Is it acceptable to have a child? Revealing Chinese household carbon footprints from a demographic perspective using the Particle Swarm Optimization (PSO) model

Abstract

Calculating personal household carbon footprints is crucial to achieve carbon neutrality while accounting for the age transition and urban-rural and gender structures. However, such a calculation is rarely performed from a demographic perspective due to the need for elaborate consumption surveys and frequent population censuses. Here, we present an integrated framework coupled input-output analysis with a Particle Swarm Optimization (PSO) model to determine the personal household carbon footprint from a demographic perspective in China. We found that personal household carbon footprints in urban and rural China have grown continuously from 1997 to 2017. The urban and rural household carbon footprints increased from 1.58 and 0.63 tons/a·person to 2.43 and 1.41 tons/a·person, respectively. In 2017, the household carbon footprints of 15- and 65-year-olds were the highest, while those of 0- and 40-year-olds were the lowest. The indirect household carbon footprint of men was greater than that of women in all age groups, with the greatest difference between men and women observed in 2017 (0.075 tons/a·person). The total household carbon footprint of a 24-year-old individual (born in 1997) was 60.9 and 27.2 tCO2in urban and rural areas, respectively, which requires an equivalent of 71 and 32 trees to achieve carbon neutrality. Herein, we highlight that a range of policies that take consider different demographic characteristics are needed to effectively reduce the carbon footprint. The data and results presented in the paper provide policymakers with useful information for the formation of appropriate policies aimed at carbon footprint reduction from a demographic perspective.