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ORIGINAL RESEARCH article

Front. Energy Res.
Sec. Sustainable Energy Systems
Volume 12 - 2024 | doi: 10.3389/fenrg.2024.1513860
This article is part of the Research Topic Clean Energy and Low-carbon Transportation View all 7 articles

Development of an input-output CGE model for collaborative management of water pollution reduction and carbon mitigation

Provisionally accepted
Jia Wang Jia Wang 1Jun Li Jun Li 1*Yupeng Fu Yupeng Fu 2*Jie Sun Jie Sun 3*Yueqing Yang Yueqing Yang 4*Shuai Su Shuai Su 5*Mengyu Zhai Mengyu Zhai 6*
  • 1 National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Beijing University of Technology, Beijing, China
  • 2 Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Saskatchewan, Canada
  • 3 Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing, Jiangsu Province, China
  • 4 BGRIMM Technology Group, Beijing, Beijing, China
  • 5 State Grid Integrated Energy Group Co.Ltd, Beijing, China
  • 6 Institute of Circular Economy, Beijing University of Technology, Beijing, China

The final, formatted version of the article will be published soon.

    Achieving the dual goals of improving water quality and reducing carbon emissions requires a systematic study of the combined effects of economic and environmental policies on industrial systems. A CGE-IWCR model is developed to examine the long-term evolution of industrial economic and environmental responses in the Yangtze River Economic Belt (YREB) under varying levels of carbon and water pollution taxes. The CGE-IWCE model offers several advantages: i) under the dual tax (carbon and water pollution tax) interventions, it can effectively forecast industrial CO2 and water pollution emissions driven by both macro and local factors from 2025 to 2060; ii) it quantitatively captures the interactions between various policy interventions, thereby providing guidance for comprehensive regional policy formulation. It is discovered that in the double-tax scenario, various combinations of carbon and water pollution taxes significantly impact direct carbon emissions and direct water pollution emissions, and from local consumption, imports, and exports in industrial sectors. Among them, the dual pressure of high carbon and water pollution taxes, which significantly raise production costs. In addition, increasing the carbon tax from 10 ¥/tonne to 50 ¥/tonne, the water pollutant equivalent (WPE) reduction rate rises from 20.79% to 52.67% with the increase in the carbon tax from 2050 to 2060, when the water pollution tax is low. Between 2025 and 2060, the carbon tax plays a significant role in influencing the total industrial output change rate in YREB. from 2025 to 2060, the water pollution tax will play a more significant role in CO2 reduction in YREB's industrial sector. The results will offer decision-making support for water pollution reduction and carbon mitigation in the YREB's industrial sector, quantitatively identify the interactions between the dual taxes, and provide new insights for analyzing the impacts of pollution reduction and carbon mitigation policies.

    Keywords: carbon and water pollution tax, pollution reduction and carbon reduction, CGE model, Yangtze River Economic Belt, eco-environmental policy

    Received: 19 Oct 2024; Accepted: 12 Nov 2024.

    Copyright: © 2024 Wang, Li, Fu, Sun, Yang, Su and Zhai. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Jun Li, National Engineering Laboratory for Advanced Municipal Wastewater Treatment and Reuse Technology, Beijing University of Technology, Beijing, China
    Yupeng Fu, Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Saskatchewan, Canada
    Jie Sun, Nanjing Institute of Environmental Sciences, Ministry of Ecology and Environment, Nanjing, 210042, Jiangsu Province, China
    Yueqing Yang, BGRIMM Technology Group, Beijing, 100160, Beijing, China
    Shuai Su, State Grid Integrated Energy Group Co.Ltd, Beijing, China
    Mengyu Zhai, Institute of Circular Economy, Beijing University of Technology, Beijing, China

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