A Stochastic Techno-Economic Analysis of a Forest Biomass Feedstock Supply Chain in the Northeast United States

Utilizing low-carbon forest biomass feedstocks in the Northeast United States for bioenergy applications has a substantial potential to mitigate greenhouse gas emissions by replacing fossil fuels. Understanding the economic feasibility of the regional forest biomass feedstock supply chain with uncertain variables is critical to supply feedstock for bioenergy projects whose lifetimes typically span over decades. This study developed a stochastic techno-economic analysis (TEA) model to assess the economic feasibility of the regional supply chain by using three 24-year scenarios that would produce primarily clean chips and dirty chips mixed with forest co-products. The stochastic TEA model produced net present values (NPVs) and minimum selling prices (MSPs) by using Monte Carlo simulation. The 1^st and 99^th percentiles of 10,000 MSP outcomes for clean chips were $40.90 and $63.80 per green metric tonne (Mg) while those for dirty chips from two different scenarios were $29.20 and $45.90/Mg and $25.50 and $47.90/Mg. The probabilities of gain for all three scenarios fell between 55% and 65%. Our sensitivity analysis revealed the variations of the NPV outcomes were most sensitive to the uncertainty of predominant forest biomass feedstock production levels and delivered prices, followed by fuel consumption and price variables.