Who needs regionalized life cycle impact assessment ? The case of Artic regions

Main Presenter:    Edgar Sergues 

Co-Authors:   Ben Amor     Louis Gosselin                                          

The Northern part of Quebec, called Nunavik, is an Arctic region about the same size as Sweden. It is not linked to any provincial roads nor to the electricity network. Therefore, energy production is almost exclusively relying on diesel generators with high GHG emissions. In a decarbonization context, several low-carbon alternatives are studied, such as solar panels and biomass.
Because of the very specific conditions, LCA in this region must be regionalized. Regionalization at the life cycle inventory (LCI) stage is well integrated in LCA software and databases. In contrast, at the life cycle impact assessment (LCIA) stage, some technical issues prevent regionalization from being properly integrated. On one hand, practical application is time-intensive, and, on the other hand, current regionalization methodologies are designed to be used at the world, continent or country aggregated resolutions that conceal regional specificities. The influence of this choice of aggregation must be investigated to unlock the application of regionalized LCIA at finer resolution.
To this intent, a new set of regionalized characterization factors (CF) is developed for the Nunavik region. This set is modelled for the eleven recommended regionalized midpoint impact categories (IC) of Impact World + methodology. Models like USEtox are parametrized for the assessed region using open access GIS (Geographical Information System) tools and various datasets (such as MERRA2 HydroSHEDS, FAO food balance sheets, WWF ecoregions, …). This new set of CF is then applied in two LCA case studies of energy generation systems in a decarbonization context in Nunavik.
Results show that LCIA regionalization affects key LCA indicators in different proportions depending on the considered IC. For example, freshwater acidification, human toxicity non-cancer and freshwater ecotoxicity are the highest impacted IC. Based on those results, the possibility to predict the influence of LCIA regionalization is investigated. It appears that the combination of two factors, relative to CF global spatial variability, contributes consistently to the influence of LCIA regionalization on key LCA indicators. First the amplitude of this variability for a given IC must be above one order of magnitude. Second the relative deviation from median value of highest contributing environmental flows must be above 75%. If these two conditions are met, LCIA regionalization will change LCA results and is therefore needed.

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