A high spatial resolution dataset of China’s biomass resource potential - Rui Wang; Wenjia Cai; Le Yu; Wei Li; Lei Zhu; Bowen Cao; Jin Li; Jianxiang Shen; Shihui Zhang; Yaoyu Nie; Can Wang (Scientific Data, 2023)
Abstract Assessing biomass resource potential is essential for China’s ambitious goals of carbon neutrality, rural revitalization, and poverty eradication. To fill the data gap of high spatial resolution biomass resources in China, this study estimates the biomass resource potential for all types of lignocellulosic biomass feedstock at 1 km resolution in 2018, including 9 types of agricultural residues, 11 types of forestry residues, and 5 types of energy crops. By combining the statistical accounting method and the GIS-based method, this study develops a transparent and comprehensive assessment framework, which is in accordance with the principle of food security, forest land and pasture protection, and biodiversity protection. In the end, we organize and store the data in different formats (GeoTIFF, NetCDF, and Excel) for GIS users, integrated modelers, and policymakers. The reliability of this high spatial resolution dataset has been proved by comparing the aggregated data at the subnational and national levels with the existing literature. This dataset has numerous potential uses and is a crucial input to many bioenergy-related studies.