Indicators for selecting between alternatives in comparative LCA of waste management systems

Life Cycle Assessment (LCA) has been widely used to compare the environmental performance of alternative waste management systems (Christensen et al., 2020). Comparative LCA allows identifying preferable alternatives in decision-making, and can prevent and minimize potential environmental impacts of emerging solutions when used as early as the research and development stage (Bisinella et al., 2021). However, LCAs are also subject to various sources of uncertainty, such as data variability, assumptions, and modelling choices. Such uncertainties are even more relevant for emerging solutions. Uncertainty analysis and quantification in LCA has been addressed by a number of authors, who identified stepwise procedures to quantify uncertainty in LCA models and their results (Bisinella et al., 2016; Clavreul et al., 2012). Further step-wise procedures and indicators from uncertainty statistics methods are required when the aim is to compare alternative solutions with LCA, under uncertainty. Ultimately, the LCA practitioner requires indicators to establish whether the LCA results of the compared alternatives, under uncertainty, are different, and whether this difference is significant. Heijungs (2021) provides an overview of methods and indicators that can fulfill this purpose, and provides an indicator for answering both questions. However, such methods and indicators are not validated based on LCA results from a case study, but on arbitrary distributions with data points of always positive sign. Depending on the aim of the LCA study, system boundaries and modelling approaches, LCA results can often also be of negative sign. Moreover, input-specific and process-specific waste LCAs are subject to various sources of uncertainty and specific modelling choices, which need to be specifically addressed. The aim of this presentation is to illustrate existing uncertainty statistics methods and indicators that can be used to compare alternative waste management solutions with LCA, under uncertainty. The presentation will be based on a real-scale waste LCA case study focusing on alternative scenarios for amending the incineration facility Amager Bakke in Copenhagen with carbon capture and storage (CCS) (Bisinella et al., 2022). References Bisinella, V., Christensen, T.H., Astrup, T.F., 2021. Future scenarios and life cycle assessment: systematic review and recommendations. Int. J. Life Cycle Assess. 26, 2143–2170. Bisinella, V., Conradsen, K., Christensen, T.H., Astrup, T., 2016. A global approach for sparse representation of uncertainty in Life Cycle Assessments of waste management systems. Int. J. Life Cycle Assess. 21, 378–394. Bisinella, V., Nedenskov, J., Riber, C., Hulgaard, T., Christensen, T.H., 2022. Environmental assessment of amending the Amager Bakke incineration plant in Copenhagen with carbon capture and storage. Waste Manag. Res. 40, 79–95. Christensen, T.H., Damgaard, A., Levis, J., Zhao, Y., Björklund, A., Arena, U., Barlaz, M.A., Starostina, V., Boldrin, A., Astrup, T.F., Bisinella, V., 2020. Application of LCA modelling in integrated waste management. Waste Manag. 118, 313–322. Clavreul, J., Guyonnet, D., Christensen, T.H., 2012. Quantifying uncertainty in LCA-modelling of waste management systems. Waste Manag. 32, 2482–95. Heijungs, R., 2021. Selecting the best product alternative in a sea of uncertainty. Int. J. Life Cycle Assess. 26, 616–632