Reviewing the underlying assumptions in waste LCA models to identify impacts on waste management decision making

Many waste LCA models are available for waste management decision and policy makers to better manage their waste streams. These models contain inherent differences in their functionality (e.g., LCI, LCIA, technical assumptions), which creates complications for non-expert LCA users to interpret results. Here, we present a unique approach to identify crucial model similarities and differences by conducting scenario runs and comparing the results in the context of waste management decision making. Five waste LCA models were evaluated, the model defaults for the LCI, LCIA, and technical assumptions related to recycling, landfilling, and combustion were used. The recycling/combustion default assumptions were relatively similar amongst models compared to their landfill defaults. For recycling, the assumption of a forest carbon credit for paper products (applied in WARM) resulted in an environmental offset and in different outcomes than other models. The major differences for landfilling resulted from landfill gas management and energy recovery defaults, with MSW-DST associated with the most conservative collection efficiencies and no energy conversion which resulted in the greatest environmental footprints compared to other models, especially SWOLF and EASETECH. While for combustion the major difference amongst models was the inclusion of non-ferrous metal ash recovery. Overall, the models agreed the most environmental favorable results were to combust paper and organic materials and recycle plastics, glass, and metals. The results here assist waste management decision makers, who are typically non-expert LCA users, to gain a greater understanding of the major differences/similarities in their LCA study when using multiple models and better decide which model's functionality aligns best with their goals and scope. Expert LCA practitioners can use the study results to identify areas needing data collection, and to facilitate discussion about the acceptance of, or lack of, important technical assumptions.