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Electricity consumption and anaerobic reactions cause direct and indirect greenhouse gas (GHG) emissions within domestic sewage treatment systems (DSTSs). GHG emissions in DSTSs were influenced by the sewage quantity and the efficacy of treatment technologies. To address combined effects of these variables, this study presented an approach for identifying pathways for GHG mitigation within the DSTSs of cities under climate change and socio-economic development, through combining life cycle analysis (LCA) and the Hierarchical Archimedean copula (HAC) methods. The approach was innovative in the following aspects: 1) quantifying the GHG emissions of the DSTSs; 2) identifying the correlations among temperature changes, socioeconomic development, and domestic sewage quantity, and 3) predicting the future fluctuations in GHG emissions from the DSTSs. The effectiveness of the proposed approach was validated through its application to an urban agglomeration in the Pearl River Delta (PRD), China. To identify the potentials of GHG mitigation in the DSTSs, two pathways (i.e., general and optimized) were proposed according to the different technical choices for establishing facilities from 2021 to 2030. The results indicated that GHG emissions from the DSTS in the PRD were [3.01, 4.96] Mt CO 2 eq in 2021, with substantial contributions from Shenzhen and Guangzhou. Moreover, GHG emissions from the sewage treatment facilities based on Anaerobic-Anoxic-Axic (AAO) technology were higher than those based on other technologies. Under the optimized pathway, GHG emissions, contributed by the technologies of Continuous Cycle Aeration System (CASS) and Oxidation Ditch (OD), were the lowest. Through the results of correlation analysis, the impact of socioeconomic development on domestic sewage quantities was more significant than that of climate change. Domestic sewage quantities in the cities of the PRD would increase by 4.10%–28.38%, 17.14%–26.01%, and 18.15%–26.50% from 2022 to 2030 under three Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5. These findings demonstrated that the capacities of domestic sewage treatment facilities in most cities of the PRD should be substantially improved from 0.12 to 2.99 times between 2022 and 2030. Under the optimized pathway, the future GHG emissions of the CASS method would be the lowest, followed by the OD method. • The correlations between domestic sewage quantity, socioeconomic development, and climate change were focused on. • A hybrid approach based on LCA and HAC was proposed for GHG mitigation in domestic sewage treatment systems. • A typical region of China was adopted for illustrating applicability of the developed approach. • Two pathways were proposed according to the different choices for technical facilities from 2022 to 2030. [ABSTRACT FROM AUTHOR]

• The method of compiling the multi-regional input output is optimized. • Carbon emissions of urban agglomerations (UAs) are studied from multiple perspectives. • Carbon flows within the UA driven by final demand and primary inputs are identified. • Carbon emissions of the UA are predicted when considering uncertainty. Urban agglomerations (UAs) play a momentous role in carbon reduction. The prerequisites for achieving carbon reduction goals in UAs are accounting and predicting their carbon emissions. When considering carbon reduction goals in China, it is crucial to pay attention to the joint influence of carbon emissions and economic benefits. Hence, in this study, an improved multi-regional input–output (MRIO) approach was established to quantify and predict carbon emissions for the UA, incorporating a biproportional scaling method (RAS) and Latin hypercube sampling (LHS). Specifically, a) the carbon emissions of UAs were quantified using the MRIO model from the perspectives of production, consumption and income; b) the carbon flows between cities in UAs were identified based on final demand and primary inputs, and c) the features of UAs' carbon emissions in the future were predicted using RAS and LHS. To verify the effectiveness of the approach, a case study of a typical UA region in China [i.e., the Pearl River Delta (PRD)] was proposed. The results showed that the contribution of sectors to carbon emissions could be identified from multiple perspectives, and carbon flows can help regions coordinate emissions reductions. The majority of future carbon emissions would be generated from the areas of population and economic agglomeration (i.e., Guangzhou and Shenzhen), although the growth trend of carbon emissions of those would keep lower. The policy of carbon reduction should be urgently carried out in locations with high carbon emissions growth rates (e.g., Zhaoqing and Zhuhai). To improve the ability for carbon reduction in the PRD, cooperation in multiple cities to promote energy efficiency is advocated. The government should also increase technical support for carbon reduction and consider the balanced development of the economy, population, and resources in the PRD. [ABSTRACT FROM AUTHOR]