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.
Publications using the AirSensor2 package
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Jul, 2023 – EGUSphere
https://doi.org/10.5194/egusphere-2023-1031
A model for rapid wildfire smoke exposure estimates using routinely-available data - rapidfire v0.1.3
Publications using the AirSensor package
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 dataMar, 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 ScienceFeb, 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 sensorsJan, 2022 – Journal of Aerosol Science
https://doi.org/10.1016/j.jaerosci.2021.105872
Tutorial: Guidelines for implementing low-cost sensor networks for aerosol monitoringDec, 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