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Coupling Coordination Analysis of Water, Energy, and Carbon Footprints for Wastewater Treatment Plants

Author

Listed:
  • Wei Chen

    (School of Geography and Environment, Shandong Normal University, Jinan 250358, China
    Antai College of Economics & Management, Shanghai Jiao Tong University, Shanghai 200240, China
    This author’s two institutions are co-first institutions.)

  • Yuhui Xie

    (School of Geography and Environment, Shandong Normal University, Jinan 250358, China)

  • Chengxin Wang

    (School of Geography and Environment, Shandong Normal University, Jinan 250358, China)

  • Yong Geng

    (School of International and Public Affairs, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Xueping Tan

    (School of Economics and Management, China University of Mining & Technology, Xuzhou 221116, China)

Abstract

It is urgent for the wastewater treatment sector to respond to global climate change. Although studies related to the water–energy–carbon (WEC) nexus have been widely conducted, the application of the coupling coordination indicator is still limited in the wastewater treatment sector. This study fills such a research gap by linking water footprint (WF), energy footprint (EF), and carbon footprint (CF) together and testing these indicators in 140 wastewater treatment plants (WWTPs) in Shandong province, China. Both the EF and CF of these WWTPs were calculated by conducting hybrid life cycle assessments, while WF was calculated by using a WF method. The results show that gray WF generated from 1 m 3 of wastewater ranged from 9.58 to 12.90 m 3 , while EF generated from 1 m 3 of wastewater ranged from 9.42 × 10 −2 to 0.22 kg oil eq and CF generated from 1 m 3 of wastewater ranged from 0.58 to 1.27 kg CO 2 eq. Also, the total WF, EF, and CF of these WWTPs in Shandong were 4.26 × 10 10 m 3 , 5.32 × 10 8 kg oil, and 3.35 × 10 9 CO 2 eq in 2021, respectively. Key factors contributing to the overall greenhouse gas (GHG) emissions were the on-site GHG emissions and off-site electricity-based GHG emissions. Meanwhile, total nitrogen was the dominant contributor to the gray WF. In addition, the coupling coordination indicators of WF, EF, and CF ranged from 0.7571 to 0.9293. Finally, this study proposed several policy recommendations to improve the overall sustainability of this wastewater treatment sector by considering local realities, including adopting multi-dimensional indicators, decarbonizing current electricity grids, promoting the utilization of renewable energy, and initiating various capacity building efforts.

Suggested Citation

  • Wei Chen & Yuhui Xie & Chengxin Wang & Yong Geng & Xueping Tan, 2025. "Coupling Coordination Analysis of Water, Energy, and Carbon Footprints for Wastewater Treatment Plants," Sustainability, MDPI, vol. 17(6), pages 1-18, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:6:p:2594-:d:1613032
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    References listed on IDEAS

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    1. Wang, Hongtao & Yang, Yi & Keller, Arturo A. & Li, Xiang & Feng, Shijin & Dong, Ya-nan & Li, Fengting, 2016. "Comparative analysis of energy intensity and carbon emissions in wastewater treatment in USA, Germany, China and South Africa," Applied Energy, Elsevier, vol. 184(C), pages 873-881.
    2. Chen, Xin & Zhou, Wenjia, 2022. "Economic and ecological assessment of photovoltaic systems for wastewater treatment plants in China," Renewable Energy, Elsevier, vol. 191(C), pages 852-867.
    3. Zeng, Siyu & Chen, Xing & Dong, Xin & Liu, Yi, 2017. "Efficiency assessment of urban wastewater treatment plants in China: Considering greenhouse gas emissions," Resources, Conservation & Recycling, Elsevier, vol. 120(C), pages 157-165.
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