Short introduction on South Sudan’s emissions

Although CO2 is the driving force behind the temperature changes, other gases such as methane (CH4) also contribute their share to global warming, for example through the exploitation of gas fields, and emissions by livestock. While methane is emitted much less than CO2 on a global scale, it is a much stronger greenhouse gas (GHG). Scientists estimated the relative strength of the important Kyoto greenhouse gases so that we can convert all emissions to an equivalent of CO2 emissions. For example, the emission of one ton of methane has approximately the warming effect of 25 tons of CO2. The factor of 25 reflects the climate forcing on a 100-year time horizon, following the Global Warming Potential presented in the IPCC Fourth Assessment Report (AR4).

With greenhouse gas emissions of approximately the equivalent of 57.9 mega tonnes of CO2 (Mt CO2eq), South Sudan contributed 0.12% to the global greenhouse gas emissions of 2017 (rank 78 - incl. EU27 on rank 3). All emissions estimates exclude emissions and absorption from land, which result from activities such as cutting down or planting of forests (Land Use, Land-Use Change and Forestry: LULUCF). Emissions from bunker fuels (international aviation and shipping) were also excluded, as they are not accounted for in national totals.

For 2030, South Sudan’s global contribution to greenhouse gas emissions is projected to stay at a similar level of approximately 0.10% (60.3 mega tonnes of CO2 equivalent / rank 86 - incl. EU27 on rank 4). The emissions projections for South Sudan were derived by downscaling the Shared Socio-Economic Pathways’ (SSPs) “Middle-of-the-Road” baseline marker scenario SSP2. These pathways describe certain narratives of socio-economic developments and were, i.a., used to derive greenhouse gas emissions scenarios that correspond to these developments. SSP2 is a narrative with little shifts in socio-economic patterns compared to historical ones, and is connected to medium socio-economic challenges for both climate mitigation and adaptation. While different models were used for each storyline, per SSP (SSPs1-5) one model was chosen as representative “marker scenario”. As the emissions projections are not readily available on country-level, but national estimates are important, the pathways were downscaled in the aftermath. In 2017, South Sudan represented 0.14% of the global population. Its Gross Domestic Product (GDP) in 2017 were 0.019% of the global GDP.

Looking at the highest contributing emissions sectors and gases separately, we find that in 2017 the highest contributing emissions sectors were Agriculture and Energy (88.6% and 7.1%). Amongst the greenhouse gases that are considered in the Kyoto Protocol, the strongest contributor with 54.7% was CH4. This was followed by N2O emissions, with a share of 41.6%. When not considering the sectors and gases independently, but the sector-gas combinations instead, Agriculture CH4 and Agriculture N2O (47.6% and 40.9%) represented the largest emissions in 2017.

Greenhouse gas mitigation and Nationally Determined Contribution (NDC)

In 2015, the majority of countries agreed to the Paris Agreement (PA), with the goal of “Holding the increase in the global average temperature to well below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C above pre-industrial levels, recognizing that this would significantly reduce the risks and impacts of climate change” (Article 2.1.a). Countries stated their pledges and targets towards achieving the PA’s goals in their Nationally Determined Contributions (NDCs). With Article 4.4 of the Paris Agreement, Parties decided that “Developed country Parties should continue taking the lead by undertaking economy-wide absolute emission reduction targets. Developing country Parties should continue enhancing their mitigation efforts, and are encouraged to move over time towards economy-wide emission reduction or limitation targets in the light of different national circumstances.”

Even though South Sudan signed the Paris Agreement in APril 2016, the country never ratified the agreement. Therefore, South Sudan does not have an NDC, but an Intended NDC (INDC), in which the country did not include a clear quantifiable GHG mitigation target. Following its INDC, South Sudan plans “Policies and actions in identified sectors of economy. The mitigation contribution is contingent upon availability of international support for means of implementation.” (INDC, p. 4). The country further indicated in regard to GHG reductions that “In absence of detailed analysis the assessment of BAU emissions and impacts of identified policies and actions of GHG emissions reductions below shall be presented at a later date.” (INDC, p. 4). To date, no update has been presented, however.

The covered sectors are identified to be “Energy generation and energy end use; Transport; and Land Use and Land Use Change” (INDC, p. 4), why from the main IPCC emissions sectors, we assess IPPU, Agriculture, and Waste to be excluded in this INDC. The country presents CO2 as targeted gas (INDC, p. 4), why we assess the remaining Kyoto GHGs (“CH4”, “N2O”, “HFCS”, “PFCS”, “SF6”, and “NF3”) not to be covered. In total, our assessment of covered sectors and gases results in only 3.2% of 2017’ emissions being estimated as included in the NDC (based on PRIMAP-hist v2.1 HISTCR exclLU, in AR4).

Regarding forests and land, the country indicates for “Reforestation and Deforestation: i. With its abundant natural forests, South Sudan aims to declare approximately 20% of its natural forests as reserve forests to protect it from deforestation. ii. It also aims on an ambitious reforestation and afforestation project to plant 20 million trees over a period of ten years (2 million trees in each of its 10 states) as outlined in the National Environmental Policy. This will contribute towards restoring watershed and water catchment areas during the post-2020 period as well as sequestering carbon and reducing emissions from deforestation and forest degradation.” (INDC, p. 3). Additionally, “To maintain a clean and green environment, South Sudan will encourage payment for ecosystem services, access to resources and benefit sharing to avoid depletion of important natural resources. This would contribute towards the sustainability and viability of initiatives to reduce emissions from deforestation and forest degradation.” (INDC, p. 4).

As we did not quantify mitigation contributions by South Sudan, we assume the country’s emissions to follow projected baseline emissions. This is of special need when aggregating country-level data to regional or global values, to then, e.g., derive estimates of the end-of-century warming levels in line with mitigation pledges.

The INDC-assessment is based on South Sudan’s INDC submitted to the UNFCCC in November 2015.

The Figure below provides additional information, regarding both the baseline emissions used in our assessment and the quantified mitigated pathways for South Sudan.

Baseline emissions and mitigated emissions pathways based on the country’s Nationally Determined Contribution. In terms of national emissions, we look at the SSP2 baseline marker scenario, and the emissions of all IPCC sectors. Contributions from LULUCF are excluded (exclLU), and the emissions are based on GWPs from AR4. The left panel (a) shows the baseline emissions, indicating the contributions of the Kyoto Greenhouse Gases CO2, CH4, N2O, and the basket of F-gases to the national emissions. If we could extract baseline data exclLU from the NDC, you can see their values as black squares (converted from GWP SAR to AR4 if needed). In the right panel (b), the quantified mitigated emissions pathways are shown, based on information from the country’s NDC and also on non-NDC emissions baselines, per target conditionality and range (marked un-/conditional best/worst). Even though not all countries have targets with different conditionalities or ranges, we need assumptions for all four cases to build one global pathway per conditionality plus range combination and to derive corresponding temperature estimates. Therefore, we indicate these four pathways here. Per combination, we performed several quantifications with differing assumptions and show the median and the minimal and maximal pathways here. Additionally, if we could quantify the targets based on data extracted purely from the NDC - or if the targets were directly given in absolute emissions, these targets are shown as squares (in the GWP originally given in the NDC).


Data sources and further information

  • Historical emissions: PRIMAP-hist v2.1 (Guetschow et al., 2016, 2019).
  • Historical socio-economic data: PRIMAP-hist Socio-Eco v2.1 (Guetschow et al., 2019).
  • Projected emissions and socio-economic data: downscaled SSPs (Guetschow et al., 2020, 2020).
  • NDC quantifications: NDCmitiQ (Guenther et al., 2020, 2021).
  • GDP is given in purchasing power parity (PPP).
  • Main emissions sectors (Intergovernmental Panel on Climate Change, IPCC): Energy, Industrial Processes and Product Use (IPPU), Agriculture and LULUCF (Land Use, Land-Use Change and Forestry), also named AFOLU (Agriculture, Forestry and Other Land Use), and Waste.
  • Kyoto GHG: basket of several GHGs, namely carbon dioxide (CO2), Methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulphur hexafluoride (SF6), and since the second Kyoto Protocol period (2013-20) additionally nitrogen fluoride (NF3).
  • Global Warming Potentials (GWPs): GHGs have very different warming potentials. To make them comparable and for aggregation purposes, GWPs are used (how much energy will 1 ton of a certain gas absorb over a defined period of time, relative to the same mass of CO2?).


1 Potsdam Institute for Climate Impact Research (PIK), 14473 Potsdam, Germany