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.

## 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>
```