Water conservation strategies reduce greenhouse gas emission from wastewater treatment plants: A domino effect
Wastewater-treatment plants (WWTPs) enable urban water reclamation but are significant sources of greenhouse-gas (GHG) emissions. Because GHG output scales with the volume and pollutant load of influent sewage, city-wide water-use patterns offer a direct yet under-examined lever for decarbonizing WW...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-07-01
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| Series: | Environmental Science and Ecotechnology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666498425000523 |
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| Summary: | Wastewater-treatment plants (WWTPs) enable urban water reclamation but are significant sources of greenhouse-gas (GHG) emissions. Because GHG output scales with the volume and pollutant load of influent sewage, city-wide water-use patterns offer a direct yet under-examined lever for decarbonizing WWTP operations. The feedbacks linking demand-side water conservation to plant emissions remain poorly understood, obscuring important mitigation co-benefits. Here we show a domino-effect feedback between urban water-use patterns with WWTP carbon emissions. Our analysis demonstrates that optimized water management can improve average WWTP eco-efficiency by up to 189 %, leading to an annual reduction in water consumption of 48.3 billion m3 and a decrease in GHG emissions by 1.67 million tons CO2-equivalent. Under this synergistic water-carbon management scenario, the wastewater sector could achieve carbon neutrality by 2037, seven years ahead of schedules based solely on technological advancements. Our findings present a novel and replicable framework that simultaneously addresses water scarcity and climate change. Unlike costly and slow-to-implement technological innovations, leveraging cross-sectoral synergies in water-intensive industries such as agriculture and manufacturing offers a pragmatic pathway to meeting critical carbon-reduction targets. |
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| ISSN: | 2666-4984 |