Price variance leads to significant uncertainty in Hybrid LCA footprints.
Abstract
Price information plays a crucial role in Hybrid LCA, linking physical process data to monetary input-output models. Prices however, are subject to market dynamics and myriad trading relations, leading to different prices for the same commodity across supply chains, or even between the different layers of the same supply chain. Given the linear relationship between the inputs into a process’ supply chain from the input-output model and the price of it’s reference product, the variability of commodity prices directly results in added uncertainty of the product’s environmental footprint. This uncertainty has so far only been assessed using non-process-specific theoretical price uncertainties. Here we use international trading statistics from BACI to model process specific commodity price distributions, and use these in an integrated hybrid model of the process database ecoinvent with the EE-MRIO database EXIOBASE. With this model we analyse the effect of price variance on the footprint of Swiss household consumption. We find that the variance of the IO part of the hybrid footprint has a 95% confidence interval of (-28%,+90%) relative to the median. Although the variance is calculated for a specific case, the magnitude highlights the importance of taking price variance into account when performing hybrid-LCA.
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