Author

Weiguo Liu

Date of Graduation

2015

Document Type

Dissertation

Degree Type

PhD

College

Davis College of Agriculture, Natural Resources and Design

Department

Division of Plant and Soil Sciences

Committee Chair

Jingxin Wang

Committee Co-Chair

Debangsu Bhattacharyya

Committee Member

Kara Cafferty

Committee Member

Shawn Grushecky

Committee Member

Jamie Schuler

Committee Member

Kaushlendra Singh

Committee Member

Sabrina Spatari

Abstract

A mixed-integer programming model was developed to optimize forest carbon sequestration considering carbon price, biomass price, harvest area restriction, and harvest method. The model was applied to examine the harvest scheduling strategies and carbon sequestration in a mixed central Appalachian hardwood forest. Sensitivity analyses were conducted over a range of carbon and biomass to timber price ratios, harvest area limitations and harvest methods. The results showed that the carbon sequestration rate of the central Appalachian hardwood forests could gradually increase as the carbon to timber price ratio changed from 0.0 to 1.0 with an average sequestration rate of 0.917 Mg·ha -1·year-1. The rise of biomass to timber price ratio reduces the carbon sequestration potential. Additionally, the carbon sequestration potential would decrease when harvest area limitation varied from 0 (no harvest) to 100 ha. The decrease could be 97.4% and 70.8% respectively when the carbon to timber price ratios were 0.0 and 0.25. Low intensity partial cut could have a higher carbon sequestration rate comparing with clearcutting when the carbon to timber price ratio was low. We analyzed the economic feasibility and environmental benefits of an alternative technology that converts coal and biomass to liquid fuels (CBTL), using West Virginia as a real case scenario with considerations of woody biomass harvest scheduling optimization, feedstock transportation and siting options of potential CBTL plants. Sensitivity analyses on required selling price (RSP) were conducted according to feedstock availability and price, biomass to coal mix ratio, liquid fuel yield, IRR, capital cost, operational and maintenance cost. A cradle-to-grave life cycle assessment (LCA) model was also developed to analyze the environment benefits of the CBTL processes. The study of siting and capacity showed that feedstock mixed ratio limited the CBTL production. Sensitivity analysis on RSP showed the price of coal had more dominant effect than that of biomass. Different biomass mixed ratio in the feedstock and liquid fuel yield led to RSP ranging from $104.3 - $157.9/bbl. LCA study indicated that greenhouse gas (GHG) emissions ranged from 80.62 kg CO2 eq to 101.46 kg CO2 eq/1,000 MJ at various biomass to coal mix ratios and liquid fuel yield if carbon capture and storage (CCS) was applied. Most of water and fossil energy were consumed in conversion process at a CBTL facility. Compared to petroleum-derived-liquid fuels, the reduction in GHG emissions in West Virginia was estimated to be between -162 and 555 million tons over a 30-year period. A mixed integer linear programming (MILP) model and life cycle assessment (LCA) model were developed to analyze economic and environmental benefits by utilizing forest residues for small scale production of bioenergy in West Virginia. The MILP was developed to optimize the costs and required selling price of biofuels under different strategies. The cradle-to-gate LCA was developed to examine the greenhouse gas emissions, blue water and fossil energy consumption associated with the biomass utilization. The RSP in base case was $90.87/bbl ethanol and $126.08/bbl for diesel and gasoline. The sensitivity analysis on RSP showed that liquid fuel yield had most prominent effect and followed by internal rate of return (IRR) and feedstock price. The LCA showed that the GHG emissions from the production of 1,000 MJ energy equivalent ethanol was 9.72 kg CO2 eq which was lower than fast pyrolysis (9.72 kg CO2 eq). Fast pyrolysis had high water and energy consumption. The uncertainty analysis showed the change of environmental impact by the change of liquid fuel yield. The risk of biomass to liquid via fast pyrolysis (BLFP) to have a negative energy output was expected when the liquid fuel yield was low. The production of ethanol required lower cost and had lower environmental impact, that is to say, the costs for reducing 1 kg CO 2 eq GHG emissions was low in biomass to ethanol (BTE), but more biomass was required to produce same amount of energy equivalent liquid fuels. Finally, a modeling process was developed to examine the economic and environmental benefits of utilizing energy crops for biofuels and bio-products. Three energy crops (hybrid willow, switchgrass and miscanthus) that can potentially grow on marginal agricultural land or abandoned mine land in the Northeastern United States were considered in the analytical process for the production of biofuels, biopower and pellet fuel. The supply chain components for both the economic and life cycle modeling processs include feedstock establishment, harvest, transportation, storage, preprocessing, energy conversion, distribution and final usage. Sensitivity analysis was also conducted to assess the effects of energy crop yield, transportation distance, bioproduct yield, different pretreatments, facility capacity and internal rate of return (IRR) on the production of bioenergy products. The RSPs were ranged from $7.39/GJ to $23.82/GJ for different bioproducts. The production of biopower had the higher required selling price (RSP) where pellet fuel had the lowest. The results also indicated that bioenergy production using hybrid willow demonstrated lower RSP than the two perennial grass feedstocks. Biopower production presented the lowest GHG emissions (less than 10 kg CO2eq per 1,000 MJ) and fossil energy consumption (less than 160 MJ per 1,000 MJ) but with the highest water consumption. The production of pellet fuel resulted in the highest GHG emissions. Sensitivity analysis indicated that bioproduct yield was the most sensitive factor to RSP and followed by transportation distance for biofuel and biopower production. Bioproduct yield and transportation distance of feedstock presented great effects on environmental impact for the production of liquid fuels and biopower.

Share

COinS