Spatial differentiation of chemical removal rates from air in life cycle impact assessment

PurposeSpatial differentiation is a topic of increasing interest within life cycle assessment (LCA). For chemical-related impacts, in this paper, we evaluate the relative influence of substance properties and of environmental characteristics on the variability in the environmental fate of chemicals using an advanced, spatially resolved model. The goal of this study is to explore spatial distribution and spatial variability of organic chemicals, assessing the variability of the removal rate from air with a multimedia spatially explicit model Multimedia Assessment of Pollutant Pathways in the Environment (MAPPE) Global with a resolution of 1 × 1°. This provides basis to help identify chemicals for which spatial differentiation will be important in LCAs, including whether differentiation will have added benefits over the use of global generic default values, such as those provided by the USEtox model.MethodologyA methodology was developed to explore spatial distribution and spatial variability of the fate of organic chemicals. Firstly, guidelines were developed to assign a hypothetical spatial distribution to chemicals which were clustered on the basis of their physical–chemical properties and persistence. Secondly, a test set of 34 representative organic chemicals was used to run MAPPE Global and USEtox model. The results of MAPPE Global were used to highlight spatial variability of removal rate from air amongst different chemicals and their related patterns of variability. A comparison between USEtox and MAPPE Global removal rates from air was performed for each chemical in order to highlight whether spatial differentiation is relevant for the assessment or not.Results and discussionHypothetical spatial distribution of chemical fate was assigned to each combination of physical–chemical properties and persistence. Besides, spatial variability of removal rates from air was assessed running MAPPE model for the test set of 34 chemicals. The variability of results spans from less than one to over four orders of magnitude, showing differences in variability for each cluster of chemicals. Furthermore, different patterns of spatial variability are associated to each cluster of chemical as the spatial pattern is driven by a specific component of the overall removal rate. The comparison between MAPPE and USEtox removal rates from air shows that for 14 out of 34 chemicals within the test set, USEtox values are close to the median of the results of MAPPE. For 11 out of 34, USEtox underestimates the removal rate from air and the results are close to the fifth percentile of MAPPE ones. This is mainly related to how wet/dry deposition and gas exchange are accounted in the two models.Conclusions and outlookThis work has made further progress towards understanding and implementing how to develop a tailored-made guidance for assessing spatial differentiation in LCA. Results on spatial distribution and spatial variability of chemical are presented as a basis for defining patterns of variability and supporting further development of spatial scenarios and archetypes to be used for life cycle impact assessment. This provides insights into whether using generic global default factors is likely to result in high uncertainty depending on the type of chemical, as well as whether pattern-specific factors would reduce the uncertainty. Uncertainties related to spatial differentiation are presented and discussed.

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