dissolve_pb_once function

Apply dissolve_pb to a dataframe and create a new column with numeric dose

This function allows dissolve_pb to be added to a piped data frame. Two additional columns will be added to the dataframe; the name of the controlling lead solid, and total dissolved lead (M).

dissolve_pb_once(
  df,
  input_water = "defined_water",
  output_col_solid = "controlling_solid",
  output_col_result = "pb",
  hydroxypyromorphite = "Schock",
  pyromorphite = "Topolska",
  laurionite = "Nasanen",
  water_prefix = TRUE
)

Arguments

• df: a data frame containing a water class column, which has already been computed using define_water_chain
• input_water: name of the column of water class data to be used as the input. Default is "defined_water".
• output_col_solid: name of the output column storing the controlling lead solid. Default is "controlling_solid".
• output_col_result: name of the output column storing dissolved lead in M. Default is "pb".
• hydroxypyromorphite: defaults to "Schock", the constant, K, developed by Schock et al (1996). Can also use "Zhu".
• pyromorphite: defaults to "Topolska", the constant, K, developed by Topolska et al (2016). Can also use "Xie".
• laurionite: defaults to "Nasanen", the constant, K, developed by Nasanen & Lindell (1976). Can also use "Lothenbach".
• water_prefix: name of the input water used for the calculation, appended to the start of output columns. Default is TRUE. Chenge to FALSE to remove the water prefix from output column names.

Returns

A data frame containing the controlling lead solid and modeled dissolved lead concentration as new columns.

Details

The data input comes from a water class column, initialized in define_water or balance_ions. Use the output_col_solid and output_col_result arguments to name the ouput columns for the controlling lead solid and total dissolved lead, respectively. The input water used for the calculation will be appended to the start of these output columns. Omit the input water in the output columns, set water_prefix to FALSE (default is TRUE).

For large datasets, using fn_once or fn_chain may take many minutes to run. These types of functions use the furrr package for the option to use parallel processing and speed things up. To initialize parallel processing, use plan(multisession) or plan(multicore) (depending on your operating system) prior to your piped code with the fn_once or fn_chain functions. Note, parallel processing is best used when your code block takes more than a minute to run, shorter run times will not benefit from parallel processing.

Examples

library(purrr)
library(furrr)
library(tidyr)
library(dplyr)

example_df <- water_df %>%
  define_water_chain() %>%
  balance_ions_chain() %>%
  dissolve_pb_once(input_water = "balanced_water")

example_df <- water_df %>%
  define_water_chain() %>%
  dissolve_pb_once(output_col_result = "dissolved_lead", pyromorphite = "Xie")

# Initialize parallel processing
plan(multisession, workers = 2) # Remove the workers argument to use all available compute
example_df <- water_df %>%
  define_water_chain() %>%
  dissolve_pb_once(output_col_result = "dissolved_lead", laurionite = "Lothenbach")

# Optional: explicitly close multisession processing
plan(sequential)

See Also

dissolve_pb