Low-Cost Air Quality Monitoring Packages

Developed by Mike Bergin Lab at Duke University


This website provides detailed instructions on how to assemble low-cost air quality sensor packages as designed by researchers in Professor Mike Bergin's lab at Duke University. These sensor packages are designed to measure fine particulate matter (PM2.5), ozone (O3), and carbon dioxide (CO2). PM2.5 and O3 are two of the most important air pollutants for human health. These sensor packages have been used successfully by our lab and collaborators around the world to answer a number of research questions and to provide individuals with information about what they are exposed to in the air they breathe. They've been used to monitor air quality in schools in Durham, North Carolina, the exposure of asthmatic children in China to air pollutants, indoor air quality in homes with cook stoves in low-income countries (e.g., India), and have been used to monitor indoor and outdoor air quality and personal exposure in a number of other settings worldwide.

These sensors currently log one-minute PM2.5, O3, CO2, temperature, and relative humidity data to a time-stamped CSV file. They can be installed in cases for indoor, outdoor or personal monitoring and, depending on your application, there are a number of modifications you can make (e.g., changing the data averaging time, including different gas sensors). This document outlines how to build and prepare your own sensors. The information in each tab of this website is as follows:

  • Materials and equipment: All components needed to assemble your own sensor packages
  • Enclosures: Depending on your application and budget you will need to decide what type of enclosure will work best for your sensor application and assemble it
  • PCB: Printed circuit board and all electronic components needed to run the sensors
  • Sensor software: Code and SD card txt files that run the teensy microcontroller and store data, and how to install these
  • Field deployment: Information on how to test sensor packages once they are assembled, setting up sensors in the field, and common problems
  • Data visualization: R-shiny app for data processing and visualization