In this episode I’m analyzing particulate matter air pollution data generated by wildfire smoke, which is a topic a bit closer to my everyday life (as opposed to the previous episode). Here, I’m trying to look at how the chemical composition of PM air pollution changes when there are wildfires. Wildfires represent a specific source of PM air pollution (in addition other sources like traffic, power plants, etc.) and they are relatively infrequent. I’m interested in seeing how the chemical composition of the PM that we inhale changes when wildfire smoke blows into populated areas.
In this analysis, I’m using data that was generated using a 3D chemical transport model called GEOS-CHEM. This model can tell us on a given day, in a given location, how much of the airborne particles came from wildfires. Using this information, we can define certain days as “smoke wave days” (analogous to heat wave days) when there is a high proportion of PM generated from wildfires.
Compare the chemical composition of airborne PM on smoke wave days versus non-smoke wave days.
Ultimately, we would want to know whether these changes in chemical composition make the PM more or less harmful, but that analysis will have to be in a future video.
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