Spatial variability of concentrations of gaseous

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Atmospheric Pollution Research xxx (2016) 1e9

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Original article

Spatial variability of concentrations of gaseous pollutants across the National Capital Region of Delhi, India S. Tyagi a, *, S. Tiwari b, A. Mishra a, Philip K. Hopke c, S.D. Attri d, A.K. Srivastava b, D.S. Bisht b a

Department of Environmental Science, School of Vocational Studies and Applied Sciences, Gautam Buddha University, Greater Noida, UP 201303, India Indian Institute of Tropical Meteorology, New Delhi Branch, 110060, India Clarkson University, Box 5708, Potsdam, NY 13699-5708, USA d India Meteorological Department, Lodi Road, New Delhi 110003, India b c

a r t i c l e i n f o

a b s t r a c t

Article history: Received 6 November 2015 Received in revised form 20 April 2016 Accepted 21 April 2016 Available online xxx

This study presents a systematic evaluation of a year-long, continuous, real-time measurements of gaseous pollutants including oxides of nitrogen (NOx ¼ NO þ NO2), carbon monoxide (CO), and ozone (O3) in the National Capital Region (NCR) of Delhi. Data are available from seven air quality monitoring stations (AMS) and meteorological parameters were measured at three meteorological observatories (MO). The daily mean concentrations of NOx and CO across NCR of Delhi (average of all seven AMSs) were 37.1 ± 11.6 ppb (NO: 18.3 and NO2: 18.8 ppb), and 2.3 ± 0.6 ppm, respectively. The highest diurnal CO concentrations were observed during midnight (21:00 to 01:00 h LT) due to nocturnal boundary conditions. The daily mean O3 concentration was 37.5 ± 11.0 ppb. The diurnal variations of O3 concentrations were characterized by the high concentrations during the daytime (07:00 to 17:00 h LT: 43.6 ppb) and low concentrations during the late evening and early morning hours (18:00 to 06:00 h LT: 31.1 ppb). From 07:00 h onwards, the O3 concentrations start increasing gradually after sunrise coinciding with the increasing solar radiation. The highest concentrations (51.7 ppb) were observed around 15:00 h. Thereafter, it is decreased. Local sources of gaseous pollutants were identified by analyzing the surface wind patterns. The annual resultant wind vector were 338 (57%) and 288 (27%) at the Hindon and Palam MOs, respectively. Local NO emissions substantially reduced the urban ozone concentrations as seen by the observed untitrated NO concentrations. Copyright © 2016 Turkish National Committee for Air Pollution Research and Control. Production and hosting by Elsevier B.V. All rights reserved.

Keywords: Oxides of nitrogen Carbon monoxide Ozone Air quality monitoring stations Resultant wind vector

1. Introduction Clean air is a basic necessity for sound health and the well-being of humans, animals, and plants. Unfortunately, during the past few decades, the atmosphere has become progressively more polluted particularly in developing countries. Large increases in population density, industrial development, and vehicular traffic are causing worsening air pollution and pose serious environmental threats in many urban and surrounding areas. One of the challenging issues in

* Corresponding author. E-mail address: [email protected] (S. Tyagi). Peer review under responsibility of Turkish National Committee for Air Pollution Research and Control (TUNCAP).

the ever growing industrial and urban environments is atmospheric trace gases (Wang et al., 2012). The major gaseous air pollutants are oxides of carbon (COx), nitrogen (NOx) and sulfur (SOx) that are emitted by various sources including transportation, power generation, refuse incineration, industrial and domestic fuel combustion (Smith, 2004). Extensive use of fossil fuels in urban transportation and industry has led to significant increases in gaseous pollutant concentrations (Rai et al., 2011) mostly through combustion (Khare, 2012; Andreae and Merlet, 2001). One of the other major contributors to fine particles and gaseous pollutants over the northern India is agricultural residue burning following the harvest (Awasthi et al., 2011). The National Capital Territory (NCT) of Delhi with an area of 1483 km2 and a population density (11,320 per km2) (Delhi Statistical Hand Book, 2014) is a developing megacity with a very

http://dx.doi.org/10.1016/j.apr.2016.04.008 1309-1042/Copyright © 2016 Turkish National Committee for Air Pollution Research and Control. Production and hosting by Elsevier B.V. All rights reserved.

Please cite this article in press as: Tyagi, S., et al., Spatial variability of concentrations of gaseous pollutants across the National Capital Region of Delhi, India, Atmospheric Pollution Research (2016), http://dx.doi.org/10.1016/j.apr.2016.04.008

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fast growing economy. Registered motor vehicles in Delhi as on 31 March 2014 were 8,293,167 (Transport Department, Govt. of N.C.T. of Delhi, 2015) with an annual increase of around 7%. Delhi has a high density of goods trucks and lorries during the night from five national highways (NH), NH-1, NH-2, NH-8, NH-10 and NH-24, passing through its territory. An estimated 80,000 trucks enter Delhi every night between 2100 and 0600 h. These trucks contribute more than 60% of the pollutants emitted by diesel vehicles inside Delhi (Indian Express, 2015). Petrol and diesel vehicles emit a wide variety of pollutants, including carbon monoxide (CO), oxides of nitrogen (NOx), volatile organic compounds (VOCs) and particulate matter. Diesel emissions also have health and climate implications (Kim Oanh et al., 2010; Gupta and Kumar, 2006; Maricq, 2007; Shrivastava et al., 2013). Oxides of nitrogen (NOx ¼ NO þ NO2) play an important role in tropospheric ozone chemistry and secondary aerosol formation, etc. They are produced by both natural (mainly lightning and microbiological processes in soil) and anthropogenic sources (fossil fuel combustion and biomass burning). The major sources of anthropogenic NOx emissions are motor vehicles and power plants (Rai et al., 2011). The photolysis of NO2 leads to the formation of O3. The regional distribution of NOx concentrations is driven by the local emissions. However, in the free troposphere, NOx is strongly influenced by long-range transport (Kunhikrishnan et al., 2006). In the lower troposphere, the NOx sources are anthropogenic such as combustion of fossil fuels. However, microbial emissions from agricultural soils and biomass burning can be significant contributors in non-urban (rural) regions (Van der A et al., 2008). Carbon monoxide (CO) is a potential health threat. Its major anthropogenic sources are motor vehicles, industrial activities, heating and incinerators (Suess and Craxford, 1978). Total emission of CO indirectly contributes to global warming through the control of tropospheric ozone (Crutzen et al., 1999). The exposure to significant levels of CO reduces the blood's ability to carry oxygen to body organs thereby causing headaches and memory problems (Chelani, 2012). Facilities to measure NOx, CO, and O3 are very limited in India (Ghude et al., 2008; Badarinath et al., 2009; Sahu et al., 2009; Tiwari et al., 2009; Singla et al., 2011; Lal et al., 2012; CSE, 2012; Beig et al., 2013) thereby producing limited data from rural and suburban areas. Gurjar et al. (2004) presented a comprehensive emission inventory of air pollutants in Delhi for the period 1990e2000 and concluded that transport sector contributed >80% of NOx, CO, and VOCs (volatile organic compounds). Shrivastava et al. (2013) also reported that CO is the major pollutant coming from the transport sector, contributing 90% of total emissions. The Central Pollution Control Board (CPCB) has reported that vehicular contribution to the total urban air pollution in Delhi and Mumbai is about 76e90% for CO, 66e74% for NOx, 5e12% for SO2 and 3e12% for PM (Gulia et al., 2015). CO and NOx emissions from vehicular transport in Delhi were found to be 284 and 130 mg/km2, respectively (Ramachandra and Shwetmala, 2009). The present work offers a comprehensive statistical analysis of the seasonal and annual temporal variation in gaseous pollutant concentrations (NOx, CO, and O3) based on one year (2014) measurement campaign in NCR of Delhi. Measurements of the gaseous pollutants were made at seven different air quality monitoring stations (AMSs). The data were analyzed hourly, daily, monthly, and seasonally during the study period. The results were studied in view of the pollution concentrations, possible emission sources, and the meteorological conditions across the NCR of Delhi. The study contributes to a better understanding of the gaseous pollutant concentrations in the rapidly growing urban region.

2. Monitoring location, technique and meteorology conditions 2.1. Air quality monitoring stations (AMS) and meteorological observatories (MO) The NCR of Delhi covers an area of about 34,000 km2 in the territorial jurisdictions of four state governments, namely National Capital Territory (NCT) of Delhi, Haryana, Uttar Pradesh, and Rajasthan. The NCT of Delhi constitutes 1483 km2 in the area whereas Haryana, Uttar Pradesh and Rajasthan contribute 13,428, 10,853, and 8380 km2, respectively. NCR of Delhi is characterized by topographical areas like the extension of the Aravalli ridge, forests, the rivers Ganga, Yamuna, and Hindon, fertile cultivated land, and is a dynamic rural-urban region with a total population of approximately 46 million (Census of India, 2011). Seven AMSs including IGI (Indira Gandhi International) Airport, Palam (close to Haryana state border) and urban traffic industrial area of NOIDA (Uttar Pradesh) and three MOs were selected for monitoring and examining of gaseous pollutants and meteorological variables across NCR of Delhi (Fig. 1). A brief description of these AMSs and MOs is as follows: 1. CVR Dheerpur (28.72 N 77.20 E): It is located in the premises of Sir C.V. Raman Industrial Training Institute at Dheerpur. The institute is located on the outer ring road and lies in the northern parts of Delhi, surrounded by the different industrial areas Viz, Wazirpur, Narela, Bhawana, Naraina etc. This AMS is approximately 18 km WNW of Hindon MO in Ghaziabad and about 4 km north of Delhi University AMS. 2. Delhi University (DU) (28.68 N 77.20 E): It is located in Delhi University in north Delhi and is in a mostly residential area called Kamla Nagar. The Hindon MO is about 17 km ESE and the Safdarjung MO is approximately 14 km to the south. It is situated about 17 km NE of IGI airport Palam MO and 7 km NW of the Safdarjung MO. 3. IITM, Delhi (28.62 N 77.17 E): This AMS is located in the campus of Indian Institute of Tropical Meteorology (IITM), Rajender Nagar, New Delhi branch, lying in the central Delhi. The site is surrounded by forests and residential colony. 4. IMD, Lodhi road (28.58 N 77.22 E): It is located in the premises of India Meteorological Department (IMD) at Lodhi Road lying in central Delhi. The surrounding area is a residential and commercial with Lodhi Gardens spread over 90 acres in the close vicinity. It is situated just 2.5 km SSW of Safdarjung MO and 12 km west of IGI airport Palam MO. 5. IGI airport, Palam (28.55 N 77.09 E): This AMS is located at a distance of 30 km SW of Hindon MO and 17 km from Safdarjung MO which is spread over an area of 5106 acres (AAI, 2015) with national highway (NH-8) lying around 3 km in SE and Gurgaon rural in adjacent SW sector. 6. CRRI, Mathura road (28.55 N 77.27 E): It is an urban traffic AMS located on the campus of Central Road Research Institute (CRRI) in south Delhi. National highway (NH-2) passes from there. 7. NCMRWF, NOIDA (28.57 N 77.32 E.): This AMS is located in the campus of National Centre for Medium Range Weather Forecasting (NCMRWF), Sector 62, New Okhla Industrial Development Area (NOIDA), Gautam Budha Nagar in Uttar Pradesh State (NCMRWF, 2015). It's an industrial area with a very busy N-S oriented national highway (NH-24), connecting Delhi to the Uttar Pradesh state capital, Lucknow. Densely populated residential colonies are spread from West and NW in the close proximity of AMS. Two major industrial localities, Sahibabad industrial area and Bulandshahr industrial area, are NW and N of this AMS.

Please cite this article in press as: Tyagi, S., et al., Spatial variability of concentrations of gaseous pollutants across the National Capital Region of Delhi, India, Atmospheric Pollution Research (2016), http://dx.doi.org/10.1016/j.apr.2016.04.008

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Fig. 1. Map of NCR of Delhi depicting Air Quality Monitoring Stations (AMSs) & Meteorological Observatories (MOs).

Meteorological observatories (three) are located across NCR of Delhi at (i) Hindon Air Force base (VIDX) MO (28.43 N, 77.22 E; 214 m AMSL) located near Ghaziabad, Uttar Pradesh. It is covered with lush green forest. However, the area outside the perimeter is devoid of greenery, is dusty, and is surrounded by many brick kilns spreading from NW to SSW as well as the industrial areas of Ghaziabad to N and SE, (ii) Safdarjung Airport (VIDD) MO (28.35 N, 77.12 E; 215 m AMSL) is situated in central Delhi, and (iii) Indira Gandhi International Palam Airport (VIDP) MO (28.55 N, 77.09 E: 237 m AMSL) is located in the premises of the airport close to Haryana.

temperature (tempmin), daily rainfall (RF), relative humidity (RH), wind direction (WD) and wind speed (WS) at each MO. The average temperatures at VIDX, VIDD and VIDP were 24.03 ± 8.96, 24.94 ± 8.89 and 25.0 ± 9.51  C, respectively. The annual RF values were 435, 545, and 569 mm at VIDX, VIDD, and VIDP, respectively. Annual resultant wind vectors were northwesterly [338 (57%)] and westerly [288 (27%)] with average WS of 2.38 ± 1.7 and 2.51 ± 1.9 m/s at VIDX and VIDP, respectively. 3. Results and discussion 3.1. Oxides of nitrogen (NOx)

2.2. Measurement techniques and meteorological conditions Gaseous pollutants, oxides of nitrogen (NOx ¼ NO þ NO2), CO, and O3, were simultaneously and continuously measured from 01st January to 31st December 2014 at the seven AMSs using NOx (Thermo Electron model 42i), CO (Thermo Electron model 48i) and O3 (Thermo Electron: Model 49i) analyzers. All gaseous pollutants instruments were regularly calibrated using the prescribed calibration system as per the manufacture's manual and as discussed in Tiwari et al. (2015) and Kumar et al. (2015). Measurement errors should typically be of the order of 5%. The NCR of Delhi in the northern region of India is influenced by four major seasons; winter (JanuaryeFebruary), SW summer monsoon (JuneeSeptember.), pre-monsoon (MarcheMay) and post-monsoon (OctobereDecember) (IMD, 2015). The meteorological data for 2014 include dry bulb temperature (DB),minimum

Variations of day-to-day, running (20-day) and monthly mean (standard deviation) concentrations of NOx for all seven AMSs are shown in Fig. 2. However, station to station variations are also depicted (Fig. 3). The mean NOx value was 37.1 ± 11.6 ppb (NO: 18.3 and NO2: 18.8 ppb) and varied from 22.8 to 62.1 ppb across the NCR of Delhi. From January to March, the mean concentrations of NO2 were greater than the NO. However, from mid-July until September, NO was greater than NO2. During the remainder of the year, mean NO and NO2 concentrations are approximately equal. Mallik and Lal (2014) reported that if the NO2 concentrations were less than NO; there is lower photochemical oxidization in the environment. Highest concentrations (41.34 ± 13.8 ppb) of NOx were recorded at CRRI followed by DU (40.69 ± 12.6 ppb), NCMRWF (39.5 ± 16.2 ppb), CVR (36.2 ± 9.1 ppb), IITM (36.1 ± 10.9 ppb), IMD (34.04 ± 11.8 ppb) and IGI (32.26 ± 6.7 ppb). At CRRI, the

Please cite this article in press as: Tyagi, S., et al., Spatial variability of concentrations of gaseous pollutants across the National Capital Region of Delhi, India, Atmospheric Pollution Research (2016), http://dx.doi.org/10.1016/j.apr.2016.04.008

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Running mean

Concentrations

Daily mean

60 50 40 30 20

(A)

5 4 3 2 1

(B)

90 75 60 45 30 15

(C)

0

30

60

Monthly mean

monsoon season (1.05) and was lower in the pre-monsoon season (0.79). The daily mean concentrations of NO2 were lower than the Indian NAAQS (42.5 ppb) (CPCB, 2012) as well as the USEPA standard (53 ppb) (USEPA, 2015) by 56% and 64%, respectively. Ahammed et al. (2006) reported an annual average NOx mixing ratio of z3.9 ppb in Anantapur, a semi-arid site in India during 2001e2003. This value was quite low as compared to the NCR of Delhi concentrations of NOx. Concentrations of NOx (32e272 ppb) in Delhi during the winter months of 1993 (Singh et al., 1997) showed a wider variation compared to the present study. Tiwari et al. (2015) found that lower concentrations of NO (17.2 ppb), NO2 (12.5 ppb) and NOx (29.7 ppb) during the year 2010e12 in a single station monitoring as compared to NCR of Delhi values. Kumar et al. (2015) reported average values of NO (NO2) of 5.0 (11.3), 4.1 (8.6), and 4.0 (10.5) ppb for the winter, autumn and summer respectively over Delhi that values were much lower than the values observed in the present study.

90 120 150 180 210 240 270 300 330 360 3.2. Carbon monoxide (CO)

Day of year

Conc. in ppb

Conc. in ppm

Conc. in ppm

Fig. 2. Daily, running and monthly mean (standard deviation) concentrations in ppb, ppm and ppb of variation of NOx (A), CO (B) and O3 (C) respectively over NCR of Delhi during the study period.

NO

42 35 28 21 14 7 0 4 3 2 1 0

NO2

CO

O3

60 40 20

As, NOx, the daily variability of CO along with its 20 days running mean values at all seven AMSs are plotted (Fig. 2) and the daily mean CO concentration across NCR of Delhi was 2.3 ± 0.6 ppm and varied from 1.3 to 5.1 ppm. The mean 1-hr concentration of CO is much lower than NAAQS (z4 ppm) and USEPA standard (35 ppm) (CPCB, 2012; USEPA, 2015). Goyal et al. (2013) reported vehicle emissions of CO, approximately 509 tons per day in Delhi for the year 2008e2009. It was found that hourly average CO values varied from 0.09 to 19.57 ppm across the AMSs. The annual mean NCMRWF concentration (2.7 ± 0.9 ppm) was 19% higher than the mean concentrations of NCR of Delhi followed by IMD (2.5 ± 0.9 ppm), IGI (2.4 ± 0.9 ppm), DU (2.3 ± 0.9 ppm), IITM (2.1 ± 1.0 ppm), CRRI (2 ± 0.9 ppm) and CVR (1.8 ± 0.8 ppm) (Fig. 3). Seasonally, the post-monsoon (2.5 ± 0.4 ppm) and winter (2.5 ± 0.3 ppm) mean concentrations of CO were the highest followed by the pre-monsoon (2.4 ± 0.8 ppm) season. However, approximately 17% lower (than the annual mean value) concentrations were observed during the south-west (SW) monsoon (1.9 ± 0.3 ppm) season. Fig. 4 shows the average diurnal pattern of CO concentrations over NCR of Delhi. Overall, the lowest area average diurnal

0

CVR

CRRI

DU

IITM

IMD NCMRWF

IGI CRRI DU IITM IMD NCMRWF IGI Mean

Monitoring sites 3.2 Fig. 3. Annual mean mass concentrations and their standard deviation of NO, NO2, CO and O3 over NCR of Delhi during the study period.

Concentrations in ppm

concentrations of NOx were z11% higher than the mean concentration across the region. This higher value is the result of higher diesel vehicular traffic on the NH-2 in the close proximity of CRRI AMS. The air quality over the residential and industrial locations across the Indian cities has indicated rapid increases in NOx concentrations with some locations showing values as high as 100e240 mg/m3; exceeding the permissible limits. These concentrations are likely to increase further in coming years (Kunhikrishnan et al., 2006). Seasonally, the variation of the concentrations of NOx was highest in the post-monsoon (40.8 ± 4.5 ppb) and monsoon (40.8 ± 4.5 ppb) seasons decreasing in the pre-monsoon (36.9 ± 4.5 ppb) and winter (36.5 ± 6.5 ppb). The NO/NO2 ratio was higher during the post-

3.0 2.8 2.6 2.4 2.2 2.0 1.8 1.6 0

2

4

6

8

10 12 14 16 18 20 22 24 Hour of the day

Fig. 4. Diurnal variation of CO over NCR of Delhi of AMSs during the study period.

Please cite this article in press as: Tyagi, S., et al., Spatial variability of concentrations of gaseous pollutants across the National Capital Region of Delhi, India, Atmospheric Pollution Research (2016), http://dx.doi.org/10.1016/j.apr.2016.04.008

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70

CVR DU IMD IGI

65 60 Concentrations in ppb

concentrations (2.05e2.07 ppm) were observed during daytime, between 14:00 to 16:00 h local time (LT) and highest (2.39e2.41 ppm) during midnight, between 21:00 to 01:00 h local time (LT), The highest concentrations of CO during the midnight may be attributed to the nocturnal boundary conditions (Plocoste et al., 2015). Few locations observed higher concentrations during morning and evening, which are due to the impact of vehicular emissions. Additionally, during the evening, the higher concentrations of CO may also be due to combustion of bio-fuels over the study region (Turnbull et al., 2014). The maximum concentration of CO in Anantapur, India during 2001e2003 was observed during the morning (06:00e07:00 h LT) and late evening hours (20:00e21:00 h LT) due to vehicular traffic (Ahammed et al., 2006). Narain and Krupnick (2007) estimated the impact of CNG Program on Delhi's air quality using monthly time-series data from 1990 to 2005 and the results suggested that the conversion of buses from diesel to CNG has helped to reduce PM10, CO, and SO2 concentrations in the city. Sindhwani and Goyal (2014) reported the emissions of CO and NOx have increased nearly 77% and 29%, respectively, from 2000 to 2010 in Delhi due to phasing out of diesel-driven buses and implementation of Bharat StageeIII norms for commercial vehicles.

5

CRRI IITM NCMRWF Mean

55 50 45 40 35 30 25 20 15

0

2

4

6

8

10 12 14 16 18 20 22 24 Hour of Day

Fig. 5. Diurnal variation of O3 over different locations over NCR of Delhi during 2014.

3.3. Ozone The daily O3 variability at all the seven AMSs during the study period is depicted in Fig. 2 and the mean concentration across NCR of Delhi were 37.5 ± 11 ppb varying from 13.9 to 86.0 ppb which is much lower than the national standards (CPCB, 2012). A significant variability in the annual mean concentrations of O3 were observed among the monitoring locations with highest (43.3 ± 10.9 ppb) at CRRI Mathura Road AMS followed by CVR (42.4 ± 23.7 ppb), DU (37.3 ± 15.8 ppb), IITM (36.5 ± 16.4 ppb), IGI (34.5 ± 14.6 ppb), NCMRWF (33.2 ± 19.5 ppb), and IMD (32.9 ± 12.9 ppb) (Fig. 3). Seasonally, during the post monsoon, O3 concentrations were highest (mean ¼ 45.3 ± 9.5 ppb) followed by the SW monsoon (mean ¼ 39.8 ± 8.0 ppb), pre-monsoon (mean ¼ 36.0 ± 9.1 ppb) and winter (mean ¼ 23.0 ± 5.4 ppb). The concentrations were lowest in the winter months and started increasing subsequently till the post monsoon season. This large seasonal variability in the concentrations of O3 and its precursors is due to the impact of variability in meteorological conditions as well as different emission sources. The lower concentrations in winter months may be attributed to the shorter daylight period, the lower solar radiation (Wang and Hao, 2012) as well as rainfall (~total rainfall in winter: 45.7 mm). The highest concentrations of O3 in post monsoon were due to the excessive biomass burning over northwest parts (Punjab & Haryana states) of the study region (Kaskaoutis et al., 2013; Chatfield and Delany, 1990). Kumar et al. (2015) reported highest/lowest concentrations (in ppb) of O3 at three different locations in Delhi (49.3/ 30.7 (Dariyapur village: rural area), 38.8/23.9 (Jawaharlal Nehru University: urban/rural mixed area), and 35.1/21.5 (Connaught Place: high traffic area) during the pre-monsoon season and suggested that it is due to photochemical oxidation by higher solar radiation and temperature. Our study is in agreement with Khoder (2009) in Egypt, Kourtidis et al. (2002) in Greece and Wang and Hao (2012) in Beijing. Fig. 5 shows the diurnal pattern of concentrations of O3 at different monitoring locations over NCR of Delhi. The diurnal variations of O3 concentrations these AMSs were characterized by the high concentrations during the daytime (07:00 to 17:00 h LT: 43.6 ppb) and low concentration (31.1 ppb) during the late evening and early morning hours (18:00 to 06:00 h LT) which is approximately 40% higher. From 07:00 onwards, the O3 concentrations start increasing gradually just after sunrise coinciding with the

increasing solar radiation. It was observed that highest concentrations (51.7 ppb) were around 15:00 h LT thereafter it is started decreasing and maintained lower values during the entire night due to lack of sunlight. In addition to solar flux variations, emissions from anthropogenic activity, planetary boundary layer forces, mixing processes of both horizontal and vertical convection and meteorological element also dominate in the variations in O3 concentrations (Nishanth et al., 2014; references therein). Tiwari et al. (2015) reported ozone concentrations start increasing during the morning (after 07:00 h LT), following sunrise and reach maximum around 15:00 h LT. Subsequently, it starts declining. NO2 decreases as O3 increases because it is a precursor for the formation of ozone and is also converted to NOx. O3 is a secondary pollutant formed through a series of photochemical reactions between oxides of nitrogen (NOx ¼ NO and NO2), carbon monoxide (CO), and volatile organic compounds (VOCs) under intense solar radiation. A comparison of Figs. 4 and 5 reveal reverse diurnal pattern with lowest concentrations of CO being observed during the afternoon hours when O3 showed a peak. The daytime O3 concentration buildup is a pronounced feature of urban polluted sites (Lal et al., 2000). The mean concentration value of O3 (13.9e86.0 ppb) across NCR of Delhi in present study was found to be less than the values of O3 (34e126 ppb) in Delhi during the winter months of 1993 (Singh et al., 1997) and at Ahmedabad (12e33 ppb) from 1991 to 95 (Lal et al., 2000). Kumar et al. (2015) also reported large variability in the diurnal analysis of O3 characterized by daytime maxima/(night-time minima) having concentrations 50.2/(17.2), 46.1/(15.7), and 56.7/(23.6) ppb at three different sites in Delhi during 2013e14.

3.4. Possible sources of gaseous pollutants Possible local sources of gaseous pollutants were identified by analyzing the surface wind regime over NCR of Delhi. Fig. 6 shows the annual wind patterns at the Hindon and Palam MOs. The resultant annual wind vector is northwesterly [338 (57%)] at Hindon with normal wind speeds varying from 2.1 to 5.7 m/s. This wind regime is relevant for the NCMRWF, NOIDA AMS since Hindon MO is located 11 km from the MO. The gaseous pollutants were transported to the NCMRWF, NOIDA

Please cite this article in press as: Tyagi, S., et al., Spatial variability of concentrations of gaseous pollutants across the National Capital Region of Delhi, India, Atmospheric Pollution Research (2016), http://dx.doi.org/10.1016/j.apr.2016.04.008

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Fig. 6. Annual distribution of wind speed (m/s) with wind direction at (A) Hindon MO & (B) IGI airport Palam MO during 2014.

AMS from the Sahibabad industrial area (located NW-7 km). The N-S oriented national highway (NH-24) lies just 500 m NW with constant heavy traffic. There are densely populated areas, Makanpur Colony, Rajeev Nagar, Sagam Park, Partap Vihar etc.,

lying to the west and northwest (Fig. 7). Fig. 6B shows that the annual resultant wind vector for the Palam MO was WNW [288 (27%)] with wind speed varying from 2.1 to 5.7 m/s. The IGI airport Palam is spread over an area of 5106 acres (AAI, 2015)

Fig. 7. Wind rose of Hindon MO, superimposed on NCMRWF, Noida AMS using Google earth map.

Please cite this article in press as: Tyagi, S., et al., Spatial variability of concentrations of gaseous pollutants across the National Capital Region of Delhi, India, Atmospheric Pollution Research (2016), http://dx.doi.org/10.1016/j.apr.2016.04.008

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with national highway (NH-8) lying around 3 km in SE; Gurgaon rural in adjacent SW sector; residential area like Janakpuri, Nevada, Bindapur etc in NW (10e15 km), Delhi cantonment in N (10 km); forest area in NE (5 km) and SE (10 km) and Dwarka residential area, Jhajjar, Khakhari Nahar semi-urban/rural areas lying to the W. The resultant wind vector from the west indicates that gaseous pollutants were transported from agricultural and rural area. Seasonally, resultant wind vector over Hindon MO were in order of the post-monsoon [338 (57%) ], pre-monsoon [300 (42%) ], winter [308 (41%)] and SW monsoon [333 (18%) ] indicating transport of gaseous pollutants across NCMRWF, NOIDA AMS from industrial areas, national highway (NH-24), and the densely populated area located to the northwest of the AMS (Fig. 7). Similarly, the seasonal resultant wind vector over IGI airport, Palam MO was in order of the postmonsoon [289 (36%)], pre-monsoon [305 (33%)], winter [269 (26%)], and SW monsoon [277 (21%)] indicating advection of gaseous pollutant to the IGI airport, Palam MO from residential areas to the northwest and semi-urban and agricultural areas to the west. Lal et al. (2000) analyzed surface ozone and its precursor's gas data for 1991e96 in Ahmedabad, India and found that the seasonal variations in CO and NOx were dominated by regional meteorology that changed the wind patterns and transports polluted air during the northeast winds and cleaner air during southwest winds.

3.5. Comparison of NCR of Delhi with other cities of India Table 1 shows a comparison of the gaseous pollutant concentrations in the NCR of Delhi (average concentrations of seven AMSs) with various cities of India. During the present study, the concentrations of NO and NO2 have increased by 6.2% and 41.8%, respectively in comparison to the study conducted during Sep. 2010 to Aug. 2012 (Tiwari et al., 2015) at the IITM, Rajender Nagar monitoring station. The concentration of NOx was higher by z5.6, 2.9 and 2.9 times compared to previously measured values in Kanpur

7

(Gaur et al., 2014), Pune (Beig et al., 2007), and Ahmadabad (Beig et al., 2007), respectively. For CO, the concentrations were found to be higher by z2, 4 and 7 times in comparison to Kanpur (Gaur et al., 2014), Anantpur (Ahammed et al., 2006) and Nainital (Kumar et al., 2010). The O3 concentrations were found to z6%, 2% and 8% higher than Delhi (Tiwari et al., 2015), Pune (Beig et al., 2007) and Ahmedabad (Beig et al., 2007) respectively, and lower by z1% compared to values measured in Nainital (Kumar et al., 2010).

4. Conclusions Measurement of NOx (NO þ NO2), CO, and O3 at seven different AMSs across the NCR of Delhi were made during 2014. Daily mean concentrations of NOx, CO, and O3 over NCR of Delhi were 37.1 ± 11.6 ppb (NO: 18.3 and NO2: 18.8 ppb), 2.3 ± 0.6 ppm, and 37.5 ± 11 ppb, respectively. Daily concentrations of CO at NCMRWF, NOIDA AMS were higher than mean values across NCR of Delhi. CO and O3 show reverse diurnal patterns with lowest CO concentrations and highest O3 concentration during the afternoon hours. The highest diurnal CO concentrations were observed during midnight due to nocturnal boundary conditions whereas high diurnal O3 concentrations were observed during day time after sunrise, coinciding with the increasing solar radiation. Possible local sources of gaseous pollutants were identified by analyzing the surface wind direction at the Hindon and Palam MOs where the annual resultant wind vectors were northwesterly 338 (57%) and westerly 228 (27%), respectively. Local NO emissions substantially reduce the urban ozone concentrations as can be seen by the concentrations of untitrated NO. Such high NO emissions can be expected to result in high ozone concentrations in downwind areas. The high NO emissions are likely the result of the switch of a significant portion of the vehicular fleet to CNG. Although such changes result in the lower particulate matter and CO emissions, they result in higher NO concentrations. This conclusion is supported by the relatively low CO and high NO concentrations observed across the study area.

Table 1 Comparative results of gaseous pollutants concentration in cities of India. City

Study period

NO (ppb)

NO2 (ppb)

NOx (ppb)

CO (ppm)

O3 (ppb)

Present study Delhia Delhib New Delhic Agrad Kanpure Punef Ahmedabadg Anantapurh Anantapuri Kannurj Nainitalk Mt. Abul

Jan.eDec. 2014 Jan. 2013eDec.2014 Sep. 2010eAug. 2012 Jan. 2000eDec. 2009 Nov.eFeb. 2003e05 Jun. 2009eMay 2013 Jun. 2003eMay 2004 Jun. 2003eMay 2004 Jan.2001eDec. 2003 Jan.eDec. 2010 Nov. 2009eOct. 2010 Oct. 2006eDec. 2008 Jan. 1993eDec. 2000

18.8

19.0

2.3

17.2

12.5 26.1

37.8 16.6 29.3

37.5 29.1 23.6 15.8 26.1 27.9 30.9 20.7 35.9 40.7 18.4 43.9 39.9

a b c d e f g h i j k l

5.7 9.6 9.5 3.9 5.1 2.5

± ± ± ± ±

4.5 5.9 2.7 0.6 0.7

1.5 ± 1.4

2.0 22.5 0.71 ± 0.2 0.72 ± 0.4

0.44 ± 0.1

0.28 ± 0.2 0.13 ± 0.1

± ± ± ±

5.7 17.8 14 5.5

± ± ± ±

3.7 4.4 11.5 10.8

Kumar et al., 2015. Tiwari et al., 2015. Chelani, 2012. Saini et al., 2008. Gaur et al., 2014. Beig et al., 2007. Beig et al., 2007. Ahammed et al., 2006. Reddy et al., 2013. Nishanth et al., 2012. Kumar et al., 2010. Naja et al., 2003.

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S. Tyagi et al. / Atmospheric Pollution Research xxx (2016) 1e9

Acknowledgements Authors thank the Vice Chancellor, Gautam Buddha University for the encouragement and support during the study period. Authors are also thankful to Director General, Indian Meteorological Department (IMD); Assistant Chief of Air Staff (Meteorology), Indian Air Force and Director, Indian Institute of Tropical Meteorology (IITM) for providing requisite data and guidance.

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