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The need for sustainable production and consumption is strongly present in today's society. To achieve this goal, a realistic quantification of environmental sustainability is needed. Calculating the environmental impact of products and processes can be done by conducting Life Cycle Assessments (LCA). The life cycle perspective ensures that all necessary inputs, processes and outputs are considered, and that environmental impacts are addressed at the point in the life cycle where they will most effectively reduce the overall impact. LCA results can guide the way for making decisions without the risk of burden shifting, but only if those results are robust and unambiguous. However, a few methodological shortcomings obstruct this, especially in the agri-food sector, such as only using central tendencies to calculate impacts thereby ignoring the possible range of input values; and the lack of consensus between the multiple possibilities that exist for allocating impacts between different products generated by the same system. In this PhD thesis, the focus lies on those two shortcomings using the apple agri-food chain as case study. Making conclusive decisions on what product or process is environmentally preferable is not possible when only using deterministic data. Yet, LCA results based on this kind of data is still being widely disseminated, meaning that uncertainty and variability are being ignored. Uncertainty and variability have a different origin and thus also a different implication, the combination is called "overall uncertainty". While uncertainty shows lack of knowledge, which can be reduced, variability reflects the natural heterogeneity in the world, which will always be observed. Published LCA studied were assessed through a systematic review, to identify to which extent uncertainty and variability have been separately accounted for. This turned out to be very limited, with only eleven studies having some kind of visualization showing which dominates the results. All methods had drawbacks attached to them. Two-dimensional Monte Carlo simulations (2DMC) was identified as a possible approach that allows to solve these drawbacks. 2DMC was introduced in the Belgian apple chain, comparing Jonagold and Kanzi apples in the cultivation chain and comparing bulk and pre-packed apples in the post-harvest chain. 2DMC allows to separately portray uncertainty and variability in LCA studies in a clear and representative way. This can help decision makers in judging the robustness of differences in product comparisons, while also indicating how the overall uncertainty can be reduced. Either the decision maker can already robustly conclude that one product could be preferred over the other, or it might be that the uncertainty and/or variability does not yet allow this. In the case that uncertainty is dominating, more knowledge should be gathered before making any decisions. In contrast, if variability is dominating, the only way to possibly reduce the overall uncertainty would be by examining the production system and making physical changes in the system itself. However, the latter is not always possible or even wanted. The second necessity for making accurate comparisons using LCA, is the equivalence of the system boundaries of the two options. However, equivalent system boundaries are currently lacking when organic crop production systems are compared to more conventional ones. Generally, when residual products from livestock systems get a second life as organic fertilizers, the impact of producing those residual products are ascribed to the livestock system, thus the system where it originates from. Meaning that no production impacts of those organic fertilizers are allocated to organic cultivation, the system where it is used and very much needed. This is in contrast with mineral fertilizers, used in conventional crop production systems, for which the production impact is allocated to the system where it is used. This inconsistency between organic and conventional crop production can lead to skewed LCA results. Multiple procedures exist to still allocate production impacts of organic fertilizers to organic cultivation, however, these can lead to very different results. Those different allocation procedures were therefore applied in an LCA of organic apple cultivation, to see where the difficulties for each procedure lies and to assess how much the results can be influenced by the chosen procedure. In the end, mass allocation was selected as the best way to approximate reality if a representative mass allocation factor is chosen that reflects the function of the organic fertilizers. The influence of factors from outside the system is limited for this procedure. In conclusion, the results show that with the discussed methodological improvements, comparing products and processes to assess their relative environmental impacts will be much more robust and conclusive. Clear decisions are much needed on industry, consumer and policy level to guide the way to sustainable production and consumption. status: published |
