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Research Article | Open Access

A differential game of transboundary pollution in the upper Yangtze river: Ecological compensation and learning-by-doing in the Chongqing-Sichuan region

Zuliang Lu1,2Mingsong Li1Longzhou Cao1,3( )Junman Li1Zhihui Cao1Zhuran Xiang1
Key Laboratory for Nonlinear Science and System Structure, Chongqing Three Gorges University, Chongqing 404000, China
Research Center for Mathematics and Economics, Tianjin University of Finance and Economics, Tianjin 300222, China
School of Computer Science, Chongqing University, Chongqing 400044, China
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Abstract

This paper investigates a differential game modeling transboundary pollution management in the Upper Yangtze River Basin under noncooperative and cooperative scenarios, incorporating emissions trading, learning-by-doing effects, and abatement investment costs. The maximum principle of optimal control theory was employed to derive equilibrium solutions for both models. Numerical simulations identified optimal emission levels and abatement investments for the Chongqing Municipality and Sichuan Province under each scenario, with the pollution stock trajectories computed using the fourth-order Runge-Kutta method. Numerical validation demonstrated that ecological compensation mechanisms enhance mitigation effectiveness. Furthermore, the study revealed that learning-by-doing efficiency gains and reductions in regional abatement investment costs synergistically enhance both pollution mitigation and economic returns within this framework.

CLC number: 49L20, 91B76

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AIMS Mathematics
Pages 24329-24351

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Cite this article:
Lu Z, Li M, Cao L, et al. A differential game of transboundary pollution in the upper Yangtze river: Ecological compensation and learning-by-doing in the Chongqing-Sichuan region. AIMS Mathematics, 2025, 10(10): 24329-24351. https://doi.org/10.3934/math.20251079

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Received: 23 July 2025
Revised: 17 September 2025
Accepted: 23 September 2025
Published: 24 October 2025
©2025 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)