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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

机译:GIS和AERMOD-WRF耦合模型在印度东部市区环境二氧化氮的时空变化和未来排放情景

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摘要

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.
机译:本研究的重点是2013年6月至2015年5月期间二氧化氮(NO2)的时空变化及其在印度东部市区(Durgapur)的未来排放情景。周围NO2的浓度显示季节性以及特定地点的特征。高车辆密度的站点(Muchipara)显示出最高的NO2浓度,其次分别是工业站点(DVC-DTPS殖民地)和住宅站点(B区)。通过基于地理信息系统的数字高程模型来描述研究区域内环境NO2的季节性变化。在所考虑的城市总面积(114.982 km 2 )中,NO2的浓度超过了5.000 km 2 ,季风后,冬季和季风前分别为0.786 km 2 和0.653 km 2 。风向图,相关性和回归分析表明,气象对地表附近NO2的稀释和扩散起着至关重要的作用。主成分分析确定了车辆来源是市区所有季节中NO2的主要来源。结合使用AMS / EPA监管模型(AERMOD)–天气研究与预报(WRF)模型来预测NO2的浓度。观测数据和模拟数据的比较表明,该模型高估了所有季节(冬季除外)中的NO2浓度。结果表明,耦合的AERMOD-WRF模型可以克服小时表面和预报污染物浓度所需的高空气象数据的不足,但是改善排放清单以及更好地了解环境NO2的汇和源对于捕捉更现实的情况。

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