Here we describe the methodology used to create the Climate Resource greenhouse gas (GHG) emissions time series consistent with countries achieving the emissions reductions targets to 2030 and out to 2050 that are contained in their submissions to the UNFCCC (United Nations Framework Convention on Climate Change). If you use this work, please refer to our earlier paper:
Meinshausen, M., Lewis, J., McGlade, C. et al. Realization of Paris Agreement pledges may limit warming just below 2 °C. Nature 604, 304–309 (2022). https://doi.org/10.1038/s41586-022-04553-z
Or for this version of the data, use the citation below:
Meinshausen, M., Lewis, J., Gütschow J., Self, A., Burdon, R., Pflüger, M., and Lai, Y., (2023), NDC factsheets 01 December 2023, available at https://www.climate-resource.com/tools/ndcs
Our quantification of the targets submitted in NDCs (nationally determined contributions) and LT-LEDS (long-term, low-emissions development strategies) starts from what countries submit to the official NDC portal and long-term strategies portal at the United Nations Framework Convention on Climate Change
Our primary historical database used is the PRIMAP-hist TP database (which is now another project of ours here at Climate Resource), specifically the dataset PRIMAP-hist TP version 2.5, available at primap.org. Only in a very few cases did we use specific data for a country, for example, if the country reported specific data in its NDC. The underlying data and the country NDCs are publicly available.
Range in ambition
Conditional and unconditional
The international community is expected to provide both technological and financial support to assist many lower-middle income and low income countries to transition to low-emissions economic growth pathways. Many of those countries’ NDCs specify both:
An unconditional target, which they implement with domestic resources; and
A conditional target with higher emissions reductions, subject to achieving international support. The conditions and support specified may relate to financial resources, technology transfer, technical cooperation, capacity-building support from other countries, the availability of market-based mechanisms, or absorptive capacity of forests and other ecosystems.
High income industrialised (Annex 1) countries only submit unconditional NDCs. These countries are regarded as having both responsibility for relatively high historical emissions and the capacity to achieve rapid decarbonisation if effective policies are implemented. Other non-Annex 1 countries that have relatively higher capacity and industrialised economies, such as South Korea, Mexico or China, also submit only unconditional NDCs.
We quantify emissions consistent with conditional targets assuming that all conditions are met. We also quantify emissions consistent with unconditional targets only.
Strong-weak ambition range
Some countries submit a target range including, for example, the USA (50%-52% below 2005 levels in 2030) and Canada (40%-45% below 2005 levels in 2030). For these countries we quantify emissions consistent with both the stronger and weaker end of the target range.
Other countries describe their emissions reduction targets in imprecise terms in their submissions to the UNFCCC. Alternative interpretations of some key underlying assumptions can lead to higher or lower 2030 emission level projections. For India’s 2070 net-zero commitment, it is unclear if the announcement relates to net-zero GHG or net-zero CO2, for example.
For countries that state their targets in a way that can be interpreted as stronger or weaker ambition or state a target range, we quantify emissions consistent with both the strong and weak ambition expression of the target. In determining the approach, we consider supporting documentation that may not be contained within the submission to the UNFCCC but assists in understanding the intent of that submission.
In these factsheets, we provide three different compilations.
The first is the unconditional setting, ranging from the weak to the strong ambition unconditional NDC target. If a country has no ambition range in its unconditional target, a single emission level results.
The second is the conditional setting, ranging from the weak to the strong ambition conditional NDC target. This shows the maximal emission level that would be in line with the full implementation of NDCs (full implementation of both conditional and unconditional elements). If the country does only have an unconditional NDC, then only that one is shown.
The third setting is the min-max setting, ranging from the highest emission level of the least ambitious unconditional target to the lowest emission level of the full implementation of the most ambitious NDC target (conditional and unconditional).
Inter- and extrapolations.
Our quantification of emissions consistent with NDCs and LT-LEDS goes through each country submission and determines the quantifiable future emissions for 2025, 2030, and 2050. In just a few cases, countries only submitted 2025 or even submitted only 2035 or even (in one case) 2040 targets. We then employ linear interpolations and extrapolations to derive the 2030 emission level.
Covered and non-covered emissions
More and more countries present their NDCs and LT-LEDS as whole-economy targets, that comprise emissions from the energy sector (usually including transport etc), the industrial and process emissions, waste, and agriculture. On forestry, i.e. the so-called land-use, land-use change and forestry (LULUCF) emissions, the countries vary in their coverage.
However, at present not all country targets cover all sectors and gases. We define economy wide coverage as CO2, CH4 and N2O for IPCC sectoral categories (1996) 1,2,3,4,6,7. That is, LULUCF and F-Gases are not required for a target to be defined as economy wide.
For each country, we implement the stated targets on the covered sectors and gases. If a country does not include a specific sector or gas explicitly in its NDC or post-2030 target, we assume a reference level for those uncovered emissions that follow the NGFS3 (Network for Greening the Financial System third vintage) GCAM current policy scenario.
The current policy reference scenario may not be considered a likely outcome at the global level. However, we consider it reasonable in this context because carbon leakage could put upward pressure on emissions by moving emission-intensive activities to countries and sectors not covered by an NDC or post-2030 target. We consider this makes it appropriate to err on the side of a higher, rather than lower emissions reference scenario for infilling uncovered sectors.
We use projected emissions from the NGFS3 GCAM current policy scenario as the basis for uncovered sector emissions for the first time in this 2023 emissions dataset. In the past we have used an SSP5 (shared socio-economic pathway) downscaled to country level. It is now eight years since the SSP5 scenario was constructed, and we consider the NGFS3 GCAM scenario is a more appropriate reference point for this purpose.
Treatment of net-emissions from LULUCF
Our primary reference point in these factsheets, and country rankings are total GHG emissions without LULUCF.
We exclude net emissions from LULUCF in the emission timeseries constructed for two principal reasons. First, countries adopt a wide range of methods for accounting for changes in LULUCF emissions and sinks, and in some cases include natural carbon uptake in their national emissions inventories. However, countries reporting natural carbon cycle fluxes as part of their LULUCF emissions is inconsistent with indicators such as the remaining global carbon budget or global net-zero CO2 year (Grassi et al. 2021). Additionally, including LULUCF arguably reduces comparability of emissions reduction efforts across countries: it creates a risk that some countries with limited ambition to reduce emissions of CO2 and other gases across the economy, appear to have high climate ambition because of their approach to accounting for changes in land sector sinks. Russia, for example, is proposing to count projected increases in carbon stored in unmanaged forests. If taken into account, this would be the primary method used to reduce Russia’s emissions, substantially increasing its reported level of mitigation ambition.
Secondly, material changes to LULUCF reporting methodologies within datasets are common as new updates are published . Year-to-year changes frequently come from the use of different sources or methodology changes within a source rather than changes in actual LULUCF emissions.
Given this, we exclude LULUCF as the intention is to report:
In a form that allows a comparison of emissions reduction efforts across countries, and
In a way that preserves reasonable consistency over time and does not result in potentially large change in emission time series year on year due to changes in LULUCF reporting methodologies.
Climate Resource and others are continuing to work on LULUCF methodologies and we may move to also reporting total GHG including LULUCF in future when these issues are better addressed.
As part of the quantification of country targets, Climate Resource makes use of reference scenarios from integrated assessment models (IAMs) that project greenhouse gas emission trajectories under different scenarios, instead of quantifying emissions consistent with country targets as stated in NDCs or LT-LEDs.
These reference scenario baselines are compared with country mitigation targets submitted to the UNFCCC. If a country’s targets submitted to the UNFCCC imply future emissions that are higher than emissions in the reference scenario, this is described as ‘hot air’.
Prior to October 2023, Climate Resource has used a ‘no policy’ reference scenario SSP5-baseline (described in Meinshausen et al., 2020, and available at IIASA SSP database). This reference scenario projected emissions to 2100 assuming a business-as-usual (BAU) trajectory without any climate policy. In this case countries were assessed as having hot air in their targets if their stated target emissions in NDCs were higher than any realistic scenario, given that the SSP5-baseline is considered a high emissions scenario.
From October 2023, Climate Resource has instead implemented the newer GCAM Current Policies Scenario from NGFS3 as the reference scenario. This change was made on the basis that the SSP scenarios are now 8 years old and the NGFS3 scenario provides a more up-to-date basis for a business as usual assessment.
Unlike the previous no policy SSP5-baseline scenario, the NGFS3 GCAM scenario models existing domestic policies in its 2030 emissions projections. Because the NGFS3 GCAM scenario takes into account these existing policy settings it leads to much lower baselines than the previous SSP5-baseline scenario.
This means that many more countries fall into the category of hot air. If a country is assessed as having a hot air target, it can still be the result of a very low ambition target. However, it may also simply indicate that the NGFS3 GCAM current policy scenario assesses domestic climate policy settings as leading to lower projected emissions than a country’s targets submitted to the UNFCCC.
Country targets that are assessed as hot air will likely be achieved, or over achieved, based on current policy settings. No additional policy is required to achieve these targets.
The emissions data is compiled for two treatments of hot air to enable the impact of this to be considered in quantifying projected emissions:
Include hot air - which takes the target as submitted by the countries (adjusted as necessary for LULUCF and uncovered sectors as described above).
Exclude hot air - in which the emission levels are capped at the NGFS3 GCAM current policy reference emission projections.
GWP (Global Warming Potentials)
Non-CO2 emissions are converted to CO2-equivalent using 100 year global warming potentials from the IPCC Sixth Assessment Reports (AR6GWP100).
Countries use different GWPs in their submissions to the UNFCCC. For those countries that do not report using AR6GWP100 we convert gases to AR6GWP100. HFCs and PFCs, which represent a basket of gases, are already reported in GWP-100s, often following the second IPCC Assessment Report (SARGWP100). For HFCs and PFCs a relative scaling of 1.4 and 1.3, respectively, is used to convert from SARGWP100 to AR6GWP100, based on calculated ratios between GWP SAR and AR6 for these species.
Per-capita emissions are calculated using the median UN population projection, 2022 edition. For international aviation, we approximate by dividing international aviation emissions by the estimated number of people that use international travel (before COVID). While the total percentage of the world's population being in a plane is roughly estimated at 10-15% in any given year (and probably 80% of humanity have never flown), the fraction of people using international flights is more like 4% or 5%. Hence, per-capita emission levels for international aviation is shown relative to 5% of the world's population.
GHG (excluding LULUCF) emissions per GDP is calculated using the IMF World Economic Outlook (2022) real GDP projections to 2027, and extrapolated out to 2030 assuming a GDP growth rate that reflects the average of the prior five years.
Climate Resource constructs two variants of the emissions time series: 'Country Reported', and the Climate Resource 'Default'. The two variants differ in the historical emissions used as a basis for quantifying country targets. In Country Reported, we use the PRIMAP-hist v2.5 CR (country reported) series which prioritises historical emissions reported by countries to the UNFCCC. It does not include any overrides to take into account third party emissions data sources or changes included in NDCs or LT-LEDS.
In the Climate Resource Default we use PRIMAP-hist v2.5 TP (Third Party) as the starting point for historical emissions for all sectors with the following three adjustments:
- All Annex I countries use PRIMAP-hist v2.5 CR CO2 LULUCF emissions.
- Where the Country Reported data is a better representation of a country’s NDC, the PRIMAP-hist v2.5 CR data is used as a source for a specific gas and category. For example, this can occur when the available third party datasets for a given species or country are considered to be substantially at odds with data assumed by the country when presenting its NDC.
- Where a specific dataset is implied by or used in the country’s NDC, it is used as an override.These “country-specific” overrides are used to ensure the historical data matches the intention of the NDC. These timeseries may scale growth rates from PRIMAP-hist to values extracted from an NDC or other country sources to match the values a country uses in its NDC.
Updated 3 December 2023, including:
- Change to the reference scenario from SSP5-baseline to NGFS3 -CGAM current policies
- Addition of both variants: Country Reported and Climate Resource Default