The AirQuality_demo.ipynb notebook highlights some of the analytics and visualization capabilities of Fire Alarm: Science Data Platform for Wildfire and Air Quality with eight use cases:

• 2023 Canadian Wildfires Impacting New York Air Quality
• 2021 Alisal Wildfire
• 2021 California Wildfires
• 2018 Carr Wildfire
• Los Angeles ports backlog Fall 2021
• Fireworks during 4th of July 2022 in Los Angeles county
• Predicting What We Breathe Los Angeles PM2.5 predictions
• OCO-3 Snapshot Area Map data:
  • Impact of the COVID-19 pandemic response to CO2 emissions
  • Bełchatów Power Station, Poland: Do observed emissions match reported emissions?

Requirements

• conda >= 22.9.0

• OS: Mac (more OS options to come)

Running the notebook

To run the AirQuality_demo.ipynb notebook, run the following commands that create a conda environment called firealarm_notebook using the environment.yml file to include all required dependencies, and install the environment as a kernelspec:

conda env create -f environment.yml
conda activate firealarm_notebook
pip install notebook
pip install ipykernel
python -m ipykernel install --user --name=firealarm_notebook
jupyter notebook

From the localhost page that opens, you can run the ideas notebook. Make sure you change the kernel by selecting the option at the top Kernel -> Change kernel -> ideas_notebook (see here for more information).