School of Economics and Management, Beihang University, Beijing, 100191, China.
School of Economics and Management, University of Chinese Academy of Sciences, Beijing, 100190, China.
Sci Data. 2023 Mar 22;10(1):153. doi: 10.1038/s41597-023-02054-w.
As the world's largest industrial producer, China has generated large amount of industrial atmospheric pollution, particularly for particulate matter (PM), SO and NO emissions. A nationwide, time-varying, and up-to-date air pollutant emission inventory by industrial sources has great significance to understanding industrial emission characteristics. Here, we present a nationwide database of industrial emissions named Chinese Industrial Emissions Database (CIED), using the real smokestack concentrations from China's continuous emission monitoring systems (CEMS) network during 2015-2018 to enhance the estimation accuracy. This hourly, source-level CEMS data enables us to directly estimate industrial emission factors and absolute emissions, avoiding the use of many assumptions and indirect parameters that are common in existing research. The uncertainty analysis of CIED database shows that the uncertainty ranges are quite small, within ±7.2% for emission factors and ±4.0% for emissions, indicating the reliability of our estimates. This dataset provides specific information on smokestack concentrations, emissions factors, activity data and absolute emissions for China's industrial emission sources, which can offer insights into associated scientific studies and future policymaking.
作为世界上最大的工业生产国，中国产生了大量的工业大气污染，特别是颗粒物（PM）、SO 和 NO 的排放。一个全国性的、随时间变化的、最新的工业污染源空气污染物排放清单对了解工业排放特征具有重要意义。在这里，我们提出了一个名为中国工业排放数据库（CIED）的全国性工业排放数据库，利用中国连续排放监测系统（CEMS）网络在 2015-2018 年期间的实际烟囱浓度来提高估计的准确性。这种每小时、源级别的 CEMS 数据使我们能够直接估计工业排放因子和绝对排放量，避免了现有研究中常见的许多假设和间接参数的使用。CIED 数据库的不确定性分析表明，不确定性范围相当小，排放因子的不确定性范围在±7.2%以内，排放量的不确定性范围在±4.0%以内，表明了我们估计的可靠性。该数据集提供了中国工业污染源烟囱浓度、排放因子、活动数据和绝对排放量的具体信息，可为相关科学研究和未来决策提供参考。
