In order to meet climate change mitigation goals, nations such as Japan need to consider strategies to reduce the impact that lifestyles have on overall emission levels. This study analyzes carbon footprints from household consumption (i.e., lifestyles) using index and structural decomposition analysis for the time period from 1990 to 2005. The analysis identified that households in their 40s and 50s had the highest levels of both direct and indirect CO₂ emissions, with decomposition identifying consumption patterns as the driving force behind these emissions and advances in CO₂ reduction technology having a reducing effect on lifestyle emissions. An additional challenge addressed by this study is the aging, shrinking population phenomenon in Japan. The increase in the number of few-member and elderly households places upward pressure on emissions as the aging population and declining national birth rate continues. The analysis results offer two mitigatory policy suggestions: the focusing of carbon reduction policies on older and smaller households, and the education of consumers toward low-carbon consumption habits. As the aging, shrinking population phenomenon is not unique to Japan, the findings of this research have broad applications globally where these demographic shifts are being experienced.

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.

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.

China's digital transformation is increasingly embodied in digital goods and services used as intermediate inputs in production. Yet existing research still provides limited evidence on whether the carbon implications of digital deepening are stable across regions and sectors, through which mechanisms they evolve, and how such heterogeneity translates into future emissions risk. To address this gap, we conceptualize digitalization as production-embedded digital inputs and examine how these inputs reshape production-based emissions across heterogeneous provincial roles and interindustry stages in China. We harmonize Asian Development Bank input-output tables with CO₂ emissions accounts to construct a national-province-sector panel for 2009-2022, and combine Tapio decoupling diagnostics, logarithmic mean Divisia index decomposition, and Monte Carlo-based STIRPAT projections for 2023-2035. Four main findings emerge. First, digital deepening and CO₂ emissions remain spatially misaligned, separating the locations where digital demand is generated from those where emissions are recorded. Second, decoupling regimes are structured rather than random. Coastal provinces with strong service-manufacturing linkages more often move toward stronger decoupling, whereas northern provinces specialized in resource extraction and heavy industry more frequently remain locked in coupling regimes. Third, the carbon consequences of digital inputs depend on shifting bundles of transmission channels. Digital inputs often intensify scale pressure, but mitigation arises when diffusion is absorbed as efficiency-enhancing capital that strengthens substitution and improves energy performance. By contrast, in upstream energy and materials systems, digital tools can raise utilization and reinforce carbon lock-in. Fourth, faster diffusion widens upper-tail emissions risk in upstream production bases, whereas metropolitan service economies stabilize earlier and display narrower uncertainty bands. Overall, the marginal carbon effect of digital inputs is not fixed in sign, but is instead a governable system outcome shaped by network position, absorption mode, and binding constraints.