Short introduction on Bangladesh’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 157.8 mega tonnes of CO2 (Mt CO2eq), Bangladesh contributed 0.33% to the global greenhouse gas emissions of 2017 (rank 42 - 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, Bangladesh’s global contribution to greenhouse gas emissions is projected to increase to approximately 0.39% (220.5 mega tonnes of CO2 equivalent / rank 41 - incl. EU27 on rank 4). The emissions projections for Bangladesh 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, Bangladesh represented 2.11% of the global population. Its Gross Domestic Product (GDP) in 2017 were 0.49% 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 Energy and Agriculture (54.7% and 28.6%). Amongst the greenhouse gases that are considered in the Kyoto Protocol, the strongest contributor with 56.0% was CO2. This was followed by CH4 emissions, with a share of 36.5%. When not considering the sectors and gases independently, but the sector-gas combinations instead, Energy CO2 and Agriculture CH4 (53.6% and 21.7%) 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 updated 2020 NDC, the country communicates that “Bangladesh already aimed for an unconditional reduction of GHG emissions by 5% from Business as Usual (BAU) levels by 2030 equivalent to 12 MtCO2e in the power, transport and industry sectors. In the unconditional part of NDC, only those mitigation measures were considered which would be implemented on the basis of current local level capacity, and financed through internal resources. Contingent upon international funding and technological support, the country targeted to reduce GHG emissions in the same sectors up to 36 MtCO2e by 2030 or 15% below BAU emissions.” (NDC2020, p. 11). Bangladesh’s 2020 submission is more of a stocktaking, but an enhanced NDC is planned, and “This updated NDC will be built on the theme of the Bangladesh Climate Change Strategy and Action Plan of emission mitigation and low carbon development and call for concentrated efforts to fulfill mitigation goals for low carbon growth while working with the global community to establish a fair and equitable post-Kyoto framework for developing countries. […] Adhering to that spirit for global action, and given the various necessary policies and measures undertaken over the last few years and some of them already bearing fruits, the government is expecting to enhance both unconditional and conditional contribution in the updated NDC.” (NDC2020, p. 17). As the GHG mitigation target has not been changed, but less target information is given in the 2020 submission, the details below are mostly from the NDC submitted in 2016.
In 2030, Bangladesh aims on target emissions that are 12 to 36 MtCO2eq SAR (GWP: NDC2016, p. 8) below BAU. Further, “Bangladesh’s mitigation contribution covers the power, transport and industry sectors. Under a BAU scenario, GHG emissions in Bangladesh in these sectors are expected to represent 69% of total emissions by 2030 (excluding LULUCF), an increase of 264% by 2030, from 64 MtCO2e in 2011 to 234 MtCO2e in 2030.” (NDC2016, p. 3). This information enables us to estimate the total BAU to be 339 MtCO2eq SAR (exclLU), and the absolute target emissions as 237 MtCO2eq SAR in the unconditional case, and 303 MtCO2eq in the conditional case. 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.
Regarding the coverage of this contribution, the Bangladesh states that “The contribution covers the power sector, and energy use in the transport and industry sectors. Other sectors are not included in the quantified contribution, but are included as action-based conditional contributions.” (NDC2016, p. 8). We therefore assess the main IPCC sectors Energy and IPPU as covered, while Agriculture, LULUCF, and Waste are not covered. For the Kyoto GHGs, the scope is clearly mentioned to consist of CO2, CH4, N2O, HFCs, PFCs, and SF6 (NDC2016, p. 8). For the seventh Kyoto GHGs NF3, e.g., PRIMAP-hist v2.1 has no historical emissions data available for Bangladesh. NF3 has only been added to the Kyoto GHG basket for the Kyoto Protocol’s second period. It is merely reported by few countries and contributed less than 0.01% to global Kyoto GHG emissions in 2017 (exclLU and exclBF, based on PRIMAP-hist v2.1 HISTCR, in AR4, with its share being influenced by the few available data). In total, our assessment of covered sectors and gases results in an estimated 55.9% of 2017’ emissions being targeted by the NDC (based on PRIMAP-hist v2.1 HISTCR exclLU, in AR4).
Further information is given on the “Approach for land-based emissions: Data was not available to allow for detailed analysis of future GHG emissions and mitigation potential in the LULUCF sector. Further work will be needed to quantify this accurately (see section 4 on INDC implementation).” (NDC2016, p. 8). In the 2020 submission, the country indicates that “To reduce the carbon emission from forestry sector, Bangladesh formulated Bangladesh National REDD+ Strategy (BNRS) and established a National Forest Monitoring System (NFMS) for periodical monitoring of tree and forest cover.” (NDC2020, p. 8). Additionally, “The Forest Investment Plan (FIP, 2017-2022) has been developed to identify the future investment opportunities to increase the forest cover, reducing the deforestation and forest degradation, improving the livelihoods of the forest dependent people through the implementation of participatory/social forestry.” (NDC2020, p. 15). Also, a potential reduction of black carbon emissions is mentioned, as “The full implementation of the National SLCP Plan is expected to reduce black carbon emissions by 40% and methane emission by 17% in 2030 compared to a business as usual scenarios.” (NDC2020, p. 8).
The NDC-assessment is based on Bangladesh’s NDCs submitted to the UNFCCC in December 2020, and in September 2016.
The Figure below provides additional information, regarding both the baseline emissions used in our assessment and the quantified mitigated pathways for Bangladesh.
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