Stratospheric impacts on dust transport and air pollution in West Africa and the Eastern Mediterranean

North Africa is the world's largest dust source, with strong winds lifting substantial amounts of dust into the atmosphere. This dust is transported towards the Atlantic and Mediterranean, impacting health, visibility, the environment, and economies. Saharan dust storms have been linked to significant mortality and morbidity in Europe. The economic costs are substantial, with billions of dollars lost annually in the Middle East and North Africa (MENA) region due to dust storms. Accurate dust forecasts are crucial for mitigating these impacts but current operational forecasts are limited to 2-5 days. Extending forecast lead times to weeks or months is necessary to allow medical, agricultural, and nautical stakeholders sufficient time to prepare. One potential method to achieve longer-range forecasts is to consider the impact of the stratosphere. Stratospheric variability, particularly sudden stratospheric warmings (SSWs), are known to influence surface weather and climate on subseasonal to seasonal timescales (2 weeks to 2 months). SSWs are characterized by a breakdown of the stratospheric polar vortex, leading to rapid warming and weakening of circumpolar winds. These events are predictable 1-2 weeks in advance and their surface impacts can last several weeks. The tropospheric response to SSWs often resembles a negative North Atlantic Oscillation (NAO), which influences dust transport from North Africa. This study investigates the previously unexplored connection between SSWs and African dust export to improve long-term prediction capabilities.

Numerous studies have examined the impacts of Saharan dust on various regions, particularly the Mediterranean and Atlantic coasts. Research has documented the health effects of dust storms, linking them to increased mortality and morbidity. The economic consequences are also significant, with studies quantifying substantial losses due to reduced visibility, infrastructure damage, and healthcare costs. Previous research has established the link between the North Atlantic Oscillation (NAO) and African dust export, showing that the NAO can influence the strength and direction of winds that transport dust. However, the connection between stratospheric phenomena, particularly sudden stratospheric warmings (SSWs), and African dust export remained largely unexplored. Existing dust forecast models typically offer only short-term predictions, limiting the ability to prepare for extended dust events. The potential for using stratospheric variability, such as SSWs, to enhance the predictability of dust transport has been recognized as a possible solution for these issues.

This research used two chemical transport models (CTMs), CESM2 and MERRA2, driven by MERRA2 meteorology, to simulate surface dust concentrations. The models were used to analyze the response of dust to SSW events. SSW events were defined by the reversal of zonal-mean westerlies at 60°N and 10 hPa in the MERRA2 reanalysis. 'SSW episodes' were defined as the 30-day periods following the onset of an SSW. 'Non-SSW episodes' were created by selecting 1000 sets of 30-day periods from extended winters without SSWs. Surface dust concentrations during SSW and non-SSW episodes were compared to quantify the dust response. The study also incorporated observations from several stations in West Africa and Greece, measuring PM10 concentrations and Aerosol Optical Depth (AOD) from AERONET, for model verification. These observational data were analyzed by regressing the sea level pressure (SLP) anomaly onto the PM10 time-series. To estimate changes in mortality due to PM2.5 exposure, a concentration-response factor from the Global Burden of Disease (GBD) study was applied to the model-simulated dust-source PM2.5 anomalies during SSW episodes. Statistical significance was assessed using two-tailed Student’s t-tests and Monte Carlo tests. The meteorological causes of the dipolar dust response were investigated by analyzing changes in surface wind fields (speed and direction) during SSW episodes compared to non-SSW episodes.

The study revealed a significant dipolar response of surface dust concentrations to SSWs. Chemical transport models showed a 20-30% increase in dust concentrations in the Eastern Mediterranean during SSW episodes and a 10-20% decrease in West Africa. This dipolar pattern was confirmed by observational data of PM10 concentrations and AOD. The increase in northward dust transport to the Eastern Mediterranean during SSWs was linked to increased southwesterly winds. The decrease in westward dust transport to West Africa was linked to weaker northeasterly trade winds and reduced surface wind speeds. On average, a single SSW resulted in 680–2460 additional premature deaths in the Eastern Mediterranean due to increased PM2.5 and prevented 1180–2040 premature deaths in West Africa due to decreased PM2.5. The magnitude of these mortality changes varied between the models. This variation reflects the uncertainty inherent in dust cycle modeling across different models. The agreement between model results and observational data of PM10 and AOD provides robust evidence for the stratospheric impacts on surface air pollution.

The findings demonstrate the significant influence of SSWs on African dust transport and air quality in West Africa and the Eastern Mediterranean. The dipolar response, with enhanced dust in the Eastern Mediterranean and reduced dust in West Africa, is a consequence of changes in large-scale meteorological patterns induced by SSWs. This effect establishes a negative NAO-like surface signal, leading to weakened subtropical ridge and changes in wind patterns. The impact on mortality highlights the importance of considering stratospheric variability in air quality forecasting and public health assessments. The ability to predict SSWs 1-2 weeks in advance provides a valuable opportunity for improved air quality warnings at subseasonal timescales, potentially allowing for proactive measures to mitigate health risks.

This study establishes a clear link between SSWs and large-scale changes in African dust transport and air pollution. The enhanced predictability of SSWs offers a new avenue for improving subseasonal air quality forecasting for West Africa and the Eastern Mediterranean, particularly for improving public health outcomes. Future research should investigate the interactions between SSWs, the NAO, and other climate patterns to refine predictions and develop more comprehensive air quality forecasting systems. In addition, further research into the specific health impacts of varying PM10 and PM2.5 concentrations at differing locations is necessary.

The study's reliance on two CTMs introduces model uncertainty. The limited number of ground-based observation stations, and the associated data gaps, might affect the representation of air quality changes. The mortality estimates rely on a concentration-response factor that has limitations and uncertainties. The use of PM10 instead of PM2.5 for the observational comparison also limits the direct comparison with mortality results. While the observed changes are statistically significant, the percentage changes vary across different regions and data sets, requiring cautious interpretation of the impact.