Main blocker is that it's unclear which of the many air quality models are most accurate in the mountains. I tried reaching out to the team leads by phone and email but no luck there.
The New York Times uses HRRR ("Rapid Refresh") in their wildfire/smoke map, but it's unclear whether this is the most accurate model for non-urban areas.
After that, it'll be some work to determine how to get a specific point's air quality value from their KMZ downloads (where each layer is a forecast at a point in time). And this'll probably be too big of a download and too computationally expensive to run every single time it's requested; we'll probably need an AWS Lambda that performs the work once every day (once the model has published) and pre-processes the results for various points along the trail, storing it in a JSON for the Twilio Function to fetch.
Main blocker is that it's unclear which of the many air quality models are most accurate in the mountains. I tried reaching out to the team leads by phone and email but no luck there.
The New York Times uses HRRR ("Rapid Refresh") in their wildfire/smoke map, but it's unclear whether this is the most accurate model for non-urban areas.
After that, it'll be some work to determine how to get a specific point's air quality value from their KMZ downloads (where each layer is a forecast at a point in time). And this'll probably be too big of a download and too computationally expensive to run every single time it's requested; we'll probably need an AWS Lambda that performs the work once every day (once the model has published) and pre-processes the results for various points along the trail, storing it in a JSON for the Twilio Function to fetch.