Calculate a range of air pollution-relevant statistics by year.
aqStats(mydata, pollutant = "no2", type = "default", data.thresh = 0, percentile = c(95, 99), transpose = FALSE, ...)
A data frame containing a
The name of a pollutant e.g.
The data capture threshold in
if data capture over the period of interest is less than this value.
Percentile values to calculate for each pollutant.
The default is to return a data frame with columns
representing the statistics. If
Other arguments, currently unused.
This function calculates a range of common and air pollution-specific
statistics from a data frame. The statistics are calculated on an annual
basis and the input is assumed to be hourly data. The function can cope with
several sites and years e.g. using
type = "site". The user can control the output by setting
Note that the input data is assumed to be in mass units e.g. ug/m3 for all species except CO (mg/m3).
The following statistics are calculated:
data.capture --- percentage data capture over a full year.
mean --- annual mean.
minimum --- minimum hourly value.
maximum --- maximum hourly value.
median --- median value.
max.daily --- maximum daily mean.
max.rolling.8 --- maximum 8-hour rolling mean.
max.rolling.24 --- maximum 24-hour rolling mean.
percentile.95 --- 95th percentile. Note that several percentiles can be calculated.
roll.8.O3.gt.100 --- number of days when the daily maximum rolling 8-hour mean ozone concentration is >100 ug/m3. This is the target value.
roll.8.O3.gt.120 --- number of days when the daily maximum rolling 8-hour mean ozone concentration is >120 ug/m3. This is the Limit Value not to be exceeded > 10 days a year.
AOT40 --- is the accumulated amount of ozone over the threshold
value of 40 ppb for daylight hours in the growing season (April to
September). Note that
longitude can also be
passed to this calculation.
hours.gt.200 --- number of hours NO2 is more than 200 ug/m3.
days.gt.50 --- number of days PM10 is more than 50 ug/m3.
For the rolling means, the user can supply the option
can be "centre" (default), "left" or "right". See
There can be small discrepancies with the AURN due to the treatment of
rounding data. The
aqStats function does not round, whereas AURN data
can be rounded at several stages during the calculations.
## Statistics for 2004. NOTE! these data are in ppb/ppm so the ## example is for illustrative purposes only aqStats(selectByDate(mydata, year = 2004), pollutant = "no2")#> # A tibble: 1 x 15 #> # Groups: default, pollutant, year  #> default pollutant year date dat.cap mean min max median #> <fct> <chr> <dbl> <dttm> <dbl> <dbl> <int> <int> <dbl> #> 1 01 Jan~ no2 2004 2004-01-01 00:00:00 99.8 55.0 0 185 51 #> # ... with 6 more variables: max_daily <dbl>, roll_8_max <dbl>, #> # roll_24_max <dbl>, percentile.95 <dbl>, percentile.99 <dbl>, hours <int>