Collections > UNC Chapel Hill Undergraduate Honors Theses Collection > Assessing Wood Biomass Residue Availability for UNC-Chapel Hill's Cogeneration Facility

As part of its Climate Action Plan, UNC has pledged to become coal-free by 2020 and carbon-neutral by 2050. As UNC’s combined heat and power (CHP) plant is the largest source of greenhouse gas (GHG) emissions, the University has aggressively initiated an effort to identify a cleaner fuel to substitute for coal. Due to technical specifications of the CHP plant, biomass has been identified as the best option, although until now no local sources are currently available. This project identifies specific wood biomass sources within a 50-mile radius of the University campus and locates potential fuel supply sources that could be used for firing or co-firing the boiler. The National Land Cover Database, ReferenceUSA platform and the NC Division of Solid Waste Management Permitted Facility List were used to identify 157 potential locations of biomass supply that were subdivided into 7 classes: Logging Residue, Construction and Demolition (C&D) Waste, Land Clearing and Inert Debris (LCID), Yard Waste (YW), Furniture Manufacturing, Mill Residue and Other Wood Waste. ArcGIS Network Analysis was used to model optimal routes and calculate transportation distances to the CHP plant from each potential supply location. A simple cost model was created that specified per unit transportation and fuel costs, including collection and harvesting, processing and on-site purchase expenses. Results from network analysis and cost modeling were combined in a linear programming model that was set to identify optimal monthly supply sources such that the fuel delivery cost is minimized. The results of the study show that there potentially exists a diverse and extensive fuel basket on a monthly basis. Of the seven classes of biomass fuel, C&D and Furniture Manufacturing were identified as the most optimal sources. Mill Residue and Other Wood Waste were optimal only during the peak demand or winter months. The remaining biomass fuel types were not optimal for use irrespective of demand fluctuations.