低炭素港湾都市のためのデジタルツイン活用型エネルギー管理：ジェノバ、リヴォルノ、ナポリの比較都市インテリジェンス枠組み
Digital-Twin-Enabled Energy Management for Low-Carbon Port Cities: A Comparative Urban-Intelligence Framework for Genoa, Livorno and Naples (原題)
Irina Di Ruocco
🤖 gxceed AI 要約
日本語
イタリアの3港湾都市（ジェノバ、リヴォルノ、ナポリ）を対象に、デジタルツインを活用した港湾エネルギー管理の枠組みを構築・比較した研究。港湾排出の大部分は海上活動が占め（80〜97%）、陸上電力の炭素削減効果は都市間で大きく異なる（0.330〜0.783 tCO2eq/MWh）。計画介入による削減率は約9〜14%だが、実施制約により効果が半減しうることを感度分析で示す。ロッテルダム等との国際比較から、統合型プラットフォームへの移行を提言する。
English
This study develops a Digital-Twin-enabled energy-management framework and applies it to three Italian port cities: Genoa, Livorno and Naples. Maritime activities dominate port emissions (80-97%), while shore-side electricity yields widely differing carbon-abatement intensity (0.330-0.783 tCO2eq/MWh). Planned interventions imply 9-14% emission reductions, but implementation constraints can halve the effect. Benchmarking against Rotterdam, Antwerp-Bruges and others, the paper proposes a transferable integrated port-energy-management architecture.
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（横浜・神戸・名古屋等）でもカーボンニュートラルポート形成が政策課題となっており、陸上電力や水素導入の効果測定・データ連携の枠組みとして参考になる。港湾単位の排出インベントリと削減効果の可視化は、自治体・港湾管理者のGX計画立案に示唆を与える。
In the global GX context
Ports are a growing frontier for global decarbonisation and disclosure, with shore power and electrification increasingly tied to CSRD/ISSB reporting and green-port finance. The paper's emphasis on verifiable environmental outcomes and integrated data platforms speaks to the shift from isolated smart assets to auditable decarbonisation infrastructure.
👥 読者別の含意
🔬研究者:港湾都市のエネルギー・排出データ統合とデジタルツイン評価の比較枠組みを学べる。
🏢実務担当者:港湾・物流拠点の脱炭素投資判断や陸上電力導入効果の試算に活用できる。
🏛政策担当者:港湾カーボンニュートラル政策の実施制約と削減効果の現実的評価に示唆。
📄 Abstract（原文）
Ports are increasingly becoming urban cyber-physical systems in which maritime operations, terminal activities, buildings, electricity networks, renewable generation and environmental pressures interact. Energy Management Systems (EMS) can coordinate energy production and consumption, while Digital Twins (DTs) can connect real-time data, simulation and decision support. Yet port digitalisation and port decarbonisation are still frequently treated as separate domains. This paper develops a Digital-Twin-enabled energy-management framework for urban ports and applies it to three Italian port-city systems: Genoa, Livorno and Naples. The study combines official energy-environmental plans, port emission inventories, operational information and infrastructure data to examine three dimensions of urban intelligence: data integration, energy-system coordination and implementation capacity. The comparison reveals a strong dominance of maritime activities in port-related emissions, accounting for approximately 80.1% in the Western Ligurian Port System, 87.85% in Livorno and 97.0% in Naples. Shore-side electricity nevertheless produces markedly different estimated environmental returns: carbon-abatement intensity ranges from 0.330 tCO2eq/MWh in Naples to 0.400 tCO2eq/MWh in Genoa Pra’ and 0.783 tCO2eq/MWh in Livorno. Planned intervention portfolios correspond to estimated emission reductions of approximately 9.0%, 14.3% and 10.2%, respectively. A sensitivity test for the Central Tyrrhenian case shows that implementation constraints can reduce the estimated portfolio effect from approximately 10.2% to 5.3%. Comparison with Rotterdam, Antwerp-Bruges, Valencia, Hamburg and Sines shows that international practice is moving from isolated smart assets toward integrated platforms linking sensing, simulation, energy optimisation and operational decisions. The paper therefore proposes a transferable architecture for Digital-Twin-enabled Port Energy Management and argues that urban intelligence emerges not from technology deployment alone, but from the capacity to connect information, prediction, physical intervention and verifiable environmental outcomes.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.59543/yrfek347first seen 2026-11-12 04:57:22 · last seen 2026-11-13 05:09:39
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