{
 "dataset": "research",
 "version": "1.4.0",
 "generated_on": "2026-10-31",
 "licence": "CC BY 4.0 for ComputeFinder-owned summaries, labels and compilation rights only, except where a record supplies a specific adaptation licence. Third-party material retains its source terms.",
 "licence_url": "https://creativecommons.org/licenses/by/4.0/",
 "licence_scope": "Only copyright and database rights controlled by ComputeFinder in its original contributions. No third-party rights are granted. Source reuse terms have not been comprehensively cleared; consult each linked source. Private submissions, contact details, code and branding are excluded.",
 "source_terms_status": "Not comprehensively cleared; check linked sources before reusing third-party material.",
 "attribution": "Compiled by ComputeFinder (https://computefinder.net). Original contributions licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/), except adaptations carrying a record-specific licence. Give appropriate credit, retain licence and source notices, and indicate changes when sharing. Each record links its primary source; retain any attribution required by that source. Material is provided as-is without warranties.",
 "note": "These are ComputeFinder-owned independently worded accounts of reports, methods and guidance, not imported source material. Guidance is not an empirical observation or modelled outcome by itself. Retain each publisher, original source link, source_notice, recorded publication/update/check dates, reuse terms, attribution and record-specific licence or derived-work notices. Publication dates and reuse terms may be unknown: null in JSON and empty in CSV never imply a source licence or a new evidence check. The two retained report-summary CC BY 4.0 bases apply only to their exact reviewed components, not to other guidance or government pages. No publisher endorsement, general source licence, underlying dataset, Annex, proprietary inputs, copied text, chart, table, image or local-project inference is supplied. As-is, without warranties. Missing values are null or absent, never zero; no prices are included.",
 "records": [
  {
   "slug": "lbnl-us-data-center-energy-usage-2025-update",
   "title": "United States Data Center Energy Usage Report: 2025 Update",
   "publisher": "Lawrence Berkeley National Laboratory",
   "original_url": "https://www.energy.gov/documents/united-states-data-center-energy-usage-report-2025-update",
   "publication_date": "18 June 2026",
   "data_period": "Modelled historical estimates cover 2016 to 2024; future scenarios cover 2025 to 2030. Primary shipment data covered only the first three quarters of 2025.",
   "scope": "United States data-centre electricity use across servers, storage, networking and facility infrastructure. Cryptocurrency mining is excluded.",
   "method": "A bottom-up model combines equipment shipments and the installed base with per-device power and use assumptions, then applies facility type and power usage effectiveness estimates. It updates the method used in the 2024 report; equipment datasets and power assumptions were compiled through December 2025.",
   "evidence_type": "scenario",
   "assumptions": "Material inputs include server and accelerator shipments and lifetimes, rated and idle power, utilisation, workload mix, facility types, power usage effectiveness and the electricity forecast used as the national denominator.",
   "uncertainty": "Four sensitivity scenarios and compounded stress-test bounds explore selected inputs. Inference utilisation lacks verifiable data. The scenarios exclude major departures caused by technology, market, supply-chain, regulatory or grid-availability changes; the bounds do not cover every uncertainty.",
   "funding_interests": "Berkeley Lab conducted the work with DOE Industrial Technologies Office support under a DOE contract. Omdia, S&P Global and IDC supplied inputs. IDC datasets were purchased; Omdia paid products were supplied with complimentary access. Industry experts commented on assumptions. These relationships do not establish whether findings are correct.",
   "reuse_terms": "The report states that it is licensed under Creative Commons Attribution 4.0. The underlying proprietary input datasets retain their own terms and are not imported here.",
   "checked_on": "5 October 2026",
   "related_question": "What does this public model estimate about US data-centre electricity use, and which assumptions shape its range?",
   "cannot_establish": "It does not establish electricity demand, water use, emissions, grid impact, planning status, local costs, consent or delivered benefits for a particular site. It is not a global estimate or a commitment that a scenario will occur.",
   "authors": "Sarah J. Smith, Alex Hubbard, Alex Newkirk, Mohan Ganeshalingam, Billie Holecek, Dale Sartor, Michael Mills and Arman Shehabi",
   "page_url": "https://computefinder.net/research/lbnl-us-data-center-energy-usage-2025-update"
  },
  {
   "slug": "iea-key-questions-energy-ai-2026",
   "title": "Key Questions on Energy and AI",
   "publisher": "International Energy Agency",
   "original_url": "https://www.iea.org/reports/key-questions-on-energy-and-ai",
   "publication_date": "16 April 2026",
   "data_period": "Periods vary by question. The data-centre demand cases show historical estimates from 2020 through 2025 and projections to 2035. Supporting market, project and supply-chain inputs include material available through early 2026.",
   "scope": "Global and regional analysis of data-centre electricity demand, power supply, constraints, affordability and selected uses of AI in energy. It covers all data-centre workloads when modelling facility electricity, then separately analyses AI-focused infrastructure where the evidence permits.",
   "method": "The electricity-demand model is a bottom-up equipment-stock model derived from annual shipments of servers, storage and network equipment, with equipment power and utilisation, facility type and power usage effectiveness assumptions. The broader report also uses project and satellite tracking, financial-market analysis, case studies and OECD economic modelling.",
   "evidence_type": "scenario",
   "assumptions": "Four cases vary demand for digital and AI services, efficiency, financing and physical constraints. Regional allocation and electricity use depend on shipment forecasts, equipment lifetimes, idle and active power, utilisation, storage and network stocks, facility archetypes, power usage effectiveness and the timing of grid, chip and energy-equipment bottlenecks. Some technical inputs use United States estimates across regions.",
   "uncertainty": "The report says uncertainty widens after 2030. Outcomes depend on AI adoption, model and hardware efficiency, market sentiment, speculative, early-stage, delayed, cancelled or otherwise unrealised project pipelines and the pace at which supply-chain and grid constraints ease. The underlying third-party datasets are not reproduced in enough detail in the public report for independent audit. Different sections have different evidence strength and cannot responsibly be combined into a single net impact.",
   "funding_interests": "The work was designed and directed within the IEA. The acknowledgements list reviewers from governments, utilities, technology and energy companies, manufacturers, research organisations, civil society and consultancies. The report says its findings reflect the IEA Secretariat and not necessarily any funder, supporter or collaborator. No separate external funding amount or sponsor is identified in the acknowledgement pages reviewed. These disclosures do not establish whether the findings are correct.",
   "reuse_terms": "The report landing page labels the report CC BY 4.0. The PDF gives Annex A, including its data tables, a separate CC BY-NC-SA 4.0 notice. The standalone data product uses the IEA non-CC terms. The IEA excludes logos, cover images, photographs and third-party components from its CC grant. ComputeFinder links to the report and uses an original attributed summary only, without copying charts, tables, data, images or third-party material.",
   "checked_on": "5 October 2026",
   "related_question": "What does the IEA's current global model say about the direction of data-centre electricity demand, and which adoption, efficiency and infrastructure assumptions shape its cases?",
   "cannot_establish": "It cannot establish the electricity or water demand, grid effect, planning merits, price effect, construction stage, community view or delivered benefit of a particular project. Its cases are not commitments, and global or regional results do not resolve a local decision.",
   "licence_url": "https://creativecommons.org/licenses/by/4.0/",
   "attribution": "IEA 2026; Key Questions on Energy and AI, https://www.iea.org/reports/key-questions-on-energy-and-ai, Licence: CC BY 4.0.",
   "derived_work_notice": "This is a work derived by ComputeFinder from IEA material and ComputeFinder is solely liable and responsible for this derived work. The derived work is not endorsed by the IEA or its Member countries in any manner.",
   "page_url": "https://computefinder.net/research/iea-key-questions-energy-ai-2026"
  },
  {
   "slug": "doe-femp-cooling-water-guidance",
   "title": "Cooling Water Efficiency Opportunities for Federal Data Centers",
   "publisher": "U.S. Department of Energy, Federal Energy Management Program",
   "original_url": "https://www.energy.gov/cmei/femp/cooling-water-efficiency-opportunities-federal-data-centers",
   "publication_date": null,
   "data_period": "Explanatory guidance; no measured time series is admitted.",
   "scope": "Selected text about internal liquid-cooling loops and final heat rejection.",
   "method": "Engineering guidance describing system variants; no figure or numeric case result is reproduced.",
   "evidence_type": "guidance",
   "assumptions": "A described arrangement is one variant, not every cooling installation.",
   "uncertainty": "The text does not measure a named facility or establish a universal water/energy trade-off.",
   "funding_interests": "FEMP is the issuing federal programme. Separate authorship or funding for the selected page component was not established.",
   "reuse_terms": null,
   "checked_on": "2026-10-31",
   "related_question": "Does an internal closed-loop label alone determine water consumption?",
   "cannot_establish": "A named site’s actual water, indirect footprint, peak electricity load or net saving.",
   "licence_url": null,
   "attribution": "Source: U.S. Department of Energy/FEMP; minimal independently worded description with original link; no endorsement.",
   "source_notice": "Source copyright and any applicable third-party rights are retained. Minimal independently worded attributed facts and ordinary unframed links only. No copied passages, figures, tables, model inputs, images, databases or broad source-use grant; no endorsement. No open licence is asserted unless separately identified for the exact component.",
   "source_updated_on": null,
   "page_url": "https://computefinder.net/research/doe-femp-cooling-water-guidance"
  },
  {
   "slug": "epa-hourly-electricity-matching-guidance",
   "title": "24/7 Hourly Matching of Electricity",
   "publisher": "U.S. Environmental Protection Agency",
   "original_url": "https://www.epa.gov/green-power-markets/247-hourly-matching-electricity",
   "publication_date": null,
   "data_period": "Explanatory procurement definitions; no measured hourly dataset is admitted.",
   "scope": "Annual-volume matching and hourly/regional matching as described by EPA.",
   "method": "Agency explanatory definitions, not a buyer audit or grid-emissions calculation.",
   "evidence_type": "guidance",
   "assumptions": "The distinction concerns timing and geographic matching rather than a specific contract.",
   "uncertainty": "The source does not establish current product availability or a named project’s physical grid supply.",
   "funding_interests": "EPA is the issuing agency. No separate external funding for the selected explanation was established.",
   "reuse_terms": null,
   "checked_on": "2026-10-31",
   "related_question": "What does annual matching establish compared with hourly/regional matching?",
   "cannot_establish": "A named PPA’s performance, local carbon intensity, congestion, additionality or zero emissions.",
   "licence_url": null,
   "attribution": "Source: U.S. Environmental Protection Agency; minimal independently worded definitions with original link; no endorsement.",
   "source_notice": "Source copyright and any applicable third-party rights are retained. Minimal independently worded attributed facts and ordinary unframed links only. No copied passages, figures, tables, model inputs, images, databases or broad source-use grant; no endorsement. No open licence is asserted unless separately identified for the exact component.",
   "source_updated_on": "2025-12-12",
   "page_url": "https://computefinder.net/research/epa-hourly-electricity-matching-guidance"
  },
  {
   "slug": "ukef-employment-measurement-2024-2025",
   "title": "UK Export Finance: Economic impacts of our support 2024 to 2025",
   "publisher": "UK Export Finance",
   "original_url": "https://www.gov.uk/government/publications/uk-export-finance-economic-impacts-of-our-support-2024-to-2025/uk-export-finance-economic-impacts-of-our-support-2024-to-2025",
   "publication_date": "2025-07-17",
   "data_period": "Report period 2024 to 2025; selected employment-method definitions can concern support across periods.",
   "scope": "Sections 5 and 6.2 only: how estimated supported employment is measured.",
   "method": "Government impact-model report; this account examines unit definitions without reproducing outputs or independently replicating the model.",
   "evidence_type": "modelled",
   "assumptions": "Working-hours standardisation and the time over which support is counted affect the employment measure.",
   "uncertainty": "Supported is not necessarily newly created or realised employment. No data-centre result is established.",
   "funding_interests": "UKEF is the government issuer reporting on its own support; this does not independently validate its estimates.",
   "reuse_terms": "Crown copyright 2025; selected government methodological content is covered by the publication’s express OGL v3.0 notice, except identified third-party material. Minimal original account only.",
   "checked_on": "2026-10-31",
   "related_question": "How do FTEs, headcount and job-years differ when employment support is reported?",
   "cannot_establish": "Actual hiring, a permanent-post conversion, data-centre construction employment or a transferable local multiplier.",
   "licence_url": "https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
   "attribution": "UK Export Finance, Economic impacts of our support 2024 to 2025, published 17 July 2025; source/licence links retained; original shortened account, no endorsement.",
   "source_notice": "Crown copyright 2025, UK Export Finance. The government publication expressly states OGL v3.0 except identified third-party material. Minimal original attributed methodological facts and ordinary links only; no numerical results, worked examples, figures, tables, model inputs or third-party content copied. No endorsement or data-centre employment inference.",
   "source_updated_on": null,
   "page_url": "https://computefinder.net/research/ukef-employment-measurement-2024-2025"
  },
  {
   "slug": "mhclg-employment-appraisal-guidance",
   "title": "The MHCLG Appraisal Guide: employment-method scope",
   "publisher": "Ministry of Housing, Communities and Local Government",
   "original_url": "https://www.gov.uk/government/publications/the-mhclg-appraisal-guide/the-mhclg-appraisal-guide",
   "publication_date": null,
   "data_period": "England-focused appraisal guidance; selected paragraphs are not an observed project dataset.",
   "scope": "Employment paragraphs 6.22 to 6.25: local/national effects, additionality and locally appropriate multipliers.",
   "method": "Government appraisal framework. Its illustrative examples and tables are not imported or treated as empirical project results.",
   "evidence_type": "guidance",
   "assumptions": "The counterfactual, location and target group affect an employment appraisal.",
   "uncertainty": "These paragraphs do not define construction job-years or verify any data-centre forecast.",
   "funding_interests": "MHCLG is the government guidance issuer. Separate funding of these selected paragraphs was not established.",
   "reuse_terms": "Crown copyright 2026; express OGL v3.0 government guidance component except identified third-party material. Original short account with attribution/source/licence links only.",
   "checked_on": "2026-10-31",
   "related_question": "Which boundaries matter before calling estimated jobs net additional local employment?",
   "cannot_establish": "A particular project’s staff count, jobs realised, FTE conversion or model multiplier.",
   "licence_url": "https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
   "attribution": "Ministry of Housing, Communities and Local Government, The MHCLG Appraisal Guide; Crown 2026/OGL v3.0; original shortened account, no endorsement.",
   "source_notice": "Crown copyright 2026, Ministry of Housing, Communities and Local Government. The HTML publication expressly states OGL v3.0 except identified third-party content. Original brief account of employment-method guidance only; no illustrations, model tables or third-party content. No endorsement.",
   "source_updated_on": "2026-02-18",
   "page_url": "https://computefinder.net/research/mhclg-employment-appraisal-guidance"
  },
  {
   "slug": "jrc-eu-digital-infrastructure-energy-2022",
   "title": "Energy Consumption in Data Centres and Broadband Communication Networks in the EU",
   "publisher": "European Commission Joint Research Centre",
   "original_url": "https://publications.jrc.ec.europa.eu/repository/handle/JRC135926",
   "publication_date": "2024-02-16",
   "data_period": "2022 estimates; source inputs include earlier years.",
   "scope": "EU-27 data-centre and telecommunications-network electricity use, treated separately.",
   "method": "Literature and public data feed a spreadsheet model: national estimates where available, IT capacity or floorspace assumptions elsewhere, and economic/digital indicators for gaps.",
   "evidence_type": "modelled",
   "assumptions": "Utilisation, PUE, power density, coverage adjustments and historical growth; lower and upper estimates vary selected assumptions.",
   "uncertainty": "Most national data-centre estimates are modelled; small-centre counts and installed capacity are uncertain.",
   "funding_interests": "European Commission JRC authorship. Separate project funding and conflicts were not identified in the reviewed front matter.",
   "reuse_terms": "The report grants CC BY 4.0 with attribution and indicated changes; non-EU third-party material is excluded. Original summary and links only; no charts, tables or underlying inputs.",
   "checked_on": "2026-10-31",
   "related_question": "How was EU electricity use estimated when national data were incomplete?",
   "cannot_establish": "Does not establish current demand, site performance, grid-queue positions, connection rights or available compute; not a forecast.",
   "licence_url": "https://creativecommons.org/licenses/by/4.0/",
   "attribution": "European Commission, Joint Research Centre, Kamiya, G. and Bertoldi, P. (2024), Energy Consumption in Data Centres and Broadband Communication Networks in the EU, Publications Office of the European Union, DOI10.2760/706491, JRC135926. Licence: CC BY4.0.",
   "source_notice": "CC BY4.0 applies to the report unless otherwise noted. Non-EU third-party material retains its own rights. No underlying proprietary dataset, figure, photograph, logo or map is imported or relicensed. ComputeFinder provides an independently worded summary; no charts, tables, report passages or underlying inputs are reproduced.",
   "page_url": "https://computefinder.net/research/jrc-eu-digital-infrastructure-energy-2022"
  }
 ]
}