A Gini approach to spatial CO2 emissions

TL;DR

This study introduces a Gini-based metric to analyze the spatial distribution of CO2 emissions relative to population density, revealing country-specific patterns and implications for climate policy.

Contribution

It develops a novel Gini-like indicator to quantify the spatial inequality of CO2 emissions in relation to population distribution across countries.

Findings

Developing countries have higher emissions in densely populated areas.

Developed countries show higher emissions in less populated regions.

Urban scaling relates to CO2 emission patterns and socio-economic development.

Abstract

Combining global gridded population and fossil fuel based CO2 emission data at 1km scale, we investigate the spatial origin of CO2 emissions in relation to the population distribution within countries. We depict the correlations between these two datasets by a quasi-Lorenz curve which enables us to discern the individual contributions of densely and sparsely populated regions to the national CO2 emissions. We observe pronounced country-specific characteristics and quantify them using an indicator resembling the Gini-index. Relating these indices with the degree of socio-economic development, we find that in developing countries locations with large population tend to emit relatively more CO2 and in developed countries the opposite tends to be the case. Based on the relation to urban scaling we discuss the connection with CO2 emissions from cities. Our results show that general statements with regard to the (in)efficiency of large cities should be avoided as it is subject to the socio-economic development of respective countries. Concerning the political relevance, our results suggest a differentiated spatial prioritization in deploying climate change mitigation measures in cities for developed and developing countries.