kernelExceed(polar, x = "wd", y = "ws",
pollutant = "pm10", type = "default",
by = c("day", "dayhour", "all"), limit = 50,
data.thresh = 0, more.than = TRUE, cols = "default",
nbin = 256, auto.text = TRUE, ...)date and at least three other numeric variables,
typically ws, wd and a pollutant.pollutant = "nox"by determines how data above the
limit are selected. by = "day" will select
all data (typically hours) on days where the daily
mean value is above limit. by = "dayhour"
pollutant concentration will be considered.timeAverage to
daily means. A value of zero means that all available
data will be used in a particular period regardless if of
the number of values available. ConveTRUE data will be selected
that are greater than limit. If FALSE data
will be selected that less than limit.cols = "black".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.lattice:levelplot and cutData. For example,
kernelExceed passes the option hemisphere =
"southern" on to cutData to provide southern
(rathekernelExceed functions is for exploring the
conditions under which exceedances of air pollution
limits occur. Currently it is focused on the daily mean
(European) Limit Value for PM10 of 50~ug/m3 not to be
exceeded on more than 35 days. However, the function is
sufficiently flexible to consider other limits e.g. could
be used to explore days where the daily mean are greater
than 100~ug/m3.
By default the function will plot the kernel density
estimate of wind speed and wind directions for all days
where the concentration of pollutant is greater
than limit. Understanding the conditions where
exceedances occur can help with source identification.
The function offers different ways of selecting the data
on days where the pollutant are greater than
limit through setting by. By default it
will select all data on days where pollutant is
greater than limit. With the default setting of
by it will select all data on those days where
pollutant is greater than limit, even if
individual data (e.g. hours) are less than limit.
Setting by = "dayhour" will additionally ensure
that all data on the those dates are also greater than
limit. Finally, by = "all" will select all
values of pollutant above limit, regardless of
when they occur.
The usefulness of the function is greatly enhanced
through using type, which conditions the data
according to the level of another variable. For example,
type = "season" will show the kernel density
estimate by spring, summer, autumn and winter and
type = "so2" will attempt to show the kernel
density estimates by quantiles of SO2 concentration. By
considering different values of type it is
possible to develop a good understanding of the
conditions under which exceedances occur.
To aid interpretation the plot will also show the
estimated number of days or hours where exeedances
occur. For type = "default" the number of days
should exactly correspond to the actual number of
exceedance days. However, with different values of
type the number of days is an estimate. It is an
estimate because conditioning breaks up individual days
and the estimate is based on the proportion of data
calculated for each level of type.polarAnnulus, polarFreq,
polarPlot# Note! the manual contains other examples that are more illuminating
# basic plot
kernelExceed(mydata, pollutant = "pm10")
# condition by NOx concentrations
kernelExceed(mydata, pollutant = "pm10", type = "nox")Run the code above in your browser using DataLab