10.18710/2NPL8CBarahmand, ZahirZahirBarahmand0000-0001-9031-596Xhttps://ror.org/05ecg5h20DataverseNO2026Earth and Environmental Sciencescircular economywaste-to-XsustainabilityBarahmand, ZahirZahirBarahmandUniversity of South-Eastern NorwayUniversity of South-Eastern NorwayEikeland, MarianneMarianneEikelandUniversity of South-Eastern Norway2026-06-282026-06-282026-07-29Excel workbooks10.1016/j.rser.2025.11550710.1038/s44458-026-00120-z10.1038/s41597-026-07820-010.1016/j.ecmx.2026.10200575092637768585text/plainapplication/zipapplication/zip2.0CC BY 4.0This dataset supports the manuscript “Feedstock Circularity Interest: A diagnostic lens for biomass- and waste-to-X technology comparison.” The study develops a diagnostic feedstock circularity-interest lens for interpreting circularity claims in biomass- and waste-to-X technologies. The lens classifies reported feedstocks into five tiers according to nominal feedstock-side circular opportunity and the evidence and governance burden required to make that opportunity credible. It is intended for strategic screening: it does not rank technologies or measure sustainability performance, but identifies which feedstock-origin, baseline-fate, composition, hazard, and governance assumptions require clearer documentation before stronger circularity or sustainability claims are made. This dataset provides the article-specific supplementary data, calculation workbooks, and documentation used to reproduce the numerical results reported in the manuscript. It contains the final tier-distribution outputs, ESI-derived descriptive indicators, sensitivity-analysis workbooks, and figure/table source files. The sensitivity analyses include the T1–T2 lower-tier coding swap, comparison of strict highest-tier concentration (HVPR) with upper-tier concentration (UTC), exclusion of weakly specified or unresolved biogenic inputs from T1, and gasification corpus-design comparisons across core, modelling, and experimental/scale-explicit strata. The dataset supports transparency and reproducibility of the article’s descriptive screening results. The underlying feedstock extraction, harmonised labelling system, dictionaries, audit evidence, and broader evidence-base resources are provided in related open datasets cited in the manuscript.University of South-Eastern Norway