Kenya

Historical emissions for the years 1990–2019, excluding LULUCF, are taken from PRIMAP data (Gütschow et al., 2021). LULUCF emissions for the years 1994, 1995, 2000, 2005, and 2010 are taken from the data reported to the UNFCCC GHG inventory database and interpolated between years.

To estimate emissions for 2020, we applied a gas-by-gas approach. For direct CO₂ emissions, we applied growth rates from the Global Carbon Budget to the latest historical data point. For non-CO₂ emissions, we used a sectoral split. For energy non-CO₂ emissions, we estimated the emissions intensity (GHG emissions/GDP) from pre-COVID scenarios and apply it to 2020 GDP projections (see below). We assume that the impact of the pandemic on industry, agriculture, waste, and other non-CO₂ emissions will be minimal, and so have extended the historical 5-year trend.

To estimate emissions for 2021, we applied the same method, but used the emissions intensity approach for direct CO₂ emissions as well.

Unconditional target: The NDC states that Kenya will bear 21% of the estimated required mitigation costs itself. In the absence of information on sectoral mitigation costs, we assume that this 21% financial contribution is equivalent to a 21% share of the targeted emission reductions. On that basis, we calculate the unconditional contribution to be equivalent to an unconditional target of 7% below BAU, including LULUCF – or 4% below BAU, excluding LULUCF emissions. This corresponds to emissions levels of 126 MtCO₂e by 2030 (excluding LULUCF) (expressed in AR4 values) (see further assumptions on GWP below).

In its first NDC, Kenya included a separate target of 47% below BAU by 2030 for the LULUCF sector. While explicit reference to this target has been dropped in the update, we assume that Kenya will meet about half of its NDC with reductions in land sector emissions.

Conditional target: If the target is met, emissions in 2030 will be 108 MtCO₂e (excl. LULUCF). The conditional contribution is equivalent to a 17% reduction below BAU by 2030 (excl. LULUCF).

Upper range (CPP Max.)

The upper bound of our current policy projection is based on a combination of data sources (IEA, 2019; U.S. Environmental Protection Agency, 2019). Energy-related CO₂ emissions are based on growth rates from the Stated Policies Scenario of the IEA Africa Energy Outlook 2019. This scenario assumes a partial implementation of Kenya’s National Electrification Strategy. We assumed other, non-energy CO₂ emissions would grow based on the same growth rate since most non-energy CO₂ emissions come from the industry sector. Industry, agriculture, waste, and other non-CO₂ emissions are based on non-CO₂ emissions projections from the US EPA. We have adjusted these projections to take into consideration the impact of the pandemic (see below) and have harmonised the series to the last historical year.

Lower range (CPP Min.)

In January 2017, the Ministry of Environment and Forestry released an assessment report containing an updated emissions baseline to inform how sectors could contribute to meeting Kenya’s NDC (Ministry of Environment and Natural Resources, 2017a). The objective of the assessment was to examine expected contributions to emissions reductions from each sector, explore sectoral mitigation actions to meet the NDC target, and examine new information that could impact the achievement of the NDC targets. The update was based on new historical activity data out to 2015 for each emission source as well as new information on drivers of future emissions (2016- 2030), such as GDP growth forecasts by sector, new projections on electricity generation projects and new forecasts for urbanisation.

For the lower end of the range, we have taken the updated emissions baseline for all sectors except electricity generation, transport and agriculture (Ministry of Environment and Natural Resources, 2017a). The data for electricity generation is taken from the 2017-2037 Least Cost Power Development Plan (LCPDP), for the transport sector, the data is taken from the 2019/2020 Transport Sector Climate Change Annual Report, which indicates a list of mitigation actions the sector plans to implement that should allow it to achieve its sectoral NDC target, and for the agriculture sector, the data is taken from the Kenyan Climate Smart Agriculture Strategy 2017-2026, which includes an indicative 2026 emissions level based on proposed mitigation actions (Government of Kenya, 2019; Ministry of Agriculture, 2018; Republic of Kenya, 2018). We did not quantify the mitigation actions outlined in National Climate Change Action Plan (NCCAP) for the electricity generation, energy demand, industry, and waste sectors due to uncertainty about their current implementation status.

We have adjusted these projections to take into consideration the impact of the pandemic (see below).

This scenario is also harmonised to the last historical year.

We applied a novel method to estimate the COVID-19 related dip in greenhouse gas emissions in 2020 and the trajectory to 2030. The uncertainty surrounding the severity and length of the pandemic creates a new level of uncertainty for current and future greenhouse gas emissions. We first update the current policy projections using most recent projections. We then distil the emission intensity (GHG emissions/GDP) from this pre-pandemic scenario and apply to it the most recent GDP projections that take into account the effect of the pandemic.

As a result of the pandemic, Kenya’s GDP dropped by -0.3% in 2020 and rebounded by 7.2% in 2021 (IMF, 2022). We use recent estimates from IMF for GDP growth from 2022 to 2027 (IMF, 2022). Since the most recent GDP projections only provide values for the next few years (up to 2027), we used the same GDP growth rate as pre-pandemic current policy scenarios for the remaining years.

The CAT uses Global Warming Potential (GWP) values from the IPCC's Fourth Assessment Report (AR4) for all its figures and time series. Assessments completed prior to December 2018 (COP24) used GWP values from the Second Assessment Report (SAR).

Kenya has indicated that it will account for its NDC using GWP values from the IPCC’s fifth assessment report (AR5). However, we assume that its reference to a BAU of 143 MtCO₂e is expressed in GWP values from the IPCC’s second assessment report (SAR). Similar to the first NDC, the updated NDC quantified the 2030 reference value based on the 2030 GHG emissions projected in the National Climate Change Action Plan (2013-2017) and values in that report are in SAR. For the purpose of this analysis, we assume that the sector contribution to achieving the target and LULUCF assumptions used in the CAT country assessment remain unchanged and we converted the IPCC SAR GWP values to AR4 GWP values. Converting from SAR to AR5 under these assumptions would increase the targets by a couple of MtCO₂e. If, however, the BAU is already in AR5 values, then the targets will be lower than the estimates provided here.