GIS-Based Assessment of Selected Agricultural Residues and Bioenergy Potential: A Spatial Approach Towards Sustainability
GISに基づく選択的農業残渣とバイオエネルギー潜在力の評価：持続可能性への空間的アプローチ (AI 翻訳)
Annarita Paiano, Marko Drizaku, Teodoro Gallucci
🤖 gxceed AI 要約
日本語
本論文は、イタリアの農業残渣（リンゴ、ブドウ等）のバイオエネルギー潜在力をGISと空間分析で評価。北部と南部で偏在する潜在力分布を可視化し、バイオマス物流最適化や循環経済の実装支援に貢献。
English
This study quantifies bioenergy potential from selected agricultural residues in Italy using GIS and Local Moran's I analysis. Results show polarized spatial patterns, with northern areas like Bolzano having high potential from apple orchards. The framework supports biomass logistics optimization and circular economy implementation.
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
イタリアの農業残渣バイオエネルギー事例だが、日本でも地域ごとのバイオマス賦存量評価やGIS活用は重要。特にSSBJのScope3対応や地域循環共生圏（ローカルSDGs）の文脈で参考になる可能性がある。
In the global GX context
While focused on Italy, this GIS-based framework for assessing agricultural residue bioenergy potential is applicable globally. It supports the circular economy and renewable energy targets relevant to ISSB and CSRD reporting, especially for agri-food sector decarbonization.
👥 読者別の含意
🔬研究者:Spatial analysis method for biomass potential quantification can be replicated in other regions.
🏢実務担当者:Use the GIS framework to optimize supply chains for agricultural residues as bioenergy feedstock.
🏛政策担当者:Data on regional bioenergy potential can inform renewable energy and waste-to-energy policies.
📄 Abstract（原文）
The transition towards the circular economy (CE) is fundamentally reshaping Italian agrifood systems, thus enhancing sustainability. The aim of this research is to establish a spatially advanced framework for quantifying, monitoring, and valorizing agricultural residues, supporting their transition from being disposed of to being a valuable secondary material for renewable bioenergy. This study provides a provincial-scale territorial screening of selected agricultural residues in Italy based on a five-year average dataset (2020–2024) of apples, peaches, grapes, fava beans, peas, lentils, and chickpeas. The main contribution lies in combining crop-specific residue quantification, GIS-based mapping, and Local Moran’s I analysis to identify spatial clusters of theoretical bioenergy potential. The results indicate a geographically polarized pattern, with northern areas, such as Bolzano, which offers over 1.06 million GJ, exhibiting substantial potential driven by apple orchards. Conversely, southern regions have emerged as major contributors to grape- and legume-derived bioenergy potential. The integration of geospatial intelligence with the assessment of agricultural residues and their energy potential supports the implementation of circularity by optimizing biomass logistics, providing practitioners and stakeholders with environmental and economic data for improved sustainability performance.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/su18136418first seen 2026-07-16 05:01:47
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