The annual emission data of conventional air pollutants (PM2.5, SO2, NH3, NOX) under different carbon neutralization technologies and air pollutant end treatment scenario combinations from 2017 to 2060, generated based on the computable general equilibrium model and the base year emission inventory, are used for the policy scenario analysis of the future coordinated treatment of carbon dioxide and air pollution in China. This data has been applied to the evaluation of the health synergy benefits of the carbon neutral technology path, as the data input of the health impact assessment model, to estimate the premature death, incidence rate and the resulting life expectancy loss, and to monetize these health impacts. The health common interests of monetization are compared with the corresponding emission reduction costs to explore the cost-effectiveness of different carbon neutral technology combinations.

File naming and required software

File naming: the data volume is small and is not named by date
Data reading method: data is stored in CSV format. The defined variables of each data are climate control scenario (scenario), air pollution control scenario (scn_air), year, province (pro), sector and pollutant type (SO2, NOx, PM2.5, NH3)

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Cite as:

Wang, C., Zhang, S. (2022). Air pollutant emission data set of China's future carbon neutrality scenario (2017-2060). A Big Earth Data Platform for Three Poles, DOI: 10.11888/HumanNat.tpdc.272825. CSTR: 18406.11.HumanNat.tpdc.272825. (Download the reference： RIS | Bibtex )

Related Literatures:

1. Zhang, S., An, K., Li, J., Weng, Y., Zhang, S., Wang, S., Cai, W., Wang, C., & Gong, P. (2021). Incorporating health co-benefits into technology pathways to achieve China’s 2060 carbon neutrality goal: A modelling study. The Lancet Planetary Health, 5(11), e808–e817. https://doi.org/10.1016/S2542-5196(21)00252-7( View Details | Bibtex)

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

Support Program

Interaction and regional performance of natural and human factors on land surface driven by global change (No:2017YFA06036001)

Copyright & License

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License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)