Summary
This page gives a criterion-by-criterion overview of all evaluation criteria, combining the scientific justifications with the computed threshold values.
Historical Vetting
Historical vetting criteria check for the alignment of scenarios with historical data. Scenarios are marked as inconsistent if they do not match reported historical real-world estimates for time periods in the past. Misalignment of a scenario means that the scenario is or has become impossible, which can often be the outcome of outdatedness of older scenarios.
Possible evaluation outcomes:
ok— Consistent with historical datafailed— Inconsistent with historical datainsufficient reporting— Variable not reported
Emissions|CO2|Energy and Industrial Processes
Why this criterion? This criterion flags scenarios that report CO₂ emissions in the energy supply, energy demand, and industry sectors that are inconsistent with historical values.
This is a concern because the underlying modelling likely makes false assumptions on the remaining GHG emissions budget and the mitigation effort required to reach net-zero emissions.
Why this threshold? Historical values are provided by the Community Emissions Data System (Hoesly, 2025).
Based on this historical data, we assume the following global threshold for years 2010, 2015, 2020 and 2025:
• Whole world: ±20% deviation.
Note that these ranges not only give models some leeway to deviate, but also account for uncertainty in the underlying data sources.
The threshold for 2025 is derived using the 2023 value and the 2022–2023 growth rate.
To account for the COVID-19 shock, the threshold for 2020 is derived using both the reported value in 2020 and the value averaged over the period Jan 2018 until Dec 2022, taking whichever is more permissive for the scenario in question.
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Final Energy
Why this criterion? This criterion flags scenarios that report final energy demand that is inconsistent with historical values.
This is a concern because the underlying modelling likely makes false assumptions on the mitigation effort required to reach net-zero emissions.
Why this threshold? Historical values are provided by the International Energy Agency (IEA, 2025), where we assume that the Final Energy variable is given by the "total final consumption" reported by the IEA.
Note that final energy includes non-energy use.
Based on this historical data, we assume the following global threshold for years 2010, 2015, 2020 and 2025:
• Whole world: ±20% deviation.
Note that these ranges not only give models some leeway to deviate, but also account for uncertainty in the underlying data sources.
The threshold for 2025 is derived using the 2023 value and the 2021–2023 growth rate.
To account for the COVID-19 shock, the threshold for 2020 is derived using both the reported value in 2020 and the value averaged over the period Jan 2018 until Dec 2022, taking whichever is more permissive for the scenario in question.
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Primary Energy|Coal
Why this criterion? This criterion flags scenarios that report coal primary energy production that is inconsistent with historical values.
This is a concern because the underlying modelling likely makes false assumptions on the mitigation effort required to reach net-zero emissions.
Why this threshold? Historical values are provided by the International Energy Agency (IEA, 2025), where we assume that Primary Energy variables are given by the "total energy supply" reported by the IEA.
Based on this historical data, we assume the following global threshold for years 2010, 2015, 2020 and 2025:
• Whole world: ±20% deviation.
Note that these ranges not only give models some leeway to deviate, but also account for uncertainty in the underlying data sources.
The threshold for 2025 is derived using the 2023 value and the 2021–2023 growth rate.
To account for the COVID-19 shock, the threshold for 2020 is derived using both the reported value in 2020 and the value averaged over the period Jan 2018 until Dec 2022, taking whichever is more permissive for the scenario in question.
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Primary Energy|Gas
Why this criterion? This criterion flags scenarios that report gas primary energy production that is inconsistent with historical values.
This is a concern because the underlying modelling likely makes false assumptions on the mitigation effort required to reach net-zero emissions.
Why this threshold? Historical values are provided by the International Energy Agency (IEA, 2025), where we assume that Primary Energy variables are given by the "total energy supply" reported by the IEA.
Based on this historical data, we assume the following global threshold for years 2010, 2015, 2020 and 2025:
• Whole world: ±20% deviation.
Note that these ranges not only give models some leeway to deviate, but also account for uncertainty in the underlying data sources.
The threshold for 2025 is derived using the 2023 value and the 2021–2023 growth rate.
To account for the COVID-19 shock, the threshold for 2020 is derived using both the reported value in 2020 and the value averaged over the period Jan 2018 until Dec 2022, taking whichever is more permissive for the scenario in question.
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Primary Energy|Nuclear
Why this criterion? This criterion flags scenarios that report nuclear primary energy production that is inconsistent with historical values.
This is a concern because the underlying modelling likely makes false assumptions on the mitigation effort required to reach net-zero emissions.
Why this threshold? Historical values are provided by the International Energy Agency (IEA, 2025), where we assume that Primary Energy variables are given by the "total energy supply" reported by the IEA.
Based on this historical data, we assume the following global threshold for years 2010, 2015, 2020 and 2025:
• Whole world: ±20% deviation.
Note that these ranges not only give models some leeway to deviate, but also account for uncertainty in the underlying data sources.
The threshold for 2025 is derived using the 2023 value and the 2021–2023 growth rate.
To account for the COVID-19 shock, the threshold for 2020 is derived using both the reported value in 2020 and the value averaged over the period Jan 2018 until Dec 2022, taking whichever is more permissive for the scenario in question.
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Primary Energy|Oil
Why this criterion? This criterion flags scenarios that report oil primary energy production that is inconsistent with historical values.
This is a concern because the underlying modelling likely makes false assumptions on the mitigation effort required to reach net-zero emissions.
Why this threshold? Historical values are provided by the International Energy Agency (IEA, 2025), where we assume that Primary Energy variables are given by the "total energy supply" reported by the IEA.
Based on this historical data, we assume the following global threshold for years 2010, 2015, 2020 and 2025:
• Whole world: ±20% deviation.
Note that these ranges not only give models some leeway to deviate, but also account for uncertainty in the underlying data sources.
The threshold for 2025 is derived using the 2023 value and the 2021–2023 growth rate.
To account for the COVID-19 shock, the threshold for 2020 is derived using both the reported value in 2020 and the value averaged over the period Jan 2018 until Dec 2022, taking whichever is more permissive for the scenario in question.
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Feasibility Concern
Feasibility criteria check for the alignment of scenarios with near-term trends and long-term developments across sectors. In the near future (i.e. next 5 years), scenarios are flagged if they substantially deviate from project announcements and market outlooks. In particular, installment rates are unlikely to exceed announced projects for technologies with long lead times (e.g. hydropower, nuclear power or carbon capture and storage). Moreover, near-term market forecasts for technologies with established markets (e.g. solar PV or wind) provide corridors of installment rates that are unlikely to be subceeded or exceeded. In the longer future (i.e. 2035 and beyond), scenarios are flagged if they report technology growth rates that are inconsistent with general growth expectations. While going above or below these near-term and long-term thresholds is not strictly impossible, those developments would require unconventional implementation and growth rates.
Possible evaluation outcomes:
ok— No feasibility concernsmedium— Moderate feasibility concernshigh— Strong feasibility concernsnot assigned— Variable not reported
Carbon Capture and Storage
Why this criterion? This criterion flags scenarios that assume a deployment of CCS technologies that is inconsistent with near-term projections (2030) or long-term feasibility constraints (2035–2040).
Near-term (2030): near-term upper and lower capacity projections can be derived from existing capacities and from current project announcements and known project lead times. Robust upper projections can be made because projects take at least 5 years to plan and construct and therefore will not be operational by 2030 if not yet announced by today. Robust lower projections can be made based on existing capacities and because retirement rates can reasonably be assumed to be low.
Long-term (2035–2040): CCS involves capturing CO₂ from flue gases and storing it geologically. The required technologies for these activities are highly non-modular and application-specific. Additionally, CCS depends on infrastructure like CO₂ pipeline networks, which still have to be built. Therefore it will likely grow more slowly than modular technologies with some degree of existing infrastructure, such as solar, wind, and batteries.
Why this threshold? Near-term (2030): CCUS projects are tracked and published annually in a database by the IEA (2024).
The projects in the CCUS database are assigned one of the following statuses:
• Operational: in operation in 2024
• Construction: under construction in 2024
• Planned: announced but without final investment decision in 2024. Projects that were decommissioned or suspended are not counted.
Based on the CCUS database, we assume the following thresholds for 2030:
• Lower, high concern: 0.0 Mt CO₂/yr to account for the fact that CCUS is an immature technology.
• Lower, medium concern: 10% less than capacities operational in 2024, as reported by the CCUS database (IEA, 2024).
• Upper, medium concern: 5% more than capacities operational or under construction, plus 1% of planned projects (without final investment decision) in 2024, as reported by the CCUS database (IEA, 2024).
• Upper, high concern: 10% more than all projects operational, under construction, or announced, as reported by the CCUS database (IEA, 2024).
Long-term (2035–2040): Kazlou (2024) derive an upper bound for feasible CCS capacity deployment in 2030 of 370 Mt CO₂/yr and 2040 of 4,300 Mt CO₂/yr (see Table 2 in the work by Kazlou (2024)), which assumes a doubling of existing plans and a 45% failure rate.
Based on this work, we assume the following thresholds:
• Upper, medium concern in 2035: 1,300 Mt CO₂/yr, which is the geometric-mean (constant-growth-rate) interpolation between the reported upper bounds for 2030 (370 Mt CO₂/yr) and 2040 (4,300 Mt CO₂/yr) derived by Kazlou (2024).
• Upper, medium concern in 2040: 4,300 Mt CO₂/yr, which is the reported upper bound derived by Kazlou (2024).
These threshold values all refer to CCS and are applied to the variable Carbon Capture|Geological Storage. However this variable is often underreported, especially in older scenarios. Therefore, the variable Carbon Capture is also assessed using the same threshold values. Note that this may lead to precautious flagging scenarios with more granular reporting of carbon capture. In these scenarios, additional categories such as CO₂ leakage or CO₂ utilization contribute to total carbon capture, which as a result may exceed the corresponding threshold even when geological storage remains below its threshold.
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Hydropower Capacity
Why this criterion? This criterion flags scenarios that assume a deployment of hydropower capacity that is inconsistent with near-term projections.
Near-term upper and lower capacity projections can be derived from existing capacities and from current project announcements and known project lead times. Robust upper projections can be made because projects take at least 5 years to plan and construct and therefore will not be operational by 2030 if not yet announced by today. Robust lower projections can be made based on exisiting capacities and because retirement rates can reasonably be assumed to be low.
Specifically, hydropower plants take 4–7 years to construct (for medium-sized projects) and up to 15 years (for large projects) to plan and construct. Small projects that can be completed within less than 4 years make up less than 3% of all projects planned globally in 2021.
For details on hydropower project lead times, see the Hydropower Special Market Report by the International Energy Agency (IEA, 2021b).
Why this threshold? Data on hydropower plant capacities was published by the IEA (2021a).
The capacity data is published in three categories:
• Operational: in operation in 2021
• Expected: expected to be operational in 2030 under normal conditions.
• Accelerated: expected to be operational in 2030 under accelerated efforts.
Based on this capacity data, we assume the following thresholds for 2030:
• Lower threshold, high concern: 10% less than hydropower capacity (without pumped storage) that was operational in 2021.
• Lower threshold, medium concern: 5% less than hydropower capacity (without pumped storage) that is expected to be operational in 2030 under normal conditions.
• Upper threshold, medium concern: 5% more than hydropower and pumped storage capacity that is expected to be operational in 2030 under accelerated efforts.
• Upper threshold, high concern: 43% more than hydropower capacity (without pumped storage) that is expected to be operational in 2030 under accelerated efforts, plus 10% more than pumped storage capacity that is expected to be operational in 2030 under normal conditions.
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Nuclear Capacity
Why this criterion? This criterion flags scenarios that assume a deployment of nuclear power-plant capacity that is inconsistent with near-term projections.
Near-term upper and lower capacity projections can be derived from existing capacities and from current project announcements and known project lead times. Robust upper projections can be made because projects take at least 5 years to plan and construct and therefore will not be operational by 2030 if not yet announced by today. Robust lower projections can be made based on exisiting capacities and because retirement rates can reasonably be assumed to be low.
Why this threshold? Data on nuclear power plants is published by the International Atomic Energy Agency (IAEA). This includes plant-level data of existing capacities (IAEA, 2024b) and estimates until 2050 (IAEA, 2024a).
The capacity data is published in three categories:
• Operational: in operation in 2024
• Construction: currently under construction
• Retired: inactive capacity that has been retired
Based on this capacity data, we assume the following thresholds for 2030:
• Lower, high concern: 0.0 GW to account for the fact that nuclear energy could, in principle, be phased out quickly, as observed in a few countries (e.g. Germany).
• Lower, medium concern: 15% less than capacities operational in 2024, as reported by the IAEA (2024b).
• Upper, medium concern: 5% more than capacities operational plus 75% of plants under construction in 2024, as reported by the IAEA (2024b).
• Upper, high concern: 10% more than the highest estimate for 2030 (461 GW) published by the IAEA (2024a).
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Onshore Wind Capacity
Why this criterion? This criterion flags scenarios that assume a deployment of on-shore wind capacity that is inconsistent with near-term market outlooks.
This technology is available at scale and has short project lead times, meaning that there are no fundamental obstacles to fast deployment. Its near-term growth can be estimated based on today's installed capacity and near-term market outlooks. While these estimates have their limitations, they can be used to set broad ranges of near-term feasibility.
Why this threshold? Existing capacities in 2024 are reported by the International Renewable Energy Agency (IRENA, 2025). Yearly additions for 2025–2028 are estimated in a market outlook by the GWEC (2024).
The outlook is based on input from regional wind associations, government targets, tender results, announced auction plans, available project pipelines, and input from industry experts.
Based on the existing capacity data and the market outlook, we assume the following thresholds for 2030:
• Lower threshold, high concern: 10% less than capacities operational in 2024, plus 33.75% of additions from the market outlook.
• Lower threshold, medium concern: 5% less than capacities operational in 2024, plus 71.25% of additions from the market outlook.
• Upper threshold, medium concern: 5% more than capacities operational in 2024, plus 157.5% of additions from the market outlook.
• Upper threshold, high concern: 10% more than capacities operational in 2024, plus 220.0% of additions from the market outlook.
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Solar PV Capacity
Why this criterion? This criterion flags scenarios that assume a deployment of solar photovoltaics capacity that is inconsistent with near-term market outlooks.
This technology is available at scale and has short project lead times, meaning that there are no fundamental obstacles to fast deployment. Its near-term growth can be estimated based on today's installed capacity and near-term market outlooks. While these estimates have their limitations, they can be used to set broad ranges of near-term feasibility.
Why this threshold? Existing capacities in 2023 are reported by Ember (2024). Yearly additions for 2024–2030 are estimated in a market outlook by BNEF (2024).
The market outlook data comprises 8 regional categories and a "buffer/unknown" category.
Based on the existing capacity data and the market outlook, we assume the following thresholds for 2030:
• Lower threshold, high concern: 10% less than capacities operational in 2023, plus 33.75% of additions from the market outlook (without buffer/unknown).
• Lower threshold, medium concern: 5% less than capacities operational in 2023, plus 71.25% of additions from the market outlook (without buffer/unknown).
• Upper threshold, medium concern: 5% more than capacities operational in 2023, plus 157.5% of additions from the market outlook (without buffer/unknown).
• Upper threshold, high concern: 10% more than capacities operational in 2023, plus 220.0% of additions from the market outlook (with buffer/unknown).
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Note
Due to reporting inconsistencies in legacy projects, several models reported capacity-values that were far below actual power generation from solar PV, causing an overly restrictive application of this criterion.
To remedy this inconsistency, we implemented an exception in the evaluation workflow for Release v1.0 and v1.1 of the SCI ensemble: any high concern flag was changed to medium if actual power generation from solar PV was above 10.5 EJ/yr in 2030, corresponding to the lowest generation value of scenarios that meet the lower bound of the capacity threshold.
Visit https://github.com/IAMconsortium/scenariocompass/tree/main/scripts/sci_v1.0 for more information.
Wind Capacity
Why this criterion? This criterion flags scenarios that assume a deployment of total wind power capacity (onshore and offshore combined) that is inconsistent with near-term market outlooks.
This technology is available at scale and has short project lead times, meaning that there are no fundamental obstacles to fast deployment. Its near-term growth can be estimated based on today's installed capacity and near-term market outlooks. While these estimates have their limitations, they can be used to set broad ranges of near-term feasibility.
Why this threshold? The same lower bounds as for the onshore wind capacity are applied to total wind capacity, reflecting the assumption that onshore wind alone provides a sufficient lower bound for total (onshore and offshore) deployment.
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Sustainability Concern
Sustainability criteria check for the alignment of scenarios with sustainability targets other than climate-change mitigation. Scenarios are flagged if they report the use of technologies, activities or practices at a level that goes beyond what would be sustainable in those other non-climate ecosystem targets. The thresholds for sustainability criteria are derived from literature focussing on the respective sustainability targets. Misalignment of a scenario does not mean that the scenario is impossible or infeasible, but rather that it is undesirable from a non-climate sustainability perspective.
Possible evaluation outcomes:
ok— No sustainability concernsmedium— Moderate sustainability concernshigh— Strong sustainability concernsnot assigned— Variable not reported
Exceeding Prudent Limit For Geological Carbon Storage
Why this criterion? This criterion flags scenarios that rely on an amount of geological carbon storage that exceeds estimated storage potentials.
This is a concern, because relying on an exceedance of physical storage potentials is unsustainable.
Why this threshold? We use geological carbon storage volumes that exceed prudent technical and sustainability limits as upper bounds on cumulative CCS as quantified by Gidden (2025).
Based on this study, we assume the following global thresholds for cumulative geological carbon storage in the period 2020–2100:
• Upper threshold, high concern: 1,460 Gt CO₂, which was identified as the median of the range by Gidden (2025) when combining spatial risk layers.
• Upper threshold, medium concern: 1,290 Gt CO₂, which was identified as the lower bound of the range by Gidden (2025) when combining spatial risk layers.
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Food Availability
Why this criterion? This criterion flags scenarios that report levels of food availability that are above or below human nutritional needs.
This is a concern, because food availability below nutritional needs would mean hunger and because food availability above nutritional needs would mean high resource use due to overconsumption.
Why this threshold? According to the Food and Agriculture Organization of the United Nations (FAO) (2020), the Minimum Dietary Energy Requirement is 2,100 kcal/cap/day. Meanwhile, the highest historical level of food availability is 4,000 kcal/cap/day.
Based on these values, we assume the following global threshold across all years:
• Upper threshold, medium concern: 5,000 kcal/cap/day
• Lower threshold, medium concern: 2,100 kcal/cap/day
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Unsustainable Bioenergy Use
Why this criterion? This criterion flags scenarios that assume a high usage of bioenergy. Specifically, we here refer to 2nd generation bioenergy crops, crop and forestry residues, municipal solid waste bioenergy and traditional biomass.
Bioenergy can be a drop-in replacement to currently used fossil fuels. When grown in a sustainable fashion, their life-cycle of production and use is GHG neutral. Bio-based energy crops can be grown at low cost and with readily available technologies.
Some decarbonisation scenarios therefore tend to assume a high use of bioenergy. Meanwhile, such a high use of bioenergy can result in (a) growth practices that are no longer GHG neutral in their life cycle (e.g. through deforestation to create more arable land for energy crops) or result in (b) a loss of natural habitats, which creates other sustainability concerns, for instance linked to a loss of biodiversity.
Why this threshold? Creutzig (2014) have derived an upper limit for sustainable biomass use of 100–300 EJ/yr. In the 6th Assessment Report of Working Group 3 of the Intergovernmental Panel on Climate Change (IPCC), a value of 100 EJ/yr is defined as the threshold for the onset of medium concern and 245 EJ/yr a threshold for the onset of high concern (IPCC, 2022). Another study by Deprez (2024) suggests that medium sustainability risks arise at 50 EJ/yr and high risks at 120 EJ/yr.
Based on these studies, we assume the following global thresholds across all years:
• Upper threshold, medium concern: 100 EJ/yr
• Upper threshold, high concern: 245 EJ/yr
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Sources
| Identifier | Bibliographic information | Links |
|---|---|---|
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Felix Creutzig, N. H. Ravindranath, Göran Berndes, Simon Bolwig, Ryan Bright, Francesco Cherubini, Helena Chum, Esteve Corbera, Mark Delucchi, Andre Faaij, Joseph Fargione, Helmut Haberl, Garvin Heath, Oswaldo Lucon, Richard Plevin, Alexander Popp, Carmenza Robledo-Abad, Steven Rose, Pete Smith, Anders Stromman, Sangwon Suh, and Omar Masera. Bioenergy and climate change mitigation: an assessment. GCB Bioenergy, 7(5):916–944, July 2014. | DOI |
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Tsimafei Kazlou, Aleh Cherp, and Jessica Jewell. Feasible deployment of carbon capture and storage and the requirements of climate targets. Nature Climate Change, 14(10):1047–1055, September 2024. | DOI |
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IPCC. Annex III: Scenarios and Modelling Methods. In Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK and New York, NY, USA, 2022. | DOI |
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Alexandra Deprez, Paul Leadley, Kate Dooley, Phil Williamson, Wolfgang Cramer, Jean-Pierre Gattuso, Aleksandar Rankovic, Eliot L. Carlson, and Felix Creutzig. Sustainability limits needed for CO\(_2\) removal. Science, 383(6682):484–486, February 2024. | DOI |
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IEA. Energy Statistics Data Browser. June 2025. | URL |
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Rachel Hoesly, Steven J Smith, Hamza Ahsan, Noah Prime, Patrick O'Rourke, Monica Crippa, Zbigniew Klimont, Diego Guizzardi, Leyang Feng, Colin Harkins, BRIAN MCDONALD, and Shuxiao Wang. CEDS v_2025_03_18 Aggregate Data. March 2025. | DOI |
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IEA. Hydropower Special Market Report: Analysis and Forecast to 2030. 2021b. | URL |
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IAEA. Energy, Electricity and Nuclear Power Estimates for the Period up to 2050. Reference Data Series No. 1. International Atomic Energy Agency, Vienna, Austria, 44th edition, 2024a. ISBN 978-92-0-123424-7. | DOI |
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IAEA. Power Reactor Information System. International Atomic Energy Agency, Vienna, Austria, 2024b. | URL |
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Ember. Yearly Electricity Data. 2024. | URL |
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BNEF. 3Q 2024 Global PV Market Outlook. 2024. | URL |
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GWEC. Global Wind Report 2024. 2024. | URL |
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Food and Agriculture Organization of the United Nations (FAO). Global Forest Resources Assessment. 2020. | DOI |
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Matthew J. Gidden, Siddharth Joshi, John J. Armitage, Alina-Berenice Christ, Miranda Boettcher, Elina Brutschin, Alexandre C. Köberle, Keywan Riahi, Hans Joachim Schellnhuber, Carl-Friedrich Schleussner, and Joeri Rogelj. A prudent planetary limit for geologic carbon storage. Nature, 645(8079):124–132, September 2025. | DOI |
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IEA. CCUS Projects Database. 2024. | URL |
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IEA. Hydropower Data Explorer. 2021a. | URL |
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IRENA. Renewable Capacity Statistics 2025. March 2025. | URL |