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The effects of carbon pricing instruments on carbon emission reduction in China’s refining industry: an evolutionary game between heterogeneous refineries

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Abstract

Carbon emissions from the refining industry are receiving increasing national attention. In view of long-term sustainable development, a carbon pricing mechanism oriented to carbon emission reduction needs to be developed. Currently, the two most common carbon pricing instruments are emission trading system and carbon tax. Therefore, it is important to study the carbon emission problems in the refining industry under emission trading system or carbon tax. Based on the current situation of China’s refining industry, this paper constructs an evolutionary game model for backward and advanced refineries to explore which instrument is more effectively applied in the refining industry and identify the effective factors that can promote carbon emission reduction in refineries. According to the numerical results, if the heterogeneity of enterprises is small, the government’s implementation of an emission trading system is the most effective measure, while carbon tax can only ensure that the equilibrium strategy solution is (1,1) when the tax rate is high. If the heterogeneity is large, the carbon tax policy will not have any effect, indicating that government implementation of an emission trading system is more effective than the carbon tax. In addition, there is a positive relationship between carbon price, carbon tax, and refineries’ agreement to carbon emission reduction. Finally, consumers’ preference for low-carbon products, R&D investment level, and R&D spillover effect have nothing to do with carbon emission reduction. Only by reducing refinery heterogeneity and improving the R&D efficiency of backward refineries can all enterprises agree to carbon emission reduction.

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Fig. 1

Source: Energy Information Administration

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Source: Annual Report of CNPC and Sinopec

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Source: China National Bureau of Statistics

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Source: China National Bureau of Statistics

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Not applicable.

Notes

  1. Source: China National Bureau of Statistics.

  2. Source: Energy Information Administration.

  3. Source: Annual Report of CNPC and Sinopec.

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Acknowledgements

The authors are grateful to the editors who provided valuable comments and suggestions to significantly improve the quality of the paper.

Funding

The work was supported by the Research Foundation of China University of Petroleum-Beijing at Karamay (No. XQZX20220012), Karamay Innovative Environment Construction Plan (Soft Science) Project in 2022, by First Class Academic Discipline Construction project of Central University of Finance and Economics: Research on investment and financing decision and operation management of infrastructure in the new era from the perspective of Interdisciplinary, by Financial Sustainable Development Research Team of Central University of Finance and Economics, and by Teaching Reform Project of China University of Petroleum-Beijing at Karamay (JG2022048).

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Authors and Affiliations

  1. School of Economics, Fudan University, Shanghai, 200000, China

    Tianyuan He

  2. School of Management Science and Engineering, Central University of Finance and Economics, Beijing, 100081, China

    Jian Guo

  3. School of Business Administration, China University of Petroleum-Beijing at Karamay, Karamay, 834000, China

    Jian Guo

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  1. Tianyuan He
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Contributions

Tianyuan He and Jian Guo conceived the study and were responsible for the design and development of the evaluation method. Tianyuan He was responsible for the calculation of the numerical simulation. Tianyuan He wrote the following sections of the article: Introduction, Overview of China’s refining industry, Model, Evolutionary game between refineries, and Numerical simulation. Jian Guo wrote the following sections of the article: Literature review, Conclusions, and Recommendations.

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Correspondence to Jian Guo.

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He, T., Guo, J. The effects of carbon pricing instruments on carbon emission reduction in China’s refining industry: an evolutionary game between heterogeneous refineries. Environ Sci Pollut Res 30, 69599–69615 (2023). https://doi.org/10.1007/s11356-023-27327-0

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