← 論文一覧に戻る

交通エネルギー転換のための建築環境変革

Built environment transformation for the transport energy transition (原題)

Chris ten Dam, Sustainable Energy Supply Systems, Gert Jan Kramer, Dick Ettema, Vinzenz Koning, Francisco Bahamonde Birke

Utrecht University Repository (Utrecht University)ジャーナル2026-09-15#エネルギー転換Origin: EU対象セクター: real_estate
原典: https://dspace.library.uu.nl/handle/1874/487250

🤖 gxceed AI 要約

日本語

本論文は、離散選択モデルを用いて建築環境が旅客交通のエネルギー関連行動に与える影響を分析し、都市密度と都心への距離が最も重要であることを示した。都市計画によりオランダの交通CO2を2050年までに約10%削減可能と推計。所得・学歴など社会人口統計学的要因の影響が技術的対策より大きいことを強調し、都市型社会住宅の整備がエネルギー貧困と転換への支持維持に寄与すると論じる。

English

Using discrete choice modeling, this thesis analyzes how built environment design shapes energy-relevant travel behavior, finding urban density and distance to city centers most influential. Ambitious urban planning could cut Dutch transport CO2 by ~10% by 2050. Sociodemographic factors outweigh technological effects, and urban social housing may reduce energy poverty and sustain support for the transition.

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

日本でもコンパクトシティ政策や立地適正化計画が進むが、交通由来CO2削減効果を定量的に示した点は、自治体のGX計画や都市計画と脱炭素の統合に示唆を与える。EV充電インフラ投資の必要性も示す。

In the global GX context

Adds empirical evidence on how urban form drives transport energy use, relevant to global decarbonization pathways and just transition debates. Highlights that technology alone (EVs) is insufficient without addressing sociodemographic disparities and urban planning.

👥 読者別の含意

🔬研究者:建築環境と交通エネルギーの関係を離散選択モデルで統合的に分析した手法と知見が参考になる。

🏢実務担当者:都市計画・不動産開発において、密度と自己完結性の高い街区設計が長期的な交通エネルギー削減に寄与することを示す。

🏛政策担当者:コンパクトシティ政策とEV充電インフラ投資のバランス、および都市型社会住宅によるエネルギー貧困対策の重要性を示唆。

📄 Abstract(原文)

This thesis aimed to answer the following central research question: what type of built environment design can best support the energy transition in the passenger transport sector? It employed discrete choice modeling frameworks to jointly analyze the influence of built environment variables on various energy-relevant travel choices, thus illuminating new energy transition pathways. In doing so, it explicitly bridged the divides between the energy science, transport modeling, and energy poverty disciplines. The results showed that the density in the walking range of residents had most effect on energy-relevant travel behavior. Distances to city centers mattered too. The residential location relative to train stations and supermarkets was of little importance. This indicates that travel energy consumption depends on the urbanity of the environment as a whole rather than on the distance to any single destination. The most important mechanism was the reduction in travel distances in urban environments. Policy should thus focus on creating neighborhoods that are not just dense, but also self-sufficient. The increased use of public and active modes by urban residents was relevant as well. Yet, the car remained the dominant mode in inner city areas, indicating that investments in BEV charging infrastructure are still required. Residents of non-green urban areas with limited parking space also owned lighter cars, which use less energy. However, the effect was limited. The indirect impact of the built environment on energy-relevant travel behavior through the intermediary variable of car ownership was likewise surprisingly limited. The above built-environment effects were considerably smaller than the differences between sociodemographic groups: households with high incomes, full-time jobs, and university degrees consistently used far more energy than their less advantaged peers. They owned new and electric cars, but also traveled much larger distances, made less use of public and active modes, and owned heavier cars. This shows the importance of looking beyond technology in the energy transition. Sociodemographic differences likewise dominated patterns of transport and domestic energy poverty. Analysis of spatial patterns showed that similar types of households did face higher domestic and transport energy costs in rural areas. Correcting for lower rural housing prices and urban-rural differences in income did not change this pattern: inhabitants of remote rural areas still spent the highest fraction of their available (housing-costs-corrected) budget on energy. Urban planning and housing policy aimed at providing (city) social housing apartments may therefore help reduce the vulnerability of low-income households to energy price shocks. The climate relevance of the above-described results was assessed through further calculations. These showed that ambitious urban planning can reduce transport energy consumption by approximately 0.5%/year. This means that The Netherlands’ total travel CO2 emissions can be reduced by 10% before 2050 (order-of-magnitude). Furthermore, reducing transport and domestic energy poverty by building sufficient urban social housing may help preserve societal and political support for the energy transition. Finally, urban planning can directly address a major rebound effect, as the rising car energy efficiency through technological climate change mitigation efforts can reduce driving costs and thus contribute to urban sprawl.

🔗 Provenance — このレコードを発見したソース

🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録(無料・3キーワードまで)。

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。