Study on the future development prospects of biomass energy in towns, townships, and subdistricts under multi-scenarios -A case study of Harbin City

Biomass energy is the most likely new energy source to replace fossil fuels. This study presents a prediction method for biomass energy supply -demand and changes in supply -demand patterns that connects the past and future. In the study, carbon peaking and carbon neutrality are taken as the time base. The FLUS model is used to simulate future land allocation in four basic scenarios: natural development scenario, agricultural development scenario, low -carbon development scenario and industrial development scenario; and townships, towns, and subdistricts are taken as the basic statistical unit. Based on this, we have examined the suitability of future development of biomass energy in rural and urban areas in each scenario, as well as its contribution to the future energy system transformation that substitutes for fossil energy. This method has been applied to the case study of townships, towns, and subdistricts in Harbin City in China. The study results show that: The degrees to which biomass energy potential can substitute for fossil energy in the four scenarios in 2030 reach 4.21%, 5.62%, 5.47%, and 3.82%, respectively. Under agricultural development scenario, the supply -demand balance areas account for 48.94%, meaning this scenario has the largest potential for energy development and transition; lowcarbon development scenario sees the highest degree of spatial supply -demand match, and thus enjoys the most advantages in energy transportation. The degrees to which biomass energy potential can substitute for fossil energy under the four scenarios in 2060 reach 2.01%, 6.96%, 5.35%, and 1.26% respectively. Agricultural development scenario still has the largest development potential, with the proportion of supply -demand balance areas jumping to 50.46%; Finally, low supply -high demand mismatch clusters are mainly concentrated in the main urban area and the central areas of townships, towns, and subdistricts. The high supply -low demand mismatch clusters are mainly distributed in the northeast. Under low -carbon development scenario, the low supply -high demand mismatch ratio has been reduced to 0.92%, the lowest supply -demand mismatch among all scenarios. Therefore, low -carbon development scenario enjoys the most spatial match advantages. This study will serve as an assessment method to advance the spatial development of biomass, and provide a geospatial basis for optimizing the layout of future energy development. Compared with previous studies, it has more spatial attributes, better reflects the complexity of biomass energy changes and is more connected with the measurement results and future policy making. In future research, we will combine multiple types of clean energy into the comparison and combined use to form a more comprehensive and specific research framework for new energy conversion. Longer -term macro -planning will go beyond the application boundaries of this research.