Most human activities that use water produced sewage. As urbanization grows, the overall demand for water grows. Correspondingly, the amount of produced sewage and pollution-induced water shortage is continuously increasing worldwide. Ensuring there are sufficient and safe water supplies for everyone is becoming increasingly challenging. Sewage treatment is an essential prerequisite for water reclamation and reuse. Sewage treatment plants' (STPs) performance in terms of economic and environmental perspective is known as a critical indicator for this purpose. Here, the window-based data envelopment analysis model was applied to dynamically assess the relative annual efficiency of STPs under different window widths. A total of five STPs across Malaysia were analyzed during 2015-2019. The labor cost, utility cost, operation cost, chemical consumption cost, and removal rate of pollution, as well as greenhouse gases' (GHGs) emissions, all were integrated to interpret the eco-environmental efficiency. Moreover, the ordinary least square as a supplementary method was used to regress the efficiency drivers. The results indicated the particular window width significantly affects the average of overall efficiencies; however, it shows no influence on the ranking of STP efficiency. The labor cost was determined as the most influential parameter, involving almost 40% of the total cost incurred. Hence, higher efficiency was observed with the larger-scale plants. Meanwhile, the statistical regression analysis illustrates the significance of plant scale, inflow cBOD concentrations, and inflow total phosphorus concentrations at [Formula: see text] on the performance. Lastly, some applicable techniques were suggested in terms of GHG emission mitigation.
Keywords: Data envelopment analysis (DEA); Greenhouse gases emissions; Ordinary least square; Sewage treatment; Technical efficiency.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.