Emissions of SO2, NOx and particulates from a pipe manufacturing ...

Environ Monit Assess (2010) 169:677–685 DOI 10.1007/s10661-009-1207-z

Emissions of SO2 , NOx and particulates from a pipe manufacturing plant and prediction of impact on air quality A. D. Bhanarkar · Deepanjan Majumdar · P. Nema · K. V. George

Received: 24 October 2008 / Accepted: 9 October 2009 / Published online: 4 November 2009 © Springer Science + Business Media B.V. 2009

Abstract Integrated pipe manufacturing industry is operation intensive and has significant air pollution potential especially when it is equipped with a captive power production facility. Emissions of SO2 , NOx , and particulate matter (PM) were estimated from the stationary sources in a state-of-the-art pipe manufacturing plant in India. Major air polluting units like blast furnace, ductile iron spun pipe facility, and captive power production facility were selected for stack gas monitoring. Subsequently, ambient air quality modeling was undertaken to predict ground-level concentrations of the selected air pollutants using Industrial Source Complex (ISC 3) model. Emissions of SO2 , NOx , and particulate matter from the stationary sources in selected facilities ranged from 0.02 to 16.5, 0.03 to 93.3, and 0.09 to 48.3 kg h−1 , respectively. Concentration of SO2 and NOx in stack gas of 1,180-kVA (1 KW = 1.25 kVA) diesel generator exceeded the upper safe limits prescribed by the State Pollution Control Board, while concentrations of the same from all other units were within the prescribed limits.

A. D. Bhanarkar · D. Majumdar (B) · P. Nema · K. V. George Air Pollution Control Division, National Environmental Engineering Research Institute Nehru Marg, Nagpur, 440020, India e-mail: [email protected]

Particulate emission was highest from the barrel grinding operation, where grinding of the manufactured pipes is undertaken for giving the final shape. Particulate emission was also high from dedusting operation where coal dust is handled. Air quality modeling indicated that maximum possible ground-level concentration of PM, SO2 , and NOx were to the tune of 13, 3, and 18 μg/m3 , respectively, which are within the prescribed limits for ambient air given by the Central Pollution Control Board. Keywords Air pollution · Air quality modeling · Ductile iron · ISC3 · India · Stack emission

Introduction With the advent of rapid industrialization, air pollution has become a real concern, particularly in inhabited areas and around large traffic corridors (Douglas et al. 2002; Mirasgedis et al. 2008). Air pollution has been held responsible for various health disorders, especially respiratory complications resulting in an increase in the number of asthmatic cases and hospital visits in various parts of the world (Delfino et al. 1998; Norris et al. 1999; Yu et al. 2000). India has not been an exception in this regard, and various governmental regulations and mechanisms on siting, commissioning, and functioning of industries have been formulated

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in India under the aegis of the Central Pollution Control Board (CPCB) and State Pollution Control Boards to minimize air pollution. Demand of good-quality submerged arc welded (SAW) pipes has increased in recent years due to growth in oil and gas sector and increase in transboundary movement of petroleum and natural gas. Moreover, a country like India aims to improve water supply and sewerage systems, more prominently in urban areas, resulting in an increasing demand of ductile iron (DI) pipes (Ductile Iron Pipe Research Association, www.dipra.org/pdf/wastewater.pdf). Pipes are consumed by various industrial sectors like oil and gas (50%), construction (30%), and various others (20%) (Indian Pipe Industry Report 2008). Various Indian companies equipped with indigenous technologies or with foreign technical assistance have embarked upon mass production of SAW and DI pipes. Production of these pipes requires a huge quantity of minerals like coal, iron ore, etc. for in situ iron production and fuels like fuel oil, low-sulfur diesel, high-speed diesel, etc. for captive power generation where power requirement exceeds the supply from the State Electric Supply Board. Some of the operations in an integrated pipe manufacturing plant emit appreciable SO2 , NOx , and particulate matter (PM). Emissions of PM, SO2 , and NOx from industrial sources vis-à-vis steel industry have been reported earlier (USEPA 1987; Bhanarkar et al. 2003, 2005a, 2008; Wang et al. 2003; Taib 1995). Prediction of impacts of emissions on the receiving environment is important as ambient air quality is critical for public health. Air pollution models may substantially help in assessing air quality and optimizing emission reduction strategies (Cora and Hung 2003; Kumar et al. 1999). Several air quality modeling studies have been carried out in the past using Industrial Source Complex (ISC) model (Lorber et al. 2000; Bhanarkar et al. 2005a, b; Sax and Isakov 2003). There is dearth of data on air pollution from SAW and DI pipe manufacturing operations, and published literature on this aspect is extremely rare in India and elsewhere. The present study was therefore attempted to assess the emissions of SO2 , NOx , and PM from various operations in an integrated pipe manufacturing plant which

Environ Monit Assess (2010) 169:677–685

would generate important information on industrial air pollution vis-à-vis DI and SAW pipe manufacturing.

Materials and methods The industry The selected industrial unit is an integrated pipe unit in the state of Gujarat in India and is regarded as one of the largest indigenous producer and exporter of steel pipes. It manufactures SAW pipes used for transportation of oil and gas by using U–O–E technology (consisting of U-ing press, O-ing press, hydrostatic testing, and expanding machine). It also manufactures large-diameter submerged arc pipes, spiral pipes, and bends for oil and gas transportation sector, carbon alloy, and stainless steel seamless pipes and tubes for industrial applications and DI pipes for water and sewage transportation. This plant has three manufacturing facilities, DI Spun Pipes, which also has a blast furnace for pig iron production, longitudinally submerged arc welded (LSAW) pipes using J–C–O–E (J-ing, C-ing, O-ing, and expanding) technology, and helical spirally welded pipes. The premises also have a captive power production (CPP) facility for meeting the power requirement of the plant. The annual pipe production of this facility during 2006 was 223,297 Mt with monthly average production of 18,606 Mt, and in the same year this facility produced 103,596, 31,283, and 88,416 Mt of DI, spiral, and LSAW pipes, respectively. Existing stationary sources and pollution control A preliminary survey was conducted in the integrated pipe manufacturing unit for familiarization with the processing units, collection of secondary data and information, and planning for stationary source monitoring. Though various types of pipe manufacturing operations are present, not all the operations are involved in emission of air pollutants. The summary of various operations carried out in the industry is presented in Table 1.


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Table 1 Summary of various operations with a stationary air pollution source at the integrated pipe manufacturing plant Operation/process

Summary

Dedusting Boiler

Dry dedusting system to recover pulverized coal dust for recycling in blast furnace Hot gas from blast furnace (BF) not burnt in the stoves is sent to the boiler and is used to generate steam, running two turbo blowers (each of 28,800-Nm3 /h capacity) that generate compressed air known as “cold blast” that comes to the stoves to get converted to hot blast which is used for air blast requirement of the blast furnace Dirty gases from BF have considerable energy value and so burnt as a fuel in the “hot blast stoves” the heat of which is used to preheat “cold blast” from blowers entering the blast furnace and convert it to “hot blast.” It consists of three internal combustion chambers with ceramic burners, fired by blast furnace gas Ductile iron is made by treating liquid iron of suitable composition with magnesium (Mg) before casting which promotes precipitation of graphite in the form of discrete nodules instead of interconnected flakes. The nodular iron so formed has high ductility, allowing castings to be used in critical applications. Ductile iron to have strength characteristics similar to mild steel including excellent tensile strength, impact resistance, and beam strength. Also, pipes made of DI withstand severe crushing loads, is corrosion resistant, is easy to install, and is almost maintenance free Zinc oxide spraying on ductile iron pipes Bitumen drying operation in hot ovens after its spraying on ductile iron pipes Used in ductile iron spun pipe (DISP) manufacturing Heat treatment of ductile iron pipes to increase strength and hardness in horizontal continuous annealing furnace using BF gas/LPG as fuel Power generation by 3,240-kVA diesel generators Power generation by 1,180-kVA diesel generators

Stove

Mg converter

Zinc coating Bitumen drying oven Barrel grinding and dusting Annealing 3,240-kVA DG 1,180-kVA DG

One of the major air polluting units is the blast furnace (BF), consisting of the furnace, boiler, stoves, and dedusting unit, for manufacturing of pig iron which is used in ductile iron spun pipe (DISP) unit. In DISP unit, various operations like zinc coating, bitumen drying, and barrel grinding are responsible for generation of air pollutants, especially particulates while CPP facility is also polluting in nature where the diesel generators emit gases and particulates. Air pollution is negligible from SAW pipe manufacturing and helical spirally welded pipe manufacturing as these operations mainly involve only welding, a weak source of air pollution. After commissioning, the industry had installed various air pollution control devices in various units for particulate emission control under the directive of the Pollution Control Board (PCB), as particulate matter was the major air pollutant of concern from these operations. Details of fuel, physical characteristics of stacks, and air pollution control devices attached to the stacks are summarized in Table 2. The State Pollution Control Board has prescribed emission norms for

particulates, SO2 , and NOx for different process units of the industry (Table 3). Stack emission monitoring Stack emission monitoring exercise was divided into two phases during the study period. During phase 1 in February 2007, apart from reconnaissance survey and familiarization with the plant processes, primary monitoring of stack gas emissions was undertaken in various units. During phase 2 in December 2007, stack emission monitoring was undertaken in the remaining polluting units which were out of operation during phase 1. Stack emission monitoring was not taken up in non-polluting units. A stack gas sampler (Model VSS-1, Vayubodhan Upakaran Ltd., New Delhi, India) was used to quantify parameters like stack gas temperature and differential stack gas pressure (Indian Standard Institution 1986c, IS: 11255 (Part 3) 1985 Method). Subsequently, stack gas velocity and isokinetic stack gas flow rate were calculated for sampling of particulate matter (Indian Standard Institution 1986a, IS: 11255 (Part

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Table 2 Physical characteristics and other details of major stacks at the integrated pipe manufacturing industry Stack

Stack attached to

Fuel used

Stack height (m)

Stack diameter (m)

Attached air pollution control device

Dedusting

Raw material storage and handling Boiler Boiler Stove Mg converter Bitumen drying oven Bitumen drying oven Barrel grinding

NA

33.4

1.484

Bag filter

LDO/BF gas LDO/BF gas BF gas NA LPG

45.0 45.0 50.0 20.0 32.8

1.38 1.38 2.25 0.488 1.375

NA NA NA Bag filter NA

LPG

32.8

1.375

NA

NA

16.5

0.584

Boiler I Boiler II Stove stack Mg converter Bitumen drying oven Bitumen drying oven Barrel grinding and dusting Barrel grinding and dusting Zinc coating

Barrel grinding

NA

16.5

0.584

Zinc coating

NA

16.5

0.584

Zinc coating

Zinc coating

NA

16.5

0.584

Zinc coating

Zinc coating

NA

16.5

0.584

Annealing furnace Annealing furnace 3,240-kVA DG 1,180-kVA DG

Annealing furnace Annealing furnace DG set DG set

BF gas/LPG

32.8

1.375

Cyclone separator and bag filter Cyclone separator and bag filter Cyclone separator and bag filter Cyclone separator and bag filter Cyclone separator and bag filter NA

BF gas/LPG

32.8

1.375

NA

LDO LDO

50.0 45.0

1.484 0.98

NA NA

LDO light diesel oil, NA not available

1) 1985 Method). Sampling of stack gas for particulates were carried out isokinetically for a suitable period to collect at least the minimum volume of stack gas specified in the relevant protocol under normal plant operational conditions. Particulate matter collected on glass fibre thimbles was subsequently estimated by gravimetric analysis and expressed as weight per volume air. SO2 concentration (w vol−1 air) was determined by absorbing stack gas in specific liquid media and subsequent titrimetric analysis of absorbed SO2 (Indian Standard Institution 1986b, IS: 11255 (Part 2) 1985 Method). A direct reading flue gas analyzer (Model Testo 350) was used for monitoring NOx (vol vol−1 air). Subsequently, emission load (kg h−1 ) of particulates and gases was determined after multiplying stack gas flow rate (Nm3 h−1 ) by concentration of specific gases/particulates (kg Nm−3 ).

Table 3 PCB-prescribed stack gas concentrations standards for PM, SO2 , and NOx in monitored units Process unit

Permissible concentration (mg/Nm3 )a PM SO2 NOx

Dedusting outlet Boiler Stove stack Mg converter Zinc coating Barrel grinding and dusting Bitumen drying oven Barrel grinding and dusting Annealing furnace 3,240-kVA DG set 1,180-kVA DG set

150 150 150 150 20b 150

– 40 40 40 – –

– 25 25 25 – –

150 150

100 ppm –

– –

150 150 150

100 ppm 100 ppm 100 ppm

50 ppm 50 ppm 50 ppm

a Permissible concentrations are in milligram per normal cubic meter unless specified otherwise b Zinc only


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Air quality modeling

N

USEPA-developed Gaussian plume dispersionbased Industrial Source Complex (ISC 3) model, which can be used for single or multiple source emissions, was used for the prediction of 24-hourly average ground-level concentration (GLC) influenced by stack emissions from the plant. The details of the ISC 3 model are documented elsewhere (USEPA 1995). So far as the dispersion of pollutants from a stack is concerned, temporal wind distribution is the most important factor for concentration buildup of air pollutants in the surrounding air basin. To examine the prevailing micrometeorological condition in the study area, wind speed and direction during winter were recorded at the site by an electronic weather station, and a wind rose was prepared from the collected data (Fig. 1). The atmospheric stability classes (Pasquill-Turner) have been computed us-

Fig. 1 Wind rose diagram of the study area for winter

Table 4 Flue gas characteristics in various units in an integrated pipe manufacturing plant Unit Unit

Stack gas temp. (K)

Gas velocity (m/s)

Dedusting outlet Boiler 1 Boiler 2 Annealing 1 Annealing 2 DG set (3,240 kVA) DG set (1,180 kVA) Zinc coating 1 Zinc coating 2 Zinc coating 3 Stove stack Mg converter Barrel grinding 1 Barrel grinding 2 Bitumen drying 1 Bitumen drying 2

318

7.9

433 452 503 473 498

PM conc. (mg/Nm3 )

PM emission (kg/h)

SO2 conc. (mg/Nm3 )

SO2 emission (kg/h)

NOx conc. (mg/Nm3 )

NOx emission (kg/h)

90.0

4.44

–

–

–

–

4.6 5.1 2.8 2.7 4.6

29.4 42.2 40.1 45.9 175.7

0.73 1.83 0.59 1.09 4.99

6.4 (2.5)a 14.4 (5.5)a 7.3 (2.8) 3.7 (1.4) 32 (12.2)

0.1 0.62 0.1 0.09 0.5

5.6 (3) 12.15 (6.5) 20.7 (11) – 875 (465)

0.03 0.53 0.05 – 3.99

614

5.0

131.3

3.81

237.4 (90.7)

6.89

1,328.49 (706.1)

38.5

313 319 313 554 316 303

10.6 11.3 9.8 14.2 13.0 13.0

26.1 38.8 29.1 1.1 10.8 132.1

0.27 0.47 0.30 0.45 0.09 1.82

– – – 30.7 (11.7) 2.7 (1.0) –

– – – 12.1 0.02 –

– – – 10.13 (5.4) 33.9 (18) –

– – – 4.0 0.08 –

319

13.5

100.3

1.46

–

–

–

–

303

5.1

15.8

0.46

32.9 (12.6)

0.96

–

–

308

5.6

17.3

0.56

13.0 (4.9)

0.42

–

–

a Values in parenthesis are in parts per million – Not monitored, as non-polluting

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Fig. 2 Isopleths of predicted SPM concentrations (μg/m3 )

10000

8000

N

Distance along North-South direction (m)

6000

4000

2000

0

-2000

-4000

-6000 Unit: µg/m 3 Maximum conc. 13 µg/m at x = - 400 m, y = 0 m

-8000

-10000 -10000 -8000 -6000 -4000 -2000

0

2000

4000

6000

3

8000 10000

Distance along East-West direction (m)

Fig. 3 Isopleths of predicted SO2 concentrations (μg/m3 )

10000

8000

N

Distance along north-south direction (m)

6000

4000

2000

0

-2000

-4000

-6000

Unit: µg/m 3 Maximum conc. 2.7 µg/m 3 at x = - 800 m, y = 0 m

-8000

-10000 -10000

-8000

-6000

-4000

-2000

0

2000

4000


6000

8000

10000


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ing Turner’s classification (Hanna et al. 1982). By using source characteristics, emission rates, wind speed and direction, ambient temperature, mixing height, and stability classes as input parameters, dispersion modeling was carried out for the prediction of GLCs of selected pollutants within 10km radial distance around the plant under study. Prediction of GLCs was carried out for winter as air pollutant dispersal is lesser in this season. Further, isopleths of 24-hourly averaged GLCs for SPM, SO2 , and NOx were plotted.

Results and discussion Stack gas characteristics and emissions Stack gas temperature varied from 303 to 614 K, with the highest value observed in the stack attached to 1,180-kVA (1 KW = 1.25 kVA) diesel generator whereas stack gas velocity ranged from 2.77 to 13.5 m s−1 , with the maximum recorded from the stack attached to the barrel grinding

Fig. 4 Isopleths of predicted NOx concentrations (μg/m3 )

operation (Table 4). Stove stack also had high exit gas temperature due to the heat carried along by BF gas. Stack gas temperature in operations like dedusting, barrel grinding, zinc coating, and Mg converter almost was at par with the ambient temperature as no combustion was involved. Substantial variation in stack gas parameters like temperature, exit gas velocity, and flow rate was observed due to difference in process and various operational parameters, stack ID fans’ capacity, and diameter of the stacks. In dedusting operation, particulate concentration was fairly high (90 mg Nm−3 ) while the emission load was second highest among all the units. Since BF waste gas is used as the fuel in stove and the boilers, particulate, SO2 , and NOx emission loads were low. Similarly, particulate emission load was low in units like annealing, zinc oxide coating, and Mg converter as these operations do not generate much particulate. On the contrary, barrel grinding operation resulted in one of the highest concentration of particulates in stack gas (132 mg Nm−3 ), since it involved pipes being subjected to grinding to

10000

8000

N

Distance along North-South direction (m)

6000

4000

2000

0

-2000

-4000

-6000 Unit: µg/m 3 Maximum conc. 18.5 µg/m 3 at x = -1000 m, y = -200 m

-8000

-10000 -10000 -8000 -6000 -4000 -2000

0

2000

4000


6000

8000 10000

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finish the outer surface. Particulate concentration in the exit gas from 3,240-kVA diesel generator was the highest among all, leading to the largest particulate emission load. Particulate emission from diesel engines is critical, since emissions of diesel particulate matter (DPM) from diesel engines are known to pose significant health threat due to their suspected carcinogenicity, especially the carbonaceous fractions consisting of organic and elemental carbon. Its emissions depend on many operating parameters, such as engine load, engine design parameters, fuel sulfur content, fuel usage rate etc. (Liu et al. 2005). SO2 emissions were generally low, with the higher emissions observed in the DG sets, where SO2 was generated during combustion of sulfur in the fuel. Similarly, NOx emissions were low except in the 1,180- and 3,240-kVA DG sets. Emissions of PM, SO2 , and NOx in the exit gas of all the units were found to be within the limit prescribed by the PCB, except in 1,180- and 3,240-kVA DG sets with regard to PM and NOx (Table 4). SO2 and NOx were not monitored in dedusting, zinc coating, and barrel grinding units as these did not involve any combustion of fossil fuel. Prediction of impact on air quality The maximum predicted concentrations of air pollutants along with their point of occurrence were obtained through air quality modeling by ISC 3 model. The model results outlined below mainly focused on the maximum concentration, since these were most significant as far as the regulatory standards are concerned. According to the currently effective National Ambient Air Quality Standards in India (CPCB 2001), the maximum allowable 24-h concentrations for PM, SO2 , and NOx are 500, 120, and 120 μg/m3 , respectively, for industrial area and 200, 80, and 80 μg/m3 , respectively, for a residential/mixed area. The model predictions indicated that the maximum concentration of PM, SO2 , and NOx would be to the tune of 13, 3, and 18 μg/m3 , respectively, which are lower than the corresponding regulatory standards, and these concentrations would occur primarily in the western direction. The predicted GLCs for PM, SO2 , and NOx in the form of isopleths are presented in Figs. 2, 3, and 4. Maximum


impact of pollutants was observed at 4–5-km distance in the southwest direction as northeast is the predominant wind direction observed in the area.

Summary and conclusion The study was conducted to quantify emissions of PM, SO2 , and NOx from the stacks of various air-polluting operations in an integrated pipe manufacturing plant in India, and the impact of the emissions on ambient air quality was also assessed using an air quality model ISC 3. Stack monitoring results indicated that particulate emission load was low in units like annealing, zinc oxide coating, and Mg converters as these operations do not generate much particulate, while barrel grinding operation emitted much higher mass of particulates. Particulate concentration in the stack gas from 3,240-kVA diesel generator was the highest among all, leading to the largest particulate emission load also. SO2 and NOx emissions were generally low while its higher emissions were observed in the DG sets, where SO2 was generated evidently during combustion of sulfur in the fuel. Concentration of PM, SO2 , and NOx in the stack gas of all the units were found to be within the limit prescribed by PCB, except in 1,180- and 3,240-kVA DG sets with regard to PM and NOx . The model-predicted air quality showed that the maximum concentration of SPM, SO2 , and NOx was lower than the corresponding regulatory standards. Maximum impact of pollutants was observed at 4–5-km distance in the southwest direction which is the most predominant wind direction in the study area. Though the impact of plant emissions on air quality was found to be small, considering the increasing demand and production of SAW and DI pipes for energy and transportation in international as well as domestic sectors, it is imperative that these industries ensure a clean environment by installing, operating, maintaining, and modernizing pollution control measures and devices, e.g., installation of higher-efficiency teflon filter bags in the bag houses and high-efficiency electrostatic precipitators for particulate control whereas options like upgrade of fuel quality or installation of scrubbers for controlling SO2 and NOx emissions


could be considered. The industry has installed air pollution control devices for particulate control in various operations but is yet to provide a proper setup for sampling at the inlets of these devices which makes it difficult to assess their efficiency, derive their optimum performance, and suggest corrective measures that may be required.

References Bhanarkar, A. D., Gajghate, D. G. & Hasan, M. Z. (2003). Assessment of air pollution from small scale industry. Environmental Monitoring and Assessment, 80, 125– 133. Bhanarkar, A. D., Goyal, S. K., Sivacoumar, R., & Chalapati Rao, C. V. (2005a). Assessment of contribution of SO2 and NO2 from different sources in Jamshedpur region, India. Atmospheric Environment, 39, 7745–7760. Bhanarkar, A. D., Chalapati Rao, C. V., & Pandit, V. I. (2005b). Air pollution modeling for power plant site selection. International Journal of Environmental Studies, 62, 527–534. Bhanarkar, A. D., Gavane, A. G., Tajne, D. S., Tamhane, S. M., & Nema, P. (2008). Composition and size distribution of particules emissions from a coal-fired power plant in India. Fuel, 87, 2095–2101. Cora, M. G., & Hung, Y. T. (2003). Air dispersion modeling: A tool for environmental evaluation and improvement. Environmental Quality Management, 12, 75–86. CPCB (2001). NAQM standards. New Delhi: Central Pollution Control Board. Delfino, R. J., Zeiger, R. S., Seltzer, J. M., & Street, D. H. (1998). Symptoms in pediatric asthmatics and air pollution: Differences in effects by symptom severity, anti-inflammatory medication use and particulate averaging time. Environmental Health Perspectives, 106, 751–761. Douglas, I., Hodgson, R., & Lawson, N. (2002). Industry, environment and health through 200 years in Manchester. Ecological Economics, 41, 235–255. Hanna, S. R., Briggs, G. A., & Hosker, R. P. Jr. (1982). Handbook of atmospheric diffusion. Washington, DC: Technical Information Center, US Department of Energy, DOE/TIC-11223. Indian Pipe Industry Report (2008). Credit analysis & research limited. www.researchandmarkets.com/reports/ 605557. Indian Standard Institution (1986a). Indian standard methods for measurement of emissions from stationary sources (Particulate matter, IS-11255 (Part 1), 1985). New Delhi: Indian Standards Institution. Indian Standard Institution (1986b). Indian standard methods for measurement of emissions from stationary

685 sources (Sulphur Dioxide, IS-11255 (Part 2), 1985). New Delhi: Indian Standards Institution. Indian Standard Institution (1986c). Indian standard methods for measurement of emissions from stationary sources (Flow rate, IS-11255 (Part 3), 1985). New Delhi: Indian Standards Institution. Kumar, A., Bellam, N. K., & Sud, A. (1999). Performance of an industrial source complex model: Predicting long-term concentrations in an urban area. Environmental Progress, 18, 93–100. Liu, Z., Lu, M., Eileen Birch, M., Keener, T. C., Khang, S. J., & Liang, F. (2005). Variations of the particulate carbon distribution from a nonroad diesel generator. Environmental Science & Technology, 39(20), 7840–7844. Lorber, M., Eschenroeder, A., & Robinson, R. (2000). Testing the US EPA’s ISCST—Version 3 Model on dioxins: A comparison of predicted and observed air and soil concentration. Atmospheric Environment, 34, 3995–4010. Mirasgedis, S., Hontou, V., Georgopoulou, E., Sarafidis, Y., Gakis, N., Lalas, D. P., et al. (2008). Environmental damage costs from airborne pollution of industrial activities in the greater Athens, Greece area and the resulting benefits from the introduction of BAT. Environmental Impact Assess Review, 28(1), 39–56. Norris, G., Young Pong, S. N., Koenig, J. Q., Larson, T. V., Sheppard, L., & Stout, J. W. (1999). An association between fine particles and asthma emergency department visits for children in Seattle. Environmental Health Perspectives, 107, 489–493. Sax, T., & Isakov, V. (2003). A case study for assessing uncertainty in local-scale regulatory air quality modelling applications. Atmospheric Environment, 37, 3481–3489. Taib, M. R. (1995). Air pollution emissions from a steel mill plant using electric arc furnace. In Proceedings of the eleventh symposium of malaysia chemical engineers. Kuala Trengganu, Malaysia, 18–19 June. USEPA (1987). Iron and steel industry particulate emissions: Source category report. EPN600/S7-86/036 Feb. 1987. USEPA (1995). User’s guide for the industrial source complex (ISC3) dispersion models, EPA 454/B-95-003a. Research Triangle Park: US Environmental Protection Agency. Wang, T., Anderson, D. R., Thompson, D., Clench, M., & Fisher, R. (2003). Studies into the formation of dioxins in the sintering process used in the iron and steel industry. 1. Characterization of isomer profiles in particulate and gaseous emissions. Chemosphere, 51, 585–594. Yu, O., Sheppard, L., Lumley, T., Koenig, J. Q. & Shapiro, G. G. (2000). Effects of ambient air pollution on symptoms of asthma in Seattle area children enrolled in the CAMP study. Environmental Health Perspectives, 108, 1209–1214.