气候变化领域集成服务门户(CCPortal): Using TROPOspheric Monitoring Instrument (TROPOMI) measurements and Weather Research and Forecasting (WRF) CO modelling to understand the contribution of meteorology and emissions to an extreme air pollution event in India

CCPortal

DOI	10.5194/acp-21-5393-2021
	Using TROPOspheric Monitoring Instrument (TROPOMI) measurements and Weather Research and Forecasting (WRF) CO modelling to understand the contribution of meteorology and emissions to an extreme air pollution event in India
	Vellalassery A.; Pillai D.; Marshall J.; Gerbig C.; Buchwitz M.; Schneising O.; Ravi A.
发表日期	2021
ISSN	1680-7316
起始页码	5393
结束页码	5414
卷号	21 期号:7
英文摘要	Several ambient air quality records corroborate the severe and persistent degradation of air quality over northern India during the winter months, with evidence of a continued, increasing trend of pollution across the Indo-Gangetic Plain (IGP) over the past decade. A combination of atmospheric dynamics and uncertain emissions, including the post-monsoon agricultural stubble burning, make it challenging to resolve the role of each individual factor. Here we demonstrate the potential use of an atmospheric transport model, the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) to identify and quantify the role of transport mechanisms and emissions on the occurrence of the pollution events. The investigation is based on the use of carbon monoxide (CO) observations from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel-5 Precursor satellite and the surface measurement network, as well as the WRF-Chem simulations, to investigate the factors contributing to CO enhancement over India during November 2018. We show that the simulated column-averaged dry air mole fraction (XCO) is largely consistent with TROPOMI observations, with a spatial correlation coefficient of 0.87. The surface-level CO concentrations show larger sensitivities to boundary layer dynamics, wind speed, and diverging source regions, leading to a complex concentration pattern and reducing the observation-model agreement with a correlation coefficient ranging from 0.41 to 0.60 for measurement locations across the IGP. We find that daily satellite observations can provide a first-order inference of the CO transport pathways during the enhanced burning period, and this transport pattern is reproduced well in the model. By using the observations and employing the model at a comparable resolution, we confirm the significant role of atmospheric dynamics and residential, industrial, and commercial emissions in the production of the exorbitant level of air pollutants in northern India. We find that biomass burning plays only a minimal role in both column and surface enhancements of CO, except for the state of Punjab during the high pollution episodes. While the model reproduces observations reasonably well, a better understanding of the factors controlling the model uncertainties is essential for relating the observed concentrations to the underlying emissions. Overall, our study emphasizes the importance of undertaking rigorous policy measures, mainly focusing on reducing residential, commercial, and industrial emissions in addition to actions already underway in the agricultural sectors. © 2021 Author(s).
语种	英语
scopus关键词	air quality; atmospheric chemistry; atmospheric pollution; biomass burning; carbon emission; concentration (composition); extreme event; meteorology; monitoring system; Sentinel; troposphere; weather forecasting; winter; Gangetic Plain; India
来源期刊	ATMOSPHERIC CHEMISTRY AND PHYSICS
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/246988
作者单位	Indian Institute of Science Education and Research (IISERB) Bhopal, Bhopal, India; Max Planck Institute for Biogeochemistry, Jena, Germany; Institute of Environmental Physics (IUP), University of Bremen, Bremen, Germany; Max Planck Partner Group (IISERB), Max Planck Society, Munich, Germany; Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
推荐引用方式 GB/T 7714	Vellalassery A.,Pillai D.,Marshall J.,et al. Using TROPOspheric Monitoring Instrument (TROPOMI) measurements and Weather Research and Forecasting (WRF) CO modelling to understand the contribution of meteorology and emissions to an extreme air pollution event in India[J],2021,21(7).
APA	Vellalassery A..,Pillai D..,Marshall J..,Gerbig C..,Buchwitz M..,...&Ravi A..(2021).Using TROPOspheric Monitoring Instrument (TROPOMI) measurements and Weather Research and Forecasting (WRF) CO modelling to understand the contribution of meteorology and emissions to an extreme air pollution event in India.ATMOSPHERIC CHEMISTRY AND PHYSICS,21(7).
MLA	Vellalassery A.,et al."Using TROPOspheric Monitoring Instrument (TROPOMI) measurements and Weather Research and Forecasting (WRF) CO modelling to understand the contribution of meteorology and emissions to an extreme air pollution event in India".ATMOSPHERIC CHEMISTRY AND PHYSICS 21.7(2021).