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Estimation of PM2.5 Emissions and Source Apportionment Using Receptor and Dispersion Models

Authors: Swetha Priya Darshini Thammadi, Sateesh Kumar Pisini, Sanjay Kumar Shukla

Abstract:

Source apportionment using Dispersion model depends primarily on the quality of Emission Inventory. In the present study, a CMB receptor model has been used to identify the sources of PM2.5, while the AERMOD dispersion model has been used to account for missing sources of PM2.5 in the Emission Inventory. A statistical approach has been developed to quantify the missing sources not considered in the Emission Inventory. The inventory of each grid was improved by adjusting emissions based on road lengths and deficit in measured and modelled concentrations. The results showed that in CMB analyses, fugitive sources - soil and road dust - contribute significantly to ambient PM2.5 pollution. As a result, AERMOD significantly underestimated the ambient air concentration at most locations. The revised Emission Inventory showed a significant improvement in AERMOD performance which is evident through statistical tests.

Keywords: CMB, GIS, AERMOD, PM2.5, fugitive, emission inventory.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1340436

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[1] Abdul-Wahab, S. A. (2003). SO2 dispersion and monthly evaluation of the industrial source complex short-term (ISCST3) model at Mina Al-Fahal Refinery, Sultanate of Oman. Environmental Management. 31: 276–291.
[2] American Environmental Protection Agency Regulatory Model (AERMOD) Lakes Environmental, ISC-AERMOD View, Interface for the U.S. EPA ISC and AERMOD models 2006-2007.
[3] Behera, S. N., Sharma, M., Dikshit, O., Shukla, S. P. (2011). Development of GIS-aided Emission Inventory of Air Pollutants for an Urban Environment, Advanced Air Pollution, Dr. Farhad Nejadkoorki (Ed.), ISBN: 978-953-307-511-2, InTech, Available from: http://www.intechopen.com/books/advanced-airpollution/development-of-gis-aided-emission-inventory-of-air-pollutants-for-an-urban-environment.
[4] Bhaskar, V. S., & Sharma, M. (2008) Assessment of fugitive road dust emissions in Kanpur, India: A note. Transportation Research. Part D. 13: 400–403.
[5] Brazell, A. J., McCabe, G. J., Verville, H. J. (1993) Solar radiation simulated by general circulation models for the southwestern United States. Climate Research. 2: 177–181.
[6] Callén, M. S., de la Cruz, M. T., López, J. M., Navarro, M. V., Mastral, A.M. (2009) Comparison of receptor models for source apportionment of the PM10 in Zaragoza (Spain). Chemosphere. 76: 1120–1129.
[7] Cartwright, H. M., Harris, S. P. (1993) Analysis of the distribution of airborne pollution using GAs. Atmospheric Environment. 27A: 1783–1791.
[8] Census of India, 2001 Series – 3 PART XII- A & B District Census Handbook, Solan Village and Town Directory, Himachal Pradesh.
[9] Chemical Mass Balance 8.2; US Environmental Protection Agency Office of Air Quality Planning & Standards Emissions, Monitoring & Analysis Division Air Quality Modelling Group, December 2004 http://www.epa.gov/scram001/receptor_cmb.htm as visited on 15.12.2012.
[10] Chow, J. C., Watson, J. G., Lowenthal, D. H., Solomon, P. A., Magliano, K. L., Ziman, S. D., and Richards, L. W. (1993). PM10 and PM2.5 Compositions in California’s San Joaquin Valley. Aerosol Science and Technology. 18: 105–128.
[11] CPCB 2011a (Central Pollution Control Board), Ministry of Environment & Forests (MoEF), Annual Report 2011-12, 'Parivesh Bhawan', East Arjun Nagar, Shahdara, Delhi – 110032 Website: cpcb.nic.in.
[12] CPCB 2011b (Central Pollution Control Board) National Summary Report, Air quality monitoring, emission inventory and source apportionment study for Indian cities, February 2011'Parivesh Bhawan', East Arjun Nagar, Shahdara, Delhi – 110032 Website: http://cpcb.nic.in/Source_Apportionment_Studies.php as visited on 15.12.2012.
[13] Dubey, N., and Pervez, S. (2008). Investigation of Variation in Ambient PM10 Levels within an Urban-Industrial Environment. Aerosol Air Quality Research. Volume 8: 54–64.
[14] Dutot, A.L., Rynkiewicz, J., Steiner, F.E., Rude, J. (2007) A 24-h forecast of ozone peaks and exceedance levels using neural classifiers and weather predictions. Environmental Modeling and Software. 22: 1261–1269.
[15] EPA-CMB8.2 user’s manual, US. Environmental Protection Agency, Office of Air Quality Planning & Standards Emissions, Monitoring & Analysis Division, Air Quality Modelling Group December 2004.
[16] Karar, K., and Gupta, A. K. (2006). Seasonal Variations and Chemical Characterization of Ambient PM10 at Residential and Industrial Sites of an Urban Region of Kolkata (Calcutta), India. Atmospheric Research. 81: 36–53.
[17] 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.
[18] Kumar, A. V., Patil R. S., Nambi, K. S. V. (2004) A composite receptor and dispersion model approach for estimation of effective emission factors for vehicles. Atmospheric Environment. 38: 7065–7072.
[19] Laupsa, H., Denby, B., Larssen, S., Schaug, J. (2007) Air4EU case study report D7.1.5: Source apportionment of particulate matter using dispersion and receptor modelling. URL: http://www.air4eu.nl/reports_products.htm.
[20] Levy, J. I., Hammittf, J. K., and Spengler, J. D. (2000). Estimating the Mortality Impacts of Particulate Matter: What Can be Learned from Between-Study Variability? Environmental Health Perspect. 108: 109–117.
[21] Loughlin, D. H., Ranjithan, S. R., Baugh Jr., J. W., Brill Jr., E. D. (2000) Application of GAs for the design of ozone control strategies. J. Air Waste Management Association 50: 1050–1063.
[22] Liu, H. Y., Bartonova, A., Schindler, M., Sharma, M., Behera, S.N., Katiyar, K., Dikshit, O. (2013). Respiratory Disease in Relation to Outdoor Air Pollution in Kanpur, India. Archives of Environmental & Occupational Health. 68: 204-217.
[23] Pallavi Pant, Harrison Roy M. (2012) Critical review of receptor modelling for particulate matter: A case study of India Atmospheric Environment. 49: 1-12.
[24] Qin, R., and Oduyemi, K. (2003) Atmospheric aerosol source identification and estimates of source contributions to air pollution in Dundee, UK. Atmospheric Environment. 37: 1799–1809.
[25] Schwartz, J., Dockery, D.W., Neas, L.M. (1996) Is daily mortality associated specifically with fine particles? Journal of Air and Waste Management Association. 46: 927–939.
[26] Sharma, M., Maloo, S. (2005) Assessment of ambient air PM10 and PM2.5 and characterization of PM10 in the city of Kanpur, India Atmospheric Environment. 39: 6015–6026.
[27] Sharma, M., Narendra Kumar V, Katiyar, S. K., Sharma R, Shukla, B. P., Sengupta, B. (2004) Cohort-Based Acute Health Effect Study of PM10 and PM2.5 Pollution in the City of Kanpur, India, Archives of Environmental Health: An International Journal. 59: 348 – 358.
[28] Singh, D., Shukla S.P., Sharma, M., Behera, S. N., Mohan, D., Singh, N.B., Pandey, G. (2014) GIS-Based On-Road Vehicular Emission Inventory for Lucknow, India Journal of Hazardous, Toxic, and Radioactive Waste © ASCE, ISSN 2153-5493/A4014006(10).
[29] Shukla, S. P., and Sharma, M. (2008). Source Appointment of Atmospheric PM10 in Kanpur, India. Environmental Engineering and Science. 25: 849–862.
[30] Sivacoumar, R., Bhanarkar, A. D., Goyal, S. K., Gadkari, S. K., Aggarwal, A. L. (2001) Airpollution modeling for an industrial complex and model performance evaluation Environmental Pollution. 111: 471–477.
[31] Swetha PriyaDarshini, Mukesh Sharma, Dhirendra Singh (2016), Synergy of receptor and dispersion modelling: Quantification of PM10 emissions from road and soil dust not included in the inventory. Atmospheric Pollution Research. 7: 403 – 411.
[32] USEPA (U.S. Environmental Protection Agency) “Guideline on Speciated Particulate Monitoring” Office of Air Quality Planning and Standards (MD-14), Research Triangle Park, NC 27711, August 1998.
[33] USEPA (U.S. Environmental Protection Agency) 2001, Paved road dust emissions, AP 42, Emission factors guide series, Office of Research and Planning, USEPA Technology Transfer Network, Office of Air quality Planning, Washington, DC.
[34] Vallius, M. J., Ruuskanen, J., Mirme, A., and Pekkanen, J. (2000) Concentrations and Estimated Soot Content of PM1, PM2.5, and PM10 in a Subarctic Urban Atmosphere. Environmental Science Technology. 34: 1919–1925.