Abstract
This paper develops a benchmarking framework to support performance-based sunshine regulation in the water sector. It uses benefit-of-the-doubt composite indicators formulated with a directional distance function. Weight restrictions are incorporated in the model to account for different perspectives in the performance assessment. The framework is tested using data of the Portuguese regulation authority concerning the activity of wastewater operators. The information obtained using this framework reflects overall performance at the firm level and complements traditional evaluations of regulatory authorities based on the analysis of individual indicators. The results can be used to disseminate best practices, motivate continuous improvement, and foster enhancements in the governance of regulated utilities.

Abstract
In this paper, we propose an innovative approach to integrate the wastewater treatment (WWT) that is carried out in a set of plants and the anaerobic digestion (AD) that is carried out in a different set of plants, all from the same system. The aim is to contribute to sustainability improvements (e.g., cost reduction and environmental and social benefits) within the system. The main drivers that support this approach are the existence of unutilized capacity in some digesters and the possibility of reducing the process sludge age to maintain its biogas potential during the aerobic treatment in the plants without AD facilities. Furthermore, the effect of co-digestion as a means of enhancing the amount of biogas that can be produced through the sludge is also considered. This innovative approach leads to a mixed-integer linear programming (MILP) model to optimize the sludge flows that connect the plants without AD facilities to the ones with anaerobic digesters. The developed approach was applied to a Portuguese water utility and the results provide new insights for an optimized sludge management process of WWTPs, also indicating that the economic benefit obtained from the proposed strategy for sludge management can lead to a reduction of up to 23.5% in terms of current energy costs.

Abstract
This paper explores robust unconditional and conditional nonparametric approaches to support performance evaluation in problematic samples. Real-world assessments often face critical problems regarding available data, as samples may be relatively small, with high variability in the magnitude of the observed indicators and contextual conditions. This paper explores the possibility of mitigating the impact of potential outlier observations and variability in small samples using a robust nonparametric approach. This approach has the advantage of avoiding unnecessary loss of relevant information, retaining all the decision-making units of the original sample. We devote particular attention to identifying peers and targets in the robust nonparametric approach to guide improvements for underperforming units. The results are compared with a traditional deterministic approach to highlight the proposed method's benefits for problematic samples. This framework's applicability in internal benchmarking studies is illustrated with a case study within the wastewater treatment industry in Portugal.

Abstract
Wastewater treatment plants constitute an essential part of the sewage system. They have the role of removing pollutants from wastewater to enable the safe disposal of the treated effluent in the natural environment. This research seeks to evaluate plants' efficiency and effectiveness, which involves minimizing energy consumption while obtaining a quality level of the treated water aligned with legislation requirements. We explore two policy scenarios regarding the measurement of effluent quality. The first assumes that pollutants' emission quotas (EQs) are fixed at each plant. The second assumes that quotas are set for the receiving waters (e.g., river or watercourse in the natural environment) so that trade-offs in EQs among plants sharing the same discharge site are possible. This latter scenario requires a system-wide analysis to identify optimal targets for pollutants removal at each plant that allow fulfilling the expected average quality levels of the effluent discharged. This paper develops a methodology to fully realize the potential for energy savings based on an innovative mixed-integer linear programming model. This model follows the data envelopment analysis axioms to estimate the frontier of the production possibility set. The approach proposed is tested in a real-world context using the plants of a Portuguese water company. The results show that the two scenarios combining efficiency and effectiveness perspectives have advantages in terms of energy savings compared to the conventional situation focused only on efficiency gains. The saving potential is slightly higher in the scenario allowing reallocation of EQs among plants.