openair (version 2.19.0)

selectRunning: Function to extract run lengths greater than a threshold

Description

This is a utility function to extract runs of values above a certain threshold. For example, for a data frame of hourly NOx values we would like to extract all those hours where the concentration is at least 500 for contiguous periods of 5 or more hours.

Usage

selectRunning(
  mydata,
  pollutant = "nox",
  criterion = ">",
  run.len = 5L,
  threshold = 500,
  type = "default",
  name = "criterion",
  result = c("yes", "no"),
  mode = c("flag", "filter"),
  ...
)

Value

A data frame

Arguments

mydata

A data frame with a date field and at least one numeric pollutant field to analyse.

pollutant

Name of variable to process.

criterion

Condition to select run lengths e.g. ">" with select data more than threshold.

run.len

Run length for extracting contiguous values of pollutant meeting the criterion in relation to the threshold.

threshold

The threshold value for pollutant above which data should be extracted.

type

Used for splitting the data further. Passed to cutData().

name

The name of the column to be appended to the data frame when mode = "flag".

result

A vector of length 2, defining how to label the run lengths when mode = "flag". The first object should be the label for the TRUE label, and the second the FALSE label - e.g., c("yes", "no").

mode

Changes how the function behaves. When mode = "flag", the default, the function appends a column flagging where the criteria was met. Alternatively, "filter" will filter mydata to only return rows where the criteria was met.

...

Additional parameters passed to cutData(). For use with type.

Author

David Carslaw

Details

This function is useful, for example, for selecting pollution episodes from a data frame where concentrations remain elevated for a certain period of time. It may also be of more general use when analysing air pollution and atmospheric composition data. For example, selectRunning() could be used to extract continuous periods of rainfall --- which could be important for particle concentrations.

Examples

# extract those hours where there are at least 5 consecutive NOx
# concentrations above 500 units
mydata <- selectRunning(mydata, run.len = 5, threshold = 500)

# make a polar plot of those conditions, which shows that those
# conditions are dominated by low wind speeds, not
# in-canyon recirculation
if (FALSE) {
polarPlot(mydata, pollutant = "nox", type = "criterion")
}