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Determination of Dispersion and Zoning of Air Pollutants in Tehran Using AERMOD Model: A Case Study of District 2 of Tehran, Iran

Document Type : Original Article

Authors

1 Student in Environmental Management, North Tehran Branch, Islamic Azad University, Tehran, Iran

2 Department of Environment, North Tehran Branch, Islamic Azad University, Tehran, Iran

Abstract

Background: Cities, as population centers, face increasingly diverse environmental problems. Hence, there is an urgent need for a healthy environment by eliminating the emission of various life-threatening air pollutants with different origins. The present study aimed to determine the air pollution zones using the AERMOD model and provide a strategic management plan to reduce air pollution in District 2 of Tehran, Iran.
Methods: In this study, the air pollutant dispersion was evaluated by the AERMOD model exploiting spatial analysis (interpolation) and field measurements. The samples were collected from 32 places in the North, South, Central, East and West of District 2 of Tehran. Air quality indices, including ozone, nitrogen dioxide, sulfur dioxide, and carbon monoxide were analyzed in the experiments. Zoning and mapping of dispersion maps and spatial analysis were performed by ArcGIS.10 software using inverse distance weighted interpolation methods in the study area.
Results: According to the results, the highest concentrations of sulfur dioxide, nitrogen dioxide, ozone, and carbon monoxide pollutants were related to stations 28, 26, 15 and 15 with values of 10.9, 54.6, 32.8, and 31.9 ppb, corresponding to the southern, eastern, southern, and southwestern regions in Sharif, Punak, and Kuy-e Nasr neighborhoods, respectively.
Conclusion:  Based on the statistical tests of correlation coefficient, normalized mean error, and normalized mean bias, all the calculated results confirmed the accuracy of constructed model and that the modeling would not have sufficient accuracy and performance without the implementation of AERMAP

Keywords

References
1.Kashipazan Qomi M, Shirgir B. Short-term prediction of Particulate Matter related to traffic flow using Support Vector Machine (Case Study: Tehran City). IQBQ. 2017; 18 (4): 201-10. (In Persian).
2.Lesani S, Edalatju A. The analysis of institution model of the fiftieth principle of constitutional law under the protection of environmental supporter Governmental and Non- Governmental Organizations. J. Environ. Sci. Tech. 2017; 19 (3): 217-27. (In Persian).
3.Yusefi Golboteh R, Sahrayi FR, Mohammadi M, Houshmand S, Mohammadi M. Measuring vehicle exhaust emissions from Peugeot 206, Samand and EL Samand in Mashhad. J. Environ. Sci. Tech. 2016; 18 (2): 63-76. (In Persian).
4.Firoozi M, Mohammadi Deh Cheshmeh M, Saeedi J. Evaluation of environmental instability indicators with emphasis on water, soil and noise pollutions using Analytical Hierarchy Process (AHP) in Ahvaz metropolis. J. Environ. Sci. Tech. 2017; 19 (3): 67-81. (In Persian).
5.Leroy C, Maro D, Hébert D, Solier L, Rozet M, Le Cavelier S, et al. A study of the atmospheric dispersion of a high release of krypton-85 above a complex coastal terrain, comparison with the predictions of Gaussian models (Briggs, Doury, and ADMS4). J. Environ. Radiat. 2010; 101 (11): 937-44.
6.Ruckerl R, Schneider A, Breitner S, Cyrys J, Peters A. Health effects of particulate air pollution: a review of epidemiological evidence, Inhal. Toxicol. 2011; 23: 555-92.
7.Kanada M, Dong L, Fujita T, Fujii M, Inoue T, Hirano Y, et al. Regional disparity and cost-effective SO2 pollution control in China: A case study in 5 Mega-cities. Energy Policy. 2013; 61: 1322-31.     
8.Rezaeian Ghiye Bashi A, Poor Ezzat AA, Hafeznia MR, Mohammadi H, Zolfagharzade MM. Prediction of the Interaction between Climate Change and Air Pollution in Tehran. 4th International Conference on Environmental Planning and Management. Tehran. Faculty of Environment - University of Tehran, 2017.  (In Persian).
9.Denby B, Horalek J, Walker SE, Eben K, Fiala J. Interpolation and assimilation methods for European scale air quality assessment and mapping. Part I: Review and recommendations. ETC/ACC Technical Paper; 2005. p.7.
10.Lee RF, Perry SG, Cimorelli AJ, Paine RJ, Venkatram A, Weil JC, et al. AERMOD: The developmental evaluation. (Gryning and Schiermeier, Eds.) Air Pollution and Its Application XI, Plenum Press, NY. 1996; 623-30.
11.Mohan M, Bhati S, Sreenivas A, Marrapu P. Performance evaluation of AERMOD and ADMS-urban for total suspended particulate matter concentrations in megacity Delhi. Aerosol Air Qual Res. 2011; 11 (7): 883-94.
12.Seangkiatiyuth K, Surapipith V, Tantrakarnapa K, W.Lothongkuma A. Application of the AERMOD modeling system for environmental impact assessment of NO2 emissions from a cement complex. J Environ Sci. 2011; 23 (6); 931-40.
13.Mokhtar MM, Hassim MH, and Taib RM. Health risk assessment of emissions from a coal-fired power plant using AERMOD modelling. Process Saf Environ Prot. 2014; 92 (5): 476-85.
14.Gibson MD, Soumita K, Satish M. Dispersion model evaluation of PM2.5, NOx and SO2 from point and major line sources in Nova Scotia, Canada using AERMOD Gaussian plume air dispersion model. Atmospheric Pollution Research. 2013; 4 (2):157-67.
15.Kesarkar AP, Dalvi M, Kaginalkar A,  Ojha A. Coupling of the Weather Research and Forecasting Model with AERMOD for pollutant dispersion modeling. A case study for PM10 dispersion over Pune, India. Journal of Atmospheric Environment. 2007; 41: 1976-88.
16.Zhang Q, Li XX, Tian Wl, Fu AY, Du WF, Wang C. GIS-based emission inventories of urban scale: A case study of Hangzhou, China. Journal of Atmospheric Environment. 2008; 42: 5150-65.
17.Mazur M, Mintz R, Lapalme M, Wiens B. Ambient air total gaseous mercury concentrations in the vicinity of coal-fired power plants in Alberta, Canada. Journal of Science of the Total Environment. 2009; 408: 373-81.
18.Zou B, Zhan FB, Wilson JG, Zeng Y. Performance of AERMOD at different time scales. Simulation Modeling Practice and Theory. 2010; 18: 612-23.
19.Anselin L, Le Gallo J. Interpolation of air quality measures in hedonic house price models: spatial aspects. Spatial Economic Analysis. 2006; 1(1):31-52.
20.Davis BM. Uses and abuses of cross –validation in geostatistics, Math Geol. 1987; 29:241-48.
21.Hiroshi  K,  Türkan H,  Vucinic S, Naqvi Sh,  Bedair R,  Rezaee R et al. Carbon monoxide poisoning Toxicol Rep. 2020; 7: 169-73.
22.Hagler GS, Thoma ED, Baldauf RW. High-resolution mobile monitoring of carbon monoxide and ultrafine particle concentrations in a near-road environment. J Air Waste Manag Assoc. 2010; 60 (3): 328-36.
23.Zhang K, Batterman S. Near-road air pollutant concentrations of CO and PM2.5: A comparison of MOBILE6.2/CALINE4 and generalized additive models. Atmospheric Environment. 2010; 44: 1740- 48.
24.Ashrafi Kh, Shafipour M, Soleimian M, Momeni MR. Determining and modeling the dispersion of volatile organic compounds evaporated from storage tanks located in Assaluyeh, Iran. Journal of Environmental Studies. 2012; 38(3): 47-60.
25.Chen Y, Wild O, Ryan E, Kumar Sahu S, Lowe D, Archer-Nicholls S, et al. Mitigation of PM2.5 and ozone pollution in Delhi: a sensitivity study during the pre-monsoon period. Atmos. Chem. Phys. 2020; 20: 499-514.
26.Mohseni Nameghi HA, case study of integrated modelling of traffic, vehicular emissions, and air pollutant concentrations for Huron Church Road, Windsor. A Dissertation Submitted to the Faculty of Graduate Studies through Civil and Environmental Engineering in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy at the University of Windsor Windsor, Ontario, Canada. 2013.
27.Mostofie N., Fataie E., HezhabrPour Gh, Kheikhah Zarkesh MM, Assessment centers and distribution centers dust (case study:NorthWest,Iran, , International Journal of Farming and Allied Sci., 2014;3(2):235-243.
28.Sun W, Shao M, Granier C, Liu Y, Ye CS, Zheng JY. Long-Term Trends of Anthropogenic SO2, NOx, CO, and NMVOCs Emissions in China. 2018, https://doi.org/10.1029/2018EF000822m
29.Trinh TT, Le TT, Nguyen TDH, Tu BM. Temperature inversion and air pollution relationship, and its effects on human health in Hanoi City, Vietnam. Environ Geochem Health. 2019; 41 (2): 929-37.
30.Jafarigol F, Atabi F, Moattar F, Nouri J. Predicting ambient concentrations of NO2 in a gas refinery located in South Pars Gas Complex. Int. J. Environ. Sci. Technol. 2016; 13: 897-906.
31.Sadigh, A., Fataei, E., Arzanloo, M. et al. Bacteria bioaerosol in the indoor air of educational microenvironments: Measuring exposures and assessing health effects. J Environ Health Sci Engineer, 2021; https://doi.org/10.1007/s40201-021-00719-5.
32.Sadigh A, Fataei A, Arzanloo A, Imani AA, Determination of Bacterial Bioaerosol Concentration in Indoor Air of Ardabil Universities in 2020, Journal of Health, 2020;11 (2):248-256.
Journal of Health Sciences & Surveillance System
Volume 9, Issue 4
October 2021
Pages 312-319
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