Assessment of carbon efficiency in wastewater treatment plants through Stochastic non-parametric data envelopment analysis (StoNED): Insights from Spanish facilities

Abstract

Evaluating the carbon efficiency (CE) of wastewater treatment plants (WWTPs) is crucial for guiding these facilities towards carbon neutrality. Nevertheless, enhancing carbon performance ought not to be pursued to the detriment of pollutant removal efficiency. In this study, the CE of WWTPs is calculated as a composite index that integrates carbon emissions with the volume of pollutants removed from wastewater, including organic matter, suspended solids, nitrogen, and phosphorus. To achieve this, the Stochastic Non-parametric Envelopment of Data (StoNED) method is employed. This approach, distinct from the commonly used Data Envelopment Analysis (DEA), accounts for both empirical data and random variations in the estimation of CE, thereby enhancing the reliability of the CE evaluation. The study assesses the CE of 109 Spanish WWTPs, finding that none of them are fully carbon efficient. This involves that all plants have potential to reduce greenhouse gas emissions without sacrificing pollutant removal efficiency. The average CE of the WWTPs is 0.529, indicating a possible reduction in carbon emissions by approximately 0.076 kg of CO2 equivalent per cubic meter of wastewater treated. The analysis also reveals that neither the volume of wastewater treated nor the type of reactor used for secondary treatment has a significant impact on the CE of the facilities. The CE metric proposed in this study serves as an important decision-support tool for advancing towards the carbon neutrality of wastewater treatment processes. By providing a more comprehensive understanding of the environmental performance of WWTPs, it helps identifying areas for improvement and guiding policy and operational decisions.