Kenya

Critically Insufficient4°C+ World

NDCs with this rating fall well outside of a country’s “fair share” range and are not at all consistent with holding warming to below 2°C let alone with the Paris Agreement’s stronger 1.5°C limit. If all government NDCs were in this range, warming would exceed 4°C. For sectors, the rating indicates that the target is consistent with warming of greater than 4°C if all other sectors were to follow the same approach.

Highly insufficient< 4°C World

NDCs with this rating fall outside of a country’s “fair share” range and are not at all consistent with holding warming to below 2°C let alone with the Paris Agreement’s stronger 1.5°C limit. If all government NDCs were in this range, warming would reach between 3°C and 4°C. For sectors, the rating indicates that the target is consistent with warming between 3°C and 4°C if all other sectors were to follow the same approach.

Insufficient< 3°C World

NDCs with this rating are in the least stringent part of a country’s “fair share” range and not consistent with holding warming below 2°C let alone with the Paris Agreement’s stronger 1.5°C limit. If all government NDCs were in this range, warming would reach over 2°C and up to 3°C. For sectors, the rating indicates that the target is consistent with warming over 2°C and up to 3°C if all other sectors were to follow the same approach.

2°C Compatible< 2°C World

NDCs with this rating are consistent with the 2009 Copenhagen 2°C goal and therefore fall within a country’s “fair share” range, but are not fully consistent with the Paris Agreement long term temperature goal. If all government NDCs were in this range, warming could be held below, but not well below, 2°C and still be too high to be consistent with the Paris Agreement 1.5°C limit. For sectors, the rating indicates that the target is consistent with holding warming below, but not well below, 2°C if all other sectors were to follow the same approach.

1.5°C Paris Agreement Compatible< 1.5°C World

This rating indicates that a government’s NDCs in the most stringent part of its “fair share” range: it is consistent with the Paris Agreement’s 1.5°C limit. For sectors, the rating indicates that the target is consistent with the Paris Agreement’s 1.5°C limit.

Role model<< 1.5°C World

This rating indicates that a government’s NDC is more ambitious than what is considered a “fair” contribution: it is more than consistent with the Paris Agreement’s 1.5°C limit. No “role model” rating has been developed for the sectors.

1.5°C Compatible< 1.5°C World

Historical emissions

Historical emissions for the years 1994, 1995, 2000, 2005 and 2010 are taken from the data reported to the UNFCCC GHG inventory database (UNFCCC, 2015). We interpolated missing time series values. PRIMAP data is used to calculate growth rates in order to expand the historical time series to 2016, excluding LULUCF (Gütschow, Jeffery, & Gieseke, 2019).

Pledges and targets

Data for the NDC business-as-usual scenario was taken from the country’s Second National Communication for the years 2015 and 2030 (Republic of Kenya, 2015). We interpolated missing time series values. As there is no gas-by-gas split available for the years 2015 and 2030, we have calculated a country-specific historical ratio between SAR and AR4 by recalculating the historical years for which a gas-by-gas spilt is available. We consider the years 1995, 2000, 2005 and 2010 to calculate the average ratio (hereafter referred to as average conversion factor). Because of disproportionate deviation, the year 1994 was not considered for the average conversion factor. The LULUCF sector was not considered either for calculating the average conversion factor as we assume CO₂ to be the main GHG in this sector.

Data for the NDC target was taken from the country’s Second National Communication and its NDC (MENR, 2015; Republic of Kenya, 2015). In order to exclude LULUCF from the NDC target, we have calculated the sector shares in the overall emissions reductions target of 30% by 2030. The LULUCF sector contributes the largest share (47%) to the overall emissions reductions target, with all the remaining sectors together contributing 53%. The projected NDC BAU by 2030, excluding LULUCF, was first multiplied by 30% and then by 53% in order to get the adjusted NDC target, without considering mitigation actions in the LULUCF sector.

Current policy projections

Upper range (CPP Max.)

Data for the upper range of the current policy projection was taken from the historical emissions time series for 2016and from the NDC Baseline Update for the year 2030 (MENR, 2017a; Republic of Kenya, 2015).

In January 2017, the Ministry of Environment and Forestry, with support from the Strengthening Adaptation and Resilience to Climate Change in Kenya (StARCK+) programme, released an assessment report containing an updated emissions baseline to inform how sectors could contribute to meeting Kenya’s NDC. 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 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 (MENR, 2017a).

Lower range (CPP Min.)

Data for the lower range of the current policy projection was taken from the historical emissions time series for 2016. Data for the year 2030 was taken from the NDC Baseline Update for all sectors except the electricity generation subsector, for which data was taken from the 2017-2037 Least Cost Power Development Plan (LCPDP) (Republic of Kenya, 2018).

Global Warming Potentials

The CAT uses Global Warming Potential (GWP) values from the IPCC’s Fourth Assessment Report (AR4) for all its figures and time series. Kenya uses GWP values from the IPCC’s Second Assessment Report (SAR), therefore we converted all figures and time series from SAR to AR4 GWP values.