Interregional carbon compensation cost forecast and priority index calculation based on the theoretical carbon deficit: China as a case

Guangchun Yang; Peipei Shang; Lichun He; Yingchun Zhang; Ying Wang; Fei Zhang; Lin Zhu; Yong Wang

doi:10.1016/j.scitotenv.2018.11.134

Interregional carbon compensation cost forecast and priority index calculation based on the theoretical carbon deficit: China as a case

Sci Total Environ. 2019 Mar 1:654:786-800. doi: 10.1016/j.scitotenv.2018.11.134. Epub 2018 Nov 10.

Authors

Guangchun Yang¹, Peipei Shang², Lichun He³, Yingchun Zhang⁴, Ying Wang¹, Fei Zhang¹, Lin Zhu¹, Yong Wang⁵

Affiliations

¹ School of Statistics, Dongbei University of Finance and Economics, Dalian, China.
² Editorial Department, Dongbei University of Finance and Economics, Dalian, China.
³ School of Public Administration, Dongbei University of Finance and Economics, Dalian, China.
⁴ School of Economics, Qingdao University, Qingdao, China.
⁵ School of Statistics, Dongbei University of Finance and Economics, Dalian, China; Postdoctoral Research Station, Dongbei University of Finance and Economics, Dalian, China. Electronic address: ywang@dufe.edu.cn.

PMID: 30448669
DOI: 10.1016/j.scitotenv.2018.11.134

Abstract

Interregional carbon compensation is an important part of ecological compensation. An accurate accounting of the interregional carbon compensation cost is the foundation for establishing a carbon compensation mechanism. Corresponding to the actual carbon deficit, this paper advances, for the first time, the concept of the theoretical carbon deficit and, improves the calculation method of the interregional carbon compensation cost based on the theoretical carbon deficit. Additionally, this paper, forecasts the carbon compensation cost among 30 provinces in China from 2017 to 2026 by using the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and the gray prediction model GM (1, 1). Finally, this paper calculates the priority indexes of the carbon compensation among provinces. The results indicate that, first, from 2017 to 2026, the carbon emissions and carbon absorption in 30 provinces in China are generally on the rise, and the increase rate of carbon absorption is less than the increase rate of carbon emissions. Second, from 2017 to 2026, China's carbon compensation cost payment provinces and carbon compensation cost recipient provinces do not change position, and the flow of the carbon compensation cost is stable. The carbon compensation cost payment provinces are mainly located in the central and eastern regions, and the carbon compensation cost recipient provinces are mainly located in the northwestern region. Third, the priority indexes of carbon compensation in China's provinces are all small and declining, and the carbon compensation among regions has little impact on regional economic development. The research results in this paper can provide a reasonable reference for the cost calculation of interregional carbon compensation and the establishment and improvement of an interregional carbon compensation mechanism.

Keywords: Carbon compensation priority index; China; GM (1, 1) model; Interregional carbon compensation; STIRPAT model; Theoretical carbon deficit.