Converts data from rolf format to an openair compatible Format

openair::openair provides Tools for the analysis of air pollution data. rOstluft focus lies in providing data from different sources to the user. The openair data format is described in openair::mydata. Basically it is a wide format with a field "date" as POSIXct or Date and the parameters as columns. Another convention are the fields "ws" for wind speed and "wd" for wind direction. Although usually the functions allows passing of the names from the wind fields with the arguments wd and ws. One disadvantage of the wide format is the loss of unit information. Normally all parameters are in expressed in mass terms. See openair::importKCL() and openair::importAURN(). This functions saves the parameter <> unit information in the attribute "units". unfortunately attributes tend to be lost by data wrangling functions. But an avid user might save the information.

Usage

rolf_to_openair(
  data,
  as_list = FALSE,
  interval = NULL,
  keep_ppb = FALSE,
  keep_interval = FALSE,
  ws = "WVv",
  wd = "WD"
)

Arguments

data: in rolf format
as_list: optional, if TRUE returns a list a tibble for each parameter and keeps the unit information. Handy for applying functions with purrr.
interval: optional filter for interval
keep_ppb: usually volume concentrations are not used for analyses and are dropped with the exception of NOx. When FALSE drops parameters with ppb/ppm units except NOx. Default FALSE
keep_interval: keep the "interval" column. Default FALSE
ws: renames this parameter to "ws". Default "WVv". Set ws = NULL to disable renaming
wd: renames this parameter to "wd". Default "WD". Set wd = NULL to disable renaming

Value

tibble in openair compatible format

Details

Some functions, for example openair::timeAverage, have the argument "type". This argument allows to specifiy columns as grouping columns. However, if type is not supplied grouping variables (character or factor) will be dropped. Most other functions need a mandatory assignment of the argument pollutant.

Examples

h1 <- system.file("extdata", "Zch_Stampfenbachstrasse_h1_2013_Jan.csv",
                   package = "rOstluft.data", mustWork = TRUE)

airmo_h1 <- read_airmo_csv(h1)
rolf_to_openair(airmo_h1)
#> # A tibble: 744 × 16
#>    date                site         CO    Hr    NO   NO2   NOx    O3     p  PM10
#>    <dttm>              <fct>     <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#>  1 2013-01-01 00:00:00 Zch_Stam… 0.805  82.9 80.5   63.9  98.0  3.44  962. 184. 
#>  2 2013-01-01 01:00:00 Zch_Stam… 0.833  83.0 78.4   61.6  95.1  3.07  962. 272. 
#>  3 2013-01-01 02:00:00 Zch_Stam… 0.874  83.6 81.3   60.9  97.0  3.04  962. 226. 
#>  4 2013-01-01 03:00:00 Zch_Stam… 0.755  84.7 62.3   56.7  79.6  2.78  962. 198. 
#>  5 2013-01-01 04:00:00 Zch_Stam… 0.767  83.7 67.1   59.2  84.8  2.72  961. 179. 
#>  6 2013-01-01 05:00:00 Zch_Stam… 0.566  82.7 11.8   46.9  34.0  5.36  961. 124. 
#>  7 2013-01-01 06:00:00 Zch_Stam… 0.509  83.1 10.5   46.5  32.7  4.94  961.  78.7
#>  8 2013-01-01 07:00:00 Zch_Stam… 0.460  79.3  6.45  44.2  28.3  7.03  961.  65.1
#>  9 2013-01-01 08:00:00 Zch_Stam… 0.334  60.3  1.71  21.2  12.4 42.7   961.  41.2
#> 10 2013-01-01 09:00:00 Zch_Stam… 0.285  62.2  1.92  21.1  12.6 41.0   961.  22.8
#> # ℹ 734 more rows
#> # ℹ 6 more variables: RainDur <dbl>, SO2 <dbl>, StrGlo <dbl>, T <dbl>,
#> #   wd <dbl>, ws <dbl>