A Systematic Transparency Assessment Framework for Life Cycle Background Database to Address Three-Level Black Boxes

Abstract

Life cycle background database (LCBD) is central to carbon footprint and life cycle assessment (LCA) modeling, yet transparency remains inconsistent across mainstream (ecoinvent, GaBi, USLCI) and emerging (TianGong, HiQLCD) databases. A lack of unified disclosure standards results in a pervasive “three–layer black box” across product coverage, model traceability, and data quality documentation. This opacity undermines the reproducibility of the results and hinders database selection. To address this, we systematically surveyed publicly available database information and constructed a full–process transparency chain: “results → model → unit processes/datasets → input and output inventory → raw data and processing.” The findings are as follows. Specifically, first, product quantity claims are frequently inflated through repetitive combinations of processes, masking limited actual diversity. Second, most databases lack reverse traceability from results to raw data, resulting in poor model reproducibility, reflecting a deficiency in basic standards. Data quality assessment methods are often misaligned with model logic, rendering the assessments themselves opaque and impractical for integration into user models. We propose the first end–to–end transparency assessment framework for LCBD, identifying key gaps and defining disclosure requirements. The framework includes a fact sheet for developers and a questionnaire tool for users, enabling evidence-based database selection. This work advances the methodological foundation for systematic transparency assessment, directly contributing to enhanced credibility, reproducibility, and standardization in the development and application of LCBD.