Use HYSPLIT back trajectory analysis and Google Earth to determine likely source regions for windblown dust.

Meteorology and Air Quality Studies

 

Learn about typical and anomalous air quality and meteorology in large city market (Mexico City, San Francisco, and Los Angeles. Take into consideration any other pandemics or societal impact air quality (smoke, dusk, ozone, etc.) has Work with raw data to get a feel for time alignment issues, make hourly averaged data, and use of Excel data base functions for making Diel averages (24 hour averages).

Doing a case study for diagnosing and understanding specific events.

Learn about and work with data from the sonic anemometer, low cost air quality sensor SPS30, photoacustic instrument, and the BAM1020 instrument used for PM measurements in cities to regulate air quality.

Use HYSPLIT back trajectory analysis and Google Earth to determine likely source regions for windblown dust.

Use remote sensing with the Cimel and MFRSR sunphotometer and spectral irradiance for obtaining column aerosol optical depth (AOD), with an eye towards satellite remote sensing of AOD.

Use Python to make wind roses and air pollution roses.

The post Use HYSPLIT back trajectory analysis and Google Earth to determine likely source regions for windblown dust. appeared first on Essay Lane.

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