Energy efficiency evaluation of wastewater treatment plants: A methodological proposal for its benchmarking

IF 4.9 2区 环境科学与生态学 Q1 ENVIRONMENTAL SCIENCES
Ramon Sala-Garrido , Manuel Mocholi-Arce , Alexandros Maziotis , Maria Molinos-Senante
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Abstract

To evaluate the energy performance of wastewater treatment plants (WWTPs), reliable, robust and holistic methods are needed. The data envelopment analysis (DEA) method, which allocates a flexible set of weights to input and output variables, has previously been used to benchmark the energy efficiency (EE) of WWTPs. However, this methodological approach suffers from discriminatory power, which makes it difficult to rank WWTPs and compare their performances because the EE scores are estimated under nonhomogeneous conditions. To overcome these limitations and to better understand the water-energy nexus, in this study, the EE of a sample of WWTPs was evaluated by allocating common weights to variables for all WWTPs in a DEA model (DEA-CSW). Evaluated WWTPs were shown to have a poor energetic performance, with an average EE score of 0.372. This means that WWTPs could save 62.8 % of their current energy use. Potential energy savings were estimated to be 118,206,789 kWh/year, which is equivalent to 29,552 tons of CO2eq/year. Based on a DEA-CSW approach, only one WWTP was identified as energy efficient; therefore, it is the best performer among the assessed WWTPs. Significant differences in the weights allocated to energy and pollutants removed from wastewater were reported by the DEA-CSW and DEA allocating flexible weights. Hence, under the latter methodological approach, some relevant variables, from the functionality perspective of WWTPs, were ignored in the EE assessment. This study demonstrates the relevance of using suitable methods to benchmark the energy performance of WWTPs to avoid misleading conclusions therefore, avoiding misguided regulatory decisions.
污水处理厂能效评估:制定基准的方法建议
要评估污水处理厂(WWTP)的能源绩效,需要可靠、稳健和全面的方法。数据包络分析(DEA)方法为输入和输出变量分配了一套灵活的权重,以前曾被用于评估污水处理厂的能源效率(EE)。然而,由于 EE 分数是在非同质条件下估算的,因此这种方法存在歧视性,难以对污水处理厂进行排序和比较其绩效。为了克服这些局限性,并更好地理解水与能源之间的关系,本研究通过在 DEA 模型(DEA-CSW)中为所有污水处理厂的变量分配共同权重,对样本污水处理厂的 EE 进行了评估。结果表明,接受评估的污水处理厂的能效表现较差,平均能效指数为 0.372。这意味着污水处理厂目前的能源使用量可节省 62.8%。据估计,潜在的能源节约量为 118,206,789 千瓦时/年,相当于 29,552 吨二氧化碳/年。根据 DEA-CSW 方法,只有一家污水处理厂被认定为节能型污水处理厂;因此,它是接受评估的污水处理厂中表现最好的一家。据报告,DEA-CSW 和分配灵活权重的 DEA 在分配给能源和从废水中去除污染物的权重方面存在显著差异。因此,在后一种方法中,从污水处理厂的功能角度来看,一些相关变量在能源效率评估中被忽略了。这项研究表明,使用合适的方法对污水处理厂的能源绩效进行基准测试具有重要意义,可避免得出误导性结论,从而避免做出错误的监管决定。
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来源期刊
Environmental Science & Policy
Environmental Science & Policy 环境科学-环境科学
CiteScore
10.90
自引率
8.30%
发文量
332
审稿时长
68 days
期刊介绍: Environmental Science & Policy promotes communication among government, business and industry, academia, and non-governmental organisations who are instrumental in the solution of environmental problems. It also seeks to advance interdisciplinary research of policy relevance on environmental issues such as climate change, biodiversity, environmental pollution and wastes, renewable and non-renewable natural resources, sustainability, and the interactions among these issues. The journal emphasises the linkages between these environmental issues and social and economic issues such as production, transport, consumption, growth, demographic changes, well-being, and health. However, the subject coverage will not be restricted to these issues and the introduction of new dimensions will be encouraged.
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