Inversed Emission Inventory for Chinese Air Quality (CAQIEI) version 1.0

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.

中国空气质量反演排放清单（The Inversed Emission Inventory for Chinese Air Quality, CAQIEI）v1.0是由中国科学院大气物理研究所（Institute of Atmospheric Physics, Chinese Academy of Sciences, IAP, CAS）联合中国环境监测总站（China National Environmental Monitoring Centre, CNEMC）及国内外多家科研机构开发的新一代中国区域长期自上而下型排放清单。该数据集由中科院大气所开发的化学数据同化系统（Chemical Data Assimilation System, ChemDAS）构建，该系统依托中国环境监测总站1000余个地面空气质量监测站点的观测数据，通过集合卡尔曼滤波（Ensemble Kalman Filter, EnKF）与嵌套空气质量预测模式系统（Nested Air Quality Prediction Modeling System, NAQPMS）实现数据约束。数据集涵盖2013至2020年中国区域经同化约束的逐月网格化排放数据，包含氮氧化物（Nitrogen Oxides, NOx）、二氧化硫（Sulfur Dioxide, SO2）、一氧化碳（Carbon Monoxide, CO）、一次PM2.5（Particulate Matter 2.5, PM2.5）、一次PM10（Particulate Matter 10, PM10）及非甲烷挥发性有机物（Non-Methane Volatile Organic Compounds, NMVOCs），空间分辨率为15千米。评估结果显示，CAQIEI可有效降低先验排放清单的偏差：后验模拟的归一化平均偏差介于-9.1%至9.5%之间，较先验模拟的偏差范围（-45.6%至93.8%）有显著改善。计算得到的均方根误差（Root Mean Square Error, RMSE）（CO为0.3 mg/m³，其余污染物为9.4~21.1，以月尺度计）与相关系数（0.76~0.94）同样较先验模拟结果有所提升。本数据集共包含8个网络通用数据格式（Network Common Data Form, NetCDF）文件，以年份命名，各文件存储对应年份中国区域各类空气污染物的逐月排放数据。各NetCDF文件的详细内容说明及数据集使用注意事项详见README.txt文档。介绍该数据集的研究论文已被《Earth System Science Data》期刊接收（DOI: 10.5194/essd-2023-477），论文中包含该数据集的详细说明与验证内容。

搜集汇总

背景与挑战

背景概述

该数据集是中国空气质量反演排放清单（CAQIEI）1.0版本，包含2013至2020年中国多种空气污染物的月网格化排放数据，水平分辨率为15公里，通过化学数据同化技术和地面监测数据优化，显著减少了排放清单的偏差。数据集以NetCDF格式存储，共8个文件，每个文件对应一年的排放数据。