Cities: Allocating climate change responsibilities at planetary scale

Abstract

Computing global cities' carbon footprints is core in allocating regional climate change responsibilities and cutting urban carbon emissions. However, cities' carbon footprint of the Global North are better documented than those in the Global South. Although cities belonging to developing countries, especially African and Asian cities, are growing significantly in terms of size, population, GDP, their carbon footprint remains poorly documented in the scientific literature. Cities' carbon footprints inventories of the Global South are usually hampered by (i) lack of local urban emissions data, (ii) reduced climate footprint, and (iii) shortages in climate finance. To bridge this gap, we aim to estimate 24,110 cities' carbon footprints using machine learning algorithms to provide a comprehensive analysis on a planetary scale, while allocating responsibilities according to the cities' regions and sizes. The findings highlight that such a granular approach can enhance future global climate collaboration by erupting a robust local, and thus global, climate-friendly actions and increase peer-cities climate readiness.