Historical diffusion of nuclear, wind and solar power in different national contexts: implications for climate mitigation pathways

Journal article, 2023

Climate change mitigation requires rapid expansion of low-carbon electricity but there is a disagreement on whether available technologies such as renewables and nuclear power can be scaled up sufficiently fast. Here we analyze the diffusion of nuclear (from the 1960s), as well as wind and solar (from the 1980-90s) power. We show that all these technologies have been adopted in most large economies except major energy exporters, but solar and wind have diffused across countries faster and wider than nuclear. After the initial adoption, the maximum annual growth for nuclear power has been 2.6% of national electricity supply (IQR 1.3%-6%), for wind - 1.1% (0.6%-1.7%), and for solar - 0.8% (0.5%-1.3%). The fastest growth of nuclear power occurred in Western Europe in the 1980s, a response by industrialized democracies to the energy supply crises of the 1970s. The European Union (EU), currently experiencing a similar energy supply shock, is planning to expand wind and solar at similarly fast rates. This illustrates that national contexts can impact the speed of technology diffusion at least as much as technology characteristics like cost, granularity, and complexity. In the Intergovernmental Panel on Climate Change mitigation pathways, renewables grow much faster than nuclear due to their lower projected costs, though empirical evidence does not show that the cost is the sole factor determining the speed of diffusion. We demonstrate that expanding low-carbon electricity in Asia in line with the 1.5 & DEG;C target requires growth of nuclear power even if renewables increase as fast as in the most ambitious EU's plans. 2 & DEG;C-consistent pathways in Asia are compatible with replicating China's nuclear power plans in the whole region, while simultaneously expanding renewables as fast as in the near-term projections for the EU. Our analysis demonstrates the usefulness of empirically-benchmarked feasibility spaces for future technology projections.