Dataset Information

Modeling the energy consumption of potable water reuse schemes.

ABSTRACT: Potable reuse of municipal wastewater is often the lowest-energy option for increasing the availability of fresh water. However, limited data are available on the energy consumption of potable reuse facilities and schemes, and the many variables affecting energy consumption obscure the process of estimating energy requirements. By synthesizing available data and developing a simple model for the energy consumption of centralized potable reuse schemes, this study provides a framework for understanding when potable reuse is the lowest-energy option for augmenting water supply. The model is evaluated to determine a representative range for the specific electrical energy consumption of direct and indirect potable reuse schemes and compare potable reuse to other water supply augmentation options, such as seawater desalination. Finally, the model is used to identify the most promising avenues for further reducing the energy consumption of potable reuse, including encouraging direct potable reuse without additional drinking water treatment, avoiding reverse osmosis in indirect potable reuse when effluent quality allows it, updating pipe networks, or using more permeable membranes. Potable reuse already requires far less energy than seawater desalination and, with a few investments in energy efficiency, entire potable reuse schemes could operate with a specific electrical energy consumption of less than 1 kWh/m3, showing the promise of potable reuse as a low-energy option for augmenting water supply.

SUBMITTER: Tow EW

PROVIDER: S-EPMC8640112 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Modeling the energy consumption of potable water reuse schemes.

Tow Emily W EW Hartman Anna Letcher AL Jaworowski Aleksander A Zucker Ines I Kum Soyoon S AzadiAghdam Mojtaba M Blatchley Ernest R ER Achilli Andrea A Gu Han H Urper Gulsum Melike GM Warsinger David M DM

Water research X 20211121

Potable reuse of municipal wastewater is often the lowest-energy option for increasing the availability of fresh water. However, limited data are available on the energy consumption of potable reuse facilities and schemes, and the many variables affecting energy consumption obscure the process of estimating energy requirements. By synthesizing available data and developing a simple model for the energy consumption of centralized potable reuse schemes, this study provides a framework for understa ...[more]

PMID: 34901816

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Project description:Wastewater reclamation and reuse have the potential to supplement water supplies, offering resiliency in times of drought and helping meet increased water demands associated with population growth. Non-potable water reuse represents the largest potential reuse market. Yet economic constraints for new water reuse infrastructure and safety concerns due to microbial water quality, and especially viral pathogen exposure, limit widespread implementation of water reuse. Cost-effective, real-time methods to measure or indicate viral quality of recycled water would do much to instill greater confidence in the practice. This manuscript discusses advancements in monitoring and modeling of viral health risks in the context of water reuse. First, we describe the current wastewater reclamation processes and treatment technologies with an emphasis on virus removal. Second, we review technologies for the measurement of viruses, both culture- and molecular-based, along with their advantages and disadvantages. We introduce promising viral surrogates and specific pathogenic viruses that can serve as indicators of viral risk for water reuse. We suggest metagenomic analyses for viral screening and flow cytometry for quantification of virus-like particles as new approaches to complement more traditional methods. Third, we describe modeling to assess health risks through quantitative microbial risk assessments (QMRAs), the most common strategy to couple data on virus concentrations with human exposure scenarios. We then explore the potential of artificial neural networks (ANNs) to incorporate suites of data from wastewater treatment processes, water quality parameters, and viral surrogates. We recommend ANNs as a means to utilize existing water quality data, alongside new complementary measures of viral quality, to achieve cost-effective strategies to assess risks associated with infectious human viruses in recycled water. Given the review, we conclude that technologies are ready for identifying and implementing viral surrogates for health risk reduction in the next decade. Incorporating modeling with monitoring data would likely result in more robust assessment of water reuse risk.

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Dataset Information

Modeling the energy consumption of potable water reuse schemes.

Publications

Modeling the energy consumption of potable water reuse schemes.

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