical denitrification and kinetics study using Ti/IrO2-TiO2-RuO2 as the anode and Cu/Zn as the cathode”. Chem. Eng. J., 214: 83-90. Panizza, M. and G. Cerisola, 2004. “Electrochemical oxidation as a final treatment of synthetic tannery wastewater”. Environ. Sci. Technol., 38(20):5470-5475. Vanlangendonck, Y., D. Corbisier and A. Van Lierde, 2005. “Influence of operating conditions on the ammonia electro-oxidation rate in wastewaters from power plants (ELONITATM technique)”. Water Res.,39(13):3028-3034. Kapałka, A., A. Katsaounis, N.L.Michels, A.Leonidova, S.Souentie, C.Comninellis and K.M. Udert, 2010. “Ammonia oxidation to nitrogen mediated by electrogenerated active chlorine on Ti/PtOx-IrO2”. Electrochem. Commun., 12 (9):1203-1205. Gendel, U. and O.Lahav, 2012. “Revealing the mechanism of indirect ammonia electrooxidation”. Electrochim. Acta, 63:209-219. Szpyrkowicz, L., S. Daniele, M. Radaelli and S. Specchia, 2006. “Removal of NO3- from water by electrochemical reduction in different reactor configurations”. Appl. Catal. B -Environ., 66 (1-2): 4050. Mattarozzia,L., S. Cattarina, N. Comisso, P. Guerriero, M. Musiani, L. Vazquez-Gomez and E. Verlato,2013. “Electrochemical reduction of nitrate and nitrite in alkaline media at CuNi alloy Electrodes”. Electrochim. Acta, 89:488-496.

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Environmental Science & Technology 2014 Vol. 1 Dortsiou, M., I. Katsounaros, C. Polatides and G. Kyriacou, 2013. “Influence of the electrode and the pH on the rate and the product distribution of the electrochemical removal of nitrate”. Environ. Technol., 34(3):373-381. Reyter,D., D. Bélanger and L. Roué, 2010. “Nitrate removal by a paired electrolysis on copper and Ti/IrO2 coupled electrodes-Influence of the anode/cathode surface area ratio”. Water Res., 44(6): 1918-1926.

139


EFFECTS OF APPLICATION TIME OF EXTERNAL ELECTRIC FIELD ON ANAMMOX BIOMASS ACTIVITY Sen Qiao, Xin Yin, Jiti Zhou (Dalian University of Technology, Dalian, China) ABSTRACT: In this study, the effects of different application time of external electric field were studied in two identical UASB reactors. The effects of three kinds of distribution modes in the total electric field applied time of 12h/24h at 2V/cm were investigated. When the impulse application time of electric field was 3h, 6h and 12 h in one cycle, the nitrogen removal rates increased 18.7%, 27.4% and 8.5%, respectively, compared with control experiment. Moreover, after the reactor with electric field was running smoothly at the optimal condition (6 h application-6 h resting) for about 215 days, the TN nitrogen removal rate reached a high value at 6468 g-N/m3/d, which was 45% much higher than that of the control. The increase of crude enzyme activities demonstrated to be the main reason for the enhancement of nitrogen removal on the anammox process. Additionally, transmission electron microscope observation proved the morphological change of anammox biomass under electric field application, which might contribute to the substrate rapid turnover and more storage. INTRODUCTION Anaerobic ammonium oxidation (anammox) has already been recognized as an innovative nitrogen removal technology for wastewater treatment (Mulder et al., 1995). Compared with the conventional biological processes (nitrification-denitrification), anammox process offers significant advantages such as no demand for oxygen and organic carbon, low sludge production and reduced CO2 or N2O emissions (Op den Camp et al. 2006). However, extremely slowly growth rate of anammox bacteria with a doubling time of 11-20 days (Strous et al. 1999) causes the longer start-up period. Consequently, enhancing the activity of anammox bacteria or shortening the start-up period of anammox reactors is a subject of great interest and challenge. Recently, external electric field might be another effective approach to enhance biomass activity. The application of electric fields for influencing cell biology was a readopted topic in biological field for several decades. The specific sensitivity of biological cells towards electric fields was since then being exploited for various purposes such as cell growth, cell killing, diagnostics, sensing devices, healing or gene transfer purposes (Amarjargal et al. 2013). When cells are exposed to electric fields, the polarization of the cell membrane and its components takes place, which may further lead to the following phenomena, such as rotation, cell membrane permeability and osmotic imbalance (Barnes et al. 2007). Moreover, some researchers have showed that the activation of enzyme would be possible by pulsed electric field treatment (Takayuki et al. 2007). Additionally, bioelectrical systems were also used to improve the growth rate of aerobic iron oxidation microorganisms and anaerobic lithotrophic iron reduction microorganisms (Ohmura et al. 2002). Thus, external electric field could increase the activity of various biomass including the enzyme activity enhancement and cell growth according to the literatures mentioned above. Therefore, we could deduce that the external electric field might exert the similar effects on anammox biomass. However, until now there existed no related-reports focusing on the application of electric field on the activity of anommox biomass. Our preliminary batch experimental results demonstrated that anamox biomass activity could be increased by external electric field (2 V/cm). However, 24 h continuous application would definitely depress anammox biomass activity at the range between 1 and 4 V/cm (Qiao et al., 2013). Thus, the main aim of this study was to investigate the effects of external electric field on the activity of anammox biomass with relatively shorter application time. Furthermore, we also explored the effects mechanism, such as the variation of crude enzyme activity and cell morphology. MATERIALS AND METHODS 140

Environmental Science & Technology 2014 Vol. 1 The anammox biomass used for continuous experiments originated from a laboratory-scale anammox upflow column reactor in our lab. Anammox bacteria of KSU-1 strain (AB057453.1) accounted for about 70-75% of the total biomass in seed biomass by FISH observation. Two identical upflow fixedbed column reactors, R1 (the control reactor, without electric field application) and R2 (with electric field application), were applied for continuous experiments. The working volumes were about 0.5 L with the inner diameter of 5 cm and the height of 25 cm. All the reactors contained 50 g (wet weight) anammox biomass resulting in an initial MLVSS concentration of 4920 mg/L for each reactor. Our preliminary experimental results demonstrated that anamox biomass activity could be increased by external electric field (2 V/cm). However, 24 h continuous application would definitely depress anammox biomass activity at the range between 1 and 4 V/cm (Qiao et al., 2013). We predicted that application time was another key factor to influence anammox biomass activity besides the electric intensity. Hence, the application time of external electric field was determined as 12 h per day in this study. For operational convenience, the application time and resting time was set as 3h-3h, 6h-6h, 12h-12h in one cycle, respectively. The applied electric field intensity of the whole continuous experiments was determined as 2V/cm based on our preliminary experimental results. The detailed running conditions of R2 were shown in Table 1. Fig. 1. Schematic diagram of two identical anammox reactors, R2 with electric field application and R1 without electric field.

Application modes Phase Application time--resting time Cycles/day Application time per day

Table 1. The detailed running conditions of R2 during the whole continuous experiments. Mode 1 I 3h-3h 4

Mode 2 Mode 3 II III 6h-6h 12h-12h 2 1 12h/24h

Mode 2 IV 6h-6h 2

Concentrations of nitrite and nitrate were determined by using an ion-exchange chromatography (ICS-1100, DIONEX, AR, USA) with an IonPac AS18 anion column after filtration with 0.22 µm pore size membranes. NH4+-N, MLSS and MLVSS concentrations were measured according to the Standard Methods (APHA 1995). Enzyme activity of hydrazine dehydrogenase was determined according to the methods described by Shimamura et al. (2007). The hydrazine dehydrogenase activity was expressed as μmol of cytochrome c reduced/mg protein/min. Nitrate reductase (Nar) activity was assayed in accordance with the methods recorded by Meincke et al. (1992) by measuring the consumption of nitrite. Nitrite reductase (Nir) activity was assayed on the basis of the methods described by Hira et al. (2012). RESULTS AND DISCUSSION Firstly, we investigated the effects of different application modes during three phases in continuous experiments. The relationship of different application modes and the corresponding anammox activities is presented in Fig. 2. Compared with the control experiment, there was an observable increase of nitrogen removal performance with the application time of 12 h per day (the applied electric field of 2V/cm). The enhancement of biological activity changed with the impulse application time of the electric field. At the end of phase I (mode 1), the TN removal efficiency of R2 was 71%, which was about 18.3% higher than that of R1. Subsequently, the nitrogen removal efficiency continued to increase after the impulse application time enhanced to 6 h (mode 2). On the running day of 30, the TN removal efficiency of R2 climbed up to 78%, while that of R1 kept quite stable at about 62% in the end of phase II. But when the impulse application

141


250

300

A I

II

III

+ NH4 -N (mg/l)

NO2 -N (mg/l)

inf.NH 4 + -N

150

eff.NH 4 + -N of R1

100

B I

250

200

eff.NH 4 + -N of R2

200

II

III

inf.NO 2 --N eff.NO 2 --N of R1

150

eff.NO 2 --N of R2

100

50 50 0

0 60 55

10

20

30

40

50

C 3 NLR, NRR (mg-TN/m /d)

45 40 35 30 25

eff.NO 3 -N of R1

20

-

eff.NO 3 -N of R2

10

20

30

40

50

30

40

50

Time (day)

1200 NLR NR R of R1 NR R of R2

1000 800 600

15

0

10

D

1400

50

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Fig. 2. Comparison of nitrogen removal performance of two reactors in different phases.

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time beyond 6h in one cycle, the activity of anammox biomass did not result in further increase rather showed a decreasing trend. During phase III, there has been a decline in the total nitrogen removal efficiency 142

Environmental Science & Technology 2014 Vol. 1 of R2 with 72% after the impulse application time increased to 12 h in one cycle (mode 3). The continuous experimental results demonstrated that application time of external electric field distinctly played a key role on the activity of anammox biomass. The peak positive effect of electric field at application mode 2 (application-rest time: 6h-6h). Thus, this mode (mode 2, applicaton-resting time: 6h-6h,) was utilized for the following continuous experiments (phase IV) to examine its long-term effects on the activity of anammox biomass.

Table 2. crude enzyme activities of both reactors during different phases. Phase I II III IV (day15) (day30) (day45) day 80 day140 day 200 day260 Sampling day Crude HDH Activity (µM nitrite/min/mg protein) Crude NIR activity (µM nitrite/min/mg protein) Crude NAR activity (µM cytochrome c/mg protein/min)

R1

1.12

1.14

1.18

1.02

1.40

1.59

1.70

R2

1.76

1.84

1.36

0.95

2.09

2.39

2.92

R1

23.35

24.26

26.29

23.07

27.62

30.41

34.82

R2

31.89

34.52

28.10

27.38

35.34

46.53

50.78

R1

1.70

1.80

1.98

1.80

2.10

2.75

3.26

R2

2.31

2.73

2.45

1.86

2.43

3.60

4.59

In phase IV, HRT shortening was applied as the main method to increase the NLRs of both reactors with the constant influent substrates concentrations. As shown in Fig.3, the NRRs of both reactors were 867 and 1002 g-N/m3/d, respectively. The inhibition of anammox biomass in R2 due to the mal-effects of external electric field during phase III resulted in the almost same nitrogen removal performance of both reactors. From phase IV, the NRR of R2 presented a rapid enhancement and could kept continuous and stable better nitrogen removal performance than that of R1. For instance, the NRR of R2 increased to only one week after the application mode returned to mode 2 (6 h application-6 h resting), which was about 16.7% than that of R1 in the same period. In the following running days, the nitrogen removal performance always showed to be always higher than those of R1. In the end of phase IV, the NLR of two reactors increased to 8641 g-N/m3/d. While the NRRs of both reactors reached 4470 and 6468g-N/m3/d, respectively. And the latter was about 45% higher than that of the former. In our study, these two reactors were operated at the similar condition except the external electric field application or not, but there presented so much difference in nitrogen removal performance between them. Hence, these results implied that appropriate external electric field application might be the main reason for this difference in nitrogen removal performance. Anammox process involved several key enzymes for converting ammonium to dinitrogen gas, such as nitrate reductase (NAR), nitrite reductase (NIR), hydrazine oxidoreductase (HZO), hydrazine dehydrogenase (HDH), and hydrazine hydrolase (HH) (Kartal et al. 2011). Among them, HDH might be the key enzyme responsible for converting N2H4 into the final N2 (Kartal et al. 2011). Table 2 described the variation of crude HDH activities of both reactors during different phases. Obviously, with the electric field applied, the crude HDH activities were enhanced greatly at all three phases in different impulse application. The peak value of 1.84 µmol cyto c reduced/min/mg protein was 1.36 folds as high as that of control reactor within 45 days’ operation, which was achieved under mode 2 (6 h application-6 h resting) at the end of phase II. During phase III, the crude HDH activity appeared a downward trend, and dropped to 1.36 µmol cyto c reduced/min/mg protein under mode 3 (mode 3, 12h-12h). In phase IV, the crude HDH activity of two reactors were measured on day 80, 140, 200 and 260 similarly, the crude HDH activity exhibited the similar changing situation with that of hemc c contents as our speculation above. At the end of phase IV on day 260, the crude HDH activity with electric field of optimal condition in R2 was increased to 2.92 cyto c reduced/min/mg protein. The peak value was about 3.1 and 1.6 folds as much as those of seed sludge and R1. Besides, the effects of electric field on the other key enzymes were also studied, such as nitrate reductase and nitrite reductase of anammox bacteria. Similarly to the crude HDH activity, the peak value of the crude NIR activity of 34.2 and NAR activity of 2.73 μM NO2--N/mg protein/min all were observed at 143

Environmental Science & Technology 2014 Vol. 1 the impulse continuous application time of 6h (mode 2). And then the crude NIR and NAR activity appeared decrease trends at the impulse continuous application time of 12h (mode 3). Furthermore, during 215 days’ cultivation (from day 45 to day 260), the crude NIR activity in R2 was from 27.38 increased to 50.38 NO2-N/mg protein/min and the NAR activity was from 1.86 increased to 4.59 NO2--N/mg protein/min, which was about 45.8% and 41% higher than those of R1 on day 260, respectively. Thus, the crude enzyme activity of anammox bacteria might be closely affected by electric field, which further promoted the nitrogen removal performance.

Fig. 3. Comparison of the TEM observations on both reactors on day 200. A, C were samples taken from R1; B, D were samples taken from R2 Samples of both reactors at day 200 (in phase IV) were taken for TEM observation, as shown in Fig. 3. The distribution of bacterial flora of two reactors showed evident differences. Compared Fig. 6A with Fig. 6B, it was obvious that the anammox bacteria was aggregated in R2 with electric field, displaying a compact cluster of cells in structure, while it presented a dispersed texture in R1, showing low cell-density in view. Considering the increase of 16S rRNA anammox bacterial copy numbers and the higher celldensity, it further confirmed that the application of electric field on the appropriate condition had a significantly positive effect on the growth rate of anammox biomass. Some cells of the two reactors showed irregular shape, the reason might be the long operation and high nitrogen loading. Besides, with electric field application, there existed a lot of curvatures and compartments inside anammoxosome from Fig 6D. The curvatures and so many compartments may be used to increase the membrane surface available for the enzyme involved in catabolism, such as the ATPases and cytochromes c proteins. The increase of anammoxosome membrane surface would provide more area to accommodate more cytochrome c or other key enzymes. Thus, the enhanced cytochrome c could exert their function as activity center. Therefore, the variation of anammox cell structure by external electric field application might be in favor of the enzyme catalytic and the substrate transition, and further affected the TN removal performance of anammox biomass. CONCLUSIONS In this study, the application of electric field of 2V/cm at the application time of 12/24h in an UASB reactor effectively improved the TN removal performance on the anammox reactor. When the continuous application time of 6h in one cycle was supplied to reactor, nitrogen removal rate increased 45% dramatically in 265 days. Besides, the applied electric field under the appropriate condition could promote the crude enzyme activity. TEM photographs indicated that the electric field could result in the variation of cell density and structure. ACKNOWLEDGEMETNS This work was supported by the Natural Science Foundation of China (Nos. 21377014, 51008045), Science and Technology Research Projects of Liaoning Provincial Department of Education (No. L2013026).

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REFERENCES Amarjargal, A., Tijing, L.D., Ruelo, M.T.G., Park, C.-H., Pant, H.R.,Vista IV, F.P., Lee, D.H., Kim, C.S., 2013. Inactivation of bacteria in batch suspension by fluidized ceramic tourmaline nanoparticles under oscillating radio frequency electric fields. Ceramics International 39, 2141-2145. APHA., 1995. Standard Methods for the Examination of Water and Wastewater, 19th ed. American Public Health Association, New York. Barnes, F.S., 2007. In: Barnes, F.S., Greenebaum, B. (Eds.), Handbook of Biological Effects of Electromagnetic Fields: Bioengineering and Biophysical Aspects of Electromagnetic Fields. CRC/Taylor & Francis, pp. 115-152. Kartal, B., Maalcke, W.J., de Almeida, N.M., Cirpus, I., Gloerich, J., Geerts, W., Op den Camp, H.J.M., Harhangi, H.R., Janssen-Megens, E.M., Francoijs, K.J., Stunnenberg, H.G., Keltjens, J.T., Jetten, M.S.M., Strous, M., 2011. Molecular mechanism of anaerobic ammonium oxidation, Nature, 479, 127130. Mulder, A., Vandegraaf, A A., Robertson, LA., Kuenen, J G., 1995. Anaerobic ammonium oxidation discovered in a denitrifying fluidized bed reactor, Microbiology Ecology., 16, 177-184. Op den Camp, H.J.M., Kartal, B., Guven, D., van Niftrik L.A., et al., 2006. Global impact and application of the anaerobic ammonium-oxidizing (anammox) bacteria. Biochem. Soc. Trans., 34, 174-178. Ohmura, N., Matsumoto, N., Sasaki, K., Saiki, H., 2002. Electrochemical regeneration of Fe(III) to support growth on anaerobic iron respiration, Appl. Envrion. Microbiol., 68, 405-407. Qiao, S., Yin X., Zhou, J.T., Furukawa K., 2013. Inhibition and recovery of continuous electric field application on the activity of anammox biomass, Biodegradation., DOI 10.1007/s10532-013-9677-7. Strous, M., Fuerst, J.A., Kramer, E.H.M., Logemann, S., Muzyer, G., van de Pas-Schoonen, K.T., Webb, R., Kuene, J.G.., Jetten, M.S.M., 1999. Missing lighotroph identified as new planctomycete, Nature, 400, 446-449. Takayuki Ohshimaa., Tsuruki Tamurab., Masayuki Satoa., 2007. Influence of pulsed electric field on various enzyme activities, Journal of Electrostatics, 65, 156-161.

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ANAEROBIC OXIDATION OF AMMONIUM COUPLED TO ELECTRICITY PRODUCTION IN A MICROBIAL ELECTROLYSIS CELL Bo Qu* and Bin Fan (Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China) The oxidation of ammonium is a critical step of biological nitrogen removal from ammonium-rich wastewater. Here we report that ammonium can be anaerobically oxidized with anodes as the electrons acceptor in microbial electrolysis cells (MECs). Enrichment cultures attached to the anode surface were established from a freshwater sediment inoculum with the anode as the sole electron acceptor and ammonium as the sole electron donor. The oxidation of ammonium was coupled to the electrical current production. Nitrate was the main product that accounted for approximately 95% of ammonium consumed, but nitrite was also detectable. Shuttling assays indicated that some soluble microbial metabolites as redox mediators were involved in electron transfer to the electrode. Analysis of 16S ribosomal RNA gene sequences showed that the anode was dominated by Nitrosomonas europaea (40.3%) and the genus Empedobacter (34.7%). In order to further investigate the mechanism responsible of anaerobic ammonium oxidation and current production, a pure culture of Nitrosomonas europaea was inoculated into the anode chamber of the same MEC. The cells could oxidize ammonium and transfer electrons to the anode when the cell-free filtrate of medium from anode chamber of enrichment culture was used as the medium or the humate analog anthraquinone-2, 6-disulfonate (AQDS) was added as a redox mediator, suggesting that Nitrosomonas europaea can anaerobically oxidize ammonium with transfer of electrons to an electrode via electron shuttling. These results demonstrate a novel pathway of biological ammonium oxidation, and have potential applications in nitrogen wastewater treatment.

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EFFECT OF BAMBOO BIOCHAR ON FERTILITY AND NUTRIENT LEACHING OF A SANDY PEAR ORCHARD SOIL IN SOUTHEAST CHINA Lou Liping 1,2, George A.Sorial2 1. Department of Environmental Engineering, Zhejiang University, Hangzhou, Zhejiang, China 2. Department of Biomedical, Chemical, and Environmental Engineering, University of Cincinnati, Cincinnati, OH 45221-0012, USA Biochar has been described as a prosperous method to improve soil fertility and sequester carbon, so it is of considerable interest in the field of Sustainable Agriculture and Environment. In this study, incubation experiment and column leaching experiment has been conducted to quantify the effect of different content of bamboo biochar (BBC) (0, 0.1, 0.3, 0.5, and 1.0% (wt/wt)) on the mineralization of organic fertilizer and the nutrient leaching in a sandy pear orchard soil. According to C, N and P mass balance analysis, the more BBC was added to soil, the more C, N and P contents were retained after two experiments. Compared with the control, the addition of 1.0% BBC to soil retained 1.85, 0.30 and 0.063 mg g-1 C, N and P, respectively. Furthermore, the influence of BBC on nitrogen was great, because the addition of 1.0% BBC not only increased the concentration of soil N by 11.84% in the manure mineralisation due to enhance microbial biomass and enzymes activity, but also reduced the cumulative content of soil N leach-loss by 43.90% in the leaching process because of its adsorption. BIOLOG analysis indicated that in BBC-amended soils the soil microbial functional diversity and the utilization of characteristic carbon substrates increased, which should be a key factor in enhancing the mineralization of chicken manure. For example, in the 1.0% BBC treatment, the average well color development (AWCD), substrate richness (S) and the three functional diversity indices (Shannon index (H’), Simpson index (D) and McIntosh index (U)) were 3.63, 1.73, 1.19, 1.05 and 2.94 times of the control respectively, and the utilization of seven characteristic carbon substrates increased by 5 to 452 times. The results supported that BBC is a promising soil ameliorant and addition of BBC to soil will be a new method to control agriculture nonpoint source pollution.

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CHANGES OF BACTTERIAL COMMUNITY DIVERSITY IN OXIC-SETTLINGANAEROBIC (OSA) ACTIVATED SLUDGE PROCESS Lianpeng Sun, Jinxin Tan, Xiaoyu Yu, Lili Chen (Sun Yat-sen University, Guangzhou, China) ABSTRACT: Operation of a conventional OSA process was modified by alternately recirculating supernatant and settled sludge. PCR amplification-TGGE fingerprint profiles were employed for studying the microbial communities of the two processes in an effort to further illuminate the biological mechanisms utilized by SBR-OSA systems to reduce sludge production. The results showed that the modified method of operation reduced sludge production by 11.8% compared to the conventional one. The anaerobic sludge bacterial communities from the two OSA systems were about hundred percent similar as determined by transverse comparison, however, the aerobic sludge bacterial communities were only 80% similar during the last stage of the experiments, and the bacterial communities in the two aerobic activated sludge reactors were distinctly different. Keywords: oxic-settling-anaerobic process; bacterial community diversity; sludge reduction; TGGE; INTRODUCTION The oxic-settling-anaerobic (OSA) process was initially applied to modify the traditional activated sludge wastewater treatment process in the 1990s, and some researchers (Chudoba et al., 1992; Wei et al., 2003; Sun et al., 2010 ) discovered that it could result in a decrease of 30%~60% in excess sludge production. The fundamental principle of the OSA process is to incorporate a sidestream anaerobic bioreactor to the Activated Sludge process. Research has shown that this results in reduced sludge production via various biological mechanisms such as energy uncoupling, sludge anaerobic digestion, etc (Chudoba et al., 1992; Saby et al., 2003).Although many investigators have researched the mechanisms of excess sludge reduction by the OSA process, no consensus explanation currently exists, and several different factors have been implicated (Chudoba et al., 1992; Saby et al., 2003; Sun et al., 2010). However, regardless of the biological mechanism(s) involved, it is likely that the process results in significant changes in the sludge microbial population, and there is a need to elucidate these changes. It has been shown that conventional methods for studying microbial diversity, such as plating on selective media, are unreliable, because only a small fraction of the bacterial species present in the natural habitat will grow on synthetic media. However, molecular analysis of natural microbial communities using bacterial 16S rRNA amplification-temporal temperature gradient gel electrophoresis (TTGE) can solve these problems and has been widely applied for the study of microbial diversity. Though the TGGE techniques have some shortcoming (Hill et al., 2000; La Montagne et al., 2002; Kisand and Wikner, 2003), for instance, a single band can frequently include several different species when profiling mixed environmental communities, it remains the most efficient methodology for the determination of relative differences or temporal changes in microbial community structure in environmental samples. In this study, a modified SBR-OSA process was established instead of the conventional one, so that the sludge bacterial community structure would be changed to a significant extent. The modified SBR-OSA process has different operational parameters, and has more sludge reduction than the control system. And it is hypothesized that the bacteria community diversity between the two processes were different for the different operational condition, it was postulated that making the changes and accomplishing improved sludge reduction in the modified OSA process would increase the population of slowly growing bacteria such that they could be detected and identified. Analysis of PCR-TTGE banding patterns were performed for biomass developed in each of the two SBR-OSA processes used to measure and compare the richness and evenness of the two bacterial communities. MATERIALS AND METHODS 148

Environmental Science & Technology 2014 Vol. 1 Experimental systems. Two sets of SBR-OSA process systems were established, a control system (OSA1) and an experimental system (OSA-2). The control system consisted of a conventional SBR with a sidestream anaerobic reactor, i.e. a conventional SBR-OSA system. Settled sludge was cycled from the SBR to the anaerobic reactor for anaerobic digestion, and then recycled back to the SBR before sludge wasting. The experimental system (OSA-2) had the same basic configuration, but was operated differently by cycling the anaerobic sludge back to the SBR only once every three days and cycling settled supernatant back the rest cycles. The aerobic reactors of these two systems were separately defined as “O-1” and “O-2”, while the anaerobic reactors were defined as “A-1” and “A-2”. The complete operation cycle for the SBRs was 6 hours, resulting in 4 cycles per day for each of the two systems. These SBR laboratory systems were fed artificial sewage which consisted of peptone, glucose, CH3COONa, NH4Cl, KH2PO4, KHSO4, NaHCO3, CaCl2, MgSO4, FeCl3, Al2(SO4)3 and other microelements, as shown in Table 1. TABLE 1. Chemical compositions of sewage

The volume of the both aerobic reactors was 4L and Item Average concentration (mg/L) HRTs were controlled at 2 days, while the SRT of the two COD 450 anaerobic reactors was maintained at 5 days and 15 days, TN 80 NH4+ 40 respectively. In OSA-1, 25mL (about 2.5% by volume) of TP 15 aerobic sludge (at the late stage of settling) went into the SS 30 anaerobic reactor A-1 via a peristaltic pump in each cycle, and Fe3+ 10 the same volume of anaerobic sludge in A-1 was pumped to the 10 Al3+ aerobic reactor simultaneously. In OSA-2, 25mL of aerobic Mg2+ 20 Ca2+ 20 sludge (at the late stage of settling) was pumped to the pH 6.5~7.5 anaerobic reactor A-2 in each cycle. The same volume of anaerobic sludge was pumped to O-2 every 3 days, while supernatant was returned to O-2 the rest days. Prior to cycling supernatant from A-2 to O-2, magnetic stirring in A-2 was stopped for settling one hour before recirculation. The activated sludge was obtained from an SBR laboratory system fed by artificial sewage, and maintained at Sun Yat-sen University. The raw sludge, used as seed sludge, was taken from the secondary sedimentation tank of an A2/O process in Lie De sewage treatment plant, Guang Zhou. After acclimation to an intermittent aeration mode, the cultivated sludge was seeded into both of the systems. Then nitrogen was put into the anaerobic reactors to exclude air, and guarantee an anaerobic environment. The room temperature was about 25 centigrade degree during the experiments. The concentration of MLSS was from 2500-4500mg/L, and no sludge was wasted during the experiments. Activated sludge DNA extraction method. The activated sludge was sampled four times from each reactor after the systems were started up, the first day of starting up, 65, 141 and 207 days of operation. The method of DNA extraction and purification were done according to Yu (2011). DNA concentration was determined spectrophotometrically at the absorbance (A) of 260 nm. The purity of DNA was estimated spectrophotometrically by analyzing A260/A230 and A260/A280 ratios to determine contamination by humic acid and protein, respectively. The size of the isolated DNA fragment was determined by agarose (1.0%) gel electrophoresis using 1 kb DNA marker. The gel was stained with 0.5 µg/ mL SYBR Green agent and photographed under UV light. PCR amplification of 16S Rdna and TTGE. The PCR reaction system was amplified using the following ：Primer-1(10 μmol/ L) 0.25μL, Primer-2(10 μmol/L) 0.25μL, dNTPs (10 mmol/L) 1μL, PCR Buffer 5μL, DNA template 2μL, Taq polymerase (2U/μL) 1μL, Sterile double distilled water 40.5μL. The reaction procedures were as follows: (1) predegeneration at 94 for 4 minutes; (2) denaturation at 94 for 1 minute; (3) annealed at 50 for 1 minute; (4) extended at 72°C for 1 minute. Then, 30 cycles were repeated from step (2) to step (4). PCR products were electrophoresed at a constant voltage of 150 V for 3 h, with a thermal gradient from 40 ºC to 55 ºC. The initial electrophoresis time was 1.5 h, and it was later extended to 3 h. Then photos were taken with a diascoptic lighting imaging system, and the intensities of the TGGE bands were analyzed.

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Environmental Science & Technology 2014 Vol. 1 Instruments and reagents. The following instruments were employed in the research: Alpha HP imaging system (Alpha Co., US); Tgradient PCR (Whatman Biometra Co., Germany); TGGE system (Whatman Biometra Co., Germany); VCX130PB ultrasonic processor (Sonics Co., US); Forma 700 freezer (Thermo Electro Co., US); electrophoresis apparatus (Liuyi Co., China). Materials and reagents include: Primer-1 for PCR reaction (Beijing Genomics Institute, China): 357F-GC-clamp 5'-CGC CCG CCG CGC CCC GCG CCC GGC CCG CCG CCC CCG CCC CCC TAC GGG AGG CAG CAG-3'; Primer-2: 518R 5'-ATT ACC GCG GCT GCT GG-3', corresponding to positions on the Escherichia coli 16S rRNA gene (rrs) sequence (Gomes et al., 2001). The aim of inserting G-C gens-clamps in the primer sequence is to raise the efficiency of gens separating in TGGE gel bands (Don et al., 1991). dNTPs (Takara Co., Japan). Taq DNA Polymerase (New Probe Co., China) andultraviolet spectrophotometer (Bio-Rad, US) were also used for analysis. RESULTS AND DISCUSSIONS The bacterial populations in the aerobic and anaerobic reactors were separately analyzed, and are discussed separately. The aerobic population results will be presented and discussed first. Changes of aerobic activated sludge bacterial community diversity. The two SBRs were operated with different styles, and it was assumed the composition of the microbial populations in two systems would be different. The results obtained by TGGE fingerprint (Figure 1 (a)) and strength analysis of the aerobic activated sludge microbes communities are shown in Figure 1. To make it convenient for intuitive and clear analysis of the TGGE profiles, dendrograms were developed, shown in Figure1 (b). Number 1 represents the first sample of O-1, and Numbers 2, 3 and 4, respectively, represents the second, third and fourth sample. Number 1＇、2＇、3＇、& 4＇respectively represent the first, second, third and forth sample from O-2. Lane t was used to show all of the obtained bands. In Figure 1 (b), thicker dendritic lines represent stronger signals of bands in the TGGE fingerprint profiles, and also represent a higher quantity of a specific kind of bacterial. When the profiles are compared vertically, it can be seen from lane 1~4 that the structure of the aerobic microbial community varied as time went on: band 1 and band 2 appeared in lane 2, while band 3 started to appear in lane 3. More species in the microbial community appeared with time (refer to Table 2). Band 5~9 appeared in lane 4. Table 2 shows that lane 3 and lane 4 were hundred percent similar, illustrating that the structure of bacterial community was basically stable and the dominant species changed no more starting from lane 3 (or sometime between lane 2 and lane 3). From lane 1＇~4＇, changes happened among the structure of the bacterial community: bands 1, 2, & 4 appeared starting in lane 2 ＇ , and species abundances kept increasing. Bands 5~9 FIGURE 1. TGGE finger atlas for aerobic sludge ((a) TGGE always existed in the 4 lanes. It can be fingerprint profiles; (b) dendrogram) concluded that the structure of the bacterial community was reasonably stabile starting in lane 3’. Compared transversely, Lane 1 and 1＇were for sludge samples taken on the day the systems were started. Because the sludge in O-1 and O-2 were cultivated under the same conditions, the bands of these two lanes are hundred percent similar, which verified the precision of the TGGE technique used during these experiments. When the structure of the bacterial communities in the aerobic sludge zone of the two systems 150


became stable, lane 4 and lane 4＇were only 80% similar, indicating that a considerable diversity existed in the structure of the aerobic microbial communities in the 2 systems. Band 3 appeared exclusively in lane 3 and 4, and band 4 appeared only in lane 3＇and 4＇. Moreover, according to Table 2, similarity between lane 2 and lane 3 was 88.9%, and was 77.8% between lane 2＇and 3＇, meaning that the sludge in O-1 needed less time to become stable than the sludge in O-2. TABLE 2. Comparability index of TGGE bands and Richness value (Rs) for the aerobic bacterial populations Item 1 2 3 4 1＇ 2＇ 3＇ 4＇ Lane 1 100 Lane 2 75.0 100 Lane 3 66.7 88.9 100 Lane 4 66.7 88.9 100 100 Lane 1＇ 100 75.0 66.7 66.7 100 Lane 2＇ 85.7 87.5 77.8 77.8 85.7 100 Lane 3＇ 66.9 88.9 80.0 80.0 66.7 77.8 100 Lane 4＇ 66.9 88.9 80.0 80.0 66.7 77.8 100 100 Number of bands 6 8 9 9 6 7 9 9 Rs (%) 60 80 90 90 60 70 90 90

When Li L. et al. (2004) analyzed the structure of sludge microbial community in coking wastewater, abundant and strong bands were obtained. However, in this study, bands in Figure 1 were relatively less abundant by contrast, as expected, mainly because the nutritional composition of coking wastewater was more complex than the wastewater used for these experiments. Thus, the highly stable nutritional composition of the artificial sewage used resulted in a less diverse microbial population than the one obtained using the industrial wastewater. The sludge reduction rate between the two systems was compared by the sludge observed yield. The sludge observed yield was determined over a given range of operation (200d) as the MLSS increase/COD used, using all the data over the range of operation for which the yield was calculated. The sludge observed yield in conventional system and modified system was 0.11 and 0.09 mg MLSS / mg COD, respectively. So sludge mass reduction in the modified SBR-OSA process was 11.8% greater than that in the conventional one, showing that the difference was related directly to the aerobic sludge characteristics in the two systems. It was assumed that there was one or more species of slowly growing bacteria in the sludge initially placed in the aerobic tanks of the SBR-OSA system, and it (they) would have an improved opportunity to become a greater fraction of the activated sludge in the modified OSA process than in the conventional OSA process because of the longer total SRT. In Figure 1, the microbial structure difference between lane 4 and lane 4＇verified that the activated sludge bacteria of the two systems were obviously different and that the hypothesis of an increased population of slow growers is very probable, and, therefore, is proposed. However, it needs to be confirmed by verifying the growing characteristics and functions of the bacteria described by lane 4 of Figure 1 using metagenome techniques. This activity is proposed for future study. Changes of anaerobic activated sludge bacterial community diversity. TGGE fingerprints and strength analysis of

FIGURE 2. TGGE finger atlas for anaerobic sludge ((a) TGGE fingerprint profiles; (b) dendrogram)

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Environmental Science & Technology 2014 Vol. 1 anaerobic sludge bacterial communities are illustrated in Figure 2. Aerobic activated sludge was placed into the anaerobic reactors. When aerobic biomass is placed in an anaerobic environment, the structure of the microbial community necessarily must make fundamental changes to adapt. The changes that occurred during experiments can be seen in Figure 2. When the atlas is compared vertically, it can be seen that significant changes happened to the bands from lane 1 to lane 4, as the aerobic sludge adapted to the anaerobic conditions during system operation. From lane 1 to lane 2, the time interval was 65 days, and the structure of the microbial community changed fundamentally. Table 3 showed that the comparability index of TGGE bands and Richness values for anaerobic bacteria population. Table 3 shows that the similarity between these 2 lanes was only 11.1%, and only band 1 appeared in both lanes as well as in all 4 lanes. Consequently, this result suggested that the bacteria corresponding to band 4 were amphimicrobe. Lane 2 was 50.0% similar to lane 3, indicating that bacterial community structure of the anaerobic sludge wasn’t yet stable after the systems had operated for 65 days. Lane 3 and lane 4 were hundred percent similar, illustrating that the anaerobic bacteria community was relatively stable during this stage. Bands 2, 4, 5, 7 and 8 appeared in lane 3 and lane 4, indicating that some of the bacterial species could only grow and reproduce when the systems were operated for a long time. Bands 3, 6 and 7 appeared starting in lane 2, which indicated that could these 3 species of bacteria grow by providing relatively relaxed anaerobic reaction conditions, which means a relatively wide rage, temperature rage and so on. From lane 1 to lane 4, the structure of the bands changed greatly, and there was a similarity of only 7.7% between the two lanes, and indicating that anaerobic reaction conditions had been achieved. The same conclusion could be applied to lanes 1＇~ 4＇, for similarity between lane 1＇and 4＇also was only 7.7%. Bands 2, 3, 5, and 6 started to appear from lane 2＇. Bands 4 and 7 appeared in lane 3＇and band 8 appeared only in lane 4＇, indicating that some of the species required more rigorous conditions for growth, such as greater reaction times and more strict anaerobic conditions. TABLE 3. Comparability index of TGGE bands and Richness values (Rs) for anaerobic bacteria population 2＇ 3＇ 4＇ Item 1 2 3 4 1＇ Lane 1 100 Lane 2 11.1 100 Lane 3 7.7 50.0 100 Lane 4 7.7 50.0 100 100 Lane 1＇ 100 11.1 7.7 7.7 100 Lane 2＇ 10.0 50.0 62.5 62.5 10.0 100 Lane 3＇ 8.3 66.7 87.5 87.5 8.3 71.4 100 Lane 4＇ 7.7 50.0 100 100 7.7 62.5 87.5 100 Number of bands 6 4 8 8 6 5 7 8 Rs (%) 46.2 30.8 61.5 61.5 46.2 38.5 53.8 61.5

When compared transversely, it is observed that lane 1 and lane 1＇were hundred percent similar, as was the similarity between lane 1 and lane 1＇of the aerobic sludge TGGE profiles (Figure 2). These four samples were from the same sludge, and were, therefore, cultivated under the same conditions. Therefore, it was expected that the structures of the microorganism communities would be the same, and this was confirmed in this study, further illustrating that TGGE techniques can analyze the microorganism community diversity precisely. The similarity between lane 3 and lane 4 was 100%, and was 87.5% between lane 3＇and lane 4＇. It can be seen that sludge in A-1 needed less time to achieve relatively stable ecological structure than sludge in A-2. This was because anaerobic reactor A-1 was operated using the traditional sludge-in and sludge-return mode of OSA operation, while anaerobic reactor A-2 was operated with a longer time between sludge return events because only supernatant was recirculated most of the time. It may be that the imbalance between the aerobic sludge entering and leaving A-2 resulted in longer times for the anaerobic environment of A-2 to reach stability, and for the bacterial community to reach stability. Lane 4 and lane 4＇were hundred percent similar, showing that at the end of the experiment, the structures of the two anaerobic microbial communities were basically the same. Thus, the separate operating conditions had no impact on the final structure of the anaerobic sludge microbial community of the two OSA systems, but it took more time for the modified OSA process to get stable than the conventional one. 152


CONCLUSION The majority of OSA investigations have mainly focused on process operating conditions and sludge production ratios to seek the mechanism of excess sludge reduction. This investigation explored changes in the bacterial community structure of two OSA processes operated under different anaerobic sludge return conditions to gain new insights into the possible mechanism of excess sludge reduction. (1) By means of TGGE fingerprint profiles changes in the sludge microbial community structures of the two SBR-OSA systems were investigated. It was shown that the microbial community structure of the sludge in two systems changed with time operation, and finally reached steady-state stability. During the last period of the experiments, microbial community structures of sludge in the two aerobic reactors were 80% similar. Based on this result, a slowly-growing dominant bacteria hypothesis was proposed as a mechanism of excess sludge production in OSA systems. (2) The results suggested that different operating methods could change the structure of aerobic sludge community even when treating the same wastewater. The similarity of the sludge communities in two anaerobic reactors was 100%, indicating that changing the operating method had no obvious impacts on the structure of the anaerobic sludge community. (3) Although drawbacks may exist in use of PCR-TGGE techniques, they are still very useful and accurate for the investigation of the diversity of bacterial communities. During the research in this study, the TGGE techniques provided very precise results. (4) As artificial wastewater was used in this study, the number of bacterial species was relatively small. It is recommended that sewage be used for further research. Also, metagenomes techniques should be used to accurately identify the slowly-growing dominant bacteria that developed in the aerobic sludge of this investigation, i.e. the microorganism corresponding to lanes 4 and 4＇. ACKNOWLEDGEMENTS This work was supported by the Science & Research Program of Guangdong (Contract No. 2012B091000029 and 2012A032300005), the Science & Research Program of Foshan (Contract No. 2012AA100091 and 2012HY100531), and the Science & Research Program of Chancheng District (Contract No. 2012B1002). We would like to thank Dr. C. W. Randall from Virginia Polytechnic Institute and State University for English-language and professional editing. REFERENCES Chudoba, P., A. Morel and B. Capedeville. 1992. “The Case of Both Energetic Uncoupling and Metabolic Selection of Microorganisms in the OSA Activated Sludge System”. Environ. Technol. 13(8): 761-770. Don, R. H., P. T. Cox, B. J. Wainwright, K. Baker and J. S. Mattick. 1991 “‘Touchdown’PCR to Circumvent Spurious Priming during Gene Amplification”. Nucleic Acids Res. 19(14): 4008. Gomes, N. C. M., H. Heuer, J. Schönfeld, R. Costa, L. Mendonca-Hagler and K. Smalla. 2001. “Bacterial Diversity of the Rhizosphere of Maize (Zea Mays) Grown in Tropical Soil Studied by Temperature Gradient Gel Electrophoresis”. Plant and Soil. 232(1-2): 167-180. Hill, G. T., N. A. Mitkowski, L. Aldrich-Wolfe, L. R. Emele, D. D. Jurkonie, A. Ficke, S. MaldonadoRamirez, S. T. Lynch and E. B. Nelson. 2000. “Methods for Assessing the Composition and Diversity of Soil Microbial Communities”. Appl. Soil Ecol. 15(1): 25-36. Kisand, V. and J. Wikner. 2003. “Limited Resolution of 16S rDNA DGGE Caused by Melting Properties and Closely Related DNA Sequences”. J. Microbiol Meth. 54(2): 183-191. LaMontagne, M. G., F. C. Michel, P. A. Holden and C. A. Reddy. 2002. “Evaluation of Extraction and Purification Methods for Obtaining PCR-Amplifiable DNA from Compost for Microbial Community Analysis”. Microbiol. Meth. 49(3): 255-264. Li, L., G. F. Wei, G. L. Tong and L. P. Zhao. 2004. “Analysis of the Microbial Community Differences between Suspending Sludge and Biofilm in Oxidation Tank for Coking Wastewater Treatment with PCR Fingerprinting Technique” (in Chinese). Chinese Journal of Microecology. 16(1): 8-12. Saby, S., D. Malik and G. H. Chen. 2003. “Effect of Low ORP in Anoxic Sludge Zone on Excess Sludge Production in Oxic-Settling-Anoxic Activated Sludge Process”. Water Res. 37(1): 11-20. 153

Environmental Science & Technology 2014 Vol. 1 Sun, L. P., C. W. Randall and J. T. Novak. 2010. “The Influence of Sludge Interchange Times on the OxicSettling-Anoxic Process”. Water Environ. Res. 82(6): 519-523. Wei, Y., R. T. Van Houten, A. R. Borger, D. H. Eikelboom and Y. Fan. 2003. “Minimization of Excess Sludge Production for Biological Wastewater Treatment”. Water Res. 37(18). 4453-4467. Yu, X. Y. 2011. Research on Changes of Bacterial Community Diversity in an Oxic- Settling- Anaerobic (OSA) Activated Sludge Process with Sludge Reduction Effect. M.S. Thesis, Sun Yat-sen University, Guangzhou, China.

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IDENTIFICATION AND CHARACTERIZATION OF DYE DEGRADER MICROBES IN MICROBIAL GRANULAR SLUDGE TREATING SYNTHETIC TEXTILE WASTEWATER K. Muda*, A. Aris*, M.R.Salim*, Z. Ibrahim**, M.Z Nawahwi**.(*Department of Environmental Engineering, Faculty of Civil Engineering, Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia; **Department of Biological Sciences, Faculty of Biosciences and Bioengineering, Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia) Microbial granular sludge has been successfully developed in sequential batch reactor system treating synthetic textile wastewater. The system was operated in sequential batch reactor system under intermittent anaerobic and aerobic reaction mode. The hydraulic retention time of the system was set at 6 hours. A total of twelve microorganisms have been successfully isolated as pure culture bacteria from the microbial granular sludge developed in synthetic textile wastewater in the sequential batch reactor system. All of the twelve pure bacteria cultures isolated were further screened for the ability of dye degradation and autoaggregation, specific COD and dye degradation rates. All of the isolated microbes showed high color removal performance varying between 78 - 92% with specific color degradation rate ranging from 0.040.42 mg/g/h. However the removal performance for COD was relatively moderate with the percentage of 15-56% and specific COD degradation rate varies between 0.29 to 4.4 mg/g/h. The percentage of autoaggregation and surface hydrophobicity among the isolated microbes showed a wide variation ranging from 18.5 ± 1.8 to 97.3 ± 1.4 and 12.5 ± 2.7 o 97.3 ± 1.4, respectively. Based on the results obtained, six bacteria isolated from the microbial granules were identified through the molecular techniques involving bacteria isolation, PCR amplification process characterization and finally determination of taxonomic and phylogenetic class of bacteria isolates via 16S rDNA sequence analysis. The six bacteria successfully identified were Pseudomonas veronii, Bacillus cereus, three species of Pseudomonas sp. and Enterobacter sp. All of these bacterial show the ability in degrading colored wastewater and were characterized as facultative anaerobes.

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COMPOST BIOREMEDIATION OF OIL SLUDGE BY USING DIFFERENT MANURES UNDER LABORATORY CONDITIONS Ubani Onyedikachi 1*, Atagana Harrison Ifeanyichukwu 2, and Thantsha Mapitsi Silvester 3 (1. Department of Environmental Sciences, University of South Africa, Pretoria, 0003, South Africa; 2. Institute for Science and Technology Education, University of South Africa, Pretoria, 0003, South Africa; 3. Department of Microbiology and Plant Pathology, University of Pretoria, Pretoria, 0083, South Africa). This study was conducted to measure the reduction in polycyclic aromatic hydrocarbons (PAHs) content in oil sludge by co-composting the sludge with pig, cow, horse and poultry manures under laboratory conditions. Four kilograms of soil spiked with 800g of oil sludge was co-composted differently with each manure in a ratio of 2:1 (w/w) spiked soil: manure and wood-chips in a ratio of 2:1 (w/v) spiked soil: woodchips. Control was set up similar as the one above but without manure. Mixtures were incubated for 10 months at room temperature. Compost piles were turned weekly and moisture level was maintained at between 50% and 70%. Moisture level, pH, temperature, CO2 evolution and oxygen consumption were measured monthly and the ash content at the end of experimentation. Bacteria capable of utilizing PAHs were isolated, purified and characterized by molecular techniques using polymerase chain reactiondenaturing gradient gel electrophoresis (PCR-DGGE), amplification of the 16S rDNA gene using the specific primers (16S-P1 PCR and 16S-P2 PCR) and the amplicons were sequenced. Extent of reduction of PAHs was measured using automated soxhlet extractor with Dichloromethane as the extraction solvent coupled with gas chromatography/mass spectrometry (GC/MS). Temperature did not exceed 27.5OC in all compost heaps, pH ranged from 5.5 to 7.8 and CO2 evolution was highest in poultry manure at 18.78µg/dwt/day. Microbial growth and activities were enhanced. Bacteria identified were Bacillus, Arthrobacter and Staphylococcus species. Results from PAH measurements showed reduction between 77 and 99%. Co-composting of spiked soils with animal manures enhanced the reduction in PAHs. Interestingly, all bacteria isolated and identified in this study were present in all treatments, including the control.

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IDENTIFICATION AND CHARACTERIZATION OF OIL SLUDGE DEGRADING BACTERIA ISOLATED FROM COMPOST Ubani Onyedikachi 1*, Atagana Harrison Ifeanyichukwu 2, and Thantsha Mapitsi Silvester 3, Adeleke Rasheed 4 (1. Department of Environmental Sciences, University of South Africa, Pretoria, 0003, South Africa; 2. Institute for Science and Technology Education, University of South Africa, Pretoria, 0003, South Africa; 3. Department of Microbiology and Plant Pathology, University of Pretoria, Pretoria, 0083, South Africa; 4. Institute for Soil, Climate and Water, Agricultural Research Council, Pretoria, South Africa) Oil sludge components (polycyclic aromatic hydrocarbons, PAHs) have been found to be cytotoxic, mutagenic and potentially carcinogenic and microorganisms such as bacteria and fungi can degrade the oil sludge to less toxic compounds such as carbon dioxide, water and salts. In the present study, we isolated different bacteria with PAH-degrading potentials from the co-composting of oil sludge and different animal manure. These bacteria were isolated on the mineral base medium and mineral salt agar plates as a growth control. A total of 31 morphologically distinct isolates were carefully selected from 5 different compost treatments for identification using polymerase chain reaction (PCR) of the 16S rDNA gene with specific primers (16S-P1 PCR and 16S-P2 PCR). The amplicons were sequenced and sequences were compared with the known nucleotides from the gene bank database. The phylogenetical analyses of the isolates showed that they belong to 3 different clades namely Firmicutes, Proteobacteria and Actinobacteria. These bacteria identified were closely related to genera Bacillus, Arthrobacter, Staphylococcus, Brevibacterium, Variovorax, Paenibacillus, Ralstonia and Geobacillus species. The results showed that Bacillus species were more dominant in all treated compost piles. Based on their characteristics these bacterial isolates have high potential to utilise PAHs of different molecular weights as carbon and energy sources. These identified bacteria are of special significance in their capacity to emulsify the PAHs and their ability to utilize them. Thus, they could be potentially useful for bioremediation of oil sludge and composting processes.

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EFFECT OF ACID TREATMENT ON SEWAGE SLUDGE DERIVED CARBONS FOR CATALYTIC WET PEROXIDE OXIDATION Yang Yu, Huangzhao Wei, Yamin Wang, Li Yu, Wentian Jiang, Songbo He, Chenglin Sun* (Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China) Nowadays, an increasing amount of sewage sludge generated by wastewater treatment plant has been an essential environmental problem. Sewage sludge pyrolysis is considered as an interesting disposal and develops rapidly since it is effective in reducing the volume of sludge and producing bio-oil. Sewage sludge derived carbon (SW) could be formed during pyrolysis of sewage sludge, which contains a high content of iron and could be employed as the catalyst in catalytic wet peroxide oxidation (CWPO). CWPO is a Fentonlike oxidation reaction and has been widely used on the treatment of industrial wastewater containing nonbiodegradable organic pollutants. Only several studies had been carried out in CWPO reaction with SW, however, it has not been reported about the surface modified SW in CWPO reaction. In our study, extruded SWs treated with different kinds of acid were studied in CWPO continuous reaction. Furthermore, the effect of surface functional groups on catalytic activity was discussed. The results showed that the FTIR spectra of SWs treated with nitric acid, sulfuric acid and perchloric acid exhibited a sharp and prominent peak at 1633 cm-1, which attributed to a high content of C=O or carboxyl groups. They performed better catalytic activity in CWPO. When the initial concentration of mcresol was 100 mg· L-1 and H2O2 was 541 mg·L-1, m-cresol conversion reached 76%, 98% and 93%, respectively, after 384 h continuous reaction at room temperature and LHSV of 1 h-1. However, m-cresol conversion was only 4% and 27% for SW and SW treated with HCl, respectively. The pH of the effluent in CWPO was also analyzed, the results indicated that the effluent by SWs treated with different acid had a lower pH about 3.5-4.0, whereas the effluent by SW was 8.2-11.4. The low pH was caused by the degradation intermediates of m-cresol such as fumaric acid, pyruvic acid, acetic acid and so on. The elements content of SWs treated with different acid were analyzed, the results implied that iron might play a main role in m-cresol degradation.

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APPRAISAL OF CERTAIN ANAEROBIC DIGESTION STUDIES Ram Pal Singh* and P. Pal (Department of Civil Engineering, MNNIT, Allahabad-211004, U.P., INDIA) ABSTRACT: From time to time, discussions of various concepts related to anaerobic digestion have surfaced in the literature. With due recognition to the complexity of the pathways of anaerobic digestion and participation of a wide variety of microorganisms, there has been a substantial growth of studies to understand, model and improve the process performance. While doing so, the available literature has been utilised to have information pertaining to kinetic parameters, conversion factors, distribution factors, etc. Appraisal of various studies on anaerobic digestion indicated certain inconsistencies in the literature with regard to the use of kinetic parameters and conversion factors. With this in view, the present study focuses on the prevailing inconsistencies in anaerobic digestion studies. On various occasions, the concepts related to anaerobic digestion have been discussed in the literature. For the purpose of this study, the same has been excluded here to avoid repetitions. From the study, it is very evident that use of kinetic parameters from literature in anaerobic systems’ modelling needs care and attention. Key Words. stoichiometric coefficients, anaerobic digestion, chemical oxygen demand (COD), kinetic parameters, microorganisms. INTRODUCTION The importance of anaerobic digestion process is well recognised in the literature. In the last few decades, several studies on anaerobic digestion have shed light on the understanding of the process performance for a variety of wastes. The role of experimental studies has been also remarkable as these provide useful information regarding various kinetic parameters which are essential to the modelling of anaerobic digestion systems. Associated with these developments in anaerobic digestion literature, there have been also inconsistencies which may often be a source of misunderstanding and confusion to the research workers, designers and operators of anaerobic digestion systems. From the review of the literature (Lawrence and McCarty (1969), Lettinga et al. (2001), and Rumana et al.(2000)), it has been found that the inconsistencies are apparent in the adoption of the kinetic parameters, use of conversion parameters, and representation of stoichiometric relationships in the modelling of anaerobic digestion process. With this in back ground, the present study addresses some of these issues and provides necessary framework for the future studies on anaerobic digestion. For the purpose of illustrating the prevalent inconsistencies in the literature, the study is organised in the following sections. KINETIC PARAMETERS Kinetic parameters are essential for defining the rate of biochemical reactions. In the literature, a variety of rate expressions have been provided. Among these, the Monod kinetics is extensively studied and for this reason, only the kinetic parameters pertaining to the Monod kinetics have been considered. As per Monod kinetics, one needs to know a set of five parameters. The parameter k indicates the amount of substrate utilised per unit mass of biomass per day. Ks indicates the half saturation constant, which is the minimum concentration of limiting substrate at which the specific growth rate is 50% of the maximum specific growth rate of microorganisms. Y represents the biomass yield coefficient and is defined as the amount of biomass produced per unit mass of substrate utilized. µmax is the maximum specific growth rate (i.e, maximum rate of change of biomass concentration per unit biomass concentration) and kd is the rate of decay of microorganisms. Using these kinetic parameters, one can model the correspondence between the substrate and the biomass. In case of anaerobic digestion, one may not always encounter a single substrate situation. In fact when a complex organic waste contains a variety of substrates, there may be a need to define kinetic parameters with respect to each contributing substrate. Alternatively, all these substrates can be represented in terms of any of these substrates. For example, in the case of anaerobic reactions utilising mixture of 159

Environmental Science & Technology 2014 Vol. 1 volatile fatty acids, i.e., acetic, propionic, and butyric acids etc., some investigators have represented such mixture of volatile acids in terms of a single substrate, i.e., acetic acid (Lawrence and McCarty, 1969). Although, such a representation may lead to much simplification in the modelling of anaerobic digestion systems, it may have its own limitations as will be discussed later in this paper. TABLE 1. Comparison of kinetic constants as per Pavlostathis and Gomez (1991), adopted from Lawrence & McCarty, (1969) for acetic, propionic and butyric acids as substrate Kinetic Constants ↓ Substrate → k, mgCOD/mgVSS.d T=35°C T=30°C T=25°C Ks, mgCOD/l T=35°C T=30°C T=25°C µmax, d-1 T=35°C T=30°C T=25°C

Y, mgVSS / mgCOD T=35°C T=30°C T=25°C kd, d-1 T=35°C T=30°C T=25°C

Kinetic constants from Pavlostathis and Gomez (1991), adopted from Lawrence & McCarty (1969) Acetic Propionic Butyric Acid acid acid

Kinetic constants from Lawrence & McCarty (1969)# Acetic acid

Propionic acid

Butyric Acid

8.7 5.1 5.0

7.7 --7.8

8.1* -----

8.7 5.1 5.0

7.7 --7.8

8.3 -----

165 356 930

60 --1145*

13 -----

165 356 930

60 --1143*

13 -----

0.357 0.275 0.250

0.313 --0.358

0.354 -----

0.348c 0.275 0.25

0.3234c --0.398

0.390c -----

0.041 0.054 0.05

0.042 --0.051

0.047 -----

0.04** 0.054 0.05

0.042** -0.051

0.047** -----

0.015 0.037 0.011

0.010 --0.040

0.027 -----

0.019 0.037 0.011

0.01 --0.04

0.027 -----

Comparison Remarks k values for butyric acid are different. Slight difference in Ks value for propionic acid at 25°C. values are slightly different for acetic acid at 35°C, but large differences for propionic and butyric acids slight difference in the value for acetic acid at 35°C. difference in the value for acetic acid at 35°C.

# - k and Ks values are expressed as equivalent concentration of acetic acid, * - value is not equal to that mentioned by Lawrence and McCarty (1969); **- unit, mg/mg; c- computed values, µmax = k.Y Probably the first study to obtain the kinetic parameters for a variety of wastes , i.e., acetic, propionic and butyric acids can be credited to Lawrence and McCarty (1969). Table 1 shows the values of the some of the kinetic parameters documented by Lawrence and McCarty (1969). It is interesting to see that these coefficients have found applications in subsequent studies of Costello et al (1991a, 1991b) and Pavlostathis and Gomez (1991). It is pertinent here to describe the adoption of kinetic parameters of Lawrence and McCarty (1969) by subsequent investigators. In order to see the equivalence and comparison of kinetic constants and their evaluations, it is essential to critically analyse them. Maximum Specific Substrate Utilization Rate (K). The maximum specific substrate utilization rate (kvalues) is expressed by Lawrence and McCarty (1969) in terms of equivalent concentrations of acetic acids. The values of k at 350C for acetic, propionic and butyric acids respectively are reported as 8.7, 7.7, and 8.3 mg COD to CH4/mg-d, as given in Table 1. To convert these values in terms of mg COD/mg.d, one needs to make use of conversion factors of 1.067, 0.8 and 0.533 as per Table 2 for acetic, propionic and butyric acids respectively.

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Environmental Science & Technology 2014 Vol. 1 In the study of Costello et al. (1991b), each substrate has been assigned a rate kinetics and thus, a separate set of kinetic parameters. If one considers the reaction of propionic acid, the value of k to be used should have been in terms of mmol of propionic acid/mg VSS.d. Unfortunately, this is not the case in Costello et al. (1991b) who have used the k in terms of mmol of equivalent concentration of acetic acid/mg biomass.d as explained below in Table 3. TABLE 2. Conversion factor for equivalent methane COD Substrate

Reactions considered

Acetic acid Propionic acid Butyric acid

CH3COO- + 2H2O→ CH4 + HCO3CH3CH2COO- + 1/2H2O→ CH3COO- + 3/4 CH4 + 1/4 CO2 CH3CH2CH2COO- + HCO3- → 2CH3COO- + 1/2 CH4 + 1/2 CO2

g methane COD/ mole of substrate consumed 1×64 = 64

g methane COD/g (as acetic acid) of substrate consumed 64/60 = 1.067

(3/4)×64 = 48

48/60 = 0.800

(1/2)×64 = 32

32/60 = 0.533

To have a proper understanding of the implications of converting different wastes into equivalent acetic acid concentration, one needs to consider the reactions of acetic, propionic and butyric acids as documented under by Lawrence and McCarty (1969), i.e. Acetic acid CH3COO- + 2H2O → CH4 + HCO3Propionic acid CH3CH2COO- + 1/2H2O→ CH3COO- + 3/4 CH4 + 1/4 CO2 CH3COO- + 2H2O→ CH4 + HCO3Overall reaction CH3CH2COO- + 3/2H2O→ 7/4 CH4 + 1/4 CO2 + HCO3-

(1) (2) (3) (4)

TABLE 3. Equivalent conversion and comparison of kinetic constants used by Costello et al. (1991) with those from Lawrence & McCarty, (1969) for acetic, propionic and butyric acids as substrate Constants ↓ Substrate →

Kinetic constants as reported by Costello et al. (1991), adopted from Lawrence & McCarty (1969) Acetic Acid

Propio-nic acid

Butyr-ic acid

k,

0.18 mmol/mg.d

0.16 mmol/mg.d

Ks,

2.57 mM

Y

kd

Kinetic constants value As per Lawrence & McCarty (1969) # Acetic Acid

Propionic acid

Butyr-ic acid

0.26 mmol/mg.d

8.1 mg/ mg.d

9.6 mg/mg.d

15.6 mg/mg.d

0.53 mM

0.083 mM

154 mg/l

32 mg/l

5 mg/l

2.5 mg/ mmol

5.0 mg/ mmol

7.5 mg/ mmol

0.04** mg/mg

0.042** mg/mg

0.047** mg/mg

0.02 d-1

0.01 d-1

0.03 d-1

0.019 d-1

0.01 d-1

0.027 d-1

Equivalent conversion of values used by Costello et al. (1991) and comparison with those of Lawrence & McCarty (1969) Acetic Acid

Propionic acid

Butyr-ic acid

0.18×60 = 10.8* mg/mg.d 2.57×60 = 154.2 mg/l 2.5/(60× 1.066) = 0.039 mg/mg almost equal

0.16×60 = 9.6 mg/mg.d 0.53×60 = 31.8 mg/l 5.0/(74× 1.512) =0.045* mg/mg

0.26×60 = 15.6 mg/mg.d 0.083×60 = 4.98 mg/l 7.5/(88× 1.816) = 0.047 mg/mg approx. equal

# - k and Ks values are expressed as equivalent concentration of acetic acid * - Value is not equal to that mentioned by Lawrence and McCarty (1969) ** - expressed as mg biological solids produced per mg COD converted to methane Butyric acid 161

equal

Environmental Science & Technology 2014 Vol. 1 CH3CH2CH2COO- + HCO3- → 2CH3COO- + 1/2 CH4 + 1/2 CO2 (5) 2CH3COO- + 2H2O→ 2CH4 + 2HCO3(6) Overall reaction CH3CH2CH2COO- + 2H2O → 5/2 CH4 + 1/2 CO2 + HCO3(7) and the reactions for glucose degradation as mentioned by Denac et al. (1988), i.e. C6H12O6 → CH3CH2CH2COOH + 2CO2 + 2H2 (8) C6H12O6 + 2H2 → 2CH3CH2COOH + 2H2O (9) C6H12O6 + 2H2O→ 2CH3COOH + 4H2 + 2CO2 (10) CH3CH2CH2COOH +2H2O→ 2CH3COOH + 2H2 (11) CH3CH2COOH +2H2O→ CH3COOH + 3H2 + CO2 (12) CH3COOH → CH4 + CO2 (13) 4H2 + CO2 → CH4 + 2H2O (14) It can be seen that in the case of acetic acids only CH4 is produced while in the case of propionic acid, hydrogen is also produced, which may further contribute to CH4 formation as per Eq. (14). This contribution may be as high as 20-30% of the total methane production (Denac et al, (1988), Pantea ad Romocea(2008)). Thus, equivalent representation of other acids (except acetic acid) may not be fully justified. It is interesting to see from the study of Lawrence and McCarty (1969) that ionic reactions do not represent the formation of hydrogen and hence, the H2-based CH4 production. From Table 3, one can also note that in case of acetic acid, the value of k used by Costello et al. (1991b) as 0.18 mmol/mg.d in their model validation is incorrect as its conversion to equivalent acetic acid concentration works out to be 10.8 mg/mg.d which is different from the value of 8.1 mg/mg.d as reported by Lawrence and McCarty (1969). The values of k mentioned by Pavlostathis and Gomez (1991) are illustrated in Table 1. Although these values are expressed in terms of mgCOD/mgVSS.d, these are truly the values of Lawrence and McCarty (1969) expressed in units of mgCOD to CH4/mg.d except for butyric acid. Thus, adoption of such values might lead to the errors in computations/predictions in modelling of high rate anaerobic treatment systems due to incorrect use of original values of Lawrence and McCarty (1969). Half Saturation Constant (Ks). Similar is the case with the Ks values which are expressed in equivalent acetic acid concentrations. These values can be used only when different volatile fatty acids are expressed in terms of equivalent acetic acid concentration. It is interesting to see that Costello et al (1991b) have not treated different substrates into equivalent acetic acids in their simulations of anaerobic digester’s performance (Table 3). If one considers the propionic acid as substrate, the units of Ks must be expressed in terms of mass of propionic acids consumed per litre. Similar is the case in the study of Pavlostathis and Gomez (1991) as can be seen in Table 1. Maximum Specific Growth Rate (µ µmax). The parameter µmax is generally expressed as (k.Y). However, one can see the incorrect evaluation of µmax values of Pavlostathis and Gomez (1991), which are different than the computed values as marked with superscript (c) in Table 1. Biomass Yield Coefficient (Y). The value of Y as reported by Costello et al. (1991b) presents another interesting scenario. Contrary to k and Ks values which were expressed in terms of equivalent acetic acid concentration, the biomass yield has been reported in terms of mmol of the actual substrate as can be seen from Table 3. The relative magnitude of specific biomass yields in different volatile fatty acids also presents an interesting situation. Considerations of the following reactions can be used for having certain idea regarding the theoretical yield with respect to synthesis of biomass having cell composition as C5H7NO2 or C5H9O3N. Following Moletta et al. (1986) approach for synthesis of biomass C5H7NO2 from acetic acid, one can have the following possible reactions: 5CH3COOH + 2 NH3 → 2 C5H7NO2 + 6 H2O (15) 3CH3CH2COOH + CO2+ 2NH3 → 2C5H7NO2 + 4 H2O + H2 (16) CH3CH2CH2COOH + CO2+ NH3 → C5H7NO2 + 2H2O (17) 162


10H2 + 5CO2+ NH3 → C5H7NO2 + 8H2O (18) 5C6H12O6 + 6NH3 → 6C5H7NO2 + 18H2O (19) Considering the reactions of glucose degradation and Eqs. (8) to (14), one can write the following overall reactions for synthesis of biomass C5H7NO2 from different acids including Eq. (19), as given below: 3CH3CH2CH2COOH + NH3 → C5H7NO2 + 5CH4 + 2CO2 (20) 4CH3CH2COOH + CO2+ 2NH3 → 2C5H7NO2 + 4 H2O + 2CH4 (21) 6CH3COOH + 2 NH3 → 2 C5H7NO2 + CH4 + CO2 + 6 H2O (22) 14H2 + 6CO2+ NH3 → C5H7NO2 + CH4 + 10H2O (23) Similarly for a biomass composition C5H9O3N, the individual reactions in case of different acids can be written after Costello et al. (1991a) as under: 5CH3COOH + 2 NH3 → 2 C5H9O3N + 4 H2O (24) 3CH3CH2COOH + CO2+ 2NH3 → 2C5H9O3N + 2H2O + H2 (25) CH3CH2CH2COOH + CO2+ NH3 → C5H9O3N + H2O (26) 10H2 + 5CO2+ NH3 → C5H9NO3 + 7H2O (27) Considering the reactions of glucose degradation and Eqs. (15) to (19), one can write the following overall reactions for synthesis of biomass C5H9O3N from different acids, as given below: 6CH3COOH + 2 NH3 → 2C5H9NO3 + CH4 + CO2 + 4H2O (28) 2CH3CH2COOH + NH3 → C5H9O3N + H2O + 2CH4 (29) 3CH3CH2CH2COOH + NH3 +H2O → C5H9O3N + 5CH4 + 2CO2 (30) 14 H2+ 6CO2+ NH3 → C5H9O3N + CH4 + 9H2O (31) Using Eqs. (15) to (31), the theoretical yield can be computed. Denac et al. (1988) and Buffière et al. (1995) indicate that yield coefficient in case of butyrate, acetate and H2 are all equal to 0.029, while in case of propionic acid the yield coefficient is 50% lower , i.e., 0.014. Such variability in yield coefficients is neither observed in Lawrence and McCarty, (1969) nor in the estimation of theoretical yields. Normally, one would expect that the theoretical value of biomass yield from a particular acid is of the same order for butyric and acetic acids in comparison to its experimental yields of acetic or butyric acids. Although such agreement is apparent for the values of biomass yield for different acids in Lawrence and McCarty (1969), the experimental value present another view regarding the relative importance of biomass yield among different acids and thus, one needs to be careful while using these biomass yield estimates. CONVERSION FACTORS A variety of conversion factors exist in the literature on anaerobic digestion. In the study, focus will be on the conversion factor of 1.3 g COD per g biomass as mentioned by Bryers, (1985), using biomass formula C5H7NO2 as basis. If this conversion factor is used in the following reaction of Graf and Andrews (1971) as given below: CH3COOH + 0.032NH3 → 0.032C5H7NO2 + 0.92CH4 + 0.92CO2 + 0.096H2O (32) From the above reaction, one can see that 1 g acetic acid ≡ (113x0.032/60) g biomass + 0.92x16/60) gCH4. But as per Bryers (1985), the biomass with composition C5H7NO2 has an equivalent COD of 1.3 g COD/ g biomass, Therefore, 1 g acetic acid ≡ (0.032x113x1.3/60) g COD + (16x4x0.92/60) gCH4-COD = 1.0596g COD ≈ 1.06 g COD, which is contrary to the reported COD value of 1 g acetic acid as 1.067 g COD. Similarly, by using a conversion factor of 1.3 in reaction (32), one obtains an equivalent acetic acid COD of 0.979 g COD/g acetic acid. This shows that the COD conversion factor of 1.3 g COD/ g biomass as mentioned by Bryers (1985), is inaccurate. Further, considering the following reactions from the literature (MetCalf and Eddy, (1997) and Nykova et al. (2002)): C5H7NO2 + 5O2 → 5CO2 + 2H2O +NH3 + energy (33) (1 g cells ≡ 160/113 = 1.4159 ≈ 1.42 g COD) C5H9O3N + 5O2 → 5CO2 + 3H2O +NH3 + energy (34) (1 g cells ≡ 160/131 = 1.2214 ≈ 1.22 g COD) From Eq. (33), one observes that the theoretically correct conversion factor for biomass C5H7NO2 is 1.42 g COD/ g biomass. Use of this conversion factor also leads to correct estimates of 1g acetic acid COD equivalence as 1.067. Although, the average of the two compositions of cells lead to 1.33 g COD per g cells, it may not be appropriate to use it arbitrarily in reactions. Further, the value of 1.42 g COD per g 163

Environmental Science & Technology 2014 Vol. 1 cell or 1.22 g COD per g cell shall be used depending upon the representative cell compositions as C5H7NO2 or C5H9O3N in reactions under considerations. Thus, the value of 1.3 g COD per g biomass for cell composition C5H7NO2 used by Bryers (1985) is questionable. Similar is the case with the Bhatti et al. (1996), who have mentioned that 1 g TOC is equivalent to 1.4 litres of CH4 and 1 g Methanol TOC as 2.67 g COD. Considering the conversion reaction of methanol to CH4 as per Florencio et al. (1995), 4CH3OH → 3CH4 + HCO3- + H+ + H2O (35) From reaction (35), it can be seen that 128 g methanol (4 moles of methanol) ≡ 3 mol methane. As 1 mole methane equals 22.4 litres at standard temperature and pressure (STP), hence,1g methanol equals 3x22.4/128 L CH4 = 0.525 L CH4 at STP. As 1 g methanol TOC = 1x12/32 g C/ g methanol = 0.375 g C/ g methanol, and 1 g Methanol TOC = 0.525/0.375= 1.4 L CH4 at STP. In fact, 1 g TOC does not have any sense. From the values of Bhatti et al. (1995), it can be seen that 1 g TOC should have been mentioned as 1 g methanol TOC. Similarly, if one considers the following reactions of acetic acid and methanol for the purpose of computing their COD values, CH3COOH + 2O2 → 2CO2 + 2H2O (36) 2CH3OH + 3O2 → 2CO2 + 4H2O (37) One can find from reaction (36) that 1 g acetic acid TOC = 1.066/0.4 = 2.67 g COD. Here, a factor 0.4 appears in denominator because 1 mol acetic acid TOC = 2x12 g C and 1 g acetic acid TOC = 2x12/60 = 0.4 g C/g acetic acid. Similarly, from reaction (37), one can find that 1 g Methanol TOC = 1.5/0.375 = 4.0 g COD (1 g Methanol = 1.5 gCOD). Thus, the value suggested by Bhatti et al. (1995) that 1 g methanol TOC = 2.67 g COD, appears incorrect. YIELD COEFFICIENT OF CO2 Determination of yield coefficients of CO2 in various reactions of different acids also becomes relevant in modelling of CO2 production in anaerobic digestion. As the COD of CO2 is zero, Denac et al., (1988) represented the yield of CO2 in unit of mole/g COD. Considering the case of acetic acid, one mol acetic acid leads to production of 1 mol of CO2; thus yield is 1 mol CO2/1 mol acetic acid = 1 mol/64 g COD = 1.5625×10-2 mol/g COD. In the same manner, the yield coefficients in case of propionic acid, H2 and glucose can be obtained as 8.929×10-3, 1.5625×10-3, and 6.944×10-3 respectively in view of different reactions (Eqs. (12), (14) and (10)). Considering the mass balance equation for CO2 production as given by Denac et al. (1988) in Eq. (15) of their research paper, one can find the incorrect use of some of these yield coefficients; particularly for H2 and glucose, which has been taken as 1.563 and 9.945×10-3 respectively. EQUIVALENT REPRESENTATION With respect to the kinetic parameters, it was emphasized that different volatile acids can be represented in terms of equivalent acetic acid concentration. Table 4 presents the approach of Lawrence and McCarty, (1969), in which the equivalent representation of different volatile acids has been reported. TABLE 4. Acetic acid equivalent conversion of propionic and butyric acid concentrations as mentioned by Lawrence & McCarty, (1969) Volatile Fatty acids as substrate Propionic acid (T=35°C) Propionic acid (T=25°C) Butyric acid (T=35°C)

mg/ l 1925.0 3715.0 2280.0

Substrate feed concentration (reported value) mg/l as acetic acid mg COD/l 1925×60/74 = 1560.8 (1560) 1925×1.512 = 2910.6 (2910) 3715×60/74 = 3012.2 (3010) 3715×1.512 = 5617.08 (5620) 2280×60/88 = 1554.54 (1555) 2280×1.816 = 4140.48 (4140)

Note: 1.512 is the COD conversion factor for propionic acid and 1.816 for butyric acid (Dinopoulou et al., 1988). Here the equivalent conversion has molar basis. In fact, in the representation of Lawrence and McCarty, (1969), the emphasis has been on the equality of moles. Contrary to the conversion values reported in columns 3 and 4 of Table 4, one can see that the number of moles of acetic acid are same as the number of moles of propionic acid. However, this 164

Environmental Science & Technology 2014 Vol. 1 approach may not necessarily represent the equality of COD values. In fact, when the conversion is done, the reciprocal of molecular weight of the propionic to acetic acids, the resulting values tend to give a closer COD matching. Table 5 shows an alternative method for acetic acid equivalent conversion of propionic and butyric acid concentrations. The computations shown in Table 5 above show that by multiplying with a factor of 1.15, one can have the same COD representation in case of propionic as well as equivalent acetic acid concentration. TABLE 5. An alternative method for acetic acid equivalent conversion of propionic and butyric acid concentrations as mentioned in Lawrence & McCarty, (1969)

Volatile acid as substrate Propionic acid (T=35°C) Propionic acid (T=35°C) Propionic acid (T=25°C) Butyric acid (T=35°C)

mg/ l 1925.0 3715.0 3715.0 2280.0

Substrate feed concentration (given value) mgCOD /l mgCOD /l as acetic acid as given acid f = (b)/(a) (a) (b) 1925×1.066×74/60 1925×1.512 = 2910.6 1.15 = 2530.86 3715×1.066×74/60 3715×1.512 = 5617.08 1.15 = 4884.23 3715×1.066×74/60 3715×1.512 = 5617.08 1.15 = 4884.23 2280×1.066×88/60 2280×1.816 = 4140.48 1.16 ≈ 1.15 = 3564.70

mg COD/l as given acid (a)x f 2910.5 5616.9 5616.9 4099.4

Note: 1.066, 1.512 and 1.816 are the COD conversion factors for acetic, propionic and butyric acids respectively (Dinopoulou et al., 1988).

CONCLUSIONS This paper considers an appraisal of few studies on kinetic parameters for anaerobic digestion and anaerobic systems modelling. The results indicated certain inconsistencies in the literature with regard to the use of kinetic parameters, and conversion factors. With this in view, the present study focuses on the prevailing inconsistencies in anaerobic digestion studies. Incorrect kinetic parameters were used in recent anaerobic system’s modelling studies. Such inconsistencies in kinetic parameters will certainly lead to erroneous predictions in modelling and simulations of anaerobic digestion systems. It is believed that the points focussed in this study on inconsistencies prevailing in the literature, will prove useful in better modelling and simulations of anaerobic digestion systems with use of correct kinetic constants. ACKNOWLEDGEMENTS Author is grateful to Director, MNNIT, Allahabad, U.P., India and MHRD, New Delhi for his encouragement and providing full support in preparation of this manuscript. REFERENCES Bhatti, Z. I., Furukawa, K., and Fujita, M. (1996). “Feasibility of methanolic waste treatment in UASB reactors”. Water Res., 30(11): 2559-2568. Bryers, J. D. (1985). “Structured Modeling of the anaerobic digestion of biomass particulates”. Biotechnol. Bioeng ., 27: 638-649. Buffière, P., Steyer, J.-P., Fonade, C., and Moletta, R. (1995). “Comprenhensive modeling of methanogenic biofilms in fluidized bed systems: mass transfer limitations and multisubstrate aspects”. Biotechnol. Bioeng., 48: 725-736. Costello, D. J., Greenfield, P. F., and Lee, P. L. (1991a). “Dynamic modelling of a single-stage high-rate anaerobic reactor - I. Model derivation”. Water Res., 25(7): 847-858. Costello, D. J., Greenfield, P. F., and Lee, P. L. (1991b). “Dynamic modelling of a single-stage high-rate anaerobic reactor - II. Model verification”. Water Res., 25(7): 859-871. 165

Environmental Science & Technology 2014 Vol. 1 Denac, M., Miguel, A., and Dunn, I. J. (1988). “Modeling dynamic experiments on the anaerobic degradation of molasses wastewater.” Biotechnol. Bioeng., 31: 1-10. Dinopoulou, G., Sterritt, R. M., and Lester, J. N. (1988). “Anaerobic acidogenesis of a complex wastewater : II. Kinetics of growth, inhibition, and product formation”. Biotechnol. Bioeng., 31: 969-978. Florencio, L., Field, J. A. and Lettinga, G. (1995). “Substrate competition between methanogens and acetogens during the degradation of methanol in UASB reactors”. Water Res., 29(3): 915-922. Graef, S. P., and Andrews, J. F. (1973). “Mathematical modeling and control of anaerobic digestion”. AIChE Symp. Ser., 136( 70): 101-131. Lawrence, A. W., and McCarty, P. L. (1969). “Kinetics of methane fermentation in anaerobic treatment”. J. Water Pollution Control Fedn., 41(2): R1-R17. Littinga, G., Rebac., S. and Zeeman, G. (2001). “Challenge of psychrophilic anaerbic wastewater treatment”. Tends in Biotechnology, 19(9): 363-370. Moletta, R., Verrier, D., and Albagnac, G. (1986). “Dynamic modelling of anaerobic digestion”. Water Res., 20(4): 427-434. Metcalf & Eddy, Inc. (1997). “Wastewater Engineering: Treatment, Disposal and Reuse”. Third Ed., Tata McGraw-Hill Publishing Co. Ltd., New York. Nykova, N., Muller, T. G., Gyllenberg, M. and Timmer, J. (2002). “Quantitative analyses of anaerobic wastewater treatment processes: identifiability and parameter estimation”. Biotechnology and Bioengineering, 78 (1): 89-103. Pantea, E. V. and Romocea, T. (2008). “Thermophilic anaerobic wastewater treatment”. Protectia Mediului, Analele Universitatii din Oradea, 8: 183-191. Pavlostathis, S. G., and Giraldo-Gomez, E. (1991). “Kinetics of anaerobic treatment”. Water Sci. Technol., 24(8): 35-59. Rumana, R., Somchai, D. and Kannitha, K. (2000). “Anaerobic processes. Literature Review”. Water Environment Research, 72(5): 576-656.

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APPLYING STATIC MAGNETIC FIELD ON PHYSICAL PROPERTIES OF ACTIVATED SLUDGE: OPTIMIZATION THROUGH RESPONSE SURFACE METHODOLOGY Nur Syamimi Zaidi*, Khalida Muda and Johan Sohaili (Universiti Teknologi Malaysia, Johor Bahru, Johor, Malaysia) ABSTRACT: One of the main challenging issues for activated sludge is the poor settleability that consequently affect the effluent quality. Batch tests were conducted to estimate the optimal conditions for improving the settleability of activated sludge under static magnetic field (SMF). A four-factor central composite design (CCD) was implemented to investigate the main and interaction effects of the variables while response surface methodology (RSM) was utilized for process optimization. Four independent variables, viz. magnetic field (15.0 – 88.0 mT), exposure time (0.5 – 48.0 h), biomass concentration (2000 – 4000 mg/L ) and mixing intensity (200 – 400 rpm) were applied and quadratic model was built to predict the responses. Analysis of variance (ANOVA) was used to evaluate the significance of the independent variables and their interactions with p-values of less than 0.05. At the optimum conditions of 88.0 mT magnetic field, 16.5 h exposure time, 2800 mg/L biomass concentration and 300 rpm mixing intensity, the responses – turbidity reduction, aggregation and settling velocity achieved its maximum values of 92%, 99% and 0.011 cm/s, respectively. The element analysis showed that the applied SMF could enhance the settling property of the activated sludge through the improvement on its aggregation capability. These suggest that the SMF is reliable in accelerating the activated sludge settleability, thus potential to enhance the performance efficiency of the wastewater treatment systems. INTRODUCTION Performance of activated sludge system is always relies on a good solid-liquid separation (Clauss et al., 1998). Even though the system has been the most commonly used technology in treating municipal and industrial wastewaters, its stable operation is still plagued by the separation and settling problems. Such problem can lead to the deterioration of the effluent quality, sludge wash-out, and further potential to collapse the overall treatment system performances (Martins et al., 2004; 2011). Hence, it is a necessity to investigate for a favorable strategy that able to enhance the property of activated sludge mainly on its settling and separation process. One of the strategies that can be implemented is by applying static magnetic field (SMF). This application was reported to significantly influence the bacterial activity in heterogeneous sewage, resulted in the enhanced performances of organic compound biodegradations (Yavuz and Çelebi, 2000; Ji et al., 2010; Łebkowska et al., 2011). The implementation of 7 mT reduced the formaldehyde (FA) concentration and COD by 30% and 26%, respectively (Łebkowska et al., 2011). Yavuz and Çelebi (2000) also observed that the substrate removal rate was initially increased by strengthening the magnetic field, reaching a maximum at 17.8 mT, but decreased with a further increase of the intensity. Liu et al. (2008) applied magnetic field in an anammox upflow system, thus resulted in significant nutrient removal. The study which varied the magnetic field between 16.8 and 218.0 mT observed a maximum increase of nitrogen removal by 30% at 60 mT. Apparently, an excessively strong magnetic field could harmed the bacteria while the low field intensity has no or less effect to the bacteria. Such evidences show that there is lack of confirmation findings on the suitable range of magnetic field that can possibly enhance the separation and settleability of the activated sludge biomass, hence improving the removal performances of the treatment system. Despite many studies conducted on the SMF application towards activated sludge, there are still lack of understandings on the influence of magnetic field, exposure time, biomass concentration and mixing intensity in enhancing the separation and settling property of activated sludge. While the important of these factors has been qualitatively studied, most studies have not yet explored the potential interactions between the factors. The traditional method, known as the one-factor-at-a-time (OFAT) does not fully explore all phenomena that could possibly occur and may cause misinterpretation of the results (Montogomery, 2005; Kusic et al., 2010; Dopar et al., 2011). Therefore, the aim of this study is to investigate the influence of 167

Environmental Science & Technology 2014 Vol. 1 magnetic field, exposure time, biomass concentration and mixing intensity on the separation and settling property of activated sludge in terms of turbidity reduction, aggregation and settling velocity. The central composite design (CCD) approach was employed to quantitatively analyze the effects of those factors, the interactions between them and to indicate any correlation between the factors and the responses. It is expected that the optimal operating factors resulting from these batch tests may offer important reference values for later continuous flow experiments. MATERIALS AND METHODS Experimental Procedures. A total volume of 500 mL containing mixture of measured wet volume activated sludge biomass (2000 – 4000 mg/L) and raw wastewater was mixed in a glass flask that placed in a shaker. The shaker was fabricated to allow an installation of the permanent magnets of sizes 100 x 50 x 5 mm, arranged at all four surfaces of the flask in alternate order. The mixture of the activated sludge was exposed to the magnetic field ranging from 15.0 to 88.0 mT within exposure time of 0.50 to 48.00 h. The initial values of the responses (i.e. turbidity reduction, aggregation and settling velocity) were initially measured before the batch tests started. Throughout the experiments, the mixture was mixed under a specified mixing intensity (200 to 400 rpm). After the magnetic exposure, the mixture was allowed to idle for 10 min before 10 mL of the liquid samples were collected and analyzed for final turbidity. The exposed sludge of 10 mL was also taken to be measured for the final settling velocity. Analytical Methods. All tests were conducted according to Standard Methods for the Examination of Water and Wastewater (APHA, 2005) – MLSS with method 2540B and settling velocity with method 2710E. A spectrophotometer (DR5000 HACH) was used for measuring COD (mg/L).YSI 556 MPS (YSI incorporated, USA) was used for recording the values of pH, temperature (°C) and dissolved oxygen (mg/L) for BOD purposes. Turbidity parameter (FNU) was measured using Milwaukee Turbiditimeter. As for aggregation, the parameter was measured in terms of turbidity. After the reaction under magnetic field was stopped, turbidity of 10 mL MLSS was measured immediately and recorded as turbidity at 0 min (T0). The final/residual turbidity (Ti) of the supernatant is then measured after 10 min. The aggregation ability (Ag%) can be calculated as; Ag% = [(T0 - Ti)/ T0] x 100%. Experimental Design. The magnetic field, exposure time, biomass concentration and mixing intensity were identified as the set of four independent process variables that been investigated due to the influence on the responses, viz. turbidity reduction, aggregation and settling velocity of activated sludge. The CCD method was adopted to decide the number of batch test experiments to be performed for optimization of the process variables. For a design of four independent variables (n = 4), each with two different levels, the total number of experiments (N) was calculated as; N = (2n + 2n + nc) = 24 + (2 x 4) + 6 = 30. This includes the standard 2n factorial points with their origin at the centre, 2n axial points fixed at a distance (α) from the centre to generate the quadratic terms and nc replicate points at the centre (Myers and Montgomery, 2001). After the range of each of the process variables have been defined, the limits are coded at ± 1 for factorial points, 0 for centre point and ± α for axial points. In this study, α for axial points was set to 1.0 (also known as facecentered) due to the consideration that region of interest is approximately same as region of operatibility (Kraber, 2002). Thus, the limit for axial points were eventually same as the factorial points. The selected process variable with their limits are given in Table 1. Table 1. Process control variables and their limits Factorial Star points* Variables -1 +1 -1 +1 A: Magnetic field (mT) 15.0 88.0 15.0 88.0 B: Exposure time (hours) 0.50 48.00 0.50 48.00 C: Biomass concentration (mg/L) 2000 4000 2000 4000 D: Mixing intensity (rpm) 200 400 200 400 * Limit for star points is the same as factorial due to the consideration of α = 1.0 (face-centered)

168

Centre point 0 51.5 24.25 3000 300


RESULTS AND DISCUSSIONS Response Surface Analysis of Turbidity Reduction, Aggregation and Settling Velocity. The results were statistically analysed using full quadratic terms, which include linear, square and interactional terms with the aid of Design-Expert® (version 6.0.4). The results of the analysis of variance (ANOVA) for the responses are summarised in Table 2. Table 2. p-values of the response surface modeling analysis p-values Term Turbidity reduction Aggregation Settling velocity A: Magnetic field 0.0023 < 0.0001 0.0368 B: Exposure time < 0.0001 < 0.0001 0.8716 C: Biomass concentration 0.0027 < 0.0001 0.6287 D: Mixing intensity 0.0097 0.7578 0.2654 A2 0.4374 0.9901 0.2488 B2 0.0446 0.0003 0.0676 0.4656 0.9422 -a C2 D2 0.4319 0.7828 0.0309 AxB 0.0421 0.0007 -a AxC 0.6691 0.0063 -a AxD 0.0521 0.3195 -a BxC 0.0361 0.0016 0.4606 BxD 0.1690 0.7408 0.4606 CxD 0.6244 0.2380 -a R-squared value 92.6% 94.4% 61.8% a Eliminated value resulted from the improved model With respect to the turbidity reduction, the results show that all the linear terms, square term in exposure time, interactional term between magnetic field and exposure time, as well as between exposure time and biomass concentration are significant. The analysed R-squared value of 92.6% indicates the acceptability of the model. The best statistical model that describes the relationship between turbidity reduction and the variables (magnetic field, exposure time, biomass concentration and mixing intensity) is given in Eq. (1). Turbidity reduction = +96.40 + 7.09*A + 18.14*B + 6.92*C – 5.73*D – 4.06*A2 – 11.16*B2 – 3.81*C2 – 4.11*D2 – 4.56*A*B – 0.89*A*C + 4.32*A*D – 4.72*B*C + 2.96*B*D 1.02*C*D (1) Figure 1 shows the contour and surface plot of the defined model (exposure time and biomass concentration) for the turbidity reduction. This interaction has the most significant p-values (0.0361) compared to the other interaction model terms. The figure clearly shows that as the exposure time increased, turbidity reduction is also increased. Such observation can be explained in terms of magnetic memory retained by the activated sludge particles throughout the reaction period. As the exposure time of the particles towards magnetic field increased, their positive and negative charges may become highly in charged. This could increase the possibility of the collision between particles thus, potential to enhance the coagulation and further reducing the turbidity (Higashitani et al., 1992; 1993; Johan, 2003). The increment in turbidity reduction is also governed by the effect of biomass concentration. Similar as the exposure time, the plot also shows that as the biomass concentration increased, turbidity reduction is also increased. This can be reasoned due to the existance of microorganisms that been supplied with respect to the activated sludge biomass. Lots of microorganisms during the reaction period could improved the reduction in turbidity as more ‘workers’ are available to degrade the particles’ contaminants. Positive effects gave by both parameters (exposure time and biomass concentration) allow the interaction to result in significant enhancement on the turbidity reduction. 169

Environmental Science & Technology 2014 Vol. 1 Statistical model as shown in Eq. (2) was also developed to relate the magnetic field, exposure time, biomass concentration and mixing intensity to aggregation.

Aggregation = +98.87 + 3.39*A + 5.89*B +3.36*C – 0.20*D – 0.021*A2 – 7.62*B2 – 0.12*C2 + 0.46*D2 – 2.82*A*B – 2.09*A*C – 0.68*A*D – 2.53*B*C – 0.22*B*D – 0.81*C*D (2)

(b)

(a)

Figure 1. (a) Contour plot and (b) response surface plot representing the relationship between the exposure time, biomass concentration and turbidity reduction

(a)

(b)

Figure 2. (a) Contour plot and (b) Three-dimensional response surface plot show the relationship between the magnetic field, exposure time and aggregation As shown in Table 2, linear term of magnetic field, exposure time and biomass concentration, square term in exposure time, interactional terms between magnetic field and exposure time, magnetic field and biomass concentration, as well as exposure time and biomass concentration are significant in influencing the aggregation of activated sludge. Figure 2 illustrate the relationship of the most significant model term (magnetic field and exposure time) on aggregation with p-value of 0.0007. Based on the figure, at low magnetic field of 15.0 mT, an increase in exposure time resulted in drastic increment of aggregation from about 83.0% to 98.6%. However, the increment is in concave shape indicates that further increase in 170

Environmental Science & Technology 2014 Vol. 1 exposure time would lead to the decrease in aggregation. This could be due to the ability of microorganisms in sustaining high magnetic effect as a result of longer exposure time. Some of the microorganisms can only sustain low level of magnetic effect. If this level is exceeded, the microorganisms may act adversely, thus show reverse effect to the activated sludge property (Yavuz and Çelebi, 2000; Zaidi et al., 2014). Contrary, an increase in magnetic field illustrated increment on aggregation (at low exposure time of 0.50 h) in more saddle shape. This type of surface plot suggested that the increment was in more progressive manner, thus showing that the aggregation enhancement of activated sludge is more stable under such condition (Chin et al., 2006). For the response of settling velocity, p-values of the model terms that been listed in Table 2 are the terms that obtained after the statistical model been improved. The purpose of the improvement is because the initial model was insignificant. As a result, the p-value of the model was improved from 0.1208 (not significant) to 0.0082 (significant). The R-squared value of this model is still slightly lower (61.8%) compared to the R-squared value for turbidity reduction (92.6%) and aggregation (94.4%). The only significant model terms are linear term of magnetic field and square term of mixing intensity. Whereas, the interactional terms viz. exposure time and biomass concentration as well as exposure time and mixing intensity are both insignificant with obtained p-values of 0.4606. Nonetheless, the best statistical model that can be used to represent the settling velocity within the range of the experimental conditions in this study is shown in Eq. (3) below. Settling velocity = + 0.011 + (1.139 x 10-4)*A + (8.333 x 10-6)*B + (2.5 x 10-5)*C – (5.833 x 10-5)*D + (1.523 x 10-4)*A2 – (2.477 x 10-4)*B2 – (2.977 x 10-4)*D2 + (4.063 x 10-5)*B*C – (4.062 x 10-5)*B*D (3) Experimental Condition Optimization. The optimization of experimental conditions was identified by considering whether the turbidity reduction, aggregation and settling velocity were higher than the arbitrarily chosen constraint values. According to the model, the predicted optimized conditions occurred at magnetic field of 88.0 mT, 16.5 h exposure time, 2800 mg/L of biomass concentration and at mixing intensity of 300 rpm. These conditions resulted in 92.1% of turbidity reduction, almost 100% (≈ 99.99%) of aggregation and 0.011 cm/s of activated sludge settling velocity. In order to verify the optimization result obtained from Design-Expert, batch test experiments were carried out in triplicate using the obtained optimum conditions. Average turbidity reduction of 89.1%, aggregation of 97.8% and settling velocity of 0.011 cm/s were recorded against the predicted optimum responses. Although there are differences between the predicted and experimental values of the responses after optimization, the deviation was still in well agreement. CONCLUSIONS This study investigated the advantage of static magnetic field (SMF) and their optimized experimental conditions for improving the physical properties of activated sludge. Under the optimal condition of 88.0 mT magnetic field, 16.5 h exposure time, 2800 mg/L biomass concentration and 300 rpm mixing intensity, the maximum turbidity reduction, aggregation and settling velocity of 92.1%, 99.99% and 0.011 cm/s, respectively, were obtained. Overall, the element analysis evidenced that the applied SMF could enhance the settling property of the activated sludge through the improvement on its aggregation capability. These suggest that the SMF is reliable in accelerating the activated sludge settleability, thus potential to enhance the removal performance efficiency of the wastewater treatment systems. ACKNOWLEDGEMENT The authors thank the Ministry of Science, Technology and Innovation (MOSTI) and Universiti Teknologi Malaysia (UTM) for financially support this research (Grant Project No: 4S032). REFERENCES 1. American Public Health Association. 2005. Standard Methods for the Examination of Water and Wastewater. 21th ed. Washington DC, USA. 171

Environmental Science & Technology 2014 Vol. 1 2. Chin C.-J.M., Chen, P.-W. and Wang, L.-J. 2006. “Removal of nano particles from CMP wastewater by magnetic seeding aggregation”. Chemosphere. 63 (10): 1809 – 1813. 3. Clauss, F., Hélaine, D., Balavoine, C. and Bidault, A. 1998. “Improving activated sludge floc structure and aggregation for enhanced settling and thickening performances”. Water Sci. Technol. 38: 35 – 44. 4. Dopar, M., Kusic, H. and Koprivanac, N. 2011. “Treatment of simulated industrial wastewater by photo-Fenton process. Part I: The optimization of process parameters using design of experiments (DOE)”. Chem. Eng. J. 173: 267 – 279. 5. Higashitani, K., Okuhara, K. and Hatade, S. 1992. “Effects of magnetic fields on stability of nonmagnetic ultrafine colloidal particles”. J. Coll. Int. Sci., 152: 125-131. 6. Higashitani, K., Kage, A., Katamura, S., Imai, K. and Hatade, S. 1993. “Effects of magnetic field on formation of CaCO3 particles”. J. Coll. Int. Sci., 156: 90-95. 7. Ji, Y., Wang, Y., Sun, J., Yan, T., Li, J., Zhao, T., Yin, X., and Sun, C. 2010. “Enhancement of biological treatment of wastewater by magnetic field”. Bioresour. Technol. 101: 8535 – 8540. 8. Johan, S. 2003. Effect of magnetic field on the sedimentation of suspended solids of sewage. Thesis of Philosophy of Doctorate: Universiti Teknologi Malaysia. 9. Kraber, S. 2002. Handbook for experimenters. Stat-Ease Inc., Minneapolis, USA. 10. Kusic, H., Jovic, M., Kos, N., Koprivanac, N. and Marin, V. 2010. “The comparison of photooxidation processes for the minimization of organic load of colored wastewater applying the response surface methodology”. J. Hazard. Mater. 183: 189 – 202. 11. Łebkowska, M., Rutkowska-Narożniak, A., Pajor, E. and Pochanke, Z. 2011. “Effect of a static magnetic field on formaldehyde biodegradation in wastewater by activated sludge”. Bioresource Technol. 102 (19): 8777 – 8782. 12. Liu, S., Yang, F., Meng, F., Chen, H. and Gong, Z. 2008. “Enhanced anammox consortium activity for nitrogen removal: Impacts of static magnetic field”. J. Biotechnol. 138 (3-4): 96 – 102. 13. Martins, A.M.P., Karahan, Ö. and van Loosdrecht, M.C.M. 2011. “Effect of polymeric substrate on sludge settleability”. Water Res. 45 (1): 263 – 273. 14. Martins, A.M.P., Pagilla, K., Heijnen, J.J. and van Loosdrecht, M.C.M. 2004. “Filamentous bulking sludge – A review”. Water Res. 38: 793 – 817. 15. Montogomery, D.C. 2005. Design and analysis of experiments. John Wiley and Sons, New York, USA. 16. Myers, R.H. and Montgomery, D.C. 2001. Response surface methodology. 2nd ed., John Wiley and Sons, New York, USA. 17. Yavuz, H. and Çelebi, S.S. 2000. “Effect of magnetic field on activity of activated sludge in wastewater treatment”. Enzyme Microb. Technol. 26: 22 – 27. 18. Zaidi, N.S., Sohaili, J., Muda, K. and Sillanpää, M. 2014. “Magnetic field application and its potential in water and wastewater treatment systems: A review”. Sep. Pur. Rev. 43: 206 – 240.

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LIFE CYCLE ASSESSMENT OF A MUNICIPAL WASTEWATER TREATMENT PLANT- A CASE STUDY IN KINMEN, TAIWAN Huan-Yu Shiu and Pei-Te Chiueh (National Taiwan University, Taipei, Taiwan) Life cycle assessment (LCA) was used to evaluate the environmental benefits and impacts associated with the treatment of a wastewater treatment plant in Kinmen, Taiwan. CML 2000 model was selected as the life cycle impact assessment tool using SimaPro software. The objective of this study is to compare current treatment process with other proposed advanced treatment processes. The system boundary of present LCA includes operation and maintenance phase, sludge treatment and disposal, and water reuse. The results show that the impact of water reuse does not lead to substantial environmental impact in most of the LCA impact categories. Water reuse is recommended for water-stressed situations, especially for Kinman which is an outlying island. Digested sludge for agricultural applications can reduce the eutrophication potential impact and have benefits for agriculture. The study reveals main environmental loading process of wastewater treatment and provided an approach for supporting the choice of treatment process.

173


EVALUATION OF BACTERIA AND METALS IN SEWAGE DUMP SITE IN JOS-NIGERIA Yakubu, Juliet M (Federal University, Wukari-Nigeria) and Agarry O. O (University of Abuja, Nigeria) The bacterial load and heavy metal content was carried out on a domestic sewage dump to determine the suitability of the soil for agricultural use as is the current practice. The total viable mean colony of the 17 bacterial species detected ranged from 214.3-229.7 for soil sample; 709-779 for soil-sewage sample and 406.3-451 for deep-pit sample cells/plate. All the isolates were mesophilic showing a decrease in number below and above 31oC. Inductively coupled Plasma Optical Emission Spectrum was used to detect 11 metals including As, Cr, Cu, Fe, K, Na, P, Sb, Se and Zn in the sludge in order to assess the pollutants and determine the suitability of the soil for agricultural purposes. The data generated showed no hazard so far for the direct use of such domestically generated sewage for agricultural use as biofertiliser.

174


THE EFFECT OF EPS ON MIXED LIQUOR CHARACTERISTICS AND MEMBRANE FOULING IN UCT¬MBR PROCESS Qiongyuan Dong, Xiaonan Feng∗, Tao Tao, Lin Chen, Junhong Zhou and Guohong Yang ( School of Environmental Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China) a

ABSTRACT: This study investigated the effect of extracellular substances (EPS) which was represented by different MLSS concentrations on mixed liquor characteristics and membrane fouling in the UCTMBR process. The system has operated for two months on the stable nutrient removal with complete sludge retention before investigation. The characteristics of mixed liquor in terms of EPS, soluble microbial products (SMP), particle size distribution (PSD), UV254 and Zeta potential were investigated in order to evaluate their correlation with membrane fouling. It was found that the concentration of EPS and SMP increased in the order of MLSS 4852 < 6326 < 7590 < 8793 mg/l, then the membrane fouling increase significantly. The correlation between flux, TMP with mixed liquor characteristics followed the order of protein content in EPS < MLSS < polysaccharide content in SMP. And the parameters of UV254, PSD, Zeta potential were positively correlated with fouling. INTRODUCTION Membrane bioreactor (MBR) process has been approved to be effective and extensively used in water and wastewater treatment. It is well know that MBR technology have many advantages over conventional activated sludge processes, including better quality effluent, higher mixed liquor suspended solid (MLSS) concentration, longer sludge retention time (SRT), and lower sludge production (Miura et al., 2006; Rosenberger et al., 2002). Moreover, since the decreased of membrane cost and the shortage of water resource, it has induced more and more researches and applications of MBR process for biological wastewater treatment and reclamation. However, membrane fouling is one of the critical technical difficulties for the pollutant efficiently removal stable and control the cost (Trussell et al., 2007; Zhiqiang et al., 2006). Given the lower sludge production of MBR, there is great interest in the complete sludge retention of MBR system (Delai Sun et al., 2007; Ersu et al., 2010; Sridang et al., 2008). It has been verified the operation parameters of SRT has great impact on fouling (Al-Halbouni et al., 2008; Le-Clech et al., 2006). In the submerged MBR process, the sludge suspension was the primary cause fouling. And the near-zero sludge discharge systems would directly affect the properties of sludge suspension. The sludge properties such as extracellular polymeric substance (EPS), soluble microbial products (SMP), floc size, Zeta potential and other parameters have complicated relations with membrane fouling. Ahmed et al. (Ahmed et al., 2007) have observed the low SRT (20d) would produce higher bound EPS which was adversely to membrane performance. Meng et al. (Meng et al., 2009) have concluded that the SRT has effect on the production of EPS and the optimum for membrane fouling control should range at 20–50 d. Recently membrane fouling was focus on operation optimization and membrane cleaning. Few researches investigated the fundamental causes of fouling in near-zero sludge discharge UCT-MBR process. This study aims to investigate the correlation of MLSS with the mixed liquor characteristics, and analysis the decisive factors of membrane fouling through correlation models. MATERIALS AND METHODS Experimental Set-up and Operation Conditions. The configuration of UCT-MBR used in this study composed of anaerobic, anoxic and aerobic reactors with 7L, 12.5L and 16L working volume respectively. The membrane modules of hollow fiber (Suzhou Litree UF Membrane Technology Co., Ltd, China), with *

Corresponding author. Tel.: +86-27-87792152; Fax: +86-27-87792101. E-mail address: [email protected] (X. Feng).

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Environmental Science & Technology 2014 Vol. 1 effective filtration area of 0.75 m2, were immersed in aerobic reactors. And the nominal pore size of membranes is 0.02 μm. The permeate generation was extracted by peristaltic pump with negative pressure on the membrane. Microporous aeration tubes were installed underneath the membrane modules to supply dissolved oxygen as well as to mitigate membrane fouling in the aerobic reactor. The anaerobic and anoxic reactors are equipped with mixers for fluid mixing. In the anoxic a baffle is set to divide the reactor into two parts with volume ratio of 1:2. The internal recycles of the mixed liquor included recycle I (RI) and recycle II (RII), which continually from aerobic to anoxic front and anoxic rear-end to anaerobic separately. The flow rate of RII and RI were 100% and 150% of influent, respectively. The operation conditions were set at optimum parameters by 70 days debugging. And there no sludge was discharged during the debugging. The four levels of MLSS concentrations in aerobic were designed as 4500, 6000, 7500 and 9000 mg/L. The measured values were 4852, 6326, 7590 and 8793 mg/L. The dissolve oxygen (DO) concentration was determined and controlled at 0.5-2mg/l, 4.4-5mg/l in anoxic and anaerobic reactor respectively. ORP value were -180～-270, -30～76, and 80～153 mV in anaerobic, anoxic and aerobic reactors. Raw Wastewater. Synthetic wastewater fed to the reactor contained sodium acetate, NH4Cl, and KH2PO4 served as nutrients of carbon, nitrogen and phosphorus, respectively. The mineral solution consisted with 30 mg/L MgSO4.7H2O and 10 mg/L CaCl2 was also added into the wastewater. The concentration of total organic carbon (TOC), NH4+-N and total P (TP) of the synthetic wastewater were 47.62±3.61, 28.62±4.2 and 4.66±1.6, respectively. And the pH of raw wastewater was 8.77. Analytical Methods. Samples were collected from the aerobic reactor and permeate effluent under steadystate conditions. The MLSS, NH4+–N and total phosphate (TP) was measured according to Standard Methods (APHA 1998). The aerobic sludge mixed liquor were sampled and filtered through 0.45 μm filters for detected of SMP, UV254. EPS were extracted following the procedure of centrifugation (4800 r/min) for 10 min, then heated at 80℃ for 20 min, then filtered through 0.45μm filters and analyzed. The components of EPS contain polysaccharides (EPSC), proteins (EPSP) and other components, which include humic acids and nucleic acids. Polysaccharides were determined according to Dubois et al. (1956) and proteins were determined according to the method of modified Folin-phenol described by Froelund et al. (1995). In this experiment, the concentration of TOC represents the total amount of EPS, and other components of EPS were calculated by EPS subtract polysaccharides and proteins contents. DO, ORP and pH were measured using DO and pH meters (YSI, USA). And the membranes flux and transmembrane pressure (TMP) were monitored daily. Statistical Analysis. Statistical analysis was carried out by using the Pearson correlations of SPSS 11.0 software. Pearson’s correlation coefficient (rp) was used for estimated the correlations between every two parameters. The rp ranges between －1 and +1, where means perfect negative and positive correlations respectively, while 0 means an absence of a relationship. Factors analysis method was used for all parameters correlation analysis. The KMO (Kaiser-MeyerOklin Measure of Smapling Adequacy) and Bartlett Sphericity Test were used firstly to determine the original variables whether suitable or not for the use of factors analysis method. RESULTS AND DISCUSSION Variation of EPS Concentrations. As shown in FIGURE 1A, the total amount of EPS concentration increased as MLSS increased from 4852 to 8793 mg/l. The protein was the major composition of EPS and its percentage was 83%~90% (FIGURE 1B), and similar result has been reported in high SRT system by Liao et al (Liao et al., 2001). The results indicated that an increase of MLSS could lead to the change of sludge mixed liquor properties. The amount of EPS and its composition was determined by the production and degradation of microorganism. On one hand the higher organic load lead to microbial growth and store the organics into intracellular polymer. However, as the MLSS concentration gradually increased to more than 7590 mg/L, microorganism was in endogenous stage for organic substances became insufficient, then EPS increased 176

Environmental Science & Technology 2014 Vol. 1 sharply and other substances also release. Meanwhile, most extracellular secretion of high molecular substance were rejected by ultrafiltration membrane and degraded as residence time increased. The contrary aspects contributed to the growth platform at MLSS of 8793 mg/l. 50

(B) 100

40

80

30

30

20

20

10

10

0

4852mg/l 6326mg/l 7590mg/l 8793mg/l

Percentage (%)

40

E-Polysaccharide E-Protein Others EPS

EPS (mg/g.VSS)

Concentration (mg/l)

(A) 50

Polysaccharide

Protein

Others

60 40 20

0

0

4852mg/l 6326mg/l 7590mg/l 8793mg/l

MLSS

MLSS

FIGURE 1. Effect of MLSS on EPS and its composition production. (A) Concentrations, (B) Percentage. Soluble Microbial Products (SMP). The compositions of SMP were similar to EPS and the FIGURE 2 illustrated polysaccharide was the major substance of 57%~63%. As shown in FIGURE 2, the total amount of SMP was markedly increased as MLSS increasing and the same trend of polysaccharide. The increased concentration of SMP was ascribed to membrane rejection and microorganism endogenous respiration production. The organic substance of influent was synthetic at low and constant concentration, as the MLSS increased it became insufficiently and microorganism used polysaccharide and protein of SMP as carbon resources. When the concentration of MLSS achieved to certain degree, the production and degradation of SMP reached balanced, then the concentration of SMP tended stability.

Concentration (mg/L)

10 8

16

Polysaccharide Protein Others SMP

14 12 10

6

8 6

4

4 2 0

SMP (mg/L)

12

2 4852mg/l

6326mg/l

7590mg/l

8793mg/l

0

MLSS

FIGURE 2 Effect of MLSS on the concentration of SMP and its compositions. TABLE 1. Pearson’s correlation coefficient (rp) between MLSS concentration and sludge properties MLSS

rp

p

EPS

0.856

0.000

EPSC

0.408

0.063

EPSP

0.863

0.000

SMP

0.787

0.000

SMPC

0.749

0.000

SMPP

0.429

0.052

177

Environmental Science & Technology 2014 Vol. 1 The concentration of MLSS showed significant positive effect on the production of EPS (rp = 0.856; p = 0.000) and SMP (rp = 0.787; p = 0.000). The EPSP also showed positive correlation with MLSS and was the most significant parameters in TABLE 1. However, EPSC and SMPP did not show significant correlation between MLSS probably due to the dominant composition of EPS and SMP were protein and polysaccharide, separately. TABLE 2. Coefficient matrix of component score COMPONENT 0.134 0.137 0.149 0.129 -0.081 0.123 0.107 0.11 0.061 0.033 0.129 -0.131

MLSS EPS EPSP EPSC EPSP/EPSC SMP SMPP SMPC SMPP/SMPC Zeta potential Cake layer of Zeta SMP-UV254

The compositions of SMP and EPS were similarly while the proportion of each component was different. There may be existed internal relations in the production, dissolution, degradation between SMP and EPS. In addition, researcher have pointed that part of SMP was dissolved EPS (Lin et al., 2014). It was concluded that MLSS influenced EPS significantly and EPS dissolution is the main way to produce SMP, whereas SMP was mainly affected by the EPS and MLSS together. Factors Analysis of Mixed Liquor Characteristics. The mixed liquor characteristics parameters including MLSS, EPS, EPSP, EPSC, EPSP/EPSC, SMP, SMPP, SMPC, SMPP/SMPC, Zeta potential, Cake layer of Zeta, and UV254 of SMP (SMP-UV254). The software of SPSS was carried out for factors analysis and the results were showed in TABLE 2. The extraction method adopt principal component and one component was extracted in TABLE 2. The all eleven parameters effect for the overall level of mix liquor was lowers than 0.2 (TABLE 2). It indicated that each parameter has strong correlations in the mix liquor. Generally, the mixed liquor characteristics are a dynamic process of factors interaction and MLSS is a public factor of influence. In addition, EPS is the closely related index with MLSS. Membrane Fouling Correlation Analysis. Based on the correlation analysis, SMP was affected by EPS and MLSS together. The effect fundamental parameters of membrane fouling were MLSS and SMP. During the experiment, the hollow fiber membrane flux was large and there was no obviously decline. In order to avoid the potential risk of measuring error and really reflect the correlation of membrane fouling and mixed liquor characteristics. Multivariate correlation analysis was adopted to make a statistics about the influence of MLSS and SMP concentration to the transmembrane pressure (TMP). Previous research considered that there lies in an exponential relationship between membrane mass transfer resistance and the concentration of MLSS and SMP. The correlation equation was assumed as follows (Eq1). The regression equation obtained by this method showed as Eq2. TMP = k·MLSSa·SMPb TMP = 0.6121·MLSS0.1281·SMP0.0751

(1) (2)

The Eq2 showed positive correlations between TMP and the concentration of MLSS and SMP. However, SMP has less effect to the TMP compared with the MLSS. As FIGURE 3 showed, the measuring value of TMP compared with its simulation value to test the accuracy of the regression equation. Results indicated that the simulation value of TMP was in agreement with the measuring value, and the average relative error was 7.84%. Therefore the regression equation was effectively. 178


17.5 measured simulated

17.0

TMP (KPa)

16.5 16.0 15.5 15.0 14.5 14.0

0

5

10 15 20 25 30 35 40 45

Sample number FIGURE 3 The comparison of measured and simulated values

CONCLUSIONS This paper investigated mixed liquors characteristics and membrane fouling in UCT-MBR process. Based on the results illustrated in this study, the following conclusions can be drawn: The concentration of EPS and SMP of mixed liquor increased as MLSS concentration increasing from 4500 mg/l to 9000 mg/l. The major component of EPS and SMP is protein and polysaccharide respectively. The concentration of MLSS has significant positive effect on the production of EPS and SMP. EPS is mainly affected by MLSS, and SMP influenced by EPS and MLSS together. MLSS and SMP are the fundamental parameters affect membrane fouling. Multivariate correlation equation is TMP = 0.6121·MLSS0.1281·SMP0.0751. REFERENCES Ahmed, Z., J. Cho, B. Lim, K. Song, and K. Ahn. 2007. “Effects of sludge retention time on membrane fouling and microbial community structure in a membrane bioreactor.” J. Membr. Sci. 287: 211-218 Al-Halbouni, D., J. Traber, S. Lyko, T. Wintgens, T. Melin, D. Tacke, A. Janot, W. Dott, J. Hollender. 2008. “Correlation of EPS content in activated sludge at different sludge retention times with membrane fouling phenomena.” Water Res. 42: 1475-1488 Delai Sun, D., S. Loong Khor, C. Teck Hay, J. O. Leckie. 2007. “Impact of prolonged sludge retention time on the performance of a submerged membrane bioreactor.” Desalination. 208: 101-112 Ersu, C.B., S.K. Ong, E. Arslankaya, Y. Lee. 2010. “Impact of solids residence time on biological nutrient removal performance of membrane bioreactor.” Water Res. 44: 3192-3202 Le-Clech, P., V. Chen, T. A. G. Fane. 2006. “Fouling in membrane bioreactors used in wastewater treatment.” J. Membr. Sci. 284: 17-53 Liao, B.Q., D.G. Allen, I. G. Droppo, G. G. Leppard, S. N. Liss. 2001. “Surface properties of sludge and their role in bioflocculation and settleability.” Water Res. 35: 339-350 Lin, H., M. Zhang, F. Wang, F. Meng, B. Liao, H. Hong, J. Chen, W. Gao. 2014. “A critical review of extracellular polymeric substances (EPSs) in membrane bioreactors: Characteristics, roles in membrane fouling and control strategies.” J. Membr. Sci. 460: 110-125 Meng, F., S. Chae, A. Drews, M. Kraume, H. Shin, F. Yang. 2009. “Recent advances in membrane bioreactors (MBRs): Membrane fouling and membrane material.” Water Res. 43: 1489-1512 Miura, Y., Y. Watanabe, S. Okabe. 2006. “Membrane Biofouling in Pilot-Scale Membrane Bioreactors (MBRs) Treating Municipal Wastewater: Impact of Biofilm Formation.” Environ. Sci. Technol. 41: 632-638 Rosenberger, S., U. Krüger, R. Witzig, W. Manz, U. Szewzyk, M. Kraume. 2002. “Performance of a bioreactor with submerged membranes for aerobic treatment of municipal waste water.” Water Res. 36: 413-420 179

Environmental Science & Technology 2014 Vol. 1 Sridang, P. C., A. Pottier, C. Wisniewski, A. Grasmick. 2008. “Performance and microbial surveying in submerged membrane bioreactor for seafood processing wastewater treatment.” J. Membr. Sci. 317: 43-49 Trussell, R. S., R.P. Merlo, S. W. Hermanowicz, D. Jenkins. 2007. “Influence of mixed liquor properties and aeration intensity on membrane fouling in a submerged membrane bioreactor at high mixed liquor suspended solids concentrations.” Water Res. 41: 947-958 Zhiqiang, C., W. Qinxue, W. Jianlong. 2006. “High rate aerobic treatment of synthetic wastewater using enhanced coagulation high-performance compact reactor (EC-HCR).” Biochem. Eng. J. 31: 223-227

180


AN APPROACH FOR SELECTION OF WASTEWATER TREATMENT UNITS USING ANALYTICAL HIERARCHY PROCESS

Nekram Rawal* and A.K.Sachan (Department of Civil Engineering, MNNIT, Allahabad-211004, U.P., INDIA) ABSTRACT: there are several established and time tested technologies available for treatment of municipal wastewater. Each technology has its own merits depending on its suitability and fulfillment of requirements and a set of criteria. This paper focuses to evaluate suitability of wastewater treatment technologies in different situations. The analytical hierarchy process (ahp), a known multi-criteria decision-analysis approach, has been incorporated to subsequently develop a decision support tool to select most suitable wastewater treatment technology for treating municipal wastewater with effluent quality conforming to indian standards. Quantitative weightings from the ahp are used to identify alternative systems that have similar outcomes in meeting the systems objective, but may have different cost structures, reliability and effluent quality. Three known technologies options were primarily taken for selection of wastewater treatment technologies, trickling filter system, waste stabilization pond and activated sludge process. The result obtained by ahp approach shows that option with waste stabilization pond is the best treatment technology among all other treatment process in terms of economic parameters. Key words. analytical hierarchy process (ahp), trickling filter, waste stabilization pond, activated sludge process.

INTRODUCTION In presently designers, engineers and constructors are working hard to find the solution of selecting such a design alternative which is technically feasible, sustainable and at the same time economic in the long run. There are several established and time tested technologies available for treatment of municipal wastewater. Each technology has its own merits and demerits depending on its suitability and fulfillment of requirements and a set of criteria. Several methods have so far been developed, tried and tested to select the best option based on the above set goals. The Analytical Hierarchy Process (AHP) is one of the method that provides a significantly better economic assessment of the long term cost effectiveness of a project with the merits and demerits of mutually exclusive design options . It is a systematic, analytical process developed by Satty, T.L.; Kearns, K.P. (1985) has been applied to a wide variety of decisions and the human judgment process (Lee et al.,2001). This technique is one of the MCDA (Multi Criteria Decision Analysis) methods with many capabilities used in different scientific disciplines and suitable for solving complicated issues such as resources allocation, project design, planning for urban development, maintenance management (Cook et al., 1984). Decision maker then find out simple pair wise comparison judgments throughout the hierarchy to arrive at overall priorities for the alternatives suggested (Higgs, 2006). The decision problem may involve social, political, technical, and economical factors. AHP analysis make it useful tool for environmental sustainability assessment and decision-making (Schmoldt et al.,2001). In environmental performance field studies, AHP has been widely employed such as; environmental impact assessment (Ramanathan, 2001), environmental quality indexing (Solnes, 2003), environmental vulnerability assessment (Tran et al.,2002), energy resources (Ramanathan et al.,1995), environmental impacts of manufacturing (Pineda-Henson et al.,2002), landfill site selection problem (Mummola, 1996), land use pattern (Malczewski et al.,1997), and resource allocation of agricultural activities (Alphonce, 1997). The AHP helps people cope with the intuitive, the rational and the irrational. At the end of the process, decision makers are fully cognizant of how and why decision was made, with results that are meaningful, easy to communicate and actionable. In this paper, an attempt is made to select the best design option of wastewater treatment technology treating 12MLD plant of municipal wastewater of semi-urban locality of India.

181


TECHNOLOGY OPTIONS The selection of treatment technology for municipal treatment eventually depends upon wastewater characteristics, treatment objectives as translated into desired effluent quality and the environmental condition. All treatment technology options lower the quality of effluent conforming to Indian standards. In this study, the three options of treatment technology are taken for consideration for AHP analysis. These three options are:- (i) Option A: Trickling filter is now almost universally adopted wastewater treatment process. Rate of filter loading is high, as such requiring lesser land areas and smaller quantities of filter media for installation. (ii) Option B: Waste Stabilization Ponds are well-established methods and having many advantages includes simplicity, low cost of construction, low maintenance, low energy consumption, robustness, and sustainability. (iii) Option C: Activated sludge process is in use since the early 1900s. The operational advantages are, lesser land area required, head loss in the plant is low, greater flexibility in operation, permitting control on the quality of effluent.

FIGURE 1. AHP principles and its steps TABLE 1. Pair-wise comparison scale for AHP preferences Numerical Rating 5 4 3 2 1 Reciprocals of the above non zero numbers

Verbal Judgments of Preferences Strongly preferred Moderately to strongly Moderately preferred Equally to moderately Equally preferred

Numerical Rating 9 8 7 6

Verbal Judgments of Preferences Extremely preferred Very strongly to extremely Very strongly preferred Strongly to very strongly

If factor i has one of the above non-zero numbers assigned to it when compared to factor j, then j has the reciprocal value when compared with i.

METHODOLOGY The analytical hierarchy process (AHP) developed by Saaty (1980) deals with the complex decision making problems, which involves many attributes/variables and some sort of subjectivity. The principles of AHP and its steps (Hambali et al.,2009) shown in Figure 1. It offers a pair-wise comparison of components 182

Environmental Science & Technology 2014 Vol. 1 of the systems, precisely if the attributes are objective or provide the scaling if the attributes are subjective in nature. The comparisons are made for each variable and sub variables and the matrix is constructed by the preferences are quantified by using a nine-point scale of comparisons and is given in Table 1[1].

FIGURE 2. Hierarchy of the project Development of Hierarchy. A three level hierarchy decision process suggested by Zeng et al., 2007 shown in Figure 2. The overall goal is to select the most suitable wastewater technology is presented at the top level of the hierarchy. The second level represents the criteria’s that influence selection of a wastewater treatment technology. Develop Pair-Wise Comparison Matrix. The all matrices are developed pair-wise comparisons as shown in Table 2, eigenvectors or the relative weights (the degree of relative importance amongst the elements), global weights, and the maximum eigenvalue ( λmax ) for each matrix are then calculated. TABLE 2. Comparative judgment matrix for selection of best wastewater treatment technology Criteria Capital cost(CC) Operation & Maintenance cost (O&M) Ability to handle flow variation(ATH) Reliability(R) Effluent quality (E)

A (TF) Higher Higher Good Very good Moderate

Technology Options B (WSP) C (ASP) Highest High Lowest Highest Moderate Fair Very good Good Good Very good

RESULTS AND DISCUSSIONS The methodology demonstrated for treating 12 MLD municipal wastewater of semi urban area at Kalyani located 40 km from Kolkata, India. The study is carried out to evaluate suitability of wastewater treatment technologies by AHP. Development of Pair-wise Comparison Matrices: The decision makers have to indicate preference or priority for each decision alternatives. Table 3 shows the pair-wise comparison matrices for each criteria i.e capital cost, operation and maintenance cost, Ability to handle flow variation, reliability and effluent quality of treatment option and Table 4 shows pair-wise comparison matrix for all five criteria in terms of importance of each in contributing to the overall goal. Calculation of Priority Vector: The Table 5 shows the priority vector for each criteria of treatment option and Table 6 shows the priority vector for all five criteria in terms of importance of each in contributing. The elements in each row are multiplied with each other and then the nth root (where n is the number of elements in the row. Next the numbers are normalized by dividing them with their sum. 183


TABLE 3. Pair-wise comparison matrix Options

A

A B C

1 1/3 2

A B C

1 3 1/2

A B C

1 1/3 1/4

A B C

1 1 1/3

A B C

1 3 4

B Capital cost 3 1 3 Operation & Maintenance 1/3 1 1/3 Ability to handle flow variation 3 1 1/3 Reliability 1 1 1/3 Effluent quality 1/3 1 2

C

1/2 1/3 1 2 3 1 4 3 1 3 3 1 1/4 1/2 1

TABLE 4. Pair-wise comparison matrix for five criteria

CC O&M ATH R E

Capital cost

Operation & Maintenance

1 1/2 1/4 1/4 1/2

2 1 1/3 1/3 1/2

Ability to handle flow variation 4 3 1 1/2 3

Reliability

Effluent quality

4 3 2 1 3

2 2 1/3 1/3 1

Consistency Ratio (CR): The value of CR is less than or equal to 0.05 for 3x3 matrices and less than or equal to 0.10 for 5x5 matrix in all five criteria, it means that the matrix is acceptable or indicates a good level of consistency in the comparative judgments represented in each matrix. Development of Overall Priority ranking of all the Design Options: The criteria priorities and the priorities of each decision alternative relative to each criterion are combined in order to develop an overall priority ranking of all the alternatives that is termed as the decision matrix shown in Table 8. The overall rank of the design options against calculations done using the AHP analysis, the Option B, Waste Stabilization Pond system is the best wastewater treatment technology and having very high overall priority vector among the criteria. CONCLUSIONS 184

Environmental Science & Technology 2014 Vol. 1 Analytical Hierarchy Process (AHP) recommends that option with waste stabilization pond is the best treatment technology among Trickling Filter and Activated Sludge Process treatment technology in terms of all other economical parameters.

TABLE 5. Priority Vector Options A B C

A B C

A B C

A B C

A B C

Capital cost (1x3x1/2)1/3 1.145 1/3 (1/3x1x1/3) 0.481 (2x3x1)1/3 1.816 Sum 3.442 Operation and maintenance cost (1x1/3x2)1/3 0.874 (3x1x3)1/3 2.079 1/3 (1/2x1/3x1) 0.550 Sum 3.503 Ability to handle flow variation (1x3x4)1/3 2.288 (1/3x1x3)1/3 1.000 (1/4x1/3x1)1/3 0.437 Sum 3.725 Reliability (1x1x3)1/3 1.442 (1x1x3)1/3 1.442 (1/3x1/3x1)1/3 0.481 Sum 3.365 Effluent quality (1x1/3x1/4)1/3 0.437 (3x1x1/2)1/3 1.145 (4x2x1)1/3 1.999 Sum 3.580

Priority vector 0.333 0.140 0.528 1.000 0.250 0.594 0.157 1.000 0.614 0.268 0.117 1.000 0.429 0.429 0.143 1.000 0.122 0.320 0.558 1.000

TABLE 6. Priority vector for the five criteria CC O&M

Geometric mean value (1x1/2x3x3x1/2)1/5 (2x1x3x3x2)1/5

1.176 2.048

Priority vector 0.202 0.352

ATH

(1/3x1/3x1x2x1/3)1/5

0.594

0.102

0.450 1.552 5.820

0.077 0.267 1.000

1/5

(1/3x1/3x1/2x1x1/3) (2x1/2x3x3x1)1/5

R E Sum

TABLE 7. The Consistency Ratio (CR) Sl. no

Consistency ratio

Remark

1

Capital cost

Criterion

0.05= 0.05

Consistent

2

Operation & Maintenance

0.048