Supplementary data and calculation workbooks for: Feedstock Circularity Interest: A diagnostic classification lens for biomass- and waste-to-X technology comparison (doi:10.18710/2NPL8C)

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Supplementary data and calculation workbooks for: Feedstock Circularity Interest: A diagnostic classification lens for biomass- and waste-to-X technology comparison

doi:10.18710/2NPL8C

DataverseNO

2026-06-30

2

Barahmand, Zahir, 2026, "Supplementary data and calculation workbooks for: Feedstock Circularity Interest: A diagnostic classification lens for biomass- and waste-to-X technology comparison", https://doi.org/10.18710/2NPL8C, DataverseNO, V2

Supplementary data and calculation workbooks for: Feedstock Circularity Interest: A diagnostic classification lens for biomass- and waste-to-X technology comparison

doi:10.18710/2NPL8C

Barahmand, Zahir (https://ror.org/05ecg5h20)

Eikeland, Marianne

University of South-Eastern Norway

2026-06-28

DataverseNO

University of South-Eastern Norway

Barahmand, Zahir

Barahmand, Zahir

2026-06-28

https://doi.org/10.18710/2NPL8C

Earth and Environmental Sciences, circular economy, waste-to-X, sustainability

This 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.

Excel workbooks

<a href="http://creativecommons.org/licenses/by/4.0">CC BY 4.0</a>

Barahmand, Zahir & Eikeland, Marianne Sørflaten (2025). EcoStrategic index: Economic value creation through product portfolio diversity for waste-to-x technologies. Volume 214 Renewable and Sustainable Energy Reviews. DOI: 10.1016/j.rser.2025.115507

Barahmand, Zahir; Tokheim, Lars-Andre; Seljeskog, Morten; Wang, Liang; Serrano, Gonzalo del Alamo & Eikeland, Marianne Sørflaten (2026). Strategic assessment of syngas-to-chemicals pathways in a post-fossil economy: A pathway-aware extension of the EcoStrategic Index. Volume 31 Energy Conversion and Management: X. DOI: 10.1016/j.ecmx.2026.102005

Barahmand, Z., Tokheim, LA., Wang, L. et al. A large-scale, LLM-assisted and validated dataset of biomass and waste conversion technologies and feedstocks. Sci Data (2026). https://doi.org/10.1038/s41597-026-07820-0

Barahmand, Zahir, 2026, "Supporting Dataset for “An evidence map of feedstock reporting in biomass- and waste-to-X conversion research”", https://doi.org/10.18710/ZB68UG, DataverseNO, V2

Barahmand, Zahir, 2026, "Supplementary dataset and reproducible codes for LLM-assisted mapping feedstocks of eight conversion technologies from over 121,000 studies", https://doi.org/10.18710/JM6U7B, DataverseNO, V2

Barahmand, Zahir, 2026, "Label system, dictionaries, and audit evidence for harmonised over 133,000 feedstock items across major conversion technologies", https://doi.org/10.18710/WEZMJE, DataverseNO, V1

Barahmand Zahir, 2025, "Supplementary code and curated data for 1,863 experimental gasification studies (laboratory to commercial scale)", https://doi.org/10.23642/USN.30702092, DataverseNO, V1

Barahmand Zahir; Eikeland Marianne Sørflaten, 2025, "Dataset and code supplement: Mapping gasification technologies and feedstocks with a dual validated large-scale literature-derived dataset", https://doi.org/10.23642/USN.30546347, DataverseNO, V1

Barahmand, Zahir & Eikeland, Marianne Sørflaten (2025). EcoStrategic index: Economic value creation through product portfolio diversity for waste-to-x technologies. Volume 214 Renewable and Sustainable Energy Reviews. DOI: 10.1016/j.rser.2025.115507

https://doi.org/10.1016/j.rser.2025.115507

Barahmand, Zahir & Eikeland, Marianne Sørflaten (2025). EcoStrategic index: Economic value creation through product portfolio diversity for waste-to-x technologies. Volume 214 Renewable and Sustainable Energy Reviews. DOI: 10.1016/j.rser.2025.115507

Barahmand, Z., Tokheim, LA., Wang, L. et al. Feedstock reporting gaps limit interpretation of circularity claims across conversion technologies. Commun. Sustain. 1, 119 (2026). https://doi.org/10.1038/s44458-026-00120-z

10.1038/s44458-026-00120-z

Barahmand, Z., Tokheim, LA., Wang, L. et al. Feedstock reporting gaps limit interpretation of circularity claims across conversion technologies. Commun. Sustain. 1, 119 (2026). https://doi.org/10.1038/s44458-026-00120-z

Barahmand, Z., Tokheim, LA., Wang, L. et al. A large-scale, LLM-assisted and validated dataset of biomass and waste conversion technologies and feedstocks. Sci Data (2026). https://doi.org/10.1038/s41597-026-07820-0

10.1038/s41597-026-07820-0

Barahmand, Z., Tokheim, LA., Wang, L. et al. A large-scale, LLM-assisted and validated dataset of biomass and waste conversion technologies and feedstocks. Sci Data (2026). https://doi.org/10.1038/s41597-026-07820-0

Barahmand, Zahir; Tokheim, Lars-Andre; Seljeskog, Morten; Wang, Liang; Serrano, Gonzalo del Alamo & Eikeland, Marianne Sørflaten (2026). Strategic assessment of syngas-to-chemicals pathways in a post-fossil economy: A pathway-aware extension of the EcoStrategic Index. Volume 31 Energy Conversion and Management: X. DOI: 10.1016/j.ecmx.2026.102005

DOI: https://doi.org/10.1016/j.ecmx.2026.102005

Barahmand, Zahir; Tokheim, Lars-Andre; Seljeskog, Morten; Wang, Liang; Serrano, Gonzalo del Alamo & Eikeland, Marianne Sørflaten (2026). Strategic assessment of syngas-to-chemicals pathways in a post-fossil economy: A pathway-aware extension of the EcoStrategic Index. Volume 31 Energy Conversion and Management: X. DOI: 10.1016/j.ecmx.2026.102005

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00_ReadMe.txt

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01_ESI_tier_distributions_and_base_ESI_subindices.zip

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Contains the main article-specific calculation workbook and CSV exports for the tier-distribution profiles and ESI-derived descriptive indicators reported in the manuscript. It also includes the base comparison across the eight-technology core corpus.

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02_ESI_Feedstock_Sensitivity.zip

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Contains the sensitivity-analysis workbooks and CSV exports used to test key coding and interpretation choices, including the T1–T2 coding swap, HVPR versus UTC comparison, exclusion of unresolved T1b cases, and gasification corpus-design comparison.

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