UC Davis

Forests are a major natural resource of the state of California, where over a third of the land is forested, and provide a wide range of environmental, economic, and social benefits. Over the past decade, unprecedented drought and insect outbreaks have resulted in large-scale tree mortality that greatly affects the functionality of the forest ecosystem and amplifies the fire hazard. Forest thinning and management is considered imperative to improve forest health and resilience. Forest resources including dead and dying trees as well as the residues produced from forest thinning and timber harvesting operations can be utilized to generate electricity to meet the increasing demand for renewable energy and mitigate the risk of wildfires. However, efforts to construct new electricity generation capacity in the state at any scale over the last several decades have faced both economic and environmental challenges. As needs for alternative management approaches have become clear in the wake of extensive drought, intensive wildfire and other stresses on the forest ecosystem, opportunities have emerged for new bioenergy projects. These projects need to be effectively planned and potential economic and environmental performance carefully evaluated. Toward this purpose, a framework model for lifecycle and technoeconomic assessment was developed to quantify environmental and economic impacts of generating electricity using forest resources, with associated web services developed for a robust web-based application that allows potential users to quickly estimate the economic and environmental performance of a potential biopower facility at specified locations. While not intended to replace detailed project engineering, siting and permitting evaluations needed for any actual project implementation, the model can provide preliminary assessments to inform decisions and highlight information needs relating to further project development. Case studies were conducted to assess the model performance and examine the ability to effectively predict costs and benefits for use of forest resources in California. For all the combinations of forest treatments and harvesting systems, levelized cost of energy (LCOE) ranges from $135 to $575 per MWh electricity generation in the case study modeling a 25 MWe facility using a conventional boiler-steam cycle, and ranges from $183 to $588 per MWh electricity generation in the case study modeling a 3 MWe gasification facility. Optimization based on a minimum feedstock cost objective function further lowers the LCOE and can be effectively realized at lower computational intensity than needed for complete evaluation over the full resource dataset by using a partial search employing an expansion factor method developed for this purpose. Substantial environmental benefits were achieved from utilizing forest resources to generate electricity as compared to open pile burning under the assumption that the biomass will be burned in open piles in the absence of bioenergy uses, and from the displacement of grid electricity given the current mix of nonrenewable and renewable sources. Two baseline scenarios were considered in the case studies, in which for both clearcut was selected as the forest treatment and the ground-based mechanized whole-tree system as the harvesting system, along with the associated technical, economic, and financial assumptions. The potential emissions reductions from utilizing the forest biomass for electricity generation are significant. The emissions of GHG, CO, NOx, PM2.5, and VOC for a 25 MWe facility using a conventional boiler-steam cycle, a 25 MWe combined heat and power facility, and a 3 MWe gasification facility achieved reductions of between 21 and 99%, 44 and 99%, and 51 and 99%, respectively. Net GHG emissions for the three modeled conversion technologies in the baseline scenarios are negative compared to open burning at -440, -926, and -1084 kg per MWh electricity generation, indicating significant opportunities for resource management with improved overall environmental performance.