中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 合肥物质科学研究院
  3. 中国科学院合肥物质科学研究院
A 6-year-long (2013-2018) high-resolution air quality reanalysis dataset in China based on the assimilation of surface observations from CNEMC

文献类型：期刊论文

作者Kong, Lei1,2,3; Tang, Xiao1,2,3; Zhu, Jiang1,2,3; Wang, Zifa1,2,3,4; Li, Jianjun5; Wu, Huangjian1,6; Wu, Qizhong7; Chen, Huansheng1; Zhu, Lili5; Wang, Wei5
刊名EARTH SYSTEM SCIENCE DATA
出版日期2021-02-23
卷号13
ISSN号1866-3508
DOI10.5194/essd-13-529-2021
通讯作者Tang, Xiao(tangxiao@mail.iap.ac.cn) ; Zhu, Jiang(jzhu@mail.iap.ac.cn)
英文摘要A 6-year-long high-resolution Chinese air quality reanalysis (CAQRA) dataset is presented in this study obtained from the assimilation of surface observations from the China National Environmental Monitoring Centre (CNEMC) using the ensemble Kalman filter (EnKF) and Nested Air Quality Prediction Modeling System (NAQPMS).This dataset contains surface fields of six conventional air pollutants in China (i.e. PM2.5, PM10, SO2, NO2, CO, and O3) for the period 2013-2018 at high spatial (15km +/- 15km) and temporal (1 h) resolutions. This paper aims to document this dataset by providing detailed descriptions of the assimilation system and the first validation results for the above reanalysis dataset. The 5-fold cross-validation (CV) method is adopted to demonstrate the quality of the reanalysis. The CV results show that the CAQRA yields an excellent performance in reproducing the magnitude and variability of surface air pollutants in China from 2013 to 2018 (CV R 2 D 0 :52-0.81, CV root mean square error (RMSE) D 0 :54 mg =m3 for CO, and CV RMSE D 16 :4-39.3 mu g =m(3) for the other pollutants on an hourly scale). Through comparison to the Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA) dataset produced by the European Centre for Medium-Range Weather Forecasts (ECWMF), we show that CAQRA attains a high accuracy in representing surface gaseous air pollutants in China due to the assimilation of surface observations. The fine horizontal resolution of CAQRA also makes it more suitable for air quality studies on a regional scale. The PM2.5 reanalysis dataset is further validated against the independent datasets from the US Department of State Air Quality Monitoring Program over China, which exhibits a good agreement with the independent observations (R 2 D 0 :74-0.86 and RMSE D 16 :8-33.6 mu g =m3 in different cities). Furthermore, through the comparison to satellite-estimated PM2.5 concentrations, we show that the accuracy of the PM2.5 reanalysis is higher than that of most satellite estimates. The CAQRA is the first high-resolution air quality reanalysis dataset in China that simultaneously provides the surface concentrations of six conventional air pollutants, which is of great value for many studies, such as health impact assessment of air pollution, investigation of air quality changes in China, model evaluation and satellite calibration, optimization of monitoring sites, and provision of training data for statistical or artificial intelligence (AI)-based forecasting. All datasets are freely available at https://doi.org/10.11922/sciencedb.00053 (Tang et al., 2020a), and a prototype product containing the monthly and annual means of the CAQRA dataset has also been released at https://doi.org/10.11922/sciencedb.00092 (Tang et al., 2020b) to facilitate the evaluation of the CAQRA dataset by potential users.
WOS关键词ENSEMBLE KALMAN FILTER ; TROPOSPHERIC CHEMISTRY REANALYSIS ; ESTIMATE PM2.5 CONCENTRATIONS ; CHEMICAL-TRANSPORT MODEL ; GROUND-LEVEL PM2.5 ; CARBON-MONOXIDE ; INTERIM REANALYSIS ; INITIAL CONDITIONS ; EAST-ASIA ; DATA SET
资助项目National Natural Science Foundation of China[91644216] ; National Natural Science Foundation of China[41575128] ; National Natural Science Foundation of China[41875164] ; CAS Strategic Priority Research Program[XDA19040201] ; CAS Information Technology Program[XXH13506-302]
WOS研究方向Geology ; Meteorology & Atmospheric Sciences
语种英语
出版者COPERNICUS GESELLSCHAFT MBH
WOS记录号WOS:000622997600001
资助机构National Natural Science Foundation of China ; CAS Strategic Priority Research Program ; CAS Information Technology Program
源URL[http://ir.hfcas.ac.cn:8080/handle/334002/120927]  
专题中国科学院合肥物质科学研究院
通讯作者Tang, Xiao; Zhu, Jiang
作者单位1.Chinese Acad Sci, LAPC, Inst Atmospher Phys, Beijing 100029, Peoples R China
2.Chinese Acad Sci, ICCES, Inst Atmospher Phys, Beijing 100029, Peoples R China
3.Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing 100049, Peoples R China
4.Chinese Acad Sci, Ctr Excellence Reg Atmospher Environm, Inst Urban Environm, Xiamen 361021, Peoples R China
5.China Natl Environm Monitoring Ctr, Beijing 100012, Peoples R China
6.Peking Univ, Guanghua Sch Management, Beijing 100871, Peoples R China
7.Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China
8.Guangdong Environm Monitoring Ctr, State Environm Protect Key Lab Reg Air Qual Monit, Guangzhou 510308, Peoples R China
9.Shanghai Environm Monitoring Ctr, Shanghai 200030, Peoples R China
10.Univ Iowa, Ctr Global & Reg Environm Res, Iowa City, IA 52242 USA
推荐引用方式
GB/T 7714		 Kong, Lei,Tang, Xiao,Zhu, Jiang,et al. A 6-year-long (2013-2018) high-resolution air quality reanalysis dataset in China based on the assimilation of surface observations from CNEMC[J]. EARTH SYSTEM SCIENCE DATA,2021,13.
APA Kong, Lei.,Tang, Xiao.,Zhu, Jiang.,Wang, Zifa.,Li, Jianjun.,...&Carmichael, Gregory R..(2021).A 6-year-long (2013-2018) high-resolution air quality reanalysis dataset in China based on the assimilation of surface observations from CNEMC.EARTH SYSTEM SCIENCE DATA,13.
MLA Kong, Lei,et al."A 6-year-long (2013-2018) high-resolution air quality reanalysis dataset in China based on the assimilation of surface observations from CNEMC".EARTH SYSTEM SCIENCE DATA 13(2021).

入库方式： OAI收割

来源：合肥物质科学研究院

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。