This repository contains scripts for analyzing particular matter data collected at Burning Man in 2019 using code from this repository, which was installed on a Raspberry Pi Zero connected to a RTC and an SDS-011 PM2.5/10 sensor.
data
├────dust
│ └───dusty.csv
├────weather
│ └───gerlack_weather.csv
├────gps
│ └───*.gpx
└────bm2019_pm_data.csv
README.md
combine_data.py
get_weather.py
Fetching Weather data requires a weather underground API key. You can sign up for one if you have a weather station, then use get_weather.py to get weather data. You will need to load the api key as an environment variable like so (if your api key was 1234567890):
export WEATHER_COM_API_KEY=1234567890
However the data from Gerlach for Burning Man 2019 has already been fetched and is in data/weather/gerlach_weather.csv.
This visualization is derived (with minimal edits) from Leaflet.Timeline's Earthquake example. It requires that the air quality data (data/dust/dusty.csv) and GPS data (data/gps/*.gpx) has been merged and subsequently converted to geojson format and stored in the data directory when running the python combine_data.py command.
The leaflet.timeline.js file was compiled using this repo, with an updated package.json that can be found in leaflet/leaflet-timeline-package.json.
git clone https://github.com/skeate/Leaflet.timeline.git
cp leaflet/leaflet-timeline-package.json Leaflet.timeline/package.json
cd Leaflet.timeline
npm install
npm run build
cp dist/leaflet.timeline.js ../leaflet/
World Health Organization Air Quality Guidelines
- 10 μg/m3 annual mean
- 25 μg/m3 24-hour mean
- 20 μg/m3 annual mean
- 50 μg/m3 24-hour mean
- 12 μg/m3 annual mean
- 35 μg/m3 24-hour mean
- 150 μg/m3 24-hour mean
- Link to wind data from Black Rock Airport.
- Link to photos for visual dust confirmation.
- Fix timezone on map.