Calculate summary statistics for air pollution data by year

Calculate a range of air pollution-relevant statistics by year.

Usage

aqStats(
  mydata,
  pollutant = "no2",
  type = "default",
  data.thresh = 0,
  percentile = c(95, 99),
  transpose = FALSE,
  ...
)

Arguments

mydata: A data frame containing a date field of hourly data.
pollutant: The name of a pollutant e.g. pollutant = c("o3", "pm10").
type: type allows timeAverage() to be applied to cases where there are groups of data that need to be split and the function applied to each group. The most common example is data with multiple sites identified with a column representing site name e.g. type = "site". More generally, type should be used where the date repeats for a particular grouping variable.
data.thresh: The data capture threshold in %. No values are calculated if data capture over the period of interest is less than this value. data.thresh is used for example in the calculation of daily mean values from hourly data. If there are less than data.thresh percentage of measurements available in a period, NA is returned.
percentile: Percentile values to calculate for each pollutant.
transpose: The default is to return a data frame with columns representing the statistics. If transpose = TRUE then the results have columns for each pollutant-site combination.
...: Other arguments, currently unused.

Details

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 transpose appropriately.

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 latitude and 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 align, which can be "centre" (default), "left" or "right". See rollingMean for more details.

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.

Author

David Carslaw

Examples


## 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 × 15
#> # Groups:   default, pollutant, year [1]
#>   default   pollutant  year date                dat.cap  mean   min   max median
#>   <fct>     <chr>     <dbl> <dttm>                <dbl> <dbl> <int> <int>  <dbl>
#> 1 01 Janua… no2        2004 2004-01-01 00:00:00    99.8  55.0     0   185     51
#> # ℹ 6 more variables: max_daily <dbl>, roll_8_max <dbl>, roll_24_max <dbl>,
#> #   percentile.95 <dbl>, percentile.99 <dbl>, hours <int>