In this work, taking advantage of a well-validated unit-based power emission database and the high temporal resolution of continuous emission monitoring systems data (CEMS), we attempt to construct daily emission estimates of coal-fired power plants in China during 2017–2020 based on multisource data fusion. A step-by-step method is developed to screen outliers and impute missing values for data from CEMS. Then, daily profiles of flue gas volume (for CO₂) and emission rates (for SO₂, NO_x, and PM_2.5) obtained from CEMS for each plant are coupled with unit-level annual emissions from CPED to achieve daily scale emission estimation.

This dataset presents daily emissions of SO₂, NO_x, PM_2.5, and CO₂ from 2017 to 2020 of 30 provinces in China (except Hong Kong, Macao, Taiwan and Tibet). If you have any questions, please contact Qiang Zhang (qiangzhang@tsinghua.edu.cn).