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.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.Peer ReviewedPostprint (author's final draft

The digital revolution in the urban water cycle and its ethical–political implications: a critical perspective

The development and application of new forms of automation and monitoring, data mining, and the use of AI data sources and knowledge management tools in the water sector has been compared to a ‘digital revolution’. The state-of-the-art literature has analysed this transformation from predominantly technical and positive perspectives, emphasising the benefits of digitalisation in the water sector. Meanwhile, there is a conspicuous lack of critical literature on this topic. To bridge this gap, the paper advances a critical overview of the state-of-the art scholarship on water digitalisation, looking at the sociopolitical and ethical concerns these technologies generate. We did this by analysing relevant AI applications at each of the three levels of the UWC: technical, operational, and sociopolitical. By drawing on the precepts of urban political ecology, we propose a hydrosocial approach to the so-called ‘digital water ‘, which aims to overcome the one-sidedness of the technocratic and/or positive approaches to this issue. Thus, the contribution of this article is a new theoretical framework which can be operationalised in order to analyse the ethical–political implications of the deployment of AI in urban water management. From the overview of opportunities and concerns presented in this paper, it emerges that a hydrosocial approach to digital water management is timely and necessary. The proposed framework envisions AI as a force in the service of the human right to water, the implementation of which needs to be (1) critical, in that it takes into consideration gender, race, class, and other sources of discrimination and orients algorithms according to key principles and values; (2) democratic and participatory, i.e., it combines a concern for efficiency with sensitivity to issues of fairness or justice; and (3) interdisciplinary, meaning that it integrates social sciences and natural sciences from the outset in all applications.Peer ReviewedPostprint (published version

Navigating environmental, economic, and technological trade-offs in the design and operation of submerged anaerobic membrane bioreactors (AnMBRs)

Anaerobic membrane bioreactors (AnMBRs) enable energy recovery from wastewater while simultaneously achieving high levels of treatment. The objective of this study was to elucidate how detailed design and operational decisions of submerged AnMBRs influence the technological, environmental, and economic sustainability of the system across its life cycle. Specific design and operational decisions evaluated included: solids retention time (SRT), mixed liquor suspended solids (MLSS) concentration, sludge recycling ratio (r), flux (J), and specific gas demand per membrane area (SGD). The possibility of methane recovery (both as biogas and as soluble methane in reactor effluent) and bioenergy production, nutrient recovery, and final destination of the sludge (land application, landfill, or incineration) were also evaluated. The implications of these design and operational decisions were characterized by leveraging a quantitative sustainable design (QSD) framework which integrated steady-state performance modeling across seasonal temperatures (using pilot-scale experimental data and the simulating software DESASS), life cycle cost (LCC) analysis, and life cycle assessment (LCA). Sensitivity and uncertainty analyses were used to characterize the relative importance of individual design decisions, and to navigate trade-offs across environmental, economic, and technological criteria. Based on this analysis, there are design and operational conditions under which submerged AnMBRs could be net energy positive and contribute to the pursuit of carbon negative wastewater treatment.This research work was possible thanks to project CTM2011-28595-C02-01/02 (funded by the Spanish Ministry of Economy and Competitiveness jointly with the European Regional Development Fund and Generalitat Valenciana GVA-ACOMP2013/203), and by the King Abdullah University of Science and Technology (KAUST) Academic Partnership Program (UIeRA 2012-06291), which are gratefully acknowledged. The authors would like also to acknowledge the Jack Kent Cooke Foundation for partial funding for B.D. Shoener.Pretel-Jolis, R.; Shoener, BD.; Ferrer, J.; Guest, J. (2015). Navigating environmental, economic, and technological trade-offs in the design and operation of submerged anaerobic membrane bioreactors (AnMBRs). Water Research. (87):531-541. https://doi.org/10.1016/j.watres.2015.07.002S5315418

Modelling gas-liquid mass transfer in wastewater treatment : when current knowledge needs to encounter engineering practice and vice versa

Abstract Gas–liquid mass transfer in wastewater treatment processes has received considerable attention over the last decades from both academia and industry. Indeed, improvements in modelling gas–liquid mass transfer can bring huge benefits in terms of reaction rates, plant energy expenditure, acid–base equilibria and greenhouse gas emissions. Despite these efforts, there is still no universally valid correlation between the design and operating parameters of a wastewater treatment plant and the gas–liquid mass transfer coefficients. That is why the current practice for oxygen mass transfer modelling is to apply overly simplified models, which come with multiple assumptions that are not valid for most applications. To deal with these complexities, correction factors were introduced over time. The most uncertain of them is the α-factor. To build fundamental gas–liquid mass transfer knowledge more advanced modelling paradigms have been applied more recently. Yet these come with a high level of complexity making them impractical for rapid process design and optimisation in an industrial setting. However, the knowledge gained from these more advanced models can help in improving the way the α-factor and thus gas–liquid mass transfer coefficient should be applied. That is why the presented work aims at clarifying the current state-of-the-art in gas–liquid mass transfer modelling of oxygen and other gases, but also to direct academic research efforts towards the needs of the industrial practitioners

Optimization methodology for high COD nutrient-limited wastewaters treatment using BAS process

Optimization of biofilm activated sludge (BAS) process via mathematical modelling is an entangle activity since economic, environmental objective and technical decision must be considered. This paper presents a methodology to optimize the operational conditions of BAS process in four steps by combining dynamic simulation techniques with non-linear optimization methods and with operative decision-making criteria. Two set of variables are separately prioritized in the methodology: essential variables related to physical operation to enforce established process performance, and refinement variables related to biological processes that can generate risks of bulking, pin-point floc and rising sludge. The proposed optimization strategy is applied for the treatment of high COD wastewater under nutrient limitation using an integrated mathematical model for COD removal that include predation, hydrolysis and a simplified approach to the limiting solids flux theory in the secondary clarifier in order to facilitate the convergence of the optimization solver. The methodology is implemented in a full-scale wastewater treatment plant for a cellulose and viscose fibre mill obtaining (i) improvement of the effluent quality index (Kg pollution/m3) up to 62% and, (ii) decrease the operating cost index (€/m3) of the process up to 30% respect the regular working operational conditions of the plant. The proposed procedure can be also applied to other biological treatments treating high COD nutrient-limited industrial wastewater such as from textile and winery production among others

Development of an environmental decision support system for the selection and integrated assessment of process flow diagrams in wastewater treatment

The wastewater treatment plays an important role in the maintenance of natural water resources. However, regardless of the technology used or the level of treatment required, the treatment plants of the XXI century are highly complex systems that not only need to meet technical requirements, but also environmental and economic criteria. In this context, decision support systems for environmental domains (English, Environmental Decision Support Systems or EDSS) are configured as an effective tool to support the selection and evaluation of integrated water treatment alternatives. The EDSS designed can be defined as interactive software, flexible and adaptable, which links the numerical models / algorithms, techniques and environmental ontologies, knowledge-based environment, and is capable of supporting decision making, either in choosing between different alternatives, improving potential solutions, or in the integrated assessment using methodologies ranging from environmental (Life Cycle Analysis) to economicLa depuració d’aigües residuals juga un paper fonamental en el manteniment dels recursos hídrics naturals. Tanmateix, sigui quina sigui la tecnologia emprada o el nivell de depuració requerit, les plantes de tractament del segle XXI són sistemes d’alta complexitat, que no només han de satisfer requeriments de tipus tècnic, sinó també de tipus ambiental i econòmic. En aquest context, els sistemes de suport a la decisió en dominis ambientals (en anglès, Environmental Decision Support Systems o EDSS) es configuren com una eina eficaç per donar suport a la selecció i a l’avaluació integrada de diferents alternatives de depuració d’aigües. El EDSS dissenyat pot definir-se com un programari interactiu, flexible i adaptable, que vincula els models numèrics/algoritmes amb tècniques basades en el coneixement i ontologies ambientals, i que és capaç de donar suport a la presa de decisió, ja sigui en l’elecció entre diferents alternatives, millorant una solució, o bé en l’avaluació integrada a través de metodologies ambientals (Anàlisi de Cicle de Vida) i econòmique