中国高速道路運用からの炭素排出の時空間ダイナミクスと駆動メカニズム
Spatiotemporal dynamics and driving mechanisms of carbon emissions from China’s expressway operations (原題)
Zhang P, liu z, Zhang y, zhang g
🤖 gxceed AI 要約
日本語
本研究は、2024年の中国全国高速道路網を対象に、交通量・車種・平均速度・混雑度を統合した活動ベースの排出算定フレームワークを用いて、路線別の運用時CO2排出量を月次で推計した。排出は主要幹線に集中し、東西・南北・首都放射状の高速道路で全体の87.6%を占める。月間排出量は最大で最小より2,100kt CO2以上多く、短期的な排出急増は速度低下と混雑悪化で増幅されることを示した。高解像度の年内分析が長期平均では見えない排出メカニズムを特定し、渋滞緩和と交通脱炭素戦略に示唆を与える。
English
This study estimates monthly route-level operational CO2 emissions across China's national expressway network in 2024 using an activity-based framework integrating traffic volume, vehicle type, speed, and congestion. Emissions concentrate on major trunk corridors, with east-west, north-south, and capital radial expressways accounting for 87.6% of total. Monthly variation exceeds 2,100 kt CO2, and short-term surges are amplified by reduced speeds and congestion. High-resolution intra-annual analysis reveals mechanisms obscured in long-term averages, informing congestion mitigation and transport decarbonization.
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
中国の高速道路運用排出の詳細分析は、日本の交通部門脱炭素策（次世代自動車普及、物流効率化、ETCデータ活用等）に示唆を与える。特に、月次・路線別の排出変動要因の解明は、日本の高速道路会社や物流企業が排出削減策を立案する際の参考となる。
In the global GX context
This China-focused study offers a methodological template for high-resolution operational emission accounting that is relevant to global transport decarbonization efforts, including those under TCFD/ISSB disclosure frameworks. The finding that congestion amplifies emissions even at similar traffic volumes underscores the climate benefits of congestion management, a transferable insight for highway operators worldwide.
👥 読者別の含意
🔬研究者:Provides a high-resolution activity-based method for operational transport emissions that can be adapted to other countries and scales.
🏢実務担当者:Highlights congestion mitigation as a concrete lever for reducing operational carbon footprint in highway networks.
🏛政策担当者:Demonstrates the importance of intra-annual emission dynamics for designing effective transport decarbonization policies.
📄 Abstract（原文）
<title>Abstract</title> <p>Highway transport represents a major source of carbon emissions; yet, highway operational emissions remain poorly characterized at fine temporal scales. In this study, we present a nationwide analysis of highway operational CO₂ emissions across China in 2024, focusing on monthly spatiotemporal dynamics. Using an activity-based emission accounting framework that integrates traffic volume, vehicle type, average speed, and congestion intensity, we quantify route-level emissions across China’s national highway network. we quantify route-level emissions across six functional expressway categories. Operational emissions are strongly concentrated along major trunk corridors, with east-west, north-south, and capital radial expressways together accounting for 87.6% of emissions across the six categories. Monthly emissions also show pronounced variation, with the highest-emission month exceeding the lowest by more than 2,100 kt CO₂. Notably, short-term emission surges are amplified by reduced speeds and intensified congestion, even under comparable traffic volumes. Our findings demonstrate that high-resolution intra-annual analysis can identify emission mechanisms that are obscured in long-term averages, providing timely insight for congestion mitigation and transport decarbonization strategies.</p>
🔗 Provenance — このレコードを発見したソース
- Research Square https://doi.org/10.21203/rs.3.rs-10726884/v1first seen 2026-09-02 04:32:03 · last seen 2026-09-15 04:21:24
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