Driving Factors and Decoupling Effects of Sea Port Carbon Emission with the “Dual Carbon” Goals: A Case Study of Shanghai Port
「ダブルカーボン」目標における港湾炭素排出の駆動要因と脱却効果：上海港を事例に (AI 翻訳)
Lili Qu, Yan Li, Shuangjie Yu
🤖 gxceed AI 要約
日本語
本研究は、世界最大のコンテナ港である上海港を対象に、2008～2023年の炭素排出量を定量化し、LMDI分解法とTapio脱却モデルを用いて主要な排出要因と脱却効果を分析した。結果、後背地の経済成長が排出増加の最大要因である一方、エネルギー強度と港湾吞吐強度の改善が排出抑制に寄与した。
English
This study quantifies carbon emissions at Shanghai Port (2008–2023) and analyzes key drivers using LMDI decomposition and Tapio decoupling models. Results show that hinterland economic growth is the dominant positive driver, while improvements in energy intensity and port throughput intensity significantly curb emissions. The paper offers insights for port decarbonization strategies.
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
日本の港湾事業者にとって、上海港の実証分析は、炭素排出の駆動要因を理解し、SSBJ対応やグリーンボート戦略の参考となる。特に、エネルギー効率向上と吞吐効率改善が排出削減に有効であることを示唆。
In the global GX context
This study contributes to the limited research on port carbon emissions, offering a robust methodology (LMDI + Tapio) applicable to global ports. For international readers, it highlights the decoupling of emissions from economic growth in a major port, relevant to ISSB and TCFD disclosure for transport infrastructure.
👥 読者別の含意
🔬研究者:Offers a comprehensive decomposition framework for port carbon emissions, combining LMDI and Tapio models for a major Chinese case.
🏢実務担当者:Provides actionable insights on key levers (energy intensity, throughput intensity) for port operators to reduce carbon footprint.
🏛政策担当者:Demonstrates that economic growth and emission reduction can be decoupled, supporting dual carbon policy targets for port clusters.
📄 Abstract（原文）
Sea ports play a crucial role in global trade and transportation, but their high energy consumption and associated carbon emissions challenge sustainable development. While carbon emissions have been widely studied in many sectors, research on port carbon emissions remains limited. The analysis covers 2008–2023, treats Shanghai Municipality as the principal economic hinterland of Shanghai Port, and draws primarily on SIPG’s annual and sustainability reports. This study quantifies carbon emissions at ports and analyzes their key drivers. Using the Logarithmic Mean Divisia Index (LMDI) method, a decomposition framework is developed to identify and assess the main factors contributing to port-related carbon emissions. By integrating the LMDI method with the Tapio decoupling model, the study further examines the decoupling process between carbon emissions and hinterland economic growth, as well as the mechanisms driving changes in decoupling. Shanghai Port, the world’s largest container port, is selected as a case study. The results show that: (1) hinterland economic development was the dominant positive driver (+90.69), whereas port throughput intensity exerted the strongest inhibitory effect (−63.24), followed by energy intensity (−47.42); (2) energy intensity and port throughput intensity promoted carbon reduction and decoupling, while hinterland economic growth constrained further decoupling, and energy structure optimization retained substantial mitigation potential.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/en19143373first seen 2026-07-19 05:07:45
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