System-Level CO2 Allocation under Supply Constraints in Industrial Clusters
産業クラスターにおける供給制約下でのシステムレベルCO2配分 (AI 翻訳)
R. Sawaly, A. Abushaikha, T. Al-ansari
🤖 gxceed AI 要約
日本語
カタールの産業パークを対象に、CO2回収・利用・貯留（CCUS）の経済的・技術的制約下での最適配分フレームワークを提案。多目的混合整数線形計画法を用い、CO2不足時の配分優先順位や純削減制約の影響を分析。結果は、大規模EORシンクへの優先配分や供給制約の重要性を示す。
English
This paper presents a centralized optimization framework for allocating captured CO2 in an industrial cluster, considering economic, technical, and environmental constraints. Using a multi-objective MILP model on a Qatar case study, it shows that under CO2 scarcity, large EOR sinks are prioritized, and low-purity sources are leveraged. The findings underscore the need for coordinated planning in CCUS deployment.
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
日本のコンビナート（石油化学・鉄鋼）でのCCUSハブ構想に示唆を与える。特に、CO2供給制約下での最適配分ロジックは、複数事業者が関与する国内のCCS/CCUSプロジェクトの設計に応用可能。
In the global GX context
This work provides a quantitative framework for CCUS hub planning that aligns with global efforts (e.g., ISSB, TCFD) requiring measurable emission reductions. The methodology supports decision-making for industrial clusters facing supply-side constraints, relevant for jurisdictions like the EU and US advancing CCUS infrastructure.
👥 読者別の含意
🔬研究者:The MILP framework offers a reproducible method for CCUS allocation under constraints, useful for further optimization studies.
🏢実務担当者:Industrial cluster operators can use the model to assess trade-offs and prioritize investments in CO2 capture and utilization.
🏛政策担当者:Regulators can leverage the insights to design policies that incentivize coordinated CCUS development and ensure environmental integrity.
📄 Abstract（原文）
Efficient deployment of carbon capture, utilisation, and storage (CCUS) within industrial clusters requires coordinated CO2 allocation under economic, technical, and environmental constraints, particularly when CO2 availability is limited. This paper presents a centralised optimisation framework for allocating captured CO2 from nine industrial sources to six utilisation and storage sinks within an industrial park in Qatar. A multi-objective mixed-integer linear programming (MILP) model is developed to minimise total system cost while accounting for capture, purification, transport, and utilisation processes, and enforcing an environmental feasibility constraint to ensure net CO2 reduction. The model is evaluated under four scenarios: a baseline case with sufficient CO2 to satisfy all sink demands, and three scarcity scenarios in which 15%, 25%, and 35% of total source emissions are available. Results show that under scarcity, allocations prioritise large EOR sinks supplied by high-volume, low-purity sources, while utilisation pathways are progressively reintroduced as availability increases. The findings highlight the critical influence of CO2 purity, sink requirements, and supply constraints on allocation outcomes and underscore the importance of centralised planning for robust CCUS deployment.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.69997/sct.174796first seen 2026-06-30 05:43:11
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