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"
willpollutant 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. ConverseTRUE 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
(rather thkernelExceed 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