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Although China boasts the largest online consumption market, there has been no prior case study addressing the carbon footprint of online consumption. The rapid expansion of online consumption has posed a challenge to China's carbon neutrality pledge. This paper aims to fill this crucial gap by conducting a pioneering study based on survey data collected from 6000 households. To achieve this goal, this study has combined provincial Multi-Regional Input-Output (MRIO) tables with residents' online consumption calculated by the Non-Linear Optimization model, and applied the Environmental Input-Output Life Cycle Assessment (EIO-LCA) model to calculate the carbon footprint of residents' online consumption. Result indicated that the average carbon footprint of residents' online consumption was 0.46 tCO 2 e in 2016, accounting for 12.30% of the total consumption carbon footprint. Notably, high-emission regions include Beijing-Tianjin, Jiangsu-Zhejiang-Shanghai, and Hubei. Moreover, the dominant sources of the online consumption carbon footprint were electricity, food, clothing, and beauty products. Furthermore, we found that the carbon footprint of online consumption tends to increase with income, with differential income elasticities observed for various products and income groups. We also quantified the average expenditure-based life-cycle carbon coefficient for parcel delivery (0.22 kgCO 2 e/yuan) and conducted two scenario analyses to assess its impact. From a policy perspective, our research on measuring the carbon footprint of residents' online consumption can provide valuable insights for designing future policies and decisions related to e-commerce and key sectors along the supply chains. Additionally, it will further encourage Chinese residents to adopt low-carbon lifestyles. • Identifies the expenditure structure of residents' online consumption. • The carbon footprint of Chinese residents' online consumption in 25 regions. • The income elasticity of online consumption carbon footprint. • The last mile emission intensity of e-commerce is quantified. [ABSTRACT FROM AUTHOR]