エネルギー配電網の気候レジリエンス：英国における証拠に基づく適応の主要要件
Climate resilience of energy distribution networks: key requirements for evidence-based adaptation in Great Britain (原題)
Colin Manning, Sean Wilkinson, Jaise Kuriakose, H. J. Fowler, Anna Whitford, Ruth Wood, Eduardo A. Martínez Ceseña, Hannah Bloomfield, James Carruthers
🤖 gxceed AI 要約
日本語
本論文は、英国の電力・ガス網運用の専門家へのインタビューと円卓会議の定性データをもとに、気候科学・産業慣行・政策知見を戦略計画へ統合する方法を検討する。天候影響の要因特定、低後悔適応策、サービス水準と許容不能リスク閾値、レジリエンス指標、影響モデルの5つの構成要素を提示する。既存の気候リスク評価は定量的気候情報が不足しており、共同開発による定量リスク評価と影響モデリングの強化が必要だと結論づける。
English
Drawing on interviews and roundtables with GB electricity and gas network experts, this paper examines how climate science, industry practice, and policy expertise can be integrated into strategic resilience planning. It presents five building blocks: identifying weather-impact drivers, low-regret adaptation options, Levels of Service and intolerable-risk thresholds, resilience metrics, and impact models combining historical data with climate projections. It concludes that co-developed quantitative risk assessment and improved impact modelling are needed for emergency planning and investment prioritisation in the net-zero 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
日本でも電力・ガス網の気候適応は喫緊の課題であり、レジリエンス投資の根拠づけやサービス水準の設定は、SSBJ開示における物理的リスク評価や適応策の説明責任に直結する。英国の産学官共創アプローチは、日本のGX推進における適応ガバナンス設計の参考になる。
In the global GX context
As TCFD/ISSB physical-risk disclosure matures, this paper addresses the gap between qualitative climate risk reporting and the quantitative, threshold-based evidence investors and regulators increasingly demand. Its five building blocks offer a transferable framework for utilities and network operators globally to justify resilience capex and align adaptation planning with net-zero electrification pathways.
👥 読者別の含意
🔬研究者:気候科学とインフラ実務を橋渡しする影響モデリングとレジリエンス指標の設計枠組みを提供する。
🏢実務担当者:配電・ガス網事業者は、サービス水準と許容不能リスク閾値の設定、適応投資の優先順位づけに本枠組みを活用できる。
🏛政策担当者:適応投資の正当化には定量リスク評価と産学官共創が不可欠であり、規制・緊急計画の枠組み設計に示唆を与える。
📄 Abstract（原文）
Maintaining and strengthening energy infrastructure resilience is critical amid climate change and the transition to net zero. Increasing frequency and intensity of extreme weather will strain already vulnerable electricity and gas infrastructure, raising the risk of outages that disrupt communities and critical services. Simultaneously, the transition to net zero requires radical transformation of electricity networks to support electrification of heating and transport, that will increase societal dependence on electricity and the potential consequences of outages. Securing political and public support for resilience investment requires clear evidence of benefits of action, and costs of inaction, co-developed by industry, academia, and policymakers. This paper draws on qualitative data produced via interviews and round-table discussions with key GB energy sector experts operating electricity and gas networks to explore how climate science, industry practice, and policy expertise can be better integrated into strategic planning. We present synthesised insights structured around five key building blocks for achieving this: (1) identify drivers of weather-related impacts; (2) identify low-regret adaptation options; (3) define Levels of Service and thresholds for intolerable risk; (4) establish resilience metrics to monitor performance; and (5) develop impact models that combine historical data with climate projections to assess future risks of failing a Level of Service and test robustness of adaptation options across various scenarios. Existing climate risk assessments lack sufficient quantitative climate information. We conclude that co-developed quantitative risk assessments and improved impact modelling are needed to support emergency planning and investment prioritisation for a secure transition to a net zero economy. We end with recommendations to strengthen evidence-based decision-making in this space.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.crm.2026.100872first seen 2026-09-11 04:59:17
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