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In line with recent trends toward decentralization, prefectural and municipal governments in Japan are becoming increasingly involved with managing global warming in their regions. As a result, there is a new need to estimate the environmental effects of regional economic activities, which can be used to establish effective energy policies at the regional level. However, the details of these effects remain unclear due to a lack of basic data. In this paper, we construct an original multi-region input-output (MRIO) table based on interregional shipments among Japan's 47 prefectures; this is done using the prefectures' single-region input-output (SRIO) tables and by applying a non-survey technique. We use the constructed MRIO table, which we make freely available online, to estimate the carbon footprint and carbon leakage of every region and consider the structure of emissions at the regional level from the standpoints of consumer and producer responsibility. The results reveal that production-based emissions often differ significantly from consumption-based emissions. In addition, the regional-level ratio of carbon leakage to carbon footprint is 51.7 % on average and ranges from 34.8 to 79.8 %. Furthermore, the effects of economic activity in and around Tokyo in terms of CO2 emissions and leakage vary across regions.

Air pollution and its health-related effects are a major concern globally, and many people die from air pollution-related diseases each year. This study employed a structural path analysis combined with a health impact inventory database analysis to estimate the number of consumption-based PM(2.5) emission-related deaths attributed to India's power supply sector. We identified critical supply chain paths for direct (production) electricity use and indirect (consumption) use. We also considered both domestic and foreign final demand and its effect on PM(2.5) emission-related deaths. Several conclusions could be drawn from our results. First, the effect of indirect electricity usage on PM(2.5) emission-related deaths is approximately four times larger than that for direct usage. Second, a large percentage of pollution-related deaths can be attributed to India's domestic final demand usage; however, electricity usage in the intermediate and final demand sectors is inextricably linked. Third, foreign final demand sectors from the Middle East, the USA, and China contribute indirectly toward PM(2.5) emission-related deaths, specifically in the rice export supply chain. The results show that the Indian government should implement urgent measures to curb electricity use in rice supply chains in order to reduce the number of PM(2.5) emission-related deaths.

AbstractDisasters often cause exogenous flow damage (i.e., the [hypothetical] difference in economic scale with and without a disaster in a certain period) to production ("supply constraint"). However, input‐output (IO) analysis (IOA) cannot usually consider it, because the Leontief quantity model (LQM) assumes that production is endogenous; the Ghosh quantity model (GQM) is considered implausible; and the Leontief price model (LPM) and the Ghosh price model (GPM) assume that quantity is fixed. This study proposes to consider a supply constraint in the LPM, introducing the price elasticity of demand. This study uses the loss of social surplus (SS) as a damage estimation because production (sales) is less informative as a damage index than profit (margin); that is, production can be any amount if without considering profit, and it does not tell exactly how much profit is lost for each supplier (upstream sector) and buyer (downstream sector). As a model application, this study examines Japan's largest five earthquakes from 1995 to 2017 and the Great East Japan Earthquake (GEJE) in March 2011. The worst earthquake at the peak tends to increase price by 10–20% and decrease SS by 20–30%, when compared with the initial month's prices/production. The worst damage tends to last eight months at most, accumulating 0.5‐month‐production damage (i.e., the sum of [hypothetical] differences in SS with and without an earthquake [for eight months] is 50% of the initial month production). Meanwhile, the GEJE in the five prefectures had cumulatively, a 25‐month‐production damage until the temporal recovery at the 37th month.