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A Novel Centralized Allocation Data Envelopment Analysis Model for Carbon Emission Allocation Under a Heterogeneous Abatement Cost: Application Within the Chinese Industrial Sector

Author

Listed:
  • Xiaohong Liu

    (School of Management, Shandong University, Jinan 250100, China)

  • Qingchun Meng

    (School of Management, Shandong University, Jinan 250100, China)

  • Ruiqi Sun

    (The Center for Economic Research, Shandong University, Jinan 250100, China)

  • Xiangwei Zhang

    (School of Management, Shandong University, Jinan 250100, China)

Abstract

This paper presents a mathematical approach to analyzing carbon abatement costs and the allocation of carbon emission allowances in China’s industrial sectors. We utilize input–output data from 30 Chinese provinces between 2009 and 2018 to estimate carbon abatement costs by applying the slack-based measure (SBM) efficiency model and its dual form. The SBM model captures inefficiencies and offers a rigorous framework for measuring abatement costs. Using these costs, we develop a centralized allocation data envelopment analysis (DEA) model, which maximizes sectoral benefits through optimal reallocation. This DEA model is formalized as a linear programming problem, with the aim of determining the efficient allocations of carbon allowances while maintaining the system’s economic productivity. Furthermore, we construct intertemporal, interregional, and spatiotemporal allocation DEA models to examine the dynamics of carbon emission allowance allocation over time, space, and combined spatiotemporal dimensions. These models offer insights into the efficiency of carbon markets under varying conditions. Our proposed new mathematical formulations reveal optimal allocation strategies that can balance emission reductions with industrial productivity. This study also provides novel mathematical frameworks for analyzing the carbon allowance distribution and contributions to both the theory and application of mathematical optimization in environmental policy design. Our findings reveal that China’s industrial carbon abatement costs exhibit significant interprovincial and regional differences. Developed provinces with higher levels of industrial development have higher carbon abatement costs, while provinces with less-developed industrial sectors have lower costs. Under the interregional allocation scenario of carbon emission allowances that consider abatement costs, developed provinces have smaller industrial carbon emission reductions, whereas less-developed provinces have larger reductions. In the intertemporal allocation scenario, provinces with larger industrial economies face greater emission reduction tasks. Under the combined interregional and intertemporal allocation scenario, industrial sectors in coastal developed provinces have lower carbon emission reductions, while those in inland less-developed provinces have higher reductions, mirroring the spatial allocation results of carbon emission allowances.

Suggested Citation

  • Xiaohong Liu & Qingchun Meng & Ruiqi Sun & Xiangwei Zhang, 2024. "A Novel Centralized Allocation Data Envelopment Analysis Model for Carbon Emission Allocation Under a Heterogeneous Abatement Cost: Application Within the Chinese Industrial Sector," Mathematics, MDPI, vol. 12(21), pages 1-27, October.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:21:p:3409-:d:1511266
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    References listed on IDEAS

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    1. Wu, Yinyin & Wang, Ping & Liu, Xin & Chen, Jiandong & Song, Malin, 2020. "Analysis of regional carbon allocation and carbon trading based on net primary productivity in China," China Economic Review, Elsevier, vol. 60(C).
    2. Yu, Anyu & You, Jianxin & Rudkin, Simon & Zhang, Hao, 2019. "Industrial carbon abatement allocations and regional collaboration: Re-evaluating China through a modified data envelopment analysis," Applied Energy, Elsevier, vol. 233, pages 232-243.
    3. Jiang, Ke & Wang, Die & Xu, Liping & Wang, Feng, 2024. "Assessing the impact of carbon quota allocation in enhancing supply chain members emission reduction and advertising efforts," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    4. Wang, Tingsong & Wu, Zehua & Cheng, Peiyue & Wang, Yadong, 2024. "The effect of carbon quota allocation methods on maritime supply chain emission reduction," Transport Policy, Elsevier, vol. 157(C), pages 155-166.
    5. E G Gomes & M P E Lins, 2008. "Modelling undesirable outputs with zero sum gains data envelopment analysis models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 616-623, May.
    6. Lozano, S. & Villa, G. & Brännlund, R., 2009. "Centralised reallocation of emission permits using DEA," European Journal of Operational Research, Elsevier, vol. 193(3), pages 752-760, March.
    7. Zhou, P. & Sun, Z.R. & Zhou, D.Q., 2014. "Optimal path for controlling CO2 emissions in China: A perspective of efficiency analysis," Energy Economics, Elsevier, vol. 45(C), pages 99-110.
    8. Pan, Xunzhang & Teng, Fei & Wang, Gehua, 2014. "Sharing emission space at an equitable basis: Allocation scheme based on the equal cumulative emission per capita principle," Applied Energy, Elsevier, vol. 113(C), pages 1810-1818.
    9. Chu, Junfei & Hou, Tianteng & Li, Feng & Yuan, Zhe, 2024. "Dynamic bargaining game DEA carbon emissions abatement allocation and the Nash equilibrium," Energy Economics, Elsevier, vol. 134(C).
    10. Sueyoshi, Toshiyuki & Li, Aijun & Liu, Xiaohong, 2019. "Exploring sources of China's CO2 emission: Decomposition analysis under different technology changes," European Journal of Operational Research, Elsevier, vol. 279(3), pages 984-995.
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