In MazamaScience/AirSensor2: Process and Display Data from Air Quality Sensors

knitr::opts_chunk$set(echo = TRUE)

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

• 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 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

MazamaScience/AirSensor2 documentation built on Oct. 31, 2024, 1:39 a.m.