Spatiotemporal analysis of major CO
主要CO2排出の時空間分析 (AI 翻訳)
Ryuta Tsurumi, Takahiro Yoshida
🤖 gxceed AI 要約
日本語
この研究は、日本における2021-2022年度の温室効果ガス報告制度の公開データを用い、建築部門のCO2排出の時空間分析を行った。延床面積データと統合することでエネルギー消費原単位を評価し、地域エネルギー管理システムの効果的な導入地点を特定した。都市における気候変動対策の策定に貢献する。
English
This study conducts spatiotemporal analysis of CO2 emissions in Japan's building sector using publicly available data from the mandatory GHG reporting system (FY2021-2022). By integrating floor area data, it evaluates energy use intensity and identifies locations where district heating/cooling and community energy management are most effective. The findings support formulation of effective urban climate mitigation measures.
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
日本独自の温室効果ガス算定・報告制度の公開データを活用した実証研究であり、SSBJや有報におけるScope 1・2排出量の開示品質向上に示唆を与える。特に、事業所単位のデータが2021年度から公開されたことで、都市レベルでの排出実態把握が可能となった点が重要。日本の建築部門のエネルギー効率改善政策に直接貢献する。
In the global GX context
This empirical study leverages the Japanese mandatory GHG reporting system (one of the world's earliest) to analyze building emissions at a spatiotemporal granularity. It demonstrates how public disclosure data can be combined with external databases to derive energy intensity metrics, offering a methodology applicable to other countries implementing similar reporting systems (e.g., under ISSB or CSRD). The findings are relevant for urban climate policy and energy management.
👥 読者別の含意
🔬研究者:Provides a methodology for integrating public GHG reporting data with building floor area databases to analyze energy intensity at urban scale.
🏢実務担当者:Useful for corporate sustainability teams to understand how public reporting data can be leveraged for benchmarking and energy efficiency planning.
🏛政策担当者:Highlights the value of making location-specific emissions data publicly available, supporting data-driven climate policy at city level.
📄 Abstract（原文）
Understanding greenhouse gas emissions from the building sector is crucial for climate change countermeasures. In Japan, a law was enacted in 2006 requiring corporations that emit greenhouse gases above a certain level to report to the national government. Furthermore, under this law, information on business locations (geographical bases) has been publicly available since fiscal year 2021, making it possible to grasp the actual spatiotemporal greenhouse gas emissions of cities based on real data, which was previously difficult to obtain from publicly available information. The purpose of this study is to conduct a spatiotemporal analysis of emission locations and emissions, focusing specifically on the building sector, using publicly available information for fiscal years 2021-2022 under Japanese Mandatory GHG Accounting and Reporting System, a Japanese law, to clarify the actual emissions of Japan's building sector. Furthermore, in the building sector, total floor area is an important variable for evaluating energy consumption efficiency. However, building total floor area is generally not available from publicly available information. Therefore, in this study, a separately obtained database of building floor area (building name and latitude/longitude) was integrated with publicly available information from the reporting system by geocoding building names and latitude/longitude information, enabling a spatiotemporal analysis of energy use intensity. The results of the spatiotemporal analysis make it possible to understand area-wide energy use (e.g., district heating and cooling) and locations where the community energy management system is most effective. These results are expected to enable the formulation of effective climate change mitigation measures in cities.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1051/e3sconf/202671610013/pdffirst seen 2026-07-04 04:42:44
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。