Date of Graduation


Document Type


Degree Type



Davis College of Agriculture, Natural Resources and Design


Forest Resource Management

Committee Chair

Jingxin Wang

Committee Co-Chair

Debangsu Bhattacharyya

Committee Member

James W Burnett

Committee Member

Joseph F McNeel

Committee Member

Daniel Robision

Committee Member

Erin M Searcy

Committee Member

Michael P Strager


World energy consumption is at an all-time high and is projected to continue growing for the foreseeable future. Currently, much of the energy that is produced comes from non-renewable fossil energy sources, which includes the burden of increased greenhouse gas emissions and the fear of energy insecurity. Woody biomass is being considered as a material that can be utilized to reduce the burden caused by fossil energy. While the technical capability to convert woody biomass to energy has been known for a long period of time, the cost of the feedstock has been considered too costly to be implemented in a large commercial scale. Increasing the use of woody biomass as an energy source requires that the supply chains are setup in a way that minimizes cost, the locational factors that lead to development are understood, the facilities are located in the most favorable locations and local resource assessments can be made.;A mixed integer linear programming model to efficiently configure woody biomass supply chain configurations and optimize the harvest, extraction, transport, storage and preprocessing of the woody biomass resources to provide the lowest possible delivered price. The characteristics of woody biomass, such as spatial distribution and low bulk density, tend to make collection and transport difficult as compared to traditional energy sources. These factors, as well as others, have an adverse effect on the cost of the feedstock. The average delivered cost was found to be between {dollar}64.69-98.31 dry Mg for an annual demand of 180,000 dry Mg. The effect of resource availability and required demand was examined to determine the impact that each would have on the total cost.;The use of woody biomass for energy has been suggested as a way to improve rural economies through job creation, reduction of energy costs and regional development. This study examined existing wood using bio-energy facilities in the northeastern United States to define the drivers of establishment of bio-energy projects. Using a spatial econometric framework, a spatial autoregressive probit model was estimated based on the Bayesian methods to define the factors that impact the location of wood using bio-energy facilities in the United States. Through the analysis it was found that the energy policy of the state is the biggest driver of the choice of location for bioenergy facilities.;The choice of site is of great importance when trying to meet the goal of producing cost-effective biofuels, due to the spatial dispersion of the biofuels and the high proportion of total cost that is incurred by transportation to the processing facility. The proximity to the fuel supply and the resulting transportation cost are the primary concern of the operators of the facilities, although this is not the primary driver that leads to the development of these projects. In order to make these endeavors successful, there must also be buy-in from the local community and its government. Previous studies have found that in addition to the environmental benefits and improved energy security, the impact that the facilities have on the local economy, in terms of job creation, improved industrial competitiveness and regional development are key drivers of bioenergy projects. A two-stage site selection approach is developed for the siting of woody biomass facilities, which combines multi-criteria analysis with mixed integer linear programming to rank potential development sites. This approach was then applied to the siting of a Coal/Biomass to liquids plant, and was able to objectively identify the optimal location of the facility.;Finally, a simulation model was developed to assess the locally available quantities and prices for biomass feedstocks. The simulation uses machine tractability in conjunction with graph theory to assess machine productivity and harvesting cost. The model was then applied to a demonstration project in which a 10,000 bbl per day Coal/Biomass to Liquid plant is being used to examine if there are sufficient feedstocks available to warrant the project. It was found that within the proposed three county procurement area that there were approximately 34% less material available than was assumed to be available from large scale feedstock data. Also, the simulation model was able to determine that the total feedstock requirement could be met at a price of {dollar}66 per dry Mg.