gxceed
← 論文一覧に戻る

Transport‐related carbon dioxide emissions: Energy pathways, decarbonization strategies, and public health implications

交通関連二酸化炭素排出:エネルギーパスウェイ、脱炭素戦略、および公衆衛生への影響 (AI 翻訳)

Suresh Vellaiyan, Shanmugavel Kuppusamy, Yuvarajan Devarajan, S. V. Niveditha, Pradeep Kumar Jangid, Sujai Selvarajan, Satish Choudhury, Vishal Kumar Sandhwar

Environmental Progress & Sustainable Energy📚 査読済 / ジャーナル2026-06-16#エネルギー転換対象セクター: transport
DOI: 10.1002/ep.70546
原典: https://doi.org/10.1002/ep.70546
📄 PDF

🤖 gxceed AI 要約

日本語

本総説は、交通部門のCO2排出と公衆衛生への影響を統合的に評価するフレームワークを提案する。実験室認証サイクルと実走行条件の乖離が実際の排出量を過小評価する問題に着目し、電化、水素、効率化、アクティブ交通、コンパクト都市計画などの脱炭素戦略を検討。気候変動による熱ストレス、アレルゲン増加、媒介感染症拡大の健康経路も論じる。

English

This review presents an integrated framework linking transport CO2 emissions, real-world driving variability, atmospheric processes, and public health outcomes. It highlights discrepancies between laboratory certification cycles and on-road emissions, and evaluates decarbonization strategies including electrification, hydrogen systems, efficiency optimization, active transport, and compact urban planning. Three climate-mediated health pathways (thermal stress, aeroallergen enhancement, vector-borne disease) are discussed.

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

日本では運輸部門のCO2排出削減が急務であり、本稿の統合フレームワークはSSBJ対応や都市計画に示唆を与える。ただしインド発のレビューであり、日本の政策・インフラとの直接的な連携は限定的。

In the global GX context

While this review provides a comprehensive multi-scale perspective on transport decarbonization and public health, it is a general synthesis without novel empirical data. For global readers, it serves as a broad reference but offers limited new insight beyond existing literature.

👥 読者別の含意

🔬研究者:This review offers a structured synthesis linking transport emissions, climate processes, and health outcomes, useful for researchers seeking an integrated perspective.

🏛政策担当者:Policymakers can use the review's framework to connect transport decarbonization strategies with health co-benefits, though specific policy recommendations are not provided.

📄 Abstract(原文)

Abstract The transport sector contributes nearly 23% of global energy‐related carbon dioxide (CO 2 ) emissions and remains a major source of urban atmospheric burden. Although CO 2 is non‐toxic at ambient concentrations, it plays a critical role in climate forcing and indirectly alters air quality and human exposure patterns. This review presents an integrated framework linking transport‐related CO 2 emissions, real‐world driving variability, atmospheric processes, and public health outcomes. The review was developed through a structured narrative synthesis of literature from transportation engineering, climate science, and environmental health domains. A multi‐scale perspective is adopted to connect vehicle‐level emission metrics with urban microclimate dynamics and broader climate responses. Particular emphasis is placed on the discrepancy between laboratory certification cycles and real‐world driving conditions, which often leads to underestimation of on‐road CO 2 emissions and associated environmental impacts. The review further examines the influence of CO 2 ‐driven climate change on atmospheric conditions, including urban heat island intensification, boundary layer dynamics, and secondary pollutant formation. Three major climate‐mediated health pathways are discussed: thermal stress, aeroallergen enhancement, and vector‐borne disease expansion. Transport decarbonization strategies, including electrification, hydrogen‐based systems, efficiency optimization, active transport, and compact urban planning, are evaluated for their environmental and public health implications. Overall, the review highlights the need for integrated modeling frameworks that combine emission inventories, atmospheric processes, and exposure metrics to support sustainable transport systems and informed environmental decision‐making.

🔗 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。