Articles | Volume 16, issue 6
https://doi.org/10.5194/essd-16-2893-2024
https://doi.org/10.5194/essd-16-2893-2024
Data description paper
 | 
21 Jun 2024
Data description paper |  | 21 Jun 2024

Development of a high-resolution integrated emission inventory of air pollutants for China

Nana Wu, Guannan Geng, Ruochong Xu, Shigan Liu, Xiaodong Liu, Qinren Shi, Ying Zhou, Yu Zhao, Huan Liu, Yu Song, Junyu Zheng, Qiang Zhang, and Kebin He

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Cited articles

An, J., Huang, Y., Huang, C., Wang, X., Yan, R., Wang, Q., Wang, H., Jing, S., Zhang, Y., Liu, Y., Chen, Y., Xu, C., Qiao, L., Zhou, M., Zhu, S., Hu, Q., Lu, J., and Chen, C.: Emission inventory of air pollutants and chemical speciation for specific anthropogenic sources based on local measurements in the Yangtze River Delta region, China, Atmos. Chem. Phys., 21, 2003–2025, https://doi.org/10.5194/acp-21-2003-2021, 2021. 
Bo, X., Jia, M., Xue, X., Tang, L., Mi, Z., Wang, S., Cui, W., Chang, X., Ruan, J., Dong, G., Zhou, B., and Davis, S. J.: Effect of strengthened standards on Chinese ironmaking and steelmaking emissions, Nat. Sustain., 4, 811–820, https://doi.org/10.1038/s41893-021-00736-0, 2021. 
Chen, H., Huang, Y., Shen, H., Chen, Y., Ru, M., Chen, Y., Lin, N., Su, S., Zhuo, S., Zhong, Q., Wang, X., Liu, J., Li, B., and Tao, S.: Modeling temporal variations in global residential energy consumption and pollutant emissions, Appl. Energ., 184, 820–829, https://doi.org/10.1016/j.apenergy.2015.10.185, 2016. 
Cheng, J., Su, J., Cui, T., Li, X., Dong, X., Sun, F., Yang, Y., Tong, D., Zheng, Y., Li, Y., Li, J., Zhang, Q., and He, K.: Dominant role of emission reduction in PM2.5 air quality improvement in Beijing during 2013–2017: a model-based decomposition analysis, Atmos. Chem. Phys., 19, 6125–6146, https://doi.org/10.5194/acp-19-6125-2019, 2019. 
Cheng, J., Tong, D., Liu, Y., Bo, Y., Zheng, B., Geng, G., He, K., and Zhang, Q.: Air quality and health benefits of China's current and upcoming clean air policies, Faraday Discuss., 226, 584–606, https://doi.org/10.1039/D0FD00090F, 2021a. 
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The commonly used method for developing large-scale air pollutant emission datasets for China faces challenges due to limited availability of detailed parameter information. In this study, we develop an efficient integrated framework to gather such information by harmonizing seven heterogeneous inventories from five research institutions. Emission characterizations are analyzed and validated, demonstrating that the dataset provides more accurate emission magnitudes and spatiotemporal patterns.
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