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Wastewater-based epidemiology is a promising tool to anticipate potential viral outbreaks not only at city-scale but also at precincts-scale or even buildings.

During the last three years, various restrictions have been set up to limit the transmission of the Coronavirus Disease (COVID-19). While these rules apply at a large scale (e.g., country-wide level) human-to-human transmission of the virus that causes COVID-19, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), occurs at a small scale. Different preventive policies and testing protocols were implemented in buildings where COVID-19 poses a threat (e.g., elderly residences) or constitutes a disruptive force (e.g., schools). In this study, we sampled sewage from different buildings (a school, a university campus, a university residence, and an elderly residence) that host residents of different levels of vulnerability. Our main goal was to assess the agreement between the SARS-CoV-2 concentration in wastewater and the policies applied in these buildings. All buildings were sampled using passive samplers while 24 h composite samples were also collected from the elderly residence. Results showed that passive samplers performed comparably well to composite samples while being cost-effective to keep track of COVID-19 prevalence. In the elderly residence, the comparison of sampling protocols (passive vs. active) combined with the strict clinical testing allowed us to compare the sensitivities of the two methods. Active sampling was more sensitive than passive sampling, as the former was able to detect a COVID-19 prevalence of 0.4 %, compared to a prevalence of 2.2 % for passive sampling. The number of COVID-19-positive individuals was tracked clinically in all the monitored buildings. More frequent detection of SARS-CoV-2 in wastewater was observed in residential buildings than in non-residential buildings using passive samplers. In all buildings, sewage surveillance can be used to complement COVID-19 clinical testing regimes, as the detection of SARS-CoV-2 in wastewater remained positive even when no COVID-19-positive individuals were reported. Passive sampling is useful for building managers to adapt their COVID-19 mitigation policies.

Altres ajuts: acords transformatius de la UAB Borja Solís is grateful for the PIF PhD grant funded by Universitat Autònoma de Barcelona. Nitrous oxide (NO) is a greenhouse gas (GHG) emitted during biological nitrogen removal from wastewater treatment plants (WWTPs). Some modelling tools have been proposed to predict NO emissions during the design and operation of WWTPs. In this study, the novel ASM2d-NO model, which accounts for the production of NO in nutrient removal WWTPs, was used to study the associated emissions from a full-scale WWTP with two independent lines. Firstly, the hydraulics of the WWTP was characterized by a residence time distribution test, showing the flow was equally divided into the two treatment lines (49.3 vs. 50.7%), that each reactor worked as an ideal continuous stirred tank reactor and the secondary settler model flux was similar to a plug-flow reactor. The ASM2d-NO model was then calibrated using experimental data obtained under dynamic conditions. A global sensitivity analysis was used to select, among 59 model parameters, five candidates that resulted to be related to nitrifying organisms. Different parameter subsets up to four parameters were evaluated, being the subset [µ, q, K, K] the best, achieving 53.3% reduction of the calibration cost function. The model fit obtained provided a reasonably description of nutrients and NO emission trends, considering the inherent operational variability suffered in full-scale WWTPs. Finally, a simulation-based study showed that, for the given WWTP and operational conditions, an unbalanced distribution of flow-rate between the two treatment lines did not result in a significant increase on NO emissions. The results obtained show that this model can be a suitable tool for predicting NO emissions in full-scale WWTPs, and can therefore be used to find operational conditions that help to minimise these emissions.

Wastewater-based epidemiology (WBE) can be a useful complementary approach to assess human exposure to poten-tially harmful chemicals, including those from personal care and household products. In this work, a fully automated multiresidue method, based on on-line solid-phase extraction liquid chromatography - tandem mass spectrometry, was developed for the determination of 27 biomarkers of human exposure to selected chemicals from personal care and household products, including parabens, UV filters, phthalates and alternative plasticizers, phosphorous flame retardants/plasticizers (PFRs), and bisphenols. These biomarkers include both the parent compounds and their human metabolites. In addition, two oxidative stress biomarkers, 8-epi-prostaglandin F2 alpha and 4-hydroxy nonenal mercapturic acid, were also considered in the study. The method was carefully optimized to tackle the challenges of analyzing compounds with different physico-chemical properties in a highly complex raw wastewater matrix, while model experiments were performed to investigate filtration losses and analyte stability. The applicability of the devel-oped method was tested by analyzing raw wastewater from four European cities: Antwerp, Brussels (Belgium), Girona (Spain), and Zagreb (Croatia). Twenty-one biomarkers (10 parent compounds and 11 metabolites) were detected in all analyzed wastewater samples. The parent compounds with the highest mass loads were PFRs, parabens, and bisphenol S, while phthalate monoesters were the most prominent metabolites. The mass loads of most compounds were quite similar across cities, but geographic differences were observed for some biomarkers, such as metabolites of phthalates and alternative plasticizers. Exposure was then assessed for seven substances for which quantitative urinary excretion data are known. Our results indicate that safe reference values were exceeded for several contaminants, including bu-tylated phthalates, bisphenol A, and tris(2-butoxyethyl) phosphate, particularly for toddlers. With this relatively sim-ple method, which requires less sample manipulation, it is possible to promptly identify and monitor exposure to harmful chemicals at the population level using the WBE approach.

Wastewater based epidemiology was employed to track the spread of SARS-CoV-2 within the sewershed areas of 10 wastewater treatment plants (WWTPs) in Catalonia, Spain. A total of 185 WWTPs inflow samples were collected over the period consisting of both the first wave (mid-March to June) and the second wave (July to November). Concentrations of SARS-CoV-2 RNA (N1 and N2 assays) were quantified in these wastewaters as well as those of Human adenoviruses (HAdV) and JC polyomavirus (JCPyV), as indicators of human faecal contamination. SARS-CoV-2 N gene daily loads strongly correlated with the number of cases diagnosed one week after sampling i.e. wastewater levels were a good predictor of cases to be diagnosed in the immediate future. The conditions present at small WWTPs relative to larger WWTPs influence the ability to follow the pandemic. Small WWTPs (, This work was partially funded by the projects PCI2019-103643, RTI2018-097346-B-I00, and AGL2017-86797-C2-1-R projects, all funded by the Spanish Ministry of Science, Innovation and Universities. S. Bofill-Mas is a Serra-Hunter fellow at the University of Barcelona. This study is performed with partial support from the Water Research Institute of the University of Barcelona. IDAEA-CSIC is a Centre of Excellence Severo Ochoa (Spanish Ministry of Science and Innovation, Project CEX2018-000794-S). ICRA authors acknowledge the support from the Economy and Knowledge Department of the Catalan Government through Consolidated Research Group (ICRA-ENV 2017 SGR 1124). ICRA is part of the CERCA program. We would like to give a big thanks to our families and colleagues, for their support and help behind the scenes.

Current practice to enhance resilience in Water Resource Recovery Facilities (WRRFs) is to ensure redundancy or back-up for most critical equipment (e.g. pumps or blowers). Model-based assessment allows evaluation of different strategies for quantitatively and efficiently enhancing resilience and justifying the allocation of resources. The goal of this study is to provide guidance for the development of tailored deterministic models of full-scale WRRFs. A framework for model-based resilience assessment is proposed that provides guidance on data collection, model selection, model calibration and scenario analysis. The framework is embedded into the Good Modeling Practice (GMP) Unified Protocol, providing a new application for resilience assessment and an initial set of stressors for WRRFs. The usefulness of the framework is illustrated through a resilience assessment of the WRRF of Girona against power outage. Results show that, for the Girona facility, limited energy back-up can cause non-compliance of WRRF discharge limits in the case of a blower power shut-down of 6 h, and around 12 h when the blower shut-down is also combined with a shut-down of the recirculation pumps. The best option to enhance resilience would be increasing the power back-up by 218%, which allows the plant to run with recirculation pumps and blowers at minimum capacity. In such a case, resilience can be further enhanced by manipulating the air supply valves to optimise the air distribution, to balance oxygen needs in each reactor with the overall system pressure. We conclude that, with industry consensus on what is considered an acceptable level of resilience, a framework for resilience assessment would be a useful tool to enhance the resilience of our current water infrastructure. Further research is needed to establish if the permit structure should accommodate levels sof functionality to account for stress events.

Current trends point to tourism as a growing economic sector for many communities worldwide with possible environmental implications including water use. One solution for these communities is water reuse, which not only has been shown to minimize potable water consumption but also other environmental impacts. Therefore, this study is a life cycle assessment of the environmental impacts (carbon footprint, aquatic eutrophication, metals depletion, and water footprint) of four distinct water management scenarios in the Spanish tourism-dependent city of Lloret de Mar. One scenario is a business-as-usual scenario where hotels are completely dependent of potable water, while the other three scenarios (Decentralized, Hybrid, and Centralized) integrate water reuse (through varying degrees of centralization) in all hotels located in the city. Results show that the implementation of water reuse incurs net carbon footprint, metals depletion, and water footprint impacts, while there is a net benefit associated with marine eutrophication impacts. This is mainly due to the treatment technologies used for potable water and greywater/wastewater treatment for reuse. Comparing water reuse scenarios, an increasing degree of centralization is associated with lower carbon and water footprints. Finally, the notable increase in water footprint associated with water reuse highlights the importance of indirect water usage, in this case, due to the degree of hydroelectricity in the Spanish electricity mix as well as generalized water scarcity issues within Spain.

Quantitative measurements of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in raw wastewater have been implemented worldwide since the beginning of the pandemic. Recent efforts are being made to evaluate different viral concentration methodologies to overcome supplier shortages during lockdowns. A set of 22-wastewater samples seeded with murine hepatitis virus (MHV), a member of the Coronaviridae family, and the bacteriophage MS2, were used to characterize and compare two ultrafiltration-based methods: a centrifugal ultrafiltration device (Centricon® Plus-70) and the automated concentrating pipette CP-Select™. Based on the recovery efficiencies, significant differences were observed for MHV, with Centricon® Plus-70 (24%) being the most efficient method. Nevertheless, concentrations of naturally occurring SARS-CoV-2, Human adenoviruses and JC polyomaviruses in these samples did not result in significant differences between methods suggesting that testing naturally occurring viruses may complement the evaluation of viral concentration methodologies. Based on the virus adsorption to solids and the necessity of a pre-centrifugation step to remove larger particles and avoid clogging when using ultrafiltration methods, we assessed the percentage of viruses not quantified after ultrafiltration. Around 23% of the detected SARS-CoV-2 would be discarded during the debris removal step. The CP-Select™ provided the highest concentration factor (up to 333×) and the lowest LoD (6.19 × 103 GC/l) for MHV and proved to be fast, automatic, highly reproducible and suitable to work under BSL-2 measures., Graphical abstract Unlabelled Image, Highlights • Centricon® and CP-Select™ performed equally for naturally occurring SARS-CoV-2 • Higher MHV recoveries were calculated using centrifugal ultrafiltration devices. • Naturally occurring viruses complement concentration methods comparison. • A 23% of detected SARS-CoV-2 adsorb to the solid fraction of wastewater. • CP-Select™ fits into a BSL-2 cabinet enabling to work under biosafety containment.

The concept of Nature-Based Solutions (NBS) has emerged to foster sustainable development by transversally addressing social, economic, and environmental urban challenges. However, there is still a considerable lack of agreement on the conceptualization of NBS, especially concerning typologies, nomenclature, and performance assessments in terms of ecosystem services (ES) and urban challenges (UC). Therefore, this article consolidates the knowledge from 4 European projects to set a path for a common understanding of NBS and thus, facilitate their mainstreaming. To do so, firstly, we performed elicitation workshops to develop an integrative list of NBS, based on the identification of overlaps among NBS from different projects. The terminologies were formalized via web-based surveys. Secondly, the NBS were clustered, following a conceptual hierarchical classification. Thirdly, we developed an integrative assessment of NBS performance (ES and UC) based on the qualitative evaluations from each project. Afterwards, we run a PCA and calculated the evenness index to explore patterns among NBS. The main conceptual advancement resides in providing a list of 32 NBS and putting forward two novel NBS categories: NBS units (NBSu) that are stand-alone green technologies or green urban spaces, which can be combined with other solutions (nature-based or not); NBS interventions (NBSi) that refer to the act of intervening in existing ecosystems and in NBSu, by applying techniques to support natural processes. The statistical analysis suggests that NBSu are more versatile than NBSi in terms of UC and ES. Moreover, the results of the integrative assessment of NBS performance suggest a greater agreement concerning the role of NBS in addressing environmental UC, cultural and regulating ES than regarding socio-economic UC and supporting and provision ES. Finally, the ‘green factor’ and the replication of non-intensive practices occurring in nature seem to be key criteria for practitioners to identify a particular solution as an NBS Authors acknowledge the support from the European Union Horizon 2020 research project EdiCitNet (GA776665), the COST Action Circular City (CA 17133), CLEaN-TOUR project (CTM2017-85385-C2-1-R), the Economy and Knowledge Department of the Catalan Government through Consolidated Research Groups ICRA-ENV (2017SGR1124) and ICRAtech (2017SGR1318). ICRA researchers thank funding from CERCA program (Generalitat de Catalunya). Lluís Corominas acknowledge the Ministry of Economy and Competitiveness for the Ramon and Cajal grant and the corresponding I3 consolidation (RYC-2013-14595). Nataša Atanasova acknowledges the project “Closing material flows by wastewater treatment with green technologies” (ID J2-8162), financially supported by the Slovenian Research Agency Open Access funding provided thanks to the CRUE-CSIC agreement with Elsevier

The ongoing COVID-19 pandemic is, undeniably, a substantial shock to our civilization which has revealed the value of public services that relate to public health. Ensuring a safe and reliable water supply and maintaining water sanitation has become ever more critical during the pandemic. For this reason, researchers and practitioners have promptly investigated the impact associated with the spread of SARS-CoV-2 on water treatment processes, focusing specifically on water disinfection. However, the COVID-19 pandemic impacts multiple aspects of the urban water sector besides those related to the engineering processes, including sanitary, economic, and social consequences which can have significant effects in the near future. Furthermore, this outbreak appears at a time when the water sector was already experiencing a fourth revolution, transitioning toward the digitalisation of the sector, which redefines the Water-Human-Data Nexus. In this contribution, a product of collaboration between academics and practitioners from water utilities, we delve into the multiple impacts that the pandemic is currently causing and their possible consequences in the future. We show how the digitalisation of the water sector can provide useful approaches and tools to help address the impact of the pandemic. We expect this discussion to contribute not only to current challenges, but also to the conceptualization of new projects and the broader task of ameliorating climate change., Graphical abstract Unlabelled Image, Highlights • The impacts of pandemic on the urban water cycle were assessed. • Data mining from sewers can be enabled by digitalisation of the water industry. • Effectiveness of public health measures can be monitored in the aggregate in sewers.

The source control of pharmaceuticals involves influencing the everyday consumption volume and compound choice. This paper evaluates how source control contributes to protecting the environmental health and decreasing the investment needs in urban wastewater infrastructure. Different levels of reduction in diclofenac consumption (as recommended by the European Medicines Agency) compensated by equivalent increases in naproxen consumption (a less environmentally harmful compound) are evaluated. The different loads of compounds are fed into a microcontaminant fate and transport model of the Llobregat river basin (Spain) to assess the investment needs in tertiary treatment to reach diclofenac and naproxen concentrations below environmental quality standards. The results show that, despite the implementation of source control measures, tertiary treatment upgrades are still required in every scenario evaluated. Even though source control of pharmaceuticals decreases the investment needs in urban wastewater infrastructure, apparent concentrations reductions (i.e. statistically significant differences relative to the reference situation) are only observed in drastic substitutions of diclofenac by naproxen (a reduction in the total diclofenac consumption by 73% and a corresponding increase in naproxen consumption). The results also show that Spain is on good track with regards to the substitution of diclofenac by naproxen (among the top 5 in Europe), and this paper shows how positive this substitution can be for the environment The authors would like to acknowledge the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 642904 (TreatRec ITN- EID). The authors acknowledge INVEST (RTI2018-097471-B-C21) and CLEaN-TOUR (CTM2017-85385-C2-1-R) projects funded by the Spanish Ministry of Economy and Competitiveness. Lluís Corominas acknowledges funding from the Spanish Ministry of Economy and Competitiveness for the RYC-2013-14595 and its following I3. Additionally, we acknowledge the Economy and Knowledge Department of the Catalan Government (Consolidated Research Group 2017 SGR 1318). ICRA researchers thank funding from the CERCA program. The authors thank Berry Bergmann (Waterschap Drents Overijsselse Delta) for providing details on the pilot study conducted in the Netherlands for the replacement of diclofenac prescriptions in Meppel. The authors also thank Barbara Kasprzyk-Hordern (University of Bath), Kathryn Hickey and John Bagnall (Wessex Water) for a fruitful discussion on the optimization of WWTP upgrades combined with source control measures, and Vicenç Acuña and Wolfgang Gernjak for internal reviews

The so-called fourth revolution in the water sector will encounter the Big data and Artificial Intelligence (AI) revolution. The current data surplus stemming from all types of devices together with the relentless increase in computer capacity is revolutionizing almost all existing sectors, and the water sector will not be an exception. Combining the power of Big data analytics (including AI) with existing and future urban water infrastructure represents a significant untapped opportunity for the operation, maintenance, and rehabilitation of urban water infrastructure to achieve economic and environmental sustainability. However, such progress may catalyze socio-economic changes and cross sector boundaries (e.g., water service, health, business) as the appearance of new needs and business models will influence the job market. Such progress will impact the academic sector as new forms of research based on large amounts of data will be possible, and new research needs will be requested by the technology industrial sector. Research and development enabling new technological approaches and more effective management strategies are needed to ensure that the emerging framework for the water sector will meet future societal needs. The feature further elucidates the complexities and possibilities associated with such collaborations. Manel Garrido-Baserba and Diego Rosso acknowledge the United States Department of Energy (CERC-WET US Project 525 2.5). Lluís Corominas acknowledges the Ministry of Economy and competitiveness for the Ramon and Cajal grant (RYC2013-465 14595) and the following I3. We thank Generalitat de Catalunya through Consolidated Research Group 2017 SGR 1318. ICRA researchers acknowledge funding from the CERCA program.

International audience; Life cycle assessment (LCA) has been widely applied in the wastewater industry, but inconsistencies in assumptions and methods have made it difficult for researchers and practitioners to synthesize results from across studies. This paper presents a critical review of published LCAs related to municipal wastewater management with a focus on developing systematic guidance for researchers and practitioners to conduct LCA studies to inform planning, design, and optimization of wastewater management and infrastructure (wastewater treatment plants, WWTPs; collection and reuse systems; related treatment technologies and policies), and to support the development of new technologies to advance treatment objectives and the sustainability of wastewater management. The paper guides the reader step by step through LCA methodology to make informed decisions on i) the definition of the goal and scope, ii) the selection of the functional unit and system boundaries, iii) the selection of variables to include and their sources to obtain inventories, iv) the selection of impact assessment methods, and v) the selection of an effective approach for data interpretation and communication to decision-makers.; L'analyse du cycle de vie (ACV) a été largement appliquée dans l'industrie du traitement des eaux usées, mais les incohérences dans les hypothèses et les méthodes ont rendu difficile pour les chercheurs et les praticiens de synthétiser les résultats des différentes études. Ce document présente un examen critique des ACV publiées relatives à la gestion des eaux usées municipales, en mettant l'accent sur l'élaboration d'orientations systématiques pour les chercheurs et les praticiens afin de mener des études ACV pour éclairer la planification, la conception et l'optimisation de la gestion des eaux usées et des infrastructures (stations d'épuration, stations d'épuration des eaux usées ; systèmes de collecte et de réutilisation ; technologies et politiques de traitement connexes), et pour soutenir le développement de nouvelles technologies afin de faire progresser les objectifs de traitement et la durabilité de la gestion des eaux usées. Le document guide le lecteur pas à pas à travers la méthodologie de l'ACV pour prendre des décisions éclairées sur i) la définition de l'objectif et du champ d'application, ii) la sélection de l'unité fonctionnelle et des limites du système, iii) la sélection des variables à inclure et de leurs sources pour obtenir des inventaires, iv) la sélection des méthodes d'évaluation d'impact, et v) la sélection d'une approche efficace pour l'interprétation des données et la communication aux décideurs.

Amultitude of pharmaceuticals enter surface waters via discharges of wastewater treatment plants (WWTPs), and many raise environmental and health concerns. Chemical fate models predict their concentrations using estimates of mass loading, dilution and in-stream attenuation. However, current comprehension of the attenuation rates remains a limiting factor for predictive models.We assessed in-stream attenuation of 75 pharmaceuticals in 4 river segments, aiming to characterize in-stream attenuation variability among different pharmaceutical compounds, as well as among river segments differing in environmental conditions. Our study revealed that in-streamattenuation was highly variable among pharmaceuticals and river segments and that none of the considered pharmaceutical physicochemical and molecular properties proved to be relevant in determining the mean attenuation rates. Instead, the octanol–water partition coefficient (Kow) influenced the variability of rates among river segments, likely due to its effect on sorption to sediments and suspended particles, and therefore influencing the balance between the different attenuation mechanisms (biotransformation, photolysis, sorption, and volatilization). The magnitude of themeasured attenuation rates urges scientists to consider themas important as dilutionwhen aiming to predict concentrations in freshwater ecosystems This research was supported by aMarie Curie European Reintegration Grant (PERG07-GA-2010-259219) and by a Marie Curie Career Integration Grant (PCIG9-GA-2011-293535) within the 7th European Community Framework Programme, aswell as by the SpanishMinistry of Economy and Competitiveness through the projects SCARCE (Consolider-Ingenio 2010 CSD2009-00065) and ENDERUS (CTM-2009-13018), and the postdoctoral grants “Juan de la Cierva” (jci-2009-05604 and jci-2010- 06397), and by the European Union through the European Regional Development Fund (FEDER). This work was partly supported by the Generalitat de Catalunya (Consolidated Research Group: Water and Soil Quality Unit 2009-SGR-965)

The Authors Investments for upgrading wastewater treatment plants (WWTPs) with tertiary treatment to reduce microcontaminant loads in surface waters at a catchment scale can be daunting. These investments are highly sensitive to the selection of environmental quality standards (EQSs) for the target microcontaminants. Our hypothesis is that there is a balance between EQS selection and investment that needs to be considered in decision-making. We used a customized microcontaminant fate and transport model coupled to an optimization algorithm to validate this hypothesis in the Llobregat river basin and for the pharmaceutical compound diclofenac. The algorithm optimizes the number of WWTPs in this catchment requiring an upgrade to minimize the total amount of diclofenac that exceeds the EQS in every river section and the total cost. We simulated and optimized 40 scenarios representing a combination of 4 potential EQSs (10, 30, 50 and 100 ng L−1), 5 levels of uncertainty bounds in the predictions of river concentrations and 2 hydrological scenarios (average flows, flows annually exceeding 30% of the days; and environmental flows, flows annually exceeding 99% of the days). The results showthat there is a nonlinear relationship between the EQS and the required investment. The investment increases by 100% from an EQS of 100 ng L−1 to 10 ng L−1, significantly increasing (by 60%) from 30 to 10 ng L−1. Thus, establishing an EQS of 30 ng L−1 would balance environmental protection and costs. The selection of the hydrological conditions also plays a key role in the upgrade analysis because the costs for environmental flows are 50% higher than for average flows. Finally, we highlight that the investment in research would allow the reduction of uncertainties, hence allowing more qualified decisions to be made and a reduction in the WWTP upgrade costs (up to 4 €·household−1·year−1) The authors would like to acknowledge the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 642904 (TreatRec ITN- EID). The authors thank Mirabella Mulder for providing details on the cost breakdown for ozonation and sand filtration. The authors also thank Rafael Marcè (ICRA), Carlos Constantino and Peter Daldorph (Atkins) for giving feedback on the article. Lluís Corominas acknowledges funding from the Spanish Ministry of Economy and Competitiveness for the RYC-2013-14595. Additionally, we acknowledge the Economy and Knowledge Department of the Catalan Government (Consolidated Research Group 2014 SGR 291)

Human consumption of pharmaceuticals leads to high concentrations of pharmaceuticals in wastewater, which is usually not or insufficiently collected and treated before release into freshwater ecosystems. There, pharmaceuticals may pose a threat to aquatic biota. Unfortunately, occurrence data of pharmaceuticals in freshwaters at the global scale is scarce and unevenly distributed, thus preventing the identification of hotspots, the prediction of the impact of Global Change (particularly streamflow and population changes) on their occurrence, and the design of appropriate mitigation actions. Here, we use diclofenac (DCL) as a typical pharmaceutical contaminant, and a global model of DCL chemical fate based on wastewater sanitation, population density and hydrology to estimate current concentrations in the river network, the impact of future changes in runoff and population, and potential mitigation actions in line with the Sustainable Development Goals. Our model is calibrated against measurements available in the literature. We estimate that 2.74 ± 0.63% of global river network length has DCL concentrations exceeding the proposed EU Watch list limit (100 ng L-1). Furthermore, many rivers downstream from highly populated areas show values beyond 1000 ng L-1, particularly those associated to megacities in Asia lacking sufficient wastewater treatment. This situation will worsen with Global Change, as streamflow changes and human population growth will increase the proportion of the river network above 100 ng L-1 up to 3.10 ± 0.72%. Given this background, we assessed feasible source and end-of-pipe mitigation actions, including per capita consumption reduction through eco-directed sustainable prescribing (EDSP), the implementation of the United Nations Sustainable Development Goal (SDG) 6 of halving the proportion of population without access to safely managed sanitation services, and improvement of wastewater treatment plants up to the Swiss standards. Among the considered end-of-pipe mitigation actions, implementation of SDG 6 was the most effective, reducing the proportion of the river network above 100 ng L-1 down to 2.95 ± 0.68%. However, EDSP brought this proportion down to 2.80 ± 0.64%. Overall, our findings indicate that the sole implementation of technological improvements will be insufficient to prevent the expected increase in pharmaceuticals concentration, and that technological solution need to be combined with source mitigation actions., Authors acknowledge the support from the Economy and Knowledge Department of the Catalan Government through Consolidated Research Group (ICRA-ENV 2017 SGR 1124), as well as from the CERCA program.

This paper introduces the application of a fully dynamic air distribution model integrated with a biokinetic process model and a detailed process control model. By using a fully dynamic air distribution model, it is possible to understand the relationships between aeration equipment, control algorithms, process performance, and energy consumption, thus leading to a significantly more realistic prediction of water resource recovery facility (WRRF) performance. Consequently, this leads to an improved design of aeration control strategies and equipment. A model-based audit has been performed for the Girona WRRF with the goal of providing a more objective evaluation of energy reduction strategies. Currently, the Girona plant uses dissolved oxygen control and has been manually optimised for energy consumption. Results from a detailed integrated model show that the implementation of an ammonia-based aeration controller, a redistribution of the diffusers, and the installation of a smaller blower lead to energy savings between 12 and 21%, depending on wastewater temperature. The model supported the development of control strategies that counter the effects of current equipment limitations, such as tapered diffuser distribution, or over-sized blowers. The latter causes an intermittent aeration pattern with blowers switching on and off, increasing wear of the equipment.

The aim of this paper is to describe the state-of-the art computer-based techniques for data analysis to improve operation of wastewater treatment plants. A comprehensive review of peer-reviewed papers shows that European researchers have led academic computer-based method development during the last two decades. The most cited techniques are artificial neural networks, principal component analysis, fuzzy logic, clustering, independent component analysis and partial least squares regression. Even though there has been progress on techniques related to the development of environmental decision support systems, knowledge discovery and management, the research sector is still far from delivering systems that smoothly integrate several types of knowledge and different methods of reasoning. Several limitations that currently prevent the application of computer-based techniques in practice are highlighted.

Impacts from urban wastewater treatment plants (WWTP) to receiving riverine surface water bodies (SWBs) depend on the load of contaminants discharged, as well as on their dilution capacity. Yet, climate change impacts on such dilution capacity and ultimately on the SWBs ecological status remain unclear. Here, we assess SWBs dilution capacity across the European continent to identify most vulnerable areas using information from centralized European databases. SWBs´ future dilution factor values are estimated based on representative concentration pathway scenarios impacts on rivers flow, and likely changes in European SWBs´ ecological status foretold. Results show that dilution factor in Europe increases by 5.4% in average. Yet, climate change effects are found to lead to a consistent dilution factor decrease for 11% of the 40074 European SWBs receiving WWTP discharge for the early century. This share reaches 17% for the midcentury period. We estimate that up to 42% of the SWBs receiving WWTP discharges and currently reaching a good ecological status show a 0.7 probability to have their ecological status downgraded due to climate change. Sites more vulnerable are located in the Mediterranean countries. Our findings highlight that climate change mitigation is essential for maintaining good ecological status in European SWBs.

This chapter evaluates the economic and environmental implications of MBR using Cost Benefit Analysis (CBA) and Life Cycle Assessment (LCA). A brief introduction to these methodologies and the main developments and achievements when applied to MBR is given before the presentation of two case studies. In the first case study, CBA and LCA were applied for the assessment of seven wastewater treatment plants using MBR and other membrane technologies. The results highlighted the benefits of removal of substances responsible for eutrophication and the relevance of the scale factor regarding electricity use, one of the main environmental and economic costs. In the second case study, LCA alone was applied for the environmental assessment of four novel MBR configurations at pilot-plant scale focusing on the removal of pharmaceutical and personal care products (PPCPs), of which only hormones were found to be relevant in terms of toxicity terms due to their higher concentrations in the influent.

This paper presents a methodology for assessing the selection of stormwater control measures (SCM) within an urban drainage system that combines hydrological-hydraulic modelling and multi-criteria analysis (MCA). The methodology's utility is illustrated on urban catchment in the city of Girona, Spain. The SWMM model was applied and calibrated to simulate SCM scenarios. Seven scenarios were evaluated consisting of one grey infrastructure measure using underground storage tank and three nature-based SCM i.e. infiltration basins, infiltration trenches, green roofs, and combinations thereof. These scenarios were evaluated with MCA including combined sewer overflow (CSO) reduction, CAPEX, OPEX, amenity, biodiversity, and feasibility regarding ownership. The results show that the scenario that included only infiltration basins was most favourable, followed by the scenario which combined infiltration basins and trenches. The underground storage tank was the least favourable with the lowest grade, due to high CAPEX and OPEX, and due to single functionality.

The prediction of sediment levels in combined sewer system (CSS) would result in enormous savings in resources for their maintenance as a reduced number of inspections would be needed. In this paper, we benchmark different machine learning (ML) methodologies to improve the maintenance schedules of the sewerage and reduce the number of cleanings using historical sediment level and inspection data of the combined sewer system in the city of Barcelona. Two ML methodologies involve the use of spatial features for sediment prediction at critical sections of the sewer, where the cost of maintenance is high because of the dangerous access, one uses a regression model to predict the sediment level of a section, and the other one a binary classification model to identify whether or not a section needs cleaning. The last ML methodology is a short-term forecast of the possible sediment level in future days to improve the ability of operators to react and solve an imminent sediment level increase. Our study concludes with three different models. The spatial and short-term regression methodologies accomplished the best results with Artificial Neural Networks (ANN) with 0.76 and 0.61 R2 scores, respectively. The classification methodology resulted in a Gradient Boosting (GB) model with an accuracy score of 0.88 and an area under the curve (AUC) of 0.909.

Obtaining high quality data collected on wastewater treatment plants is gaining increasing attention in the wastewater engineering literature. Typical studies focus on recognition of faulty data with a given set of installed sensors on a wastewater treatment plant. Little attention is however given to how one can install sensors in such a way that fault detection and identification can be improved. In this work, we develop a method to obtain Pareto optimal sensor layouts in terms of cost, observability, and redundancy. Most importantly, the resulting method allows reducing the large set of possibilities to a minimal set of sensor layouts efficiently for any wastewater treatment plant on the basis of structural criteria only, with limited sensor information, and without prior data collection. In addition, the developed optimization scheme is fast. Practically important is that the number of sensors needed for both observability of all flows and redundancy of all flow sensors is only one more compared to the number of sensors needed for observability of all flows in the studied wastewater treatment plant configurations.

Purpose: The objective was to provide comprehensive life cycle inventories for the construction and renovation of sewers. A detailed inventory was provided with multiple options of pipe materials, diameters and site-specific characteristics, and was embedded into the Excel ® -based tool SewerLCA. The tool allows for life cycle evaluation of different sewers. It was applied to determine the most important phases, processes, and related parameters involved in the construction and renovation of sewers from an environmental and economical perspective. Methods: Comprehensive life cycle inventories (LCIs) for sewers construction and renovation were obtained by first identifying all processes involved after interviewing construction experts and reviewing sewer construction budgets from a Catalan company; and second transforming the processes into masses of materials and energy usage using construction databases. In order to run the life cycle impact assessment (LCIA) the materials and energy typologies from the inventories were matched to their corresponding equivalents into available LCI databases. Afterwards the potential impacts were calculated through the use of LCIA characterization factors from ReCiPe. Life cycle assessment (LCA) was run several times to assess the construction of a 1-km-long sewer with varying pipe materials, life spans for each material, diameters, transport distances, site-specific characteristics, and pipe deposition options. Results and discussion: The environmental impacts generated by construction and renovation of a 1 km Polyvinylchloride (PVC) pipe with a diameter of 40 cm are mainly associated with pipe laying and backfilling of the trench. The evaluation of several pipe materials and diameters shows that the exclusion of renovation would underestimate the impacts by 38 to 82 % depending on the pipe materials and diameters. Including end-of-life phase for plastic pipe materials increases climate change (up to an extra 71 %) and human toxicity (up to an extra 147 %) impacts (among all diameters). The preferred pipe materials from an environmental point of view are precast concrete and High-Density Polyethylene (HDPE). Site-specific characteristics (specially the presence of rocky soil and asphalt placement) and material life span have a high influence on the overall environmental profile, whereas changes in transport distances have only a minor impact ( < 4 %). Conclusions: Environmental impacts during the construction and renovation of sewers are subject to differences in material type, site-specific characteristics and material life span. Renovation of sewers has a large influence on all potential environmental impacts and costs and, hence, should not be omitted in LCA studies. The treatment and disposal processes of plastic pipes at the end of their life has to be accounted in LCA studies The authors would like to thank Voltes S.L.U. for the technical support, Banc BEDEC, the Ramon and Cajal grant from Lluís Corominas RYC-2013-14595), Marie Curie Career Integration Grant PCIG9-GA-2011-293535 and Marie Curie SANITAS ITN Project GA 289193), Waterfate project (CTM2012-38314-C0201). Serni Morera’s FI scholarship (2015FI_B2 00071), STSMscholarship from EU-Cost Action Water2020 (ECOST-STSM-ES1202-110614-044095). LEQUIA and ICRA were recognized as consolidated research groups by the Catalan Government with codes 2014-SGR-1168 and 2014-SGR-291, respectively

Humans are nowadays exposed to numerous chemicals in our day-to-day life, including parabens, UV filters, phosphorous flame retardants/plasticizers, bisphenols, phthalates and alternative plasticizers, which can have different adverse effects to human health. Estimating human’s exposure to these potentially harmful substances is, therefore, of paramount importance. Human biomonitoring (HBM) is the existing approach to assess exposure to environmental contaminants, which relies on the analysis of specific human biomarkers (parent compounds and/or their metabolic products) in biological matrices from individuals. The main drawback is its implementation, which involves complex cohort studies. A novel approach, wastewater-based epidemiology (WBE), involves estimating exposure from the analysis of biomarkers in sewage (a pooled urine and feces sample of an entire population). One of the key challenges of WBE is the selection of biomarkers which are specific to human metabolism, excreted in sufficient amounts, and stable in sewage. So far, literature data on potential biomarkers for estimating exposure to these chemicals are scattered over numerous pharmacokinetic and HBM studies. Hence, this review provides a list of potential biomarkers of exposure to more than 30 widely used chemicals and report on their urinary excretion rates. Furthermore, the potential and challenges of WBE in this particular field is discussed through the review of pioneer WBE studies, which for the first time explored applicability of this novel approach to assess human exposure to environmental contaminants. In the future, WBE could be potentially applied as an “early warning system”, which could promptly identify communities with the highest exposure to environmental contaminants.

The advent of affordable computing, low-cost sensor hardware, and high-speed and reliable communications have spurred ubiquitous installation of sensors in complex engineered systems. However, ensuring reliable data quality remains a challenge. Exploitation of redundancy among sensor signals can help improving the precision of measured variables, detecting the presence of gross errors, and identifying faulty sensors. The cost of sensor ownership, maintenance efforts in particular, can still be cost-prohibitive however. Maximizing the ability to assess and control data quality while minimizing the cost of ownership thus requires a careful sensor placement. To solve this challenge, we develop a generally applicable method to solve the multi-objective sensor placement problem in systems governed by linear and bilinear balance equations. Importantly, the method computes all Pareto-optimal sensor layouts with conventional computational resources and requires no information about the expected sensor quality.