Spatio-Temporal Variation and Futuristic Emission Scenario of Ambient Nitrogen Dioxide over an Urban Area of Eastern India Using GIS and Coupled AERMOD–WRF Model

Abstract

The present study focuses on the spatio-temporal variation of nitrogen dioxide (NO2) during June 2013 to May 2015 and its futuristic emission scenario over an urban area (Durgapur) of eastern India. The concentration of ambient NO2 shows seasonal as well as site specific characteristics. The site with high vehicular density (Muchipara) shows highest NO2 concentration followed by industrial site (DVC- DTPS Colony) and the residential site (B Zone), respectively. The seasonal variation of ambient NO2 over the study area is portrayed by means of Geographical Information System based Digital Elevation Model. Out of the total urban area under consideration (114.982 km2), the concentration of NO2 exceeded the National Ambient Air Quality Standard (NAAQS) permissible limit over an area of 5.000 km2, 0.786 km2 and 0.653 km2 in post monsoon, winter and pre monsoon, respectively. Wind rose diagrams, correlation and regression analyses show that meteorology plays a crucial role in dilution and dispersion of NO2 near the earth’s surface. Principal component analysis identifies vehicular source as the major source of NO2 in all the seasons over the urban region. Coupled AMS/EPA Regulatory Model (AERMOD)–Weather Research and Forecasting (WRF) model is used for predicting the concentration of NO2. Comparison of the observed and simulated data shows that the model overestimates the concentration of NO2 in all the seasons (except winter). The results show that coupled AERMOD–WRF model can overcome the unavailability of hourly surface as well as upper air meteorological data required for predicting the pollutant concentration, but improvement of emission inventory along with better understanding of the sinks and sources of ambient NO2 is essential for capturing the more realistic scenario.

Remote Sensing Assessment of the Impact of Land Use and Land Cover Change on the Environment of Barddhaman District, West Bengal, India

“…On the other hand, increases in vegetation, particularly in forest cover and in water bodies, may have more positive effects on the natural environment (Trombulak and Frissell, 2000;Myhre et al, 2013;Sahim, 2018). Several previous studies have described air quality and its impact on the surrounding environment of Barddhaman (Reddy and Ruj, 2003;Gupta et al, 2009;Chatterjee, 2011;Banerjee, 2013;Palit et al, 2013;Roy et al, 2015;Chattopadhyay et al, 2017;Dey et al, 2017). Others have used remote sensing or census data to describe land use and land cover change arising from urban and industrial expansion (Sikdar et al, 2004;Chatterjee et al, 2012;Gupta and Roy, 2012;Banerjee, 2013).…”

Spatio-Temporal Study of Criteria Pollutants in Nigerian City

“…This also correlates to SO 2 pattern of distribution and similarly shows that lower NO 2 distribution at Fegge/Nupe square is due to prevalent high wind speeds and precipitation [14]. Another significant contributor of NO 2 are the industrial activities centered on upper Iweka, has been similarly observed [25,26]. Moreover, the distance from the monitoring site might equally affect the density of NO 2 concentration per unit area [22].…”

Influences of boundary layer phenomena and meteorology on ambient air quality status of an urban area in eastern India

“…Long-range horizontal transport also plays a crucial role in the variation of ground level ozone concentration . Many researchers have focused on the monitoring and analysis of air pollutants and air quality in different parts of India like Kolkata, Delhi, Lucknow, Haryana, Chennai, Mumbai, Dhanbad-Jharia, Raniganj-Asansol, Durgapur and Burdwan (Lal and Patil, 2001;Jain and Saxena, 2002;Goyal and Sidhartha, 2003;Reddy and Ruj, 2003;Verma et al, 2003;Kaushik et al, 2006;Pulikesi et al, 2006;Gupta et al, 2008;Chattopadhyay et al, 2010;Dey et al, 2014Dey et al, , 2017.…”