Allocation Games: Addressing the Ill-Posed Nature of Allocation in Life-Cycle Inventories.

Allocation is required when a life cycle contains multi-functional processes. One approach to allocation is to partition the embodied resources in proportion to a criterion, such as product mass or cost. Many practitioners apply multiple partitioning criteria to avoid choosing one arbitrarily. However, life cycle results from different allocation methods frequently contradict each other, making it difficult or impossible for the practitioner to draw any meaningful conclusions from the study. Using the matrix notation for life-cycle inventory data, we show that an inventory that requires allocation leads to an ill-posed problem: an inventory based on allocation is one of an infinite number of inventories that are highly dependent upon allocation methods. This insight is applied to comparative life-cycle assessment (LCA), in which products with the same function but different life cycles are compared. Recently, there have been several studies that applied multiple allocation methods and found that different products were preferred under different methods. We develop the Comprehensive Allocation Investigation Strategy (CAIS) to examine any given inventory under all possible allocation decisions, enabling us to detect comparisons that are not robust to allocation, even when the comparison appears robust under conventional partitioning methods. While CAIS does not solve the ill-posed problem, it provides a systematic way to parametrize and examine the effects of partitioning allocation. The practical usefulness of this approach is demonstrated with two case studies. The first compares ethanol produced from corn stover hydrolysis, corn stover gasification, and corn grain fermentation. This comparison was not robust to allocation. The second case study compares 1,3-propanediol (PDO) produced from fossil fuels and from biomass, which was found to be a robust comparison.

Economic and Sustainability Impacts of Yield and Composition Variation in Bioenergy Crops: Switchgrass (Panicum virgatum L.).

Economically viable production of biobased products and fuels requires high-yielding, high-quality, sustainable process-advantaged crops, developed using bioengineering or advanced breeding approaches. Understanding which crop phenotypic traits have the largest impact on biofuel economics and sustainability outcomes is important for the targeted feedstock crop development. Here, we evaluated biomass yield and cell-wall composition traits across a large natural variant population of switchgrass (Panicum virgatum L.) grown across three common garden sites. Samples from 331 switchgrass genotypes were collected and analyzed for carbohydrate and lignin components. Considering plant survival and biomass after multiple years of growth, we found that 84 of the genotypes analyzed may be suited for commercial production in the southeastern U.S. These genotypes show a range of growth and compositional traits across the population that are apparently independent of each other. We used these data to conduct techno-economic analyses and life cycle assessments evaluating the performance of each switchgrass genotype under a standard cellulosic ethanol process model with pretreatment, added enzymes, and fermentation. We find that switchgrass yield per area is the largest economic driver of the minimum fuel selling price (MSFP), ethanol yield per hectare, global warming potential (GWP), and cumulative energy demand (CED). At any yield, the carbohydrate content is significant but of secondary importance. Water use follows similar trends but has more variability due to an increased dependence on the biorefinery model. Analyses presented here highlight the primary importance of plant yield and the secondary importance of carbohydrate content when selecting a feedstock that is both economical and sustainable.

Techno-economic analysis and life cycle assessment of a biorefinery utilizing reductive catalytic fractionation.

Reductive catalytic fractionation (RCF) is a promising approach to fractionate lignocellulose and convert lignin to a narrow product slate. To guide research towards commercialization, cost and sustainability must be considered. Here we report a techno-economic analysis (TEA), life cycle assessment (LCA), and air emission analysis of the RCF process, wherein biomass carbohydrates are converted to ethanol and the RCF oil is the lignin-derived product. The base-case process, using a feedstock supply of 2000 dry metric tons per day, methanol as a solvent, and H2 gas as a hydrogen source, predicts a minimum selling price (MSP) of crude RCF oil of $1.13 per kg when ethanol is sold at $2.50 per gallon of gasoline-equivalent ($0.66 per liter of gasoline-equivalent). We estimate that the RCF process accounts for 57% of biorefinery installed capital costs, 77% of positive life cycle global warming potential (GWP) (excluding carbon uptake), and 43% of positive cumulative energy demand (CED). Of $563.7 MM total installed capital costs, the RCF area accounts for $323.5 MM, driven by high-pressure reactors. Solvent recycle and water removal via distillation incur a process heat demand equivalent to 73% of the biomass energy content, and accounts for 35% of total operating costs. In contrast, H2 cost and catalyst recycle are relatively minor contributors to operating costs and environmental impacts. In the carbohydrate-rich pulps, polysaccharide retention is predicted not to substantially affect the RCF oil MSP. Analysis of cases using different solvents and hemicellulose as an in situ hydrogen donor reveals that reducing reactor pressure and the use of low vapor pressure solvents could reduce both capital costs and environmental impacts. Processes that reduce the energy demand for solvent separation also improve GWP, CED, and air emissions. Additionally, despite requiring natural gas imports, converting lignin as a biorefinery co-product could significantly reduce non-greenhouse gas air emissions compared to burning lignin. Overall, this study suggests that research should prioritize ways to lower RCF operating pressure to reduce capital expenses associated with high-pressure reactors, minimize solvent loading to reduce reactor size and energy required for solvent recovery, implement condensed-phase separations for solvent recovery, and utilize the entirety of RCF oil to maximize value-added product revenues.