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airnow

airnow is an R package for querying and retrieving air quality information from AirNow via the AirNow API. Current and historical readings as well as forecasts can be retrieved as tidy data frames.

Installation

You can install the stable version of airnow from CRAN:

If you’d like to try out the development version of airnow, you can install directly from GitHub:

# install.packages("remotes")
remotes::install_github("briandconnelly/airnow")

Creating an API Key

The AirNow API is generally free to use. The set_airnow_key() function can be used to help you create and configure your API key.

Examples

Current air quality in Seattle

The AirNow API allows you to query air conditions either by ZIP code or latitude/longitude. Here, we’ll get the current conditions in Seattle by ZIP code:

library(airnow)

get_airnow_observations(zip = "98101")
#> # A tibble: 3 × 21
#>   date_observed hour_observed local_time_zone utc_datetime        reporting_area
#>   <date>                <int> <chr>           <dttm>              <chr>         
#> 1 2026-09-12               14 PDT             2026-09-12 21:00:00 Seattle-Belle…
#> 2 2026-09-12               14 PDT             2026-09-12 21:00:00 Seattle-Belle…
#> 3 2026-09-12               14 PDT             2026-09-12 21:00:00 Seattle-Belle…
#> # ℹ 16 more variables: reporting_area_code <chr>, reporting_area_agency <chr>,
#> #   state_code <chr>, latitude <dbl>, longitude <dbl>, site_id <chr>,
#> #   site_name <chr>, reporting_agency <chr>, parameter <fct>, aqi <int>,
#> #   category_number <int>, category_name <ord>, lookup_behavior <chr>,
#> #   considered_monitors <chr>, lookup_boundary <chr>, source <fct>

Tomorrow’s forecast for Napa, by reporting area

Every location belongs to an AirNow reporting area. The bundled airnow_areas table lists them, and get_airnow_reporting_area() finds the one for a ZIP code or coordinate pair.

get_airnow_reporting_area(zip = "94558")
#> # A tibble: 1 × 5
#>   reporting_area_code reporting_area state_code latitude longitude
#>   <chr>               <chr>          <chr>         <dbl>     <dbl>
#> 1 ca064               Napa           CA             38.3     -122.

get_airnow_forecasts(area = "ca064")
#> # A tibble: 6 × 14
#>   date_issue date_valid reporting_area reporting_area_code state_code latitude
#>   <date>     <date>     <chr>          <chr>               <chr>         <dbl>
#> 1 2026-09-12 2026-09-12 Napa           ca064               CA             38.3
#> 2 2026-09-12 2026-09-13 Napa           ca064               CA             38.3
#> 3 2026-09-12 2026-09-14 Napa           ca064               CA             38.3
#> 4 2026-09-12 2026-09-15 Napa           ca064               CA             38.3
#> 5 2026-09-12 2026-09-16 Napa           ca064               CA             38.3
#> 6 2026-09-12 2026-09-17 Napa           ca064               CA             38.3
#> # ℹ 8 more variables: longitude <dbl>, parameter <fct>, aqi <int>,
#> #   category_number <int>, category_name <ord>, action_day <lgl>,
#> #   discussion <chr>, forecast_agency <chr>

Find the site with the lowest air quality near Washington state 

library(airnow)
library(dplyr)

get_airnow_monitors(
  box = c(-125.394211, 45.295897, -116.736984, 49.172497),
  verbose = TRUE
) |>
  slice_max(order_by = aqi, n = 1) |>
  select(site_name, site_agency, latitude, longitude, aqi, datetime_observed)
#> # A tibble: 1 × 6
#>   site_name site_agency             latitude longitude   aqi datetime_observed  
#>   <fct>     <fct>                      <dbl>     <dbl> <int> <dttm>             
#> 1 Troy      Idaho Department of En…     46.7     -117.    67 2026-09-12 20:00:00

Disclaimer

This package and its author are not affiliated with AirNow or its partners. See the Data Exchange Guidelines for more details about this data set and how it should be used. Data are typically refreshed once per hour. Please be kind to this service and limit your request rate.