The influence of carbon sink trading on carbon emission reduction in agricultural supply chains

IF 0.9 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Tingting Meng, Yukun Cheng, Xujin Pu, Rui Li
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引用次数: 0

Abstract

As global climate change intensifies, the agricultural sector, responsible for over 30% of global greenhouse gas emissions, faces an urgent imperative to mitigate emissions and align with international climate commitments. Carbon sink trading, a market-based mechanism that incentivizes emission reductions through sequestration credits, has emerged as an important tool for accelerating carbon peaking and neutrality goals. This study investigates the influence of carbon sink trading on the strategic interactions between farmers and retailers in agricultural supply chains. Employing differential game theory, we construct three cooperative models: decentralized, Stackelberg leader-follower, and centralized, and derive equilibrium strategies for each using the Hamilton-Jacobi-Bellman framework. Through numerical simulations, we evaluate the influence of carbon sink trading on the emission reduction efforts of farmers and retailers, the extent of emission reductions in the supply chain, and the overall profits. Comparative analysis against baseline scenarios without carbon trading reveals that the integration of carbon sink markets enhances profit margins across all models and improves the level of emission reduction in the agricultural supply chain. In addition, our results show that the centralized model outperforms other configurations, followed by the Stackelberg model, with the decentralized model exhibiting the least effectiveness. These findings provide actionable insights for policymakers and supply chain managers to design carbon trading frameworks that harmonize economic incentives with ecological sustainability.

碳汇交易对农业供应链碳减排的影响
随着全球气候变化加剧,占全球温室气体排放量30%以上的农业部门迫切需要减少排放,并与国际气候承诺保持一致。碳汇交易是一种以市场为基础的机制,通过封存信用额度激励减排,已成为加速实现碳峰值和中和目标的重要工具。本研究探讨碳汇交易对农业供应链中农户与零售商战略互动的影响。运用微分博弈论,构建了分散、Stackelberg领导-追随者和集中式三种合作模型,并利用Hamilton-Jacobi-Bellman框架推导了每种合作模型的均衡策略。通过数值模拟,我们评估了碳汇交易对农民和零售商减排努力、供应链减排程度和整体利润的影响。与没有碳交易的基线情景的比较分析表明,碳汇市场的整合提高了所有模式的利润率,并提高了农业供应链的减排水平。此外,我们的研究结果表明,集中式模型优于其他配置,其次是Stackelberg模型,分散模型的有效性最低。这些发现为决策者和供应链管理者设计协调经济激励与生态可持续性的碳交易框架提供了可行的见解。
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来源期刊
Journal of Combinatorial Optimization
Journal of Combinatorial Optimization 数学-计算机:跨学科应用
CiteScore
2.00
自引率
10.00%
发文量
83
审稿时长
6 months
期刊介绍: The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering. The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.
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