hazardous pollutants in power station emissions ...

COOPERATIVE RESEARCH CENTRE FOR COAL IN SUSTAINABLE DEVELOPMENT Established and supported under the Australian Government’s Cooperative Research Centres Program

HAZARDOUS POLLUTANTS IN POWER STATION EMISSIONS

RESEARCH REPORT 51

Authors:

M I Attalla * H R Malfroy * S Morgan * K R Riley * P F Nelson #

* CSIRO Energy Technology # Graduate School of the Environment, Macquarie University

November 2004

QCAT Technology Transfer Centre, Technology Court Pullenvale Qld 4069 AUSTRALIA Telephone (07) 3871 4400 Facsimile (07) 3871 4444 Email: [email protected]

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DISTRIBUTION LIST CCSD Chairman; Chief Executive Officer; Research Manager, Manager Technology; Files Industry Participants Australian Coal Research Limited ............................................................. Mr Ross McKinnon BHP Billiton Minerals - Coal .................................................................... Mr Ross Willims ................................................................................................................ Mr Alan Davies CNA Resources.......................................................................................... Mr Ashley Conroy CS Energy .................................................................................................. Dr Chris Spero Delta Electricity ......................................................................................... Mr Steve Saladine Queensland Natural Resources, Mines and Energy................................... Mr Bob Potter Rio Tinto (TRPL)....................................................................................... Mr David Cain .................................................................................................................... Dr Jon Davis Stanwell Corporation ................................................................................. Dr Paul Simshauser Tarong Energy ........................................................................................... Mr Burt Beasley The Griffin Coal Mining Co Pty Ltd ......................................................... Mr Jim Coleman Wesfarmers Premier Coal Ltd ................................................................... Mr Peter Ashton Western Power ........................................................................................... Mr Keith Kirby Xstrata Coal Pty Ltd................................................................................... Mr Barry Isherwood Research Participants CSIRO ……............................................................................................... Dr David Brockway Curtin University of Technology ............................................................... Dr Barney Glover Macquarie University ................................................................................ Prof Jim Piper The University of Newcastle ..................................................................... Prof Adrian Page The University of New South Wales ......................................................... Prof David Young The University of Queensland ................................................................... Prof Don McKee


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TABLE OF CONTENTS LIST OF TABLES.............................................................................. II LIST OF FIGURES ........................................................................... III 1

INTRODUCTION .........................................................................5

2

NATIONAL POLLUTANT INVENTORY – COAL FIRED ELECTRICITY GENERATION ....................................................8

3

MODELLING TRACE ELEMENT EMISSIONS .........................12

4

SAMPLING AND ANALYSIS OF NPI LISTED TRACE ELEMENTS IN POWER STATION FLUE GAS ........................15

5

RESULTS ..................................................................................19

5.1

6

ESTIMATING TRACE METAL EMISSIONS USING THE NPI WORKBOOK....................................................................................................... 19

OUTSTANDING HAPS..............................................................31

6.1

HEXAVALENT CHROMIUM........................................................................... 31

6.2

HYDROGEN CHLORIDE.................................................................................. 35

6.3

MAGNESIUM OXIDE FUME ........................................................................... 36

6.4

NICKEL CARBONYL ........................................................................................ 37

6.5

NICKEL SUBSULPHIDE................................................................................... 39

6.6

SUMMARY .......................................................................................................... 40

7

CONCLUSIONS ........................................................................41

8

RECOMMENDATIONS .............................................................43

9

REFERENCES ..........................................................................44

i

LIST OF TABLES Table 2-1 Substance Categories and Reporting Thresholds ............................. Table 2-2 NPI Substances of Potential Relevance to Fossil Fuel Electric Power Generation ............................................................................. Table 4-1 Stack sampling undertaken in NSW in 1999.................................... Table 4-2 Stack sampling undertaken in Queensland in 1999.......................... Table 5-1 Emission Factors for Black Coal Combustion (Trace Elements) from Table 7 of the NPI Manual ...................................................... Table 5-2 Trace metal content of feed coal ...................................................... Table 6-1: Details of Cr (VI) measurements by XANES .................................

ii

8 9 16 17 20 21 34

LIST OF FIGURES Figure 5-1 Antimony – Comparison between emission estimates based on stack measurements and NPI EETs................................................ Figure 5-2 Arsenic – Comparison between emission estimates based on stack measurements and NPI EETs. Note log scale on y-axis. ............... Figure 5-3 Beryllium – Comparison between emission estimates based on stack measurements and NPI EETs................................................ Figure 5-4 Cadmium – Comparison between emission estimates based on stack measurements and NPI EETs................................................ Figure 5-5 Cobalt – Comparison between emission estimates based on stack measurements and NPI EETs ......................................................... Figure 5-6 Chromium – Comparison between emission estimates based on stack measurements and NPI EETs................................................ Figure 5-7 Lead – Comparison between emission estimates based on stack measurements and NPI EETs ......................................................... Figure 5-8 Manganese – Comparison between emission estimates based on stack measurements and NPI EETs................................................ Figure 5-9 Mercury – Comparison between emission estimates based on stack measurements and NPI EETs................................................ Figure 5-10 Nickel – Comparison between emission estimates based on stack measurements and NPI EETs................................................ Figure 5-11 Selenium – Comparison between emission estimates based on stack measurements and NPI EETs. Note log scale on y axis. ...... Figure 5-12 Composite figure containing all data presented in figures 5.1 to 5.11. ................................................................................................ Figure 6-1: Detail of least-squares fitting of chromium XANES spectra for samples A and C. Upper spectrum contains significant Cr(VI), whereas the lower spectrum contains very little, if any, Cr(VI). Note the difference in vertical scales. ............................................

iii

24 24 25 25 26 26 27 27 28 28 29 29

34

EXECUTIVE SUMMARY The emission of hazardous air pollutants (HAPS) has received increasing regulatory attention in recent years. A number of countries now have pollutant emission inventories, which include both the “criteria” pollutants (sulphur dioxide, oxides of nitrogen, particulate matter and lead, for example) and potentially hazardous pollutants, including compounds containing elements such as arsenic and mercury and organic compounds such as benzene, dioxins and furans. HAPs are generally only emitted in trace amounts, but are included in the pollutant inventories due to their toxicity and potential health impacts. In 1998, the National Pollutant Inventory (NPI) commenced in Australia. The NPI is Australia's national public database of pollutant emissions, containing information on the emission of 90 substances to air, water and land from industrial and nonindustrial sources. In order to assist NPI reporting, Environment Australia released a number of industry handbooks, which contain emission estimation techniques (EETs) for the reportable substances. Initial use of the Emission Estimation Technique Manual for Fossil Fuel Electric Power Generation raised a number of issues and concerns, which detracted from the “user friendliness” of the document but more importantly impacted on the quality of data reported. In response to these identified shortcomings in the NPI reporting manual for the black coal electricity generators, the Co-operative Research Centre for Black Coal Utilisation (now the CRC for Coal in Sustainable Development) initiated this project to be undertaken by CSIRO Energy Technology. The principal aims of the project were identified as being to: •

assess existing measurements and reporting procedures for substances listed in the NPI of relevance to coal fired electricity generation;

•

attempt to correlate emissions with coal properties and furnace design and operating conditions;

•

examine the scientific literature for tools and analytical techniques available to the coal fired power generation industry for the assessment and accurate measurement of the following five NPI substances for which there is currently no information on analytical techniques or emissions factors available: chromium(VI), hydrogen chloride, magnesium oxide fume, nickel carbonyl and nickel subsulphide.

This report provides a critical assessment of the NPI workbook and where applicable, advice on new emission factors and analytical techniques for selected reportable substances in the NPI. At the facility level, this will enable individual facilities to improve the quality of the data reported to the NPI. At the industry level the project will contribute to improving the quality and consistency of reporting to the NPI. 1

During the course of the current project, the Electricity Supply Association of Australia (ESAA) commissioned a review and revision of the NPI Estimation Technique Manual for Fossil Fuel Electric Power Generation by Pacific Power International (PPI). The CRC for Coal in Sustainable Development (CCSD) researchers collaborated closely with ESAA and PPI, providing them with the results of relevant research as it became available. It is understood that these data contributed to a revised workbook, which, although not yet officially released by Environment Australia, was endorsed by Environment Australia and state jurisdictions for use in 2002. The conclusions arising from the current project are: 1. Of the 90 substances included on the NPI reporting list, 43 are potentially relevant to coal fired electricity generators. This project’s focus was on point source emissions of substances, which are products of combustion. Fugitive, including evaporative emissions were not addressed. 2. Simple emission factors, based solely on energy or material inputs, were found to consistently, significantly over estimate emissions from power stations in NSW and Queensland and are considered unsuitable for use in Australia. 3. NPI emission equations which require site specific information were found to be generally reasonable in predicting emissions from NSW and Queensland power stations and considered suitable for NPI reporting purposes. 4. Further work on emissions under Australian operating conditions would be required to improve the accuracy of the emission equations. It is expected that the current CCSD Project 2.1.5 (Fine Particle Emissions from Power Stations) will contribute valuable information in this regard. 5. The performance of the emission equations, to a significant extent, depends on the quality of input data – coal concentrations, ash content and gross particle collection efficiency. 6. Modelling of emissions based on coal properties and composition, high temperature chemistry and the performance of air pollution control devices is an attractive option for reporting in the long term. However the ability to undertake this modelling has not yet advanced to a stage where it can be used with confidence to report emissions. 7. In making emissions measurements, the two major sources of variability are the sampling methodology and the analytical procedure. The sampling protocol must allow for coal characteristics, power station load, inertial effects in ducts, operating condition of the particle collection devices including poor performance (eg torn bags in a fabric filter station) and cleaning routines (eg rapping of ESP plates). It is not always possible to achieve these requirements. 8. The industry’s NPI Manual is deficient in its treatment of a number of substances. A detailed review of a number of these substances resulted in 2

suggested improvements in the emissions estimation techniques (EETs) for hexavalent chromium, hydrogen chloride, magnesium oxide fume, nickel carbonyl and nickel subsulphide. 9. The detailed review found that: •

hexavalent chromium was, at most, likely to contribute 5% to total chromium emissions

•

the use of representative coal chlorine data provides a conservative, reliable method of estimating hydrogen chloride emissions

•

magnesium oxide fume may be present in the exhaust gases of power stations, albeit at very low levels, but at this stage it is not feasible for these emissions to be quantified

•

nickel carbonyl and nickel subsulphide were unlikely to be present in measurable quantities in the exhaust gases of efficient coal fired power stations and that therefore it was reasonable for emissions of these substances to be reported as “zero” to the NPI

10. Estimation techniques for a number of other substances considered in this project, including mercury, selenium, PM10 and PAHs require further development for NPI reporting purposes. 11. A number of reportable substances that were not addressed in this project require consideration for NPI reporting purposes, for example copper, zinc, sulphuric acid. The recommendations arising from the project are: 1. Continue to review and assess theoretical and modelling approaches to emission estimation. 2. Consider the use of results from current CCSD Project 2.1.5 (Fine Particle Emissions from Power Stations) in improving existing emission estimation techniques. 3. Consider the merits of undertaking a further project to: •

Improve the EETs for a number of NPI substances such as mercury, selenium, PM10 and PAH.

•

Develop and/or improve the EETs for a number of NPI substances, which were beyond the scope of this project, for example, copper, zinc and sulphuric acid.

4. Continue to monitor developments in the sampling and analysis of emissions from coal-fired combustion. 3

5. Consider preparing a sampling and analytical protocol to be followed in any future emission measurement program undertaken for NPI reporting purposes.

4

1 INTRODUCTION Coal is the most abundant organic-rich sedimentary rock in the earth’s crust and in 2000 was estimated to provide 23.5% of the world’s primary energy (Key World Energy Statistics from the IEA) http://www.iea.org/statist/keyworld2002/keyworld2002.pdf). The use of coal has been associated with a number of potential environmental and health concerns including: • Carbon dioxide emissions contributing to the enhanced greenhouse effect • Emissions of oxides of sulphur and nitrogen contributing to acid deposition and secondary aerosol production • Particulate emissions contributing to fine particle levels as well as the degradation of amenity. The above impacts have been well studied and are generally related to the emission of the better known, and more regulated pollutants, often referred to as the criteria pollutants. Some constituents of coal and by-products of coal combustion are also potentially toxic to humans and/or ecosystem components. The potential toxic emissions arise either from the release of trace metals/compounds bound with the coal’s mineral and organic components or from the production of organic compounds, due to combustion and post combustion conditions. These potentially toxic or hazardous air pollutants (HAPs) may be released to the atmosphere or aquatic environment during power generation processes and may pose environmental and/or human health risks, depending on their concentration, physical and chemical forms and toxicity and the characteristics of the receiving environments. Other factors that govern the release of these toxic species to the environment are the partitioning behaviour of trace elements during combustion and emission control systems. The emission of HAPs has received increasing regulatory attention in recent years. A number of countries now have pollutant emission inventories which include both the criteria pollutants (sulphur dioxide, oxides of nitrogen, particulate matter etc.) and also potentially hazardous pollutants, which may only be emitted in trace amounts. Some of the better-known pollutant inventories are: • • • •

National Pollutant Release Inventory (Environment Canada) Scottish Pollution Inventory Toxic Release Inventory (USEPA) UK Pollution Inventory

In 1998 the National Pollutant Inventory (NPI) commenced in Australia. The NPI is Australia's national public database of pollutant emissions, containing information on the emission of 90 substances to air, water and land from industrial and nonindustrial sources.

5

While emissions of the criteria pollutants are generally reasonably well characterised for larger industrial facilities, data on the emission of HAPs is sparse and often either unreliable or specific to a particular facility. In order to assist NPI reporting, Environment Australia has released a number of industry handbooks which contain emission estimation techniques (EETs) for the reportable substances. Initial use of the Emission Estimation Technique Manual for Fossil Fuel Electric Power Generation raised a number of issues and concerns including: • • • • • •

inconsistency in application of NPI reporting requirements; layout of the NPI Manual and user friendliness; the relevance of some substances to the electricity industry; the absence of emission factors for some substances; inclusion of substances for which no emission estimation techniques are available; and inclusion of inappropriate emission factors for some substances.

The objectives of the current project are to: 1. Assess existing measurements and reporting procedures for substances listed in the NPI of relevance to coal fired electricity generation. 2. Examine correlations between emissions and coal properties, furnace design and operating conditions. 3. Examine the scientific literature for tools and analytical techniques available to the coal fired power generation industry for the assessment and accurate measurement of the following five NPI substances for which there is currently no information on analytical techniques or emissions factors available: chromium(VI), hydrogen chloride, magnesium oxide fume, nickel carbonyl and nickel sub sulphide. The output from the project is a final report, which provides a critical assessment of the NPI workbook, and where applicable, advice on new emission factors and analytical techniques for selected reportable substances in the NPI. At the facility level this will enable individual facilities to improve the quality of the data reported to the NPI. At the industry level the project will contribute to improving the quality and consistency of reporting to the NPI. During the course of the current project, the Electricity Supply Association of Australia (ESAA) commissioned a review and revision of the NPI Estimation Technique Manual for Fossil Fuel Electric Power Generation by Pacific Power International (PPI). The CRC for Coal in Sustainable Development (CCSD) researchers collaborated closely with ESAA and PPI, providing them with the results of relevant research as it became available. It is understood that these data contributed to a revised workbook, which, although not yet officially released by Environment Australia, was endorsed by them and state jurisdictions for use in 2002. Section 2 of this report provides an overview of the NPI, paying particular attention to issues of relevance to the coal fired electricity generating industry. 6

Section 3 examines the tools available for modelling and predicting trace element emissions from coal combustion. Section 4 reviews sampling and analytical work undertaken in NSW and Queensland as part of the industry’s program to address its NPI reporting responsibilities. In Section 5 a comparison is made between data collected at the power stations, as described in Section 4, and the EETs in the industry NPI workbook. In Section 6 detailed consideration is given to the five “outstanding” HAPs chromium(VI), hydrogen chloride, magnesium oxide fume, nickel carbonyl and nickel sub sulphide, and presents a recommended NPI reporting method for each substance. Conclusions and recommendations arising from the project are presented in Sections 7 and 8 respectively.

7

2 NATIONAL POLLUTANT INVENTORY – COAL FIRED ELECTRICITY GENERATION To facilitate reporting under the National Pollutant Inventory (NPI) the NPI Workbook for the Electricity Industry was developed in 1998/99 by a consultant working for the Electricity Supply Association of Australia (ESAA). The material was subsequently published by Environment Australia as the “Emission Estimation Technique Manual for Fossil Fuel Electric Power Generation” in March 1999. NPI reporting by electricity generating businesses progressed using this manual1. The Manual provides guidance and estimation techniques for substances which need to be considered by electricity businesses in meeting their NPI reporting requirements. The NPI full reporting list includes 90 substances2. Each substance is included in one or two of five categories, and each category has a corresponding reporting threshold. If a facility’s emission or use of a substance exceeds the relevant threshold it is required to report on its emission of that substance to air, water and land. Of the five categories, two category thresholds relate to the use of substances, one to nutrient emissions to water, and two to fuel combustion or energy use. The NPI substance categories and associated reporting thresholds are shown in Table 2-1 Table 2-1 Substance Categories and Reporting Thresholds Category 1 Use

Reporting Threshold A facility usesa 10 tonnes or more of the substance per year.

1a Use of VOCs

A facility uses 25 tonnes or more of Volatile Organic Compounds (VOCs). For a bulk storage facility, uses 25 tonnes or more of VOCs and has a 25 kilo tonne or greater design storage capacity for material containing VOCs

2a Fuel combustion /energy use 2b Fuel combustion /energy use 3 Water

400 tonnes per year or 1 tonne per hour

a.

2,000 tonnes per year or 60,000 MWhs or rated at 20 MW 15 tonnes nitrogen, 3 tonnes phosphorous

The NEPM defines use as meaning the handling, import, processing, co-incidental production or other use of the substance.

Large coal fired electricity generating facilities are required to report on all Category 2a and 2b substances by virtue of their fuel use. Whether reporting emissions of substances in Categories 1, 1a and 3 is required is site specific, depending on fuel characteristics as well as quantity of fuel used (Categories 1 and 1a) and emissions to water (Category 3). 1

A revised manual was available to electricity generating facilities in 2002. The full reporting list plus other information relevant to the NPI can be viewed at the following URL: http://www.npi.ea.gov.au/about/index.html (2000) 2

8

A screening assessment by Pacific Power International (2002) identified 43 of the 90 NPI substances as being of possible relevance to fossil fuel electricity generators. These substances, along with comments regarding the thresholds are shown in Table 2-2 Table 2-2 NPI Substances of Potential Relevance to Fossil Fuel Electric Power Generation Substance Ammonia (total)

Threshold 1

Relevance Possible

Antimony & compounds Arsenic &compounds Benzene

1

Beryllium & compounds Boron & compounds Cadmium & compounds Carbon monoxide Chlorine Chromium (III) compounds Chromium (VI) compounds Cobalt & compounds Copper & compounds Cumene (1methylethylbenzene) Cyanide (inorganic) compounds Cyclohexane

1/2b

1/2b 1

1 1/2b

Possible Yes Possible

Comment Water treatment emission Air emission - Flue gas conditioning/NOx control or triggered by water treatment use. Depending on concentration in coal

Triggered by liquid fuel use – evaporative and combustion emission

Yes Possible

Depending on concentration in coal

Yes

1/2a 1 1/2b

Yes Possible Yes

1/2b

Yes

1 1/2b 1

Possible Yes Possible

Triggered by fuel oil use – evaporative and combustion emission

1

Possible

Only for largest coal fired stations

1

Possible

Dichloromethane Ethylbenzene

1 1

Possible Possible

Triggered by liquid fuel use – evaporative and combustion emission Degreaser Triggered by liquid fuel use – evaporative and combustion emission

Fluoride compounds n-Hexane

1/2b 1

Yes Possible

9

Water treatment – emission to water/air


For gas combustion. Triggered by liquid fuel use – evaporative and combustion emission.

Substance Hydrochloric acid Lead & compounds Magnesium oxide fume Manganese & compounds Mercury & compounds Nickel & compounds Nickel carbonyl Nickel subsulphide Oxides of nitrogen PM10 Polychlorinated dioxin & furans Polycyclic aromatic hydrocarbon Selenium & compounds Sulphur dioxide Sulphuric acid

Threshold 1/2a 1/2b 1/2b 1

Relevance Yes Yes Yes Possible

1/2b 1/2b 1/2b 1/2b 1/2a 1/2a 2b

Yes Yes Yes Yes Yes Yes Yes

2a

Yes

1/2a 1

Yes Possible

Tetrachloroethylene Toluene (methylbenzene) Total nitrogen Total phosphorus Total VOC

1 1

Possible Possible

3 3 1a/2a

Possible Possible Yes

Trichloroethylene Xylenes (individual or mixed isomers) Zinc and compounds

1 1

Possible Possible

1

Possible

1

Possible

Comment



Water treatment. SO3/SO4 emission to air Degreaser Triggered by liquid fuel use – evaporative and combustion emission Water emission Water emission Triggered by liquid fuel use – evaporative and combustion emission Degreaser Triggered by liquid fuel use – evaporative and combustion emission Depending on concentration in coal

A number of emission estimation techniques (EETs) are available for use by reporting facilities. In general, there are four types of EET that may be used to estimate emissions from a facility. The four types described in the NPI Guide are: • • • •

sampling or direct measurement; mass balance; fuel analysis or other engineering calculations; and emission factors

In practice, facilities are likely to make use of all four EET techniques in meeting their NPI reporting requirements. In the Results section of this report the appropriateness of using emission factors developed in the United States is examined. 10

Initial use of the Manual by reporting facilities identified a number of specific deficiencies including: • consistency in application of NPI reporting requirements; • layout of the NPI Manual and user friendliness; • the relevance of some substances to the electricity industry; • absence of emission factors for some substances; • inclusion of substances for which no emission estimation technique are available; and • inclusion of inappropriate emission factors for some substances. The current report addresses a number of these deficiencies, particularly the last 4 points above and hence will contribute to improved NPI reporting by coal-fired electricity generators.

11

3 MODELLING TRACE ELEMENT EMISSIONS Under the NPI legislation, power stations are required to report emissions of toxic trace elements and organic compounds to atmosphere as detailed in Section 2. The reasons for this requirement are that releases of such species to the environment are attracting more interest, and, in some cases, regulatory authorities are actively considering control and reduction measures. Accurate and representative reporting of emissions is, therefore, a high priority. There are at least three options which could be considered for the reporting of emissions: •

Direct measurements of emissions at the specific locations in question. While this would appear to be the ideal situation representative measurements are difficult to obtain and very expensive for the trace species required by the NPI. The measurements require detailed probing of the large power station ducts and vary with load, type of coal and operational condition of the particle capture technology (eg ESP rapping or tears in fabric filter bags). Reliance on direct measurements alone could result in inconsistencies across the industry, and large changes in the amounts reported year to year from individual facilities.

•

Modelling of emissions based on coal properties and composition, high temperature chemistry and the performance of air pollution control devices is attractive in the long term. However the ability to undertake this modelling has not yet advanced to a stage where it can be used with confidence to report emissions.

•

Development of a database of emissions based on measurements at a large number of plants, and the calculation of emission factors for emissions from this database. This approach is the one that has been adopted by the NPI, and other pollutant inventories, drawing heavily on available US data.

The database and emission factor approach would appear to present the best opportunity currently to develop procedures for estimating emissions of trace species from coal combustion plant. However there are a number of problems which emerge when the available data are considered. These include: • • • •

Data quality; significant problems of sampling and analysis have not always been adequately addressed in some studies, particularly the older ones. Data accessibility; the data are not always available in the open literature; for example, EPRI has a large data set which is only completely available to its members Data variability; for reasons not yet completely understood, significant variability in the deportment of selected trace elements in full scale plants is observed Data quantity; in many cases the amount of emission data of acceptable quality for a particular substance is limited.

12

In part, these problems are related to the complexity of the processes by which emissions of trace elements occur. The more volatile trace elements may be emitted in the gas phase or enriched on the fine (sub micron) particulate fraction, and hence escapes capture by electrostatic precipitators or bag filters. Alternatively, trace elements may reside in the fly ash collected by gas cleaning devices or in the bottom ashes or slags. Their ultimate fate, in the latter case, will depend on the utilisation and/or disposal options chosen for the ash or slag, and in many cases will be determined by the leachability of the trace elements. Senior et al (2000) argue that emissions of trace elements from coal combustion are determined by: • • •

modes of occurrence of the elements in the coal; transformations of the elements into vapour and particles in the furnace; and the ability of the vapours and particles to penetrate the air pollution control devices (APCDs).

It has also been shown that post-combustion reactions and transformations of trace elements can also play an important role in determining their deportment in combustion (Helble 2000a). Current knowledge of these processes is incomplete, and modelling or estimation techniques, which account for all these effects are still in the process of development. Similarly, emissions of trace organic species such as PAHs and dioxins are significantly affected by plant combustion conditions, and gas quench rates, and are difficult to accurately predict using our existing understanding. Given this position it is likely that existing and new field data will provide the basis for reporting for some time to come, in spite of the limitations and problems noted above. The most extensive data sets have been collected in the US and Europe and these form the basis of the reporting procedures incorporated into the NPI workbook for Fossil Fuel Electric Power Generation. The US data for trace metals has been critically reviewed by Helble (2000b). This review shows that the US databases provide information on coal rank, ash content, sulphur content, trace element concentrations, coal higher heating value, trace element emissions rate, and particle emissions rate. Emissions of individual trace elements are reported based on the following relationship:

Ei = Ai ,in (1 − η i ) = C i (1 − η i ) / H

(1)

where: Ei Ai,in Ci ηi

is the emission on a mass per fuel energy content basis is the concentration of the trace element i at the inlet to the air pollution control device (mass per unit fuel energy content) is the concentration (mass fraction) of trace element i in the coal on an as received basis, and is the capture efficiency of trace element i in the air pollution control device 13

The particle collection efficiency, η, of an air pollution control device is defined (Helble, 2000b) as:

η =1− PM out / PM in

(2)

where: PMout, inis the particulate matter concentration (mass per unit heat input) at the outlet or inlet to the air pollution control device PMout can be expressed (Helble, 2000b) in terms of coal parameters as: PM out = PM in (1 − η ) = f a (1 − η ) / H

(3)

where: fa H

is the mass fraction of ash in the coal on an as-received basis, and is the higher heating value of the coal on an energy content per unit mass basis

Combination of equations (1) and (3) gives an expression for trace element emissions as a function of measurable parameters: Ei =

C i PM out (1 − η i ) f a (1 − η )

(4)

However the broad range of trace element emissions observed at different plant has led to the development of a modified version of equation (4):  (C PM out )  Ei = ai  i  fa  

bi

(5)

where ai and bi are constants. Equation 5 is the form recommended by EPRI for interpretation of the DOE and PISCES data (see Helble (2000b) and references quoted there). It is also the basis for the equations used in the NPI workbook, but it should be recognised that this is an empirical approach, and one which does not allow for the enrichment of many trace elements in the fine particle sizes. As these particles are more difficult to capture in electrostatic precipitators, this simplification may be significant. Helble (2000b) has developed a model, which includes trace element concentrations as a function of particle size, and size dependent particulate capture efficiencies. Using this model he is able to show that the predictions of emitted concentrations of volatile trace elements such as arsenic and selenium can be improved. At present data for Australian coals and facilities are not extensive enough for the refinements incorporated in Helble’s model, and the correlational approach used in the NPI, based largely on US data, should be the preferred method for reporting emissions. As the database from local facilities increases, and as results of the fine particle project (CCSD Project 2.1.5) become available, there may be opportunities to further refine the reporting procedures in the NPI.

14

4 SAMPLING AND ANALYSIS OF NPI LISTED TRACE ELEMENTS IN POWER STATION FLUE GAS As discussed in Section 2, the fossil fuel electricity generation NPI workbook contains a number of emission estimation techniques (EETs). Included in the EETs are: • sampling or direct measurement; and • emission factors. Emission factors are generally developed from sampling or direct measurements – an emission factor can be specific to one facility or generic in that it might apply to type of facility (such as a black coal pulverised boiler, for example), or to a type of control device (such as a fabric filter or electrostatic precipitator). The emission factors included in the NPI workbook were generally sourced from the USEPA’s Compilation of Air Emission Factors, AP-42, Fifth edition, Volume 1: Stationary Point and Area Sources, (USEPA 1996). These factors were developed from stack sampling undertaken on a range of facilities in the United States, and as such they may not be representative of conditions applying in Australia. In order to test the appropriateness of applying AP-42 emission factors locally, a number of the black coal electricity generators in NSW and Queensland undertook stack-testing programs for a range of the NPI listed substances. The stack testing within each state was undertaken by the same organisations following the same sampling protocols. However, the sampling and analytical protocols adopted by the 2 state programs were different (as discussed below). Listed in Table 4-1 and Table 4-2 is a summary of the sampling undertaken at the NSW and Queensland coal fired power stations.

15

Table 4-1 Stack sampling undertaken in NSW in 1999 Stations sampled

Bayswater, Liddell, Eraring, Vales Point, Wallerawang, Mt Piper

Contractor

Stephenson and Associates

Contract supervisor Sampling requirements

Pacific Power International

Substances sampled Oxygen, carbon dioxide and carbon monoxide Particulate matter

Method (1)

Comment

EPANSW draft Methods 24 and 25

Grab samples, Teledyne Max 5 combustion analyser

Metals Chromium species (VI) Sulphur trioxide Hydrogen sulphide

Duplicate sampling Gas and particulate phases, where appropriate Full, or near, full load Concurrent coal sampling

EPANSW draft Method 15 Packed Alundum Thimble Filtration method EPANSW draft Method Heated glass probe, filter, 12; USEPA Method 29 impingers. ICPMS analysis USEPA Particulate only EPANSW draft Method 13+ EPANSW draft Method 5

Chloride, Acid gases EPANSW draft Method 8 Cyanide

EPANSW draft Method

Fluoride

EPANSW draft Method 9

Nickel carbonyl and Nickel subsulphide

Based on NIOSH Method 6007

Methane Volatile organic Compounds

Collection using NIOSH 127 and 206 16

Glass or stainless steel probe, impingers, ion chromatography In stack analysis, Gastech analyser. Expressed as HCl. Glass or stainless steel probe, impingers, ion chromatography. Glass or stainless steel probe, impingers, distillation and colorimetric analysis. Particulate phase not sampled in first tests. Glass steel probe, impingers, Specific Ion Electrode Filter and activated carbon. Found to be non-specific for the substances. Grab samples analysed with hydrocarbon analyser fitted with Flame ionisation detector Activated carbon tube. Analysis using Gas chromatography/Mass

Dioxins/Furans, PAHs, PCBs Ash and Moisture

Spectrometry and Gas Chromatography/Photoionisation detection. EPANSW draft Method 23 Filter, resin trap, impinger train. ISO1711- 1981;ISO50681983

Exhaust gas velocity

Pitot tube and inclined manometer. 1. EPANSW draft methods have subsequently been published in the Approved methods for the sampling and analysis of air pollutants in New South Wales (2001) Table 4-2 Stack sampling undertaken in Queensland in 1999 Stations sampled

Callide B No. 2 unit Stanwell No. 1 unit Tarong No. 2 unit

Contractors

CSIRO Energy Technology and AUSTA (Sigma Process Solutions) Duplicate sampling of gas phases Gas and particulate phases, where appropriate Steady load Concurrent coal, flyash and bottom ash sampling

Sampling requirements

Substances sampled Method Major and trace USEPA Method 29 elements

Comment Vapour phase

Particulate matter not analysed The fundamental requirements for the estimation of the atmospheric emissions from coal-fired power stations are: • sampling under representative operating and fuel conditions • accurately measuring the normalised gas flow through the ducts • collecting a representative sample of the particulate matter passing through the duct • using appropriate sampling techniques to collect “vapour phase” trace elements and gases • Accurate analysis of collected gas and particulate phase samples. From the above tables it can be seen that appropriate reference methods were employed in the sampling programs, although in the case of the Queensland program, the collected particulate matter was not analysed. Of the above issues the major ones are related to variability in fuel composition and variability in the particle collection technology. Included in the latter are rapping of the plates of an ESP or bag shaking. The presence of torn bags in a fabric filter installation can also have a significant impact on the emissions.

17

As the power station ducts are normally quite large (eg 4x4m) and not necessarily laid out in long runs, there is the possibility that inertial effects will give rise to particle segregation. It is generally accepted that the particulate loading across the inlet duct of the air pollution control devices is usually stratified. Stratification at the outlet of the devices is less pronounced. Consequently, adequate sampling of the duct geometry is crucial. This is dealt with by Australian Standard Method AS 4323.2-1995 which allows for an increase in sampling locations depending on the location of bends and the sampling position. From the above points it is apparent that despite the application of reference test methods and procedures it is possible that there will be considerable variability in the results obtained. While some of these results may indeed be due to deficiencies in sampling and analysis it is considered that inherent variability and complexity in the processes involved and the (often) very low concentrations of these substances in the gas stream may be responsible for at least part of the variability. These considerations lead to the conclusion that in estimating mass emissions over a period, such as the annual reporting required by the NPI, reliance on a single or small number of stack tests is likely to lead to results which are not representative and which may vary significantly from period to period. An alternative approach, which is likely to provide more representative emissions data, is that described in the previous section, which involves the development of a database of emissions based on measurements at a large number of plants, and the calculation of emission factors for emissions from this database. As noted previously this is the approach adopted in most pollution inventories, including the NPI. The applicability and reliability of this approach is tested in the next section of this report.

18

5 RESULTS 5.1 ESTIMATING TRACE METAL EMISSIONS USING THE NPI WORKBOOK Three emission estimation techniques (EETs) are available in the NPI Emission Estimation Technique Manual for Fossil Fuel Electric Power Generation (available at http://www.npi.ea.gov.au/handbooks/approved_handbooks/ffossilfuel.html) to provide estimates of emissions for most of the trace metals included in the NPI. These EETs are as shown in Table 5.1. As discussed in Section 2 these EETs were obtained from the USEPA’s Compilation of Air Emission Factors, AP-42, Fifth edition, Volume 1: Stationary Point and Area Sources, 1996. Factor 1 and Factor 2 in the table are simple generic emission factors. Factor 1 emissions are based solely on heat input and apply to uncontrolled bituminous and sub-bituminous pulverised, dry bottom combustion. Factor 2 emissions are based on the mass of coal feed, as fired, and apply to controlled combustion, either using electrostatic precipitators or fabric filters. The emission equations in the table are based on energy input and apply to combustion of both black and brown coal in controlled boilers. The equations require site-specific input data on: • concentration of the trace element in the coal • mass fraction of ash in coal • total particulate emissions per GJ of energy input. In this section the estimated emissions, calculated using both Factor 2 and the relevant equations from the NPI workbook, are compared with the actual emissions as determined from the sampling programs described in Section 4. The purpose of making these comparisons was to assess whether EETs developed in the United States could be confidently used to predict emissions under Australian conditions. The uncontrolled Factor 1 EETs have not been assessed, as they are rated as “poor” by .the USEPA, whereas Factor 2 and the Equations are generally rated as “excellent” (see Table 5.1). The amount of trace metal in the feed coal to the various power stations, required as input to the emission equations, is shown in Table 5-2, along with Australian and international ranges for each trace metal. No Australian or international ranges were available for antimony, magnesium, tin or vanadium. It can be seen that the trace metal concentrations of most of the feed coals falls within the expected range. A notable exception to this result is the arsenic concentration at Bayswater, which is much higher than levels detected in any other feed coal, and well outside the Australian and international ranges. Similarly, manganese at Qld 13 was considerably higher than that detected in the other coals and fell well outside the expected ranges, as did beryllium at Mt Piper. These anomalous results indicate the desirability of

3

The Queensland power station data is reported anonymously.

19

collecting and analysing representative coal samples on a regular basis, perhaps two to four times a year. Table 5-1 Emission Factors for Black Coal Combustion (Trace Elements) from Table 7 of the NPI Manual SUBSTANCE

Antimony & compounds Arsenic & compounds Beryllium & compounds Boron & compounds Cadmium & compounds Chromium compounds Chromium (VI) compounds Cobalt & compounds Copper & compounds Lead & compounds Magnesiume Manganese Mercury & compounds Nickel & compoundsf Selenium & compounds Zinc & compounds

EMISSION FACTOR Equationa

Rating

Factor 1b uncontrolled

kg/PJ 0.675* [(C/A) * PM]0.63

A

kg/PJ ND

2.73 * [(C/A) * PM]0.85 1.31 * [(C/A) * PM]1.1

A A

294 35e

A

ND 19

ND 2.17 * [(C/A) * PM]0.5 2.6 * [(C/A) * PM]0.58d ND

A

538 - 676d ND

1.31 * [(C/A) * PM]0.69 ND 2.87 * [(C/A) * PM]0.8 ND 2.71 * [(C/A) * PM]0.6 ND 2.84 * [(C/A) * PM]0.48 ND

A

ND ND 218 ND 98 - 1282 7 443- 555 ND

A A A

ND

ND

Rating

Factor 2c controlled

kg/tonne 9 * 10-6

A

E E

2.1 * 10-4 1.1 * 10-5

A A

E

ND 2.6 * 10-5

A

1.3 * 10-4f 4 * 10-5

A D

5 * 10-5 ND 2.1 * 10-4 5.5 * 10-3 2.5 * 10-4 4.2 * 10-5 1.4 * 10-4 6.5 * 10-4

A

E

E E E E

ND

Compilation of Air Emission Factors, AP-42, Fifth edition, Volume 1: Stationary Point and Area Sources, 1996 (Tables 1.1-15, 1.1-16 and 1.1-17 unless otherwise stated) Notes: Rating A - Excellent, B - Above Average, C - Average, D - Below Average, E - Poor, U - Unrated PJ petajoule (1015 joule) ND No data available a Derived from Table 1.1-15, AP-42 (1996) in the units kg/PJ of heat input. The equations apply to combustion of black coal and brown coal with controlled boilers and are based on heat input. C = concentration of metal in the coal, parts per million by mass (wet basis), A = weight fraction of ash in the coal. For example, 10% ash is 0.1-ash fraction. PM = site-specific emission factor for total particulate matter (kg/GJ), ie. particulate matter emitted per GJ heat input. To calculate emission rate use: Emission rate (tonne/year) = (Emission Factor (kg/PJ) x Heat Input (PJ/year))/103 (Heat input (PJ) = [higher heating value(MJ/kg) x coal use (tonne/year)] /106) b Derived from Table 1.1-16, AP-42 (1996) and based on heat input. Applies to uncontrolled bituminous and sub-bituminous coal combustion, pulverised coal, and dry bottom unless otherwise noted. A range of factors represents the factors in the literature. The emission factor is in kg/PJ of heat input. Emissions should be adjusted to account for control equipment c Derived from Table 1.1-17, AP-42 (1996). The emission factors (kg/tonne) are based on coal feed, as fired, and apply to controlled coal combustion for boilers utilising electrostatic precipitators or fabric filters d Equation for chromium (III & VI) e No specific data for tangential firing f for chromium (III & VI)

20

Rating

A A A A A A

Table 5-2 Trace metal content of feed coal

Element

Amount in mg/kg Bayswater Liddell

As 16.3 B 22 Be 1.9 Cd 0.11 Co 7.6 Cr 29 Cu 24 Hg 0.23 Mg 1247 Mn 137 Ni 18 Pb 11 Sb 0.5 Se 1.43 Sn 1.7 V 52 Zn 34.33 a From Dale (1995)

3.2 14 1.9 0.10 5.8 14 25 0.06 1400 105 6 12 0.7 0.92 1.9 51 26.5

Eraring

Vales Point

Mt Piper

Wallerawang

Qld 1

Qld 2

Qld 3

0.6 32 2.3 0.06 2.3 11 12 0.05 680 72 6 13 0.8 0.93 1.7 28.5 20

1.3 29 1.9 0.05 3.5 9 12 0.04 700 113 7 10 1.0 0.95 1.3 29 20

1.5 27 4.3 0.09 2.0 8 13 0.02 345 17 9 11 0.7 1.08 2.05 27.5 32

1.5 26 2.7 0.08 1.6 8 13 0.02 490 20 6 13 0.6 1.31 1.95 27.5 16.5

1.4 18 0.8 0.12 7.5 12 19 0.03 1305 432 12 9 0.2 0.40 1.62 32.83 30.5

7.3 9 0.5 0.05 3.2 8 17 0.04 1775 205 6 6 0.3 0.61 0.52 25.65 19.72

2.1 11 1.6 0.14 7.8 9 22 0.02 296 7 7 10 0.3 0.52 1.53 66.67 61.33

21

Australian Range a 0.65-2.7 12-47 0.2-2.0 0.055-0.09 1.7-10.5 2-21 6-16 0.02-0.076 N/A 5-157 5-21 4.5-9.5 N/A 0.3-0.84 N/A N/A 35-580

International Range a 0.36-9.8 11-123 0.1-2.0 0.01-0.19 1.2-7.8 2.9-34 1.8-20 0.03-0.19 N/A 8-93 1.5-21 1.1-22 N/A 0.15-5.0 N/A N/A 25-1420

Figures 5.1 to 5.11 show comparisons between emission estimates based on the stack measurements undertaken in NSW and Queensland and estimates based on the NPI EETs Factor 2 and Equations. In considering these graphs the following points should be noted: •

Data labelled as “Factor 2” gives a plot of the predicted annual emission using Factor 2 in the NPI handbook (i.e., tonnes of coal times the default emission factor in kg Substance/t coal) versus measured annual emission calculated from the power station emission test data

•

Data labelled as “Equation” gives a plot of the predicted annual emission using the empirical equations in the NPI handbook as reproduced in Table 7 above, e.g., Antimony = 0.675*[(C/A)*PM]0.63 versus measured annual emission calculated from the power station emission test data

•

The line shown in the graphs represents the 1:1 correlation between predicted and measured trace element quantities.

•

For mercury and selenium emissions, prediction based on a Factor 2 calculation only is presented as the NPI handbook does not include equations.

The following describes the performance of the EETs for most of the NPI metals. Antimony Figure 5.1 shows that NPI Factor 2 generally significantly over predicted emissions. The use of the NPI equation to calculate emission factors yielded significantly better predictions of emissions, generally within a factor of ~five of emission estimates based on measurements. Arsenic Figure 5.2 shows that emissions for arsenic were significantly over predicted by NPI Factor 2, the estimated emissions were all higher than the measured emissions, with the estimated emissions ranging from being 8 times to more than 1000 times higher than the measured emissions. The NPI equation supplied yielded emission estimates that were in better agreement with the actual emissions, than the Factor 2 approach, for most of the power stations. However, the estimated emissions for two of the stations were considerably higher than the actual measured emission. This may in part be due to anomalously high coal concentrations, as noted above, and shown in Table 5-2. Beryllium, Cadmium and Cobalt Figures 5.3, 5.4 and 5.5 for beryllium, cadmium and cobalt respectively show that Factor 2 emission estimates for these elements are higher, and often significantly so, than measured estimates for almost all power stations.

In general, the use of NPI equations, instead of Factor 2, results in estimates that are within a factor of ~five of estimates based on measurements, although there are still cases where the discrepancy is greater. Chromium The emission rates for chromium (total) are shown in Figure 5.6. The use of Factor 2 gave chromium emission rates that agreed reasonably well with the measured emissions for all six NSW power stations, although there were significant outliers. The predictive capability of Factor 2 was poor for the three Queensland power stations. The NPI equations gave

22

chromium emissions that were reasonably close to the measured emissions for 6 of the 9 power stations with a significant outlier. Lead Lead emissions were generally predicted very well by the NPI equation (although again there was a significant outlier), as shown in Figure 5.7, while Factor 2 predictions were very poor. Manganese Factor 2 and equation estimates for manganese emissions were variable, as shown in Figure 5.8, with the equation estimates tending to be more reliable than those produced by Factor 2. Note that manganese is not on the NPI reporting list. Mercury No NPI emission equation is available for mercury. Figure 5.9 shows that Factor 2 estimates are variable, resulting in good agreement with measured results at three stations but significant differences between predicted and measured results at the other 6 stations. Nickel The emission estimates obtained for nickel using the equation approach were scattered about the line of perfect agreement as seen in Figure 5.10. Again, the emission equation tended to better fit the data than the Factor 2 approach. Selenium The NPI Manual does not contain an emission equation for selenium. Figure 5.11 shows that the Factor 2 emission estimates are very poor. Boron, Copper, Tin, Vanadium and Zinc The NPI manual does not contain either a Factor 2 or Equation for these elements. Note that emissions of tin and vanadium are not included on the NPI reporting list.

Several conclusions can be drawn from the results shown in the figures and tables, discussed above: • simple emission factors, based solely on heat input or coal consumption, are unlikely to result in reliable emission estimates. • emission equations which are based on local factors, such as concentration in coal, ash content and collection efficiency, are capable of producing reasonable emission estimates for NPI reporting purposes. • reliable emission estimation techniques are not available in the manual for a number of NPI substances. .

23

70

60

Predicted emissions (kg/year)

Factor 2 Equation

50

40

30

20

10

0 0

1

2

3

4

5

6

7

8

9

Measured emissions (kg/year)

Figure 5-1 Antimony – Comparison between emission estimates based on stack measurements and NPI EETs

10000


Factor 2 Equation 1000

100

10

1 0

5

10

15

20

25


Figure 5-2 Arsenic – Comparison between emission estimates based on stack measurements and NPI EETs. Note log scale on y-axis.

24

80

70


Factor 2 Equation

60

50

40

30

20

10

0 0

2

4

6

8

10

12

14

16


Figure 5-3 Beryllium – Comparison between emission estimates based on stack measurements and NPI EETs

200

180


Factor 2 Equation

160

140

120

100

80

60

40

20

0 0

2

4

6

8

10

12

14

16


Figure 5-4 Cadmium – Comparison between emission estimates based on stack measurements and NPI EETs

25

400

350

Predicted emissions kg/year)

Factor 2 Equation

300

250

200

150

100

50

0 0

5

10

15

20

25

30


Figure 5-5 Cobalt – Comparison between emission estimates based on stack measurements and NPI EETs

1600


1400

Factor 2 Equation

1200

1000

800

600

400

200

0 0

200

400

600

800

1000

1200

1400

1600


Figure 5-6 Chromium – Comparison between emission estimates based on stack measurements and NPI EETs

26

1600


1400

Factor 2 Equation

1200

1000

800

600

400

200

0 0

20

40

60

80

100

120

140

160

180


Figure 5-7 Lead – Comparison between emission estimates based on stack measurements and NPI EETs

2000


1800

1600

Factor 2 Equation

1400

1200

1000

800

600

400

200

0 0

50

100

150

200

250

300

350

400


Figure 5-8 Manganese – Comparison between emission estimates based on stack measurements and NPI EETs

27

350


300

Factor 2 250

200

150

100

50

0 0

10

20

30

40

50

60


Figure 5-9 Mercury – Comparison between emission estimates based on stack measurements and NPI EETs


1200

1000

Factor 2 Equation 800

600

400

200

0 0

50

100

150

200

250

300

350

400

450


Figure 5-10 Nickel – Comparison between emission estimates based on stack measurements and NPI EETs

28

10000


Factor 2

1000

100

10

1 0

20

40

60

80


100

120

Figure 5-11 Selenium – Comparison between emission estimates based on stack measurements and NPI EETs. Note log scale on y axis.

10000 1:1 +/- factor 5

Emission Estimates from EETs (kg/year)

1000

+/- factor 10 Equation Factor 2

100

10

1 0.1

1

10

100

1000

10000

0.1

0.01

Emission estimates based on measurements (kg/year)

Figure 5-12 Composite figure containing all data presented in figures 5.1 to 5.11.

29

5.1.1 Summary of Assessment of performance of EETs

Figure 5.12 is a composite figure containing all data presented in figures 5.1 to 5.11, on log log scales. A line of perfect agreement for all the data has also been shown along with lines delineating emission estimates from EETs which are within a factor of five and within a factor of ten of estimates based on stack measurements. Figure 5.12 clearly indicates that EETs based on site-specific factors, such as elemental coal concentration, ash fraction and particulate collection efficiency significantly outperform simple generic emission factors, relative to stack measurement results. Most estimates using the equation EETs fall within a factor of five of estimates based on stack measurements, whereas a significant number of the simple factor estimates are at least an order of magnitude greater than the respective estimates based on stack measurements.

30

6 OUTSTANDING HAPS The aim of the second stage of the project has been to examine the scientific literature for tools and analytical techniques available to the coal-fired power generation industry for the assessment and accurate measurement of the following five NPI reportable substances: • • • • •

Hexavalent chromium (Cr (VI)); Hydrogen chloride (HCl); Magnesium oxide fumes (MgO); Nickel carbonyl (Ni(CO)4); and Nickel sub sulphide (Ni3S2).

The reporting of emissions of these substances by fossil fuel electricity generators to the NPI is required, regardless of the amount of emission, based on their classification. Currently, the NPI workbook contains simple USEPA AP-42 emission factors for HCl and Cr(VI) , which as discussed in Section 5 are unlikely to be reliable under Australian conditions. For the magnesium and nickel species there is no information on analytical techniques or emission factors provided in the NPI workbook to enable facilities to estimate their emissions. This has meant that either reporting facilities have been unable to report on these five substances or have reported based on poorly supported emission factors or reported using uncertain measured results. Examination of the scientific literature yielded a lack of published information on analytical techniques on the determination of these substances in coal fired power station stack emissions. However, analytical techniques for these substances have been used in various fields and this literature review summarises those methods. The information provided here was obtained and reviewed from the on-line sources: Web of Science, Cambridge Scientific Abstracts – Environmental Sciences and Pollution Management Database, SciFinder, Current Contents and IEA Coal Abstracts, 1987 – 1999. In addition to information from the sources noted above, this section also presents information arising from; • A CRC measurement program for Cr(VI) and Ni(CO)4 • Communication with overseas researchers (Helble, Wendt )

6.1 HEXAVALENT CHROMIUM Chromium species found in coal combustion emissions are present as trivalent, Cr(III) and hexavalent Cr(VI) compounds. Of greater concern is Cr(VI), it being considerably more toxic than Cr(III) and a known carcinogen (International Agency for Research on Cancer (IARC) http://www-cie.iarc.fr/htdocs/monographs/vol49/chromium.html). The following summarises a number of methods for determining chromium speciation found in the literature. •

The USEPA Method 306 entitled ‘Determination of Chromium Emissions from Decorative and Hard Chromium Electroplating and Chromium Anodising Operations’ is, as the name implies, applied to emissions from electroplating operations. The method involves iso-kinetic sampling of flue emissions and analysis by either 31

inductively coupled plasma atomic emission spectrometry (ICP-AES) for total chromium concentrations ≥ 35 µg/L or graphite furnace atomic absorption spectrometry for total chromium concentrations < 35 µg/L. The method allows for the determination of Cr(VI) emissions by ion chromatography with the ion chromatograph equipped with a post column reactor and visible wavelength detector. A preconcentration system can be used to enhance the method for trace levels of Cr(VI). •

Huggins et al (1999) used X-ray absorption fine structure spectroscopy to estimate both chromium species in coal ash samples to 50 ppm chromium with an uncertainty of ± 5%. The method was based on the relative heights of the pre-edge peaks in the xray absorption near-edge structure spectra of the chromium species. Their results indicated that the Cr(VI) content for all but one of the ash samples was at or below the detection limit (between 3-5%) for Cr(VI). Although, the most sensitive technique for chromium speciation, the method suffers from being prohibitively expensive as a routine analytical technique.

•

To measure Cr(VI) in air, Freed (1996) used ion chromatography, enhancing the sensitivity of the method with a concentrator column prior to injection. Detection at 520 nm was accomplished by complexing the eluted Cr(VI) with diphenylcarbohydrazide.

•

Wavelength dispersive x-ray fluorescence spectrometry was utilised by Hurst (1996) to measure water-soluble Cr(VI) in chromium plating mist in workplace air samples. Samples of the mist were collected on PVC filters and screened for total Cr and to screen out samples with no Cr. Filters showing a definite chromium content were then placed in distilled water buffered to pH 4 and any Cr(VI) precipitated as Cr(VI)dibenzyldithiocarbamate complex. The precipitate was collected and analysed by XRF. A Cr(VI) recovery rate of between 79 % to 95 % was obtained.

•

Prokisch et al (1997) used a high performance liquid chromatographic technique employing a specially prepared aluminium oxide filled micro-column in association with ICP-AES to measure the Cr(III) and Cr(VI) contents of a number of materials. The materials included in this work were seven international standards and waste, incinerated waste and ash samples. For lower chromate concentrations, GFAAS replaced the ICP-AES in an off-line method. The authors noted from their study that a portion of the Cr (III) content of the waste material under investigation can be oxidised to Cr(VI) by the incineration process.

•

Reviewing developments in thermal ionisation mass-spectrometric techniques for isotope analysis, Heumann et al (1995) cite an example of the application of positive thermal ionisation mass spectrometry in connection with isotope dilution to Cr(III) and Cr(VI) speciation analysis in various water samples. Nusko and Heumann (1997) developed an isotope dilution mass spectrometric (IDMS) method using positive thermal ions formation for Cr(III) and Cr(VI) speciation in aerosol particles. The IDMS method also contributed to the certification of a corresponding standard reference material organised by the Standard Reference Bureau of the European Union.

•

Rychlovsky et al (1998) devised an on-line simultaneous sorption pre-concentration plus atomic absorption spectrometry (AAS) method that is based on the reaction 32

product of Cr(III) with Chromazurol S in weakly acidic solution and the sorption of the reaction product of Cr(VI) with sodium diethylcarbamate in strongly acidic solution. Sorption of both the products was achieved using reversed C18 phase columns both complexes formed being eluted directly into an AAS nebuliser using methanol. The method can be used for initial concentrations of Cr(III) and Cr(VI) below 1ppm. It was tested with practical samples and the detection limits were 0.2 µg//L for Cr(III) and 2.4 µg//L for Cr(VI). •

A method for the determination of low concentrations of Cr(VI) in waters by high performance liquid chromatography (HPLC) was developed by Padarauskus et al (1998). The Cr(VI) was complexed with 1,5-diphenylcarbazide and concentrated on a C-18 column. The complex was then eluted with sulphuric acid / acetonitrile solution and detected photometrically at 546 nm.

•

Bittner and Broekaert (1998) investigated a more complex method for preconcentration and speciation determination of chromium. The complexes formed by both Cr(III) and Cr(VI) with ammonium pyrrolidine dithiocarbamate were concentrated by reversed phase solid phase extraction (SPE) using an automated solid phase extractor and determined by reversed phase liquid chromatography (RPLC) using UV spectrophotometric detection.

As evidenced from the above descriptions measurement of chromium(VI) is difficult and in 2 United States studies assumptions were made regarding the occurrence of Cr(VI) in the emissions from coal combustion. The USEPA Study into Utility Hazardous Air Pollutants in 1998 (USEPA 1998b) assumed that 11% of total chromium emissions from coal fired plant were in the form of Cr (VI). Another study, quoted in the USEPA Study (USEPA 1998b) by EPRI assumed Cr (VI) contributed 5% of total chromium emissions. As part of this project, measurements of Cr (VI) in fly ashes collected from a number of Australian power stations were determined by X-ray near edge adsorption spectroscopy (XANES). These measurements were commissioned and performed by the University of Kentucky and the results of the measurements are discussed in detail by Huggins and Huffman (2001). The samples were collected from the final pass of the ESPs or from the fabric filters at the power stations. Figure 6-1 shows the XANES spectra obtained for two of the samples. Clearly one sample contains significant Cr(VI), and the other contains very little, if any. Table 6-1 shows details of the samples and the results obtained for all. It was found that Cr (VI) contributed from less than 3 % and up to 13% to total Cr emissions. Of the seven samples analysed, five returned results less than the method’s limit of detection (3%).

33

0.4

Cr(VI) Normalized Absorption

0.3

0.2

CSIRO "A"

0.1

0

-0.1 -8

-4

0

4

8

12

Energy, eV Data

Fit

Edge

Peak 1

Peak 2

0.2

Absorption

0.15 CSIRO "C"

0.1 0.05 0 -0.05 -0.1 -8

-4

0

4

8

Energy, eV Data

Fit

Edge

Peak 1

Peak 2

Figure 6-1: Detail of least-squares fitting of chromium XANES spectra for samples A and C. Upper spectrum contains significant Cr(VI), whereas the lower spectrum contains very little, if any, Cr(VI). Note the difference in vertical scales.

Table 6-1: Details of Cr (VI) measurements by XANES

Sample Power Station A B C

Comments

NSW 1 NSW 2 NSW 3

Final zone ESP hopper Final zone ESP hopper Fabric filter fly ash sample processed to enrich finer material D Qld 1 Final zone ESP hopper E Qld 2 Final zone ESP hopper F Qld 3 A fly ash from fabric filter hopper G Qld 3 B fly ash from fabric filter hopper a Uncertainty no more than ± 3% 34

Cr (VI) content determined by XANES (% of total Cr)a 13 2 1 1 3 7 2

These results are consistent with theoretical and experimental work undertaken in the United States (Linak et 1996, Linak and Wendt 1998). Theoretical equilibrium calculations have found that: • Although some Cr(VI) compounds are favoured at high temperatures, they are not favoured at low temperatures in the absence of chlorine. • When chlorine is added, Cr(VI) species are favoured at stack temperatures • Cr(VI) disappears in the exhaust with the addition of relatively small amounts of sulphur, even in the presence of larger amounts of chlorine. • Experimental studies confirmed these theoretical results, the authors noting that Cr(VI) is an extremely difficult substance to collect and analyse. The experimental data found that: • In the absence of chlorine and sulphur approximately 2% of the total Cr in the stack gas was Cr(VI). • Addition of very high levels (6,700 ppm) of chlorine increased the Cr(VI) percentage to approximately 8%. • Less than 100 ppm of sulphur is capable of decreasing Cr(VI) to less than detection levels, even with 2,900 ppm of chlorine present. The USEPA AP-42 emission equation for total chromium is considered appropriate for use in estimating emissions from black coal as it takes into account coal concentration, ash fraction, particulate collection efficiency and is based on energy input. The United States and local results, discussed above, suggest that under Australian conditions with chlorine and sulphur levels in the flue gas in the range of 300 – 600 ppm and 300 – 700 ppm respectively the percentage of chromium in the hexavalent form would generally be low. The occurrence of a minority of test results showing slightly elevated Cr(VI) percentages, suggests that the use of 5% Cr as Cr(VI), as assumed by EPRI would be suitably conservative. It is recommended that the emission equation for total chromium be used for black coal in conjunction with the assumed Cr (VI) fraction of 5% and that the balance (95%) of total chromium be reported as Cr (III).

6.2 HYDROGEN CHLORIDE The emission factor that is provided in the NPI workbook is based on US data (AP-42) and is therefore generally based on higher chlorine content of US coals in comparison to Australian coals. An emission factor or estimation method based specifically on the chlorine content of Australian coals or plant data would provide a more accurate emission estimate. The following methods for HCl determination may be useful for confirming an Australian coal-based emission factor. •

USEPA Methods 26 ‘Determination of Hydrogen Halide and Halogen Emissions from Stationary Sources Non-Isokinetic Method’ and 26A (Determination of Hydrogen Halide and Halogen Emissions from Stationary Sources Isokinetic Method). These methods are employed for analysis of wet gas streams. The substances of interest are absorbed in dilute acid and alkaline solutions. Halide ions in each solution are determined by ion chromatography. Sun et al (2000) used bench scale combustion tests involving a variety of conditions to evaluate Method 26A. They concluded that 35

the Method would not accurately speciate low concentrations of chlorine in coal combustion flue gas. •

Sloss and Gardner (1995) reviewed reported methods for sampling and analysis of trace emissions from coal-fired power plant stacks. Included in these methods were ion chromatography (CFR, 1994), ion selective electrodes (CEA, 1994) and potentiometric titration (VDI, 1984) for determining HCl in Method 26A impinger solutions. Instruments available for continuously monitoring HCl were also reviewed. McCulloch et al (1998) employed annular denuder systems to trap various acid gases including HCl and ion chromatography to analyse solutions used to elute trapped species. Complementary to Sloss and Gardner’s review is Cremer and Warner’s review (1993) of HCl and HF continuous emission analysers in their report entitled ‘Continuous Monitoring Instrumentation for Emissions to Air From Large Combustion Plant’.

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Also reported in the literature is the use of a solid-state electrochemical sensor to measure trace quantities of hydrogen chloride gas in a humid atmosphere (Pelloux and Gondran, 1999). The use of long path Fourier transform infrared spectroscopy (FT-IR) to measure HCl and other corrosive gases has also been reported (May, et al 1995).

It is recommended that the existing emission factor in the NPI Workbook of 0.6 kg of HCl per tonne of coal consumed for black coal combustion not be used, unless necessary, but rather a simple mass balance approach be adopted, based on the chlorine content of coal burnt and, if considered necessary, the fraction of chlorine retained in ash. Ash chlorine measurements may be more relevant for brown coal combustion where the low ash fraction and high sodium concentrations may result in a relatively high retention of chlorine in ash (Helble 2000).

6.3 MAGNESIUM OXIDE FUME A survey of the literature via The Web of Science did not yield any results on MgO fumes, however a search of Sci-Finder yielded 3 papers that were related to shotcrete and welding fumes. No detailed analytical methods were reported. A more detailed examination of Chemical Abstracts for “ash fumes” and “MgO in ash” produced more useful information and viable analytical techniques. Mattigod and Ervin (1982) developed a scheme for the density separation and identification of compound forms in size fractionated fly ash. The scheme has been developed to utilise a linear density gradient that incorporates a dispersing polymer and the subsequent analysis by X-Ray Diffraction (XRD). The scheme developed is useful in identifying crystalline components that are present in concentrations