Given the increasing importance of the wastewater sector in terms of energy usage, the understanding of the level of energy efficiency of wastewater treatment plants (WWTPs) is useful to both the industry itself as well as policy makers. Here, based on economic foundations, we apply a Stochastic Frontier Analysis (SFA) approach for energy demand modelling to estimate energy efficiency in the wastewater sector. Using specific SFA models and panel data from 183 Swiss WWTPs over the period 2001 to 2015, the paper illustrates that distinguishing between persistent and transient inefficiency is essential to deduce appropriate energy efficiency diagnosis in WWTPs. In this respect, persistent energy inefficiency is found to be more severe than transient energy inefficiency. Furthermore, it is shown that the age of the equipment influences the demand for energy and the energy savings due to technological innovation are quantified. Finally, economies of output density and scale are estimated demonstrating that for plants operating below optimal scale significant energy savings can be achieved if plants would be operated at higher size. Instead, our analysis reveals also that for plants larger than 100000 Population Equivalent, at least from an energy efficiency point of view, it would be no more beneficial to increase their scale.

中文翻译：

---

基于经济基础的废水部门的瞬态和持续能效

鉴于污水处理部门在能源使用方面的重要性日益增加，了解污水处理厂 (WWTP) 的能效水平对行业本身和政策制定者都有帮助。在这里，基于经济基础，我们将随机前沿分析 (SFA) 方法应用于能源需求建模，以估计废水部门的能源效率。本文使用 2001 年至 2015 年期间来自 183 个瑞士污水处理厂的特定 SFA 模型和面板数据，说明区分持续性和暂时性低效率对于推断适当的污水处理厂能效诊断至关重要。在这方面，发现持续的能源效率低下比瞬时能源效率低下更严重。此外，结果表明，设备使用年限影响能源需求，量化技术创新带来的节能效果。最后，对输出密度和规模经济的估计表明，对于在最佳规模以下运行的工厂，如果工厂以更大的规模运行，则可以实现显着的节能。相反，我们的分析还表明，对于大于 100000 人口当量的工厂，至少从能源效率的角度来看，扩大规模将不再有利。