Drivers of household carbon footprints across EU regions, from 2010 to 2015
2010年から2015年におけるEU地域別の家計カーボンフットプリントの要因 (AI 翻訳)
Jemyung Lee, Yosuke Shigetomi, Keiichiro Kanemoto
🤖 gxceed AI 要約
日本語
EU27か国の83地域における家計カーボンフットプリント（CF）を2010年と2015年について推定し、構造分解分析により変化の要因を5つ（排出原単位、サプライチェーン構造、人口、一人当たり消費、最終需要シェア）に分解した。地域ごとにCFの要因が異なり、人口密度や所得、消費パターンが影響することを示した。地域レベルの気候政策立案に有用な知見を提供する。
English
This study estimates household carbon footprints for 83 macro-regions across 27 EU countries for 2010 and 2015, using multi-regional input-output tables and micro-consumption data. Structural decomposition analysis identifies five driving factors: emission intensity, supply chain structure, population, per capita consumption, and final demand share. Results show that drivers vary by region, population density, income, and consumption patterns, offering insights for regional climate policy.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本ではSSBJ開示や地域脱炭素ロードマップが進む中、地域別の家計CFの要因分解は、自治体の排出削減策や企業のScope3算定の参考になる。EUの方法論は日本の地域別排出量推計にも応用可能。
In the global GX context
This study provides a detailed regional decomposition of household carbon footprints, relevant to global efforts on sub-national climate action and consumption-based accounting. It offers a methodological framework that can inform regional policy design and complement national-level inventories under the Paris Agreement.
👥 読者別の含意
🔬研究者:Provides a methodological framework for regional carbon footprint decomposition using MRIO and micro-data, useful for consumption-based accounting research.
🏢実務担当者:Offers insights into regional consumption patterns and drivers that can inform corporate Scope 3 assessments and regional sustainability strategies.
🏛政策担当者:Highlights the importance of regional heterogeneity in designing effective climate policies, supporting targeted interventions.
📄 Abstract（原文）
Abstract Urban regions are responsible for a significant proportion of carbon emissions. The carbon footprint (CF) is a practical measure to identify the responsibility of individuals, cities, or nations in climate change. Numerous CF studies have focused on national accounts, and a few combined consumer consumption and global supply chains to estimate additionally detailed spatial CF. However, the drivers of temporal change in detailed spatial CF are largely unknown, along with regional, spatial, and socioeconomic disparities. Here, we uncovered the drivers of changes in household CFs in EU regions, at the finest scale currently available, between 2010 and 2015. This study mapped the household CFs of 83 macro-regions across 27 EU nations and identified the driving factors underlying their temporal change. We combined multi-regional input-output tables and micro-consumption data from 275 247 and 272 045 households in 2010 and 2015, respectively. We decomposed EU regional CF, employing structural decomposition analysis, into five driving factors: emission intensity, supply chain structure, population, per capita consumption, and final demand share. For a deeper assessment of changes in the contribution of consumption patterns, we further categorized the regional CF into 15 factors, including 11 per capita consumption categories. We found that household CF drivers vary depending on region, population density, income, and consumption patterns. Our results can help policymakers adopt climate policies at the regional level by reflecting on the residents’ socioeconomic, spatial, and consumption conditions, for further ambitious climate actions.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1088/1748-9326/acc95efirst seen 2026-08-02 17:30:11
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