Particulate matter pollution over a Mediterranean urban area.

Area of Science:

• Environmental Science
• Atmospheric Chemistry
• Air Quality Monitoring

Background:

• Particulate matter (PM) pollution is a significant environmental and health concern in urban areas.
• Understanding the spatial and temporal distribution of PM is crucial for developing effective air quality management strategies.
• Mediterranean urban regions like the Greater Athens Area (GAA) face complex air pollution challenges influenced by local emissions and regional transport.

Purpose of the Study:

• To investigate the spatial and temporal distribution of PM10, PM2.5, and PM1 in the Greater Athens Area.
• To analyze the influence of atmospheric circulation, local transport, and compare PM behavior with inorganic pollutants (NOx, O3).
• To evaluate the Comprehensive Air Quality Model with extensions (CAMx) for air pollution modeling in the GAA.

Main Methods:

• Conducted a sampling campaign during cold and warm periods of 2008 to collect data on PM10, PM2.5, and PM1.
• Analyzed the influence of synoptic circulation patterns and local transport mechanisms.
• Applied and evaluated the Comprehensive Air Quality Model with extensions (CAMx) against measurement data.

Main Results:

• Local sources like traffic and industry were identified as dominant contributors to PM loads, especially in 'hot spot' areas.
• Calm conditions and southerly flows exacerbated particulate pollution, affecting both urban and background stations. Saharan dust outbreaks increased particle size and exceedances of EU limit values.
• PM1 consistently formed the largest fraction of PM2.5 mass. PM10 was primarily composed of coarse particles, particularly during Saharan dust events.

Conclusions:

• Systematic and parallel monitoring and modeling of pollutant dispersion are essential for understanding and managing particulate pollution in the GAA.
• The findings support the need for targeted pollution control strategies based on source identification and meteorological influences.
• Numerical modeling, like CAMx, is a valuable tool for assessing air quality and informing policy decisions.