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City-wide model-based analysis of heat recovery from wastewater using an uncertainty-based approach
Lund University, Sweden.
RISE Research Institutes of Sweden, Built Environment, Infrastructure and concrete technology. Lund University, Sweden.ORCID iD: 0000-0003-1547-8413
RISE Research Institutes of Sweden, Built Environment, Infrastructure and concrete technology. Lund University, Sweden.
RISE Research Institutes of Sweden, Built Environment, Infrastructure and concrete technology.ORCID iD: 0000-0001-9838-2470
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2022 (English)In: Science of the Total Environment, ISSN 0048-9697, E-ISSN 1879-1026, Vol. 820, article id 153273Article in journal (Refereed) Published
Abstract [en]

Around 90% of the energy requirement for urban water systems management is for heating domestic tap water. In addition, the energy content of wastewater is mainly in the form of heat (85%). Hence, there is an obvious interest in recovering a large portion of this heat. However, city-wide scenario analyses that evaluate heat recovery at various locations while considering impacts on wastewater treatment plant (WWTP) performance are currently very limited. This study presents a comprehensive model-based city-wide evaluation considering four different heat recovery locations (appliance, household, precinct and WWTP effluent) for a Swedish city with varying degrees of implementation using an uncertainty-based approach. Results show that heat recovery at the appliance level, with heat exchangers installed at 77% of the showers at domestic households, leads to a mean energy recovery of 127 MWh/day with a 0.25 °C reduction in mean WWTP inlet temperature compared to the default case without heat recovery. The highest mean temperature reduction compared to the default case is 1.5 °C when heat is recovered at the precinct level for 77% of the domestic wastewater flow rate. Finally, the impact on WWTP nitrification capacity is negligible in this case due to its large existing capacity and design. © 2022 The Authors

Place, publisher, year, edition, pages
Elsevier B.V. , 2022. Vol. 820, article id 153273
Keywords [en]
City-wide modelling, Heat recovery, Uncertainty analysis, Wastewater, Effluents, Heating, Recovery, Waste heat, Wastewater treatment, City-wide modeling, Energy content, Energy requirements, Management IS, Model-based analysis, Systems management, Tap water, Uncertainty, Urban water systems, Waste water treatment plants, article, effluent, energy recovery, flow rate, household, nitrification, waste water treatment plant
National Category
Water Engineering
Identifiers
URN: urn:nbn:se:ri:diva-58497DOI: 10.1016/j.scitotenv.2022.153273Scopus ID: 2-s2.0-85123381630OAI: oai:DiVA.org:ri-58497DiVA, id: diva2:1638976
Note

Funding details: LU 2020/2-32; Funding details: Svenska Forskningsrådet Formas, 942-2016-80; Funding details: Svenskt Vatten, SWWA, 16-106; Funding text 1: The authors acknowledge the financial support provided by the Swedish research council Formas ( 942-2016-80 ), Swedish Water ( 16-106 ), Sweden Water Research , and Tekniska Verken i Linköping for the project HÅVA (‘Sustainability analysis for heat recovery from wastewater’). Tekniska Verken i Linköping is also gratefully acknowledged for their financial support and for supporting measurement campaigns. The computations were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) through the Center for Scientific and Technical Computing at Lund University (LUNARC) under project LU 2020/2-32.; Funding text 2: The authors acknowledge the financial support provided by the Swedish research council Formas (942-2016-80), Swedish Water (16-106), Sweden Water Research, and Tekniska Verken i Link?ping for the project H?VA (?Sustainability analysis for heat recovery from wastewater?). Tekniska Verken i Link?ping is also gratefully acknowledged for their financial support and for supporting measurement campaigns. The computations were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) through the Center for Scientific and Technical Computing at Lund University (LUNARC) under project LU 2020/2-32.

Available from: 2022-02-18 Created: 2022-02-18 Last updated: 2023-05-25Bibliographically approved

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Arnell, MagnusAhlström, Marcus

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