A bottom-up estimation of woody biomass energy potential including forest growth in Japan

Ryoga Ono, Rémi Delage and Toshihiko Nakata

Renewable Energy, 2024, vol. 229, issue C

Abstract: Until now, top-down estimation using the areal weighting interpolation method was applied to estimate the woody biomass energy potential for each of the 1741 municipalities in Japan. However, it was difficult to utilize the uncertain results in policy making. In contrast, bottom-up estimation can reflect the regional characteristics and provide novel benefits to policymakers. In this study, bottom-up estimation using the method of aggregation approach was carried out from the geospatial data for artificial forests, excluding protected forest, and considering forest growth. The data was collected from both national and each prefecture government. The forest growth of each forest division was adjusted by curve fitting and compared with statistical values to verify the estimation results. The woody biomass energy potential was defined as the amount of unused wood generated from harvesting to produce materials. In Japan, the total potential was 0.26–0.74 [EJ/year]. Comparing with the top-down estimation, these results were 34 % overestimated for the maximum value and 54 % underestimated for the minimum value. The detail results of geospatial distribution were statistically analyzed. Moran's I statistic was 0.68, and a hierarchical clustering with proportion resulted in the largest distribution with the majority of Japanese Ceder.

Keywords: Woody biomass energy potential; Renewable energy systems; Forest growth; Bottom-up estimation; Spatial distribution; Hierarchical clustering (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:229:y:2024:i:c:s0960148124007456

DOI: 10.1016/j.renene.2024.120677

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