High-rate activated sludge at very short SRT: Key factors for process stability and performance of COD fractions removal.

In high-rate activated sludge (HRAS) processes, reducing the solid retention time (SRT) minimizes COD oxidation and allows to obtain the maximum energy recovery. The aim of this research was to operate a pilot plant with an automatic control strategy to assure the HRAS process stability and high COD fractions removal at very low SRT. This study combines simulation and experimental tools (pilot plant 35 m3·d - 1) operating at SRT (0.2 d), HRT (0.6 h) and DO (0.5 mg·L - 1) treating high-strength raw wastewater, at 18-26°C, at variable flow. The research includes the effects of temperature, influent concentration and MLSS reactor concentration over the sCOD, cCOD and pCOD removal. The study points out that the best parameter to control the HRAS at a low SRT is not strictly the SRT but rather the reactor MLSS concentration: operating at 2,000±200mg·L - 1 assured a stable process despite the large influents variation. Low SVI values of 50-70ml·g - 1 indicated the good settling properties of the biomass. With only a 6.9% COD oxidation, a high organic matter removal (57±9% for COD and 56±10% for BOD5), was reached. The high removal efficiencies for pCOD (74%) compared to the (29%) for sCOD and (12%) for cCOD also confirmed the importance of settling efficiency and stability in the HRAS. The direct correlation between COD influent and COD removal makes advisable to use the HRAS as a replacement of the primary clarifier. The HRAS acted efficiently as a filter for COD and pCOD peak loads and, in a lesser extent, for BOD5, while sCOD peaks were not buffered. The adopted model presented a good fit for COD fractions except for pCOD when the temperature exceeds 23 °C.

Increasing resilience through nudges in the urban water cycle: An integrative conceptual framework to support policy decision-making.

Relevant challenges associated with the urban water cycle must be overcome to meet the United Nations Sustainable Development Goals (SDGs) and improve resilience. Unlike previous studies that focused only on the provision of drinking water, we propose a framework that extends the use of the theory of nudges to all stages of the overall urban water cycle (drinking water and wastewater services), and to agents of influence (citizens, organizations, and governments) at different levels of decision making. The framework integrates four main drivers (the fourth water revolution, digitalization, decentralization, and climate change), which influence how customers, water utilities and regulators approach the challenges posed by the urban water cycle. The proposed framework, based on the theory of nudges first advanced by the Nobel Prize in behavioral economics Richard H. Thaler and Cass R. Sunstein (Thaler and Sunstein, 2009), serves as a reference for policymakers to define medium- and long-term strategies and policies for improving the sustainability and resilience of the urban water cycle. Finally, we provide new insights for further research on resilience approaches to the management of the urban water cycle as an element to support the more efficient formulation of policies.

The third route: A techno-economic evaluation of extreme water and wastewater decentralization.

Water systems need to become more locally robust and sustainable in view of increased population demands and supply uncertainties. Decentralized treatment is often assumed to have the potential to improve the technical, environmental, and economic performance of current technologies. The techno-economic feasibility of implementing independent building-scale decentralized systems combining rainwater harvesting, potable water production, and wastewater treatment and recycling was assessed for six main types of buildings ranging from single-family dwellings to high-rise buildings. Five different treatment layouts were evaluated under five different climatic conditions for each type of building. The layouts considered varying levels of source separation (i.e., black, grey, yellow, brown, and combined wastewater) using the corresponding toilet types (vacuum, urine-diverting, and conventional) and the appropriate pipes and pumping requirements. Our results indicate that the proposed layouts could satisfy 100% of the water demand for the three smallest buildings in all but the aridest climate conditions. For the three larger buildings, rainwater would offset annual water needs by approximately 74 to 100%. A comprehensive economic analysis considering CapEx and OpEx indicated that the cost of installing on-site water harvesting and recycling systems would increase the overall construction cost of multi-family buildings by around 6% and single-family dwellings by about 12%, with relatively low space requirements. For buildings or combined water systems with more than 300 people, the estimated total price of on-site water provision (including harvesting, treatment, recycling, and monitoring) ranged from $1.5/m3 to $2.7/m,3 which is considerably less than the typical tariffs collected by utilities in the United States and Western Europe. Where buildings can avoid the need to connect to centralized supplies for potable water and sewage disposal, water costs could be even lower. Urine-diversion has the potential to yield the least expensive solution but is the least well developed and had higher uncertainty in the cost analysis. More mature layouts (e.g., membrane bioreactors) exhibited less cost uncertainty and were economically competitive. Our analysis indicates that existing technologies can be used to create economically viable systems that greatly reduce demands on centralized utilities and, under some conditions, eliminate the need for centralized water supply or sewage collection.

Benchmarking empirical models for THMs formation in drinking water systems: An application for decision support in Barcelona, Spain.

Drinking water treatment plants (DWTPs) face changes in raw water quality, which affect the formation of disinfection by-products. Several empirical modelling approaches have been reported in the literature, but most of them have been developed with lab-scale data, which may not be representative of real water systems. Therefore, the application of these models for real-time operation of DWTPs might be limited. At the present study, multiple linear regression (MLR) and multi-layer perceptrons (MLP) were benchmarked using field-scale data for predicting the THMs formation in a case-study DWTP in Barcelona, Spain. After fitting the studied models, MLR exhibited good fit with the validation data set (R2 = 0.88 and MAE = 4.0 µg·L-1) and described the most plausible input-output relationships with field-scale data. The MLR predictive model was incorporated into an environmental decision support system (EDSS) for assessing the THMs formation at two critical points of the distribution network. A Monte Carlo scheme was applied for quantifying uncertainty of model predictions at these points, considering low and high water quality scenarios and different degrees of treatment by an electrodialysis reversal process. The results show that the use of the proposed EDSS can help in real operation of complex drinking water systems, which face important changes in water quality throughout the year.

When the fourth water and digital revolution encountered COVID-19.

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.

Implementation of an environmental decision support system for controlling the pre-oxidation step at a full-scale drinking water treatment plant.

Drinking water treatment plants (DWTPs) face changes in raw water quality, and treatment needs to be adjusted to produce the best water quality at the minimum environmental cost. An environmental decision support system (EDSS) was developed for aiding DWTP operators in choosing the adequate permanganate dosing rate in the pre-oxidation step. To this end, multiple linear regression (MLR) and multi-layer perceptron (MLP) models are compared for choosing the best predictive model. Besides, a case-based reasoning (CBR) model was approached to provide the user with a distribution of solutions given similar operating conditions in the past. The predictive model consisted of an MLP and has been validated against historical data with sufficient good accuracy for the utility needs (R2 = 0.76 and RSE = 0.13 mg·L-1). The integration of the predictive and the CBR models in an EDSS gives the user an augmented decision-making capacity of the process and has great potential for both assisting experienced users and for training new personnel in deciding the operational set-point of the process.

A composite indicator approach to assess the sustainability and resilience of wastewater management alternatives.

Evaluating the sustainability of wastewater management alternatives is a challenging task. This paper proposes an innovative methodology to assess and compare the sustainability of four wastewater management alternatives: a) centralised water resource recovery facility (WRRF) based on activated sludge (AS); b) centralised WRRF with membrane bioreactors (MBR); c) decentralised WRRFs with upflow anaerobic sludge blanket reactors and trickling filters; d) centralised-decentralised hybrid system. In doing so, a composite indicator embracing total annual equivalent costs, carbon emission intensity, eutrophication and resilience (based on robustness and rapidity metrics) was developed using the analytic hierarchy process (AHP) method. The results show that decentralised and hybrid systems contribute less to carbon emission and eutrophication because of energy and fertilizer harvest and with a trade-off of higher costs of 7-17% than the ones of AS and MBR. In addition, decentralised and hybrid systems are more resilient, contributing to lower environmental impacts facing natural disasters. Based on the weights obtained by AHP, the decentralised alternative appears to be the most sustainable option due to its best performance in terms of carbon emission intensity and resilience. By contrast, the MBR alternative appeared the least sustainable evaluated wastewater management alternative. However, this alternative is sustainable option when the eutrophication criterion is heavily prioritized. The proposed approach contributes to the selection of the most sustainable wastewater management alternative from a holistic perspective.

The Fourth-Revolution in the Water Sector Encounters the Digital Revolution.

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.

The Economics of Wastewater Treatment Decentralization: A Techno-economic Evaluation.

The existing wastewater treatment infrastructure has not adequately established an efficient and sustainable use of energy, water, and nutrients. A proposed scheme based on source separation and water-efficient use is compared to the current wastewater management paradigm (one largely based on activated sludge) using techno-economic terms. This paper explores the economic viability of adopting more sustainable management alternatives and expands the understanding of the economics of decentralization and source-separation. The feasibility of three different potential types of source-separation (with different levels of decentralization) are compared to the conventional centralized activated sludge process by using recognized economic assessment methodologies together with widely accepted modeling tools. The alternatives were evaluated for two common scenarios: new developments and retrofit due to the aging of existing infrastructures. The results prove that source-separated alternatives can be competitive options despite existing drawbacks (only when countable incomes are included), while the hybrid approach resulted in the least cost-effective solution. A detailed techno-economic evaluation of the costs of decentralization provides insight into the current constraints concerning the paradigm shift and the cost of existing technologic inertia.

Optimal fresh water blending: A methodological approach to improve the resilience of water supply systems.

Climate change and socioeconomic factors have increased the complexity of urban water supply systems. Thus, fresh water sources are being gradually diversified to improve the reliability and resilience of the systems. However, as the number of source blending options grows, optimization tools are needed to design drinking water supply systems that comply with indicators of cost, resilience, and water quality. This paper proposes a pioneering methodological approach, based on an ant-colony-optimization (ACO) algorithm, to optimize the blending of drinking water from different sources to minimize operational costs of a given system originating from a number of impaired water sources while complying with water quality standards. To evidence the potential of the ACO algorithm to solve such a system, a virtual case study was designed that considers eight fresh water sources, including seawater desalination and potable reuse. Seven scenarios were developed with different weightings to service outage, water conveyance and treatment costs while complying with water quality goals in regard to total organic carbon, nitrates, and total dissolved solids. It was shown that the cost per volumetric unit of water can vary considerably depending on the weightings of the three cost items. This paper provides a rigorous scientific approach to propose a methodology supporting the decision-making process of selecting a mixture of different sources to achieve the overall lowest system cost. Hence, this work contributes to improving the resilience and sustainability of urban water supplies.

Using a detailed inventory of a large wastewater treatment plant to estimate the relative importance of construction to the overall environmental impacts.

The aim of this work is to quantify the relative contribution to the overall environmental impact of the construction phase compared to the operational phase for a large conventional activated sludge wastewater treatment plant (WWTP). To estimate these environmental impacts, a systematic procedure was designed to obtain the detailed Life Cycle Inventories (LCI) for civil works and equipment, taking as starting point the construction project budget and the list of equipment installed at the Girona WWTP, which are the most reliable information sources of materials and resources used during the construction phase. A detailed inventory is conducted by including 45 materials for civil works and 1,240 devices for the equipment. For most of the impact categories and different life spans of the WWTP, the contribution of the construction phase to the overall burden is higher than 5% and, especially for metal depletion, the impact of construction reaches 63%. When comparing to the WWTP inventories available in Ecoinvent the share of construction obtained in this work is about 3 times smaller for climate change and twice higher for metal depletion. Concrete and reinforcing steel are the materials with the highest contribution to the civil works phase and motors, pumps and mobile and transport equipment are also key equipment to consider during life cycle inventories of WWTPs. Additional robust inventories for similar WWTP can leverage this work by applying the factors (kg of materials and energy per m3 of treated water) and guidance provided.

Optimized MBR for greywater reuse systems in hotel facilities.

Greywater is an important alternative water source, particularly in semi-arid, touristic areas, where the biggest water demand is usually in the dry period. By using this source wisely, tourist facilities can substantially reduce the pressure to scarce water resources. In densely urbanized touristic areas, where space has high value, compact solutions such as MBR based greywater reuse systems appear very appropriate. This research focuses on technical and economical evaluation of such solution by implementing a pilot MBR to a hotel with separated grey water. The pilot was operated for 6 months, with thorough characterisation of the GW performed, its operation was monitored and its energy consumption was optimized by applying a control system for the air scour. Based on the pilot operation a design and economic model was set to estimate the feasibility (CAPEX, OPEX, payback period of investment) of appropriate scales of MBR based GW systems, including separation of GW, MBR technology, clean water storage and disinfection. The model takes into account water and energy prices in Spain and a planning period of 20 years. The results demonstrated an excellent performance in terms of effluent quality, while the energy demand for air-scour was reduced by up to 35.2%, compared to the manufacturer recommendations. Economical evaluation of the entire MBR based GW reuse system shows its feasibility for sizes already at 5 m3/day (60 PE). The payback period of the investment for hotels like the demonstration hotel, treating 30 m3/day is 3 years.

Crossing the Death Valley to Transfer Environmental Decision Support Systems to the Water Market.

Environmental decision support systems (EDSSs) are attractive tools to cope with the complexity of environmental global challenges. Several thoughtful reviews have analyzed EDSSs to identify the key challenges and best practices for their development. One of the major criticisms is that a wide and generalized use of deployed EDSSs has not been observed. The paper briefly describes and compares four case studies of EDSSs applied to the water domain, where the key aspects involved in the initial conception and the use and transfer evolution that determine the final success or failure of these tools (i.e., market uptake) are identified. Those aspects that contribute to bridging the gap between the EDSS science and the EDSS market are highlighted in the manuscript. Experience suggests that the construction of a successful EDSS should focus significant efforts on crossing the death-valley toward a general use implementation by society (the market) rather than on development.

Optimal management of substrates in anaerobic co-digestion: An ant colony algorithm approach.

Sewage sludge (SWS) is inevitably produced in urban wastewater treatment plants (WWTPs). The treatment of SWS on site at small WWTPs is not economical; therefore, the SWS is typically transported to an alternative SWS treatment center. There is increased interest in the use of anaerobic digestion (AnD) with co-digestion as an SWS treatment alternative. Although the availability of different co-substrates has been ignored in most of the previous studies, it is an essential issue for the optimization of AnD co-digestion. In a pioneering approach, this paper applies an Ant-Colony-Optimization (ACO) algorithm that maximizes the generation of biogas through AnD co-digestion in order to optimize the discharge of organic waste from different waste sources in real-time. An empirical application is developed based on a virtual case study that involves organic waste from urban WWTPs and agrifood activities. The results illustrate the dominate role of toxicity levels in selecting contributions to the AnD input. The methodology and case study proposed in this paper demonstrate the usefulness of the ACO approach in supporting a decision process that contributes to improving the sustainability of organic waste and SWS management.

Coordinated management of combined sewer overflows by means of environmental decision support systems.

During heavy rainfall, the capacity of sewer systems and wastewater treatment plants may be surcharged producing uncontrolled wastewater discharges and a depletion of the environmental quality. Therefore there is a need of advanced management tools to tackle with these complex problems. In this paper an environmental decision support system (EDSS), based on the integration of mathematical modeling and knowledge-based systems, has been developed for the coordinated management of urban wastewater systems (UWS) to control and minimize uncontrolled wastewater spills. Effectiveness of the EDSS has been tested in a specially designed virtual UWS, including two sewers systems, two WWTP and one river subjected to typical Mediterranean rain conditions. Results show that sewer systems, retention tanks and wastewater treatment plants improve their performance under wet weather conditions and that EDSS can be very effective tools to improve the management and prevent the system from possible uncontrolled wastewater discharges.

Occurrence and in-stream attenuation of wastewater-derived pharmaceuticals in Iberian rivers.

A multitude 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-stream attenuation 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 the measured attenuation rates urges scientists to consider them as important as dilution when aiming to predict concentrations in freshwater ecosystems.

Modelling of arsenic retention in constructed wetlands.

A new model was developed in order to simulate the most significant arsenic retention processes that take place in constructed wetlands (CWs) treating high arsenic waters. The present contribution presents the implementation phases related to plants (arsenic uptake and accumulation, root arsenic adsorption, and root oxygen release), showing the first simulation results of the complete model. Different approaches with diverse influent configurations were simulated. In terms of total arsenic concentrations in effluent, the simulated data closely matched the data measured in all evaluated cases. The iron and arsenic species relationships, and the arsenic retention percentages obtained from simulations, were in agreement with the experimental data and literature. The arsenic retention efficiency increased whenever a new phase was implemented, reaching a maximum efficiency range of 85-95%. According to the quality of the obtained results, it can be considered that the implementation of all steps of RCB-ARSENIC provided reasonably good response values.

Integration of freshwater environmental policies and wastewater treatment plant management.

In the last decade the political awareness of river water quality issues has grown substantially over the world and legislation is accordingly adapting. In the European Union (EU), two different directives regulate separately the characteristics of the discharged water and the chemical status of the receiving freshwater ecosystem. On the one hand, the characteristics of the urban effluents are regulated by the EU Directive 91/271/EEC, which defines limits on different elements set in the form of both static emission limits and minimum percentage load reductions. On the other hand, the characteristics of the receiving freshwater ecosystems are described in the EU Water Framework Directive (2000/60/EEC), which sets minimum 'good' chemical and ecological status in water bodies that should be achieved by 2015, and aims for an ecosystem-based management. With the support of an example, we show that there is a gap in these EU environmental policies leading to non-integrated management, which may result on adverse environmental and economical consequences. We believe that these policies should be updated and tuned to account for an integrated perspective, allowing a more efficient and sustainable management of wastewater treatment plants, maximizing the ecological, economical and social benefits of the system as a whole.

Implementation of a knowledge-based methodology in a decision support system for the design of suitable wastewater treatment process flow diagrams.

In light of rapid global change, the demand for wastewater treatment is increasing rapidly and will continue to do so in the near future. Wastewater management is a complex puzzle for which the proper pieces must be combined to achieve the desired solution, requiring the simultaneous consideration of technical, economic, social and environmental issues. In this context, a knowledge-based methodology (KBM) for the conceptual design of wastewater treatment plant (WWTP) process flow diagrams (PFDs) and its application for two scenarios is presented in this paper. The core of the KBM is composed of two knowledge bases (KBs). The first, a specification knowledge base (S-KB), summarizes the main features of the different treatment technologies: pollutants removal efficiency, operational costs and technical reliability. The second, a compatibility knowledge base (C-KB), contains information about the different interactions amongst the treatment technologies and determines their degree of compatibility. The proposed methodology is based on a decision hierarchy that uses the information contained in both KBs to generate all possible WWTP configurations, screening and selecting appropriate configurations based on user-specified requirements and scenario characteristics. The design of the most adequate treatment train for small and medium sized wastewater treatment plants (2000 and 50,000 p.e. respectively) according to different restrictions (space constraints, operation simplicity and cost optimization) was the example in order to show the usefulness of the KBM.

Model-based knowledge acquisition in environmental decision support system for wastewater integrated management.

The main goal of the Water Framework Directive is to achieve good chemical and ecological status of water bodies by 2015. The implementation of integrated river basin management, including sewer systems, wastewater treatment plants and receiving water bodies, is essential to accomplishing this objective. Integrated management is complex and therefore the implementation of control systems and the development of decision support systems are needed to facilitate the work of urban wastewater system (UWS) managers. Within this context, the objective of this paper is to apply integrated modelling of an UWS to simulate and analyse the behaviour of the 'Congost' UWS in Spain, and to optimize its performance against different types of perturbations. This analysis results in optimal operating set-points for each perturbation, improves river water quality, minimizes combined sewer overflows and optimizes flow lamination from storm water tanks. This is achieved by running Monte Carlo simulations and applying global sensitivity analysis. The set-points will become part of the knowledge base composed of a set of IF-THEN rules of the environmental decision support system being developed for this case study.