Meta-Analysis of Life Cycle Energy and Greenhouse Gas Emissions for Priority Biobased Chemicals


Research and development for biobased chemical production has become a strategic priority in many countries, due to the widespread availability of renewable feedstocks and the potential for reduced life cycle greenhouse gas (GHG) emissions and fossil energy use compared to petrochemicals. These environmental benefits are not assured, however, as a multiplicity of processing features (i.e., biofeedstock, conversion platform, and energy/solvent recovery) and life cycle modeling factors (i.e., coproducts, allocation scheme, study scope, and location) influence the overall GHG emissions and energy use of a biobased chemical production scheme. Consequently, there has been high variability in reported environmental impacts of biobased chemical production across prior life cycle assessment (LCA) studies. This meta-analysis considered 34 priority biobased chemicals across 86 discrete LCA case studies. Most biobased chemicals exhibited reduced GHG emissions and net energy use compared to petrochemical counterparts, with exceptions including <i>p</i>-xylene, acetic acid, and adipic acid. Seven priority biobased chemicals had no reported results, predominantly lignin-derived. GHG emissions reductions were compared against proposed thresholds from the Roundtable on Sustainable Biomaterials (RSB), the International Sustainability & Carbon Certification (ISCC), and those applied to U.S. biofuels under the Renewable Fuels Standard (RFS2) program. ANCOVA and ANOVA statistical tests were utilized to identify process and life cycle modeling factors that contribute significantly to environmental metrics. Conversion platform was found to be a statistically significant (α = 0.1) factor for GHG emissions, with thermochemical routes having the highest emissions results, while LCA coproduct allocation scheme was significant for nonrenewable energy use. Recommendations for harmonizing and prioritizing future work are discussed

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oai:figshare.com:article/4040688Last time updated on 2/12/2018

This paper was published in FigShare.

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