This function is used to explore the conditions leading to exeedances of air quality limits. Currently the focus is on understanding the conditions under which daily limit values for PM10 are in excess of a specified threshold. Kernel density estimates are calculated and plotted to highlight those conditions.
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,
...
)A data frame minimally containing date and at least
three other numeric variables, typically ws, wd and a
pollutant.
x-axis variable. Mandatory.
y-axis variable. Mandatory
Mandatory. A pollutant name corresponding to a variable in
a data frame should be supplied e.g. pollutant = "nox"
The type of analysis to be done. The default is will produce a
single plot using the entire data. Other types include "hour" (for hour
of the day), "weekday" (for day of the week) and "month" (for month of
the year), "year" for a polarPlot for each year. It is also possible to
choose type as another variable in the data frame. For example,
type = "o3" will plot four kernel exceedance plots for different
levels of ozone, split into four quantiles (approximately equal numbers
of counts in each of the four splits). This offers great flexibility for
understanding the variation of different variables dependent on another.
See function cutData for further details.
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" will select only those data above limit on days where
the daily mean value is above limit. by = "hour" will
select all data above limit.
The threshold above which the pollutant concentration
will be considered.
The data capture threshold to use (
the data using 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. Conversely, a value of 100 will mean
that all data will need to be present for the average to be calculated,
else it is recorded as NA.
If TRUE data will be selected that are greater than
limit. If FALSE data will be selected that less than
limit.
Colours to be used for plotting. Options include "default",
"increment", "heat", "spectral", "hue", "brewer1" and user defined (see
manual for more details). The same line colour can be set for all
pollutant e.g. cols = "black".
number of bins to be used for the kernel density estimate.
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.
Other graphical parameters passed onto lattice:levelplot
and cutData. For example, kernelExceed passes the option
hemisphere = "southern" on to cutData to provide southern
(rather than default northern) hemisphere handling of type = "season".
Similarly, common axis and title labelling options (such as xlab,
ylab, main) are passed to levelplot via quickText
to handle routine formatting.
To be completed.
The kernelExceed 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.
# NOT RUN {
# Note! the manual contains other examples that are more illuminating
# basic plot
kernelExceed(mydata, pollutant = "pm10")
# condition by NOx concentrations
# }
# NOT RUN {
kernelExceed(mydata, pollutant = "pm10", type = "nox")
# }
# NOT RUN {
# }
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