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percentileMapStatic() creates a ggplot2 map using percentile roses as markers. As this function returns a ggplot2 object, further customisation can be achieved using functions like ggplot2::theme() and ggplot2::guides().


  pollutant = NULL,
  percentile = c(25, 50, 75, 90, 95),
  intervals = "fixed",
  latitude = NULL,
  longitude = NULL,
  facet = NULL,
  cols = "turbo",
  alpha = 1,
  key = FALSE,
  facet.nrow = NULL,
  d.icon = 150,
  d.fig = 3,



A data frame. The data frame must contain the data to plot the directional analysis marker, which includes wind speed (ws), wind direction (wd), and the column representing the concentration of a pollutant. In addition, data must include a decimal latitude and longitude.


The column name(s) of the pollutant(s) to plot. If multiple pollutants are specified, they will each form part of a separate panel.


A ggmap object obtained using ggmap::get_map() or a similar function to use as the basemap.


The percentile value(s) to plot. Must be between 0–100. If percentile = NA then only a mean line will be shown.


One of:

  • "fixed" (the default) which ensures all of the markers use the same radial axis scale.

  • "free" which allows all of the markers to use different radial axis scales.

  • A numeric vector defining a sequence of numbers to use as the intervals, e.g., intervals = c(0, 10, 30, 50).

latitude, longitude

The decimal latitude/longitude. If not provided, will be automatically inferred from data by looking for a column named "lat"/"latitude" or "lon"/"lng"/"long"/"longitude" (case-insensitively).


Used for splitting the input data into different panels, passed to the type argument of openair::cutData(). facet cannot be used if multiple pollutant columns have been provided.


The colours used for plotting. See openair::openColours() for more information.


The alpha transparency to use for the plotting surface (a value between 0 and 1 with zero being fully transparent and 1 fully opaque).


Should a key for each marker be drawn? Default is FALSE.


Passed to the nrow argument of ggplot2::facet_wrap().


The diameter of the plot on the map in pixels. This will affect the size of the individual polar markers. Alternatively, a vector in the form c(width, height) can be provided if a non-circular marker is desired.


The diameter of the plots to be produced using openair in inches. This will affect the resolution of the markers on the map. Alternatively, a vector in the form c(width, height) can be provided if a non-circular marker is desired.


Arguments passed on to openair::percentileRose


Name of wind direction field.


type determines how the data are split i.e. conditioned, and then plotted. The default is will produce a single plot using the entire data. Type can be one of the built-in types as detailed in cutData e.g. “season”, “year”, “weekday” and so on. For example, type = "season" will produce four plots --- one for each season.

It is also possible to choose type as another variable in the data frame. If that variable is numeric, then the data will be split into four quantiles (if possible) and labelled accordingly. If type is an existing character or factor variable, then those categories/levels will be used directly. This offers great flexibility for understanding the variation of different variables and how they depend on one another.

Type can be up length two e.g. type = c("season", "weekday") will produce a 2x2 plot split by season and day of the week. Note, when two types are provided the first forms the columns and the second the rows.


Should the wind direction data be smoothed using a cyclic spline?


When method = "default" the supplied percentiles by wind direction are calculated. When method = "cpf" the conditional probability function (CPF) is plotted and a single (usually high) percentile level is supplied. The CPF is defined as CPF = my/ny, where my is the number of samples in the wind sector y with mixing ratios greater than the overall percentile concentration, and ny is the total number of samples in the same wind sector (see Ashbaugh et al., 1985).


Default angle of “spokes” is when smooth = FALSE.


Show the mean by wind direction as a line?


Line type for mean line.


Line width for mean line.


Line colour for mean line.


Should the percentile intervals be filled (default) or should lines be drawn (fill = FALSE).


Sometimes the placement of the scale may interfere with an interesting feature. The user can therefore set angle.scale to any value between 0 and 360 degrees to mitigate such problems. For example angle.scale = 45 will draw the scale heading in a NE direction.


Either TRUE (default) or FALSE. If TRUE titles and axis labels will automatically try and format pollutant names and units properly e.g. by subscripting the `2' in NO2.


Adds additional text/labels to the scale key. For example, passing the options key.header = "header", key.footer = "footer1" adds addition text above and below the scale key. These arguments are passed to drawOpenKey via quickText, applying the auto.text argument, to handle formatting.


see key.footer.


Location where the scale key is to plotted. Allowed arguments currently include "top", "right", "bottom" and "left".


a ggplot2 plot with a ggmap basemap

Further customisation using ggplot2

As the outputs of the static directional analysis functions are ggplot2 figures, further customisation is possible using functions such as ggplot2::theme(), ggplot2::guides() and ggplot2::labs().

If multiple pollutants are specified, subscripting (e.g., the "x" in "NOx") is achieved using the ggtext package. Therefore if you choose to override the plot theme, it is recommended to use [ggplot2::theme()] and [ggtext::element_markdown()] to define the strip.text parameter.

When arguments like limits, percentile or breaks are defined, a legend is automatically added to the figure. Legends can be removed using ggplot2::theme(legend.position = "none"), or further customised using ggplot2::guides() and either color = ggplot2::guide_colourbar() for continuous legends or fill = ggplot2::guide_legend() for discrete legends.

See also

the original openair::percentileRose()

percentileMap() for the interactive leaflet equivalent of percentileMapStatic()

Other static directional analysis maps: annulusMapStatic(), diffMapStatic(), freqMapStatic(), polarMapStatic(), pollroseMapStatic(), windroseMapStatic()