From aed160d7f0eaf5865e2bd9bf6c4b1c9d7b13d911 Mon Sep 17 00:00:00 2001 From: Ranke Johannes Date: Wed, 31 Jan 2024 13:16:17 +0100 Subject: Reorganise data generation - Use inst/data_generation for R code generating data as in some of my other packages - data/*.RData files were checked using https://github.com/jranke/dotfiles/blob/main/bin/rda_diff contents were not changed - Remove ChangeLog, the history is in the git logs - Update docs and some links contained therein - use \doi{} markup - Move logs to log directory --- docs/reference/soil_scenario_data_EFSA_2017.html | 192 ++++++++++------------- 1 file changed, 80 insertions(+), 112 deletions(-) (limited to 'docs/reference/soil_scenario_data_EFSA_2017.html') diff --git a/docs/reference/soil_scenario_data_EFSA_2017.html b/docs/reference/soil_scenario_data_EFSA_2017.html index 7e8044e..96cdd1b 100644 --- a/docs/reference/soil_scenario_data_EFSA_2017.html +++ b/docs/reference/soil_scenario_data_EFSA_2017.html @@ -1,69 +1,14 @@ - - - - - - - -Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017 • pfm - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Properties 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

@@ -116,61 +47,98 @@ concentration in soil as given in the EFSA guidance (2017, p. 14/15). Also, the scenario and model adjustment factors from p. 16 and p. 18 are included.

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+ 
soil_scenario_data_EFSA_2017
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- -

Format

- +
+

Format

A data frame with one row for each scenario. Row names are the scenario codes, e.g. CTN for the Northern scenario for the total concentration in soil. Columns are mostly self-explanatory. rho is the dry bulk density of the top soil.

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Source

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+
+

Source

EFSA (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

- 
soil_scenario_data_EFSA_2017
#>        Zone Country T_arit T_arr Texture  f_om theta_fc   rho f_sce f_mod
-#> CTN   North Estonia    5.7   7.6  Coarse 0.220    0.244 0.707   1.4     3
-#> CTC Central  Poland    7.4   9.3  Coarse 0.122    0.244 0.934   1.4     3
-#> CTS   South  France   10.2  11.7  Medium 0.070    0.349 1.117   1.4     3
-#> CLN   North Denmark    8.0   9.2  Medium 0.025    0.349 1.371   1.6     4
-#> CLC Central Austria    9.3  11.3  Medium 0.018    0.349 1.432   1.6     4
-#> CLS   South   Spain   15.4  16.7  Medium 0.010    0.349 1.521   1.6     4
-#>     FOCUS_zone prec
-#> CTN    Hamburg  639
-#> CTC    Hamburg  617
-#> CTS    Hamburg  667
-#> CLN    Hamburg  602
-#> CLC Châteaudun  589
-#> CLS    Sevilla  526
+ doi:10.2903/j.efsa.2017.4982

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+ +
+

Examples

+ 
soil_scenario_data_EFSA_2017
+#>        Zone Country T_arit T_arr Texture  f_om theta_fc   rho f_sce f_mod
+#> CTN   North Estonia    5.7   7.6  Coarse 0.220    0.244 0.707   1.4     3
+#> CTC Central  Poland    7.4   9.3  Coarse 0.122    0.244 0.934   1.4     3
+#> CTS   South  France   10.2  11.7  Medium 0.070    0.349 1.117   1.4     3
+#> CLN   North Denmark    8.0   9.2  Medium 0.025    0.349 1.371   1.6     4
+#> CLC Central Austria    9.3  11.3  Medium 0.018    0.349 1.432   1.6     4
+#> CLS   South   Spain   15.4  16.7  Medium 0.010    0.349 1.521   1.6     4
+#>     FOCUS_zone prec
+#> CTN    Hamburg  639
+#> CTC    Hamburg  617
+#> CTS    Hamburg  667
+#> CLN    Hamburg  602
+#> CLC Châteaudun  589
+#> CLS    Sevilla  526
+
+waldo::compare(soil_scenario_data_EFSA_2017, soil_scenario_data_EFSA_2015)
+#> `old` is length 12
+#> `new` is length 10
+#> 
+#> `names(old)[8:12]`: "rho" "f_sce" "f_mod" "FOCUS_zone" "prec"
+#> `names(new)[8:10]`: "rho" "f_sce" "f_mod"                    
+#> 
+#> `old$Country`: "Estonia" "Poland"  "France" "Denmark" "Austria"        "Spain"
+#> `new$Country`: "Estonia" "Germany" "France" "Denmark" "Czech Republik" "Spain"
+#> 
+#> `old$T_arit`: 5.7 7.4 10.2 8.0 9.3 15.4
+#> `new$T_arit`: 4.7 8.0 11.0 8.2 9.1 12.8
+#> 
+#> `old$T_arr`: 7.6  9.3 11.7 9.2 11.3 16.7
+#> `new$T_arr`: 7.0 10.1 12.3 9.8 11.2 14.7
+#> 
+#> `old$Texture`: "Coarse" "Coarse" "Medium"      "Medium" "Medium" "Medium"
+#> `new$Texture`: "Coarse" "Coarse" "Medium fine" "Medium" "Medium" "Medium"
+#> 
+#> `old$f_om`: 0.220 0.122 0.070 0.025 0.018 0.010
+#> `new$f_om`: 0.118 0.086 0.048 0.023 0.018 0.011
+#> 
+#> `old$theta_fc`: 0.244 0.244 0.349 0.349 0.349 0.349
+#> `new$theta_fc`: 0.244 0.244 0.385 0.347 0.347 0.347
+#> 
+#> `old$rho`: 0.707 0.934 1.117 1.371 1.432 1.521
+#> `new$rho`: 0.950 1.050 1.220 1.390 1.430 1.510
+#> 
+#> `old$f_sce`: 1.4 1.4 1.4 1.6 1.6 1.6
+#> `new$f_sce`: 3.0 2.0 2.0 2.0 1.5 1.5
+#> 
+#> And 3 more differences ...
+
+
+
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