New Checklist Sets a Pass-or-Fail Bar for Transparency in Life Cycle Assessment Studies

Life cycle assessment, the workhorse method for quantifying the environmental footprint of products and technologies, has a transparency problem that researchers say has gone unaddressed for nearly two decades. A team led by A. Kamal Kamali and Guido Sonnemann of the University of Bordeaux, working with collaborators in France and Japan, now proposes a deceptively simple fix: a minimum reporting threshold, operationalized as a 31-item checklist, that determines whether an LCA study discloses enough information to be judged transparent at all. The work, published in Cleaner Engineering and Technology, argues that transparency should stop being treated as a vague continuum where any study can always be made somewhat more transparent, and instead become a binary pass-or-fail test grounded in the method’s own international standards.

The stakes are higher than they might appear. LCA is increasingly deployed not on mature industrial processes but on emerging technologies, from novel photovoltaic materials to experimental hydrogen pathways, where data are scarce, assumptions abound, and modeling choices multiply. When those choices go unreported, other researchers cannot reproduce the work, reviewers cannot properly scrutinize it, and the field accumulates results that cannot be compared or built upon. The scale of the problem is documented in prior reviews: an analysis of a random sample of 319 LCA articles found that only about 40 percent provided a complete and transparent description of their life cycle inventory data, the numerical backbone of any assessment.

The roots of the problem reach back to the founding standards of the method. ISO 14040 describes transparency as an important guiding principle, defining it as the open, comprehensive, and understandable presentation of information, and ISO 14044 specifies items that must be reported on methods, data, and results. But the standards deliberately grant practitioners wide latitude in selecting modeling choices, and that judgment is supposed to be made explicit through reporting and justification. In practice, the new study argues, three obstacles have prevented this: no minimum required information has ever been defined for a study to count as transparent; reporting requirements are scattered across multiple documents, generating duplicates and vague mandates; and the standards have not kept pace with the extra demands of assessing technologies at early stages of maturity.

To build the checklist, the researchers systematically reviewed ISO 14040, 14044, 14025, and 14071, along with the European International Reference Life Cycle Data System Handbook and recent methodological guidance for emerging-technology LCA. They extracted 140 reporting items verbatim, then screened them ruthlessly. Thirty-three were excluded as duplicates, either identical repetitions across documents or semantic duplicates that expressed the same requirement in different words. Twenty-one were dropped as too generic to define a concrete reporting obligation, such as calls for full transparency in value choices without specifying any actual decision to disclose. Twenty-four were judged irrelevant to peer-reviewed research articles, including executive summaries and administrative requirements specific to environmental product declarations. The surviving 62 items were consolidated into 31 checklist entries, each carrying reporting guidance, a location field for authors to indicate where the information appears, and a pass-or-fail field for reviewers.

Twenty-four of the 31 items are obligatory for every LCA study, covering fundamentals such as the functional unit, reference flow, system boundary, foreground and background system definitions, data sources, impact assessment method, and limitations. The remaining seven are conditional, triggered only by specific study contexts. An allocation procedure must be reported only when a product system is multifunctional; a scale-up method only when lab data are extrapolated to industrial scale; calculation steps only when inventory flows are computed or transformed rather than taken directly from databases. The decision rule is deliberately non-compensatory: a study passes only if it reports all obligatory items and all applicable conditional ones. The logic, the authors explain, follows directly from the ISO definition, since a study missing any required information is neither fully open nor comprehensively reported, and therefore cannot be called transparent.

To test whether the checklist could actually be applied, the team screened 370 records from a Scopus search and assessed ten recently published LCA case studies of emerging technologies. The results were revealing. Core items such as the reasons for the study, system boundary, data sources, and limitations were reported in all ten articles, and sensitivity analysis in nine. But two items drawn directly from ISO 14044 received zero passes across the entire sample: the description of previous iterations of the goal and scope, and cut-off criteria, the rules governing which flows and processes were excluded from the model. Their systematic omission, the authors note, may have implications for those studies’ implicit claims of ISO alignment. Other items fared barely better: temporal scope was reported in only three of ten studies, targeted audience in four, and completeness and consistency checks in one and two respectively.

The team then demonstrated what full compliance looks like by conducting a complete LCA of an emerging photovoltaic material, a silver bismuth sulfide film prepared by one-step solution crystallization, and reporting it against every checklist item. The case study is technically instructive in its own right. The functional unit was defined as one kilowatt-hour of electricity generated in southern Europe at 5.15 percent power conversion efficiency, requiring a reference flow of about 24 milligrams of film. The cradle-to-gate assessment found that producing that film at laboratory scale, where spin coating wastes over 99 percent of the precursor solution, emits 0.28 kilograms of carbon dioxide equivalent, close to the footprint of simply buying a kilowatt-hour of European grid electricity.

Contribution analysis pinpointed the hotspots with striking clarity: silver nitrate dominates most impact categories, with more than 99 percent of that impact traceable to silver itself, while bismuth nitrate, driven by bismuth metal production, ranks second. Untreated process emissions, including nitrates, nitrogen oxides, and thiourea, dominate three toxicity-related categories. When the researchers modeled industrial-scale deposition using slot-die coating with material utilization rates of 80 or 90 percent, instead of the current 0.69 percent achieved in the lab, climate impacts fell roughly 98-fold, to around 0.005 kilograms of carbon dioxide equivalent. The conclusion for solar researchers is blunt: the absorber material’s proof of concept is secure, but future work should prioritize replacing silver or designing cells that allow its recovery.

The authors are candid about the limits of their proposal. The checklist defines a minimum reporting requirement, not a complete measure of scientific transparency or methodological rigor; it cannot predefine study-specific limitations, and some items remain generic across study contexts. Different scale-up methods, for instance, demand different forms of documentation, from fully reported engineering equations to access to simulation models, and the checklist does not yet specify which. The authors suggest that large language models could eventually help by pre-filling the checklist from a manuscript, leaving authors to verify the output, and they recommend that journals adapt the tool for peer review, drawing on the structured verification logic already used by environmental product declaration programs.

What the study ultimately offers is a paradigm shift in how the field talks about openness. Transparency has long functioned as an aspiration, invoked in papers and standards but never tested. By converting it into a pass-or-fail threshold with traceable lineage to ISO requirements, the Bordeaux-led team gives authors a concrete target, reviewers a consistent yardstick, and editors a potential instrument for screening submissions. Adoption will require coordinated effort from standards bodies, researchers, and journal editors, and the checklist itself is presented as a starting point rather than a final word. But for a method whose credibility rests on whether its assumptions and data choices can be seen, the message lands: a study that hides its modeling decisions is not slightly less transparent. It is not transparent at all.

Subject of Research: A minimum transparency reporting threshold and checklist for life cycle assessment of emerging technologies

Article Title: Toward a Minimum Threshold for Transparent Reporting in LCA of Emerging Technologies: A Checklist

Article References: Kamali, A. K., Cojocaru, L., Toupance, T., Kubo, T., Segawa, H., Laratte, B., & Sonnemann, G. (2026). Toward a Minimum Threshold for Transparent Reporting in LCA of Emerging Technologies: A Checklist. Cleaner Engineering and Technology, 34, Article 101323. https://doi.org/10.1016/j.clet.2026.101323

Image Credits: AI Generated

DOI: 10.1016/j.clet.2026.101323

Keywords: life cycle assessment, transparency, ISO 14040, emerging technologies, reporting checklist, peer review, photovoltaics, silver bismuth sulfide, life cycle inventory, sustainability, functional unit, scale-up