WRF-CHEM simulations of Unhealthy PM10 concentrations during Four Dust Events in Senegal
Winter season Saharan dust aerosols are transported into West Africa and pose as a natural hazard with individual dust events significantly reducing air quality. Because of the limited surface network of Particulate Matter (PM) measurements, there is significant uncertainty for each dust event. We simulate four multi-day dust events using the Weather, Research and Forecasting Chemistry (WRF-CHEM) in Senegal during December 2016, December 2017, February 2019, and March 2019. We use Geospatial Informational System (GIS) mapping to estimate PM10 concentrations for the fourteen administrative districts within Senegal. Saharan dust events are evaluated using surface PM10 concentrations at Dakar, Moderate Resolution Imaging Spectrometer (MODIS) Aerosol Optical Depth (AOD), Aerosol Robotic Network (AERONET), and the WRF-CHEM model to evaluate dust concentrations across Senegal. We show that north-south pressure gradients from southeast moving high-pressure systems over North Africa were responsible for dust generation and transport into Senegal during 2016 and 2017. Conversely, Saharan depressions moving across the Sahara Desert were responsible for the two high-impact dust events in February and March of 2019. Based on our analysis, the most severe of the four dust events impacting Senegal occurred in December 2017, with hazardous PM10 concentrations simulated for seven days affecting an estimated 86% of Senegal's population. A network of surface dust observations and forecasts are critical for protecting the Sahelian public from dangerous dust events. Together, they allow for preventative measures to minimize harmful PM10 concentration exposure, especially for children under five, the elderly, and those with existing respiratory and cardiovascular disease.
Files
Metadata
Work Title | WRF-CHEM simulations of Unhealthy PM10 concentrations during Four Dust Events in Senegal |
---|---|
Access | |
Creators |
|
Keyword |
|
License | CC BY-NC 4.0 (Attribution-NonCommercial) |
Work Type | Dataset |
Publisher |
|
Publication Date | October 1, 2022 |
Subject |
|
Language |
|
DOI | doi:10.26207/fhb3-3p24 |
Geographic Area |
|
Deposited | July 20, 2022 |
Versions
Analytics
Collections
This resource is currently not in any collection.