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Chemical production from crude oil represents a substantial percentage of the yearly fossil fuel use worldwide, and this could be partially offset by renewable feedstocks such as woody biomass and energy crops. Past techno-economic and environmental analyses have been conducted for isolated feedstocks on a regional or national scope. This study encompasses complete supply chain logistics analysis, delivered cost financial analysis, national availability, and environmental life cycle assessment (LCA) for 18 selected cellulosic feedstocks from around the world. A biochemical conversion route to monomeric sugars is assumed for estimated sugar yields and biosugar feedstock cost analysis. US corn grain was determined to have the highest delivered cost, while rice hulls in Indonesia resulted in the lowest cost of the feedstocks studied. Monomeric sugar yields from literature ranged from 358 kg BDMT-1 for US forest residues to 700 kg BDMT-1 for corn syrup. Environmental LCA was conducted in SimaPro using ecoinvent v2.2 data and the TRACI 2 impact assessment method for mid-point impacts cradle-to-incoming biorefinery gate. Carbon absorption during biomass growth contributed most substantially to the reduction of net global warming potential. Rice hulls and switchgrass resulted in the highest global warming potential, followed closely by corn and Thai sugarcane bagasse. Contribution analysis shows that chemical inputs such as fertilizer use contribute substantially to the net environmental impacts for these feedstocks. [ABSTRACT FROM AUTHOR]

The cradle-to-grave environmental impacts of thermochemical ethanol from loblolly pine, eucalyptus, unmanaged hardwoods, forest residues, and switchgrass biomass feedstocks were determined and compared to gasoline. The Tool for the Reduction and Assessment of Chemical and Other Impacts (TRACI) method was implemented in SimaPro 7.3 to calculate midpoint environmental impacts. Two normalization value sets were used and weighting was performed to produce a single environmental score. Greenhouse gas (GHG) emission reductions of cellulosic ethanol as compared to gasoline were 65%–77%, depending on the biomass feedstock, qualifying these biofuels as cellulosic ethanol under the Renewable Fuel Standards (RFS2). Effects of direct land-use change were significant (~ 18%) and could increase the GHG emissions for switchgrass derived ethanol above the federal GHG reduction thresholds for cellulosic ethanol. The production and use of cellulosic ethanol reduced fossil fuel consumption by between 95% and 97% and by 81% for forest and switchgrass derived ethanol, respectively. Cellulosic ethanol, however, did not reduce all environmental impact categories (e.g., eutrophication, ozone depletion respiratory effects, acidification, and smog) compared to gasoline. The fuel scenario ranking from lowest impact to highest impact consistently remained the same for GHG emissions, fossil fuel use, and the two single weight score analysis methods and was, in ascending order, forest residues with no forest establishment burdens, forest residues with forest establishment burdens, natural hardwood, pine, switchgrass, and finally gasoline. The GHG emission reductions from the use of cellulosic ethanol at the renewable fuel standards mandated production volume of 16 billion gallons of cellulosic ethanol per year by 2020 would result in 9–10 billion metric tonnes of GHG emissions avoided. [ABSTRACT FROM AUTHOR]

The integration of combinatorial green chemistry (CGC), a more benign approach to combinatorial chemistry, with environmental life cycle assessment (LCA) methodologies as an improved process development methodology is discussed. It is expected that the CGC approach will require less labor and result in more globally optimized assay results, leading to more optimized unit process design. The technique utilizes chemical assay stage information to rapidly predict globally optimized process conditions based on techno-economic and LCA indicators. A simplified kraft pulping case study of the application of CGC-LCA is demonstrated herein, but CGC analyses could be applied to virtually any chemical-based project development and implementation project. [ABSTRACT FROM AUTHOR]