High-resolution Simulation Dataset of Hourly PM_2.5 Chemical Composition in China (CAQRA-aerosol) from 2013 to 2020

Scientific knowledge on the chemical compositions of fine particulate matter (PM_2.5) is essential for properly assessing its health and climate effects, and for decisionmakers to develop efficient mitigation strategies. A high-resolution PM_2.5 chemical composition dataset (CAQRA-aerosol) is developed in this study, which provides hourly maps of organic carbon, black carbon, ammonium, nitrate, and sulfate in China from 2013 to 2020 with a horizontal resolution of 15 km. This paper describes the method, access, and validation results of this dataset. It shows that CAQRA-aerosol has good consistency with observations and achieves higher or comparable accuracy with previous PM_2.5 composition datasets. Based on CAQRA-aerosol, spatiotemporal changes of different PM_2.5 compositions were investigated from a national viewpoint, which emphasizes different changes of nitrate from other compositions. The estimated annual rate of population-weighted concentrations of nitrate is 0.23 µg m⁻³ yr⁻¹ from 2015 to 2020, compared with −0.19 to −1.1 µg m⁻³ yr⁻¹ for other compositions. The whole dataset is freely available from the China Air Pollution Data Center (https://doi.org/10.12423/capdb_PKU.2023.DA).