Accessing bioenergy potential based on Loblolly pine residues using based-GIS models in Virginia

here is a lack of an assured supply of biomass feedstock for the bioenergy industry, which is often considered a prerequisite for more significant investments in biomass conversion capacity in the US. Cellulosic feedstocks offer the potential to reduce the diversion of food grains (e.g., corn) for energy production, thereby eliminating the food vs. fuel debate. Loblolly pine (Pinus taeda L.) is a perennial evergreen tree found throughout the southern United States and is essential for commercial timber. It proliferates readily, has low maintenance needs, long life expectancy, and is a dependable source of woody biomass. The study aims to employ geographical information systems (GIS) based bioenergy expansion strategies that suit specific geographical attributes, and are sustainable, economically viable, and socially desirable. We applied fuzzy logic combined with analytical hierarchy process analyses to reclassify and collate biophysical factors such as topography, site index, and land use land cover as well as socio-economic factors such as urban areas, critical species habitats, and local infrastructure to identify suitable regions for growing Loblolly pine. Further, we apply growth and yield model to estimate potential biomass at the sites. Finally, network location analyses to rank suitable sites for allocation of bioenergy plants based on residues of the pine production in Virginia.