Beyond the Limit: The estimated air pollution damages of overshooting the temperature target
Clàudia Rodés-Bachs1,2*, Laurent Drouet2,3, Peter Rafaj4, Massimo Tavoni2,3,5, Lara Aleluia Reis2,3,
1 Basque Center for Climate Change, Leioa, Spain
2 CMCC Foundation - Euro-Mediterraneo Center on Climate Change, Italy
3 RFF-CMCC European Institute on Economics and the Environment (EIEE), Italy
4 International Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, Austria
5 Politecnico di Milano, Milan, Italy
* corresponding author: [email protected]
Outdoor air pollution causes millions of premature deaths, illnesses, and economic losses, with 4.7 million deaths attributed to it in 2021 by the Global Burden of Disease. Climate change mitigation policies over the next decades could provide co-benefits by reducing air pollution. The Intergovernmental Panel on Climate Change AR6 report explores scenarios using a carbon budget approach -the net-zero pathways- designed to avoid temporary overshoot of the 1.5ºC temperature limit. We assess if net-zero pathways consistently improve air pollution outcomes using a global source-receptor air pollution model to estimate concentrations, health impacts, and economic damages. We analyze key uncertainties in air pollution-related mortality and damages, focusing on non-overshooting scenarios. Using multiple relative risk functions to estimate deaths and additional functions to calculate economic damage, we find that stringent climate policies, avoiding overshoot and keeping below 2ºC, offer significant health and economic co-benefits, particularly for China and India, and avoid 274 thousand premature deaths and 791 billion USD2020 in damages by 2030.
The global climate change mitigation scenario dataset analyzed in this study is available in Zenodo:
To reproduce the results and figures shown in Rodés-Bachs et al.,
- Install
R
here - https://www.r-project.org/ - Install
R studio
from here - https://www.rstudio.com/ - Run the script called
plt_figures_paper.R
chunk by chunk to generate the figures. - Run the script called
si_main.R
to generate the SI figures.