Process modeling in prospective life cycle assessment: implications for value-added fuels and chemicals derived from bioresources

Bahar Riazi

doi:10.17918/00000104

Decarbonization of the transportation sector through the development of low carbon fuels from biomass may play an important role in the mitigation of global climate change. Life cycle assessment (LCA) is a systematic tool used to evaluate environmental tradeoffs across product life cycles and has been used to compare the environmental performance of biofuels relative to petroleum-based fuels. Prior LCA research has concluded that the environmental benefits and tradeoffs of biofuels depend on multiple factors, including feedstock, co-product allocation method, geography, and applied conversion processes. Moreover, there are technological challenges affecting profitability and hence commercialization of biorefineries. An important strategy for improving the economics of renewable fuel facilities is co-producing value-added products such as lubricants and polymers. In addition to carbon abatement, bio-based co-products can reduce toxicity and disposal costs relative to their petroleum-based alternatives. The building blocks of an LCA are physical accounts of mass and energy flows for individual materials or processes that are all compiled in a life cycle inventory (LCI). One of the challenges in building the LCI of specialty chemicals and new and early-stage biomass conversion technologies is a lack of data in commercially available LCA databases. The main objective of this thesis is to evaluate the environmental performance of emerging bioconversion technologies that produce renewable fuels and value-added products by developing and testing computational LCI models at varying levels of detail. In each objective, a unique method is applied to build the required life cycle inventory model and estimate missing uncertain parameters which include using experimental data combined with existing data and building new conversion pathways and testing upper and lower bounds to understand uncertainty in model performance, applying different thermodynamic and kinematic equations combined with Ab Initio methods, building a detailed model using process modeling simulation and expanding LCIA metrics, and evaluating environmental and economic differences through process modeling. Different feedstock resources including soybean oil, an edible feedstock, biomass sorghum, a dedicated energy crop, forest residue and corn stover, non-edible residues, and poultry fat waste and beef tallow, ready to use sources of free fatty acid that are waste, are examined. The methods applied in each objective of this thesis to estimate missing inputs required for building LCI can be generalized and used for other processes and products as well. Also, in selected objectives of this thesis techno-economic analysis (TEA) is combined with LCA demonstrating valuable insight through evaluation of tradeoffs of both environmental and economic performance of new products and processes relative to existing products in the market that are produced from a different resource or through a different bioconversion process.

Process modeling in prospective life cycle assessment: implications for value-added fuels and chemicals derived from bioresources

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Process modeling in prospective life cycle assessment: implications for value-added fuels and chemicals derived from bioresources

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