气候变化领域集成服务门户(CCPortal): Modelling air quality during the EXPLORE-YRD campaign – Part I. Model performance evaluation and impacts of meteorological inputs and grid resolutions

CCPortal

DOI	10.1016/j.atmosenv.2020.118131
	Modelling air quality during the EXPLORE-YRD campaign – Part I. Model performance evaluation and impacts of meteorological inputs and grid resolutions
	Wang X.; Li L.; Gong K.; Mao J.; Hu J.; Li J.; Liu Z.; Liao H.; Qiu W.; Yu Y.; Dong H.; Guo S.; Hu M.; Zeng L.; Zhang Y.
发表日期	2021
ISSN	1352-2310
卷号	246
英文摘要	The EXPeriment on the eLucidation of the atmospheric Oxidation capacity and aerosol foRmation and their Effects in the Yangtze River Delta (EXPLORE-YRD) campaign was carried out between May and June 2018 at a regional site in Taizhou, China. The EXPLORE-YRD campaign helped construct a detailed air quality model to understand the formation of O3 and PM2.5 further, identify the key sources of elevated air pollution events, and design efficient emission control strategies to reduce O3 and PM2.5 pollution in YRD. In this study, we predicted the air quality during the EXPLORE-YRD campaign using the Weather Research and Forecasting/Community Multiscale Air Quality modelling system (WRF/CMAQ) and evaluated model performance on O3 and PM2.5 concentrations and compositions. Air quality was predicted using two sets of reanalysis data—NCEP Final (FNL) Operational Global Analysis and ECMWF Reanalysis v5.0 (ERA5)—and three horizontal resolutions of 36, 12, and 4 km. The results showed that PM2.5 concentration was generally under-predicted using both the FNL and ERA5 data. ERA5 yielded slightly higher PM2.5 predictions during the EXPLORE-YRD campaign. Both reanalysis data sets under-predicted the high PM2.5 pollution processes on 29–30 May 2018, indicating that reanalysis data is not essential for under-predicting extreme PM2.5 pollution processes. The performance of O3 was similar in both the reanalysis data sets, because O3 is mostly sensitive to temperature predictions and FNL and ERA5 yielded similar temperature results. Although the average performance of PM2.5 and O3 predictions yielded by FNL and ERA5 was similar, large differences were observed in certain locations on specific days (e.g. in Hangzhou between 29 May and June 6, 2018 and in Hefei on 1–3 June 2018). Therefore, the choice of reanalysis data could be an important factor affecting the predictions of PM2.5 and O3, depending on locations and episodes. Comparable results were obtained using predictions with different horizontal resolutions, indicating that grid resolution was not crucial for determining the model performance of both PM2.5 and O3 during the campaign. © 2020 Elsevier Ltd
英文关键词	Air quality; Emission control; River pollution; Weather forecasting; Air quality modeling; Atmospheric oxidation capacity; Horizontal resolution; Meteorological input; Model performance evaluations; Multiscale air quality; Temperature prediction; Weather research and forecasting; Quality control; air quality; concentration (composition); emission control; meteorology; modeling; ozone; particulate matter; pollutant source; spatiotemporal analysis; strategic approach; air quality; article; forecasting; particulate matter 2.5; prediction; weather; China
语种	英语
来源期刊	Atmospheric Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/169079
作者单位	Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing, 210044, China; State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China; CAS Center for Excellence in Regional Atmospheric Environment, Chinese Academy of Science, Xiamen, 361021, China
推荐引用方式 GB/T 7714	Wang X.,Li L.,Gong K.,等. Modelling air quality during the EXPLORE-YRD campaign – Part I. Model performance evaluation and impacts of meteorological inputs and grid resolutions[J],2021,246.
APA	Wang X..,Li L..,Gong K..,Mao J..,Hu J..,...&Zhang Y..(2021).Modelling air quality during the EXPLORE-YRD campaign – Part I. Model performance evaluation and impacts of meteorological inputs and grid resolutions.Atmospheric Environment,246.
MLA	Wang X.,et al."Modelling air quality during the EXPLORE-YRD campaign – Part I. Model performance evaluation and impacts of meteorological inputs and grid resolutions".Atmospheric Environment 246(2021).