Policy and model uncertainties and their impact on NDC emission levels

The main policy uncertainty factor is the projected emissions of the current policies scenarios, that affect NDC projections when the NDC targets are above current policies. In that case, NDC teargets are capped by projected emissions levels resulting from the current policies scenarios. The second important policy uncertainty is conditionality. Countries' conditional targets will be implemented if the required international support (finance, technology transfer and/or capacity-building) is provided. The impact of conditionality is smaller compared to previous studies, as (i) a higher number of updated NDCs—representing 80% of global emissions—are mainly unconditional, and (ii) the NDC projections are constrained to the level resulting from current policies. The latter has a significant effect on the (un)conditional NDC targets of India, Iran, Mexico, Russian Federation, Turkey, Vietnam and Ethiopia, as they are considerably higher than their current policies projections. A new important uncertainty factor relates to the peaking of China's emissions in terms of timing and its peaking emissions level.

The most significant model/technical uncertainty factor on a global level was uncertainty in measuring historical emissions, which we estimate by using different historical datasets for all GHG emissions and land-use related emissions. The impact of the historical emissions variation remains high (about two-fifth of the overall uncertainty) due to the uncertainty in historical emissions, in particular for the variations in land-use emissions. The second most important model/technical uncertainty is socioeconomic (SSP) baseline variation, which contributes to about one-fifth of the overall uncertainty. Its impact is much lower compared to previous studies, where it contributes to about half. This is due to multiple causes: (i) although the intensity targets of China's and India's NDCs still contribute largely to overall uncertainty, its impact is lower than before, as both countries do not have a range in their intensity targets anymore. In addition, China's non-fossil and peaking targets hold greater significance for NDC emissions projections as its intensity targets are already achieved under the current policies scenario. (ii) The group of countries with updated NDC targets that could not be quantified now only covers less than 5% of global emissions. For these countries, current policy emission levels were assumed and therefore the uncertainty in current policy projections has a lower impact. (iii) There are more countries with GHG targets representing about 60% of global emissions, which results in less variation due to differences in socio-economic baseline assumptions.

The analysis improves our understanding of NDCs by identifying which factors generate high uncertainty and/or are not sufficiently defined. Our results also have implications for the global stocktake tool process as they indicate policy measures to reduce uncertainties in future NDC updates. Policy uncertainty, for example, is related to how governments decide to formulate their NDCs. Thus, it could be reduced by policy choices that remove ambiguity or improve transparency and comparability to NDCs. Although this was also recommended by earlier studies, our results suggests lack of progress towards these recommendations to date. Some options to reduce policy uncertainty include:

• Improving national emission inventories which would clarify base year targets
• Submitting national emission projections under current policies to clarify baseline targets
• Providing assumptions of economic development to clarify intensity targets and
• Increasing the NDCs scope to cover all economic sectors and all GHGs