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<p>Scientific knowledge on the chemical compositions of fine particulate matter (PM<sub>2.5</sub>) is essential for properly assessing its health and climate effects, and for decisionmakers to develop efficient mitigation strategies. A high-resolution PM<sub>2.5</sub> 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<sub>2.5</sub> composition datasets. Based on CAQRA-aerosol, spatiotemporal changes of different PM<sub>2.5</sub> 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<sup>−3</sup> yr<sup>−1</sup> from 2015 to 2020, compared with −0.19 to −1.1 µg m<sup>−3</sup> yr<sup>−1</sup> for other compositions. The whole dataset is freely available from the China Air Pollution Data Center (<a href="https://doi.org/10.12423/capdb_PKU.2023.DA">https://doi.org/10.12423/capdb_PKU.2023.DA</a>).</p>

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High-resolution Simulation Dataset of Hourly PM2.5 Chemical Composition in China (CAQRA-aerosol) from 2013 to 2020

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年1月22日

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  • Lei Kong,
  • Xiao Tang,
  • Jiang Zhu,
  • Zifa Wang,
  • Bing Liu,
  • Yuanyuan Zhu,
  • Lili Zhu,
  • Duohong Chen,
  • Ke Hu,
  • Huangjian Wu,
  • Qian Wu,
  • Jin Shen,
  • Yele Sun,
  • Zirui Liu,
  • Jinyuan Xin,
  • Dongsheng Ji,
  • Mei Zheng

摘要

Scientific knowledge on the chemical compositions of fine particulate matter (PM2.5) is essential for properly assessing its health and climate effects, and for decisionmakers to develop efficient mitigation strategies. A high-resolution PM2.5 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 PM2.5 composition datasets. Based on CAQRA-aerosol, spatiotemporal changes of different PM2.5 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).