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Free keywords:
coal phase-out; coal transition; Integrated Assessment Models; technology learning; innovation; renewables
Abstract:
A rapid phase-out of unabated coal use is essential to limit global warming to below 2°C. This review
presents a comprehensive assessment of coal transitions in mitigation scenarios consistent with the
Paris Agreement, using data from more than 1500 publicly available scenarios generated by more than
30 integrated assessment models. Our ensemble analysis uses clustering techniques to categorize coal
transition pathways in models and bridges evidence on technological learning and innovation with
historical data of energy systems. Six key findings emerge: First, we identify three archetypal coal
transitions within Paris-consistent mitigation pathways. About 38% of scenarios are ‘coal phase out’
trajectories and rapidly reduce coal consumption to near zero. ‘Coal persistence’ pathways (42%)
reduce coal consumption much more gradually and incompletely. The remaining 20% follow ‘coal
resurgence’ pathways, characterised by increased coal consumption in the second half of the century..
Second, coal persistence and resurgence archetypes rely on the widespread availability and rapid
scale-up of carbon capture and storage technology (CCS). Third, coal-transition archetypes spread
across all levels of climate policy ambition and scenario cycles, reflecting their dependence on model
structures and assumptions. Fourth, most baseline scenarios – including the shared socio-economic
pathways (SSPs) - show much higher coal dependency compared to historical observations over the
last 60 years. Fifth, coal-transition scenarios consistently incorporate very optimistic assumptions
about the cost and scalability of CCS technologies, while being pessimistic about the cost and scalability
of renewable energy technologies. Sixth, evaluation against coal-dependent baseline scenarios
suggests that many mitigation scenarios overestimate the technical difficulty and costs of coal phase-
outs. To improve future research, we recommend using up-to-date cost data and evidence about
innovation and diffusion dynamics of different groups of zero or low-carbon technologies. Revised SSP
quantifications need to incorporate projected technology learning and consistent cost structures,
while reflecting recent trends in coal consumption.
