The Relationship between Observed and Modeled AOD and Surface PM10 during an Eastern Mediterranean Dust Event

Air pollution is a well-known environmental risk in many parts of the world, and depending on the geographic location, natural sources such as dust from deserts, smoke from wildfires and agricultural burning, and anthropogenic sources such as burning of fossil fuels can all be major contributors to poor air quality. In regions affected by pollution from mineral dust, such as Saharan dust, timely and accurate forecasts of air quality are especially valuable since excessive particulate matter (PM) occurrences from desert dust have a major impact on human health.

In order the to improve the future air quality forecasts of Saharan mineral dust transport over the Eastern Mediterranean, an online Weather Research and Forecasting model with chemistry (WRF-Chem) is configured with 0.1°×0.1° spatial resolution HTAP emission inventory to cover the region with 30km horizontal resolution. NOAA Gridpoint Statistical Interpolation (GSI) data analysis system is used to assimilate Moderate Resolution Imaging Spectoradiometer (MODIS (collection 6)) Terra and Aqua aerosol optical depth (AOD) retrievals over the region for April 2008. Real-time Air Quality Modeling System (RAQMS) 2°×2° global analyses is used to provide the lateral boundary conditions (LBC) for 30km run (30km_Assim). This is the first WRF-Chem DA study investigating natural dust influences on air quality in Anatolian peninsula.

Both WRF-Chem Control and WRF-Chem/GSI surface PM10 predictions are consistent with the ground observations as the model captures the spatial and temporal variability. The correlation between ground observations to the WRF-Chem Control run is found to be 0.47 and the correlation between ground observations WRF-Chem/GSI is found to be 0.52. Daily comparisons of the WRF-Chem Control and WRF-Chem/GSI to ground observations show that the both runs tend to underestimate the ground observations with observations minus model biases of 1.98 μg/m³ and 0.78 μg/m³, respectively. Comparisons between observed and modeled AOD and surface PM₁₀ show that AODs are more significantly correlated with the surface PM₁₀ concentrations in assimilation run than in control run. The lowest correlation between observed and modeled AODs and surface PM₁₀ are found during the high dust event day due to the aerosol lofting and decoupling from the surface.