A methodology and decision support tool for informing state-level bioenergy policymaking: New Jersey biofuels as a case study

This dissertation seeks to provide key information and a decision support tool that states can use to support long-term goals of fossil fuel displacement and greenhouse gas reductions. The research yields three outcomes: (1) A methodology that allows for a comprehensive and consistent inventory and assessment of bioenergy feedstocks in terms of type, quantity, and energy potential. Development of a standardized methodology for consistent inventorying of biomass resources fosters research and business development of promising technologies that are compatible with the state's biomass resource base. (2) A unique interactive decision support tool that allows for systematic bioenergy analysis and evaluation of policy alternatives through the generation of biomass inventory and energy potential data for a wide variety of feedstocks and applicable technologies, using New Jersey as a case study. Development of a database that can assess the major components of a bioenergy system in one tool allows for easy evaluation of technology, feedstock and policy options. The methodology and decision support tool is applicable to other states and regions (with location specific modifications), thus contributing to the achievement of state and federal goals of renewable energy utilization. (3) Development of policy recommendations based on the results of the decision support tool that will help to guide New Jersey into a sustainable renewable energy future.;The database developed in this research represents the first ever assessment of bioenergy potential for New Jersey. It can serve as a foundation for future research and modifications that could increase its power as a more robust policy analysis tool. As such, the current database is not able to perform analysis of tradeoffs across broad policy objectives such as economic development vs. CO2 emissions, or energy independence vs. source reduction of solid waste. Instead, it operates one level below that with comparisons of kWh or GGE generated by different feedstock/technology combinations at the state and county level. Modification of the model to incorporate factors that will enable the analysis of broader energy policy issues as those mentioned above, are recommended for future research efforts.