Abstract
Rational prediction of future CO2 at the regional level is essential to the carbon emission reduction targets in China. The primary aim of this study is to examine the applicability of an up-to-date forecast algorithm, namely dynamic mode decomposition (DMD), in provincial CO2 emission prediction. The testing results validate the accuracy and application value of the DMD short-run forecast, which may provide method reference for relevant policy formulation and research areas. Moreover, the 2020 provincial economic situation and CO2 emissions in China are projected via DMD. On this basis, the unqualified provinces regarding CO2 emission reduction are identified considering the relative standard and absolute standard, and the corresponding mitigation paths are proposed through decoupling analysis and shadow price calculation. The results indicate that the unqualified provinces include Heilongjiang, Gansu, Shanxi, Hebei, Liaoning, Jilin, Shaanxi, and Inner Mongolia. The open-emission-reduction mechanism should be adopted in the first five provinces; the conservative one should be applied in the other provinces.
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Funding
Research presented in this manuscript is supported by the National Social Science Foundation in China [grant number: 17BJL043], the Soft Science Research Program of Shaanxi Province, China [grant number: 2019KRM157], and the Planning Foundation of Social Science in Xi'an City, China [grant number: JG70].
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Conception and design of this study: Wanping Yang; acquisition of data: Bingyu Zhao; analysis and/or interpretation of data: Bingyu Zhao; drafting the manuscript: Bingyu Zhao; revising the manuscript critically for important intellectual content: Bingyu Zhao, Wanping Yang.
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Zhao, B., Yang, W. Short-run forecast and reduction mechanism of CO2 emissions: a Chinese province-level study. Environ Sci Pollut Res 29, 12777–12796 (2022). https://doi.org/10.1007/s11356-020-09936-1
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DOI: https://doi.org/10.1007/s11356-020-09936-1