Subset of EFSA crop interception default values for groundwater modelling

- General utility functions - Functions that are independent of specific fate modelling areas -
- `geomean()` -	Calculate the geometric mean
- `one_box()` -	Create a time series of decline data
- `plot(<one_box>)` -	Plot time series of decline data
- `sawtooth()` -	Create decline time series for multiple applications
- `twa()` -	Calculate a time weighted average concentration
- `max_twa()` -	The maximum time weighted average concentration for a moving window
- `pfm_degradation()` -	Calculate a time course of relative concentrations based on an mkinmod model
- `SFO_actual_twa()` -	Actual and maximum moving window time average concentrations for SFO kinetics
- `FOMC_actual_twa()` -	Actual and maximum moving window time average concentrations for FOMC kinetics
- `reexports` `set_nd_nq` `set_nd_nq_focus` -	Objects exported from other packages
- `TSCF()` -	Estimation of the transpiration stream concentration factor
- Predicted environmental concentrations in soil - -
- `PEC_soil()` -	Calculate predicted environmental concentrations in soil
- `PEC_soil_mets()` -	Calculate initial and accumulation PEC soil for a set of metabolites
- `soil_scenario_data_EFSA_2015` -	Properties of the predefined scenarios from the EFSA guidance from 2015
- `soil_scenario_data_EFSA_2017` -	Properties of the predefined scenarios from the EFSA guidance from 2017
- `PEC_FOMC_accu_rel()` -	Get the relative accumulation of an FOMC model over multiples of an interval
- `EFSA_washoff_2017` -	Subset of EFSA crop washoff default values
- Predicted environmental concentrations in groundwater - -
- `FOCUS_GW_scenarios_2012` -	A very small subset of the FOCUS Groundwater scenario definitions
- `EFSA_GW_interception_2014` -	Subset of EFSA crop interception default values for groundwater modelling
- Predicted environmental concentrations in surface water - -
- `PEC_sw_drift()` -	Calculate predicted environmental concentrations in surface water due to drift
- `drift_data_JKI` -	Deposition from spray drift expressed as percent of the applied dose as -published by the JKI
- `PEC_sw_drainage_UK()` -	Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method
- `PEC_sw_sed()` -	Calculate predicted environmental concentrations in sediment from surface -water concentrations
- `PEC_sw_focus()` -	Calculate PEC surface water at FOCUS Step 1
- `chent_focus_sw()` -	Create a chemical compound object for FOCUS Step 1 calculations
- `FOCUS_Step_12_scenarios` -	Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator
- `PEC_sw_exposit_drainage()` -	Calculate PEC surface water due to drainage as in Exposit 3
- `PEC_sw_exposit_runoff()` -	Calculate PEC surface water due to runoff and erosion as in Exposit 3
- `perc_runoff_exposit` -	Runoff loss percentages as used in Exposit 3
- `perc_runoff_reduction_exposit` -	Runoff reduction percentages as used in Exposit
- `TOXSWA_cwa` -	R6 class for holding TOXSWA water concentration data and associated statistics
- `read.TOXSWA_cwa()` -	Read TOXSWA surface water concentrations
- `plot(<TOXSWA_cwa>)` -	Plot TOXSWA surface water concentrations
- Classifications and indicators - Evaluating environmental fate properties -
- `SSLRC_mobility_classification()` -	Determine the SSLRC mobility classification for a chemical substance from its Koc
- `GUS()` `print(<GUS_result>)` -	Groundwater ubiquity score based on Gustafson (1989)
- Work with chent objects containing relevant information - -
- `endpoint()` `soil_DT50()` `soil_Kfoc()` `soil_N()` `soil_sorption()` -	Retrieve endpoint information from the chyaml field of a chent object
- Utilities - -
- `get_vertex()` -	Fit a parabola through three points

res_raw	Character vector of a residue time series, or matrix of -residue values with rows representing depth profiles for a specific sampling -time, and columns representing time series of residues at the same depth. -Values below the limit of detection (lod) have to be coded as "nd", values -between the limit of detection and the limit of quantification, if any, have -to be coded as "nq". Samples not analysed have to be coded as "na". All -values that are not "na", "nd" or "nq" have to be coercible to numeric
lod	Limit of detection (numeric)
loq	Limit of quantification(numeric). Must be specified if the FOCUS rule to -stop after the first non-detection is to be applied
time_zero_presence	Do we assume that residues occur at time zero? -This only affects samples from the first sampling time that have been -reported as "nd" (not detected).
set_first_sample_nd	Should the first sample be set to "first_sample_nd_value" -in case it is a non-detection?
first_sample_nd_value	Value to be used for the first sample if it is a non-detection
ignore_below_loq_after_first_nd	Should we ignore values below the LOQ after the first -non-detection that occurs after the quantified values?

- - - -

- ->>>>>>> refs/remotes/origin/main

@@ -85,25 +46,17 @@

Subset of EFSA crop interception default values for groundwater modelling

Usage

EFSA_GW_interception_2014

-<<<<<<< HEAD -

Format

A matrix containing interception values, currently only for some selected crops

Source

-=======

Format

A matrix containing interception values, currently only for some selected crops

Source

->>>>>>> refs/remotes/origin/main

European Food Safety Authority (2014) EFSA Guidance Document for evaluating laboratory and field dissipation studies to obtain DegT50 values of active substances of plant protection products and transformation @@ -111,43 +64,9 @@ products of these active substances in soil. EFSA Journal 12(5):3662, 37 pp., doi:10.2903/j.efsa.2014.3662

-<<<<<<< HEAD -

Examples

EFSA_GW_interception_2014
-=======
     
     Examples
-    if (FALSE) {
-  # This is the code that was used to define the data
-  bbch <- paste0(0:9, "x")
-  crops <- c(
-    "Beans (field + vegetable)",
-    "Peas",
-    "Summer oilseed rape", "Winter oilseed rape",
-    "Tomatoes",
-    "Spring cereals", "Winter cereals")
-  EFSA_GW_interception_2014 <- matrix(NA, length(crops), length(bbch),
-    dimnames = list(Crop = crops, BBCH = bbch))
-  EFSA_GW_interception_2014["Beans (field + vegetable)", ] <-
-    c(0, 0.25, rep(0.4, 2), rep(0.7, 5), 0.8)
-  EFSA_GW_interception_2014["Peas", ] <-
-    c(0, 0.35, rep(0.55, 2), rep(0.85, 5), 0.85)
-  EFSA_GW_interception_2014["Summer oilseed rape", ] <-
-    c(0, 0.4, rep(0.8, 2), rep(0.8, 5), 0.9)
-  EFSA_GW_interception_2014["Winter oilseed rape", ] <-
-    c(0, 0.4, rep(0.8, 2), rep(0.8, 5), 0.9)
-  EFSA_GW_interception_2014["Tomatoes", ] <-
-    c(0, 0.5, rep(0.7, 2), rep(0.8, 5), 0.5)
-  EFSA_GW_interception_2014["Spring cereals", ] <-
-    c(0, 0, 0.2, 0.8, rep(0.9, 3), rep(0.8, 2), 0.8)
-  EFSA_GW_interception_2014["Winter cereals", ] <-
-    c(0, 0, 0.2, 0.8, rep(0.9, 3), rep(0.8, 2), 0.8)
-  save(EFSA_GW_interception_2014,
-    file = "../data/EFSA_GW_interception_2014.RData")
-}
-EFSA_GW_interception_2014
->>>>>>> refs/remotes/origin/main
+    EFSA_GW_interception_2014
 #>                            BBCH
 #> Crop                        0x   1x   2x   3x   4x   5x   6x   7x   8x   9x
 #>   Beans (field + vegetable)  0 0.25 0.40 0.40 0.70 0.70 0.70 0.70 0.70 0.80
@@ -159,24 +78,6 @@ products of these active substances in soil. EFSA Journal
 #>   Winter cereals             0 0.00 0.20 0.80 0.90 0.90 0.90 0.80 0.80 0.80
 
     

-<<<<<<< HEAD
-  

-  
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-    
-


-
-
-      
-  
Developed by Johannes Ranke.
-
-
-
-  
Site built with pkgdown 2.0.7.
-
-
-


-=======
   On this page


 
@@ -190,16 +91,10 @@ products of these active substances in soil. EFSA Journal


->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
-<<<<<<< HEAD
   
 
-=======
->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/EFSA_washoff_2017.html b/docs/reference/EFSA_washoff_2017.html
index 371f27e..3603cda 100644
--- a/docs/reference/EFSA_washoff_2017.html
+++ b/docs/reference/EFSA_washoff_2017.html
@@ -1,43 +1,5 @@
 
-<<<<<<< HEAD
-Subset of EFSA crop washoff default values — EFSA_washoff_2017 • pfm
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-    Subset of EFSA crop washoff default values
-=======
-Subset of EFSA crop washoff default values — EFSA_washoff_2017 • pfmSubset of EFSA crop washoff default values — EFSA_washoff_2017 • pfm
@@ -48,7 +10,7 @@
     
     pfm
 
-    0.6.0
+    0.6.1
 
     
     
 
->>>>>>> refs/remotes/origin/main
     
   
 
@@ -85,28 +46,11 @@
     Subset of EFSA crop washoff default values
     
 
-    
+    
+    Usage
     EFSA_washoff_2017
     
 
-<<<<<<< HEAD
-    
-    Format
-    A matrix containing wash-off factors, currently only for some selected crops
-    
-    
-    Source
-    European Food Safety Authority (2017) EFSA guidance document for
-  predicting environmental concentrations of active substances of plant
-  protection products and transformation products of these active substances
-  in soil. EFSA Journal 15(10) 4982
-  doi:10.2903/j.efsa.2017.4982
-    
-
-    
-    Examples
-    EFSA_washoff_2017
-=======
     
     Format
     A matrix containing wash-off factors, currently only for some selected crops
@@ -122,36 +66,7 @@ doi:10.2903/j.efsa.2017.4982
 
     
     Examples
-    if (FALSE) {
-  # This is the code that was used to define the data
-  bbch <- paste0(0:9, "x")
-  crops <- c(
-    "Beans (field + vegetable)",
-    "Peas",
-    "Summer oilseed rape", "Winter oilseed rape",
-    "Tomatoes",
-    "Spring cereals", "Winter cereals")
-  EFSA_washoff_2017 <- matrix(NA, length(crops), length(bbch),
-    dimnames = list(Crop = crops, BBCH = bbch))
-  EFSA_washoff_2017["Beans (field + vegetable)", ] <-
-    c(NA, 0.6, rep(0.75, 2), rep(0.8, 5), 0.35)
-  EFSA_washoff_2017["Peas", ] <-
-    c(NA, 0.4, rep(0.6, 2), rep(0.65, 5), 0.35)
-  EFSA_washoff_2017["Summer oilseed rape", ] <-
-    c(NA, 0.4, rep(0.5, 2), rep(0.6, 5), 0.5)
-  EFSA_washoff_2017["Winter oilseed rape", ] <-
-    c(NA, 0.1, rep(0.4, 2), rep(0.55, 5), 0.3)
-  EFSA_washoff_2017["Tomatoes", ] <-
-    c(NA, 0.55, rep(0.75, 2), rep(0.7, 5), 0.35)
-  EFSA_washoff_2017["Spring cereals", ] <-
-    c(NA, 0.4, 0.5, 0.5, rep(0.65, 3), rep(0.65, 2), 0.55)
-  EFSA_washoff_2017["Winter cereals", ] <-
-    c(NA, 0.1, 0.4, 0.6, rep(0.55, 3), rep(0.6, 2), 0.4)
-  save(EFSA_washoff_2017,
-    file = "../data/EFSA_washoff_2017.RData")
-}
-EFSA_washoff_2017
->>>>>>> refs/remotes/origin/main
+    EFSA_washoff_2017
 #>                            BBCH
 #> Crop                        0x   1x   2x   3x   4x   5x   6x   7x   8x   9x
 #>   Beans (field + vegetable) NA 0.60 0.75 0.75 0.80 0.80 0.80 0.80 0.80 0.35
@@ -163,24 +78,6 @@ doi:10.2903/j.efsa.2017.4982
 #>   Winter cereals            NA 0.10 0.40 0.60 0.55 0.55 0.55 0.60 0.60 0.40
 
     

-<<<<<<< HEAD
-  

-  
-    Contents
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-
-
-      
-  
Developed by Johannes Ranke.
-
-
-
-  
Site built with pkgdown 2.0.7.
-
-
-      

-=======
   On this page
     

 
@@ -194,16 +91,10 @@ doi:10.2903/j.efsa.2017.4982
 

 
     

->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
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->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/FOCUS_GW_scenarios_2012.html b/docs/reference/FOCUS_GW_scenarios_2012.html
index 4b6b993..20140cc 100644
--- a/docs/reference/FOCUS_GW_scenarios_2012.html
+++ b/docs/reference/FOCUS_GW_scenarios_2012.html
@@ -1,45 +1,6 @@
 
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-A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012 • pfm
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-    A very small subset of the FOCUS Groundwater scenario definitions
-=======
 A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012 • pfmA very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012 • pfm
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-    Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator
-=======
 Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios • pfmStep 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios • pfmActual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa • pfm
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-    Actual and maximum moving window time average concentrations for FOMC kinetics
-=======
-Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa • pfmActual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa • pfm
@@ -48,7 +10,7 @@
     
     pfm
 
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@@ -85,12 +46,8 @@
     Actual and maximum moving window time average concentrations for FOMC kinetics
     
 
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-=======
     
     Usage
->>>>>>> refs/remotes/origin/main
     FOMC_actual_twa(
   alpha = 1.0001,
   beta = 10,
@@ -98,16 +55,6 @@
 )
     
 
-<<<<<<< HEAD
-    
-    Source
-    FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation
-  Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1,
-  18 December 2014, p. 251
-    
-    
-    Arguments
-=======
     
     Source
     FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation
@@ -116,7 +63,6 @@ Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Versi
     
     
     Arguments
->>>>>>> refs/remotes/origin/main
     alpha
 Parameter of the FOMC model
 
@@ -129,15 +75,6 @@ Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Versi
 The output times, and window sizes for time weighted average concentrations
 
 
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-    Author
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-=======
     
     Author
     Johannes Ranke
@@ -145,7 +82,6 @@ Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Versi
 
     
     Examples
->>>>>>> refs/remotes/origin/main
     FOMC_actual_twa(alpha = 1.0001, beta = 10)
 #>         actual       twa
 #> 0   1.00000000       NaN
@@ -161,24 +97,6 @@ Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Versi
 #> 100 0.09088729 0.2397608
 
     
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-  
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-    Contents
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-      
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Developed by Johannes Ranke.
-
-
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-  
Site built with pkgdown 2.0.7.
-
-
-      
-=======
   On this page
     
 
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->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
-<<<<<<< HEAD
   
 
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->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/GUS.html b/docs/reference/GUS.html
index b68df33..7638dcd 100644
--- a/docs/reference/GUS.html
+++ b/docs/reference/GUS.html
@@ -1,47 +1,7 @@
 
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-Groundwater ubiquity score based on Gustafson (1989) — GUS • pfm
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-    Groundwater ubiquity score based on Gustafson (1989)
-=======
 Groundwater ubiquity score based on Gustafson (1989) — GUS • pfmGroundwater ubiquity score based on Gustafson (1989) — GUS • pfm
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-  
-    
-    Get the relative accumulation of an FOMC model over multiples of an interval
-    
-    PEC_FOMC_accu_rel.Rd
-    
-
-    
-    Get the relative accumulation of an FOMC model over multiples of an interval
-    
-
-    
-    PEC_FOMC_accu_rel(n, interval, FOMC)
-    
-
-    
-    Arguments
-=======
-Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel • pfmGet the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel • pfm
@@ -62,7 +10,7 @@
     
     pfm
 
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+    0.6.1
 
     
     
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-      
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Developed by Johannes Ranke.
-
-
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-  
Site built with pkgdown 2.0.7.
-
-
-      
-=======
   On this page
     
 
@@ -161,16 +85,10 @@
 
 
     
->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
-<<<<<<< HEAD
   
 
-=======
->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/PEC_soil.html b/docs/reference/PEC_soil.html
index 447e01d..46c92f4 100644
--- a/docs/reference/PEC_soil.html
+++ b/docs/reference/PEC_soil.html
@@ -1,51 +1,9 @@
 
-<<<<<<< HEAD
-Calculate predicted environmental concentrations in soil — PEC_soil • pfm
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-    Calculate predicted environmental concentrations in soil
-=======
 Calculate predicted environmental concentrations in soil — PEC_soil • pfmCalculate predicted environmental concentrations in soil — PEC_soil • pfmCalculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets • pfm
-    
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-    Calculate initial and accumulation PEC soil for a set of metabolites
-    
-    PEC_soil_mets.Rd
-    
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-    Calculate initial and accumulation PEC soil for a set of metabolites
-    
-
-    
-    PEC_soil_mets(rate, mw_parent, mets, interval = 365, ...)
-    
-
-    
-    Arguments
-=======
-Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets • pfmCalculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets • pfm
@@ -62,7 +10,7 @@
     
     pfm
 
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-=======
 
 interval
 The interval for accumulation calculations
@@ -170,16 +89,10 @@ maximum occurrence in soil and their soil DT50
 
 
     
->>>>>>> refs/remotes/origin/main
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-=======
->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/PEC_sw_drainage_UK.html b/docs/reference/PEC_sw_drainage_UK.html
index f8ee95d..3996f9c 100644
--- a/docs/reference/PEC_sw_drainage_UK.html
+++ b/docs/reference/PEC_sw_drainage_UK.html
@@ -1,45 +1,6 @@
 
-<<<<<<< HEAD
-Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK • pfm
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-    Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method
-=======
 Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK • pfmCalculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK • pfm
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-    Calculate predicted environmental concentrations in surface water due to drift
-=======
 Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift • pfmCalculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift • pfm>>>>>> refs/remotes/origin/main
 in the worksheet "Konzept Drainage". Although there are four groups of
 compounds ("Gefährdungsgruppen"), only one distinction is made in the
 calculations, between compounds with low mobility (group 1) and compounds
 with modest to high mobility (groups 2, 3 and 4). In this implementation,
 the group is derived only from the Koc, if not given explicitly. For
-<<<<<<< HEAD
-details, see the discussion of the function arguments below.'>
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-    Calculate PEC surface water due to drainage as in Exposit 3
-=======
-details, see the discussion of the function arguments below.'>Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage • pfmCalculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage • pfmpfm
 
-    0.6.0
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->>>>>>> refs/remotes/origin/main
     
   

 
@@ -107,12 +64,8 @@ the group is derived only from the Koc, if not given explicitly. For
 details, see the discussion of the function arguments below.
     
 
-<<<<<<< HEAD
-    
-=======
     
     Usage
->>>>>>> refs/remotes/origin/main
     PEC_sw_exposit_drainage(
   rate,
   interception = 0,
@@ -126,23 +79,13 @@ details, see the discussion of the function arguments below.
 )
     
 
-<<<<<<< HEAD
-    
-    Source
-    Excel 3.02 spreadsheet available from
-  https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html
-    
-    
-    Arguments
-=======
     
     Source
     Excel 3.02 spreadsheet available from
-https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3
+https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html
     
     
     Arguments
->>>>>>> refs/remotes/origin/main
     rate
 The application rate in g/ha
 
@@ -154,60 +97,6 @@ details, see the discussion of the function arguments below.
 Koc
 The sorption coefficient to soil organic carbon used to determine the mobility. A trigger
 value of 550 L/kg is used in order to decide if Koc >> 500.
-<<<<<<< HEAD
-
-
-mobility
-Overrides what is determined from the Koc.
-
-
-DT50
-The soil half-life in days
-
-
-t_drainage
-The time between application and the drainage event, where degradation occurs, in days
-
-
-V_ditch
-The volume of the ditch is assumed to be 1 m * 100 m * 30 cm = 30 m3
-
-
-V_drainage
-The drainage volume, equivalent to 1 mm precipitation on 1 ha for spring/summer or 10 mm for
-autumn/winter/early spring.
-
-
-dilution
-The dilution factor
-
-
-    
-    Value
-    
-
-A list containing the following components
-
-perc_runoff
-The runoff percentages for dissolved and bound substance
-
-    runoff
-A matrix containing dissolved and bound input for the different distances
-
-    PEC_sw_runoff
-A matrix containing PEC values for dissolved and bound substance
-      for the different distances. If the rate was given in g/ha, the PECsw are in microg/L.
-
-  
-
-    
-    See also
-    perc_runoff_exposit for runoff loss percentages and perc_runoff_reduction_exposit for runoff reduction percentages used
-    
-
-    
-    Examples
-=======
 
 
 mobility
@@ -258,7 +147,6 @@ for the different distances. If the rate was given in g/ha, the PECsw are in mic
 
     
     Examples
->>>>>>> refs/remotes/origin/main
       PEC_sw_exposit_drainage(500, Koc = 150)
 #> $perc_drainage_total
 #> spring autumn 
@@ -274,24 +162,6 @@ for the different distances. If the rate was given in g/ha, the PECsw are in mic
 #> 
 
     
-<<<<<<< HEAD
-  
-  
-    Contents
-    
-
-
-
-      
-  
Developed by Johannes Ranke.
-
-
-
-  
Site built with pkgdown 2.0.7.
-
-
-      
-=======
   On this page
     

 
@@ -305,16 +175,10 @@ for the different distances. If the rate was given in g/ha, the PECsw are in mic
 

 
     

->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
-<<<<<<< HEAD
   
 
-=======
->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/PEC_sw_exposit_runoff.html b/docs/reference/PEC_sw_exposit_runoff.html
index db121b4..21731f3 100644
--- a/docs/reference/PEC_sw_exposit_runoff.html
+++ b/docs/reference/PEC_sw_exposit_runoff.html
@@ -1,45 +1,6 @@
 
-<<<<<<< HEAD
-Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    Calculate PEC surface water due to runoff and erosion as in Exposit 3
-=======
 Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff • pfmCalculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    Calculate PEC surface water at FOCUS Step 1
-=======
-input files are generated that are suitable as input also for Step 2
-to be used with the FOCUS calculator.">Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus • pfmCalculate PEC surface water at FOCUS Step 1 — PEC_sw_focus • pfm
@@ -65,7 +22,7 @@ to be used with the FOCUS calculator.">Calculate predicted environmental concentrations in sediment from surface
-water concentrations — PEC_sw_sed • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    Calculate predicted environmental concentrations in sediment from surface
-water concentrations
-=======
 
     Skip to contents
     
@@ -55,7 +14,7 @@ water concentrations
     
     pfm
 
-    0.6.0
+    0.6.1
 
     
     
 
->>>>>>> refs/remotes/origin/main
     
   
 
@@ -94,12 +52,8 @@ water concentrations
 PEC calculator
     
 
-<<<<<<< HEAD
-    
-=======
     
     Usage
->>>>>>> refs/remotes/origin/main
     PEC_sw_sed(
   PEC_sw,
   percentage = 100,
@@ -111,13 +65,8 @@ PEC calculator
 )
     
 
-<<<<<<< HEAD
-    
-    Arguments
-=======
     
     Arguments
->>>>>>> refs/remotes/origin/main
     PEC_sw
 Numeric vector or matrix of surface water concentrations in µg/L for
 which the corresponding sediment concentration is to be estimated
@@ -148,26 +97,12 @@ g/cm3)
 The units of the estimated sediment PEC value
 
 
-<<<<<<< HEAD
-    
-    Value
-=======
     
     Value
->>>>>>> refs/remotes/origin/main
     
 
 The predicted concentration in sediment
     
-<<<<<<< HEAD
-    
-    Author
-    Johannes Ranke
-    
-
-    
-    Examples
-=======
     
     Author
     Johannes Ranke
@@ -175,30 +110,11 @@ g/cm3)
 
     
     Examples
->>>>>>> refs/remotes/origin/main
     PEC_sw_sed(PEC_sw_drift(100, distances = 1), percentage = 50)
 #>      1 m 
 #> 2.130769 
 
     
-<<<<<<< HEAD
-  
-  
-    Contents
-    
-
-
-
-      
-  
Developed by Johannes Ranke.
-
-
-
-  
Site built with pkgdown 2.0.7.
-
-
-      
-=======
   On this page
     
 
@@ -212,16 +128,10 @@ g/cm3)
 
 
     
->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
-<<<<<<< HEAD
   
 
-=======
->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/SFO_actual_twa.html b/docs/reference/SFO_actual_twa.html
index dc25585..6dc6862 100644
--- a/docs/reference/SFO_actual_twa.html
+++ b/docs/reference/SFO_actual_twa.html
@@ -1,43 +1,5 @@
 
-<<<<<<< HEAD
-Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    Actual and maximum moving window time average concentrations for SFO kinetics
-=======
-Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa • pfmActual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa • pfm
@@ -48,7 +10,7 @@
     
     pfm
 
-    0.6.0
+    0.6.1
 
     
     
 
->>>>>>> refs/remotes/origin/main
     
   
 
@@ -85,20 +46,6 @@
     Actual and maximum moving window time average concentrations for SFO kinetics
     
 
-<<<<<<< HEAD
-    
-    SFO_actual_twa(DT50 = 1000, times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100))
-    
-
-    
-    Source
-    FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation
-  Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1, 
-  18 December 2014, p. 251
-    
-    
-    Arguments
-=======
     
     Usage
     SFO_actual_twa(DT50 = 1000, times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100))
@@ -112,7 +59,6 @@ Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Versi
     
     
     Arguments
->>>>>>> refs/remotes/origin/main
     DT50
 The half-life.
 
@@ -121,15 +67,6 @@ Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Versi
 The output times, and window sizes for time weighted average concentrations
 
 
-<<<<<<< HEAD
-    
-    Author
-    Johannes Ranke
-    
-
-    
-    Examples
-=======
     
     Author
     Johannes Ranke
@@ -137,7 +74,6 @@ Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Versi
 
     
     Examples
->>>>>>> refs/remotes/origin/main
     SFO_actual_twa(10)
 #>           actual       twa
 #> 0   1.0000000000       NaN
@@ -153,24 +89,6 @@ Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Versi
 #> 100 0.0009765625 0.1441286
 
     
-<<<<<<< HEAD
-  
-  
-    Contents
-    
-
-
-
-      
-  
Developed by Johannes Ranke.
-
-
-
-  
Site built with pkgdown 2.0.7.
-
-
-      
-=======
   On this page
     
 
@@ -184,16 +102,10 @@ Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Versi
 
 
     
->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
-<<<<<<< HEAD
   
 
-=======
->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/SSLRC_mobility_classification.html b/docs/reference/SSLRC_mobility_classification.html
index 3ea5599..3e5e945 100644
--- a/docs/reference/SSLRC_mobility_classification.html
+++ b/docs/reference/SSLRC_mobility_classification.html
@@ -1,45 +1,6 @@
 
-<<<<<<< HEAD
-Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    Determine the SSLRC mobility classification for a chemical substance from its Koc
-=======
 Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification • pfmDetermine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification • pfmpfm
 
-    0.6.0
+    0.6.1
 
     
     

 
->>>>>>> refs/remotes/origin/main
     
   

 
@@ -84,23 +44,11 @@ checked against the spreadsheet published on the CRC website">SSLRC_mobility_classification.Rd

     

 
-<<<<<<< HEAD
-    
-=======
     
->>>>>>> refs/remotes/origin/main
     This implements the method specified in the UK data requirements handbook and was
 checked against the spreadsheet published on the CRC website
     
 
-<<<<<<< HEAD
-    
-    SSLRC_mobility_classification(Koc)
-    
-
-    
-    Arguments
-=======
     
     Usage
     SSLRC_mobility_classification(Koc)
@@ -108,37 +56,10 @@ checked against the spreadsheet published on the CRC website
 
     
     Arguments
->>>>>>> refs/remotes/origin/main
     Koc
 The sorption coefficient normalised to organic carbon in L/kg
 
 
-<<<<<<< HEAD
-    
-    Value
-    
-
-A list containing the classification and the percentage of the
-  compound transported per 10 mm drain water
-    
-    
-    References
-    HSE's Chemicals Regulation Division (CRD) Active substance
-  PECsw calculations (for UK specific authorisation requests)
-  https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/active-substance-uk.htm
-  accessed 2019-09-27
-Drainage PECs Version 1.0 (2015) Spreadsheet published at
-  https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/pec-tools-2015/PEC%20sw-sed%20(drainage).xlsx
-  accessed 2019-09-27
-    
-    
-    Author
-    Johannes Ranke
-    
-
-    
-    Examples
-=======
     
     Value
     
@@ -163,7 +84,6 @@ accessed 2019-09-27
 
     
     Examples
->>>>>>> refs/remotes/origin/main
     SSLRC_mobility_classification(100)
 #> $`Mobility classification`
 #> [1] "Moderately mobile"
@@ -180,24 +100,6 @@ accessed 2019-09-27
 #> 
 
     
-<<<<<<< HEAD
-  
-  
-    Contents
-    
-
-
-
-      
-  
Developed by Johannes Ranke.
-
-
-
-  
Site built with pkgdown 2.0.7.
-
-
-      
-=======
   On this page
     
 
@@ -211,16 +113,10 @@ accessed 2019-09-27
 
 
     

->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
-<<<<<<< HEAD
   
 
-=======
->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/TOXSWA_cwa.html b/docs/reference/TOXSWA_cwa.html
index 18e5cdd..281315a 100644
--- a/docs/reference/TOXSWA_cwa.html
+++ b/docs/reference/TOXSWA_cwa.html
@@ -1,51 +1,9 @@
 
-<<<<<<< HEAD
-R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    R6 class for holding TOXSWA water concentration data and associated statistics
-=======
 R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa • pfmR6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    Estimation of the transpiration stream concentration factor
-=======
-or ionic.">Estimation of the transpiration stream concentration factor — TSCF • pfmEstimation of the transpiration stream concentration factor — TSCF • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    Create a chemical compound object for FOCUS Step 1 calculations
-=======
-Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw • pfmCreate a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw • pfm
@@ -48,7 +10,7 @@
     
     pfm
 
-    0.6.0
+    0.6.1
 
     
     
 
->>>>>>> refs/remotes/origin/main
     
   
 
@@ -85,12 +46,8 @@
     Create a chemical compound object for FOCUS Step 1 calculations
     
 
-<<<<<<< HEAD
-    
-=======
     
     Usage
->>>>>>> refs/remotes/origin/main
     chent_focus_sw(
   name,
   Koc,
@@ -105,13 +62,8 @@
 )
     
 
-<<<<<<< HEAD
-    
-    Arguments
-=======
     
     Arguments
->>>>>>> refs/remotes/origin/main
     name
 Length one character vector containing the name
 
@@ -120,65 +72,6 @@
 Partition coefficient between organic carbon and water
 in L/kg.
 
-<<<<<<< HEAD
-
-DT50_ws
-Half-life in water/sediment systems in days
-
-
-DT50_soil
-Half-life in soil in days
-
-
-DT50_water
-Half-life in water in days (Step 2)
-
-
-DT50_sediment
-Half-life in sediment in days (Step 2)
-
-
-cwsat
-Water solubility in mg/L
-
-
-mw
-Molar weight in g/mol.
-
-
-max_soil
-Maximum observed fraction (dimensionless) in soil
-
-
-max_ws
-Maximum observed fraction (dimensionless) in water/sediment
-systems
-
-
-    
-    Value
-    
-
-A list with the substance specific properties
-    
-
-  
-  
-    Contents
-    
-
-
-
-      
-  
Developed by Johannes Ranke.
-
-
-
-  
Site built with pkgdown 2.0.7.
-
-
-      
-=======
 
 DT50_ws
 Half-life in water/sediment systems in days
@@ -233,16 +126,10 @@ systems
 
 
     
->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
-<<<<<<< HEAD
   
 
-=======
->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/drift_data_JKI.html b/docs/reference/drift_data_JKI.html
index 9478b5f..e6dea46 100644
--- a/docs/reference/drift_data_JKI.html
+++ b/docs/reference/drift_data_JKI.html
@@ -1,52 +1,11 @@
 
-<<<<<<< HEAD
-Deposition from spray drift expressed as percent of the applied dose as
-published by the JKI — drift_data_JKI • pfmDeposition from spray drift expressed as percent of the applied dose as
-published by the JKI — drift_data_JKI • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    Deposition from spray drift expressed as percent of the applied dose as
-published by the JKI
-=======
 
     Skip to contents
     
@@ -55,7 +14,7 @@ published by the JKI
     
     pfm
 
-    0.6.0
+    0.6.1
 
     
     
 
->>>>>>> refs/remotes/origin/main
     
   
 
@@ -95,24 +53,14 @@ published by the German Julius-Kühn Institute (JKI).
     
 
 
-<<<<<<< HEAD
-    
-    Format
-=======
     
     Format
->>>>>>> refs/remotes/origin/main
     A list currently containing matrices with spray drift percentage
 data for field crops (Ackerbau), and Pome/stone fruit, early and late
 (Obstbau frueh, spaet).
     
-<<<<<<< HEAD
-    
-    Source
-=======
     
     Source
->>>>>>> refs/remotes/origin/main
     JKI (2010) Spreadsheet 'Tabelle der Abdrifteckwerte.xls', retrieved
 from
 http://www.jki.bund.de/no_cache/de/startseite/institute/anwendungstechnik/abdrift-eckwerte.html
@@ -121,13 +69,8 @@ on 2015-06-11, not present any more 2024-01-31
 the authorization procedure for plant protection products Mitt. Biol.
 Bundesanst. Land- Forstwirtsch. 383, 133-141
     
-<<<<<<< HEAD
-    
-    Details
-=======
     
     Details
->>>>>>> refs/remotes/origin/main
     The data were extracted from the spreadsheet cited below using the R code
 given in the example section. The spreadsheet is not included in the package
 as its licence is not clear.
@@ -143,62 +86,9 @@ equipment (tragbare Spritz- und Sprühgerate).
 included.
     
 
-<<<<<<< HEAD
-    
-    Examples
-    drift_data_JKI
-=======
     
     Examples
-    
-if (FALSE) {
-  # This is the code that was used to extract the data
-  library(readxl)
-  abdrift_path <- "inst/extdata/Tabelle der Abdrifteckwerte.xls"
-  JKI_crops <- c("Ackerbau", "Obstbau frueh", "Obstbau spaet", "Weinbau frueh", "Weinbau spaet",
-    "Hopfenbau", "Flaechenkulturen > 900 l/ha", "Gleisanlagen")
-  names(JKI_crops) <- c("Field crops", "Pome/stone fruit, early", "Pome/stone fruit, late",
-    "Vines early", "Vines late", "Hops", "Areic cultures > 900 L/ha", "Railroad tracks")
-  drift_data_JKI <- list()
-
-  for (n in 1:8) {
-    drift_data_raw <- read_excel(abdrift_path, sheet = n + 1, skip = 2)
-    drift_data <- matrix(NA, nrow = 9, ncol = length(JKI_crops))
-    dimnames(drift_data) <- list(distance = drift_data_raw[[1]][1:9],
-                                            crop = JKI_crops)
-    if (n == 1) { # Values for railroad tracks only present for one application
-      drift_data[, c(1:3, 5:8)] <- as.matrix(drift_data_raw[c(2:7, 11)][1:9, ])
-    } else {
-      drift_data[, c(1:3, 5:7)] <- as.matrix(drift_data_raw[c(2:7)][1:9, ])
-    }
-    drift_data_JKI[[n]] <- drift_data
-  }
-
-  # Manual data entry from the Rautmann paper
-  drift_data_JKI[[1]]["3", "Ackerbau"] <- 0.95
-  drift_data_JKI[[1]][, "Weinbau frueh"] <- c(NA, 2.7, 1.18, 0.39, 0.2, 0.13, 0.07, 0.04, 0.03)
-  drift_data_JKI[[2]]["3", "Ackerbau"] <- 0.79
-  drift_data_JKI[[2]][, "Weinbau frueh"] <- c(NA, 2.53, 1.09, 0.35, 0.18, 0.11, 0.06, 0.03, 0.02)
-  drift_data_JKI[[3]]["3", "Ackerbau"] <- 0.68
-  drift_data_JKI[[3]][, "Weinbau frueh"] <- c(NA, 2.49, 1.04, 0.32, 0.16, 0.10, 0.05, 0.03, 0.02)
-  drift_data_JKI[[4]]["3", "Ackerbau"] <- 0.62
-  drift_data_JKI[[4]][, "Weinbau frueh"] <- c(NA, 2.44, 1.02, 0.31, 0.16, 0.10, 0.05, 0.03, 0.02)
-  drift_data_JKI[[5]]["3", "Ackerbau"] <- 0.59
-  drift_data_JKI[[5]][, "Weinbau frueh"] <- c(NA, 2.37, 1.00, 0.31, 0.15, 0.09, 0.05, 0.03, 0.02)
-  drift_data_JKI[[6]]["3", "Ackerbau"] <- 0.56
-  drift_data_JKI[[6]][, "Weinbau frueh"] <- c(NA, 2.29, 0.97, 0.30, 0.15, 0.09, 0.05, 0.03, 0.02)
-  drift_data_JKI[[7]]["3", "Ackerbau"] <- 0.55
-  drift_data_JKI[[7]][, "Weinbau frueh"] <- c(NA, 2.24, 0.94, 0.29, 0.15, 0.09, 0.05, 0.03, 0.02)
-  drift_data_JKI[[8]]["3", "Ackerbau"] <- 0.52
-  drift_data_JKI[[8]][, "Weinbau frueh"] <- c(NA, 2.16, 0.91, 0.28, 0.14, 0.09, 0.04, 0.03, 0.02)
-
-  # Save the data
-  save(drift_data_JKI, file = "data/drift_data_JKI.RData")
-}
-
-# And these are the resulting data
-drift_data_JKI
->>>>>>> refs/remotes/origin/main
+    drift_data_JKI
 #> [[1]]
 #>         crop
 #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet
@@ -393,24 +283,6 @@ included.
 #> 
 
     

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-=======
   On this page
     

 
@@ -424,16 +296,10 @@ included.
 

 
     

->>>>>>> refs/remotes/origin/main
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->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/endpoint.html b/docs/reference/endpoint.html
index 0f012a0..6705770 100644
--- a/docs/reference/endpoint.html
+++ b/docs/reference/endpoint.html
@@ -1,49 +1,8 @@
 
-<<<<<<< HEAD
-Retrieve endpoint information from the chyaml field of a chent object — endpoint • pfm
-    
-
-    
-      
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-    
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-        pfm
-        0.6.1
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-    Retrieve endpoint information from the chyaml field of a chent object
-=======
 Retrieve endpoint information from the chyaml field of a chent object — endpoint • pfmRetrieve endpoint information from the chyaml field of a chent object — endpoint • pfm
-    
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-    Calculate the geometric mean
-=======
 Calculate the geometric mean — geomean • pfmCalculate the geometric mean — geomean • pfmpfm
 
-    0.6.0
+    0.6.1
 
     
     
 
->>>>>>> refs/remotes/origin/main
     
   
 
@@ -101,14 +58,6 @@ This function returns NA if NA values are present and na.rm = FALSE
 If at least one element of the vector is 0, it returns 0.
     
 
-<<<<<<< HEAD
-    
-    geomean(x, na.rm = FALSE)
-    
-
-    
-    Arguments
-=======
     
     Usage
     geomean(x, na.rm = FALSE)
@@ -116,7 +65,6 @@ If at least one element of the vector is 0, it returns 0.
 
     
     Arguments
->>>>>>> refs/remotes/origin/main
     x
 Vector of numbers
 
@@ -125,26 +73,12 @@ If at least one element of the vector is 0, it returns 0.
 Should NA values be omitted?
 
 
-<<<<<<< HEAD
-    
-    Value
-=======
     
     Value
->>>>>>> refs/remotes/origin/main
     
 
 The geometric mean
     
-<<<<<<< HEAD
-    
-    Author
-    Johannes Ranke
-    
-
-    
-    Examples
-=======
     
     Author
     Johannes Ranke
@@ -152,34 +86,12 @@ If at least one element of the vector is 0, it returns 0.
 
     
     Examples
->>>>>>> refs/remotes/origin/main
     geomean(c(1, 3, 9))
 #> [1] 3
 geomean(c(1, 3, NA, 9))
 #> [1] NA
-<<<<<<< HEAD
 geomean(c(1, -3, 9)) # returns an error
 #> Error in geomean(c(1, -3, 9)): Only defined for positive numbers
-
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-=======
-if (FALSE) geomean(c(1, -3, 9)) # returns an error
 

     

   On this page
@@ -195,16 +107,10 @@ If at least one element of the vector is 0, it returns 0.
 

 
     

->>>>>>> refs/remotes/origin/main
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diff --git a/docs/reference/get_vertex.html b/docs/reference/get_vertex.html
index 6a03c3c..d0eff28 100644
--- a/docs/reference/get_vertex.html
+++ b/docs/reference/get_vertex.html
@@ -1,45 +1,6 @@
 
-<<<<<<< HEAD
-Fit a parabola through three points — get_vertex • pfm
-    
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-  

-

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-      
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-  
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-    Fit a parabola through three points
-=======
 Fit a parabola through three points — get_vertex • pfmFit a parabola through three points — get_vertex • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
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-    
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-  

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-        
-      
-          General utility functions 
-          
Functions that are independent of specific fate modelling areas
-        

-          geomean() 
-        Calculate the geometric mean

-          one_box() 
-        Create a time series of decline data

-          plot(<one_box>) 
-        Plot time series of decline data

-          sawtooth() 
-        Create decline time series for multiple applications

-          twa() 
-        Calculate a time weighted average concentration

-          max_twa() 
-        The maximum time weighted average concentration for a moving window

-          pfm_degradation() 
-        Calculate a time course of relative concentrations based on an mkinmod model

-          SFO_actual_twa() 
-        Actual and maximum moving window time average concentrations for SFO kinetics

-          FOMC_actual_twa() 
-        Actual and maximum moving window time average concentrations for FOMC kinetics

-          reexports set_nd_nq set_nd_nq_focus 
-        Objects exported from other packages

-          TSCF() 
-        Estimation of the transpiration stream concentration factor

-          Predicted environmental concentrations in soil 
-          
-        

-          PEC_soil() 
-        Calculate predicted environmental concentrations in soil

-          PEC_soil_mets() 
-        Calculate initial and accumulation PEC soil for a set of metabolites

-          soil_scenario_data_EFSA_2015 
-        Properties of the predefined scenarios from the EFSA guidance from 2015

-          soil_scenario_data_EFSA_2017 
-        Properties of the predefined scenarios from the EFSA guidance from 2017

-          PEC_FOMC_accu_rel() 
-        Get the relative accumulation of an FOMC model over multiples of an interval

-          EFSA_washoff_2017 
-        Subset of EFSA crop washoff default values

-          Predicted environmental concentrations in groundwater 
-          
-        

-          FOCUS_GW_scenarios_2012 
-        A very small subset of the FOCUS Groundwater scenario definitions

-          EFSA_GW_interception_2014 
-        Subset of EFSA crop interception default values for groundwater modelling

-          Predicted environmental concentrations in surface water 
-          
-        

-          PEC_sw_drift() 
-        Calculate predicted environmental concentrations in surface water due to drift

-          drift_data_JKI 
-        Deposition from spray drift expressed as percent of the applied dose as
-published by the JKI

-          PEC_sw_drainage_UK() 
-        Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method

-          PEC_sw_sed() 
-        Calculate predicted environmental concentrations in sediment from surface
-water concentrations

-          PEC_sw_focus() 
-        Calculate PEC surface water at FOCUS Step 1

-          chent_focus_sw() 
-        Create a chemical compound object for FOCUS Step 1 calculations

-          FOCUS_Step_12_scenarios 
-        Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator

-          PEC_sw_exposit_drainage() 
-        Calculate PEC surface water due to drainage as in Exposit 3

-          PEC_sw_exposit_runoff() 
-        Calculate PEC surface water due to runoff and erosion as in Exposit 3

-          perc_runoff_exposit 
-        Runoff loss percentages as used in Exposit 3

-          perc_runoff_reduction_exposit 
-        Runoff reduction percentages as used in Exposit

-          TOXSWA_cwa 
-        R6 class for holding TOXSWA water concentration data and associated statistics

-          read.TOXSWA_cwa() 
-        Read TOXSWA surface water concentrations

-          plot(<TOXSWA_cwa>) 
-        Plot TOXSWA surface water concentrations

-          Classifications and indicators 
-          
Evaluating environmental fate properties
-        

-          SSLRC_mobility_classification() 
-        Determine the SSLRC mobility classification for a chemical substance from its Koc

-          GUS() print(<GUS_result>) 
-        Groundwater ubiquity score based on Gustafson (1989)

-          Work with chent objects containing relevant information 
-          
-        

-          endpoint() soil_DT50() soil_Kfoc() soil_N() soil_sorption() 
-        Retrieve endpoint information from the chyaml field of a chent object

-          Utilities 
-          
-        

-          get_vertex() 
-        Fit a parabola through three points
-
-  
-    Contents
-    
-
-
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-      
-  
Developed by Johannes Ranke.
-
-
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-  
Site built with pkgdown 2.0.7.
-
-
-      
-=======
-Function reference • pfmFunction reference • pfm
@@ -245,7 +10,7 @@ water concentrations
     
     pfm
 
-    0.6.0
+    0.6.1
 
     
     
 
     
->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
-<<<<<<< HEAD
   
 
-=======
->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/max_twa.html b/docs/reference/max_twa.html
index e333d30..4d469eb 100644
--- a/docs/reference/max_twa.html
+++ b/docs/reference/max_twa.html
@@ -1,51 +1,9 @@
 
-<<<<<<< HEAD
-The maximum time weighted average concentration for a moving window — max_twa • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    The maximum time weighted average concentration for a moving window
-=======
 The maximum time weighted average concentration for a moving window — max_twa • pfmThe maximum time weighted average concentration for a moving window — max_twa • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    Create a time series of decline data
-=======
-Create a time series of decline data — one_box • pfmCreate a time series of decline data — one_box • pfm
@@ -48,7 +10,7 @@
     
     pfm
 
-    0.6.0
+    0.6.1
 
     
     
 
->>>>>>> refs/remotes/origin/main
     
   
 
@@ -85,12 +46,8 @@
     Create a time series of decline data
     
 
-<<<<<<< HEAD
-    
-=======
     
     Usage
->>>>>>> refs/remotes/origin/main
     one_box(x, ini, ..., t_end = 100, res = 0.01)
 
 # S3 method for numeric
@@ -103,13 +60,8 @@
 one_box(x, ini = "model", ..., t_end = 100, res = 0.01)
     
 
-<<<<<<< HEAD
-    
-    Arguments
-=======
     
     Arguments
->>>>>>> refs/remotes/origin/main
     x
 When numeric, this is the half-life to be used for an exponential
 decline. When a character string specifying a parent decline model is given
@@ -128,13 +80,8 @@ all observed variables.
 
 ...
 Further arguments passed to methods
-<<<<<<< HEAD
-
-
-=======
 
 
->>>>>>> refs/remotes/origin/main
 t_end
 End of the time series
 
@@ -147,25 +94,15 @@ all observed variables.
 A named numeric vector containing the model parameters
 
 
-<<<<<<< HEAD
-    
-    Value
-=======
     
     Value
->>>>>>> refs/remotes/origin/main
     
 
 An object of class one_box, inheriting from ts.
     
 
-<<<<<<< HEAD
-    
-    Examples
-=======
     
     Examples
->>>>>>> refs/remotes/origin/main
     # Only use a half-life
 pred_0 <- one_box(10)
 plot(pred_0)
@@ -188,24 +125,6 @@ all observed variables.
 
 
     
-<<<<<<< HEAD
-  
-  
-    Contents
-    
-
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Developed by Johannes Ranke.
-
-
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-  
Site built with pkgdown 2.0.7.
-
-
-      
-=======
   On this page
     
 
@@ -219,16 +138,10 @@ all observed variables.
 
 
     
->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
-<<<<<<< HEAD
   
 
-=======
->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/perc_runoff_exposit.html b/docs/reference/perc_runoff_exposit.html
index 4f3c3e8..2311d09 100644
--- a/docs/reference/perc_runoff_exposit.html
+++ b/docs/reference/perc_runoff_exposit.html
@@ -1,43 +1,5 @@
 
-<<<<<<< HEAD
-Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    Runoff loss percentages as used in Exposit 3
-=======
-Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit • pfmRunoff loss percentages as used in Exposit 3 — perc_runoff_exposit • pfm
@@ -48,7 +10,7 @@
     
     pfm
 
-    0.6.0
+    0.6.1
 
     
     
 
->>>>>>> refs/remotes/origin/main
     
   
 
@@ -85,36 +46,11 @@
     A table of the loss percentages used in Exposit 3 for the twelve different Koc classes
     
 
-    
+    
+    Usage
     perc_runoff_exposit
     
 
-<<<<<<< HEAD
-    
-    Format
-    A data frame with percentage values for the dissolved fraction and the fraction
-  bound to eroding particles, with Koc classes used as row names
Koc_lower_bound
-The lower bound of the Koc class
-
-    dissolved
-The percentage of the applied substance transferred to an
-      adjacent water body in the dissolved phase
-
-    bound
-The percentage of the applied substance transferred to an
-      adjacent water body bound to eroding particles
-
-  
-
-    
-    Source
-    Excel 3.02 spreadsheet available from
-  https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html
-    
-
-    
-    Examples
-=======
     
     Format
     A data frame with percentage values for the dissolved fraction and the fraction
@@ -134,12 +70,11 @@ adjacent water body bound to eroding particles
     
     Source
     Excel 3.02 spreadsheet available from
-https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html
+https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html
     
 
     
     Examples
->>>>>>> refs/remotes/origin/main
     print(perc_runoff_exposit)
 #>              Koc_lower_bound dissolved bound
 #> 0-20                       0     0.110 0.000
@@ -156,24 +91,6 @@ adjacent water body bound to eroding particles
 #> >50000                 50000     0.001 0.451
 
     
-<<<<<<< HEAD
-  
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-    Contents
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Developed by Johannes Ranke.
-
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Site built with pkgdown 2.0.7.
-
-
-      
-=======
   On this page
     
 
@@ -187,16 +104,10 @@ adjacent water body bound to eroding particles
 
 
     
->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
-<<<<<<< HEAD
   
 
-=======
->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/perc_runoff_reduction_exposit.html b/docs/reference/perc_runoff_reduction_exposit.html
index 1a354c3..24a199e 100644
--- a/docs/reference/perc_runoff_reduction_exposit.html
+++ b/docs/reference/perc_runoff_reduction_exposit.html
@@ -1,43 +1,5 @@
 
-<<<<<<< HEAD
-Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    Runoff reduction percentages as used in Exposit
-=======
-Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit • pfmRunoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit • pfm
@@ -48,7 +10,7 @@
     
     pfm
 
-    0.6.0
+    0.6.1
 
     
     
 
->>>>>>> refs/remotes/origin/main
     
   
 
@@ -85,14 +46,6 @@
     A table of the runoff reduction percentages used in Exposit 3 for different vegetated buffer widths
     
 
-<<<<<<< HEAD
-    
-    perc_runoff_reduction_exposit
-    
-
-    
-    Format
-=======
     
     Usage
     perc_runoff_reduction_exposit
@@ -100,30 +53,12 @@
 
     
     Format
->>>>>>> refs/remotes/origin/main
     A named list of data frames with reduction percentage values for the
 dissolved fraction and the fraction bound to eroding particles, with
 vegetated buffer widths as row names. The names of the list items are the Exposit versions
 from which the values were taken.
dissolved
 The reduction percentage for the dissolved phase
 
-<<<<<<< HEAD
-    bound
-The reduction percentage for the particulate phase
-
-  
-
-    
-    Source
-    Excel 3.02 spreadsheet available from
-  https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html
-Agroscope version 3.01a with additional runoff factors for 3 m and 6 m buffer zones received from Muris Korkaric (not published).
-  The variant 3.01a2 was introduced for consistency with previous calculations performed by Agroscope for a 3 m buffer zone.
-    
-
-    
-    Examples
-=======
 bound
 The reduction percentage for the particulate phase
 
@@ -132,14 +67,13 @@ from which the values were taken.
dissolved
     
     Source
     Excel 3.02 spreadsheet available from
-https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html
+https://www.bvl.bund.de/SharedDocs/Downloads/04_Pflanzenschutzmittel/zul_umwelt_exposit.html
 Agroscope version 3.01a with additional runoff factors for 3 m and 6 m buffer zones received from Muris Korkaric (not published).
 The variant 3.01a2 was introduced for consistency with previous calculations performed by Agroscope for a 3 m buffer zone.
     
 
     
     Examples
->>>>>>> refs/remotes/origin/main
     print(perc_runoff_reduction_exposit)
 #> $`3.02`
 #>           dissolved bound
@@ -169,24 +103,6 @@ The variant 3.01a2 was introduced for consistency with previous calculations per
 #> 
 
     
-<<<<<<< HEAD
-  
-  
-    Contents
-    
-
-
-
-      
-  
Developed by Johannes Ranke.
-
-
-
-  
Site built with pkgdown 2.0.7.
-
-
-      
-=======
   On this page
     
 
@@ -200,16 +116,10 @@ The variant 3.01a2 was introduced for consistency with previous calculations per
 
 
     
->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
-<<<<<<< HEAD
   
 
-=======
->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/pfm_degradation.html b/docs/reference/pfm_degradation.html
index 5ed36f9..8b21cf5 100644
--- a/docs/reference/pfm_degradation.html
+++ b/docs/reference/pfm_degradation.html
@@ -1,43 +1,5 @@
 
-<<<<<<< HEAD
-Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
-    Calculate a time course of relative concentrations based on an mkinmod model
-=======
-Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation • pfmCalculate a time course of relative concentrations based on an mkinmod model — pfm_degradation • pfm
@@ -48,7 +10,7 @@
     
     pfm
 
-    0.6.0
+    0.6.1
 
     
     
 
->>>>>>> refs/remotes/origin/main
     
   
 
@@ -85,12 +46,8 @@
     Calculate a time course of relative concentrations based on an mkinmod model
     
 
-<<<<<<< HEAD
-    
-=======
     
     Usage
->>>>>>> refs/remotes/origin/main
     pfm_degradation(
   model = "SFO",
   DT50 = 1000,
@@ -101,13 +58,8 @@
 )
     
 
-<<<<<<< HEAD
-    
-    Arguments
-=======
     
     Arguments
->>>>>>> refs/remotes/origin/main
     model
 The degradation model to be used. Either a parent only model like
 'SFO' or 'FOMC', or an mkinmod object
@@ -134,14 +86,13 @@ is calculated (SFO model).
 The output times
 
 
-<<<<<<< HEAD
-    
-    Author
+    
+    Author
     Johannes Ranke
     
 
-    
-    Examples
+    
+    Examples
     head(pfm_degradation("SFO", DT50 = 10))
 #>   time    parent
 #> 0    0 1.0000000
@@ -150,34 +101,6 @@ is calculated (SFO model).
 #> 3    3 0.8122524
 #> 4    4 0.7578583
 #> 5    5 0.7071068
-
-    
-  
-  
-    Contents
-    
-
-
-
-      
-  
Developed by Johannes Ranke.
-
-
-
-  
Site built with pkgdown 2.0.7.
-
-
-      
-=======
-    
-    Author
-    Johannes Ranke
-    
-
-    
-    Examples
-    head(pfm_degradation("SFO", DT50 = 10))
-#> Error in head(pfm_degradation("SFO", DT50 = 10)): could not find function "head"
 
     
   On this page
@@ -193,16 +116,10 @@ is calculated (SFO model).
 
 
     
->>>>>>> refs/remotes/origin/main
-
-  
 
   
 
-<<<<<<< HEAD
   
 
-=======
->>>>>>> refs/remotes/origin/main
   
 
diff --git a/docs/reference/plot.TOXSWA_cwa.html b/docs/reference/plot.TOXSWA_cwa.html
index 6cde064..1b89187 100644
--- a/docs/reference/plot.TOXSWA_cwa.html
+++ b/docs/reference/plot.TOXSWA_cwa.html
@@ -1,45 +1,6 @@
 
-<<<<<<< HEAD
-Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa • pfm
-    
-
-    
-      
-  
-    
-      
-      
-        pfm
-        0.6.1
-      
-    
-
-    
-      
-  Reference
-
-      

-  

-

-
-      
-
-      

-  
-    
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-=======
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diff --git a/docs/reference/read.TOXSWA_cwa.html b/docs/reference/read.TOXSWA_cwa.html
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-Read TOXSWA surface water concentrations — read.TOXSWA_cwa • pfm
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-    Read TOXSWA surface water concentrations
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-renamed to ConLiqWatLay in the out file.">Read TOXSWA surface water concentrations — read.TOXSWA_cwa • pfmRead TOXSWA surface water concentrations — read.TOXSWA_cwa • pfmObjects exported from other packages — reexports • pfmObjects exported from other packages — reexports • pfm
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->>>>>>> refs/remotes/origin/main
   
 
   
diff --git a/docs/reference/sawtooth.html b/docs/reference/sawtooth.html
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-Create decline time series for multiple applications — sawtooth • pfm
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 Create decline time series for multiple applications — sawtooth • pfmCreate decline time series for multiple applications — sawtooth • pfm
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-    Set non-detects and unquantified values in residue series without replicates
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-    This function automates replacing unquantified values in residue time and
-depth series. For time series, the function performs part of the residue
-processing proposed in the FOCUS kinetics guidance for parent compounds
-and metabolites. For two-dimensional residue series over time and depth,
-it automates the proposal of Boesten et al (2015).
-    
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-    set_nd_nq(res_raw, lod, loq = NA, time_zero_presence = FALSE)
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-set_nd_nq_focus(
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-  ignore_below_loq_after_first_nd = TRUE
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-    res_raw Character vector of a residue time series, or matrix of
-residue values with rows representing depth profiles for a specific sampling
-time, and columns representing time series of residues at the same depth.
-Values below the limit of detection (lod) have to be coded as "nd", values
-between the limit of detection and the limit of quantification, if any, have
-to be coded as "nq". Samples not analysed have to be coded as "na". All
-values that are not "na", "nd" or "nq" have to be coercible to numeric
lod Limit of detection (numeric)
loq Limit of quantification(numeric). Must be specified if the FOCUS rule to
-stop after the first non-detection is to be applied
time_zero_presence Do we assume that residues occur at time zero?
-This only affects samples from the first sampling time that have been
-reported as "nd" (not detected).
set_first_sample_nd Should the first sample be set to "first_sample_nd_value"
-in case it is a non-detection?
first_sample_nd_value Value to be used for the first sample if it is a non-detection
ignore_below_loq_after_first_nd Should we ignore values below the LOQ after the first
-non-detection that occurs after the quantified values?
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-    Value
-
-    A numeric vector, if a vector was supplied, or a numeric matrix otherwise
-    Functions
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-set_nd_nq_focus: Set non-detects in residue time series according to FOCUS rules
-
-    References
-
-    Boesten, J. J. T. I., van der Linden, A. M. A., Beltman, W. H.
-J. and Pol, J. W. (2015). Leaching of plant protection products and their
-transformation products; Proposals for improving the assessment of leaching
-to groundwater in the Netherlands — Version 2. Alterra report 2630, Alterra
-Wageningen UR (University & Research centre)
-FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation
-  Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1,
-  18 December 2014, p. 251
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-    Examples
-    # FOCUS (2014) p. 75/76 and 131/132
-parent_1 <- c(.12, .09, .05, .03, "nd", "nd", "nd", "nd", "nd", "nd")
-set_nd_nq(parent_1, 0.02)
#>  [1] 0.12 0.09 0.05 0.03 0.01   NA   NA   NA   NA   NA
parent_2 <- c(.12, .09, .05, .03, "nd", "nd", .03, "nd", "nd", "nd")
-set_nd_nq(parent_2, 0.02)
#>  [1] 0.12 0.09 0.05 0.03 0.01 0.01 0.03 0.01   NA   NA
set_nd_nq_focus(parent_2, 0.02, loq = 0.05)
#>  [1] 0.12 0.09 0.05 0.03 0.01   NA   NA   NA   NA   NA
parent_3 <- c(.12, .09, .05, .03, "nd", "nd", .06, "nd", "nd", "nd")
-set_nd_nq(parent_3, 0.02)
#>  [1] 0.12 0.09 0.05 0.03 0.01 0.01 0.06 0.01   NA   NA
set_nd_nq_focus(parent_3, 0.02, loq = 0.05)
#>  [1] 0.12 0.09 0.05 0.03 0.01 0.01 0.06 0.01   NA   NA
metabolite <- c("nd", "nd", "nd", 0.03, 0.06, 0.10, 0.11, 0.10, 0.09, 0.05, 0.03, "nd", "nd")
-set_nd_nq(metabolite, 0.02)
#>  [1]   NA   NA 0.01 0.03 0.06 0.10 0.11 0.10 0.09 0.05 0.03 0.01   NA
set_nd_nq_focus(metabolite, 0.02, 0.05)
#>  [1] 0.00   NA 0.01 0.03 0.06 0.10 0.11 0.10 0.09 0.05 0.03 0.01   NA
#
-# Boesten et al. (2015), p. 57/58
-table_8 <- matrix(
-  c(10, 10, rep("nd", 4),
-    10, 10, rep("nq", 2), rep("nd", 2),
-    10, 10, 10, "nq", "nd", "nd",
-    "nq", 10, "nq", rep("nd", 3),
-    "nd", "nq", "nq", rep("nd", 3),
-    rep("nd", 6), rep("nd", 6)),
-  ncol = 6, byrow = TRUE)
-set_nd_nq(table_8, 0.5, 1.5, time_zero_presence = TRUE)
#>       [,1]  [,2]  [,3] [,4] [,5] [,6]
-#> [1,] 10.00 10.00  0.25 0.25   NA   NA
-#> [2,] 10.00 10.00  1.00 1.00 0.25   NA
-#> [3,] 10.00 10.00 10.00 1.00 0.25   NA
-#> [4,]  1.00 10.00  1.00 0.25   NA   NA
-#> [5,]  0.25  1.00  1.00 0.25   NA   NA
-#> [6,]    NA  0.25  0.25   NA   NA   NA
-#> [7,]    NA    NA    NA   NA   NA   NA
table_10 <- matrix(
-  c(10, 10, rep("nd", 4),
-    10, 10, rep("nd", 4),
-    10, 10, 10, rep("nd", 3),
-    "nd", 10, rep("nd", 4),
-    rep("nd", 18)),
-  ncol = 6, byrow = TRUE)
-set_nd_nq(table_10, 0.5, time_zero_presence = TRUE)
#>       [,1]  [,2]  [,3] [,4] [,5] [,6]
-#> [1,] 10.00 10.00  0.25   NA   NA   NA
-#> [2,] 10.00 10.00  0.25   NA   NA   NA
-#> [3,] 10.00 10.00 10.00 0.25   NA   NA
-#> [4,]  0.25 10.00  0.25   NA   NA   NA
-#> [5,]    NA  0.25    NA   NA   NA   NA
-#> [6,]    NA    NA    NA   NA   NA   NA
-#> [7,]    NA    NA    NA   NA   NA   NA
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diff --git a/docs/reference/soil_scenario_data_EFSA_2015.html b/docs/reference/soil_scenario_data_EFSA_2015.html
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-=======
 Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015 • pfmProperties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015 • pfmProperties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017 • pfm
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 Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017 • pfmProperties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017 • pfmCalculate a time weighted average concentration — twa • pfm
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 Calculate a time weighted average concentration — twa • pfmCalculate a time weighted average concentration — twa • pfm

Subset of EFSA crop interception default values for groundwater modelling

Usage

Format

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Format

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Examples

Examples

Subset of EFSA crop washoff default values

Usage

Format

Source

Examples

Format

Examples

A very small subset of the FOCUS Groundwater scenario definitions

Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator

Actual and maximum moving window time average concentrations for FOMC kinetics

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Source

Arguments

Source

Arguments

Author

Examples

Author

Examples

Groundwater ubiquity score based on Gustafson (1989)

Get the relative accumulation of an FOMC model over multiples of an interval

Arguments

Arguments

Value

Value

Calculate predicted environmental concentrations in soil

Calculate initial and accumulation PEC soil for a set of metabolites

Arguments

Arguments

Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method

Calculate predicted environmental concentrations in surface water due to drift

Calculate PEC surface water due to drainage as in Exposit 3

Usage

Source

Arguments

Source

Arguments

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See also

Examples

Examples

Calculate PEC surface water due to runoff and erosion as in Exposit 3

Calculate PEC surface water at FOCUS Step 1

Calculate predicted environmental concentrations in sediment from surface -water concentrations

Usage

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Value

Author

Examples

Author

Examples

Actual and maximum moving window time average concentrations for SFO kinetics

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Arguments

Usage

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Examples

Determine the SSLRC mobility classification for a chemical substance from its Koc

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Usage

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Author

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