A Blueprint for Data-Driven Climate Action: A Quantified Mitigation Pathway for Chiang Mai Using GHG Accounting and Spatial Analysis
データ駆動型気候行動のための青写真：GHG会計と空間分析を用いたチェンマイの定量化された緩和経路 (AI 翻訳)
Sate Sampattagul, Phakphum Paluang, Shabbir H. Gheewala, Ratchayuda Kongboon
🤖 gxceed AI 要約
日本語
本研究は、タイ・チェンマイ県を事例に、GHGインベントリと空間分析を統合した再現可能なサブナショナル気候行動フレームワークを開発。2019年基準の総排出量は5,387,482 tCO2e（BASIC+）で、固定エネルギー（40%）と運輸（32%）が支配的。BAUシナリオでは2030年に635万tCO2eに達する見込み。太陽光屋根の詳細分析により、適切な屋根への30%導入で年間約2070 GWhのクリーンエネルギーが生成可能であり、2030年排出量の16%を相殺できることを示した。
English
This study develops a replicable, data-driven framework for subnational climate action, demonstrated through a case study of Chiang Mai, Thailand. It integrates a comprehensive GHG inventory with spatial analysis to identify location-specific mitigation strategies. Total emissions in 2019 were 5,387,482 tCO2e (BASIC+), dominated by stationary energy (40%) and transportation (32%). A key finding is that a conservative 30% adoption of rooftop solar could generate 2070 GWh annually, offsetting 16% of projected 2030 emissions.
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
日本の自治体（都道府県・市区町村）が、SSBJや有報での気候関連開示に対応する際、本フレームワークはGHGインベントリと空間分析を組み合わせた実践的な手法を提供する。特に、再生可能エネルギー導入ポテンシャルの定量評価は、日本の地域脱炭素ロードマップ策定に直接応用可能。
In the global GX context
This paper provides a practical blueprint for subnational entities worldwide to develop evidence-based climate action plans. Its integration of GHG accounting with spatial analysis for renewable energy potential is directly relevant to global efforts under the Paris Agreement and the Race to Zero campaign, offering a replicable methodology for cities and regions.
👥 読者別の含意
🔬研究者:A replicable methodology combining GHG inventories with spatial analysis for subnational climate action planning.
🏢実務担当者:A practical framework for local governments to quantify mitigation strategies, especially rooftop solar potential, using open data.
🏛政策担当者:Evidence that subnational solar deployment can significantly offset projected emissions, supporting local climate target setting.
📄 Abstract（原文）
This study develops a replicable, data-driven framework for subnational climate action, demonstrated through a case study of Chiang Mai Province, Thailand. The framework integrates a comprehensive greenhouse gas (GHG) inventory with spatial analysis to identify and quantify location-specific mitigation strategies. Using 2019 as the base year, total emissions were 5,387,482 tCO2e (BASIC+), dominated by stationary energy (40%) and transportation (32%). Under a Business-as-Usual scenario, emissions are projected to reach 6.35 million tCO2e by 2030, highlighting an urgent need for intervention. As a key mitigation strategy, this research conducts a detailed spatial analysis of solar rooftop potential. The findings reveal a significant opportunity: a conservative 30% adoption rate on suitable rooftops could generate approximately 2070 GWh of clean energy annually, leading to an emissions reduction of over 1 million tCO2e. Crucially, this single intervention could offset 16% of the province’s projected 2030 emissions. This study presents a viable pathway for subnational entities to contribute to national climate targets, offering a practical blueprint for other cities and regions globally to develop effective, evidence-based climate action plans.
🔗 Provenance — このレコードを発見したソース
- openaire https://doi.org/10.3390/urbansci9120494first seen 2026-05-05 19:07:56
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