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基于GIS和AERMOD-WRF耦合模型的印度东部某城市地区环境二氧化氮时空变化及未来排放情景分析

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.

作者信息

Dey Sharadia, Gupta Srimanta, Sibanda Precious, Chakraborty Arun

机构信息

School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Private Bag X01 Scottsville, Pietermaritzburg, South Africa.

Department of Environmental Science, The University of Burdwan, Golapbag, Burdwan, West Bengal, India.

出版信息

PLoS One. 2017 Jan 31;12(1):e0170928. doi: 10.1371/journal.pone.0170928. eCollection 2017.

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.

摘要

本研究聚焦于2013年6月至2015年5月期间印度东部城市地区(杜尔加布尔)二氧化氮(NO₂)的时空变化及其未来排放情景。环境中NO₂的浓度呈现出季节性以及特定地点的特征。车辆密度高的地点(穆奇帕拉)NO₂浓度最高,其次分别是工业地点(达莫德尔山谷公司 - 达莫德尔热力发电站殖民地)和住宅地点(B区)。通过基于地理信息系统的数字高程模型描绘了研究区域内环境NO₂的季节变化。在所考虑的整个城市区域(114.982平方千米)中,季风后、冬季和季风前NO₂浓度分别在5.000平方千米、0.786平方千米和0.653平方千米的区域超过了国家环境空气质量标准(NAAQS)的允许限值。风向玫瑰图、相关性和回归分析表明,气象学在地球表面附近NO₂的稀释和扩散中起着关键作用。主成分分析确定车辆源是城市区域所有季节中NO₂的主要来源。耦合的美国国家环保局法规模型(AERMOD) - 天气研究与预报(WRF)模型用于预测NO₂的浓度。观测数据与模拟数据的比较表明,该模型在所有季节(冬季除外)均高估了NO₂的浓度。结果表明,耦合的AERMOD - WRF模型可以克服预测污染物浓度所需的每小时地面和高空气象数据不可用的问题,但改进排放清单以及更好地了解环境NO₂的汇和源对于获取更现实的情景至关重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7014/5283685/6ac3b2306796/pone.0170928.g001.jpg

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