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What Is the Best Use of Biomass? A Harmonized <scp>LCA</scp> ‐ <scp>TEA</scp> Framework Quantifying Economic and Environmental Metrics for Bioenergy Pathways

バイオマスの最適利用とは？経済・環境指標を定量化する調和化LCA-TEAフレームワーク (AI 翻訳)

Saurajyoti Kar, Troy R. Hawkins, Doris Oke, Udayan Singh, Ling Tao, Arpit Bhatt

GCB Bioenergy📚 査読済 / ジャーナル2026-04-08#CCUSOrigin: US
DOI: 10.1111/gcbb.70115
原典: https://doi.org/10.1111/gcbb.70115

🤖 gxceed AI 要約

日本語

本研究は、バイオマスエネルギー経路のGHG削減ポテンシャル、最低販売価格、限界削減費用を評価する調和化LCA-TEAフレームワークを開発。19経路（液体燃料、バイオ電力、水素）をCCS有無で分析し、CCS導入で複数経路がネット・ネガティブに。バイオ電力+CCSが最も低い限界削減費用（$32-68/tCO2e）を示す一方、液体燃料・水素は航空・重工業などの削減困難セクターに重要。低炭素電力系統の影響も評価。

English

This study develops a harmonized LCA-TEA framework to evaluate GHG reduction potential, minimum fuel selling price, and marginal abatement cost (MAC) for 19 bioenergy pathways (liquid biofuels, bioelectricity, hydrogen) with and without CCS. Results show CCS enables net-negative carbon intensities for several pathways, with bioelectricity+CCS achieving the lowest MAC ($32-68/tCO2e). Liquid biofuels and hydrogen remain critical for hard-to-abate sectors. The framework is open-source and considers low-carbon grid scenarios.

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

日本ではバイオマス発電のFIT/FIP制度や、カーボンニュートラル燃料（e-fuel、SAF）の導入が進む中、本フレームワークは経路間の比較評価に有用。特にCCS付きバイオマス発電の限界削減費用は、日本のカーボンプライシング議論に示唆を与える。ただし米国データがベースのため、日本のバイオマス供給・コスト構造に合わせた調整が必要。

In the global GX context

This framework provides a rigorous, open-source tool for comparing bioenergy pathways on both cost and carbon metrics, directly relevant to global CCS deployment debates and hard-to-abate sector strategies. The MAC estimates ($32-600/tCO2e) offer benchmarks for carbon pricing and subsidy design. The analysis of low-carbon grid interactions is timely as grids decarbonize worldwide.

👥 読者別の含意

🔬研究者:Provides a harmonized LCA-TEA methodology and benchmark data for 19 bioenergy pathways, useful for further optimization and policy modeling.

🏢実務担当者:Offers cost and carbon intensity data to inform investment decisions in bioenergy projects, especially with CCS integration.

🏛政策担当者:Highlights cost-effective abatement options (bioelectricity+CCS) and the role of biomass in hard-to-abate sectors, informing carbon pricing and renewable energy policy.

📄 Abstract（原文）

ABSTRACT Bioresource utilization is expected to play a pivotal role in complementing existing energy pathways and enhancing energy resilience. This study develops a harmonized life cycle assessment (LCA) and techno‐economic analysis (TEA) framework to evaluate the greenhouse gas (GHG) reduction potential, minimum fuel selling price (MFSP), and marginal abatement cost (MAC) of bioenergy pathways. We analyze 19 pathways, including liquid biofuels (via catalytic fast pyrolysis, Fischer–Tropsch synthesis, and gasification), bioelectricity, and biomass‐to‐hydrogen, with and without carbon capture and storage (CCS). The GHG impacts are assessed using the GREET 2022 model, while U.S. Billion‐Ton 2016 biomass availability projections are used to estimate scale‐up potential. Additionally, we evaluate the influence of a low‐carbon electricity grid on pathway performance. Our results show that CCS implementation reduces carbon intensities (CI) to net‐negative values for several pathways, with MAC ranging from $32 to $600 per metric ton (MT) CO2e avoided. Bioelectricity pathways with CCS achieve the lowest MAC ($32–$68/tCO2e), while liquid biofuels and hydrogen pathways remain critical for hard‐to‐abate sectors like aviation and heavy industry. Pathways with net‐positive electricity demand benefit from a low‐carbon grid, whereas those co‐producing electricity experience increased MAC under lower electricity grid CI scenarios. This open‐source framework provides a robust tool for harmonized evaluation of bioenergy pathways, enabling policymakers and stakeholders to identify cost‐effective strategies for biomass utilization and carbon abatement at scale. The findings underscore the importance of CCS, co‐product credits, and feedstock availability in optimizing bioenergy deployment for a low‐carbon economy.

🔗 Provenance — このレコードを発見したソース

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。