| Project/Area Number |
18K11745
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 64050:Sound material-cycle social systems-related
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| Research Institution | National Agriculture and Food Research Organization |
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Principal Investigator |
Hayashi Kiyotada 国立研究開発法人農業・食品産業技術総合研究機構, 農業環境研究部門, 主席研究員 (40355475)
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| Project Period (FY) |
2018-04-01 – 2023-03-31
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| Project Status |
Completed (Fiscal Year 2022)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2020: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2019: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2018: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | ライフサイクルアセスメント（LCA） / シナリオ不確実性 / プロスペクティブLCA / 意思決定 / 持続可能な調達 / 土地利用変化 / 原料調達 |
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| Outline of Final Research Achievements |
Specifying uncertainties due to data availability is essential to achieve sustainable procurement through applying life cycle assessment (LCA). Therefore, the concept of epistemic uncertainty, which can be refined through knowledge acquisition, was employed, and scenario uncertainty was formulated. Firstly, a new method was developed to incorporate the decision-maker’s knowledge, which departs from the conventional method based on data quality formulation. Subsequently, life cycle GHG emissions from land use change were calculated considering the state of knowledge, and the probability distribution was also derived using the knowledge information. Additionally, a framework was developed to establish a connection between the perspective of the food value chain and the transition to sustainable agricultural systems.
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| Academic Significance and Societal Importance of the Research Achievements |
ライフサイクルアセスメント（LCA）が様々な場面で利用されるようになったが、計算結果の信頼性については多くの課題が残されている。本研究では、不確実性を解析する視点からその課題にアプローチし、データの質ではなく、想定されているシナリオに起因する不確実性（エピステミック不確実性）を導出する方法を提案した。これにより、LCAを政策等で活用する場面において、様々なシナリオと不確実性分析を直接関連付けることが可能となり、農業技術改善の程度や環境ラベルの効果等をより現実的な視点から検討できるようになる。
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