No abstract

Life cycle assessment (LCA) analysts are increasingly being asked to conduct life cycle-based systems level analysis at the earliest stages of technology development. While early assessments provide the greatest opportunity to influence design and ultimately environmental performance, it is the stage with the least available data, greatest uncertainty, and a paucity of analytic tools for addressing these challenges. While the fundamental approach to conducting an LCA of emerging technologies is akin to that of LCA of existing technologies, emerging technologies pose additional challenges. In this paper, we present a broad set of market and technology characteristics that typically influence an LCA of emerging technologies and identify questions that researchers must address to account for the most important aspects of the systems they are studying. The paper presents: (a) guidance to identify the specific technology characteristics and dynamic market context that are most relevant and unique to a particular study, (b) an overview of the challenges faced by early stage assessments that are unique because of these conditions, (c) questions that researchers should ask themselves for such a study to be conducted, and (d) illustrative examples from the transportation sector to demonstrate the factors to consider when conducting LCAs of emerging technologies. The paper is intended to be used as an organizing platform to synthesize existing methods, procedures and insights and guide researchers, analysts and technology developer to better recognize key study design elements and to manage expectations of study outcomes. K E Y W O R D Searly stage technology assessment, environmental impacts, industrial ecology, life cycle assessment (LCA), research and development (R&D), unintended consequences

Plastics production is responsible for 1% and 3% of U.S. greenhouse gas (GHG) emissions and primary energy use, respectively. Replacing conventional plastics with bio-based plastics (made from renewable feedstocks) is frequently proposed as a way to mitigate these impacts. Comparatively little research has considered the potential for green energy to reduce emissions in this industry. This paper compares two strategies for reducing greenhouse gas emissions from U.S. plastics production: using renewable energy or switching to renewable feedstocks. Renewable energy pathways assume all process energy comes from wind power and renewable natural gas derived from landfill gas. Renewable feedstock pathways assume that all commodity thermoplastics will be replaced with polylactic acid (PLA) and bioethylene-based plastics, made using either corn or switchgrass, and powered using either conventional or renewable energy. Corn-based biopolymers produced with conventional energy are the dominant near-term biopolymer option, and can reduce industry-wide GHG emissions by 25%, or 16 million tonnes CO 2 e/year (mean value). In contrast, switching to renewable energy cuts GHG emissions by 50%-75% (a mean industry-wide reduction of 38 million tonnes CO 2 e/year). Both strategies increase industry costs-by up to $85/tonne plastic (mean result) for renewable energy, and up to $3000 tonne À1 plastic for renewable feedstocks. Overall, switching to renewable energy achieves greater emission reductions, with less uncertainty and lower costs than switching to corn-based biopolymers. In the long run, producing bio-based plastics from advanced feedstocks (e.g. switchgrass) and/or with renewable energy can further reduce emissions, to approximately 0 CO 2 e/year (mean value).

Interest in biobased products has been motivated, in part, by the claim that these products have lower life cycle greenhouse gas (GHG) emissions than their fossil counterparts. This study investigates GHG emissions from U.S. production of three important biobased polymer families: polylactic acid (PLA), polyhydroxybutyrate (PHB) and bioethylene-based plastics. The model incorporates uncertainty into the life cycle emission estimates using Monte Carlo simulation. Results present a range of scenarios for feedstock choice (corn or switchgrass), treatment of coproducts, data sources, end of life assumptions, and displaced fossil polymer. Switchgrass pathways generally have lower emissions than corn pathways, and can even generate negative cradle-to-gate emissions if unfermented residues are used to coproduce energy. PHB (from either feedstock) is unlikely to have lower emissions than fossil polymers once end of life emissions are included. PLA generally has the lowest emissions when compared to high emission fossil polymers, such as polystyrene (mean GHG savings up to 1.4 kg CO2e/kg corn PLA and 2.9 kg CO2e/kg switchgrass PLA). In contrast, bioethylene is likely to achieve the greater emission reduction for ethylene intensive polymers, like polyethylene (mean GHG savings up to 0.60 kg CO2e/kg corn polyethylene and 3.4 kg CO2e/kg switchgrass polyethylene).