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Energy efficiency evaluation of wastewater treatment plants (WWTPs) based on data envelopment analysis

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  • Yang, Junwen
  • Chen, Bin

Abstract

The energy use intensity of wastewater treatment facilities has been increasing in recent decades in China. In this paper, data envelopment analysis is used to evaluate the energy efficiency of municipal wastewater treatment plants (WWTPs) in China. In the DEA model, the six input indicators were load rate, design scale, unit electricity consumption, sludge generation, actual treatment volume and accumulated electricity consumption, and the six outputs were COD, BOD, SS, NH3-N, TN and TP pollutant removals per amount of electricity consumption. A total of 4100 plants were assessed in China in 2018. The relative efficiencies of 14 plants at 1.0, with an average electricity consumption of 0.091 kWh/m3 compared to the national average consumption of 0.38 kWh/m3, served as a benchmark for the remaining inefficient plants. According to the Malmquist index results, during 2014–2018, on average, 40.54% of the WWTPs experienced productivity improvements, 71.24% of the plants increased their technical efficiency relative to the frontier, and 27.21% of the plants showed progress on the production frontier. Western areas in China consume a large proportion of renewable energy with higher energy efficiency levels, while central and eastern areas had lower energy efficiency trends and high pollutant emissions levels. The oxidation pond method has the highest comprehensive technical efficiency of 0.446, nearly eight times the average efficiency level. It is suggested that wastewater treatment industries should not only consider technical efficiency increases but also match their pollutant burdens and implementation of discharge standards with energy-saving targets.

Suggested Citation

  • Yang, Junwen & Chen, Bin, 2021. "Energy efficiency evaluation of wastewater treatment plants (WWTPs) based on data envelopment analysis," Applied Energy, Elsevier, vol. 289(C).
    • Handle: RePEc:eee:appene:v:289:y:2021:i:c:s0306261921002099
    DOI: 10.1016/j.apenergy.2021.116680
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    Citations

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    Cited by:

    1. 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.
    2. Liu, Runxi & Huang, Runyao & Shen, Ziheng & Wang, Hongtao & Xu, Jin, 2021. "Optimizing the recovery pathway of a net-zero energy wastewater treatment model by balancing energy recovery and eco-efficiency," Applied Energy, Elsevier, vol. 298(C).
    3. Yin, Sihua & Yang, Haidong & Xu, Kangkang & Zhu, Chengjiu & Zhang, Shaqing & Liu, Guosheng, 2022. "Dynamic real–time abnormal energy consumption detection and energy efficiency optimization analysis considering uncertainty," Applied Energy, Elsevier, vol. 307(C).
    4. Junghyun Park & Jae Leame Yoo & Jongsik Yu, 2021. "Effect of Hotel Air Quality Management on Guests’ Cognitive and Affective Images and Revisit Intentions," IJERPH, MDPI, vol. 18(17), pages 1-13, September.
    5. Xiong, Yu-Tong & Zhang, Jing & Chen, You-Peng & Guo, Jin-Song & Fang, Fang & Yan, Peng, 2021. "Geographic distribution of net-zero energy wastewater treatment in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    6. Ewelina Płuciennik-Koropczuk & Sylwia Myszograj & Mirosław Mąkowski, 2022. "Reducing CO 2 Emissions from Wastewater Treatment Plants by Utilising Renewable Energy Sources—Case Study," Energies, MDPI, vol. 15(22), pages 1-14, November.
    7. Huang, Runyao & Shen, Ziheng & Wang, Hongtao & Xu, Jin & Ai, Zisheng & Zheng, Hongyuan & Liu, Runxi, 2021. "Evaluating the energy efficiency of wastewater treatment plants in the Yangtze River Delta: Perspectives on regional discrepancies," Applied Energy, Elsevier, vol. 297(C).
    8. Lin, Chihao & Xiao, Xiangmin & Li, Yu-You & Liu, Jianyong, 2023. "Evaluation of the economic and environmental benefits of partial nitritation anammox and partial denitrification anammox coupling preliminary treatment in mainstream wastewater treatment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    9. Liu, Lingchi & Zhang, Xiaohong & Lyu, Yanfeng, 2022. "Performance comparison of sewage treatment plants before and after their upgradation using emergy evaluation combined with economic analysis: A case from Southwest China," Ecological Modelling, Elsevier, vol. 472(C).
    10. Salman, Muhammad & Long, Xingle & Wang, Guimei & Zha, Donglan, 2022. "Paris climate agreement and global environmental efficiency: New evidence from fuzzy regression discontinuity design," Energy Policy, Elsevier, vol. 168(C).
    11. Esra Kalya & Alper Alver, 2023. "Determining the contribution of the wastewater treatment plant to the sustainable environment with water footprint indicators," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(11), pages 12999-13014, November.
    12. Sylwia Myszograj & Dariusz Bocheński & Mirosław Mąkowski & Ewelina Płuciennik-Koropczuk, 2021. "Biogas, Solar and Geothermal Energy—The Way to a Net-Zero Energy Wastewater Treatment Plant—A Case Study," Energies, MDPI, vol. 14(21), pages 1-15, October.

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