Wednesday (9/25): 8:30am-10:00am, Primrose B
During this special session, representatives from federal agencies and the Federal LCA Commons (FLCAC) data curation team will present on coordinated federal life cycle inventory (LCI) data gap and data quality assessments. These data gap and quality assessments help prioritize LCI data development to support government procurement of lower embodied carbon construction materials and broader LCA community data needs. The session will include the following presentations:
- EPA will provide an update on an LCI data gap analysis based on datasets identified in published construction material PCRs and insights from active PCR committees. EPA will share its data quality assessment methodology for evaluating secondary data to be used in support of its Label Program for Low Embodied Carbon Construction Materials.
- The ERG FLCAC data curation team will review the methodology and results from a data gap assessment completed for the Federal LCA Commons based on a hotspot analysis using both environmentally-extended input-output models and process-based life cycle datasets. The FLCAC data curation team will also share findings from an assessment of data quality for existing FLCAC processes.
- NIST will present its data gap assessment method based on published PCRs, EPDs and available public LCIs, and results from LCA models comparing public and private datasets to identify and quantify the relative importance of public LCI data gaps. NIST will also provide progress on development of a machine-readable public database of extensive information reported in publicly published EPDs through ML/AI tools.
Following the initial presentations, we will facilitate an open panel discussion to learn from the audience about public secondary LCI data needs within the LCA community. The panel will also share opportunities for LCI data engagement, including through increased support for industry data submission to the USLCI database. The session organizers will use feedback from the audience to inform and prioritize LCI data gaps.