An impact assessment dataset is a structured collection of data used within Life Cycle Impact Assessment (LCIA) to evaluate the environmental impacts of a product system. It encompasses two distinct types of datasets: impact category datasets and impact assessment method datasets.
The first type, an impact category dataset, contains a set of characterisation factors and/or weighting factors along with their supporting documentation, all referring to a single impact category. These characterisation factors are derived from characterisation models and are applied to convert Life Cycle Inventory (LCI) results into common units of impact category indicators. For example, an impact category dataset for climate change would include characterisation factors that convert various greenhouse gas emissions into CO₂ equivalents, enabling consistent quantification of global warming potential.
The second type, an impact assessment method dataset, consists of a collection of impact categories with accompanying documentation and rationale for the selection and combination of these categories. This represents a complete assessment framework rather than data for a single impact category. Examples include comprehensive LCIA methods such as ReCiPe, CML, or TRACI, each of which defines a specific set of impact categories, characterisation models, and sometimes normalisation and weighting approaches that together form a coherent methodology for environmental impact assessment.
Together, these datasets provide the foundation for transforming the elementary exchanges identified in Life Cycle Inventory analysis into meaningful environmental impact indicators. They enable LCA practitioners to assess diverse environmental concerns, from climate change and acidification to human toxicity and resource depletion, using scientifically grounded and internationally recognised characterisation models aligned with ISO 14040 and ISO 14044 standards.
