インドネシアにおける低炭素かつ労働配慮型農業移行の優先順位
Low-Carbon and Labour-Sensitive Agricultural Transition Priorities in Indonesia (原題)
Putri Meliza Sari, Mega Amelia Putri, Pangeran Aristofanes Musthafa, Rowiyah Asengbaramae
🤖 gxceed AI 要約
日本語
インドネシアの農業部門の低炭素移行を支援するため、環境評価と会計を統合した枠組みを提案。EXIOBASEのMRIOデータを用い、16の農業・畜産・水産部門を5層で分析し、野菜・果物・油糧種子・水産・稲作を優先部門と特定。サプライチェーン排出が直接排出の約2.2倍であることを示し、労働と排出の両立を重視した政策分類を提供。
English
This study proposes an integrated environmental assessment and accounting framework to support low-carbon, labour-sensitive agricultural transition in Indonesia. Using EXIOBASE MRIO data, it evaluates 16 agricultural sectors across five analytical layers, identifying vegetables, oil seeds, fisheries, and paddy rice as core priorities. Supply-chain emissions are 2.195 times direct emissions, highlighting upstream pressures. The framework offers a policy-oriented typology balancing emissions, labour, and robustness.
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
日本では農業分野のGXは食料安全保障と絡めて注目されつつあり、本枠組みの労働配慮型の評価手法は、日本の農業政策や地域振興における脱炭素と雇用の両立を考える際に参考になる。また、サプライチェーン排出の考慮は、日本の食品産業のScope 3対応にも示唆を与える。
In the global GX context
Globally, this paper contributes to the growing literature on just transition and agricultural decarbonization. Its integrated framework combining environmental accounting, labour sensitivity, and robustness testing offers a replicable methodology for other developing economies. The finding on supply-chain multipliers reinforces the importance of Scope 3 thinking in agricultural policy.
👥 読者別の含意
🔬研究者:Provides a novel integrated framework for agricultural transition prioritization that combines environmental accounting with labour and robustness considerations.
🏢実務担当者:Offers a screening tool for agri-food companies to identify priority sectors for decarbonization while considering supply-chain and labour impacts.
🏛政策担当者:Demonstrates a method for designing socially inclusive low-carbon agricultural policies, relevant for national and regional planning.
📄 Abstract（原文）
This study develops an integrated environmental assessment and accounting framework to support policy decisions on a low-carbon and labour-sensitive agricultural transition in Indonesia. Rather than treating decarbonisation as an emissions-only ranking exercise, the framework combines sustainability appraisal, sectoral environmental accounting, and robustness diagnostics. Using the 2022 industry-by-industry multiregional input–output (MRIO) table from EXIOBASE 3.10.1, the study evaluates sixteen Indonesian primary agricultural, livestock, fisheries, and aquaculture sectors through five analytical layers: sector validation and caution flags; direct Socio-Environmental Structure-Scale-Risk (SE-SSR) indicators; environmentally extended multiregional input–output (EE-MRIO) footprint simulation; probabilistic and deterministic robustness tests; and rule-based transition classification. The results identify cultivation of vegetables, fruit, and nuts; cultivation of oil seeds; fishing and aquaculture; and cultivation of paddy rice as core robust priorities, although they represent different transition pathways. Poultry farming emerges as a footprint-mediated employment opportunity rather than a core robust priority, while caution-flagged sectors require additional validation before policy use. The mean supply-chain footprint for the selected greenhouse gases, expressed in carbon dioxide equivalent (CO2e), is 2.195 times the corresponding direct greenhouse-gas (GHG) emissions, demonstrating that upstream supply-chain pressures materially affect sector priorities. The findings show that transition priorities cannot be defined by emissions performance alone, but require joint assessment of labour relevance, supply-chain effects, robustness, and data quality. The framework provides a policy-oriented typology for transition screening and socially inclusive agricultural management.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1142/s1464333226500109first seen 2026-09-02 04:50:56
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