Application and adaptation of a scale-up framework for life cycle assessment to resource recovery from waste systems. (25th June 2022) - Elginoz, Nilay; Owusu-Agyeman, Isaac; Finnveden, Göran; Hischier, Roland; Rydberg, Tomas; Cetecioglu, Zeynep
Abstract: Prospective life cycle assessment (LCA) studies are widely used for evaluating emerging resource recovery systems. Simulations, engineering-based process calculations and stoichiometric methods are frequently used methods to generate life cycle inventory (LCI) in prospective LCAs. The engineering-based upscaling calculation is an efficient method for LCI generation requiring fewer resources than simulations. This study aims to test an engineering-based upscaling method for LCI generation and adapt it to biochemical resource recovery processes. The method's validity for biochemical resource recovery processes was tested using data for biogas generation by anaerobic digestion in laboratory, pilot, and full scales, and using a combination of lab-scale data and kinetic equations. Biogas generation was chosen for two reasons: (1) there are several emerging technologies based on anaerobic digestion with products other than biogas, and (2) data is available for different scales. The results showed, a substantial difference between the methane production amount in actual and conceptual plants, is an important cause of the variation in impact category results. Different estimations of fugitive emissions have an important impact on the global warming potential results. Combination of lab-scale data and kinetic equations approximates best with the actual plant for the abiotic depletion, eutrophication, freshwater aquatic ecotoxicity, global warming and photochemical ozone creation potentials. The results are sensitive to biogas generation amount in several categories. Highlights: Production yields achieved in the lab and actual plant affect impact category results. Equations specific to intended products together with experimental data are proposed. Conceptual design based on lab data couple with kinematic equations resembles better. The results are sensitive to biogas generation amount.