<p>The evaluation of energy efficiency in wastewater treatment plants (WWTPs) is essential for improving operational management, reducing energy consumption, and mitigating emissions. In this study, the energy efficiency of WWTPs in Jiangsu Province, China, was assessed using three-stage data envelopment analysis (DEA), and the results were compared with those from other provinces. Tobit regression analysis was also performed to explore the key factors affecting energy efficiency. The results revealed that energy efficiency in Jiangsu’s WWTPs was generally at a low level (&lt; 0.26), with only two plants achieving an efficiency score of 1. Scale efficiency was at a relatively high level (&gt; 0.69), but technical efficiency was at a lower level (&gt; 0.33), contributing to the low level of overall efficiency. Compared with the other provinces, Jiangsu (0.241) exhibited moderate performance, with Zhejiang (0.403) and Shanghai (0.387) ranking higher, while Yunnan had the lowest (0.208). Factors influencing efficiency included technology type, treatment volume, plant age, and pollutant removal rate. Anaerobic–anoxic–oxic technology had a moderate level of efficiency but was less effective than were rotating biological contactors and anaerobic–oxic technologies. Energy efficiency levels decreased with increasing treatment scale and plant age but improved with increasing pollutant removal rates in plants meeting the Class I-B standard. This study provides a novel application of three-stage DEA in evaluating the energy efficiency of WWTPs and offers valuable insights to support more energy-efficient operational and management practices.</p>

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Evaluation of the energy efficiency of urban wastewater treatment plants based on three-stage data envelopment analysis (DEA)

  • Yunqi Tang,
  • Xiaohui Cheng,
  • Li Ge,
  • Qingmiao Yu,
  • Jinju Geng

摘要

The evaluation of energy efficiency in wastewater treatment plants (WWTPs) is essential for improving operational management, reducing energy consumption, and mitigating emissions. In this study, the energy efficiency of WWTPs in Jiangsu Province, China, was assessed using three-stage data envelopment analysis (DEA), and the results were compared with those from other provinces. Tobit regression analysis was also performed to explore the key factors affecting energy efficiency. The results revealed that energy efficiency in Jiangsu’s WWTPs was generally at a low level (< 0.26), with only two plants achieving an efficiency score of 1. Scale efficiency was at a relatively high level (> 0.69), but technical efficiency was at a lower level (> 0.33), contributing to the low level of overall efficiency. Compared with the other provinces, Jiangsu (0.241) exhibited moderate performance, with Zhejiang (0.403) and Shanghai (0.387) ranking higher, while Yunnan had the lowest (0.208). Factors influencing efficiency included technology type, treatment volume, plant age, and pollutant removal rate. Anaerobic–anoxic–oxic technology had a moderate level of efficiency but was less effective than were rotating biological contactors and anaerobic–oxic technologies. Energy efficiency levels decreased with increasing treatment scale and plant age but improved with increasing pollutant removal rates in plants meeting the Class I-B standard. This study provides a novel application of three-stage DEA in evaluating the energy efficiency of WWTPs and offers valuable insights to support more energy-efficient operational and management practices.