Understanding Air Quality Data

The Puget Sound Clean Air Agency recently had an opportunity to work with a small group of community scientists from the South Park and Georgetown neighborhoods in Seattle, WA. The community received a grant from the Port of Seattle for neighborhood air quality monitoring using portable, relatively inexpensive air sensors. The Agency worked with the group in two different workshops to teach the group more about air quality and how to analyze data.

In the first workshop, staff members from our planning, analysis and forecasting teams taught the group about air quality and how to use three different types of particulate sensors (PurpleAir, Dylos, and AirBeam 2). Over the next few months, the community group used the sensors to monitor the air quality in their neighborhoods. These sensors will remain property of the community even after their monitoring study ends, which is critical as it gives the community their own resources to communicate how air pollution impacts their community and keeps tools within the community itself.


After the community members completed their study we worked them to help analyze and understand the data collected from the sensors. The community members looked at their data at a high level, and then downloaded raw data to create graphs and summary statistics. This showed the community group the importance of the scientific method and hypothesis testing for future monitoring studies. Overall, the conclusion was that the air was cleaner than previously expected. This was a great learning opportunity for us at the Agency to know what some of the concerns and interests the community has and how we can support those efforts in the future.