全球智库信息集成服务系统(G2TT): Constraining the uncertainty in emissions over India with a regional air quality model evaluation.

G2TT

来源类型	Article
规范类型	其他
DOI	10.1016/j.atmosenv.2017.11.052
	Constraining the uncertainty in emissions over India with a regional air quality model evaluation.
	Karambelas A; Holloway T; Kiesewetter G; Heyes C
发表日期	2018
出处	Atmospheric Environment 174: 194-203
出版年	2018
语种	英语
摘要	To evaluate uncertainty in the spatial distribution of air emissions over India, we compare satellite and surface observations with simulations from the U.S. Environmental Protection Agency (EPA) Community Multi-Scale Air Quality (CMAQ) model. Seasonally representative simulations were completed for January, April, July, and October 2010 at 36 km × 36 km using anthropogenic emissions from the Greenhouse Gas-Air Pollution Interaction and Synergies (GAINS) model following version 5a of the Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants project (ECLIPSE v5a). We use both tropospheric columns from the Ozone Monitoring Instrument (OMI) and surface observations from the Central Pollution Control Board (CPCB) to closely examine modeled nitrogen dioxide (NO2) biases in urban and rural regions across India. Spatial average evaluation with satellite retrievals indicate a low bias in the modeled tropospheric column (-63.3%), which reflects broad low-biases in majority non-urban regions (-70.1% in rural areas) across the sub-continent to slightly lesser low biases reflected in semi-urban areas (-44.7%), with the threshold between semi-urban and rural defined as 400 people per km2. In contrast, modeled surface NO2 concentrations exhibit a slight high bias of +15.6% when compared to surface CPCB observations predominantly located in urban areas. Conversely, in examining extremely population dense urban regions with more than 5000 people per km2 (dense-urban), we find model overestimates in both the column (+57.8) and at the surface (+131.2%) compared to observations. Based on these results, we find that existing emission fields for India may overestimate urban emissions in densely populated regions and underestimate rural emissions. However, if we rely on model evaluation with predominantly urban surface observations from the CPCB, comparisons reflect model high biases, contradictory to the knowledge gained using satellite observations. Satellites thus serve as an important emissions and model evaluation metric where surface observations are lacking, such as rural India, and support improved emissions inventory development.
主题	Air Quality & ; Greenhouse Gases (AIR) ; Young Scientists Summer Program (YSSP) ; Mitigation of Air Pollution (MAG)
关键词	India Model Satellite OMI NO2 Emissions
URL	http://pure.iiasa.ac.at/id/eprint/14990/
来源智库	International Institute for Applied Systems Analysis (Austria)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/131438
推荐引用方式 GB/T 7714	Karambelas A,Holloway T,Kiesewetter G,et al. Constraining the uncertainty in emissions over India with a regional air quality model evaluation.. 2018.