Impact of seasonal meteorology and averaging time on vehicular pollution modeling
Awkash Kumar (),
Rashmi S. Patil,
Anil Kumar Dikshit and
Rakesh Kumar
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Awkash Kumar: Indian Institute of Technology, Bombay
Rashmi S. Patil: Indian Institute of Technology, Bombay
Anil Kumar Dikshit: Indian Institute of Technology, Bombay
Rakesh Kumar: National Environmental Engineering Research Institute Mumbai Zone
International Journal of System Assurance Engineering and Management, 2017, vol. 8, issue 2, No 107, 1937-1944
Abstract:
Abstract Air quality modeling requires three types of input data viz. emission, meteorology and geographical information and it can help to distinguish the influence of these factors for air pollution. In this present study, a constant emission has been considered for a region and it has been applied in vehicular pollution modeling with various averaging time period of seasons for the year. Chembur, the most polluted area of Mumbai city (India) due to industrial and vehicular sources, has been selected for this study. Generally, temporal and spatial interpolated meteorological data are used in air quality modeling, which is collected from a nearby meteorological station. In this paper, AERMOD was processed with onsite meteorological data, derived from Weather Research and Forecasting (WRF) model. It was applied for a 1 day period and 1 month of winter and monsoon season and again for whole year 2011. The results of AERMOD showed interesting behavior of the model for different averaging times. There is a general understanding in air quality modeling that concentration decreases with increase in averaging time. In this study, the results show that the concentration decreases with increasing of averaging time in winter season while concentration increases with increasing of averaging time period in monsoon season. Also, WRF model has been used for simulating for a year successfully which saves enormous time and resources of collecting meteorological data from a station and gives good result.
Keywords: Vehicular pollution modeling; AERMOD; WRF; Meteorology; Season (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1007/s13198-017-0624-6
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