How different SSPs will affect air quality and human health: the DISTENDER project framework

The World Health Organization (WHO) estimates that air pollution causes seven million deaths annually. As climate change is expected to affect future air quality patterns, understanding the links between air pollution, climate change, and their health impacts remains a pressing research challenge. Addressing this challenge, this study, conducted within the HE Project DISTENDER, explores potential health impacts attributable to air pollution under four Shared Socio-Economic Pathways (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) across five European regions: Austria, the EURAF region (Montado-Dehesa in the Iberian Peninsula), the North-east Netherlands, metropolitan area of Turin (Italy), and urban area of Guimarães (Portugal). These diverse case studies span different characteristics in terms of sectors, scale, climate impacts, environmental, socioeconomic and cultural factors, and climate policy goals, enhancing the replicability of findings.

Air pollutant concentrations (PM10, PM2.5, NO₂) were assessed using the Gaussian model URBAIR^®, configured with spatial resolutions ranging from 9000 to 500 meters, depending on the domain. Simulations were performed for each year from 2015 to 2049 in two rounds. In Round1, the URBAIR simulations were using as input data the meteorological variables provided by the statistical downscaling of CanESM5, EC-EARTH3, and MPI-ESM1-2-HR global climate models (GCMs), for the selected SSPs scenarios, keeping land use and air pollutants emissions as in the present. In Round2a, the same meteorological variables of Round1 were used, but only considering EC-EARTH3 GCM, and land use and air pollutants emissions were changed according with each SSP narrative.

For both rounds, following the European Environmental Agency methodology and according to the WHO guidelines, concentration-response functions for different morbidity and mortality health indicators were used to estimate health impacts of long-term exposures, considering the modelled concentrations by grid cell and pollutant, together with population data stratified by age and sex. For Round1 population was kept as in the present, and in Round2a was updated following the SSP narratives.

In General, results indicate distinct trends in mortality and morbidity indicators related to air pollution for the coming years, depending on the case study and the GCM used. For Round1, for all case studies and GCMs, the SSP5-8.5 scenario (the one with higher climate change impacts) is the one that presents the highest number of cases for both mortality and morbidity. However, in Round2a, for each case study, it is possible to verify relevant differences between the results linked with each SSP scenario, as well as high interannual variability. These differences relative to Round1 are mainly determined by changes in: (i) land use; (ii) emissions; and (iii) population.

This study underscores the need for interdisciplinary methods to support climate-resilient development at regional and local levels. The analysis of multiple SSPs scenarios allow for a more complete view of the interactions between climate and air quality policies, allowing to support decision makers in the development of ‘win-win’ strategies that simultaneously improve air quality and limit climate change. The findings provide a basis for scalable strategies that address context-specific climate impacts and foster systemic transformations, supporting decision-makers in advancing resilient and sustainable development pathways.