The AirSensor2 package’s predecessor, the AirSensor package has been widely used in air quality analysis throughout North America and the world. This document provides links to projects and publications that mention the AirSensor or AirSensor2 packages.
Jul, 2023 – Frontiers in Environmental
Science
https://doi.org/10.3389/fenvs.2023.1223160
Developing high-resolution PM2.5 exposure models by integrating low-cost
sensors, automated machine learning, and big human mobility
data
Mar, 2022 – Sensors for Indoor and Outdoor Air Quality
Monitoring: From Research to Citizen Science Applications
https://doi.org/10.3390/s22072543
Towards the
Development of a Sensor Educational Toolkit to Support Community and
Citizen Science
Feb, 2022 – Environmental Modeling &
Software
https://doi.org/10.1016/j.envsoft.2021.105256
AirSensor v1.0: Enhancements to the open-source R package to enable deep
understanding of the long-term performance and reliability of PurpleAir
sensors
Jan, 2022 – Journal of Aerosol Science
https://doi.org/10.1016/j.jaerosci.2021.105872
Tutorial: Guidelines for implementing low-cost sensor networks for
aerosol monitoring
Dec, 2020 – Environmental Modeling &
Software
https://doi.org/10.1016/j.envsoft.2020.104832
The
AirSensor open-source R-package and DataViewer web application for
interpreting community data collected by low-cost sensor
networks