The impact of population aging on household carbon emissions and its heterogeneity: evidence from CGSS 2018 data in China

Abstract Background Against the backdrop of the “Dual Carbon” goals and accelerated population aging, changes in household demographic structure may influence household carbon emissions; however, existing research has not fully examined these effects and their heterogeneity at the micro household level. This study aims to investigate the impact of population aging on household carbon emissions and its heterogeneity based on Chinese household microdata. Methods Using data from the 2018 China General Social Survey (CGSS), this study employed the STIRPAT model and OLS regression. It characterizes population aging from three dimensions—“whether there are elderly members”, “proportion of elderly members”, and “average age of elderly members”—to examine its impact on total household carbon emissions, direct carbon emissions, and indirect carbon emissions, and further analyzes the heterogeneity of urban-rural, regional, climate conditions, as well as the mediating effect of household expenditure. Results This study found a significant negative correlation between population aging and household carbon emissions, with the “structural effect” being stronger than the “age effect”. Households with elderly members have significantly reduced carbon emissions, and the higher the proportion of elderly members, the more significant the reduction in household carbon emissions. The impact of population aging on indirect carbon emissions is stronger than that on direct carbon emissions, indicating that it mainly exerts its effect by reducing expenditure and adjusting consumption structure. Heterogeneity analysis shows that the reduction in household carbon emissions caused by population aging is more pronounced in rural, central, and northern China. Conclusion Population aging has reduced household carbon emissions, which is of significant value for low-carbon governance. Policymakers should incorporate population aging into the household emission reduction framework and consider urban-rural and regional differences to promote differentiated low-carbon policy design.