Achieving residential energy targets in the EU: A multi country comparison of regulatory and economic instruments (code and data)
EUにおける住宅用エネルギー目標の達成：規制・経済的手段の多国間比較（コードとデータ） (AI 翻訳)
Özer, Ece, Conselvan, Francesca, Harringer, Daniel, Müller, Andreas, Kranzl, Lukas
🤖 gxceed AI 要約
日本語
本リソースは、EU加盟7か国における住宅用エネルギー目標達成のための規制・経済的手段を比較した研究のコードとデータを公開する。Invert/Opt建物ストックモデルを用い、4つの政策シナリオ下での最終・一次エネルギー需要、面積加重一次エネルギー消費量等を提供する。分析は暖房主体の国々を対象とし、MEPSや一次エネルギー係数の影響を評価している。
English
This release provides the code and data for a study comparing regulatory and economic instruments to achieve residential energy targets in seven EU member states. Using the Invert/Opt building stock model, it outputs final and primary energy demand, area-specific primary energy demand, and gross floor area under four policy scenarios, with emphasis on heating-dominated countries and the impact of MEPS and primary energy factors.
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
本データセットはEUの住宅エネルギー政策を多国間で比較しており、日本の省エネ基準やZEH（ネット・ゼロ・エネルギー・ハウス）政策の効果検証に示唆を与え得る。特に、規制と経済的措置の組み合わせ効果を定量的に分析する手法は、日本の住宅分野のGX戦略立案に参考となる。
In the global GX context
This multi-country comparison of policy instruments for residential energy efficiency provides valuable empirical evidence for the global discourse on building decarbonization. The open data and scenario analysis (including MEPS and primary energy factor sensitivity) offer a replicable framework that can inform policy design beyond the EU, particularly for regions considering similar regulatory and economic instruments.
👥 読者別の含意
🔬研究者:Energy system modelers and policy analysts can use the open data and scripts to reproduce the analysis or extend it to other countries, exploring the interplay of regulatory and economic instruments.
🏛政策担当者:Policymakers in the EU and elsewhere can gain insights into the effectiveness of different policy combinations (e.g., MEPS, subsidies) for achieving residential energy targets, supported by a transparent modeling framework.
📄 Abstract（原文）
First public release of the code and data for: Achieving residential energy targets in the EU: A multi country comparison of regulatory and economic instruments. Ece Özer, Francesca Conselvan, Daniel Harringer, Andreas Müller, Lukas Kranzl. Energy Policy (under review), 2026. Contents data/ — Invert/Opt building stock model outputs (final and primary energy demand, area-specific PED, gross floor area) for four policy scenarios under constant and decreasing PEF assumptions, plus model inputs (primary energy factors, MEPS threshold distributions, worst-performing-buildings data) for seven heating dominated EU Member States. scripts/ — Python scripts reproducing the paper's figures (FED carrier mix, sPED reduction trajectories, four-driver decomposition, target-achievement heatmaps, 2020 baseline). figures/ — the figures as used in the paper. Code is released under MIT; data under CC BY 4.0. Produced within the EPBD.wise project (EU Grant Agreement No. 101120194).
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/20493676first seen 2026-06-02 04:11:51 · last seen 2026-06-08 04:13:29
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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。