Characterization of aerosol sources in León (Spain) using Positive Matrix Factorization and weather types

Area of Science:

• Environmental Science
• Atmospheric Chemistry
• Air Quality Monitoring

Background:

• Particulate matter (PM10) poses significant air quality challenges in urban environments.
• Understanding the sources and transport of PM10 is crucial for effective pollution control strategies.
• Previous source apportionment studies often lack detailed integration with meteorological data.

Purpose of the Study:

• To identify and quantify sources of PM10 in a suburban area of León, Spain.
• To associate identified aerosol sources with specific atmospheric circulation weather types.
• To develop a predictive model for PM10 source apportionment using meteorological and chemical data.

Main Methods:

• Conducted a one-year aerosol sampling campaign (2016-2017).
• Applied Positive Matrix Factorization (PMF) to identify six primary aerosol sources: traffic, aged sea salt, secondary aerosols, dust, marine aerosol, and biomass burning.
• Developed linear models correlating PM10 concentrations and chemical composition with circulation weather types and geostrophic flow.

Main Results:

• Traffic (29%) and aged sea salt (26%) were the dominant PM10 sources.
• Specific weather patterns were linked to elevated levels of certain sources (e.g., traffic and secondary aerosols with cyclonic types, dust with northerly flows).
• Linear models showed strong correlations with PMF results, accurately predicting PM10 mass concentration based on meteorological and chemical variables.

Conclusions:

• The study successfully identified key PM10 sources in León and their relationship with atmospheric dynamics.
• The developed linear models provide a valuable tool for estimating PM10 source contributions using readily available meteorological and chemical data.
• This approach offers a practical method for air quality management and source-specific pollution assessment in the region.