Ken'Ichi Matsumoto

Residential consumption is a major source of greenhouse gas emissions, and rapid population aging is reshaping how these emissions are generated and distributed. In aging societies, later-life carbon outcomes are influenced not only by income and consumption needs but also by intergenerational support, housing conditions, digital access, and climatic exposure. China provides an important setting because population aging, strong family support systems, and large cross-city climatic differences coexist with substantial heterogeneity in household living conditions. However, micro-level evidence remains limited regarding how carbon-footprint heterogeneity varies across adjacent later-life cohorts and across these multiple dimensions. Here we show, by linking an environmentally extended multi-regional input–output framework to data for 15 243 individuals in 104 Chinese cities, that assigned per-capita household consumption-based carbon footprints differ systematically between adults aged 45–64 years and those aged 65 years and older, and that the nonlinear associations with key socioeconomic factors also vary across cohorts: income exhibits a U-shaped association, whereas assets and intergenerational support exhibit inverted-U associations, with these relationships differing in strength between the two groups. Model-implied scenario contrasts indicate that the largest predicted differentials arise across climate-related settings, reaching 407.95 kg-CO ₂ /cap for cold-versus-temperate conditions and 190.87 kg-CO ₂ /cap for hot-versus-temperate conditions. In addition, a reduction in durable-goods expenditure among high-income adults aged 45–64 years is associated with a predicted decline of 112.6 kg-CO ₂ /cap, of which vehicle outlays account for the largest share. These findings suggest that later-life carbon heterogeneity is shaped not only by affluence but also by cohort–specific consumption patterns and climate-related living environments, thereby providing a more differentiated basis for mitigation design in aging societies.

The intersection of the COVID-19 pandemic and tourism has significantly influenced emissions from supply chains, highlighting a complex dynamic between tourism and climate change. Although the pandemic represents a unique event within a specific timeframe, analyzing its impact on tourism provides valuable insights into the characteristics of tourism carbon footprints (TCF) in the context of sudden public health crises. Accordingly, we used the latest data available from the global multi-regional input–output table of EXIOBASE3 and Japan’s tourist consumption statistics to estimate the TCF from all tourist sources in Japan based on the global economic system, and we visualized the carbon flow caused by population mobility. The decomposition of the environmental impact of the pandemic response further identified the driving forces of TCF changes. The main findings suggested that substantial differences exist in the emission levels and sectoral distributions of TCF between inbound and domestic tourism in Japan. Domestic TCF accounted for the majority of the overall TCF, and it also showed a stronger ability to withstand the pandemic impact, accounting for over 90% of Japan’s TCF during the pandemic. The pandemic greatly reduced the TCF and further exacerbated the driving differences. Prior to the pandemic, Japan’s TCF had diverse driving forces; however, pandemic-induced restrictions magnified the volume effect, especially in the inbound TCF, whereas other effects remained substantial for the domestic TCF.

The enhancement of the carbon trading mechanism signifies a gradual transition in China’s environmental regulatory framework, shifting from a command and control approach to a market-based incentive model. Despite the significance of this shift, existing research has insufficiently explored the impact of market-oriented environmental policies on consumption-based emissions. This study leverages the carbon trading policies implemented in 2013 as a quasi-natural experiment, combined with a precise measurement of urban and rural household carbon emissions (HCE) during 2005–2021. Employing a difference-in-differences method, we evaluate the heterogeneous impact of these policies on urban and rural HCE. The results demonstrate a significantly negative effect of the policies on indirect HCE, a conclusion that remains robust across various placebo and robustness tests. Furthermore, we identify the transmission mechanisms through which carbon trading policies affect the reduction in HCE. The results indicate that the policy has a significant negative impact on indirect HCE, with a notable urban–rural difference. The effect of the policy is −0.829 for urban areas and −0.365 for rural areas, a conclusion that remains robust across various placebo and robustness checks. Additionally, we identified two transmission mechanisms through which carbon trading policies operate: financial deepening and employment effects. Lastly, we found that carbon trading policies can reduce carbon inequality between urban and rural areas by 46.8%.

CO₂ emissions embodied in domestic trade between Japanese prefectures are gradually increasing and becoming an important growth point in the country’s CO₂ emissions. The primary objective of this study is to evaluate the CO₂ emissions embodied in Japan’s domestic imports and exports to visualize the carbon transfer paths between prefectures according to the attributes of production and consumption: also to identify the influencing factors of the carbon flow. This study estimated the CO₂ emissions embodied in domestic imports and exports by prefectures using input–output analysis, followed by the log-mean Divisia index decomposition approach, which is used to quantify the influencing factor of net export CO₂ emissions across prefectures. The results show substantial regional differences in the CO₂ emissions embodied in domestic imports and exports across prefectures. Manufacturing prefectures satisfy most of Japan’s domestic demand for industrial products and are the main net exporters of CO₂ emissions. Carbon flow is more obvious in economically advanced regions (such as the Kanto and Kansai regions) and covers more prefectures through carbon transfer. Consumer prefectures import the most CO₂ emissions and export large amounts of CO₂ emissions to other prefectures. Among the three factors influencing net export CO₂ emissions, the technology effect has the most significant impact through the carbon intensity of domestic trade flows. These findings highlight the substantial differences in CO₂ emissions embodied in domestic trade and the influencing factors across prefectures in Japan. The responsibility for emission reduction is attributable to both manufacturing and consumer prefectures.