Validation of a decision support tool for wastewater treatment selection

Castillo, A.; Porro, José; Garrido-Baserba, Manel; Rosso, Diego; Renzi, D.; Fatone, Francesco; Gómez, V.; Comas, Joaquím; Poch, Manel

doi:10.1016/j.jenvman.2016.09.087

Cited by 42 publications

(19 citation statements)

References 18 publications

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“…Sociocultural aspects can also be easily considered in EDSS for planning purposes by modifying the assigned weights of the existing social criteria (increasing or decreasing depending on the local relevance) or, if needed, by adding more specific criteria. See the case for NOVEDAR EDSS, which has also been validated with case studies from US . Therefore, transferability of our EDSS is easy and has already been demonstrated, since a significant part of the knowledge base can be generalized while the specific part related to sociocultural difference not yet but we foresee that being easy as well.…”

Section: Discussionsupporting

confidence: 83%

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

et al. 2017

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sensors, and the overwhelming evidence of environmental strain and global economic issues caused by the extensive pressure on resources exerted by the demands of growing populations indicate that environmental systems composed of multiple interacting agents or variables that cause emergent behavior require complex manage ment strategies. In addition, improving environment-friendly practices related to the use and/or reuse of natural resources to minimize detrimental effects on the natural environment has become a prominent issue. Therefore, increasingly advanced and sophisticated management tools capable of integrating heuristic knowledge and quantitative and qualitative information are required.The initial concept of a decision support system (DSS) emerged in the business, economics, and management sciences. A DSS is an intelligent information system that reduces the time in which decisions are made within a domain and improves the consistency and quality of these decisions. [1] DSSs use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives; [2,3] and such systems focus on strategic decisions and not operational ones. More specifically, a DSS should contribute to the reduction of the uncertainty faced by managers when they need to take decisions regarding future options. [4] Similar definitions can be found in ref. [5,6] Environmental decision support systems (EDSSs) are a class of DSS that demonstrates all of the capabilities of a DSS on an environmental field scale. [5,7,8] EDSSs have been increasingly applied in more intense and efficient ways, and an increased number of systems have been developed. A metric of their increasing implementation is that more than 3300 references have been cited on this topic in specialized journals over the last ten years (search on SCOPUS on February 2016).The quality and quantity of available water resources is decreasing because of the intensive use of surface and groundwater by cities, industry and agriculture, and the associated impacts of the point pollution and diffuse discharge of the generated wastewater. [9] The optimal and integrated management of water resources is a paradigmatic example of circumstances in which an EDSS can play an important role by integrating data from different origins and with different quality with infrastructures managed by several public and private actors under different legal frameworks with a final goal of preserving 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...

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Section: Discussionsupporting

confidence: 83%

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

et al. 2017

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“…Therefore, two key stakeholder groups are researchers and other innovators working on the forefront of process engineering, as well as funding agencies, venture capitalists, and/or other investors in technology development. Secondly, as water service providers endeavor to integrate management of wastewater into a holistic urban water infrastructure, the importance of moving beyond a cost and benefit decision‐making approach to the use of a multidisciplinary approach that integrates several analytical tools (e.g., life cycle assessment (LCA), life cycle cost analysis (LCCA), assessment of societal indicators, and multicriteria decision analysis (MCDA) to account for stakeholder priorities) is increasingly recognized (Castillo et al., ; Garrido‐Baserba et al., ; Guest et al., ). This requires engagement of numerous stakeholders for integrated decision‐making; generation of data on the environmental and ecological impacts, economics, and social implications of decisions; technical performance of treatment technologies; and an enhanced understanding of tradeoffs in decision outcomes in the local context.…”

Section: Methodsmentioning

confidence: 99%

Sustainability metrics for assessing water resource recovery facilities of the future

Cornejo

Becker

Pagilla

et al. 2019

Water Environment Research

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The recovery of water, energy, and nutrients from water resource recovery facilities (WRRFs) is needed to address major global challenges, such as increasing water demand and decreasing availability of non-renewable resources. To meet these challenges, innovative technological developments must lead to increased adoption of water and resource recovery processes, while addressing stakeholder needs (e.g., innovators, practioners, regulators). A testbed network of over 90 partner facilities within the U.S. and abroad will help accelerate innovation and widespread adoption of novel processes through multi-scale testing and demonstration of technologies. In this paper, we define a common set of environmental, economic, technical, and social performance metrics for innovative technologies that will meet the needs of multiple stakeholders in the decision-making process. These triple bottom line performance metrics can be used to track the sustainability of technologies in a consistent and transparent manner, while aiding the decision making process for WRRFs of the future.

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“…Hence, more than 200 retrofitting EDITOR'S CHOICE-RESEARCH ARTICLE alternatives were considered in the developed superstructure optimization framework using static models. Castillo, Porro, et al (2016) also evaluated different alternatives for the retrofitting of a WRRF using technical, environmental, economic, and social assessment in a decision support system. The outcome was a reliable basis to support decision makers on the bases of a total score with the contribution of different criterion using selected weights based on the specific need of each study and on expert criteria.…”

Section: Comparison To Previous Work and Limitations Of The Proposedmentioning

confidence: 99%

“…Variability and uncertainty were later incorporated in WRRF design (Benedetti et al, 2013). Recently, decision support systems using static models and multicriteria evaluation (Castillo, Cheali, et al, 2016;Castillo, Porro, et al, 2016) have demonstrated their capability to support decision-makers in selecting treatment alternatives for retrofitting WRRFs. The EDITOR'S CHOICE-RESEARCH ARTICLE optimal selection of WRRF processes using a superstructure optimization framework was also reported by Bozkurt, van Loosdrecht, Gernaey, and Sin (2016), where the early stage decision was addressed.…”

Section: Introductionmentioning

confidence: 99%

Systematic comparison framework for selecting the best retrofitting alternative for an existing water resource recovery facility

Machado

Lafuente

Baeza

2020

Water Environment Research

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A systematic comparison framework for selecting the best retrofitting alternative for a water resource recovery facility (WRRF) is proposed in this work. The procedure is applied comparing different possible plant configurations to retrofit an existent anoxic/oxic (A/O) WRRF (Manresa, Spain) aiming to include enhanced biological phosphorus removal (EBPR). The framework for comparison was built on system analysis using a calibrated IWA ASM2d model. A multicriteria set of performance variables, as the operational and capital expenditures (OPEX and CAPEX, respectively) and robustness tests for measuring how fast the plant configuration refuses external disturbances (like ammonium and phosphate peak loads), were used for comparison. Starting from the existent WRRF, four plant configurations were tested: single A 2 /O (only one anoxic reactor converted to anaerobic), double A 2 /O (two anoxic reactors converted to anaerobic), BARDENPHO, and UCT. The double A 2 /O plant configuration was the most economical and reliable alternative for improving the existent Manresa WRRF capacity and implementing EBPR, since the effluent quality increased 3.8% compared to the current plant configuration. In addition, the double A 2 /O CAPEX was close to €165,000 which was at the same order of the single A 2 /O and lower than the BARDENPHO and UCT alternatives. © 2020 Water Environment Federation • Practitioner points • Four configurations including EBPR were evaluated for retrofitting an A/O WRRF. • A new multicriteria comparison framework was used to select the best configuration. • Up to 13 criteria related to effluent quality, robustness and costs were included. • A single function based on the combination of all the criteria was also evaluated.

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Validation of a decision support tool for wastewater treatment selection

Cited by 42 publications

References 18 publications

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

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

Sustainability metrics for assessing water resource recovery facilities of the future

Systematic comparison framework for selecting the best retrofitting alternative for an existing water resource recovery facility

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