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Circular economy has become a very popular item in the last decades in many fields. Particularly, in the water and wastewater sector, since a lot of pressure has been put on water resources. Although the main target of the application of circular economy in this sector has been waste management, the current research intends to extend its application to other aspects. In this sense, it is highlighted the role that asset management could play in wastewater treatments plants extending the useful life of the equipment and the facilities, and how it could contribute to the circular economy, measuring the impact in economic and environmental terms. Making use of the Analytical Hierarchy Process (AHP) it can be observed that maintenance tasks are one of the most important factors to avoid equipment deterioration. This research offers valuable results that will be useful to assess the condition of the equipment helping the decision-makers to optimize the maintenance tasks and plan replacement strategies that will lead to accomplishing the principles of circular economy, increasing the service life span of the equipment, and reducing the repairing costs, and minimizing the environmental impact associated to the replacement of the equipment., Competing Interests: Declaration of competing interest The authors of the manuscript, entitled THE BENEFITS OF CIRCULAR ECONOMY STRATEGIES IN URBAN WATER FACILITIES, whose names are listed immediately below certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria, educational grants, participation in speakers' bureaus, membership, employment, consultancies, stock ownership, or other equity interest, and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The present work analyses the existence of congestion in a set of wastewater treatment plants (WWTPs) for the first time. The study sample included 47 WWTPs managed by the same operator and located in the Valencia region (eastern Spain). The method of analysis consisted in applying a new statistical model to identify and correct congestion situations based on data envelopment analysis (DEA), which takes into account undesirable outputs and multiple projections. The results showed a strong concentration of congested WWTPs (48.94-57.45%). Furthermore, the necessary corrections to avoid the congestion statuses entailed an average input reduction between 57.03 and 74.13% and an average increase in desirable outputs between 46.08% and 50.08%. In addition, only plant size had a significant relationship with the correction levels. The remaining contextual variables (age, overcapacity and type of water and sludge line) failed to show any significant impact on those corrections. To conclude, policy recommendations to improve the management of WWTPs are put forward, notably improving the management of smaller plants, which concentrate the largest percentage of correction.

The current literature about pharmaceutical and personal care compounds (PPCPs) focuses on identifying their concentration and toxicological risk both in surface water and in wastewater. However, the influence of urban areas (population ageing, income level, hospitals and others) has not yet been analysed. Knowing how a population (and its facilities) affects PPCPs' presence in wastewater is important to identify the conditions that are responsible for their presence. In this work, the influence of water consumption, population ageing, income level, hospitals and nursing homes on the anti-inflammatory concentration have been analysed. To fill the gap between the quantitative data on PPCPs' concentration and the qualitative reasoning of the influence of urban areas on the anti-inflammatory concentration, the use of fuzzy-set qualitative comparative analysis (fsQCA) is proposed. The fsQCA results are presented as recipes that show the different causal combinations of conditions that explain the presence of anti-inflammatories in wastewater. Using fsQCA for urban wastewater management with the aim of explaining the presence of anti-inflammatories in wastewater treatment plants (WWTPs) is a novelty in the literature. The results obtained here show the influence of water consumption (WATCON), hospitals (HOSP) and population ageing (POPAG) as the main conditions for the anti-inflammatory concentration in Valèncian wastewater. Specifically, these conditions are present in all the recipes obtained with consistency of 99%. Through the results obtained, it would be possible to identify that HOSP are the main facilities that discharge anti-inflammatories into urban wastewater. Hence, the necessity of preventive measures to avoid the anti-inflammatory discharge into water bodies has been showed. Furthermore, under a methodological point of view, this work highlights the eligibility of fsQCA as a wastewater cycle management tool., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The water cycle, from catchment to discharge, is a sector that involves an important investment and operation and maintenance costs. In particular, sewage treatment is a challenge for governments because they are having to consider economic, environmental, and social aspects. Within the European Union, implementation of Directive 91/271/EEC is responsible for the location of wastewater treatment facilities in the territory, due to the requirement that all urban areas must have this infrastructure to reduce the environmental impact of treated water in water bodies. Different sizes of municipalities affect the design of each wastewater treatment plant (WWTP) and cause variations in the operation process. The presence of scale economies in this sector has a significant influence on the efficiency of the wastewater treatment process and has a direct impact on the operational costs. Based on the pursuit of economic and environmental efficiency, this analysis extends the scope of the current literature because it recommends a specific, population equivalent (p.e.) range for which it would be suitable to achieve efficiency in wastewater treatment facilities-shedding light on the open debate about scale economies in WWTPs., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Understanding the energy cost structure of wastewater treatment plants is a relevant topic for plant managers due to the high energy costs and significant saving potentials. Currently, energy cost models are generally generated using logarithmic, exponential or linear functions that could produce not accurate results when the relationship between variables is highly complex and non-linear. In order to overcome this issue, this paper proposes a new methodology based on machine-learning algorithms that perform better with complex datasets. In this paper, machine learning was used to generate high-performing energy cost models for wastewater treatment plants, using a database of 317 wastewater treatment plants located in north-west Europe. The most important variables in energy cost modelling were identified and for the first time, the energy price was used as model parameter and its importance evaluated., (Copyright © 2018. Published by Elsevier Ltd.)

Operational parameters of the wastewater treatment process do not always fit the design ones for several reasons, such as the seasonality or an inaccurate estimation of the population connected. This fact has an effect on the performance of the Wastewater Treatment Plants (WWTPs) and their energy costs. The aim of this paper is to develop a cost function for the energy cost that takes into account the mismatching between the design and the operational inflow. For this purpose, a performance index is constructed in order to represent how far the operational inflow is from the design one, and will be included in the cost model. Moreover, three cost functions, depending on the size of the plants are developed in order to provide the managers of the WWTPs with valuable information that could be used to optimise the wastewater treatment process., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

The selection of the most appropriate wastewater treatment (WWT) technology is a complex problem since many alternatives are available and many criteria are involved in the decision-making process. To deal with this challenge, the analytic network process (ANP) is applied for the first time to rank a set of seven WWT technology set-ups for secondary treatment in small communities. A major advantage of ANP is that it incorporates interdependent relationships between elements. Results illustrated that extensive technologies, constructed wetlands and pond systems are the most preferred alternatives by WWT experts. The sensitivity analysis performed verified that the ranking of WWT alternatives is very stable since constructed wetlands are almost always placed in the first position. This paper showed that ANP analysis is suitable to deal with complex decision-making problems, such as the selection of the most appropriate WWT system contributing to better understand the multiple interdependences among elements involved in the assessment., (Copyright © 2015 Elsevier B.V. All rights reserved.)

The assessment of productivity change of wastewater treatment plants (WWTPs) is essential to improve the performance over time of the facilities evaluated. This study assessed and compared the productivity growth of WWTPs operating with non-homogeneous technologies. The metafrontier Malmquist productivity index (MMPI) was computed for a sample of 99 WWTPs encompassing 4 alternative technologies: activated sludge (AS), aerated lagoon (AL), trickling filter (TF) and rotating biological contactor (BD). The results indicated that, on average, WWTPs with AS and BD exhibited better performance over time than WWTPs with AL and TF. The MMPI indicates that, over the period 2007-2009, the productivity rose by 0.9% and 0.3% for AS and BD technologies, respectively, whilst for the AL and TF processes, the productivity decreased by 0.5% and 2.2%, respectively. The decomposition of the MMPI into efficiency change (EC) and technical change (TC) illustrated that EC was a positive driver of productivity change for WWTPs that use AS, whilst TC contributed positively to the productivity growth of WWTPs using AL and BD. Several policy implications to help managers make informed decisions were drawn from our empirical analysis., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Abstract: In light of the growing importance of water reuse as an alternative source of water resources in many regional areas, the objective of this paper is to analyse the efficiency of wastewater treatment plants as a basic requisite to improve the potential of the water reuse. The analytical benchmarking methodology Data Envelopment Analysis (DEA) is used to calculate efficiency measurements. An efficiency index is obtained for each plant by means of mathematical programming techniques, aiming to minimise the inputs used in the water treatment process. This indicator is used as a reference to analyse plants'' activity through a series of variables including the size of the plant or its cost structure. Given the importance of wastewater treatment in the Valencia Region (Spain), empirical research has been carried out for 338 plants located in this area. We verify the fact that the largest plants run more efficiently than smaller plants, as was to be expected. At the same time, there is evidence that a series of representative variables in the treatment process are clearly linked to efficiency. Maintenance and waste management costs are the most important factors to explain the differences between plants in terms of efficiency. Finally, the benchmarking methodology (Data Envelopment Analysis) is confirmed as a very useful management tool for the study of wastewater sector. [Copyright &y& Elsevier]

Wastewater treatment plants (WWTPs) are aging and its effects on the process are more evident as time goes by. Due to the deterioration of the facilities, the efficiency of the treatment process decreases gradually. Within this framework, this paper proves the increase in the energy consumption of the WWTPs with time, and finds differences among facilities size. Accordingly, the paper aims to develop a dynamic energy cost function capable of predicting the energy cost of the process in the future. The time variable is used to introduce the aging effects on the energy cost estimation in order to increase the accuracy of the estimation. For this purpose, the evolution of energy costs will be assessed and modelled for a group of WWTPs using the methodology of cost functions. The results will be useful for the managers of the facilities in the decision making process. [ABSTRACT FROM AUTHOR]