Life-Cycle Assessment and Uncertainty Analysis of Producing Biogas from Food Waste: A Case-Study of the First Dry-Process Biogas Plant in Sweden
(English)Manuscript (preprint) (Other academic)
Anaerobic digestion of source-sorted food waste is increasing in Sweden. Traditionally, all large-scale co-digestion plants in Sweden, including the ones which digest food waste, are based on wet process. In this article life-cycle assessment (LCA) is used in order to investigate the environmental performance of the first dry-process biogas plant based on source-sorted municipal food waste in Sweden. The environmental performance of this plant is compared with existing typical plants which are based on wet process. Biogas production systems are complex, and there are knowledge gaps and large uncertainties regarding some of the processes. Most existing biogas LCA studies do not take into account these uncertainties and use single values in their life-cycle inventories. In this study uncertainty propagation in LCA of biogas production system is performed and the results are discussed in order to gain system-level insights on the main factors that influence the performance of producing biogas from food waste and the key uncertainties. An attributional process-based LCA model is used to study the global warming potential, eutrophication potential, acidification potential, and non-renewable cumulative energy demand of producing biogas from food waste. A reference case is used which is based on an actual biogas plant in Sweden which uses dry process for treating source-sorted food waste. For the wet process, this case is altered using Swedish literature data on wet digestion systems. For uncertainty management, a combination of approaches, including possibility/fuzzy intervals and stochastic distributions are used. Possibility/fuzzy intervals are used for data collection, but they are translated into probability distributions and Monte Carlo simulation. A simple method for quantifying the uncertainties of the LCA results is used, so the critical uncertainties can be assessed, compared, and discussed. In addition, several key performance indicators were introduced to complement the LCA results.The results of the LCA and KPIs show that using dry process for processing of food waste has a better or comparable environmental performance compared to most existing (wet-process) biogas plants in Sweden. When uncertainties are considered, two systems are more comparable. Regardless of the choice of wet or dry process for treatment of food waste, there are large uncertainties in the non-technical parts of the system which are less dependent to the technical choices or scenario assumptions. Decision-makers who are interested in using biogas systems for treatment of source sorted food waste, should take dry process into consideration. From an energy and environmental perspective, dry process can have good or better performance compared to many existing plants which are based on the wet process. This is mainly due to simpler pretreatment and digestate management. Taking into account the uncertainties (knowledge gaps, and variabilities) in assessing and comparing the performance of biogas production from food waste, provides a more realistic picture of their strengths and weaknesses. Since some of the impacts (and benefits such as carbon sequestration) of using food waste for biogas production and its digestate as biofertilizer lies in areas with high uncertainties, communication of these benefits to wider socio-political actors can play an important role for the development of biogas from food waste in Sweden, because many of the benefits of biogas solutions are not visible when analyzed by LCA approaches that do not take into account these uncertainties.
life-cycle assessment, key performance indicators, uncertainty analysis, food waste, biogas, dry process
IdentifiersURN: urn:nbn:se:liu:diva-130774OAI: oai:DiVA.org:liu-130774DiVA: diva2:954663
ProjectsBRC-RP3 (system quantification projects)-Biogas from Food waste
FunderSwedish Energy AgencyLinköpings universitet