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REVIEW 3 major objections 5 minor 47 references

Modelling hydrogen integration in energy system models: Best practices for policy insights

T0 review · 3 major / 5 minor · reviewed 2026-08-10 · deepseek-v4-flash

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Pith's one-line read A review of eleven national energy-system models finds that hydrogen is typically represented through a simplified but complete supply-chain view, and derives best-practice lessons for policy modelling.

desk verdict Useful hydrogen modeling review with a few citation gaps and a mildly overstated 'most models' claim; the stress-test's 3-of-8 count is itself wrong. read the letter →

arxiv 2502.05183 v2 pith:3N4UB6ZI submitted 2025-01-21 physics.soc-ph cs.CEmath.OC

Muhammad Maladoh Bah , Sheng Wang , Mohsen Kia , Andrew Keane , Terence O'Donnell This is my paper · ORCID
classification physics.soc-phcs.CEmath.OC
keywords energysystemmodelshydrogensupplychainpolicymodellingnationalstrategiesstoragetransportproductionmodelreview
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

To see how national planners actually handle hydrogen, the paper reviews eleven energy-system models that have informed national hydrogen strategies. It argues that the established practice is a deliberately simplified representation that still touches every stage of the hydrogen supply chain—production, storage, transport, trade, demand, and policy. The authors present this simplification as a sensible trade-off between analytical accuracy and computational cost, not as a deficiency. The review's value is a set of practical suggestions—add more production routes and carriers, richer operating details, both short- and long-duration storage, import/export parameterisation, and policy mechanisms—that analysts can use when building or improving national models.

What carries the argument

The machinery is the review's two-layer selection plus a seven-part comparison grid. Layer one starts from the 43 countries with published hydrogen strategies and traces each strategy to its underlying modelling framework; layer two adds candidate models from six earlier hydrogen-modelling reviews, giving eleven models. The comparison grid—production, storage, transportation, trade, demand, spatial/temporal resolution, and policy—is the analytical engine: it converts heterogeneous documentation into a structured record of what each model includes or omits, and those omissions drive the paper's suggestions.

What would settle it

A reproducible audit of the full set of models referenced in the 43 national hydrogen strategies—including those the review excluded for missing documentation or language reasons—that found most such models use dedicated high-fidelity hydrogen modules for production, storage, and transport would falsify the claim that simplified representation is the norm.

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Extended reading notes

Core claim

On its own terms, the paper's central discovery is a pattern: among the eleven models, the common choice is a simplified hydrogen module that covers each supply-chain leg at a coarse but usable level. Production is usually limited to steam methane reforming and electrolysis, storage is mostly gaseous and underground, transport is mostly pipelines (often repurposed gas pipelines), demand is disaggregated by sector, and some form of policy support—tax credits, subsidies, or policy scenarios—is included in most models. The paper frames this as striking a balance between accuracy and preserving computational resources. From the gaps in these representations, it derives best-practice suggestions, including broader production and carrier options, higher-resolution operational features, storage mechanisms ranging from linepack to salt caverns, coupled domestic-international trade modelling, and explicit representation of region-specific support schemes.

Load-bearing premise

The load-bearing premise is that the eleven selected models are representative of the national energy-system models actually used for hydrogen policy insight, since a selection biased by documentation availability or language barriers would undermine the review's generalisations.

Editorial extensions

If this is right

  • If the simplified-representation pattern holds, national planners can obtain policy-relevant hydrogen insight from integrated energy-system models without building separate high-fidelity hydrogen tools for every supply-chain stage.
  • Adding production routes beyond SMR and electrolysis—such as ATR, gasification, and biomass—together with hydrogen carriers like ammonia and methanol, could reveal cost-optimal or nationally better-suited options that current models miss.
  • Representing both short-duration storage (linepack, above-ground tanks) and seasonal storage (salt caverns, depleted fields) is needed to capture hydrogen's flexibility value; most reviewed models cover only the underground, long-duration end.
  • Because most reviewed models already include some policy representation, the practical bottleneck for policy modelling lies in the accuracy of the underlying supply-chain detail rather than in the absence of policy variables.
  • Hydrogen trade should be parameterised together with domestic production—via import/export volumes, prices, and transport costs—rather than treated as a fixed exogenous supply, since current national models rarely couple the two.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • One testable extension of the paper's result: use its seven-element grid as a shared rubric to audit models outside the selected eleven; if the same coarse-production, pipeline-heavy pattern appears, the 'simplified but complete' description becomes a stronger description of the field.
  • The suggestion to embed operational detail implies a modular architecture that the paper does not spell out: keep the long-term capacity-expansion model, but attach a separate unit-commitment or dispatch module only where hydrogen interacts with short-term renewable variability.
  • The paper's policy finding implies that hydrogen policy modelling is less immature than often assumed; future work could shift from 'should models include policy?' to 'which policy instruments are represented with enough fidelity to distinguish contracts-for-difference from tax credits?'
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. This paper reviews how hydrogen is represented in eleven national energy system models, drawing on country hydrogen strategies and six prior review papers. It compares the models across hydrogen production, storage, transportation, trade, demand, spatial and temporal resolution, and policy representation, and it proposes best-practice modeling suggestions for each supply-chain stage. The central claim is that existing models usually adopt a simplified representation of the hydrogen supply chain, and the paper concludes that most models incorporate some form of hydrogen policy.

Significance. The paper is a useful and readable synthesis of model documentation, and its supply-chain-oriented suggestions are practical for energy analysts building or extending national hydrogen models. Its multi-layered selection method, starting from published national hydrogen strategies, is a reasonable way to identify policy-relevant models, and the comparison tables (especially Table 7 on transport and Table 8 on demand) condense information that is otherwise scattered across model documentation. The paper also explicitly acknowledges its main limitation, namely the restricted model set. However, the value of the review is weakened by two substantial presentational issues: the conclusion that 'most models' represent hydrogen policies is not supported by the paper's own Table 9, and Table 4 cites several sources that are absent from the reference list. These issues are local and fixable, so the contribution can be made sound with revision.

major comments (3)
  1. [Section 6 and Table 9] The conclusion that 'most models factor in some variant of hydrogen policies' is contradicted by Table 9. Counting the explicit entries, only Balmorel, PRIMES, the IEA GEC Model, and NEMS are marked 'Yes'; EnergyPLAN and HDSAM are 'No'; PyPSA and the Canada EFMS are 'Not stated'; and TIMES is noted as country dependent. That is at most four affirmative entries out of eight listed models, which is not 'most,' and 'Not stated' entries cannot be taken as evidence of policy coverage. This overstatement matters because the abstract advertises coverage of hydrogen policies and Section 5.6 derives modeling suggestions from the premise that policy mechanisms are typically included. Please revise the claim to reflect the actual inventory, and qualify the policy suggestions accordingly.
  2. [Table 4 and reference list] Table 4 cites Hoffmann (2024), Pedersen (2021), Usman (2022), and Argonne (2007) as sources, but none of these entries appears in the reference list. This makes the storage-modeling comparison in Table 4 unverifiable as currently written. The same table also attributes storage modeling features to specific models on the basis of these missing references, so the authors should either add the full citations or replace them with verifiable sources for each model.
  3. [Section 4.6 and Table 8] The text states that 'most of the reviewed models adopt higher temporal resolutions (i.e., hourly)', but Table 8 reports 'Not stated' for the Canada EFMS and PRIMES, a blank for TIMES, and 'Seasonal' or one-day hourly for NEMS and HDSAM. The affirmative entries are Balmorel, EnergyPLAN, HDSAM (hourly for one day), and the IEA GEC Model, which does not clearly establish a majority across the eleven models. This is a secondary instance of the same overreach as the policy claim; please either rephrase the generalization or provide a more detailed breakdown of temporal resolutions per model.
minor comments (5)
  1. [Table 8] The TIMES row in Table 8 is empty instead of being completed with 'country dependent' entries or an explicit 'not stated' marker, which would be consistent with the note in Table 9.
  2. [Section 4.1.6] The ammonia synthesis list jumps from '(2)' to '(4)' in the numbering; the cooling and separation step should be '(3)'.
  3. [Section 4.7] The sentence 'Most of the reviewed models’ factor in hydrogen policies' contains a grammatical error: it should read 'Most of the reviewed models factor in hydrogen policies' or similar.
  4. [Section 4.2.2] The subsection on carbon storage is largely background material and is not tied to the reviewed models; consider condensing it and linking it to the CCS discussion in Section 4.1.2.
  5. [Table 1 and Section 4] The N-ZIP model appears in Table 1 and is discussed in the production section, but it is absent from the comparative tables in Sections 4.2, 4.3, 4.5, and 4.7; please clarify why it is excluded from those comparisons.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the paper is a descriptive review whose recommendations are synthesized from externally documented model features; no fitted input is renamed as a prediction and no self-citation chain is load-bearing.

full rationale

This paper is a literature and model review rather than a derivation or quantitative modeling study. It selects eleven models using published national hydrogen strategies and six prior review papers (Section 3), then compiles reported features across production, storage, transport, trade, demand, and policies (Section 4), and finally proposes best practices (Section 5). No quantity is fitted to data and then relabeled as a prediction, and no result is obtained by substituting a definition for itself. The central observation that existing models often adopt simplified hydrogen representations is an inductive summary of the surveyed documentation, and the policy suggestions are explicitly framed as recommendations grounded in the Section 4 inventory rather than as outputs derived from those models. The skeptical reading that Table 9 supports only 3 of 8 affirmative policy-representation entries concerns the accuracy of the claim that 'most models factor in some variant of hydrogen policies' relative to the paper's own table; this is an evidentiary or correctness issue, not circularity, because the review's argument does not assume that claim as a premise needed to produce its conclusions. Similarly, Table 4's citation of Hoffmann 2024, Pedersen 2021, and Usman 2022 without corresponding reference-list entries is a verifiability defect, not a circular-reasoning defect. The conclusion's stated limitation that the review design restricts the assessment to a specific set of models is an acknowledged scope constraint and does not conceal an imported assumption. Self-citations are not load-bearing: the paper relies on external model documentation and prior independent reviews, and no author-specific uniqueness theorem or ansatz is invoked to force a choice. Therefore the appropriate circularity score is 0.

Assumptions & free parameters 0 free parameters · 2 assumptions · 0 invented entities

No free parameters or invented entities are involved. The review's claims rest on the representativeness of the selected models and the accuracy of secondary documentation.

assumptions (2)
  • domain assumption Models selected in Section 3 are representative of national energy system models used for hydrogen policy.
    The review generalizes from eleven models to national practices; selection depended on published strategies, documentation access, and language feasibility, as acknowledged in Section 3 and Section 6.
  • domain assumption Secondary sources, including prior reviews, model documentation, and techno-economic reports, accurately describe the reviewed models.
    The paper does not run or validate the models; claims in Tables 4, 7, 8 and cost figures rely on cited literature, some of which is missing from the reference list.

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Cite this review

Pith. "Pith review of Modelling hydrogen integration in energy system models: Best practices for policy insights." pith.science (2026). https://pith.science/paper/3N4UB6ZI

@misc{pith2026250205183,
  author       = {Pith},
  title        = {Pith review of: Modelling hydrogen integration in energy system models: Best practices for policy insights},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/3N4UB6ZI}},
  note         = {Machine review of arXiv:2502.05183}
}
read the original abstract

The rapid emergence of hydrogen in long-term energy strategies requires a broad understanding on how hydrogen is currently modelled in national energy system models. This study provides a review on hydrogen representation within selected energy system models that are tailored towards providing policy insights. The paper adopts a multi-layered review approach and selects eleven notable models for the review. The review covers hydrogen production, storage, transportation, trade, demand, modeling strategies, and hydrogen policies. The review suggests existing models would often opt for a simplified representation that can capture each stage of the hydrogen supply chain. This approach allows models to strike a balance between accuracy and preserving computational resources. The paper provides several suggestions for modeling hydrogen in national energy system models.

Discussion (0). Continue with ORCID to comment.

Reference graph

Works this paper leans on

47 extracted references · 38 canonical work pages

  1. [2]

    https://doi.org/10.1088/2516-1083/abab68 Blanco, H., Leaver, J., Dodds, P.E., Dickinson, R., García-Gusano, D., Diego, I., Lind, A., Wang, C., Danebergs, J., Baumann, M.,

    work page doi:10.1088/2516-1083/abab68

  2. [13]

    IFE/E-2021/005)

    Documentation of IFE-TIMES-Norway v2 (No. IFE/E-2021/005). Institute for Energy Technology. DeCarolis, J., Daly, H., Dodds, P., Keppo, I., Li, F., McDowall, W., Pye, S., Strachan, N., Trutnevyte, E., Usher, W., Winning, M., Yeh, S., Zeyringer, M.,

    work page 2021

  3. [14]

    https://doi.org/10.3390/en14185917 Balyk, O., Andersen, K., Dockweiler, S., Gargiulo, M., Karlsson, K., Næraa, R., Petrović, S., Tattini, J., Termansen, L.B., Venturini, G.,

    work page doi:10.3390/en14185917

  4. [15]

    Formalizing best practice for energy system optimization modelling. Appl. Energy 194, 184–198. http://dx.doi.org/10.1016/j.apenergy.2017.03.001 DECHEMA, acatech,

    doi:10.1016/j.apenergy.2017.03.001 2017

  5. [16]

    E3-Modelling

    PRIMES Model Version 2018: Detailed model description. E3-Modelling. Ea Energianalyse,

    work page 2018

  6. [17]

    Hydrogen 3, 402–417

    Green Hydrogen Blends with Natural Gas and Its Impact on the Gas Network. Hydrogen 3, 402–417. https://doi.org/10.3390/hydrogen3040025 Ekhtiari, A., Flynn, D., Syron, E.,

    work page doi:10.3390/hydrogen3040025

  7. [18]

    https://doi.org/10.3390/en13226047 Element Energy,

    work page doi:10.3390/en13226047

  8. [20]

    A critical review on the current technologies for the generation, storage, and transportation of hydrogen. Int. J. Hydrog. Energy 47, 13771–13802. https://doi.org/10.1016/j.ijhydene.2022.02.112 Frieden, F., Leker, J.,

    work page doi:10.1016/j.ijhydene.2022.02.112 2022

Show all 47 references
  1. [21]

    Future costs of hydrogen: a quantitative review. Sustain. Energy Fuels 8, 1806–1822. https://doi.org/10.1039/D4SE00137K Gaeta, M.,

    doi

  2. [23]

    The role of hydrogen in low carbon energy futures–A review of existing perspectives. Renew. Sustain. Energy Rev. 82, 3027–3045. https://doi.org/10.1016/j.rser.2017.10.034 Hosseini, S.E.,

    2017 doi

  3. [24]

    Hydrogen UK,

    Hydrogen Insights 2023: The state of the global hydrogen economy, with a deep dive into renewable hydrogen cost evolution. Hydrogen UK,

    2023

  4. [25]

    IEA, 2023b

    International Energy Agency (IEA), Paris, France. IEA, 2023b. Global Energy and Climate Model. International Energy Agency (IEA), Paris, France. IEA, 2021a. Net Zero by 2050: A Roadmap for the Global Energy Sector. International Energy Agency (IEA). IEA, 2021b. Ammonia technol...

  5. [26]

    International Renewable Energy Agency (IRENA), Masdar City, UAE

    World Energy Transitions Outlook 2023: 1.5°C Pathway. International Renewable Energy Agency (IRENA), Masdar City, UAE. IRENA,

    2023

  6. [27]

    Hydrogen infrastructure modeling in macro-energy systems models - Lessons learned, best practices, and potential next steps (workshop insights). Int. J. Hydrog. Energy 70, 629–634. https://doi.org/10.1016/j.ijhydene.2024.05.137 Li, L., Manier, H., Manier, M.-A.,

    2024 doi

  7. [28]

    Hydrogen supply chain network design: An optimization- oriented review. Renew. Sustain. Energy Rev. 103, 342–360. https://doi.org/10.1016/j.rser.2018.12.060 Lugovoy, O.,

    2018 doi

  8. [29]

    Review of modelling approaches used in the HSC context for the UK. Int. J. Hydrog. Energy 42, 24927–24938. https://doi.org/10.1016/j.ijhydene.2017.04.303 Matteo, N.,

    2017 doi

  9. [30]

    McKinsey & Company,

    Global Hydrogen Flows - 2023 Update. McKinsey & Company,

    2023

  10. [31]

    Energy Rep

    A review on underground hydrogen storage: Insight into geological sites, influencing factors and future outlook. Energy Rep. 8, 461–499. https://doi.org/10.1016/j.egyr.2021.12.002 Mulky, L., Srivastava, S., Lakshmi, T., Sandadi, E.R., Grour, S., Thomas, N.A., Priya, S.S., Sudh...

    2021 doi

  11. [33]

    https://doi.org/10.1016/j.jksus.2020.101282 Gouveia, J.P., Dias, L., Seixas, J.,

    2020

  12. [34]

    Joule 7, 1793–1817

    The potential role of a hydrogen network in Europe. Joule 7, 1793–1817. https://doi.org/10.1016/j.joule.2023.06.016 Nicoli, M.,

    2023 doi

  13. [35]

    Advances in hydrogen storage materials: harnessing innovative technology, from machine learning to computational chemistry, for energy storage solutions. Int. J. Hydrog. Energy 67, 1270–1294. https://doi.org/10.1016/j.ijhydene.2024.03.223 Oxford Institute for Energy Studies,

    doi

  14. [36]

    Hydrogen carriers: Production, transmission, decomposition, and storage. Int. J. Hydrog. Energy 46, 24169–24189. https://doi.org/10.1016/j.ijhydene.2021.05.002 Patonia, A., Poudineh, R.,

    2021 doi

  15. [37]

    National Renewable Energy Laboratory (NREL)

    H2A Hydrogen Production Model: Version 3.2018 User Guide. National Renewable Energy Laboratory (NREL). Raj, A., Larsson, I.A.S., Ljung, A.-L., Forslund, T., Andersson, R., Sundström, J., Lundström, T.S.,

    2018

  16. [38]

    Evaluating hydrogen gas transport in pipelines: Current state of numerical and experimental methodologies. Int. J. Hydrog. Energy 67, 136–149. https://doi.org/10.1016/j.ijhydene.2024.04.140 Ravn, H.,

    2024 doi

  17. [39]

    Techno-economic analysis of conventional and advanced high-pressure tube trailer configurations for compressed hydrogen gas transportation and refueling. Int. J. Hydrog. Energy 43, 4428–4438. https://doi.org/10.1016/j.ijhydene.2018.01.049 Richard, L.,

    doi

  18. [40]

    A review of hydrogen production and supply chain modeling and optimization. Int. J. Hydrog. Energy 48, 13731–13755. https://doi.org/10.1016/j.ijhydene.2022.12.242 Riester, C.M., García, G., Alayo, N., Tarancón, A., Santos, D.M.F., Torrell, M.,

    2022 doi

  19. [41]

    Fuels 3, 392–407

    Business Model Development for a High-Temperature (Co-)Electrolyser System. Fuels 3, 392–407. https://doi.org/10.3390/fuels3030025 SARI/EI,

    doi

  20. [42]

    SG/2018/18)

    Climate Change Plan: The Third Report on Proposals and Policies 2018- 2032 Technical Annex (No. SG/2018/18). The Scottish Government. 43 Song, S., Lin, H., Sherman, P., Yang, X., Nielsen, C.P., Chen, X., McElroy, M.B.,

    2018

  21. [43]

    URL https://www.statista.com/statistics/1364669/forecast- global-hydrogen-production-share-by-technology/ VITO,

    Forecast production share of hydrogen worldwide in 2050, by technology [WWW Document]. URL https://www.statista.com/statistics/1364669/forecast- global-hydrogen-production-share-by-technology/ VITO,

  22. [44]

    Research on the dynamic characteristics of natural gas pipeline network with hydrogen injection considering line-pack influence. Int. J. Hydrog. Energy 48, 25469–25486. https://doi.org/10.1016/j.ijhydene.2023.03.298 Zhang, T., Qadrdan, M., Wu, J., Couraud, B., Stringer, M., Wa...

    2023 doi

  23. [167]

    https://doi.org/10.1016/j.rser.2022.112698 Bolat, P., Thiel, C.,

    2022

  24. [208]

    https://doi.org/10.1016/j.rser.2024.114964 Züttel, A.,

    2024

  25. [235]

    https://doi.org/10.1016/j.compstruct.2019.111809 Daly, H.E., Fais, B.,

    2019

  26. [325]

    https://doi.org/10.1016/j.matchemphys.2024.129710 Netherlands 2030,

    2024

  27. [2003]

    Materials for hydrogen storage. Mater. Today 6, 24–33. https://doi.org/10.1016/S1369-7021(03)00922-2

    doi

  28. [2004]

    Naturwissenschaften 91, 157–172

    Hydrogen storage methods. Naturwissenschaften 91, 157–172. https://doi.org/10.1007/s00114-004-0516-x Züttel, A.,

    doi

  29. [2012]

    Models, methods and approaches for the planning and design of the future hydrogen supply chain. Int. J. Hydrog. Energy 37, 5318–5327. https://doi.org/doi:10.1016/j.ijhydene.2011.08.041 Daghia, F., Baranger, E., Tran, D.T., Pichon, P.,

    2011 doi

  30. [2014]

    Part 1: Developing pathways

    Hydrogen supply chain architecture for bottom-up energy systems models. Part 1: Developing pathways. Int. J. Hydrog. Energy 39, 8881–8897. http://dx.doi.org/10.1016/j.ijhydene.2014.03.176 Burke, A., Ogden, J., Fulton, L., Cerniauskas, S.,

    2014 doi

  31. [2017]

    Integrating short term variations of the power system into integrated energy system models: A methodological review. Renew. Sustain. Energy Rev. 76, 839–856. http://dx.doi.org/10.1016/j.rser.2017.03.090 Cosmi, C., Leo, S.D., Loperte, S., Macchiato, M., Pietrapertosa, F., Salvi...

    2017 doi

  32. [2018]

    Liquid organic hydrogen carriers for transportation and storing of renewable energy – Review and discussion. J. Power Sources 396, 803–823. https://doi.org/10.1016/j.jpowsour.2018.04.011 AFRY ,

    2018 doi

  33. [2019]

    Energy Stud

    TIMES-DK: Technology-rich multi-sectoral optimisation model of the Danish energy system. Energy Stud. Rev. 23, 13–22. https://doi.org/10.1016/j.esr.2018.11.003 Balyk, O., Glynn, J., Aryanpur, V ., Gaur, A., McGuire, J., Smith, A., Yue, X., Daly, H.,

    2018 doi

  34. [2021]

    The economics of bioenergy with carbon capture and storage (BECCS) deployment in a 1.5 °C or 2 °C world. Glob. Environ. Change 68, 102262. https://doi.org/10.1016/j.gloenvcha.2021.102262 Faye, O., Szpunar, J., Eduok, U.,

    2021

  35. [2022]

    TIM: modelling pathways to meet Ireland’s long-term energy system challenges with the TIMES- Ireland Model (v1.0). Geosci. Model Dev. 15, 4991–5019. https://doi.org/10.5194/gmd-15- 4991-2022 Bistline, J., Cole, W., Damato, G., DeCarolis, J., Frazier, W., Linga, V ., Marcy, C.,...

    2022 doi

  36. [2023]

    Carbon Resour

    Hydrogen storage by liquid organic hydrogen carriers: Catalyst, renewable carrier, and technology – A review. Carbon Resour. Convers. 6, 334–351. https://doi.org/10.1016/j.crcon.2023.03.007 Collins, S., Deane, J.P., Poncelet, K., Panos, E., Pietzcker, R.C., Ó Gallachóir, B.P.,

    2023 doi

  37. [2024]

    Canada’s Energy Future 2023 - Modeling Methods [WWW Document]. Can. Energy Regul. URL https://www.cer-rec.gc.ca/en/data-analysis/canada-energy-future/2023-modeling- methods/ (accessed 7.24.24). Chu, C., Wu, K., Luo, B., Cao, Q., Zhang, H.,

    2023

  38. [2025]

    Energy Reform, Dublin, Ireland

    SPINE H2-IRL 2023-202 Derivable 5.3 Final Report. Energy Reform, Dublin, Ireland. Fajardy, M., Morris, J., Gurgel, A., Herzog, H., Mac Dowell, N., Paltsev, S.,

    2023

  39. [6953]

    https://doi.org/10.1038/s41467-021-27214-7 Statista Research Department,

    doi

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