Environmental Researches

Environmental Researches

Air Dispersion Simulation Due to Non- Urban Road Traffic Using CALPUFF: A Case Study in Lorestan, Iran

Document Type : Original Article

Authors
1 Assistant Professor, Dept. of the Environmental Sciences, Behbahan Khatam Alanbia University of Technology, Behbahab, Iran
2 Associate Professor, Dept. of the Environmental Sciences, Isfahan University of Technology, Isfahan, Iran
3 Professor, Dept. of the Environmental Sciences, Isfahan University of Technology, Isfahan, Iran
4 Professor, Dept. of the Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran
10.22034/eiap.2024.182735.1952
Abstract
Roads as main infrastructure of development in spite of their social and economic advantages would lead to increase of air pollutants due to vehicles traffic. The main of this study is to estimate of suburban road networks impacts based on air pollution modeling approach. For this purpose, dispersion limits of CO, NO2, PM10 and SO2 pollutants emitted from Lorestan road network’s traffic have been investigated. The CALPUFF model were used to simulate pollutants in four seasons. Traffic volume and velocity, pollutants emission rate, synoptic meteorological data, land cover map, digital elevation model and slope map were used as input data. The result of modeling for 2461 km of road showed that maximum concentration of pollutants is in autumn and located in distance about 2 km from the roads. Based on the modeling outputs, SO2 gas has most distribution than the rest of pollutants. The most rate of rural population exposed to the air pollution of road networks are 11/5 percentage of all population of Lorestan province. This occurs in autumn. Although the mainly studies on air pollution have been focused in urban areas, but the results of this study in a province with natural regions showed even these regions are not in safe from the air pollution. Therefore, it is essential to attention of environmental consideration in road design and routing phase as well as decrease of vehicle’s age of suburban road transportation.
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Abdul-Wahab, S. A. & Fadlallah, S. O. 2014. A study of the effects of vehicle emissions on the atmosphere of Sultan Qaboos University in Oman. Atmosphericenvironment, 98: 158–167.
Ali, M. & Athar M. 2008. Air pollution due to traffic, air quality monitoring along three sections of National Highway N-5, Pakistan. Environmental monitoring and Assessment, 136(3):219-26.
BARLOW, T. J.; Latham, S.; McCrae, I. & Boulter, P. 2009. A reference book of driving cycles for use in the measurement of road vehicle emissions. TRL Published Project Report.
Batterman, S.; Burke, J.; Isakov, V.; Lewis, T.; Mukherjee, B. & Robins, T. 2014. A comparison of exposure metrics for traffic-related air pollutants: Application to epidemiology studies in Detroit, Michigan. International journal of environmental research and public health, 11(9): 9553–9577.
Cordova, A.M.; Arévalo, J.; Marín, J.C.; Baumgardner, D.; Raga, G.B.; Pozo, D.; Ochoa, C.A. & Rondanelli, R. 2016. On the Transport of Urban Pollution in an Andean Mountain Valley, Aerosol Air Qual. Res. 16, 593–605.
Demirarslan, K.; Çetin Doğruparmak, Ş.; & Karademir, A. 2017. Evaluation of three pollutant dispersion models for the environmental assessment of a district in Kocaeli, Turkey. GLOBAL NEST JOURNAL, 19(1): 37–48.
Dresser, A. L.; & Huizer, R. D. 2011. CALPUFF and AERMOD model validation study in the near field: Martins Creek revisited. Journal of the Air & Waste Management Association, 61(6): 647–659.
Etyemezian, V.; Kuhns, H.; Gillies, J.; Chow, J.; Hendrickson, K.; McGown, M.; & Pitchford, M. 2003. Vehicle based road dust emission measurement (III): effect of speed, traffic volume, location, and season on PM10 road dust emissions in the Treasure Valley, ID. Atmospheric Environment, 37(32): 4583–4593.
Fallah-Shorshani, M.; Shekarrizfard, M.; & Hatzopoulou, M. 2017. Evaluation of regional and local atmospheric dispersion models for the analysis of traffic-related air pollution in urban areas. Atmospheric Environment, 167: 270–282.
Fujisada, H.; Bailey, G. B.; Kelly, G. G.; Hara, S. & Abrams, M. J. 2005. Aster dem performance. IEEE transactions on Geoscience and Remote Sensing, 43(12): 2707–2714.
Hatzopoulou, M. & Miller, E. J. 2010. Linking an activity-based travel demand model with traffic emission and dispersion models: transport’s contribution to air pollution in Toronto. Transportation Research Part D: Transport and Environment, 15(6):315–325.
Helldin, J. O.; Collinder, P.; Bengtsson, D.; Karlberg, A. & Askling, J. 2013. Assessment of traffic noise impact in important bird sites in Sweden–A practical method for the regional scale. Oecologia Australis, 17(1): 48–62.
Kyrkilis, G.; Chaloulakou, A. & Kassomenos, P. A. 2007. Development of an aggregate Air Quality Index for an urban Mediterranean agglomeration: Relation to potential health effects. Environment International, 33(5): 670–676.
 Lee, G.; Ritchie, S. G.; Saphores, J.-D.; Jayakrishnan, R.; Ogunseitan, O. & others. 2012. Assessing air quality and health benefits of the Clean Truck Program in the Alameda corridor, CA. Transportation Research Part A: Policy and Practice, 46(8): 1177–1193.
MacIntosh, D. L.; Stewart, J. H.; Myatt, T. A.; Sabato, J. E.; Flowers, G. C.; Brown, K. W.; Hlinka, D. J. & Sullivan, D. A. 2010. Use of CALPUFF for exposure assessment in a near-field, complex terrain setting. Atmospheric Environment, 44(2): 262–270.
Mintz, D. 2009. Technical assistance document for the reporting of daily air quality-the air quality index (AQI). Tech. Research Triangle Park, US Environmental Protection Agency.
Nagendra, S. S.; Diya, M.; Chithra, V.; Menon, J. S. & Peter, A. E. 2016. Characteristics of air pollutants at near and far field regions of a national highway located at an industrial complex. Transportation Research Part D: Transport and Environment, 48: 1–13.
Redling, K.; Elliott, E.; Bain, D. & Sherwell, J. 2013. Highway contributions to reactive nitrogen deposition: tracing the fate of vehicular NOx using stable isotopes and plant biomonitors. Biogeochemistry, 116(1–3): 261–274.
Ruggieri, M. & Plaia, A. 2012. An aggregate AQI: comparing different standardizations and introducing a variability index. Science of the Total Environment, 420: 263–272.
Scire, J. S.; Strimaitis, D. G.; Yamartino, R. J. & others. 2000. A user’s guide for the CALPUFF dispersion model. Earth Tech, Inc. Concord, MA.
Statistical center of Iran. 2016. Statistical data and information. Available at: www.amar.org.ir. (in Persian)
Tartakovsky, D.; Broday, D. M. & Stern, E. 2013. Evaluation of AERMOD and CALPUFF for predicting ambient concentrations of total suspended particulate matter (TSP) emissions from a quarry in complex terrain. Environmental pollution, 179: 138–145.
Toro, J.; Duarte, O.; Requena, I. & Zamorano, M. 2012. Determining vulnerability importance in environmental impact assessment: The case of Colombia. Environmental impact assessment review, 32(1): 107–117.
Transportation and Road Ministry. 2007. Guidelines for environmental assessment of road transport projects. Transportation Research Institute. (in Persian)
Yu, H. & Stuart, A. L. 2013. Spatiotemporal distributions of ambient oxides of nitrogen, with implications for exposure inequality and urban design. Journal of the Air & Waste Management Association, 63(8): 943–955.