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ノルトライン＝ヴェストファーレン州のマルチモーダルCO2輸送ネットワーク最適化 — 結果データセット

Multimodal CO₂ Transport Network Optimization for North Rhine-Westphalia — Results Dataset (原題)

Lütz, Luna, Neuwirth, Marius, Fleiter, Tobias

Zenodoデータセット2026-08-26#CCUSOrigin: EU経営インパクト: コスト削減対象セクター: cross_sector
DOI: 10.5281/zenodo.22114700
原典: https://zenodo.org/records/22114700

🤖 gxceed AI 要約

日本語

本データセットは、ノルトライン＝ヴェストファーレン州の産業クラスターにおけるCO2輸送ネットワーク最適化の結果を提供する。パイプライン、鉄道、トラック、内陸はしけ、海上タンカーを組み合わせ、地質貯留までの最小コスト経路を混合整数線形最適化で導出。11シナリオ（産業範囲、パイプライン新設/既存、貯留場所）のネットワーク形状、コスト、モーダルシフトをGeoJSONとExcelで収録。

English

This dataset provides the optimization results for a multimodal CO2 transport network in North Rhine-Westphalia, determining least-cost routes to geological storage via pipeline, rail, truck, barge, and tanker. It covers 11 scenarios with network geometry, costs, and modal splits, supporting CCUS infrastructure planning.

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

日本ではCCS事業法や長期脱炭素電源オークションなどCCUS整備が進むが、国内貯留容量の制約から輸送ネットワーク設計が重要。本データセットの方法論は、日本の産業クラスター（瀬戸内、京浜など）でのCO2輸送インフラ計画に応用可能で、政策立案や事業者間連携に示唆を与える。

In the global GX context

Globally, CCUS infrastructure is critical for hard-to-abate sectors, and this dataset offers a replicable optimization framework for multimodal CO2 transport. It provides empirical evidence on cost-effective network design, relevant for regions developing CCS clusters and for aligning with EU and global climate targets.

👥 読者別の含意

🔬研究者:Provides a detailed dataset and methodology for optimizing multimodal CO2 transport networks, useful for validating models and exploring scenario impacts.

🏢実務担当者:Offers insights into cost-effective CO2 transport infrastructure planning, aiding decisions on pipeline vs. alternative modes for industrial clusters.

🏛政策担当者:Highlights the importance of coordinated CO2 transport infrastructure and provides data to inform regional CCS cluster development policies.

📄 Abstract（原文）

This dataset holds the optimization results behind the article "Multimodal CO2 Transport Network Optimization: A Case Study for North Rhine-Westphalia". A multimodal mixed-integer linear optimization determines how the captured CO2 of the North Rhine-Westphalia industrial cluster reaches geological storage at least cost, choosing between pipeline, rail, truck, inland barge and seagoing tanker. For every scenario the dataset gives the resulting network geometry, showing which emitter is served by which mode along which route to which storage site and at what cost, together with the emitter and storage input data and the values plotted in the main-text figures. Contents geojson/  — optimized network geometry, one folder per scenario and one file per layer: 89 files, 11 scenarios, 11 layer types (sources, terminals, onshore pipeline, rail, truck and inland-barge connections, offshore pipelines and their segments, offshore tankers, storage nodes, activated pipeline segments). EPSG:4326. Each file carries authorship, licence, DOI, scenario and layer metadata in its header. input_data/  — emitter inventories ( sites_S1 ,  sites_S2 ,  sites_EA ) and offshore storage nodes, with coordinates, captured quantities, modal access, capacities, injection rates and storage tariffs. supplementary_data.xlsx  — run index of all reported runs with their settings, captured volume, transport cost, onshore pipeline length and modal split, plus the plotted values of the cost-composition and modal-split figures. README.txt  — scenario naming, attribute definitions, units, conventions.  LICENSE.txt  — licence terms and citation. Scenarios. S1 covers the hard-to-abate industries (cement, lime, waste incineration), about 14.9 Mt CO2 per year; S2 adds steel and chemicals, about 39.4 Mt per year; EA covers the announced pre-FID early-adopter projects, about 5.1 Mt per year. "endo" uses greenfield pipelines only, "plus" adds the announced exogenous corridors, "pure" allows offshore storage only, "both" offshore and onshore.  Conventions. Flows in tonnes per year, lengths in kilometres, costs annualized in EUR  with a 5 % discount rate. Transport cost excludes storage and injection, and activated exogenous corridor segments are priced at full cost. All GeoJSON attributes are optimization outputs, not model inputs. Attribution. Rail and inland-waterway route geometry follows the OpenStreetMap network: this dataset contains information from OpenStreetMap, made available under the Open Database License (ODbL) v1.0; map data © OpenStreetMap contributors, https://www.openstreetmap.org/copyright . The emitter inventory builds on the E-PRTR / EEA Industrial Emissions Portal (2024), European Environment Agency. Map lines delineate study areas and do not necessarily depict accepted national boundaries. Citation. Lütz, L., Neuwirth, M., Fleiter, T. (2026). Multimodal CO2 Transport Network Optimization for North Rhine-Westphalia — Results Dataset. Zenodo. https://doi.org/10.5281/zenodo.22114700 — please cite the accompanying article as well.

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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。