本数据集编制了 2005 年至 2021 年中国大陆大气污染物和二氧化碳耦合排放数据集，即 ABaCAS-EI v2.0（空气效益与成本及达标评估系统-排放清单 2.0 版），它是 ABaCAS-EI 的更新版本。该数据集涵盖二氧化碳和 9 类空气污染物，包括 11 个主要来源类别和 280 多个分类。
\n该数据集按物种、部门、年份和省份介绍了排放量。
\n1) 种类包括 CO2 、SO2、NOx、PM10、PM2.5、BC、OC、VOCs、NH3 和 CO；
\n2) 报告了 15 个排放部门：农业氮肥施用、农业畜牧业、居民生物燃料燃烧、居民化石燃料燃烧、居民溶剂使用、其他居民源、工业锅炉、生物质露天焚烧、发电厂、水泥工业、钢铁工业、其他工业流程、工业溶剂使用、非道路机械和道路车辆；
\n3) 2005 年至 2021 年；
\n4) 中国大陆所有 31 个省份。
", "ds_source": "活动数据大多从官方来源收集，并有质量保证。大气污染物的排放因子来自局部实验或相关文献的综合，二氧化碳的排放因子参考了中国温室气体排放清单指南（国家发改委，2011 年）和政府间气候变化专门委员会（IPCC）发布的指南。大气污染物的特定措施去除率及其应用比例收集自官方报告、国家环境统计数据、工业调查和以往研究。与CO2相关的数据则从 IPCC 指南和文献中收集。", "ds_process_way": "
本研究采用蒙特卡罗模拟来量化排放量估算的不确定性，重复蒙特卡罗模拟 10,000 次，以 95% 的置信区间估算排放量。每个物种总排放量的不确定性是通过合并各省分部门获得的数值而得出的。", "ds_quality": "
数据质量良好。
", "ds_acq_start_time": "2005-01-01 00:00:00", "ds_acq_end_time": "2021-12-31 00:00:00", "ds_acq_place": "中国", "ds_acq_lon_east": 130.01666666666668, "ds_acq_lat_south": 3.8666666666666667, "ds_acq_lon_west": 73.66666666666667, "ds_acq_lat_north": 53.5, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 851925, "ds_files_count": 3, "ds_format": "xlsx", "ds_space_res": "", "ds_time_res": "年", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "3c6860a3-fb55-47d7-878e-051c959d9187.png", "ds_thumb_from": 2, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "a4dd5849-78f2-44c5-b0f1-3450e952b2a2", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.15" ], "quality_level": 3, "publish_time": "2023-12-27 11:00:17", "last_updated": "2026-01-14 10:43:12", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.FIGSHARE.DB4149.2023", "i18n": { "en": { "title": "China Atmospheric Pollutant and Carbon Dioxide Emission Trends Dataset (2005-2021)", "ds_format": "xlsx", "ds_source": "The activity data is mostly collected from official sources and has quality assurance. The emission factors of atmospheric pollutants come from local experiments or comprehensive literature, while the emission factors of carbon dioxide refer to the guidelines for China's greenhouse gas emission inventory (National Development and Reform Commission, 2011) and the guidelines issued by the Intergovernmental Panel on Climate Change (IPCC). The specific removal rates and application ratios of atmospheric pollutants are collected from official reports, national environmental statistical data, industrial surveys, and previous research. The data related to CO2is collected from IPCC guidelines and literature.", "ds_quality": "
The data quality is good.
", "ds_ref_way": "", "ds_abstract": "This data set has compiled the coupled emission data set of air pollutants and carbon dioxide in Chinese Mainland from 2005 to 2021, namely, ABACAS-EI v2.0 (air efficiency and cost and compliance assessment system - emission inventory version 2.0), which is the updated version of ABACAS-EI. This dataset covers carbon dioxide and 9 types of air pollutants, including 11 major source categories and over 280 classifications.
\nThis dataset introduces emissions by species, sector, year, and province.
\n1) Types include CO2 、SO2、NOx、PM10、PM2.5、BC、OC、VOCs、NH3 And CO
\n2) Reported 15 emission sectors: agricultural nitrogen fertilizer application, agricultural animal husbandry, residential biofuel combustion, residential fossil fuel combustion, residential solvent use, other residential sources, industrial boilers, biomass open burning, power plants, cement industry, steel industry, other industrial processes, industrial solvent use, non road machinery and road vehicles;
\n3) From 2005 to 2021;
\n4) All 31 provinces in Chinese Mainland.
", "ds_time_res": "年", "ds_acq_place": "China", "ds_space_res": "", "ds_projection": "", "ds_process_way": "This study used Monte Carlo simulation to quantify the uncertainty of emissions estimation, repeating the Monte Carlo simulation 10000 times and estimating emissions with a 95% confidence interval. The uncertainty of the total emissions of each species is obtained by merging the values obtained from each province's sub sectors.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "recommendation_value": 0, "license_type": "https://creativecommons.org/licenses/by/4.0/", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "belong_to_nieer": false, "ds_topic_tags": [ "中国", "空气污染物和二氧化碳排放", "大气科学" ], "ds_subject_tags": [ "大气科学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国" ], "ds_time_tags": [ 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021 ], "ds_contributors": [ { "true_name": "王书肖", "email": "shxwang@tsinghua.edu.cn", "work_for": "清华大学环境学院", "country": "中国" }, { "true_name": " 吴清茹", "email": "qrwu@tsinghua.edu.cn", "work_for": "清华大学环境学院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "王书肖", "email": "shxwang@tsinghua.edu.cn", "work_for": "清华大学环境学院", "country": "中国" }, { "true_name": " 吴清茹", "email": "qrwu@tsinghua.edu.cn", "work_for": "清华大学环境学院", "country": "中国" } ], "ds_managers": [ { "true_name": "王书肖", "email": "shxwang@tsinghua.edu.cn", "work_for": "清华大学环境学院", "country": "中国" }, { "true_name": " 吴清茹", "email": "qrwu@tsinghua.edu.cn", "work_for": "清华大学环境学院", "country": "中国" } ], "category": "大气本底" }