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Emission path planning based on dynamic abatement cost curve

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  • Guo, Jian-Xin
  • Zhu, Lei
  • Fan, Ying
Abstract
Global climate change is one of the most serious environmental problems that has attracted an unprecedented global attention. The scientific community has recognized that human activity is mostly responsible for global climate warming. Therefore, states participating in the United Nations Framework Convention on Climate Change (UNFCCC) have initiated a series of negotiations on how to develop their own emission reduction targets. However, the realization of these targets is at the expense of economic development to a great extent. Therefore, an abatement plan is necessary to decide how and when to implement emission reduction targets. A marginal abatement cost curve (MACC), often used as an important quantitative tool to estimate abatement burden or evaluate abatement performance, should be considered carefully. In this paper, we enrich the traditional MACC by introducing the concept of an “immediate unit marginal abatement cost” to describe its intrinsic incremental abatement difficulty. This cost is proved to be agreed with the actual situation in many ways, and is therefore very suitable for practical use. Two-factor learning curve are considered in the model, which can go some way in improving the performance of the revised MACC. Using a parameterization method, the original problem can be converted into a tractable nonlinear programming problem. We use an algorithm to search for the approximate global optimal solution. The effectiveness and the efficiency of the algorithm are discussed respectively. In the results, we find that the abatement path distinguishes largely under different abatement targets. Some plausible reasons and policy advices are given.

Suggested Citation

  • Guo, Jian-Xin & Zhu, Lei & Fan, Ying, 2016. "Emission path planning based on dynamic abatement cost curve," European Journal of Operational Research, Elsevier, vol. 255(3), pages 996-1013.
    • Handle: RePEc:eee:ejores:v:255:y:2016:i:3:p:996-1013
    DOI: 10.1016/j.ejor.2016.06.023
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    3. Chenhao Fang & Tieju Ma, 2021. "Technology adoption with carbon emission trading mechanism: modeling with heterogeneous agents and uncertain carbon price," Annals of Operations Research, Springer, vol. 300(2), pages 577-600, May.
    4. Jiang, Hong-Dian & Purohit, Pallav & Liang, Qiao-Mei & Dong, Kangyin & Liu, Li-Jing, 2022. "The cost-benefit comparisons of China's and India's NDCs based on carbon marginal abatement cost curves," Energy Economics, Elsevier, vol. 109(C).
    5. Shuhong Wang & Xiaojing Yi, 2023. "Can the Financial Industry ‘Anchor’ Carbon Emission Reductions?— The Mediating and Moderating Effects of the Technology Market," Energy & Environment, , vol. 34(3), pages 533-559, May.
    6. He, Weijun & Wang, Bo & Danish, & Wang, Zhaohua, 2018. "Will regional economic integration influence carbon dioxide marginal abatement costs? Evidence from Chinese panel data," Energy Economics, Elsevier, vol. 74(C), pages 263-274.
    7. Hui Li & Xianchun Tan & Jianxin Guo & Kaiwei Zhu & Chen Huang, 2019. "Study on an Implementation Scheme of Synergistic Emission Reduction of CO 2 and Air Pollutants in China’s Steel Industry," Sustainability, MDPI, vol. 11(2), pages 1-22, January.
    8. Jiang, Hong-Dian & Purohit, Pallav & Liang, Qiao-Mei & Liu, Li-Jing & Zhang, Yu-Fei, 2023. "Improving the regional deployment of carbon mitigation efforts by incorporating air-quality co-benefits: A multi-provincial analysis of China," Ecological Economics, Elsevier, vol. 204(PA).
    9. Guo, Jian-Xin & Huang, Chen, 2020. "Feasible roadmap for CCS retrofit of coal-based power plants to reduce Chinese carbon emissions by 2050," Applied Energy, Elsevier, vol. 259(C).
    10. Guo, Jian-Xin & Tan, Xianchun & Gu, Baihe & Zhu, Kaiwei, 2022. "Integration of supply chain management of hybrid biomass power plant with carbon capture and storage operation," Renewable Energy, Elsevier, vol. 190(C), pages 1055-1065.
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