Air-Quality

Exploring data-driven solutions for local environmental groups.

Summary

An internal incubator project for the Code for Chicago Brigade. Using publicly available datasets (from sources such as EPA, PurpleAir, and Chicago Data Portal), this project aims to examine the air quality measures throughout Chicago and explore data-driven solutions for local environmental groups.

Possible explorations include studying correlations between air quality and socioeconomic indicators, developing localized air quality reports and warnings.

Getting Started

1. Clone the repository.
2. Set up a local environment using the requirements.txt file.
   pip install -r requirements.txt
3. Obtain an EPA AirNow API key here and a PurpleAir API key by emailing [email protected]
4. Create a file called .env in the root directory. This file is ignored via the .gitignore file to avoid committing secrets.
5. Open .env in a text editor and add the following as the contents, replacing the second part with your personal API key:

EPA_KEY='REPLACE_ME_WITH_AIRNOW_API_KEY'
PURPLE_AIR_KEY='REPLACE_ME_WITH_PURPLE_AIR_API_READ_KEY'

AirNow Sensor Map

The map above highlights the lack of official air quality sensors in more urban and industrial areas of Chicago. This map can be created by running src > visualization > map_airnow_sensors.py

Questions to Explore

1. How well is the AirNow data correlated with more localized PurpleAir sensors?
   • Start with PurpleAir sensors in the vicinity of McKinley Park
2. Can we use open PurpleAir data to create more localized air quality reports and warnings?
3. Are the AirNow sensors equitably located?
   • Use Census or Social Vulnerability Index data

Contributing

If you have a feature request or notice a bug, please add an issue. If you would like to contribute to the code base, but are unsure how, please check out the First Contributions repository.