Short introduction on Tanzania’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 93.9 mega tonnes of CO2 (Mt CO2eq), Tanzania contributed 0.19% to the global greenhouse gas emissions of 2017 (rank 59 - 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, Tanzania’s global contribution to greenhouse gas emissions is projected to increase to approximately 0.23% (131.1 mega tonnes of CO2 equivalent / rank 52 - incl. EU27 on rank 4). The emissions projections for Tanzania 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, Tanzania represented 0.72% of the global population. Its Gross Domestic Product (GDP) in 2017 were 0.11% 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 (64.0% and 23.5%). Amongst the greenhouse gases that are considered in the Kyoto Protocol, the strongest contributor with 59.7% was CH4. This was followed by N2O emissions, with a significantly lower share of 27.4%. When not considering the sectors and gases independently, but the sector-gas combinations instead, Agriculture CH4 and Agriculture N2O (39.1% and 24.8%) 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.”

In its NDC, the country communicates that “Tanzania will reduce greenhouse gas emissions economy wide between 10-20% by 2030 relative to the BAU scenario of 138 - 153 Million tones of carbon dioxide equivalent (MtCO2e) - gross emissions, depending on the baseline efficiency improvements, consistent with its sustainable development agenda. The emissions reduction is subject to review after the first Biennial Update Report (BUR).” (NDC, p. 6). The reference year for the provided BAU scenario is the year 2000 (NDC, p. 3). Tanzania additionally indicates that “implementation of the identified INDCs will strongly depend on how the international community meets its commitments in terms of financial and technological support.” (NDC, p. 8).

Based on the average over the given BAU scenario emissions (145.5 MtCO2eq, in line with the BAU displayed in the NDC’s Fig. 1, p. 7), the 10 to 20% reduction relative to BAU result in target emissions of 116.4-131.0 MtCO2eq. The availability of national estimates of emissions mitigation targets and pathways in line with countries’ NDCs is of great importance when, e.g., aggregating to global emissions to then derive, i.a., the resulting end-of-century warming levels. While the “Identified mitigation priority sectors are: Energy, Transport, Forestry and Waste management.” (NDC, p. 2), Tanzania’s contribution is also stated to be “economy wide” (NDC, p. 6). Based on this information, we assess all main IPCC sectors (Energy, IPPU, Agriculture, LULUCF, and Waste) to be covered in the country’s NDC. Concerning the covered gases, no information is provided, and we assume CO2, CH4, and N2O to be included, and the F-gases to be excluded by Tanzania’s contribution. In total, this results in an estimated 100.0% of 2017’ emissions being targeted by the NDC (based on PRIMAP-hist v2.1 HISTCR exclLU, in AR4). The BAU emissions are “gross emissions”, rather than net emissions that would include removals from LULUCF. Hence, we classify the BAU and absolute target emissions presented above as excluding LULUCF. This classification is connected to uncertainties, however.

Regarding LULUCF, Tanzania’s NDC includes further information, i.a., “the country has a total of 88 million hectares of land areas, of which 48.1 million are forested land and under different management regimes, with a current estimated total of 9.032 Trillion tones of carbon stock. The estimates are based on the present stocks from limited studies. This implies that Tanzania is a net sink.” (NDC, p. 3). In the Forest sector, the country plans several measures: “a) Enhancing and up-scaling implementation of participatory forest management programmes. b) Facilitating effective and coordinated implementation of actions that will enhance contribution of the entire forest sector including Forest policies, National Forest Programmes and REDD+ related activities. c) Strengthening national wide tree planting programmes and initiatives. d) Strengthening protection and conservation of natural forests to maintain ecological integrity and continued benefiting from service provisions of the sector. e) Enhancement and conservation of forest carbon stocks.”(NDC, p. 8).

The NDC-assessment is based on Tanzania’s NDC submitted to the UNFCCC in May 2018.

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

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