Last updated April 29, 2026
This workshop will introduce participants to two open source R packages designed specifically for working with air quality data from regulatory monitors and low-cost sensors. The AirMonitor and AirSensor2 packages have been developed with funding from, and have been used by the US EPA, the US Forest Service and the South Coast Air Quality Management District. These R packages are part of a suite of R packages that provide core functionality for environmental monitoring at fixed locations. The full suite of packages represent a decade of continuous development with a focus on compact data formats, robust data analysis, compelling data visualization and a simple, easy-to-learn coding style.
Attendees will become familiar with the AirMonitor and AirSensor2 R packages and will be able to quickly download, process and visualize data from AirNow and sensor manufacturers PurpleAir, Clarity and AirGradient. Various analysis and data visualization functions will be introduced but the focus will be on data access and the creation of uniform dataframes of hourly measurements appropriate for use in research studies and reports.
The R packages presented provide functionality for data ingest and manipulation and are designed for individuals who sometimes need to work independently, i.e. without the support of IT staff. The target audience includes anyone who works with Air Quality data from regulatory monitors and low cost sensors and who is a regular user of R/RStudio. Attendees should have a basic understanding of R data types and common functions. Familiarity with the dplyr package will be especially helpful.
Over the last decade, Jonathan Callahan has been responsible for the creation of multiple open source R packages focused on environmental monitoring time series. These are used operationally in data processing, analysis and visualization systems at the US Forest Service AirFire Team, in the EPA AirNow Fire & Smoke map and elsewhere.
The following R packages are actively maintained:
- MazamaRollUtils – Fast rolling functions for R written in C++
- MazamaCoreUtils – Utilities to help write production R code
- MazamaSpatialUtils – Harmonized spatial datasets and spatial search functions
- MazamaLocationUtils – Utilities for working with monitoring site “known locations”
- MazamaTimeSeries – Core functionality for environmental time series data
- AirMonitor – Utilities for working with air quality monitoring data
- AirMonitorPlots – Plotting functions for the AirMonitor package
- AirSensor2 – Utilities for working with data from low-cost air quality sensors
Each package has a dedicated Slack channel for announcements, support and to help build communities of practice around these shared tools. You may request an invitation to join from jonathan.callahan@dri.edu.
Attendees are strongly encouraged to install the required packages and data files before the workshop begins.
As with any hands-on workshop, advanced preparation by individuals will allow us to quickly start working with data. Please ensure that the following software and data files have been installed on your laptop in advance of the workshop:
This workshop is designed for those who are already familiar with R and RStudio and use them on a regular basis.
Ensure that you are running R version 4.4 or higher.
Ensure that you have installed RStudio Desktop version 2025.09 or higher.
Most (but not all) of the packages we will be using are available on CRAN. However, several packages have been updated in preparation of this workshop. Please install the latest versions of these packages from GitHub.
Type the following commands at the RStudio Console prompt to get fully updated:
install.packages("AirMonitor")
install.packages("devtools")
devtools::install_github("mazamascience/MazamaCoreUtils")
devtools::install_github("mazamascience/MazamaTimeSeries")
devtools::install_github("mazamascience/AirMonitor")
devtools::install_github("mazamascience/AirMonitorPlots")
devtools::install_github("mazamascience/AirSensor2")
The MazamaSpatialUtils package is used to enhance spatial metadata when ingesting sensor data. Simplified spatial datasets for countries and timezones are installed with the package but other, larger datasets must be installed manually in a dedicated directory. Work with the AirSensor2 package requires installation of datasets with state and county boundaries.
The default location for spatial data used in this workshop is underneath
your home directory in ~/Data/Spatial/. The following chunk of code will
create this directory and populate it with the required datasets.
At the RStudio Console prompt type:
dir.create("~/Data/Spatial", recursive = TRUE)
MazamaSpatialUtils::setSpatialDataDir("~/Data/Spatial")
MazamaSpatialUtils::installSpatialData("NaturalEarthAdm1")
MazamaSpatialUtils::installSpatialData("USCensusCounties")
Finally, you should install all of the documentation, data and scripts for this workshop by cloning this repository.
You can create a new project from a GitHub repository by using the RStudio menubar:
- File > New Project...
- Version Control > Git
- URL: https://github.com/MazamaScience/ASIC-2026.git
Choose a directory into which to clone the repository, check "Open in new session" and then press "Create Project".
If you prefer, you can use a separate terminal window or the RStudio Terminal window to issue a shell command to clone the GitHub repository.
At the terminal prompt, type:
git clone git@github.com:mazamascience/ASIC-2026.git
If you don't have a git account or can't log in, you may need to use the https location:
git clone https://github.com/MazamaScience/ASIC-2026.git
During the workshop, we will work through the numbered scripts found in
R_workshop/R/:
R/
├── 01_AirMonitor_recipes.R
├── 02_AirSensor2_PurpleAir_recipes.R
└── 03_AirSensor2_OpenAQ_recipes.R
Each of these scripts is well commented so that anyone should be able to work through them in order if you have installed the necessary libraries and datasets.
Interim datasets obtained using API keys have been saved to the data/ directory
so that you can follow along even if you don't have any API keys.
Congratulations!
You have finished installing all required software for this workshop.