Data from: A proxy method to bridge LCA data gaps using automated material classification and probabilistic under-specification

Life cycle assessments (LCAs) are essential for understanding the
environmental impacts of material production. However, gaps in life cycle
inventory (LCI) data for material and chemical inputs present a key
challenge for LCA practitioners, especially in the early design stages.
Strategies for filling in these gaps require additional time and
expertise, which can hinder the LCA’s completion. This dataset is the
result of classifying existing LCI data for chemical and material
production processes by the product’s chemical structure, then evaluating
environmental impact distributions of all chemicals and materials within a
chemical group. LCI data for this dataset was collected from the Federal
LCA Commons, and the open-source web tool ClassyFire was used to classify
products by their chemical structure into the ChemOnt chemical taxonomy.
This results in a dataset of environmental impact distributions based on
existing LCI data and chemical structure, appropriate to be used as proxy
environmental impact data for chemicals or specialty materials when data
specific to that product does not exist. This dataset includes descriptive
statistics, specifically the minimum, 20th percentile, median, 80th
percentile, and maximum environmental impact for each environmental impact
and chemical entity group. The environmental impacts evaluated are Global
Warming Potential (GWP, evaluated using IPCC AR5 characterization
factors), Acidification Potential (AP), Eutrophication Potential (EP),
Ozone Depletion Potential (ODP), and Photochemical Oxidant Creation
Potential (POCP). Input materials with data gaps may be classified into
the same chemical taxonomy, where proxy environmental impact values can be
selected from the available distributions to quickly fill in any data
gaps. For an example of how this data may be used, please see the
associated spreadsheet tool in the Supplemental Information section. The
methods used to create dataset were applied to classify material
production processes available in the Federal LCA Commons in this dataset,
however could be similarly applied to other LCA databases.