Biofuels are considered to be a promising sustainable alternative to traditional fossil fuels. There are many different technologies under development hence it is important to evaluate their economic potential and environmental impacts at early stage. This dissertation displays a systematic platform for evaluating performance of biofuel production systems by considering both economic and environmental metrics. It also demonstrates the necessity of incorporating uncertainty analysis into the results.

Techno-economic analysis is helpful in identifying pathways that have great potential of producing economically competitive end products. It also assists in understanding cost structure and thus guiding research efforts to effectively reducing costs of investigated pathway. Two case studies are used to show the four steps of techno-economic analysis: process modeling, mass and energy balance analysis, economic analysis and sensitivity analysis.

Results of techno-economic analysis are always uncertain to some extent as a result of uncertainties in the input parameters. It is thus important to quantify the uncertainties associated with the results of techno-economic analysis. This dissertation deals with the uncertainties by Monte-Carlo simulation. Uncertainties in input parameters is determined with historical data. A larger set of data is then generated and serve as input of the Monte-Carlo simulation. Uncertainties in the output results are then quantified using the output of the Monte-Carlo simulation.

The last part of the dissertation demonstrates the use of life cycle analysis as a powerful method to assess the environmental impacts of biofuel production technologies. Unlike previous studies with focus on greenhouse gas emissions, this dissertation focuses on fine particulate matters (PM2.5) and its precursors. A case study is analyzed to show how life cycle analysis can help with policy design.