Supply Chain Impact Mapping (SCIM) Matlab Tool
Description
Version 5: Runs with all matlab versions and is based on EXIOBASE version 3.4. In contrast to version 4, this Matlab tool is provided as zip file containing the data for the year 1995 and 2015. The data for the remaining years can be downloaded from the exiobase homepage (https://www.exiobase.eu/index.php/data-download/exiobase3mon) or requested. Also, further information on how to work with the tool are available upon request (contact: livia.cabernard@istp.ethz.ch) This version was recently applied for mapping the impacts of the global plastics supply chain: https://doi.org/10.1038/s41893-021-00807-2 The methodology is described by the example of global material production in https://doi.org/10.1016/j.scitotenv.2019.04.434 and https://doi.org/10.1038/s41561-021-00690-8, and prevents the issue of double counting based on https://doi.org/10.1016/j.resconrec.2017.12.011. The regionalized impact assessment is based on UNEP-SETAC: https://www.lifecycleinitiative.org/training-resources/global-guidance-lcia-indicators-v-1/ and described in: https://doi.org/10.1007/s11367-017-1333-8 (water stress), https://doi.org/10.1021/acs.est.5b06153 (land-use related biodiversity loss) and https://doi.org/10.1021/acs.est.7b02589 (PM health impacts) Further application examples of SCIM (a selection): • Global Resource Outlook 2019 (Chapter 3): https://www.resourcepanel.org/reports/global-resources-outlook • Natural resource use in the G20: https://www.resourcepanel.org/reports/natural-resource-use-group-20 and https://doi.org/10.1088/1748-9326/ac52c7 • Brazil's food and beverage industry: https://doi.org/10.1016/j.jclepro.2021.129283 • Mining-related biodiversity loss footprint of metals and global electricity generation: https://doi.org/10.31223/X5T064 (using the Resolved Exiobase database REX: https://doi.org/10.5281/zenodo.6609852)