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- W4306292733 startingPage "134695" @default.
- W4306292733 abstract "Decarbonization of urban water systems has been increasingly important for addressing the target of climate change mitigation. Yet, little insight has been derived regarding how water use and energy transition policies jointly alter climate impact of water systems in cities. In this study, using 21 cities in Guangdong Province (China) as a case study, we account for the carbon dioxide emissions related to energy use in urban water systems (UWSs) over 2006–2035. By constructing a city-scale water-carbon nexus model, we project future trajectories of electricity-related CO2 emissions in UWSs by considering dynamics of water demand and varying pathways of energy transition. We show that increasing need of tap water purification is a main contributor to electricity-related CO2 emissions, followed by tap water distribution and wastewater treatment. The electricity-related CO2 emissions in most cities could peak before 2030 under a fast-decarbonization energy transition pathway, despite the rise of urban water demand. Fast-urbanizing cities like Foshan, Shantou and Qingyuan may witness a 4–23% increase of emissions between 2020 and 2035. With a more rapid increase of proportion of cleaner energies in electricity mix, the fast-decarbonization pathway could end up with 21% more reduction of emissions on average during 2020–2035, compared to currently-planned energy transition pathway. Under the stringent climate goal of China, cities should foster a joint mechanism between water system and grid companies that leads to a more effective low-carbon governance of water systems." @default.
- W4306292733 created "2022-10-15" @default.
- W4306292733 creator A5010748983 @default.
- W4306292733 creator A5033763955 @default.
- W4306292733 date "2022-12-01" @default.
- W4306292733 modified "2023-10-18" @default.
- W4306292733 title "Carbon peaks of water systems in Chinese cities under varying water demand dynamics and energy transition pathways" @default.
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- W4306292733 doi "https://doi.org/10.1016/j.jclepro.2022.134695" @default.
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