Recognizing social forestry's role in bioenergy optimization through geospatial fuzzy-multicriteria analysis

IF 4.4 2区 工程技术 Q2 ENERGY & FUELS
Harkunti Pertiwi Rahayu , Al Hilal Firdaus S. Alim , Kornelis Blok , Seigo Nasu , Ganesha Mangkoesoebroto
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Abstract

Current bioenergy development has emphasized on degraded land, since the sustainability of bioenergy in the forest sector remains a subject of debate related with emissions and deforestation risk. Thus, this study aims to open new perspectives of how degraded land and social forestry can be potentially combined to significantly impact the energy transition and environmental-societal enhancement. Considering sustainability of Bali as a small island with its unique customary governance structure, a model of biomass energy optimization using geospatial fuzzy-multicriteria analysis was developed to select potential green energy source sites. Firstly, potential degraded land and social forestry were mapped to identify potential feedstock, then normalized using Euclidian Distance and Fuzzy Logic based on identified five sustainability criteria. They are availability of raw material, road, port, transmission, and demand proximities. Meanwhile, using identified three restriction criteria, i.e. protected area, slope and land-use restrictions, a restriction map was developed. The two maps were then integrated using Geospatial-based multicriteria analysis, fuzzy logic and Analytical Hierarchy Process (AHP) weighting method, to further identify potential green energy source map. The integration shown a significant increase of 60 % in land availability for bioenergy development. Results of study recognized potential 36,527 ha of degraded land; 21,671 ha of social forestry; and 40 optimal locations for bioenergy facilities, considering various spatial and temporal criteria. To conclude, the identified 120 social forestry sites in Bali involving 78,385 household provide opportunity to a community based socio-economic coupled with revitalizing environment efforts, which lead to massive net zero emissions community participation. Further, the integration of social forestry and degraded land should be highly recommended to policy maker in bioenergy development.

Abstract Image

通过地理空间模糊多标准分析认识社会林业在生物能源优化中的作用
目前的生物能源开发侧重于退化土地,因为森林部门生物能源的可持续性仍是一个与排放和毁林风险有关的争论主题。因此,本研究旨在开辟新的视角,探讨如何将退化土地和社会林业结合起来,对能源转型和环境社会改善产生重大影响。考虑到巴厘岛作为一个具有独特习俗治理结构的小岛的可持续性,本研究利用地理空间模糊多标准分析法建立了一个生物质能源优化模型,以选择潜在的绿色能源地点。首先,绘制了潜在的退化土地和社会林业地图,以确定潜在的原料,然后根据确定的五项可持续性标准,利用欧几里得距离和模糊逻辑进行归一化处理。这五项标准分别是原料可得性、道路、港口、传输和需求邻近性。同时,利用已确定的三个限制标准,即保护区、坡度和土地使用限制,绘制了限制地图。然后,利用基于地理空间的多标准分析、模糊逻辑和层次分析法(AHP)加权法对两张地图进行整合,进一步确定潜在的绿色能源地图。整合结果显示,可用于生物能源开发的土地大幅增加了 60%。考虑到各种空间和时间标准,研究结果确认了 36 527 公顷潜在的退化土地、21671 公顷社会林业和 40 个生物能源设施的最佳地点。总之,在巴厘岛确定的 120 个社会林业地点涉及 78,385 个家庭,为基于社区的社会经济和振兴环境工作提供了机会,这将导致大规模的净零排放社区参与。此外,应向生物能源开发的政策制定者强烈推荐社会林业与退化土地的结合。
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来源期刊
Energy for Sustainable Development
Energy for Sustainable Development ENERGY & FUELS-ENERGY & FUELS
CiteScore
8.10
自引率
9.10%
发文量
187
审稿时长
6-12 weeks
期刊介绍: Published on behalf of the International Energy Initiative, Energy for Sustainable Development is the journal for decision makers, managers, consultants, policy makers, planners and researchers in both government and non-government organizations. It publishes original research and reviews about energy in developing countries, sustainable development, energy resources, technologies, policies and interactions.
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