In davidcarslaw/openairmaps: Create Maps of Air Pollution Data

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  message = FALSE,
  warning = FALSE,
  out.width = "100%"
)

This vignette outlines some core functionality in {openairmaps}. For further examples, please see the online book.

library(openairmaps)

Access UK Monitoring Data with Lat/Lng Information

openair::importUKAQ() has the meta argument which appends the latitude and longitude of each site to the returned data. If not using data from importUKAQ(), ensure that your data has coordinate data appended in a similar way.

london_data <-
  openair::importUKAQ(site = c("my1", "hors", "cll2"),
                      year = 2020,
                      meta = TRUE)

london_data

names(london_data)

To find sites to import data from, you can visualise UK monitoring networks using networkMap(). Alternatively, searchNetwork() will allow you to target a specific region.

networkMap(source = c("aurn", "aqe"),
           year = 2020,
           control = "variable")

Polar Plot Maps

The polarMap() family includes polarMap(), annulusMap(), freqMap(), percentileMap(), windroseMap(), pollroseMap(), and diffMap(), and all work similarly to create interactive air quality maps:

polarMap(london_data,
         c("no2", "pm10"), 
         popup = c("site", "site_type"),
         label = "site")

By setting static to TRUE you will receive a static version of the map, which may be more useful for academic articles.

polarMap(london_data,
         c("no2", "pm10"),
         static = TRUE,
         d.icon = 100)

Trajectory Maps

trajMap() has almost identical arguments to openair::trajPlot(), and likewise trajLevelMap() with openair::trajLevel().

trajMap(traj_data, colour = "pm10")

trajLevelMap(traj_data)

davidcarslaw/openairmaps documentation built on March 1, 2025, 7:50 p.m.