The challenge of accessing data
Life Cycle Assessment (LCA) studies rely on inventories describing resource, material and energy inputs, as well as emissions and waste associated with processes. These datasets may be spread across national, sectoral, academic and commercial databases, using different formats, nomenclatures and access conditions.
The Global LCA Data Access (GLAD) network, maintained by the United Nations Environment Programme’s Life Cycle Initiative, was created to make it easier to find and access life-cycle inventory datasets from independent providers.
How GLAD works
GLAD connects independently operated databases, known as nodes. It provides a search interface and common metadata to help users discover datasets and understand their characteristics. Metadata, nomenclature and data-exchange requirements support greater interoperability.
GLAD is not a single central database that owns all the inventories. Providers remain responsible for their own nodes and the conditions under which data can be accessed. Availability, licensing and any usage fees therefore continue to depend on the provider.
Finding a dataset is not the same as validating it
GLAD makes discovery easier, but selecting an inventory still requires critical assessment. Users should check geographical and technological representativeness, reference period, coverage, methodology, data quality and licence conditions. A dataset being discoverable does not automatically make it suitable for a study’s goal and scope.
Interoperability also does not remove all methodological differences. Format conversion can make datasets easier to use, but users should check whether metadata, flows and essential information have been preserved.
Why national data matter
National databases, such as SICV Brasil, can provide inventories that better represent local production conditions. Participation in interoperability networks increases the visibility of these datasets and makes them easier for users in other countries to discover.
For LCA practitioners, GLAD is a starting point for searching data sources. The final choice should still be based on the fitness of the inventory for the system being studied, with decisions documented transparently.