Saudi Arabia

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.

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.

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.

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.

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.

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.

Historical emissions

Historical emissions up to 2012 were obtained gas by gas from UNFCCC (2018) and converted into AR4 global warming potentials (GWPs). For 2013–2015, a combination of different data sources was used to complete the emissions trajectory excluding land use, land use change and forestry (LULUCF): IEA (2019) for energy-related CO₂ emissions, IEA (2019) for other CO₂ emissions and US EPA (2019) for non-CO₂ emissions, with a trend extrapolation for other CO₂ emissions for 2015. LULUCF values for 1990, 2000, 2010 and 2012 were taken from UNFCCC (2018).

NDC and other targets

Since Saudi Arabia has not yet communicated the business as usual (BAU) scenario for its NDC target, we quantified the target based on our estimates of the BAU. The lower end of the BAU range represents extrapolation of Saudi Arabia’s 2005–2010 emissions trend. The upper end of the range represents a baseline projection starting in 2010 and assumes no further expansion of renewable and nuclear power generation. We based this scenario on adjusted projections from KAUST (2014) for energy-related emissions, complemented by US EPA (2012) projections for non-CO₂ emissions and extrapolation of the historic trend for other CO₂ emissions from IEA (IEA, 2017).

Current policy projections

Our current policy projection range reflects optimistic and pessimistic assumptions on the implementation of the targets for renewable energy from Saudi Arabia’s “Vision 2030”. Both pathways are based on growth rates from KAUST (2014) for energy-related emissions, US EPA (2019) projections for non-CO₂ emissions and extrapolation of the historical trend for other CO₂ emissions.

Since the KAUST projections assume the plan of installing 54 GW of renewables and 17 GW of nuclear was going to be executed by 2032, we additionally quantified the downscaling of the renewable and nuclear power targets. For the lower end of the range we assume the 2023 and 2030 targets for renewable energy are met, and nuclear power reaches 2.8 GW in 2030. For the upper end of the range we assume renewable capacity remains at 9.5 GW post-2023, in line with the previous target announced in 2016, with no nuclear capacity additions by 2030. For both pathways, we used the average emission factor of fossil power generation in 2011–2015 from IEA (IEA, 2017) and full load hours for renewable and nuclear power from the KAUST projections.

The effect of deregulation in energy prices by a subsidy phase-out is reflected in both pathways and calculated based on the expected impact on the consumption of diesel oil and gasoline. An IISD report estimated that the effect of subsidy phase-out would result in a reduction in emissions by 30.4% below BAU in 2025 and 27.8% in 2030 if subsidies had been phased out by 2020 (Merrill, Bassi, Bridle, & Christensen, 2015). Based on this study, we estimate that the delayed phase-out will lead to a reduction of fuel consumption, resulting in emissions reductions of 53 MtCO₂e in 2030. The effect of the introduced 5% VAT for fuels is not quantified in our assessment since there is no data available on the effect of this policy.

COVID-19 impact

We applied a novel method to estimate the COVID-19 related dip in greenhouse gas emissions in 2020 and the deployment through 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 use the current policy projections based on our most recent projections, usually prepared before the pandemic. We then distil the emission intensity (GHG emissions/GDP) from this pre-pandemic scenario and apply to it most recent GDP projections that take into account the effect of the pandemic. The GDP projections from the IMF (2020) and the World Bank (2020) capture the range of existing estimates. To our knowledge, there are no domestic GDP forecasts capturing the impact of the COVID-19 crisis on GDP. As the most recent GDP projections only provide values for 2020 and 2021, for the years 2022-2030 we use the GDP growth that was used as a basis for the original pre-pandemic current policy scenario.

Global Warming Potential values

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).