Abstract
Projecting future climate change is important for implementing the 2015 Paris Agreement, which aims to limit greenhouse gas emissions to a level that would keep global average temperature increase to 2100 below 1.5°C, and in any event well below 2°C. The Intergovernmental Panel on Climate Change uses emissions scenarios for projecting climate change, but since 2017 an alternative fully statistical Bayesian probabilistic approach has been developed. This relies on the IPAT equation that expresses emissions as the product of population, Gross Domestic Product (GDP) per capita, and carbon intensity, namely carbon emissions per unit of GDP. Here we use data on population, GDP and emissions for 2015-2024 to assess probabilistically the changes in climate change prospects associated with post-Paris emissions.
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