Modelled domestic pathways

We have updated our modelled domestic pathways to reflect the IPCC AR6 scenario database. We have started to use these new pathways in our country updates from September 2023. We will update this page shortly to reflect these method developments.

We use the modelled domestic pathways to assess whether targets or policies are on track towards full decarbonisation in line with the 1.5°C warming limit. The modelled domestic pathways aim at providing feasible emission reduction pathways within each country, complementing the important focus on fair shares.

Most developing countries will need support to meet a 1.5°C modelled domestic pathway. This framework allows us to see where, and how much, support they are due. Conversely, developed countries should be achieving at least their 1.5°C modelled domestic pathway domestically and using their own resources.

In this section, we explain how the modelled domestic pathways are derived and some of the limitations of the data and methods we have available.

Scenarios of integrated assessment models (IAM) quantify storylines of future development of the coupled energy-land-economy-climate system and describe the anthropogenic emissions of greenhouse gases across sectors and regions over the twenty-first century. Between feasible transition pathways for a given set of technological, socio-economic and policy assumptions, these models select global least-cost solutions rather than an equitable distribution of burdens. Alongside the IPCC Special Report on 1.5°C (IPCC SR1.5) (Rogelj et al., 2018) a consolidated scenario ensemble of 414 scenarios from 13 global models in five world regions that lead to warming impacts from 1.5°C to above 4°C has been published (Huppmann et al., 2019).

Paris Agreement compatible pathways are defined as in the IPCC SR1.5 as those that limit warming to 1.5°C with no or limited overshoot (<0.1°C). In these pathways, the increase of global average temperature above its pre-industrial level is limited to below 1.6°C for the whole twenty-first century and below 1.5°C by 2100.

The scenarios considered were generated by Integrated Assessment Models, which are part of the IPCC Special report on 1.5°C, published in 2018. As there is a delay in the publication of emission and energy consumption data, often two to three years, the majority of the historical scenario data only goes up until 2015 or even earlier. Scenario data thus may differ from more recent historical data in the period between 2015 and the present. We address this issue with data harmonisation routines to match historical data.

Beyond possible discrepancies with recent historical data, care should be taken in the interpretation of global model results. While the global pathways provide useful guidance for an upper-limit of emissions trajectories for developed countries, they underestimate the feasible space for such countries to reach net zero earlier. The current generation of models tend to depend strongly on land-use sinks outside of currently developed countries and include fossil fuel use well beyond the time at which these could be phased out, compared to what is understood from bottom-up approaches.

The scientific teams which provide these global pathways constantly improve the technologies represented in their models – and novel carbon dioxide removal (CDR) technologies are now being included in new studies focused on deep mitigation scenarios meeting the Paris Agreement. A wide assessment database of these new scenarios is not yet available; thus, we rely on available scenarios which focus particularly on bioenergy with carbon capture and storage (BECCS) as a net-negative emission technology to offset so-called “hard to abate” sectors or to bring global temperature back down to a safer level.

The amount of CDR required depends on the pace of global progress in reducing emissions; early action to rapidly decarbonise and reduce the overall need for CDR are essential. While measures to reduce emissions often come with co-benefits for society (for example, improved energy access, lower costs, cleaner air), the same is not true for many CDR options. If deployed at a larger scale, CDR technologies would entail negative side-effects across different dimensions of sustainable development objectives. Their technological and economic viability have not been proven yet and limited progress has been observed in planning and deploying them at national levels (Fyson et al., 2020).

The IPCC SR1.5 finds limits for a sustainable use of both carbon dioxide removal options globally by 2050 to be below 5 GtCO₂ p.a. for bioenergy with carbon capture and sequestration (BECCS) and below 3.6 GtCO₂ p.a. for sequestration through afforestation and reforestation (AR) while noting uncertainty in the assessment of sustainable use and economic and technical potential in the latter half of the century (Fuss et al., 2018; IPCC, 2018). Accordingly, we filter the used scenario ensemble and remove scenarios exceeding the BECCS limitation in 2050 or the AR limit as an average over the second half of the century, noting that forestry-related sequestration can exhibit interannual variability.

Each scenario in the filtered scenario ensemble provides consistent greenhouse gas emissions pathways for the sectors Energy, Industrial Processes and Product Use, Agriculture and Waste from 2010 to 2100 for five world regions. The modelled domestic pathways are derived from these by

(1) harmonising each scenario to historical sectoral emissions of the year 2015,

(2) downscaling the emissions from the world regions to countries, and

(3) summarising the downscaled total greenhouse gas emissions for each country with the median and a low percentile of the scenarios for the temperature categories.

The discrepancy of historical emissions in the scenarios from the official UNFCCC data inventory of national greenhouse gas emissions is addressed by harmonising the scenario data in each world region and sector to a consistent value in 2015 with Aneris the automated IAM harmonisation tool developed for the CMIP6 intercomparison project (Gidden et al., 2018). The historical value in 2015 was derived by extending the UNFCCC data with PRIMAP-hist sectoral emissions and aggregating the country emissions to the world regions. For the dominant emissions of the Energy sector a total carbon budget preserving method was chosen instead.

For downscaling the emissions in the Energy, Industrial processes and Waste sectors from the world region to individual countries a methodology based on intensity convergence is used; more specifically the Impact, Population, Affluence, and Technology (IPAT) method as developed by van Vuuren et al. (2007) and extended by Gidden et al. (2019). It assumes that emissions intensities (i.e. the ratio of emissions to GDP) will converge from their values in the historical base year to the world region intensity in the last year of the scenario data, in the year 2100. This is made possible by an exponential interpolation of emission intensities from the base-year to the convergence year. Together with the yearly GDP by the given scenario, this interpolation defines how the emissions of the macro region are shared amongst the countries.

In most pathways, the Energy - CO2 emissions become negative long before 2100. We move and scale the exponential convergence model to account for the shift from positive to negative emissions in the downscaling routine.

Since emissions in the Agriculture sector do not necessarily correlate with the GDP development, the emissions for individual countries are determined by assuming the emission shares of the countries in the base year (2015) remain constant over the whole scenario period, a simple downscaling methodology called “base-year pattern”.

After the emissions projections of each sector have been harmonised and downscaled to the individual countries, they are aggregated to consistent economy-wide emissions pathways for each scenario in the filtered scenario ensemble. We then assess the full distribution of the downscaled outcomes in temperature categories. The temperature categories are defined in the same manner as those used for the fair share framework – we group pathways that would lead to a 66% or greater chance of holding warming below 2, 3, and 4°C. Pathways that would keep warming below 1.5°C with a 50% probability, and fit the sustainability criteria defined above, are labelled 1.5°C compatible.

Within each of these temperature categories, we determine the median (50th percentile) country-level emissions pathway as a representative for each country and use it as a threshold for the respective temperature category.

• Fuss, S., Lamb, W. F., Callaghan, M. W., Hilaire, J., Creutzig, F., Amann, T., Beringer, T., Minx, J. C., Luderer, G., & Nemet, G. F. (2018). Negative emissions — Part 2 : Costs , potentials and side effects.
• Fyson, C.L., Baur, S., Gidden, M., & Schleussner, C.-F. (2020). Fair-share carbon dioxide removal increases major emitter responsibility. Nature Climate Change, 10, 836–841. https://doi.org/https://doi.org/10.1038/s41558-020-0857-2
• Gidden, M., Fujimori, S., van den Berg, M., Klein, D., Smith, S. J., van Vuuren, D. P., & Riahi, K. (2018). A methodology and implementation of automated emissions harmonization for use in Integrated Assessment Models. Environmental Modelling and Software, 105, 187–200. https://doi.org/10.1016/j.envsoft.2018.04.002
• Gidden, M., Riahi, K., Smith, S. J., Fujimori, S., Luderer, G., Kriegler, E., van Vuuren, D. P., van den Berg, M., Feng, L., Klein, D., Calvin, K., Doelman, J. C., Frank, S., Fricko, O., Harmsen, M., Hasegawa, T., Havlik, P., Hilaire, J., Hoesly, R., … Takahashi, K. (2019). Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century. Geoscientific Model Development, 12, 1443–1475.
• Huppmann, D., Kriegler, E., Krey, V., Riahi, K., Rogelj, J., Calvin, K., Humpenoeder, F., Popp, A., Rose, S. K., Weyant, J., Bauer, N., Bertram, C., Bosetti, V., Doelman, J., Drouet, L., Emmerling, J., Frank, S., Fujimori, S., Gernaat, D., … Zhang, R. (2019). IAMC 1.5°C Scenario Explorer and Data hosted by IIASA. https://doi.org/10.5281/ZENODO.3363345
• IPCC. (2018). Summary for Policymakers. In V. Masson-Delmotte, P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P. R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J. B. R. Matthews, Y. Chen, X. Zhou, M. I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, & T. Waterfield (Eds.), Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, (Issue October 2018). IPCC.
• Rogelj, J., Shindell, D., Jiang, K., Fifita, S., Forster, P., Ginzburg, V., Handa, C., Kheshgi, H., Kobayashi, S., Kriegler, E., Mundaca, L., Seferian, R., & Vilarino, M. V. (2018). Mitigation Pathways Compatible With 1.5°C in the Context of Sustainable Development. In Global warming of 1.5°C. An IPCC Special Report [...] (p. 82pp). IPCC. https://www.ipcc.ch/site/assets/uploads/sites/2/2019/02/SR15_Chapter2_Low_Res.pdf
• van Vuuren, D. P., Lucas, P. L., & Hilderink, H. (2007). Downscaling drivers of global environmental change: Enabling use of global SRES scenarios at the national and grid levels. Global Environmental Change, 17(1), 114–130. https://doi.org/10.1016/j.gloenvcha.2006.04.004

Back to top

Continue to Climate Finance Rating