2026-10-12T07:44:16Z https://www.scidb.cn/oai

10.57760/sciencedb.13151 2025-12-24T13:50:50Z

2025-12-24 Inversed Emission Inventory for Chinese Air Quality (CAQIEI) version 1.0 doi:10.57760/sciencedb.13151 en The Inversed Emission Inventory for Chinese Air Quality (CAQIEI) version 1.0 is a new long-term top-down emission inventory in China developed by the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP, CAS), collaborated with China National Environmental Monitoring Centre (CNEMC) and other research institutes at home and abroad. It was produced by the chemical data assimilation system (ChemDAS) developed by the IAP, CAS which was constrained by observations from over 1000 surface air quality monitoring sites from CNEMC by using the ensemble Kalman filter (EnKF) and the Nested Air Quality Prediction Modeling system (NAQPMS). It contains constrained monthly gridded emissions of NOx, SO2, CO, primary PM2.5, primary PM10, and NMVOCs in China from 2013 to 2020, with a horizontal resolution of 15 km. The evaluation results suggest that the CAQIEI can effectively reduce the biases in the a priori emission inventory, with the normalized mean biases ranging from −9.1% to 9.5% in the a posteriori simulation, which are significantly reduced from the biases in the a priori simulations (−45.6% to 93.8%). The calculated RMSEs (0.3 mg/m3 for CO and 9.4–21.1 for other species, on the monthly scale) and correlation coefficients (0.76–0.94) were also improved from the a priori simulations. There are totally 8 Network Common Data Form files (NetCDF) in this dataset, which were named by the year and contain the monthly emissions of different air pollutants in China in each year. Detailed description of the content of each NetCDF file as well as some important notes when using this dataset is available in README.txt. A paper introducing this dataset has been accpeted by Earth System Science Data (DOI: 10.5194/essd-2023-477), where detailed descriptions and validation of this dataset are available. top-down emission inventory; chemical data assimilation; ensemble Kalman filter; air quality modeling Kong Lei Xiao Tang Zifa Wang Jiang Zhu Jianjun Li Huangjian Wu Qizhong Wu Huansheng Chen Lili Zhu Wei Wang Bing Liu Qian Wang Duohong Chen Yuepeng Pan Jie Li Lin Wu Gregory R. Carmichael PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.5194/essd-2023-477 Science Data Bank