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Deliverable 2.4

Filed in Deliverables

Comparing Sectoral and Technological Transformation in National NDC and 2°C/1.5°C Pathways

 

The present contribution goes beyond traditional ‘gap analysis’, in terms of aggregate emissions, to provide a systemic analysis of the ‘transformation gap’ between national NDC and ‘well below 2°C’/1.5°C scenarios. We use the decarbonisation wedges methodology elaborated by Mathy et al. (2018) which allows quantifying the impact of contrasted sectoral development assumptions and of potential structural change of the economy on mitigation strategy analysis. The methodology is applied to five EU countries: Germany, Italy, France, Poland and UK and to global mitigation scenarios.

Results show the diversity in mitigation actions between Western European countries and Eastern European countries where strong growth of economic and sectoral activities and the coal-intensive energy system raise major mitigation issues.

Whether at the level of European countries or at the global level, the contribution of the
decarbonisation of energy carriers increases over time and takes an important role in emission reductions after 2030 as the introduction of new energy vectors necessitates time for development of new infrastructure. The techno-economic feasibility and realism of the high level of energy decarbonisation required after 2030 in NDC scenarios is questionable: carbon capture and storage (CCS) and coal/gas substitution are massively required only after 2030 to decarbonise the power sector. Additional demand-side mitigation actions, the penetration of renewables and an early but gradual decrease in coal capacity in the power sector are the major additional wedges needed to increase NDC ambition before 2030.

This work provides methodological lessons for improving low-carbon scenario modelling approaches and highlights the need to make assumptions on the evolution of sectoral activities more transparent and to systematise the development of contrasted alternatives on structural transformation assumptions.

 

Published: 31st July 2018
Author: S. Mathy et al.