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1.
Environ Monit Assess ; 193(5): 295, 2021 Apr 24.
Artículo en Inglés | MEDLINE | ID: mdl-33893565

RESUMEN

In this paper, a 2-D turbulent closure model, based on the pollutant mass conservation equation, is adopted to estimate the local and background pollutants in the predominant wind direction for the stable atmosphere during winter mornings. The background concentration of pollutants can severely affect the regional pollution level, and its monitoring is a challenging task. Here, the turbulent closure model is employed across three cities in India, viz., Patiala, Delhi, and Agra, to estimate SO2 and NOx concentration along the predominant wind direction to demonstrate the potential of numerical models. The direction of the prevailing wind in this area during January 2003 was NNW (330°). Patiala is followed by Delhi and then Agra in the predominant wind direction. The sensitivity analysis of surface temperature on pollutant concentration reveals that concentration would increase by its square as temperature dips. So, during low or no horizontal wind, pollution episodes will be inevitable. Thus, the pollution hotspots are also identified in these three cities. Delhi had a high pollution load. So, the impact of local pollution in Delhi, through dispersion, was found significant in Agra. NOx hot spots (exceed the 30 µg/m3 limit) are found all across Delhi, except IGI Airport and two other locations. However, no SO2 hotspot (exceed the 60 µg/m3 limit) is found in Delhi. The proposed model output is verified with the WRF-CFD model results. Compared to the WRF-CFD model, the proposed model has overestimated NOx and SO2 concentration maximum by 14.4% and 23.5%, respectively. The overestimation occurred primarily due to ignoring atmospheric chemical reactions (e.g., acid condensation, etc.) for which the atmospheric factors were not so conducive.


Asunto(s)
Contaminantes Atmosféricos , Contaminación del Aire , Contaminantes Atmosféricos/análisis , Contaminación del Aire/análisis , Ciudades , Monitoreo del Ambiente , India , Material Particulado/análisis , Viento
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