The potential of mitigating greenhouse gas emissions from urban domestic water systems in highly urbanized areas

Abstract

In highly urbanized areas, domestic water consumption and wastewater discharge are affected by several dynamic factors, such as economy, population, and environment, which further influence the greenhouse gas (GHG) mitigation potential of urban domestic water systems (UDWSs). To analyze GHG emission features of the UDWSs and their interactions with urban economic development, a hybrid approach of correlation analysis and a programming model was incorporated in a life-cycle framework to provide decision-making support for GHG mitigation strategies in the UDWSs. To verify the applicability of the method, Shenzhen city in Guangdong Province was chosen to analyze the potential of the UDWS for mitigating GHG emissions. The GHG emissions from the UDWS in Shenzhen was 747.82 kt CO2 eq in 2020. Compared with 2020, domestic water consumption would increase by 11.35 % and 18.67 % in 2025 and 2030, and wastewater discharge would increase by 12.88 % and 19.73 % in 2025 and 2030, respectively. In the trend of socio-economic development, the amount of water demand and wastewater discharge of urban residents would increase by 11.49 % to 18.75 % and 12.88 % to 19.75 % from 2020 to 2030, respectively. Optimum strategies of technologies for wastewater treatment and energy mix for electricity generation were obtained, with consideration of GHG mitigation goals in the future. As energy consumption contributed more than 25 % of GHG emissions in the USDWs of Shenzhen, the contributions of new energy sources for electricity production (i.e., offshore wind, solar photovoltaic, biomass, and nuclear) would increase by 0.58–1.02 times and 0.68–1.20 times from 2020 to 2025 and 2025 to 2030, respectively. The capacity of wastewater treatment would increase by 53.33 % to 80.00 % and 27.44 % to 29.82 % of the SBR and AAO technologies, respectively. Thus, it is suggested that decision makers should pay close attention to optimizing energy mix of electricity production.