diff options
| author | Johannes Ranke <jranke@uni-bremen.de> | 2023-11-12 21:59:34 +0100 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2023-11-12 21:59:34 +0100 |
| commit | 4079a2c496aa4e8c6dc2a93afedcbedbf7a852b5 (patch) | |
| tree | 8281ddd094c84d3bd0663fe2f060985f4a212e6b | |
| parent | d66bd4aa0bf9c4d9b8793a4e308c9e80691b440f (diff) | |
Enable markdown and rebuild docs
46 files changed, 290 insertions, 271 deletions
diff --git a/DESCRIPTION b/DESCRIPTION index a12f90b..a159c56 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -27,4 +27,5 @@ LazyLoad: yes LazyData: yes Encoding: UTF-8 URL: https://pkgdown.jrwb.de/pfm, https://github.com/jranke/pfm +Roxygen: list(markdown = TRUE, r6 = TRUE) RoxygenNote: 7.2.3 diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml index eeed6da..6571239 100644 --- a/docs/pkgdown.yml +++ b/docs/pkgdown.yml @@ -2,7 +2,7 @@ pandoc: 2.17.1.1 pkgdown: 2.0.7 pkgdown_sha: ~ articles: {} -last_built: 2023-11-12T20:34Z +last_built: 2023-11-12T20:59Z urls: reference: https://pkgdown.jrwb.de/pfm/reference article: https://pkgdown.jrwb.de/pfm/articles diff --git a/docs/reference/EFSA_washoff_2017.html b/docs/reference/EFSA_washoff_2017.html index 1e292af..b424de9 100644 --- a/docs/reference/EFSA_washoff_2017.html +++ b/docs/reference/EFSA_washoff_2017.html @@ -54,10 +54,10 @@ <div class="section level2"> <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2> <p>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. <em>EFSA Journal</em> <b>15</b>(10) 4982 - doi:10.2903/j.efsa.2017.4982</p> +predicting environmental concentrations of active substances of plant +protection products and transformation products of these active substances +in soil. <em>EFSA Journal</em> <b>15</b>(10) 4982 +doi:10.2903/j.efsa.2017.4982</p> </div> <div class="section level2"> diff --git a/docs/reference/FOCUS_GW_scenarios_2012.html b/docs/reference/FOCUS_GW_scenarios_2012.html index 84c2fac..2e9982b 100644 --- a/docs/reference/FOCUS_GW_scenarios_2012.html +++ b/docs/reference/FOCUS_GW_scenarios_2012.html @@ -1,6 +1,6 @@ <!DOCTYPE html> -<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Currently, only scenario names with acronyms and a small subset of the soil definitions are provided. The -soil definitions are from page 46ff. from FOCUS (2012)."><title>A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012 • pfm</title><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012"><meta property="og:description" content="Currently, only scenario names with acronyms and a small subset of the soil definitions are provided. The +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Currently, only scenario names with acronyms and a small subset of the soil definitions are provided. The +soil definitions are from page 46ff. from FOCUS (2012)."><title>A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012 • pfm</title><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012"><meta property="og:description" content="Currently, only scenario names with acronyms and a small subset of the soil definitions are provided. The soil definitions are from page 46ff. from FOCUS (2012)."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> @@ -45,7 +45,7 @@ soil definitions are from page 46ff. from FOCUS (2012)."><!-- mathjax --><script </div> <div class="ref-description section level2"> - <p>Currently, only scenario names with acronyms and a small subset of the soil definitions are provided. The + <p>Currently, only scenario names with acronyms and a small subset of the soil definitions are provided. The soil definitions are from page 46ff. from FOCUS (2012).</p> </div> @@ -60,9 +60,9 @@ soil definitions are from page 46ff. from FOCUS (2012).</p> </div> <div class="section level2"> <h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a></h2> - <p>FOCUS (2012) Generic guidance for Tier 1 FOCUS ground water assessments. Version 2.1. - FOrum for the Co-ordination of pesticde fate models and their USe. - http://focus.jrc.ec.europa.eu/gw/docs/Generic_guidance_FOCV2_1.pdf</p> + <p>FOCUS (2012) Generic guidance for Tier 1 FOCUS ground water assessments. Version 2.1. +FOrum for the Co-ordination of pesticde fate models and their USe. +http://focus.jrc.ec.europa.eu/gw/docs/Generic_guidance_FOCV2_1.pdf</p> </div> <div class="section level2"> diff --git a/docs/reference/FOCUS_Step_12_scenarios.html b/docs/reference/FOCUS_Step_12_scenarios.html index dc1e4c3..bcf71ed 100644 --- a/docs/reference/FOCUS_Step_12_scenarios.html +++ b/docs/reference/FOCUS_Step_12_scenarios.html @@ -53,9 +53,9 @@ The text file is not included in the package as its licence is not clear.</p> <div class="section level2"> <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2> <p>A list containing the scenario names in a character vector called 'names', - the drift percentiles in a matrix called 'drift', interception percentages in - a matrix called 'interception' and the runoff/drainage percentages for Step 2 - calculations in a matrix called 'rd'.</p> +the drift percentiles in a matrix called 'drift', interception percentages in +a matrix called 'interception' and the runoff/drainage percentages for Step 2 +calculations in a matrix called 'rd'.</p> </div> <div class="section level2"> diff --git a/docs/reference/FOMC_actual_twa.html b/docs/reference/FOMC_actual_twa.html index f7b0140..226d44f 100644 --- a/docs/reference/FOMC_actual_twa.html +++ b/docs/reference/FOMC_actual_twa.html @@ -58,8 +58,8 @@ <div class="section level2"> <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2> <p>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</p> +Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1, +18 December 2014, p. 251</p> </div> <div class="section level2"> <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2> diff --git a/docs/reference/GUS.html b/docs/reference/GUS.html index d2aa03b..e3a451e 100644 --- a/docs/reference/GUS.html +++ b/docs/reference/GUS.html @@ -93,7 +93,7 @@ be conducted under use conditions.</p></dd> <dt>Koc</dt> <dd><p>The sorption constant normalised to organic carbon. Gustafson does not mention the nonlinearity of the sorption constant commonly -found and usually described by Freundlich sorption, therefore it is +found and usually described by Freundlich sorption, therefore it is unclear at which reference concentration the Koc should be observed (and if the reference concentration would be in soil or in porewater).</p></dd> @@ -104,7 +104,7 @@ chyaml field, this information is used, with defaults specified below.</p></dd> <dt>degradation_value</dt> -<dd><p>Which of the available degradation values should +<dd><p>Which of the available degradation values should be used?</p></dd> @@ -149,7 +149,7 @@ be Koc values at a concentration of 1 mg/L in the water phase.</p></dd> <p>A list with the DT50 and Koc used as well as the resulting score - of class GUS_result</p> +of class GUS_result</p> </div> <div class="section level2"> <h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a></h2> diff --git a/docs/reference/PEC_soil.html b/docs/reference/PEC_soil.html index abe8e5a..98ac3ac 100644 --- a/docs/reference/PEC_soil.html +++ b/docs/reference/PEC_soil.html @@ -225,33 +225,33 @@ from the EFSA guidance from 2015 (p. 80) are be reproduced, this is not true for the TWA concentrations given for the same example in the EFSA guidance from 2017 (p. 92).</p> <p>According to the EFSA guidance (EFSA, 2017, p. 43), leaching should be - taken into account for the EFSA 2017 scenarios, using the evaluation depth - (here mixing depth) as the depth of the layer from which leaching takes - place. However, as the amount leaching below the evaluation depth - (often 5 cm) will partly be mixed back during tillage, the default in this function - is to use the tillage depth for the calculation of the leaching rate.</p> +taken into account for the EFSA 2017 scenarios, using the evaluation depth +(here mixing depth) as the depth of the layer from which leaching takes +place. However, as the amount leaching below the evaluation depth +(often 5 cm) will partly be mixed back during tillage, the default in this function +is to use the tillage depth for the calculation of the leaching rate.</p> <p>If temperature information is available in the selected scenarios, as - e.g. in the EFSA scenarios, the DT50 for groundwater modelling - (destination 'PECgw') is taken from the chent object, otherwise the DT50 - with destination 'PECsoil'.</p> +e.g. in the EFSA scenarios, the DT50 for groundwater modelling +(destination 'PECgw') is taken from the chent object, otherwise the DT50 +with destination 'PECsoil'.</p> </div> <div class="section level2"> <h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a></h2> <p>EFSA Panel on Plant Protection Products and their Residues (2012) - Scientific Opinion on the science behind the guidance for scenario - selection and scenario parameterisation for predicting environmental - concentrations of plant protection products in soil. <em>EFSA Journal</em> - <b>10</b>(2) 2562, doi:10.2903/j.efsa.2012.2562</p> +Scientific Opinion on the science behind the guidance for scenario +selection and scenario parameterisation for predicting environmental +concentrations of plant protection products in soil. <em>EFSA Journal</em> +<b>10</b>(2) 2562, doi:10.2903/j.efsa.2012.2562</p> <p>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. <em>EFSA Journal</em> <b>15</b>(10) 4982 - doi:10.2903/j.efsa.2017.4982</p> +predicting environmental concentrations of active substances of plant +protection products and transformation products of these active substances +in soil. <em>EFSA Journal</em> <b>15</b>(10) 4982 +doi:10.2903/j.efsa.2017.4982</p> <p>EFSA (European Food Safety Authority) (2015) EFSA guidance document for - predicting environmental concentrations of active substances of plant - protection products and transformation products of these active substances - in soil. <em>EFSA Journal</em> <b>13</b>(4) 4093 - doi:10.2903/j.efsa.2015.4093</p> +predicting environmental concentrations of active substances of plant +protection products and transformation products of these active substances +in soil. <em>EFSA Journal</em> <b>13</b>(4) 4093 +doi:10.2903/j.efsa.2015.4093</p> </div> <div class="section level2"> <h2 id="author">Author<a class="anchor" aria-label="anchor" href="#author"></a></h2> diff --git a/docs/reference/PEC_sw_drainage_UK.html b/docs/reference/PEC_sw_drainage_UK.html index 8e649b9..5068319 100644 --- a/docs/reference/PEC_sw_drainage_UK.html +++ b/docs/reference/PEC_sw_drainage_UK.html @@ -102,12 +102,12 @@ published on the CRC website</p> <div class="section level2"> <h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a></h2> <p>HSE's Chemicals Regulation Division (CRD) Active substance - PECsw calculations (for UK specific authorisation requests) - <a href="https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/active-substance-uk.htm" class="external-link">https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/active-substance-uk.htm</a> - accessed 2019-09-27</p> +PECsw calculations (for UK specific authorisation requests) +<a href="https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/active-substance-uk.htm" class="external-link">https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/active-substance-uk.htm</a> +accessed 2019-09-27</p> <p>Drainage PECs Version 1.0 (2015) Spreadsheet published at - <a href="https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/pec-tools-2015/PEC%20sw-sed%20(drainage).xlsx" class="external-link">https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/pec-tools-2015/PEC%20sw-sed%20(drainage).xlsx</a> - accessed 2019-09-27</p> +<a href="https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/pec-tools-2015/PEC%20sw-sed%20(drainage).xlsx" class="external-link">https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/pec-tools-2015/PEC%20sw-sed%20(drainage).xlsx</a> +accessed 2019-09-27</p> </div> <div class="section level2"> <h2 id="author">Author<a class="anchor" aria-label="anchor" href="#author"></a></h2> diff --git a/docs/reference/PEC_sw_drift.html b/docs/reference/PEC_sw_drift.html index 3e1d4c8..d7e940c 100644 --- a/docs/reference/PEC_sw_drift.html +++ b/docs/reference/PEC_sw_drift.html @@ -87,7 +87,7 @@ with input via spray drift.</p> <dt>drift_data</dt> -<dd><p>Source of drift percentage data. If 'JKI', the [drift_data_JKI] +<dd><p>Source of drift percentage data. If 'JKI', the <a href="drift_data_JKI.html">drift_data_JKI</a> included in the package is used. If 'RF', the Rautmann formula is used, if implemented for the crop type and number of applications</p></dd> diff --git a/docs/reference/PEC_sw_exposit_drainage.html b/docs/reference/PEC_sw_exposit_drainage.html index 74f1b60..f57fc56 100644 --- a/docs/reference/PEC_sw_exposit_drainage.html +++ b/docs/reference/PEC_sw_exposit_drainage.html @@ -82,7 +82,7 @@ details, see the discussion of the function arguments below.</p> <div class="section level2"> <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2> <p>Excel 3.02 spreadsheet available from - <a href="https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3" class="external-link">https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3</a></p> +<a href="https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3" class="external-link">https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3</a></p> </div> <div class="section level2"> <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2> @@ -128,19 +128,17 @@ autumn/winter/early spring.</p></dd> <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2> -<p>A list containing the following components</p> -<p></p> -<dl><dt>perc_runoff</dt> +<p>A list containing the following components</p><dl><dt>perc_runoff</dt> <dd><p>The runoff percentages for dissolved and bound substance</p></dd> - <dt>runoff</dt> +<dt>runoff</dt> <dd><p>A matrix containing dissolved and bound input for the different distances</p></dd> - <dt>PEC_sw_runoff</dt> +<dt>PEC_sw_runoff</dt> <dd><p>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.</p></dd> +for the different distances. If the rate was given in g/ha, the PECsw are in microg/L.</p></dd> + - </dl></div> <div class="section level2"> <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2> diff --git a/docs/reference/PEC_sw_exposit_runoff.html b/docs/reference/PEC_sw_exposit_runoff.html index a3845ee..73e3e43 100644 --- a/docs/reference/PEC_sw_exposit_runoff.html +++ b/docs/reference/PEC_sw_exposit_runoff.html @@ -67,7 +67,7 @@ in the worksheet "Konzept Runoff".</p> <div class="section level2"> <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2> <p>Excel 3.02 spreadsheet available from - <a href="https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3" class="external-link">https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3</a></p> +<a href="https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3" class="external-link">https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3</a></p> </div> <div class="section level2"> <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2> @@ -115,19 +115,17 @@ and the bound fraction.</p></dd> <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2> -<p>A list containing the following components</p> -<p></p> -<dl><dt>perc_runoff</dt> +<p>A list containing the following components</p><dl><dt>perc_runoff</dt> <dd><p>The runoff percentages for dissolved and bound substance</p></dd> - <dt>runoff</dt> +<dt>runoff</dt> <dd><p>A matrix containing dissolved and bound input for the different distances</p></dd> - <dt>PEC_sw_runoff</dt> +<dt>PEC_sw_runoff</dt> <dd><p>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.</p></dd> +for the different distances. If the rate was given in g/ha, the PECsw are in microg/L.</p></dd> + - </dl></div> <div class="section level2"> <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2> diff --git a/docs/reference/PEC_sw_focus.html b/docs/reference/PEC_sw_focus.html index 78f6453..e758347 100644 --- a/docs/reference/PEC_sw_focus.html +++ b/docs/reference/PEC_sw_focus.html @@ -91,7 +91,7 @@ to be used with the FOCUS calculator.</p> <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2> <dl><dt>parent</dt> <dd><p>A list containing substance specific parameters, e.g. -conveniently generated by [chent_focus_sw].</p></dd> +conveniently generated by <a href="chent_focus_sw.html">chent_focus_sw</a>.</p></dd> <dt>rate</dt> @@ -113,7 +113,7 @@ applications are given explicitly</p></dd> <dt>met</dt> <dd><p>A list containing metabolite specific parameters. e.g. -conveniently generated by [chent_focus_sw]. If not NULL, +conveniently generated by <a href="chent_focus_sw.html">chent_focus_sw</a>. If not NULL, the PEC is calculated for this compound, not the parent.</p></dd> @@ -121,18 +121,18 @@ the PEC is calculated for this compound, not the parent.</p></dd> <dd><p>The fraction of the application rate reaching the waterbody via drift. If NA, this is derived from the scenario name and the number of applications via the drift data defined by the -[FOCUS_Step_12_scenarios]</p></dd> +<a href="FOCUS_Step_12_scenarios.html">FOCUS_Step_12_scenarios</a></p></dd> <dt>f_rd</dt> <dd><p>The fraction of the amount applied reaching the waterbody via -runoff/drainage. At Step 1, it is assumed to be 10<!-- %, be it the --> +runoff/drainage. At Step 1, it is assumed to be 10%, be it the parent or a metabolite</p></dd> <dt>scenario</dt> <dd><p>The name of the scenario. Must be one of the scenario -names given in [FOCUS_Step_12_scenarios]</p></dd> +names given in <a href="FOCUS_Step_12_scenarios.html">FOCUS_Step_12_scenarios</a></p></dd> <dt>region</dt> @@ -174,21 +174,21 @@ should be written</p></dd> <div class="section level2"> <h2 id="note">Note<a class="anchor" aria-label="anchor" href="#note"></a></h2> <p>The formulas for input to the waterbody via runoff/drainage of the - parent and subsequent formation of the metabolite in water is not - documented in the model description coming with the calculator. As one would - expect, this appears to be (as we get the same results) calculated by - multiplying the application rate with the molar weight - correction and the formation fraction in water/sediment systems.</p> +parent and subsequent formation of the metabolite in water is not +documented in the model description coming with the calculator. As one would +expect, this appears to be (as we get the same results) calculated by +multiplying the application rate with the molar weight +correction and the formation fraction in water/sediment systems.</p> <p>Step 2 is not implemented.</p> </div> <div class="section level2"> <h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a></h2> <p>FOCUS (2014) Generic guidance for Surface Water Scenarios (version 1.4). - FOrum for the Co-ordination of pesticde fate models and their USe. - http://esdac.jrc.ec.europa.eu/public_path/projects_data/focus/sw/docs/Generic<!-- %20FOCUS_SWS_vc1.4.pdf --></p> +FOrum for the Co-ordination of pesticde fate models and their USe. +http://esdac.jrc.ec.europa.eu/public_path/projects_data/focus/sw/docs/Generic%20FOCUS_SWS_vc1.4.pdf</p> <p>Website of the Steps 1 and 2 calculator at the Joint Research - Center of the European Union: - http://esdac.jrc.ec.europa.eu/projects/stepsonetwo</p> +Center of the European Union: +http://esdac.jrc.ec.europa.eu/projects/stepsonetwo</p> </div> <div class="section level2"> diff --git a/docs/reference/SFO_actual_twa.html b/docs/reference/SFO_actual_twa.html index e07138c..0c3813f 100644 --- a/docs/reference/SFO_actual_twa.html +++ b/docs/reference/SFO_actual_twa.html @@ -54,8 +54,8 @@ <div class="section level2"> <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2> <p>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</p> +Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1, +18 December 2014, p. 251</p> </div> <div class="section level2"> <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2> diff --git a/docs/reference/SSLRC_mobility_classification.html b/docs/reference/SSLRC_mobility_classification.html index 398734d..0530260 100644 --- a/docs/reference/SSLRC_mobility_classification.html +++ b/docs/reference/SSLRC_mobility_classification.html @@ -65,17 +65,17 @@ checked against the spreadsheet published on the CRC website</p> <p>A list containing the classification and the percentage of the - compound transported per 10 mm drain water</p> +compound transported per 10 mm drain water</p> </div> <div class="section level2"> <h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a></h2> <p>HSE's Chemicals Regulation Division (CRD) Active substance - PECsw calculations (for UK specific authorisation requests) - <a href="https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/active-substance-uk.htm" class="external-link">https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/active-substance-uk.htm</a> - accessed 2019-09-27</p> +PECsw calculations (for UK specific authorisation requests) +<a href="https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/active-substance-uk.htm" class="external-link">https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/active-substance-uk.htm</a> +accessed 2019-09-27</p> <p>Drainage PECs Version 1.0 (2015) Spreadsheet published at - <a href="https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/pec-tools-2015/PEC%20sw-sed%20(drainage).xlsx" class="external-link">https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/pec-tools-2015/PEC%20sw-sed%20(drainage).xlsx</a> - accessed 2019-09-27</p> +<a href="https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/pec-tools-2015/PEC%20sw-sed%20(drainage).xlsx" class="external-link">https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/pec-tools-2015/PEC%20sw-sed%20(drainage).xlsx</a> +accessed 2019-09-27</p> </div> <div class="section level2"> <h2 id="author">Author<a class="anchor" aria-label="anchor" href="#author"></a></h2> diff --git a/docs/reference/TOXSWA_cwa.html b/docs/reference/TOXSWA_cwa.html index a5a9a49..8908748 100644 --- a/docs/reference/TOXSWA_cwa.html +++ b/docs/reference/TOXSWA_cwa.html @@ -157,7 +157,7 @@ for the requested moving window sizes in days.</p></dd> </div><p></p><hr><a id="method-TOXSWA_cwa-moving_windows"></a><div class="section"> <h3 id="method-moving-windows-">Method <code>moving_windows()</code><a class="anchor" aria-label="anchor" href="#method-moving-windows-"></a></h3> -<p>Add to the `windows` field described above.</p><div class="section"> +<p>Add to the <code>windows</code> field described above.</p><div class="section"> <h4 id="usage-1">Usage<a class="anchor" aria-label="anchor" href="#usage-1"></a></h4> <p></p><div class="r"><div class="sourceCode"><pre><code><span><span class="va">TOXSWA_cwa</span><span class="op">$</span><span class="fu">moving_windows</span><span class="op">(</span><span class="va">windows</span>, total <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div><p></p></div> </div> @@ -179,7 +179,7 @@ suspended matter will be used.</p></dd> </div><p></p><hr><a id="method-TOXSWA_cwa-get_events"></a><div class="section"> <h3 id="method-get-events-">Method <code>get_events()</code><a class="anchor" aria-label="anchor" href="#method-get-events-"></a></h3> <p>Populate a datataframe with event information for the specified -threshold value. The resulting dataframe is stored in the `events` +threshold value. The resulting dataframe is stored in the <code>events</code> field of the object.</p><div class="section"> <h4 id="usage-2">Usage<a class="anchor" aria-label="anchor" href="#usage-2"></a></h4> <p></p><div class="r"><div class="sourceCode"><pre><code><span><span class="va">TOXSWA_cwa</span><span class="op">$</span><span class="fu">get_events</span><span class="op">(</span><span class="va">thresholds</span>, total <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div><p></p></div> @@ -201,7 +201,7 @@ suspended matter will be used.</p></dd> </div><p></p><hr><a id="method-TOXSWA_cwa-print"></a><div class="section"> <h3 id="method-print-">Method <code><a href="https://rdrr.io/r/base/print.html" class="external-link">print()</a></code><a class="anchor" aria-label="anchor" href="#method-print-"></a></h3> -<p>Print a `TOXSWA_cwa` object</p><div class="section"> +<p>Print a <code>TOXSWA_cwa</code> object</p><div class="section"> <h4 id="usage-3">Usage<a class="anchor" aria-label="anchor" href="#usage-3"></a></h4> <p></p><div class="r"><div class="sourceCode"><pre><code><span><span class="va">TOXSWA_cwa</span><span class="op">$</span><span class="fu">print</span><span class="op">(</span><span class="op">)</span></span></code></pre></div><p></p></div> </div> @@ -237,7 +237,31 @@ suspended matter will be used.</p></dd> <span class="r-in"><span><span class="va">H_sw_R1_stream</span><span class="op">$</span><span class="fu">moving_windows</span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">7</span>, <span class="fl">21</span><span class="op">)</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/print.html" class="external-link">print</a></span><span class="op">(</span><span class="va">H_sw_R1_stream</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> <TOXSWA_cwa> data from file 00003s_pa.cwa segment 20 </span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in head(self$cwas):</span> could not find function "head"</span> +<span class="r-out co"><span class="r-pr">#></span> datetime t t_firstjan t_rel_to_max cwa_mug_per_L</span> +<span class="r-out co"><span class="r-pr">#></span> 20 1978-10-01 00:00:00 0.000 273.0000 -55.333 0</span> +<span class="r-out co"><span class="r-pr">#></span> 40 1978-10-01 01:00:00 0.042 273.0417 -55.291 0</span> +<span class="r-out co"><span class="r-pr">#></span> 60 1978-10-01 02:00:00 0.083 273.0833 -55.250 0</span> +<span class="r-out co"><span class="r-pr">#></span> 80 1978-10-01 03:00:00 0.125 273.1250 -55.208 0</span> +<span class="r-out co"><span class="r-pr">#></span> 100 1978-10-01 04:00:00 0.167 273.1667 -55.166 0</span> +<span class="r-out co"><span class="r-pr">#></span> 120 1978-10-01 05:00:00 0.208 273.2083 -55.125 0</span> +<span class="r-out co"><span class="r-pr">#></span> cwa_tot_mug_per_L</span> +<span class="r-out co"><span class="r-pr">#></span> 20 0</span> +<span class="r-out co"><span class="r-pr">#></span> 40 0</span> +<span class="r-out co"><span class="r-pr">#></span> 60 0</span> +<span class="r-out co"><span class="r-pr">#></span> 80 0</span> +<span class="r-out co"><span class="r-pr">#></span> 100 0</span> +<span class="r-out co"><span class="r-pr">#></span> 120 0</span> +<span class="r-out co"><span class="r-pr">#></span> Moving window analysis</span> +<span class="r-out co"><span class="r-pr">#></span> window max_TWAC max_AUC_h max_AUC_d</span> +<span class="r-out co"><span class="r-pr">#></span> 1 7 days 2.3926551 401.9660 16.74859</span> +<span class="r-out co"><span class="r-pr">#></span> 2 21 days 0.8369248 421.8101 17.57542</span> +<span class="r-out co"><span class="r-pr">#></span> Event statistics for threshold 2 </span> +<span class="r-out co"><span class="r-pr">#></span> t_start cwa_max duration pre_interval AUC_h AUC_d</span> +<span class="r-out co"><span class="r-pr">#></span> 1 44.375 4.167238 0.208 44.375 17.77202 0.740501</span> +<span class="r-out co"><span class="r-pr">#></span> 2 55.042 40.584010 0.583 10.459 398.21189 16.592162</span> +<span class="r-out co"><span class="r-pr">#></span> Event statistics for threshold 10 </span> +<span class="r-out co"><span class="r-pr">#></span> t_start cwa_max duration pre_interval AUC_h AUC_d</span> +<span class="r-out co"><span class="r-pr">#></span> 1 55.083 40.58401 0.459 55.083 379.433 15.80971</span> </code></pre></div> </div> </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> diff --git a/docs/reference/TSCF-1.png b/docs/reference/TSCF-1.png Binary files differindex 048befb..788f4d3 100644 --- a/docs/reference/TSCF-1.png +++ b/docs/reference/TSCF-1.png diff --git a/docs/reference/TSCF.html b/docs/reference/TSCF.html index eb1398b..6ac2f56 100644 --- a/docs/reference/TSCF.html +++ b/docs/reference/TSCF.html @@ -83,7 +83,7 @@ or ionic.</p> <div class="section level2"> <h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a></h2> <p>FOCUS (2014) Generic Guidance for Tier 1 FOCUS Ground Water Assessments. - Version 2.2, May 2014 +Version 2.2, May 2014 Dettenmaier EM, Doucette WJ and Bugbee B (2009) Chemical hydrophobicity and uptake by plant roots. Environ. Sci. Technol 43, 324 - 329</p> </div> @@ -91,13 +91,11 @@ by plant roots. Environ. Sci. Technol 43, 324 - 329</p> <div class="section level2"> <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2> <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">TSCF</span>, <span class="op">-</span><span class="fl">1</span>, <span class="fl">5</span>, xlab <span class="op">=</span> <span class="st">"log Kow"</span>, ylab <span class="op">=</span> <span class="st">"TSCF"</span>, ylim <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">0</span>, <span class="fl">1.1</span><span class="op">)</span><span class="op">)</span></span></span> -<span class="r-plt img"><img src="TSCF-1.png" alt="" width="700" height="433"></span> <span class="r-in"><span><span class="va">TSCF_2</span> <span class="op"><-</span> <span class="kw">function</span><span class="op">(</span><span class="va">x</span><span class="op">)</span> <span class="fu">TSCF</span><span class="op">(</span><span class="va">x</span>, method <span class="op">=</span> <span class="st">"dettenmaier09"</span><span class="op">)</span></span></span> <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/curve.html" class="external-link">curve</a></span><span class="op">(</span><span class="va">TSCF_2</span>, <span class="op">-</span><span class="fl">1</span>, <span class="fl">5</span>, add <span class="op">=</span> <span class="cn">TRUE</span>, lty <span class="op">=</span> <span class="fl">2</span><span class="op">)</span></span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in curve(TSCF_2, -1, 5, add = TRUE, lty = 2):</span> could not find function "curve"</span> <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/graphics/legend.html" class="external-link">legend</a></span><span class="op">(</span><span class="st">"topright"</span>, lty <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fl">2</span>, bty <span class="op">=</span> <span class="st">"n"</span>,</span></span> <span class="r-in"><span> legend <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"Briggs et al. (1982)"</span>, <span class="st">"Dettenmaier et al. (2009)"</span><span class="op">)</span><span class="op">)</span></span></span> -<span class="r-err co"><span class="r-pr">#></span> <span class="error">Error in legend("topright", lty = 1:2, bty = "n", legend = c("Briggs et al. (1982)", "Dettenmaier et al. (2009)")):</span> could not find function "legend"</span> +<span class="r-plt img"><img src="TSCF-1.png" alt="" width="700" height="433"></span> </code></pre></div> </div> </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2> diff --git a/docs/reference/endpoint.html b/docs/reference/endpoint.html index 5e038b1..b17611e 100644 --- a/docs/reference/endpoint.html +++ b/docs/reference/endpoint.html @@ -115,12 +115,12 @@ this function.</p> <dt>value</dt> -<dd><p>The name of the value we want. The list given in the +<dd><p>The name of the value we want. The list given in the usage section is not exclusive</p></dd> <dt>aggregator</dt> -<dd><p>The aggregator function. Can be mean, +<dd><p>The aggregator function. Can be mean, <code><a href="geomean.html">geomean</a></code>, or identity, for example.</p></dd> @@ -147,10 +147,10 @@ about precision?</p></dd> <p>The result from applying the aggregator function to - the values converted to a numeric vector, rounded to the - given number of significant digits, or, if raw = TRUE, - the values as a character value, retaining any implicit - information on precision that may be present.</p> +the values converted to a numeric vector, rounded to the +given number of significant digits, or, if raw = TRUE, +the values as a character value, retaining any implicit +information on precision that may be present.</p> </div> <div class="section level2"> <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2> diff --git a/docs/reference/max_twa.html b/docs/reference/max_twa.html index 98088fa..15d5201 100644 --- a/docs/reference/max_twa.html +++ b/docs/reference/max_twa.html @@ -82,10 +82,10 @@ SFO, FOMC and DFOP models and to the parent compound</p> <div class="section level2"> <h2 id="references">References<a class="anchor" aria-label="anchor" href="#references"></a></h2> <p>FOCUS (2006) “Guidance Document on Estimating Persistence and - Degradation Kinetics from Environmental Fate Studies on Pesticides in EU - Registration” Report of the FOCUS Work Group on Degradation Kinetics, - EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, - <a href="http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics" class="external-link">http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics</a></p> +Degradation Kinetics from Environmental Fate Studies on Pesticides in EU +Registration” Report of the FOCUS Work Group on Degradation Kinetics, +EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, +<a href="http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics" class="external-link">http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics</a></p> </div> <div class="section level2"> <h2 id="see-also">See also<a class="anchor" aria-label="anchor" href="#see-also"></a></h2> diff --git a/docs/reference/perc_runoff_exposit.html b/docs/reference/perc_runoff_exposit.html index ee29f54..ba35561 100644 --- a/docs/reference/perc_runoff_exposit.html +++ b/docs/reference/perc_runoff_exposit.html @@ -50,23 +50,23 @@ <div class="section level2"> <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2> <p>A data frame with percentage values for the dissolved fraction and the fraction - bound to eroding particles, with Koc classes used as row names</p><dl><dt>Koc_lower_bound</dt> +bound to eroding particles, with Koc classes used as row names</p><dl><dt>Koc_lower_bound</dt> <dd><p>The lower bound of the Koc class</p></dd> - <dt>dissolved</dt> +<dt>dissolved</dt> <dd><p>The percentage of the applied substance transferred to an - adjacent water body in the dissolved phase</p></dd> +adjacent water body in the dissolved phase</p></dd> - <dt>bound</dt> +<dt>bound</dt> <dd><p>The percentage of the applied substance transferred to an - adjacent water body bound to eroding particles</p></dd> +adjacent water body bound to eroding particles</p></dd> + - </dl></div> <div class="section level2"> <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2> <p>Excel 3.02 spreadsheet available from - <a href="https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html" class="external-link">https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html</a></p> +<a href="https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html" class="external-link">https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html</a></p> </div> <div class="section level2"> diff --git a/docs/reference/perc_runoff_reduction_exposit.html b/docs/reference/perc_runoff_reduction_exposit.html index f398ca1..808b110 100644 --- a/docs/reference/perc_runoff_reduction_exposit.html +++ b/docs/reference/perc_runoff_reduction_exposit.html @@ -59,17 +59,17 @@ vegetated buffer widths as row names. The names of the list items are the Exposi from which the values were taken.</p><dl><dt>dissolved</dt> <dd><p>The reduction percentage for the dissolved phase</p></dd> - <dt>bound</dt> +<dt>bound</dt> <dd><p>The reduction percentage for the particulate phase</p></dd> - + </dl></div> <div class="section level2"> <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2> <p>Excel 3.02 spreadsheet available from - <a href="https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html" class="external-link">https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html</a></p> +<a href="https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html" class="external-link">https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html</a></p> <p>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.</p> +The variant 3.01a2 was introduced for consistency with previous calculations performed by Agroscope for a 3 m buffer zone.</p> </div> <div class="section level2"> diff --git a/docs/reference/soil_scenario_data_EFSA_2015.html b/docs/reference/soil_scenario_data_EFSA_2015.html index 239596c..79cfc68 100644 --- a/docs/reference/soil_scenario_data_EFSA_2015.html +++ b/docs/reference/soil_scenario_data_EFSA_2015.html @@ -1,8 +1,8 @@ <!DOCTYPE html> -<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the -concentration in soil as given in the EFSA guidance (2015, p. 13/14). 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Also, the +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the +concentration in soil as given in the EFSA guidance (2015, p. 13/14). 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Also, the scenario and model adjustment factors from p. 15 and p. 17 are included."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> @@ -47,25 +47,25 @@ scenario and model adjustment factors from p. 15 and p. 17 are included."><!-- m </div> <div class="ref-description section level2"> - <p>Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the -concentration in soil as given in the EFSA guidance (2015, p. 13/14). Also, the + <p>Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the +concentration in soil as given in the EFSA guidance (2015, p. 13/14). Also, the scenario and model adjustment factors from p. 15 and p. 17 are included.</p> </div> <div class="section level2"> <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2> - <p>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. <code>rho</code> is the dry bulk density of the top soil.</p> + <p>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. <code>rho</code> is the dry bulk density of the top soil.</p> </div> <div class="section level2"> <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2> <p>EFSA (European Food Safety Authority) (2015) - EFSA guidance document for predicting environmental concentrations - of active substances of plant protection products and transformation products of these - active substances in soil. <em>EFSA Journal</em> <b>13</b>(4) 4093 - doi:10.2903/j.efsa.2015.4093</p> +EFSA guidance document for predicting environmental concentrations +of active substances of plant protection products and transformation products of these +active substances in soil. <em>EFSA Journal</em> <b>13</b>(4) 4093 +doi:10.2903/j.efsa.2015.4093</p> </div> <div class="section level2"> diff --git a/docs/reference/soil_scenario_data_EFSA_2017.html b/docs/reference/soil_scenario_data_EFSA_2017.html index 8e5739e..11eaa53 100644 --- a/docs/reference/soil_scenario_data_EFSA_2017.html +++ b/docs/reference/soil_scenario_data_EFSA_2017.html @@ -1,8 +1,8 @@ <!DOCTYPE html> -<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the -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."><title>Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017 • pfm</title><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017"><meta property="og:description" content="Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the -concentration in soil as given in the EFSA guidance (2017, p. 14/15). Also, the +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the +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."><title>Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017 • pfm</title><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017"><meta property="og:description" content="Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the +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."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]> <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> @@ -47,25 +47,25 @@ scenario and model adjustment factors from p. 16 and p. 18 are included."><!-- m </div> <div class="ref-description section level2"> - <p>Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the -concentration in soil as given in the EFSA guidance (2017, p. 14/15). Also, the + <p>Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the +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.</p> </div> <div class="section level2"> <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2> - <p>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. <code>rho</code> is the dry bulk density of the top soil.</p> + <p>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. <code>rho</code> is the dry bulk density of the top soil.</p> </div> <div class="section level2"> <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2> <p>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. <em>EFSA Journal</em> <b>15</b>(10) 4982 - doi:10.2903/j.efsa.2017.4982</p> +EFSA guidance document for predicting environmental concentrations +of active substances of plant protection products and transformation products of these +active substances in soil. <em>EFSA Journal</em> <b>15</b>(10) 4982 +doi:10.2903/j.efsa.2017.4982</p> </div> <div class="section level2"> diff --git a/docs/search.json b/docs/search.json index 220611b..6a26a16 100644 --- a/docs/search.json +++ b/docs/search.json @@ -1 +1 @@ -[{"path":"https://pkgdown.jrwb.de/pfm/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Johannes Ranke. Author, maintainer.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Johannes Ranke (2023). pfm: Utilities Pesticide Fate Modelling. R package version 0.6.0, https://github.com/jranke/pfm, https://pkgdown.jrwb.de/pfm.","code":"@Manual{, title = {pfm: Utilities for Pesticide Fate Modelling}, author = {{Johannes Ranke}}, year = {2023}, note = {R package version 0.6.0, https://github.com/jranke/pfm}, url = {https://pkgdown.jrwb.de/pfm}, }"},{"path":"https://pkgdown.jrwb.de/pfm/index.html","id":"pfm","dir":"","previous_headings":"","what":"Utilities for Pesticide Fate Modelling","title":"Utilities for Pesticide Fate Modelling","text":"R package pfm provides utilities fate modelling, including dealing FOCUS pesticide fate modelling tools, (currently TOXSWA cwa files), made available GNU public license.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Utilities for Pesticide Fate Modelling","text":"easiest way install package probably use drat: Alternatively can install package using devtools package. Using quick = TRUE skips docs, multiple-architecture builds, demos, vignettes.","code":"install.packages(\"drat\") drat::addRepo(\"jranke\") install.packages(\"pfm\") library(devtools) install_github(\"jranke/pfm\", quick = TRUE)"},{"path":"https://pkgdown.jrwb.de/pfm/index.html","id":"use","dir":"","previous_headings":"","what":"Use","title":"Utilities for Pesticide Fate Modelling","text":"Please refer reference.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/index.html","id":"examples","dir":"","previous_headings":"","what":"Examples","title":"Utilities for Pesticide Fate Modelling","text":"One recent nice example usage package visualisation time weighted average sawtooth curve obtained several overlays mkinfit predictions shown .","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_GW_interception_2014.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014","title":"Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014","text":"Subset EFSA crop interception default values groundwater modelling","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_GW_interception_2014.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014","text":"matrix containing interception values, currently selected crops","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_GW_interception_2014.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014","text":"European Food Safety Authority (2014) EFSA Guidance Document evaluating laboratory field dissipation studies obtain DegT50 values active substances plant protection products transformation products active substances soil. EFSA Journal 12(5):3662, 37 pp., doi:10.2903/j.efsa.2014.3662","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_GW_interception_2014.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014","text":"","code":"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 #> 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 #> Peas 0 0.35 0.55 0.55 0.85 0.85 0.85 0.85 0.85 0.85 #> Summer oilseed rape 0 0.40 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.90 #> Winter oilseed rape 0 0.40 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.90 #> Tomatoes 0 0.50 0.70 0.70 0.80 0.80 0.80 0.80 0.80 0.50 #> Spring cereals 0 0.00 0.20 0.80 0.90 0.90 0.90 0.80 0.80 0.80 #> Winter cereals 0 0.00 0.20 0.80 0.90 0.90 0.90 0.80 0.80 0.80"},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_washoff_2017.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset of EFSA crop washoff default values — EFSA_washoff_2017","title":"Subset of EFSA crop washoff default values — EFSA_washoff_2017","text":"Subset EFSA crop washoff default values","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_washoff_2017.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Subset of EFSA crop washoff default values — EFSA_washoff_2017","text":"matrix containing wash-factors, currently selected crops","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_washoff_2017.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Subset of EFSA crop washoff default values — EFSA_washoff_2017","text":"European Food Safety Authority (2017) EFSA guidance document predicting environmental concentrations active substances plant protection products transformation products active substances soil. EFSA Journal 15(10) 4982 doi:10.2903/j.efsa.2017.4982","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_washoff_2017.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Subset of EFSA crop washoff default values — EFSA_washoff_2017","text":"","code":"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 #> 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 #> Peas NA 0.40 0.60 0.60 0.65 0.65 0.65 0.65 0.65 0.35 #> Summer oilseed rape NA 0.40 0.50 0.50 0.60 0.60 0.60 0.60 0.60 0.50 #> Winter oilseed rape NA 0.10 0.40 0.40 0.55 0.55 0.55 0.55 0.55 0.30 #> Tomatoes NA 0.55 0.75 0.75 0.70 0.70 0.70 0.70 0.70 0.35 #> Spring cereals NA 0.40 0.50 0.50 0.65 0.65 0.65 0.65 0.65 0.55 #> Winter cereals NA 0.10 0.40 0.60 0.55 0.55 0.55 0.60 0.60 0.40"},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_GW_scenarios_2012.html","id":null,"dir":"Reference","previous_headings":"","what":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","title":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","text":"Currently, scenario names acronyms small subset soil definitions provided. soil definitions page 46ff. FOCUS (2012).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_GW_scenarios_2012.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","text":"","code":"FOCUS_GW_scenarios_2012"},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_GW_scenarios_2012.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","text":"object class list length 2.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_GW_scenarios_2012.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","text":"FOCUS (2012) Generic guidance Tier 1 FOCUS ground water assessments. Version 2.1. FOrum Co-ordination pesticde fate models USe. http://focus.jrc.ec.europa.eu/gw/docs/Generic_guidance_FOCV2_1.pdf","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_GW_scenarios_2012.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","text":"","code":"FOCUS_GW_scenarios_2012 #> $names #> Cha Ham Jok Kre Oke #> \"Châteaudun\" \"Hamburg\" \"Jokioinen\" \"Kremsmünster\" \"Okehampton\" #> Pia Por Sev Thi #> \"Piacenza\" \"Porto\" \"Sevilla\" \"Thiva\" #> #> $soils #> location horizon number pH_H2O perc_clay perc_oc rel_deg #> 1 Cha Ap 1 8.0 30.0 1.39 1.0 #> 2 Cha B1 2 8.1 31.0 0.93 0.5 #> 3 Cha B2 3 8.2 25.0 0.70 0.5 #> 4 Cha II C1 4 8.5 26.0 0.30 0.3 #> 5 Cha II C1 5 8.5 26.0 0.30 0.0 #> 6 Cha II C2 6 8.5 24.0 0.27 0.0 #> 7 Cha M 7 8.3 31.0 0.21 0.0 #> 8 Ham Ap 1 6.4 7.2 1.50 1.0 #> 9 Ham BvI 2 5.6 6.7 1.00 0.5 #> 10 Ham BvII 3 5.6 0.9 0.20 0.3 #> 11 Ham Bv/Cv 4 5.7 0.0 0.00 0.3 #> 12 Ham Cv 5 5.5 0.0 0.00 0.3 #> 13 Ham Cv 6 5.5 0.0 0.00 0.0 #> 14 Jok Ap 1 6.2 3.6 4.06 1.0 #> 15 Jok Bs 2 5.6 1.8 0.84 0.5 #> 16 Jok BC1 3 5.4 1.2 0.36 0.3 #> 17 Jok BC2 4 5.4 1.7 0.29 0.3 #> 18 Jok BC2 5 5.4 1.7 0.29 0.0 #> 19 Jok Cg 6 5.3 1.9 0.21 0.0 #> 20 Kre <NA> 1 7.7 14.0 3.60 1.0 #> 21 Kre <NA> 2 7.0 25.0 1.00 0.5 #> 22 Kre <NA> 3 7.1 27.0 0.50 0.5 #> 23 Kre <NA> 4 7.1 27.0 0.50 0.3 #> 24 Kre <NA> 5 7.1 27.0 0.50 0.0 #> 25 Oke A 1 5.8 18.0 2.20 1.0 #> 26 Oke Bw1 2 6.3 17.0 0.70 0.5 #> 27 Oke BC 3 6.5 14.0 0.40 0.3 #> 28 Oke C 4 6.6 9.0 0.10 0.3 #> 29 Oke C 5 6.6 9.0 0.10 0.0 #> 30 Pia Ap 1 7.0 15.0 1.26 1.0 #> 31 Pia Ap 2 7.0 15.0 1.26 0.5 #> 32 Pia Bw 3 6.3 7.0 0.47 0.5 #> 33 Pia Bw 4 6.3 7.0 0.47 0.3 #> 34 Pia 2C 5 6.4 0.0 0.00 0.3 #> 35 Pia 2C 6 6.4 0.0 0.00 0.0 #> 36 Por <NA> 1 4.9 10.0 1.42 1.0 #> 37 Por <NA> 2 4.8 8.0 0.78 0.5 #> 38 Por <NA> 3 4.8 8.0 0.78 0.3 #> 39 Por <NA> 4 4.8 8.0 0.78 0.0 #> 40 Sev <NA> 1 7.3 14.0 0.93 1.0 #> 41 Sev <NA> 2 7.3 13.0 0.93 1.0 #> 42 Sev <NA> 3 7.8 15.0 0.70 0.5 #> 43 Sev <NA> 4 8.1 16.0 0.58 0.3 #> 44 Sev <NA> 5 8.1 16.0 0.58 0.0 #> 45 Sev <NA> 6 8.2 22.0 0.49 0.0 #> 46 Thi Ap1 1 7.7 25.3 0.74 1.0 #> 47 Thi Ap2 2 7.7 25.3 0.74 0.5 #> 48 Thi Bw 3 7.8 29.6 0.57 0.5 #> 49 Thi Bw 4 7.8 31.9 0.31 0.3 #> 50 Thi Ck1 5 7.8 32.9 0.18 0.3 #> 51 Thi Ck1 6 7.8 32.9 0.18 0.0 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_Step_12_scenarios.html","id":null,"dir":"Reference","previous_headings":"","what":"Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios","title":"Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios","text":"data extracted scenario.txt file using R code shown . text file included package licence clear.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_Step_12_scenarios.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios","text":"list containing scenario names character vector called 'names', drift percentiles matrix called 'drift', interception percentages matrix called 'interception' runoff/drainage percentages Step 2 calculations matrix called 'rd'.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_Step_12_scenarios.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios","text":"","code":"if (FALSE) { # This is the code that was used to extract the data scenario_path <- \"inst/extdata/FOCUS_Step_12_scenarios.txt\" scenarios <- readLines(scenario_path)[9:38] FOCUS_Step_12_scenarios <- list() sce <- read.table(text = scenarios, sep = \"\\t\", header = TRUE, check.names = FALSE, stringsAsFactors = FALSE) FOCUS_Step_12_scenarios$names = sce$Crop rownames(sce) <- sce$Crop FOCUS_Step_12_scenarios$drift = sce[, 3:11] FOCUS_Step_12_scenarios$interception = sce[, 12:15] sce_2 <- readLines(scenario_path)[41:46] rd <- read.table(text = sce_2, sep = \"\\t\")[1:2] rd_mat <- matrix(rd$V2, nrow = 3, byrow = FALSE) dimnames(rd_mat) = list(Time = c(\"Oct-Feb\", \"Mar-May\", \"Jun-Sep\"), Region = c(\"North\", \"South\")) FOCUS_Step_12_scenarios$rd = rd_mat save(FOCUS_Step_12_scenarios, file = \"data/FOCUS_Step_12_scenarios.RData\") } # And this is the resulting data FOCUS_Step_12_scenarios #> $names #> [1] \"cereals, spring\" \"cereals, winter\" #> [3] \"citrus\" \"cotton\" #> [5] \"field beans\" \"grass / alfalfa\" #> [7] \"hops\" \"legumes\" #> [9] \"maize\" \"oil seed rape, spring\" #> [11] \"oil seed rape, winter\" \"olives\" #> [13] \"pome / stone fruit, early applns\" \"pome / stone fruit, late applns\" #> [15] \"potatoes\" \"soybeans\" #> [17] \"sugar beets\" \"sunflowers\" #> [19] \"tobacco\" \"vegetables, bulb\" #> [21] \"vegetables, fruiting\" \"vegetables, leafy\" #> [23] \"vegetables, root\" \"vines, early applns\" #> [25] \"vines, late applns\" \"appln, aerial\" #> [27] \"appln, hand (crop < 50 cm)\" \"appln, hand (crop > 50 cm)\" #> [29] \"no drift (incorp or seed trtmt)\" #> #> $drift #> 1 2 3 4 5 6 #> cereals, spring 2.759 2.438 2.024 1.862 1.794 1.631 #> cereals, winter 2.759 2.438 2.024 1.862 1.794 1.631 #> citrus 15.725 12.129 11.011 10.124 9.743 9.204 #> cotton 2.759 2.438 2.024 1.862 1.794 1.631 #> field beans 2.759 2.438 2.024 1.862 1.794 1.631 #> grass / alfalfa 2.759 2.438 2.024 1.862 1.794 1.631 #> hops 19.326 17.723 15.928 15.378 15.114 14.902 #> legumes 2.759 2.438 2.024 1.862 1.794 1.631 #> maize 2.759 2.438 2.024 1.862 1.794 1.631 #> oil seed rape, spring 2.759 2.438 2.024 1.862 1.794 1.631 #> oil seed rape, winter 2.759 2.438 2.024 1.862 1.794 1.631 #> olives 15.725 12.129 11.011 10.124 9.743 9.204 #> pome / stone fruit, early applns 29.197 25.531 23.960 23.603 23.116 22.760 #> pome / stone fruit, late applns 15.725 12.129 11.011 10.124 9.743 9.204 #> potatoes 2.759 2.438 2.024 1.862 1.794 1.631 #> soybeans 2.759 2.438 2.024 1.862 1.794 1.631 #> sugar beets 2.759 2.438 2.024 1.862 1.794 1.631 #> sunflowers 2.759 2.438 2.024 1.862 1.794 1.631 #> tobacco 2.759 2.438 2.024 1.862 1.794 1.631 #> vegetables, bulb 2.759 2.438 2.024 1.862 1.794 1.631 #> vegetables, fruiting 2.759 2.438 2.024 1.862 1.794 1.631 #> vegetables, leafy 2.759 2.438 2.024 1.862 1.794 1.631 #> vegetables, root 2.759 2.438 2.024 1.862 1.794 1.631 #> vines, early applns 2.699 2.496 2.546 2.499 2.398 2.336 #> vines, late applns 8.028 7.119 6.898 6.631 6.636 6.431 #> appln, aerial 33.200 33.200 33.200 33.200 33.200 33.200 #> appln, hand (crop < 50 cm) 2.759 2.438 2.024 1.862 1.794 1.631 #> appln, hand (crop > 50 cm) 8.028 7.119 6.898 6.631 6.636 6.431 #> no drift (incorp or seed trtmt) 0.000 0.000 0.000 0.000 0.000 0.000 #> 7 8 >8 #> cereals, spring 1.578 1.512 1.512 #> cereals, winter 1.578 1.512 1.512 #> citrus 9.102 8.656 8.656 #> cotton 1.578 1.512 1.512 #> field beans 1.578 1.512 1.512 #> grass / alfalfa 1.578 1.512 1.512 #> hops 14.628 13.520 13.520 #> legumes 1.578 1.512 1.512 #> maize 1.578 1.512 1.512 #> oil seed rape, spring 1.578 1.512 1.512 #> oil seed rape, winter 1.578 1.512 1.512 #> olives 9.102 8.656 8.656 #> pome / stone fruit, early applns 22.690 22.241 22.241 #> pome / stone fruit, late applns 9.102 8.656 8.656 #> potatoes 1.578 1.512 1.512 #> soybeans 1.578 1.512 1.512 #> sugar beets 1.578 1.512 1.512 #> sunflowers 1.578 1.512 1.512 #> tobacco 1.578 1.512 1.512 #> vegetables, bulb 1.578 1.512 1.512 #> vegetables, fruiting 1.578 1.512 1.512 #> vegetables, leafy 1.578 1.512 1.512 #> vegetables, root 1.578 1.512 1.512 #> vines, early applns 2.283 2.265 2.265 #> vines, late applns 6.227 6.173 6.173 #> appln, aerial 33.200 33.200 33.200 #> appln, hand (crop < 50 cm) 1.578 1.512 1.512 #> appln, hand (crop > 50 cm) 6.227 6.173 6.173 #> no drift (incorp or seed trtmt) 0.000 0.000 0.000 #> #> $interception #> no interception minimal crop cover #> cereals, spring 0 0.00 #> cereals, winter 0 0.00 #> citrus 0 0.80 #> cotton 0 0.30 #> field beans 0 0.25 #> grass / alfalfa 0 0.40 #> hops 0 0.20 #> legumes 0 0.25 #> maize 0 0.25 #> oil seed rape, spring 0 0.40 #> oil seed rape, winter 0 0.40 #> olives 0 0.70 #> pome / stone fruit, early applns 0 0.20 #> pome / stone fruit, late applns 0 0.20 #> potatoes 0 0.15 #> soybeans 0 0.20 #> sugar beets 0 0.20 #> sunflowers 0 0.20 #> tobacco 0 0.20 #> vegetables, bulb 0 0.10 #> vegetables, fruiting 0 0.25 #> vegetables, leafy 0 0.25 #> vegetables, root 0 0.25 #> vines, early applns 0 0.40 #> vines, late applns 0 0.40 #> appln, aerial 0 0.20 #> appln, hand (crop < 50 cm) 0 0.20 #> appln, hand (crop > 50 cm) 0 0.20 #> no drift (incorp or seed trtmt) 0 0.00 #> average crop cover full canopy #> cereals, spring 0.20 0.70 #> cereals, winter 0.20 0.70 #> citrus 0.80 0.80 #> cotton 0.60 0.75 #> field beans 0.40 0.70 #> grass / alfalfa 0.60 0.75 #> hops 0.50 0.70 #> legumes 0.50 0.70 #> maize 0.50 0.75 #> oil seed rape, spring 0.70 0.75 #> oil seed rape, winter 0.70 0.75 #> olives 0.70 0.70 #> pome / stone fruit, early applns 0.40 0.65 #> pome / stone fruit, late applns 0.40 0.65 #> potatoes 0.50 0.70 #> soybeans 0.50 0.75 #> sugar beets 0.70 0.75 #> sunflowers 0.50 0.75 #> tobacco 0.70 0.75 #> vegetables, bulb 0.25 0.40 #> vegetables, fruiting 0.50 0.70 #> vegetables, leafy 0.40 0.70 #> vegetables, root 0.50 0.70 #> vines, early applns 0.50 0.60 #> vines, late applns 0.50 0.60 #> appln, aerial 0.50 0.70 #> appln, hand (crop < 50 cm) 0.50 0.70 #> appln, hand (crop > 50 cm) 0.50 0.70 #> no drift (incorp or seed trtmt) 0.00 0.00 #> #> $rd #> Region #> Time North South #> Oct-Feb 5 4 #> Mar-May 2 4 #> Jun-Sep 2 3 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":null,"dir":"Reference","previous_headings":"","what":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"Actual maximum moving window time average concentrations FOMC kinetics","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"","code":"FOMC_actual_twa( alpha = 1.0001, beta = 10, times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100) )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"FOCUS (2014) Generic Guidance Estimating Persistence Degradation Kinetics Environmental Fate Studies Pesticides EU Registration, Version 1.1, 18 December 2014, p. 251","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"alpha Parameter FOMC model beta Parameter FOMC model times output times, window sizes time weighted average concentrations","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"","code":"FOMC_actual_twa(alpha = 1.0001, beta = 10) #> actual twa #> 0 1.00000000 NaN #> 1 0.90908224 0.9530973 #> 2 0.83331814 0.9115995 #> 4 0.71426168 0.8411664 #> 7 0.58820408 0.7580202 #> 14 0.41663019 0.6253074 #> 21 0.32254415 0.5387324 #> 28 0.26312277 0.4767543 #> 42 0.19227599 0.3925054 #> 50 0.16663681 0.3583198 #> 100 0.09088729 0.2397608"},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":null,"dir":"Reference","previous_headings":"","what":"Groundwater ubiquity score based on Gustafson (1989) — GUS","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"groundwater ubiquity score GUS calculated according following equation $$GUS = \\log_{10} DT50_{soil} (4 - \\log_{10} K_{oc})$$","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"","code":"GUS(...) # S3 method for numeric GUS(DT50, Koc, ...) # S3 method for chent GUS( chent, degradation_value = \"DT50ref\", lab_field = \"laboratory\", redox = \"aerobic\", sorption_value = \"Kfoc\", degradation_aggregator = geomean, sorption_aggregator = geomean, ... ) # S3 method for GUS_result print(x, ..., digits = 1)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"... Included generic allow arguments later. Therefore also added specific methods. DT50 Half-life chemical soil. field half-life according Gustafson (1989). However, leaching sub-soil can completely excluded field dissipation experiments Gustafson refer normalisation procedure, says field study conducted use conditions. Koc sorption constant normalised organic carbon. Gustafson mention nonlinearity sorption constant commonly found usually described Freundlich sorption, therefore unclear reference concentration Koc observed (reference concentration soil porewater). chent chent given appropriate information present chyaml field, information used, defaults specified . degradation_value available degradation values used? lab_field laboratory field half-lives used? defaults lab implementation, order avoid double-accounting mobility. comparability original GUS values given Gustafson (1989) desired, non-normalised first-order field half-lives obtained actual use conditions used. redox Aerobic anaerobic degradation data sorption_value available sorption values used? Defaults Kfoc generally available European pesticide peer review process. values generally use reference concentration 1 mg/L porewater, means expected Koc values concentration 1 mg/L water phase. degradation_aggregator Function aggregating half-lives sorption_aggregator Function aggregation Koc values x object class GUS_result printed digits number digits used print method","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"list DT50 Koc used well resulting score class GUS_result","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"Gustafson, David . (1989) Groundwater ubiquity score: simple method assessing pesticide leachability. Environmental toxicology chemistry 8(4) 339–57.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_FOMC_accu_rel.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","title":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","text":"Get relative accumulation FOMC model multiples interval","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_FOMC_accu_rel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","text":"","code":"PEC_FOMC_accu_rel(n, interval, FOMC)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_FOMC_accu_rel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","text":"n number applications interval Time applications FOMC Named numeric vector containing FOMC parameters alpha beta","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_FOMC_accu_rel.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","text":"numeric vector containing n accumulation factors n applications","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate predicted environmental concentrations in soil — PEC_soil","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"basic calculation contaminant concentration bulk soil based complete, instantaneous mixing. interval given, attempt made calculating long term maximum concentration using concepts layed PPR panel opinion (EFSA PPR panel 2012 EFSA guidance PEC soil calculations (EFSA, 2015, 2017).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"","code":"PEC_soil( rate, rate_units = \"g/ha\", interception = 0, mixing_depth = 5, PEC_units = \"mg/kg\", PEC_pw_units = \"mg/L\", interval = NA, n_periods = Inf, tillage_depth = 20, leaching_depth = tillage_depth, crop = \"annual\", cultivation = FALSE, chent = NA, DT50 = NA, FOMC = NA, Koc = NA, Kom = Koc/1.724, t_avg = 0, t_act = NULL, scenarios = c(\"default\", \"EFSA_2017\", \"EFSA_2015\"), leaching = scenarios == \"EFSA_2017\", porewater = FALSE )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"rate Application rate units specified rate_units Defaults g/ha interception fraction application rate reach soil mixing_depth Mixing depth cm PEC_units Requested units calculated PEC. mg/kg currently supported PEC_pw_units mg/L currently supported interval Period deeper mixing. default NA, .e. deeper mixing. annual deeper mixing, set 365 degradation units days n_periods Number periods considered long term PEC calculations tillage_depth Periodic (see interval) deeper mixing cm leaching_depth EFSA (2017) uses mixing depth (ecotoxicological evaluation depth) calculate leaching annual crops tillage takes place. default, losses layer tillage depth taken account implementation. crop Ignored scenarios EFSA_2017. annual crops supported scenarios used. crops single cropping cycle per year currently supported. cultivation mechanical cultivation sense EFSA (2017) take place, .e. twice year depth 5 cm? Ignored scenarios EFSA_2017 chent optional chent object holding substance specific information. Can also name substance character string DT50 specified, overrides soil DT50 endpoints chent object DT50 specified available chent object, zero degradation assumed FOMC specified, named numeric vector containing FOMC parameters alpha beta. overrides degradation endpoints, degradation interval maximum PEC calculated using parameters without temperature correction Koc specified, overrides Koc endpoints chent object Kom Calculated Koc default, can explicitly specified Kom t_avg Averaging times time weighted average concentrations t_act Time series actual concentrations scenarios 'default', DT50 used without correction soil properties specified REACH guidance (R.16, Table R.16-9) used porewater PEC calculations. \"EFSA_2015\", DT50 taken modelling half-life 20°C pF2 ('chent' specified, DegT50 destination 'PECgw' used), corrected using Arrhenius activation energy 65.4 kJ/mol. Also model scenario adjustment factors EFSA guidance used. leaching leaching taken account? default FALSE, except EFSA_2017 scenarios used. porewater equilibrium porewater concentrations estimated based Kom organic carbon fraction soil instead total soil concentrations? Based equation (7) given PPR panel opinion (EFSA 2012, p. 24) scenarios specified EFSA guidance (2015, p. 13).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"predicted concentration soil","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"assumes complete load soil time specified 'interval' (typically 365 days) dosed . PPR panel opinion cited (EFSA PPR panel 2012), temperature correction using Arrhenius equation performed. Total soil porewater PEC values scenarios defined EFSA guidance (2017, p. 14/15) can easily calculated.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"time weighted average (TWA) concentrations given examples EFSA guidance 2015 (p. 80) reproduced, true TWA concentrations given example EFSA guidance 2017 (p. 92). According EFSA guidance (EFSA, 2017, p. 43), leaching taken account EFSA 2017 scenarios, using evaluation depth (mixing depth) depth layer leaching takes place. However, amount leaching evaluation depth (often 5 cm) partly mixed back tillage, default function use tillage depth calculation leaching rate. temperature information available selected scenarios, e.g. EFSA scenarios, DT50 groundwater modelling (destination 'PECgw') taken chent object, otherwise DT50 destination 'PECsoil'.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"EFSA Panel Plant Protection Products Residues (2012) Scientific Opinion science behind guidance scenario selection scenario parameterisation predicting environmental concentrations plant protection products soil. EFSA Journal 10(2) 2562, doi:10.2903/j.efsa.2012.2562 EFSA (European Food Safety Authority) 2017) EFSA guidance document predicting environmental concentrations active substances plant protection products transformation products active substances soil. EFSA Journal 15(10) 4982 doi:10.2903/j.efsa.2017.4982 EFSA (European Food Safety Authority) (2015) EFSA guidance document predicting environmental concentrations active substances plant protection products transformation products active substances soil. EFSA Journal 13(4) 4093 doi:10.2903/j.efsa.2015.4093","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"","code":"PEC_soil(100, interception = 0.25) #> scenario #> t_avg default #> 0 0.1 # This is example 1 starting at p. 92 of the EFSA guidance (2017) # Note that TWA concentrations differ from the ones given in the guidance # for an unknown reason (the values from EFSA (2015) can be reproduced). PEC_soil(1000, interval = 365, DT50 = 250, t_avg = c(0, 21), Kom = 1000, scenarios = \"EFSA_2017\") #> scenario #> t_avg CTN CTC CTS #> 0 19.76834 13.8619 10.53795 #> 21 19.59345 13.7169 10.39882 PEC_soil(1000, interval = 365, DT50 = 250, t_av = c(0, 21), Kom = 1000, scenarios = \"EFSA_2017\", porewater = TRUE) #> scenario #> t_avg CLN CLC CLS #> 0 0.5541984 0.6779249 0.9816693 #> 21 0.5484576 0.6693125 0.9609119 # This is example 1 starting at p. 79 of the EFSA guidance (2015) PEC_soil(1000, interval = 365, DT50 = 250, t_avg = c(0, 21), scenarios = \"EFSA_2015\") #> scenario #> t_avg CTN CTC CTS #> 0 21.96827 11.53750 9.145259 #> 21 21.78517 11.40701 9.017370 PEC_soil(1000, interval = 365, DT50 = 250, t_av = c(0, 21), Kom = 1000, scenarios = \"EFSA_2015\", porewater = TRUE) #> scenario #> t_avg CLN CLC CLS #> 0 0.7589401 0.6674322 0.9147861 #> 21 0.7506036 0.6590345 0.8987279 # The following is from example 4 starting at p. 85 of the EFSA guidance (2015) # Metabolite M2 # Calculate total and porewater soil concentrations for tier 1 scenarios # Relative molar mass is 100/300, formation fraction is 0.7 * 1 results_pfm <- PEC_soil(100/300 * 0.7 * 1 * 1000, interval = 365, DT50 = 250, t_avg = c(0, 21), scenarios = \"EFSA_2015\") results_pfm_pw <- PEC_soil(100/300 * 0.7 * 1000, interval = 365, DT50 = 250, t_av = c(0, 21), Kom = 100, scenarios = \"EFSA_2015\", porewater = TRUE)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil_mets.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets","title":"Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets","text":"Calculate initial accumulation PEC soil set metabolites","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil_mets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets","text":"","code":"PEC_soil_mets(rate, mw_parent, mets, interval = 365, ...)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil_mets.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets","text":"rate Application rate units specified mw_parent molecular weight parent compound mets dataframe metabolite identifiers rownames columns \"mw\", \"occ\" \"DT50\" holding molecular weight, maximum occurrence soil soil DT50 interval interval accumulation calculations ... arguments passed PEC_soil","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"implements method specified UK data requirements handbook checked spreadsheet published CRC website","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"","code":"PEC_sw_drainage_UK( rate, interception = 0, Koc, latest_application = NULL, soil_DT50 = NULL, model = NULL, model_parms = NULL )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"rate Application rate g/ha interception fraction application rate reach soil Koc sorption coefficient normalised organic carbon L/kg latest_application Latest application date, formatted e.g. \"01 July\" soil_DT50 Soil degradation half-life, SFO kinetics used model soil degradation model used. Either one \"FOMC\", \"DFOP\", \"HS\", \"IORE\", mkinmod object model_parms named numeric vector containing model parameters","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"predicted concentration surface water µg/L","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"HSE's Chemicals Regulation Division (CRD) Active substance PECsw calculations (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 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","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"","code":"PEC_sw_drainage_UK(150, Koc = 100) #> [1] 8.076923"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"basic, vectorised form simple calculation contaminant concentration surface water based complete, instantaneous mixing input via spray drift.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"","code":"PEC_sw_drift( rate, applications = 1, water_depth = 30, drift_percentages = NULL, drift_data = c(\"JKI\", \"RF\"), crop = \"Ackerbau\", distances = c(1, 5, 10, 20), rate_units = \"g/ha\", PEC_units = \"µg/L\" )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"rate Application rate units specified applications Number applications selection drift percentile water_depth Depth water body cm drift_percentages Percentage drift values calculate PECsw. 'drift_data' 'distances' NULL. drift_data Source drift percentage data. 'JKI', [drift_data_JKI] included package used. 'RF', Rautmann formula used, implemented crop type number applications crop Crop name (use German names JKI data), defaults \"Ackerbau\" distances distances m get PEC values rate_units Defaults g/ha PEC_units Requested units calculated PEC. µg/L currently supported","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"predicted concentration surface water","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"","code":"PEC_sw_drift(100) #> 1 m 5 m 10 m 20 m #> 0.92333333 0.19000000 0.09666667 0.05000000 # Alternatively, we can use the formula for a single application to \"Ackerbau\" from the paper PEC_sw_drift(100, drift_data = \"RF\") #> 1 m 5 m 10 m 20 m #> 0.92350000 0.19114149 0.09699222 0.04921742 # This makes it possible to also use different substances PEC_sw_drift(100, distances = c(1, 3, 5, 6, 10, 20, 50, 100), drift_data = \"RF\") #> 1 m 3 m 5 m 6 m 10 m 20 m 50 m #> 0.92350000 0.31512171 0.19114149 0.15990435 0.09699222 0.04921742 0.02007497 #> 100 m #> 0.01018678 # Using custom drift percentages is also supported PEC_sw_drift(100, drift_percentages = c(2.77, 0.95, 0.57, 0.48, 0.29, 0.15, 0.06, 0.03)) #> 2.77 % 0.95 % 0.57 % 0.48 % 0.29 % 0.15 % 0.06 % #> 0.92333333 0.31666667 0.19000000 0.16000000 0.09666667 0.05000000 0.02000000 #> 0.03 % #> 0.01000000"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"reimplementation calculation described Exposit 3.02 spreadsheet file, worksheet \"Konzept Drainage\". Although four groups compounds (\"Gefährdungsgruppen\"), one distinction made calculations, compounds low mobility (group 1) compounds modest high mobility (groups 2, 3 4). implementation, group derived Koc, given explicitly. details, see discussion function arguments .","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"","code":"PEC_sw_exposit_drainage( rate, interception = 0, Koc = NA, mobility = c(NA, \"low\", \"high\"), DT50 = Inf, t_drainage = 3, V_ditch = 30, V_drainage = c(spring = 10, autumn = 100), dilution = 2 )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"Excel 3.02 spreadsheet available https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"rate application rate g/ha interception fraction intercepted crop Koc sorption coefficient soil organic carbon used determine mobility. trigger value 550 L/kg used order decide Koc >> 500. mobility Overrides determined Koc. DT50 soil half-life days t_drainage time application drainage event, degradation occurs, days V_ditch volume ditch assumed 1 m * 100 m * 30 cm = 30 m3 V_drainage drainage volume, equivalent 1 mm precipitation 1 ha spring/summer 10 mm autumn/winter/early spring. dilution dilution factor","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"list containing following components perc_runoff runoff percentages dissolved bound substance runoff matrix containing dissolved bound input different distances PEC_sw_runoff matrix containing PEC values dissolved bound substance different distances. rate given g/ha, PECsw microg/L.","code":""},{"path":[]},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"","code":"PEC_sw_exposit_drainage(500, Koc = 150) #> $perc_drainage_total #> spring autumn #> 0.2 1.0 #> #> $perc_peak #> spring autumn #> 12.5 25.0 #> #> $PEC_sw_drainage #> spring autumn #> 1.562500 4.807692 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"reimplementation calculation described Exposit 3.02 spreadsheet file, worksheet \"Konzept Runoff\".","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"","code":"PEC_sw_exposit_runoff( rate, interception = 0, Koc, DT50 = Inf, t_runoff = 3, exposit_reduction_version = c(\"3.02\", \"3.01a\", \"3.01a2\", \"2.0\"), V_ditch = 30, V_event = 100, dilution = 2 )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"Excel 3.02 spreadsheet available https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"rate application rate g/ha interception fraction intercepted crop Koc sorption coefficient soil organic carbon DT50 soil half-life days t_runoff time application runoff event, degradation occurs, days exposit_reduction_version version reduction factors used. \"3.02\" current version used Germany, \"3.01a\" version additional percentages 3 m 6 m buffer zones used Switzerland. \"3.01a2\" version introduced consistency previous calculations performed 3 m buffer zone Switzerland, reduction applied dissolved bound fraction. V_ditch volume ditch assumed 1 m * 100 m * 30 cm = 30 m3 V_event unreduced runoff volume, equivalent 10 mm precipitation 1 ha dilution dilution factor","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"list containing following components perc_runoff runoff percentages dissolved bound substance runoff matrix containing dissolved bound input different distances PEC_sw_runoff matrix containing PEC values dissolved bound substance different distances. rate given g/ha, PECsw microg/L.","code":""},{"path":[]},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"","code":"PEC_sw_exposit_runoff(500, Koc = 150) #> $perc_runoff #> dissolved bound #> 0.248 0.001 #> #> $runoff #> dissolved bound total #> No buffer 1.240 0.00500 1.24500 #> 5 m 0.744 0.00300 0.74700 #> 10 m 0.496 0.00075 0.49675 #> 20 m 0.248 0.00025 0.24825 #> #> $PEC_sw_runoff #> dissolved bound total #> No buffer 4.769231 0.019230769 4.788462 #> 5 m 4.133333 0.016666667 4.150000 #> 10 m 3.542857 0.005357143 3.548214 #> 20 m 2.480000 0.002500000 2.482500 #> PEC_sw_exposit_runoff(600, Koc = 10000, DT50 = 195, exposit = \"3.01a\") #> $perc_runoff #> dissolved bound #> 0.037 0.159 #> #> $runoff #> dissolved bound total #> No buffer 0.21964521 0.94388078 1.16352600 #> 3 m 0.16473391 0.66071655 0.82545046 #> 5 m 0.13178713 0.56632847 0.69811560 #> 6 m 0.12080487 0.42474635 0.54555122 #> 10 m 0.08785809 0.14158212 0.22944020 #> 20 m 0.04392904 0.04719404 0.09112308 #> #> $PEC_sw_runoff #> dissolved bound total #> No buffer 0.8447893 3.6303107 4.4751000 #> 3 m 0.7844472 3.1462693 3.9307165 #> 5 m 0.7321507 3.1462693 3.8784200 #> 6 m 0.7106169 2.4985080 3.2091248 #> 10 m 0.6275578 1.0113008 1.6388586 #> 20 m 0.4392904 0.4719404 0.9112308 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"reimplementation FOCUS Step 1 2 calculator version 3.2, authored Michael Klein, R. Note results multiple applications compared corresponding results single application. current, done automatically implementation. Step 1 PECs calculated. However, input files generated suitable input also Step 2 used FOCUS calculator.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"","code":"PEC_sw_focus( parent, rate, n = 1, i = NA, comment = \"\", met = NULL, f_drift = NA, f_rd = 0.1, scenario = FOCUS_Step_12_scenarios$names, region = c(\"n\", \"s\"), season = c(NA, \"of\", \"mm\", \"js\"), interception = c(\"no interception\", \"minimal crop cover\", \"average crop cover\", \"full canopy\"), met_form_water = TRUE, txt_file = \"pesticide.txt\", overwrite = FALSE, append = TRUE )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"parent list containing substance specific parameters, e.g. conveniently generated [chent_focus_sw]. rate application rate g/ha. Overriden applications given explicitly n number applications application interval comment comment input file met list containing metabolite specific parameters. e.g. conveniently generated [chent_focus_sw]. NULL, PEC calculated compound, parent. f_drift fraction application rate reaching waterbody via drift. NA, derived scenario name number applications via drift data defined [FOCUS_Step_12_scenarios] f_rd fraction amount applied reaching waterbody via runoff/drainage. Step 1, assumed 10 parent metabolite scenario name scenario. Must one scenario names given [FOCUS_Step_12_scenarios] region 'n' Northern Europe 's' Southern Europe. NA, Step 1 PECsw calculated season '' October February, 'mm' March May, 'js' June September. NA, step 1 PECsw calculated interception One 'interception' (default), 'minimal crop cover', 'average crop cover' 'full canopy' met_form_water metabolite formation water taken account? can switched check influence compare previous versions Steps 12 calculator txt_file name, potentially full path Steps.12 input text file specification run(s) written overwrite existing file location specified txt_file overwritten? takes effect append FALSE. append input text file appended?","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"formulas input waterbody via runoff/drainage parent subsequent formation metabolite water documented model description coming calculator. one expect, appears (get results) calculated multiplying application rate molar weight correction formation fraction water/sediment systems. Step 2 implemented.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"FOCUS (2014) Generic guidance Surface Water Scenarios (version 1.4). FOrum Co-ordination pesticde fate models USe. http://esdac.jrc.ec.europa.eu/public_path/projects_data/focus/sw/docs/Generic Website Steps 1 2 calculator Joint Research Center European Union: http://esdac.jrc.ec.europa.eu/projects/stepsonetwo","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"","code":"# Parent only dummy_1 <- chent_focus_sw(\"Dummy 1\", cwsat = 6000, DT50_ws = 6, Koc = 344.8) PEC_sw_focus(dummy_1, 3000, f_drift = 0, overwrite = TRUE, append = FALSE) #> $f_drift #> [1] 0 #> #> $eq_rate_drift_s #> [1] 3000 #> #> $eq_rate_rd_s #> [1] 3000 #> #> $eq_rate_rd_parent_s #> [1] NA #> #> $input_drift_s #> [1] 0 #> #> $input_rd_s #> [1] 300 #> #> $f_rd_sw #> [1] 0.6850566 #> #> $f_rd_sed #> [1] 0.3149434 #> #> $PEC #> type #> Time PECsw TWAECsw PECsed TWAECsed #> 0 6.850566e+02 NA 2.362075e+03 NA #> 1 6.103161e+02 647.68635 2.104370e+03 2233.2225 #> 2 5.437298e+02 612.03420 1.874780e+03 2110.2939 #> 4 4.315586e+02 548.76030 1.488014e+03 1892.1255 #> 7 3.051580e+02 469.88375 1.052185e+03 1620.1592 #> 14 1.359325e+02 339.57370 4.686951e+02 1170.8501 #> 21 6.055102e+01 257.45458 2.087799e+02 887.7034 #> 28 2.697241e+01 203.47173 9.300089e+01 701.5705 #> 42 5.352005e+00 140.10377 1.845371e+01 483.0778 #> 50 2.123945e+00 118.24602 7.323361e+00 407.7123 #> 100 6.585062e-03 59.30629 2.270529e-02 204.4881 #> #> $PEC_sw_max #> [1] 685.0566 #> #> $PEC_sed_max #> [1] 2362.075 #> # Metabolite new_dummy <- chent_focus_sw(\"New Dummy\", mw = 250, Koc = 100) M1 <- chent_focus_sw(\"M1\", mw = 100, cwsat = 100, DT50_ws = 100, Koc = 50, max_ws = 0, max_soil = 0.5) PEC_sw_focus(new_dummy, 1000, scenario = \"cereals, winter\", met = M1) #> $f_drift #> [1] 0.02759 #> #> $eq_rate_drift_s #> [1] 0 #> #> $eq_rate_rd_s #> [1] 200 #> #> $eq_rate_rd_parent_s #> [1] 0 #> #> $input_drift_s #> [1] 0 #> #> $input_rd_s #> [1] 20 #> #> $f_rd_sw #> [1] 0.9375 #> #> $f_rd_sed #> [1] 0.0625 #> #> $PEC #> type #> Time PECsw TWAECsw PECsed TWAECsed #> 0 62.50000 NA 31.25000 NA #> 1 62.06828 62.28414 31.03414 31.14207 #> 2 61.63954 62.06890 30.81977 31.03445 #> 4 60.79093 61.64158 30.39547 30.82079 #> 7 59.53987 61.00800 29.76994 30.50400 #> 14 56.71995 59.56326 28.35997 29.78163 #> 21 54.03358 58.16414 27.01679 29.08207 #> 28 51.47444 56.80902 25.73722 28.40451 #> 42 46.71404 54.22460 23.35702 27.11230 #> 50 44.19417 52.81945 22.09709 26.40973 #> 100 31.25000 45.08422 15.62500 22.54211 #> #> $PEC_sw_max #> [1] 62.5 #> #> $PEC_sed_max #> [1] 31.25 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","title":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","text":"method 'percentage' equivalent used CRD spreadsheet PEC calculator","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","text":"","code":"PEC_sw_sed( PEC_sw, percentage = 100, method = \"percentage\", sediment_depth = 5, water_depth = 30, sediment_density = 1.3, PEC_sed_units = c(\"µg/kg\", \"mg/kg\") )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","text":"PEC_sw Numeric vector matrix surface water concentrations µg/L corresponding sediment concentration estimated percentage percentage sediment, used percentage method method method used calculation sediment_depth Depth sediment layer water_depth Depth water body cm sediment_density density sediment L/kg (equivalent g/cm3) PEC_sed_units units estimated sediment PEC value","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","text":"predicted concentration sediment","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","text":"","code":"PEC_sw_sed(PEC_sw_drift(100, distances = 1), percentage = 50) #> 1 m #> 2.130769"},{"path":"https://pkgdown.jrwb.de/pfm/reference/SFO_actual_twa.html","id":null,"dir":"Reference","previous_headings":"","what":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","title":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","text":"Actual maximum moving window time average concentrations SFO kinetics","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SFO_actual_twa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","text":"","code":"SFO_actual_twa(DT50 = 1000, times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100))"},{"path":"https://pkgdown.jrwb.de/pfm/reference/SFO_actual_twa.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","text":"FOCUS (2014) Generic Guidance Estimating Persistence Degradation Kinetics Environmental Fate Studies Pesticides EU Registration, Version 1.1, 18 December 2014, p. 251","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SFO_actual_twa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","text":"DT50 half-life. times output times, window sizes time weighted average concentrations","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SFO_actual_twa.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SFO_actual_twa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","text":"","code":"SFO_actual_twa(10) #> actual twa #> 0 1.0000000000 NaN #> 1 0.9330329915 0.9661297 #> 2 0.8705505633 0.9337803 #> 4 0.7578582833 0.8733416 #> 7 0.6155722067 0.7923030 #> 14 0.3789291416 0.6400113 #> 21 0.2332582479 0.5267498 #> 28 0.1435872944 0.4412651 #> 42 0.0544094102 0.3248093 #> 50 0.0312500000 0.2795222 #> 100 0.0009765625 0.1441286"},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"implements method specified UK data requirements handbook checked spreadsheet published CRC website","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"","code":"SSLRC_mobility_classification(Koc)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"Koc sorption coefficient normalised organic carbon L/kg","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"list containing classification percentage compound transported per 10 mm drain water","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"HSE's Chemicals Regulation Division (CRD) Active substance PECsw calculations (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 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","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"","code":"SSLRC_mobility_classification(100) #> $`Mobility classification` #> [1] \"Moderately mobile\" #> #> $`Percentage drained per mm of drain water` #> [1] 0.7 #> SSLRC_mobility_classification(10000) #> $`Mobility classification` #> [1] \"Non mobile\" #> #> $`Percentage drained per mm of drain water` #> [1] 0.008 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":null,"dir":"Reference","previous_headings":"","what":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"R6 class holding TOXSWA water concentration (cwa) data associated statistics. like maximum moving window average concentrations, dataframes holding events exceeding specified thresholds. Usually, instance class generated read.TOXSWA_cwa.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"R6Class generator object.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"public-fields","dir":"Reference","previous_headings":"","what":"Public fields","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"filename Length one character vector holding filename. basedir Length one character vector holding directory file came . zipfile null, giving path zip file file read. segment Length one integer, specifying segment cwa data read. substance TOXSWA name substance. cwas Dataframe holding concentrations. events List dataframes holding event statistics threshold. windows Matrix maximum time weighted average concentrations (TWAC_max) areas curve µg/day * h (AUC_max_h) µg/day * d (AUC_max_d) requested moving window sizes days.","code":""},{"path":[]},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"public-methods","dir":"Reference","previous_headings":"","what":"Public methods","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"TOXSWA_cwa$new() TOXSWA_cwa$moving_windows() TOXSWA_cwa$get_events() TOXSWA_cwa$print() TOXSWA_cwa$clone()","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"method-new-","dir":"Reference","previous_headings":"","what":"Method new()","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"Create TOXSWA_cwa object file","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"usage","dir":"Reference","previous_headings":"","what":"Usage","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"","code":"TOXSWA_cwa$new( filename, basedir, zipfile = NULL, segment = \"last\", substance = \"parent\", total = FALSE )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"filename filename basedir directory look zipfile Optional path zipfile holding file segment Either \"last\" number segment read data substance TOXSWA substance name (TOXSWA 4 higher) total total concentrations read ? FALSE, free concentrations read","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"method-moving-windows-","dir":"Reference","previous_headings":"","what":"Method moving_windows()","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"Add `windows` field described .","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"usage-1","dir":"Reference","previous_headings":"","what":"Usage","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"","code":"TOXSWA_cwa$moving_windows(windows, total = FALSE)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"arguments-1","dir":"Reference","previous_headings":"","what":"Arguments","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"windows Window sizes days total TRUE, total concentration including amount adsorbed suspended matter used.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"method-get-events-","dir":"Reference","previous_headings":"","what":"Method get_events()","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"Populate datataframe event information specified threshold value. resulting dataframe stored `events` field object.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"usage-2","dir":"Reference","previous_headings":"","what":"Usage","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"","code":"TOXSWA_cwa$get_events(thresholds, total = FALSE)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"arguments-2","dir":"Reference","previous_headings":"","what":"Arguments","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"thresholds Threshold values µg/L. total TRUE, total concentration including amount adsorbed suspended matter used.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"method-print-","dir":"Reference","previous_headings":"","what":"Method print()","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"Print `TOXSWA_cwa` object","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"usage-3","dir":"Reference","previous_headings":"","what":"Usage","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"","code":"TOXSWA_cwa$print()"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"method-clone-","dir":"Reference","previous_headings":"","what":"Method clone()","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"objects class cloneable method.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"usage-4","dir":"Reference","previous_headings":"","what":"Usage","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"","code":"TOXSWA_cwa$clone(deep = FALSE)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"arguments-3","dir":"Reference","previous_headings":"","what":"Arguments","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"deep Whether make deep clone.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"","code":"H_sw_R1_stream <- read.TOXSWA_cwa(\"00003s_pa.cwa\", basedir = \"SwashProjects/project_H_sw/TOXSWA\", zipfile = system.file(\"testdata/SwashProjects.zip\", package = \"pfm\")) H_sw_R1_stream$get_events(c(2, 10)) H_sw_R1_stream$moving_windows(c(7, 21)) print(H_sw_R1_stream) #> <TOXSWA_cwa> data from file 00003s_pa.cwa segment 20 #> Error in head(self$cwas): could not find function \"head\""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TSCF.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimation of the transpiration stream concentration factor — TSCF","title":"Estimation of the transpiration stream concentration factor — TSCF","text":"FOCUS groundwater guidance (FOCUS 2014, p. 41) states reliable measured log Kow neutral pH must available order apply Briggs equation. clarified can regarded reliable, equation stated produced non-ionic compounds, suggesting compound ionogenic (weak acid/base) ionic.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TSCF.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimation of the transpiration stream concentration factor — TSCF","text":"","code":"TSCF(log_Kow, method = c(\"briggs82\", \"dettenmaier09\"))"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TSCF.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimation of the transpiration stream concentration factor — TSCF","text":"log_Kow decadic logarithm octanol-water partition constant method Short name estimation method.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TSCF.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimation of the transpiration stream concentration factor — TSCF","text":"Dettenmaier equation given show views subject exist.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TSCF.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Estimation of the transpiration stream concentration factor — TSCF","text":"FOCUS (2014) Generic Guidance Tier 1 FOCUS Ground Water Assessments. Version 2.2, May 2014 Dettenmaier EM, Doucette WJ Bugbee B (2009) Chemical hydrophobicity uptake plant roots. Environ. Sci. Technol 43, 324 - 329","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TSCF.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimation of the transpiration stream concentration factor — TSCF","text":"","code":"plot(TSCF, -1, 5, xlab = \"log Kow\", ylab = \"TSCF\", ylim = c(0, 1.1)) TSCF_2 <- function(x) TSCF(x, method = \"dettenmaier09\") curve(TSCF_2, -1, 5, add = TRUE, lty = 2) #> Error in curve(TSCF_2, -1, 5, add = TRUE, lty = 2): could not find function \"curve\" legend(\"topright\", lty = 1:2, bty = \"n\", legend = c(\"Briggs et al. (1982)\", \"Dettenmaier et al. (2009)\")) #> Error in legend(\"topright\", lty = 1:2, bty = \"n\", legend = c(\"Briggs et al. (1982)\", \"Dettenmaier et al. (2009)\")): could not find function \"legend\""},{"path":"https://pkgdown.jrwb.de/pfm/reference/chent_focus_sw.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","title":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","text":"Create chemical compound object FOCUS Step 1 calculations","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/chent_focus_sw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","text":"","code":"chent_focus_sw( name, Koc, DT50_ws = NA, DT50_soil = NA, DT50_water = NA, DT50_sediment = NA, cwsat = 1000, mw = NA, max_soil = 1, max_ws = 1 )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/chent_focus_sw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","text":"name Length one character vector containing name Koc Partition coefficient organic carbon water L/kg. DT50_ws Half-life water/sediment systems days DT50_soil Half-life soil days DT50_water Half-life water days (Step 2) DT50_sediment Half-life sediment days (Step 2) cwsat Water solubility mg/L mw Molar weight g/mol. max_soil Maximum observed fraction (dimensionless) soil max_ws Maximum observed fraction (dimensionless) water/sediment systems","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/chent_focus_sw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","text":"list substance specific properties","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":null,"dir":"Reference","previous_headings":"","what":"Deposition from spray drift expressed as percent of the applied dose as\npublished by the JKI — drift_data_JKI","title":"Deposition from spray drift expressed as percent of the applied dose as\npublished by the JKI — drift_data_JKI","text":"Deposition spray drift expressed percent applied dose published German Julius-Kühn Institute (JKI).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Deposition from spray drift expressed as percent of the applied dose as\npublished by the JKI — drift_data_JKI","text":"list currently containing matrices spray drift percentage data field crops (Ackerbau), Pome/stone fruit, early late (Obstbau frueh, spaet).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Deposition from spray drift expressed as percent of the applied dose as\npublished by the JKI — drift_data_JKI","text":"JKI (2010) Spreadsheet 'Tabelle der Abdrifteckwerte.xls', retrieved http://www.jki.bund.de/no_cache/de/startseite/institute/anwendungstechnik/abdrift-eckwerte.html 2015-06-11 Rautmann, D., Streloke, M Winkler, R (2001) New basic drift values authorization procedure plant protection products Mitt. Biol. Bundesanst. Land- Forstwirtsch. 383, 133-141","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Deposition from spray drift expressed as percent of the applied dose as\npublished by the JKI — drift_data_JKI","text":"data extracted spreadsheet cited using R code given example section. spreadsheet included package licence clear. Additional spray drift values taken publication Rautmann et al. (2001). Specifically, values early vines, values 3 m buffer incomplete spreadsheet. Note vegetables, ornamentals small fruit, values field crops used crops < 50 cm, vales late vines used crops > 50 cm. JKI spreadsheet, indicated values used spray applications handheld/knapsack equipment (tragbare Spritz- und Sprühgerate). Values non-professional use listed JKI spreadsheet included.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Deposition from spray drift expressed as percent of the applied dose as\npublished by the JKI — drift_data_JKI","text":"","code":"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 #> [[1]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 2.77 NA NA NA NA #> 3 0.95 29.20 15.73 2.70 8.02 #> 5 0.57 19.89 8.41 1.18 3.62 #> 10 0.29 11.81 3.60 0.39 1.23 #> 15 0.20 5.55 1.81 0.20 0.65 #> 20 0.15 2.77 1.09 0.13 0.42 #> 30 0.10 1.04 0.54 0.07 0.22 #> 40 0.07 0.52 0.32 0.04 0.14 #> 50 0.06 0.30 0.22 0.03 0.10 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 4.440 NA #> 3 19.33 NA 0.018721696 #> 5 11.57 0.180 0.014363896 #> 10 5.77 0.050 0.010026007 #> 15 3.84 0.020 0.008124366 #> 20 1.79 0.012 0.006998158 #> 30 0.56 0.005 0.005670811 #> 40 0.25 0.003 NA #> 50 0.13 0.002 0.004350831 #> #> [[2]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 2.38 NA NA NA NA #> 3 0.79 25.53 12.13 2.53 7.23 #> 5 0.47 16.87 6.81 1.09 3.22 #> 10 0.24 9.61 3.11 0.35 1.07 #> 15 0.16 5.61 1.58 0.18 0.56 #> 20 0.12 2.59 0.90 0.11 0.36 #> 30 0.08 0.87 0.40 0.06 0.19 #> 40 0.06 0.40 0.23 0.03 0.12 #> 50 0.05 0.22 0.15 0.02 0.08 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 3.780 NA #> 3 17.73 NA NA #> 5 9.60 0.160 NA #> 10 4.18 0.040 NA #> 15 2.57 0.020 NA #> 20 1.21 0.011 NA #> 30 0.38 0.005 NA #> 40 0.17 0.003 NA #> 50 0.09 0.002 NA #> #> [[3]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 2.01 NA NA NA NA #> 3 0.68 23.96 11.01 2.49 6.90 #> 5 0.41 15.79 6.04 1.04 3.07 #> 10 0.20 8.96 2.67 0.32 1.02 #> 15 0.14 4.24 1.39 0.16 0.54 #> 20 0.10 2.01 0.80 0.10 0.34 #> 30 0.07 0.70 0.36 0.05 0.18 #> 40 0.05 0.33 0.21 0.03 0.11 #> 50 0.04 0.19 0.13 0.02 0.08 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 3.420 NA #> 3 15.93 NA NA #> 5 8.57 0.150 NA #> 10 3.70 0.040 NA #> 15 2.26 0.020 NA #> 20 1.05 0.010 NA #> 30 0.34 0.004 NA #> 40 0.15 0.003 NA #> 50 0.08 0.002 NA #> #> [[4]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 1.85 NA NA NA NA #> 3 0.62 23.61 10.12 2.44 6.71 #> 5 0.38 15.42 5.60 1.02 2.99 #> 10 0.19 8.66 2.50 0.31 0.99 #> 15 0.13 4.01 1.28 0.16 0.52 #> 20 0.10 1.89 0.75 0.10 0.33 #> 30 0.06 0.66 0.35 0.05 0.17 #> 40 0.05 0.31 0.20 0.03 0.11 #> 50 0.04 0.17 0.13 0.02 0.08 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 2.290 NA #> 3 15.38 NA NA #> 5 8.26 0.120 NA #> 10 3.55 0.030 NA #> 15 2.17 0.020 NA #> 20 0.93 0.009 NA #> 30 0.31 0.004 NA #> 40 0.14 0.002 NA #> 50 0.08 0.002 NA #> #> [[5]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 1.75 NA NA NA NA #> 3 0.59 23.12 9.74 2.37 6.59 #> 5 0.36 15.06 5.41 1.00 2.93 #> 10 0.18 8.42 2.43 0.31 0.98 #> 15 0.12 3.83 1.24 0.15 0.51 #> 20 0.09 1.81 0.72 0.09 0.33 #> 30 0.06 0.63 0.34 0.05 0.17 #> 40 0.05 0.30 0.20 0.03 0.11 #> 50 0.04 0.17 0.13 0.02 0.08 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 2.120 NA #> 3 15.12 NA NA #> 5 7.99 0.110 NA #> 10 3.36 0.030 NA #> 15 2.03 0.010 NA #> 20 0.88 0.008 NA #> 30 0.29 0.004 NA #> 40 0.14 0.002 NA #> 50 0.07 0.002 NA #> #> [[6]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 1.64 NA NA NA NA #> 3 0.56 22.76 9.21 2.29 6.41 #> 5 0.34 14.64 5.18 0.97 2.85 #> 10 0.17 8.04 2.38 0.30 0.95 #> 15 0.11 3.71 1.20 0.15 0.50 #> 20 0.09 1.75 0.68 0.09 0.32 #> 30 0.06 0.61 0.31 0.05 0.17 #> 40 0.04 0.29 0.17 0.03 0.11 #> 50 0.03 0.16 0.11 0.02 0.07 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 1.980 NA #> 3 14.90 NA NA #> 5 7.79 0.100 NA #> 10 3.23 0.030 NA #> 15 1.93 0.010 NA #> 20 0.83 0.008 NA #> 30 0.28 0.004 NA #> 40 0.13 0.002 NA #> 50 0.07 0.001 NA #> #> [[7]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 1.61 NA NA NA NA #> 3 0.55 22.69 9.10 2.24 6.33 #> 5 0.33 14.45 5.11 0.94 2.81 #> 10 0.17 7.83 2.33 0.29 0.94 #> 15 0.11 3.62 1.20 0.15 0.49 #> 20 0.08 1.71 0.67 0.09 0.31 #> 30 0.06 0.60 0.30 0.05 0.16 #> 40 0.04 0.28 0.17 0.03 0.10 #> 50 0.03 0.16 0.11 0.02 0.07 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 1.930 NA #> 3 14.63 NA NA #> 5 7.60 0.100 NA #> 10 3.13 0.030 NA #> 15 1.86 0.010 NA #> 20 0.81 0.008 NA #> 30 0.26 0.004 NA #> 40 0.12 0.002 NA #> 50 0.06 0.001 NA #> #> [[8]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 1.52 NA NA NA NA #> 3 0.52 22.24 8.66 2.16 6.26 #> 5 0.31 14.09 4.92 0.91 2.78 #> 10 0.16 7.58 2.29 0.28 0.93 #> 15 0.11 3.48 1.14 0.14 0.49 #> 20 0.08 1.65 0.65 0.09 0.31 #> 30 0.05 0.57 0.29 0.04 0.16 #> 40 0.04 0.27 0.16 0.03 0.10 #> 50 0.03 0.15 0.11 0.02 0.07 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 1.640 NA #> 3 13.53 NA NA #> 5 7.15 0.090 NA #> 10 3.01 0.020 NA #> 15 1.82 0.010 NA #> 20 0.78 0.007 NA #> 30 0.25 0.003 NA #> 40 0.12 0.002 NA #> 50 0.06 0.001 NA #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/endpoint.html","id":null,"dir":"Reference","previous_headings":"","what":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","title":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","text":"R6 class objects class chent represent chemical entities can hold list information loaded chemical yaml file chyaml field. information extracted optionally aggregated function.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/endpoint.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","text":"","code":"endpoint( chent, medium = \"soil\", type = c(\"degradation\", \"sorption\"), lab_field = c(NA, \"laboratory\", \"field\"), redox = c(NA, \"aerobic\", \"anaerobic\"), value = c(\"DT50ref\", \"Kfoc\", \"N\"), aggregator = geomean, raw = FALSE, signif = 3 ) soil_DT50( chent, aggregator = geomean, signif = 3, lab_field = \"laboratory\", value = \"DT50ref\", redox = \"aerobic\", raw = FALSE ) soil_Kfoc(chent, aggregator = geomean, signif = 3, value = \"Kfoc\", raw = FALSE) soil_N(chent, aggregator = mean, signif = 3, raw = FALSE) soil_sorption( chent, values = c(\"Kfoc\", \"N\"), aggregators = c(Kfoc = geomean, Koc = geomean, N = mean), signif = c(Kfoc = 3, N = 3), raw = FALSE )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/endpoint.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","text":"chent chent object get information medium medium information sought type information type lab_field NA, want laboratory field endpoints redox NA, looking aerobic anaerobic data value name value want. list given usage section exclusive aggregator aggregator function. Can mean, geomean, identity, example. raw number(s) returned stored chent object (character value) retain original information precision? signif many significant digits want values values returned aggregators named vector aggregator functions used","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/endpoint.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","text":"result applying aggregator function values converted numeric vector, rounded given number significant digits, , raw = TRUE, values character value, retaining implicit information precision may present.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/endpoint.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","text":"functions soil_* functions extract soil specific endpoints. Freundlich exponent, capital letter N used order facilitate dealing data R. pesticide fate modelling, exponent often called 1/n.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/geomean.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the geometric mean — geomean","title":"Calculate the geometric mean — geomean","text":"Based posts thread Stackoverflow http://stackoverflow.com/questions/2602583/geometric-mean----built-function returns NA NA values present na.rm = FALSE (default). negative values present, gives error message. least one element vector 0, returns 0.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/geomean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the geometric mean — geomean","text":"","code":"geomean(x, na.rm = FALSE)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/geomean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the geometric mean — geomean","text":"x Vector numbers na.rm NA values omitted?","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/geomean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the geometric mean — geomean","text":"geometric mean","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/geomean.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate the geometric mean — geomean","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/geomean.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the geometric mean — geomean","text":"","code":"geomean(c(1, 3, 9)) #> [1] 3 geomean(c(1, 3, NA, 9)) #> [1] NA if (FALSE) geomean(c(1, -3, 9)) # returns an error"},{"path":"https://pkgdown.jrwb.de/pfm/reference/get_vertex.html","id":null,"dir":"Reference","previous_headings":"","what":"Fit a parabola through three points — get_vertex","title":"Fit a parabola through three points — get_vertex","text":"inspired answer stackoverflow https://stackoverflow.com//717791","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/get_vertex.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fit a parabola through three points — get_vertex","text":"","code":"get_vertex(x, y)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/get_vertex.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fit a parabola through three points — get_vertex","text":"x Three x coordinates y Three y coordinates","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/max_twa.html","id":null,"dir":"Reference","previous_headings":"","what":"The maximum time weighted average concentration for a moving window — max_twa","title":"The maximum time weighted average concentration for a moving window — max_twa","text":"generate time series using sawtooth, need make sure length time series allows finding maximum. therefore recommended check using plot.one_box using window size argument max_twa.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/max_twa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"The maximum time weighted average concentration for a moving window — max_twa","text":"","code":"max_twa(x, window = 21)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/max_twa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"The maximum time weighted average concentration for a moving window — max_twa","text":"x object type one_box window size moving window","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/max_twa.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"The maximum time weighted average concentration for a moving window — max_twa","text":"method working directly fitted mkinfit objects uses equations given PEC soil section FOCUS guidance restricted SFO, FOMC DFOP models parent compound","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/max_twa.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"The maximum time weighted average concentration for a moving window — max_twa","text":"FOCUS (2006) “Guidance Document Estimating Persistence Degradation Kinetics Environmental Fate Studies Pesticides EU Registration” Report FOCUS Work Group Degradation Kinetics, EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics","code":""},{"path":[]},{"path":"https://pkgdown.jrwb.de/pfm/reference/max_twa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"The maximum time weighted average concentration for a moving window — max_twa","text":"","code":"pred <- sawtooth(one_box(10), applications = data.frame(time = c(0, 7), amount = c(1, 1))) max_twa(pred) #> $max #> parent #> 0.9537545 #> #> $window_start #> parent #> 0 #> #> $window_end #> parent #> 21 #> pred_FOMC <- mkinfit(\"FOMC\", FOCUS_2006_C, quiet = TRUE) max_twa(pred_FOMC) #> 21 #> 18.22124"},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a time series of decline data — one_box","title":"Create a time series of decline data — one_box","text":"Create time series decline data","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a time series of decline data — one_box","text":"","code":"one_box(x, ini, ..., t_end = 100, res = 0.01) # S3 method for numeric one_box(x, ini = 1, ..., t_end = 100, res = 0.01) # S3 method for character one_box(x, ini = 1, parms, ..., t_end = 100, res = 0.01) # S3 method for mkinfit one_box(x, ini = \"model\", ..., t_end = 100, res = 0.01)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a time series of decline data — one_box","text":"x numeric, half-life used exponential decline. character string specifying parent decline model given e.g. FOMC, parms must contain corresponding parameters. x mkinfit object, decline calculated object. ini initial amount. x mkinfit object, ini 'model', fitted initial concentrations used. Otherwise, ini must numeric. length one, used parent initial values metabolites zero, otherwise, must give values observed variables. ... arguments passed methods t_end End time series res Resolution time series parms named numeric vector containing model parameters","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a time series of decline data — one_box","text":"object class one_box, inheriting ts.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a time series of decline data — one_box","text":"","code":"# Only use a half-life pred_0 <- one_box(10) plot(pred_0) # Use a fitted mkinfit model require(mkin) fit <- mkinfit(\"FOMC\", FOCUS_2006_C, quiet = TRUE) pred_1 <- one_box(fit) plot(pred_1) # Use a model with more than one observed variable m_2 <- mkinmod(parent = mkinsub(\"SFO\", \"m1\"), m1 = mkinsub(\"SFO\")) #> Temporary DLL for differentials generated and loaded fit_2 <- mkinfit(m_2, FOCUS_2006_D, quiet = TRUE) #> Warning: Observations with value of zero were removed from the data pred_2 <- one_box(fit_2, ini = \"model\") plot(pred_2)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_exposit.html","id":null,"dir":"Reference","previous_headings":"","what":"Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit","title":"Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit","text":"table loss percentages used Exposit 3 twelve different Koc classes","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_exposit.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit","text":"data frame percentage values dissolved fraction fraction bound eroding particles, Koc classes used row names Koc_lower_bound lower bound Koc class dissolved percentage applied substance transferred adjacent water body dissolved phase bound percentage applied substance transferred adjacent water body bound eroding particles","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_exposit.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit","text":"Excel 3.02 spreadsheet available https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_exposit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit","text":"","code":"print(perc_runoff_exposit) #> Koc_lower_bound dissolved bound #> 0-20 0 0.110 0.000 #> >20-50 20 0.151 0.000 #> >50-100 50 0.197 0.000 #> >100-200 100 0.248 0.001 #> >200-500 200 0.224 0.004 #> >500-1000 500 0.184 0.020 #> >1000-2000 1000 0.133 0.042 #> >2000-5000 2000 0.084 0.091 #> >5000-10000 5000 0.037 0.159 #> >10000-20000 10000 0.031 0.192 #> >20000-50000 20000 0.014 0.291 #> >50000 50000 0.001 0.451"},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_reduction_exposit.html","id":null,"dir":"Reference","previous_headings":"","what":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","title":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","text":"table runoff reduction percentages used Exposit 3 different vegetated buffer widths","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_reduction_exposit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","text":"","code":"perc_runoff_reduction_exposit"},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_reduction_exposit.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","text":"named list data frames reduction percentage values dissolved fraction fraction bound eroding particles, vegetated buffer widths row names. names list items Exposit versions values taken. dissolved reduction percentage dissolved phase bound reduction percentage particulate phase","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_reduction_exposit.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","text":"Excel 3.02 spreadsheet available https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html Agroscope version 3.01a additional runoff factors 3 m 6 m buffer zones received Muris Korkaric (published). variant 3.01a2 introduced consistency previous calculations performed Agroscope 3 m buffer zone.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_reduction_exposit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","text":"","code":"print(perc_runoff_reduction_exposit) #> $`3.02` #> dissolved bound #> No buffer 0 0 #> 5 m 40 40 #> 10 m 60 85 #> 20 m 80 95 #> #> $`3.01a` #> dissolved bound #> No buffer 0 0 #> 3 m 25 30 #> 5 m 40 40 #> 6 m 45 55 #> 10 m 60 85 #> 20 m 80 95 #> #> $`3.01a2` #> dissolved bound #> No buffer 0 0 #> 3 m 25 25 #> #> $`2.0` #> dissolved bound #> No buffer 0.0 0.0 #> 20 m 97.5 97.5 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/pfm_degradation.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","title":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","text":"Calculate time course relative concentrations based mkinmod model","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/pfm_degradation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","text":"","code":"pfm_degradation( model = \"SFO\", DT50 = 1000, parms = c(k_parent = log(2)/DT50), years = 1, step_days = 1, times = seq(0, years * 365, by = step_days) )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/pfm_degradation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","text":"model degradation model used. Either parent model like 'SFO' 'FOMC', mkinmod object DT50 half-life. used simple exponential decline calculated (SFO model). parms parameters used degradation model years many years degradation predicted? step_days step size days output ? times output times","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/pfm_degradation.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/pfm_degradation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","text":"","code":"head(pfm_degradation(\"SFO\", DT50 = 10)) #> Error in head(pfm_degradation(\"SFO\", DT50 = 10)): could not find function \"head\""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.TOXSWA_cwa.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","title":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","text":"Plot TOXSWA hourly concentrations chemical substance specific segment TOXSWA surface water body.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.TOXSWA_cwa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","text":"","code":"# S3 method for TOXSWA_cwa plot( x, time_column = c(\"datetime\", \"t\", \"t_firstjan\", \"t_rel_to_max\"), xlab = \"default\", ylab = \"default\", add = FALSE, threshold_factor = 1000, thin_low = 1, total = FALSE, LC_TIME = \"C\", ... )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.TOXSWA_cwa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","text":"x TOXSWA_cwa object plotted. time_column used time axis. \"t_firstjan\" chosen, time given days relative first January first year. xlab, ylab Labels x y axis. add add existing plot? threshold_factor factor data lower maximum order get thinned plotting (see next argument). thin_low integer greater 1, data close zero (smaller 1/threshold_factor maximum) series thinned factor order decrease amount data included plots total total concentration water plotted, including substance sorbed suspended matter? LC_TIME Specification locale used format dates ... arguments passed plot adding existing plot","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.TOXSWA_cwa.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.TOXSWA_cwa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","text":"","code":"H_sw_D4_pond <- read.TOXSWA_cwa(\"00001p_pa.cwa\", basedir = \"SwashProjects/project_H_sw/TOXSWA\", zipfile = system.file(\"testdata/SwashProjects.zip\", package = \"pfm\")) plot(H_sw_D4_pond) plot(H_sw_D4_pond, time_column = \"t\") plot(H_sw_D4_pond, time_column = \"t_firstjan\") plot(H_sw_D4_pond, time_column = \"t_rel_to_max\") H_sw_R1_stream <- read.TOXSWA_cwa(\"00003s_pa.cwa\", basedir = \"SwashProjects/project_H_sw/TOXSWA\", zipfile = system.file(\"testdata/SwashProjects.zip\", package = \"pfm\")) plot(H_sw_R1_stream, time_column = \"t_rel_to_max\")"},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.one_box.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot time series of decline data — plot.one_box","title":"Plot time series of decline data — plot.one_box","text":"Plot time series decline data","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.one_box.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot time series of decline data — plot.one_box","text":"","code":"# S3 method for one_box plot( x, xlim = range(time(x)), ylim = c(0, max(x)), xlab = \"Time\", ylab = \"Residue\", max_twa = NULL, max_twa_var = dimnames(x)[[2]][1], ... )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.one_box.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot time series of decline data — plot.one_box","text":"x object type one_box plotted xlim Limits x axis ylim Limits y axis xlab Label x axis ylab Label y axis max_twa numeric value given, maximum time weighted average concentration(s) /shown graph. max_twa_var Variable maximum time weighted average shown max_twa NULL. ... arguments passed methods","code":""},{"path":[]},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.one_box.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot time series of decline data — plot.one_box","text":"","code":"dfop_pred <- one_box(\"DFOP\", parms = c(k1 = 0.2, k2 = 0.02, g = 0.7)) plot(dfop_pred) plot(sawtooth(dfop_pred, 3, 7), max_twa = 21) # Use a fitted mkinfit model m_2 <- mkinmod(parent = mkinsub(\"SFO\", \"m1\"), m1 = mkinsub(\"SFO\")) #> Temporary DLL for differentials generated and loaded fit_2 <- mkinfit(m_2, FOCUS_2006_D, quiet = TRUE) #> Warning: Observations with value of zero were removed from the data pred_2 <- one_box(fit_2, ini = 1) pred_2_saw <- sawtooth(pred_2, 2, 7) plot(pred_2_saw, max_twa = 21, max_twa_var = \"m1\")"},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":null,"dir":"Reference","previous_headings":"","what":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"Read TOXSWA hourly concentrations chemical substance specific segment TOXSWA surface water body. Per default, data last segment imported. TOXSWA 4 reports values end hour (ConLiqWatLayCur) summary file, use value well instead hourly averages (ConLiqWatLay). TOXSWA 5.5.3 variable renamed ConLiqWatLay file.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"","code":"read.TOXSWA_cwa( filename, basedir = \".\", zipfile = NULL, segment = \"last\", substance = \"parent\", total = FALSE, windows = NULL, thresholds = NULL )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"filename filename cwa file (TOXSWA 2.x.y similar) file using FOCUS TOXSWA 4 (.e. TOXSWA 4.4.2) higher. basedir path directory cwa file resides. zipfile Optional path zip file containing cwa file. segment segment data read. Either \"last\", segment number. substance .files, default value \"parent\" leads reading concentrations parent compound. Alternatively, substance interested can selected code name. total Set TRUE order read total concentrations well. necessary .files generated TOXSWA 4.4.2 similar, .cwa files. .cwa files, total concentration always read well. windows Numeric vector width moving windows days, calculating maximum time weighted average concentrations areas curve. thresholds Numeric vector threshold concentrations µg/L generating event statistics.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"instance R6 object class TOXSWA_cwa.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"","code":"H_sw_D4_pond <- read.TOXSWA_cwa(\"00001p_pa.cwa\", basedir = \"SwashProjects/project_H_sw/TOXSWA\", zipfile = system.file(\"testdata/SwashProjects.zip\", package = \"pfm\"))"},{"path":"https://pkgdown.jrwb.de/pfm/reference/reexports.html","id":null,"dir":"Reference","previous_headings":"","what":"Objects exported from other packages — reexports","title":"Objects exported from other packages — reexports","text":"objects imported packages. Follow links see documentation. mkin set_nd_nq, set_nd_nq_focus","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/sawtooth.html","id":null,"dir":"Reference","previous_headings":"","what":"Create decline time series for multiple applications — sawtooth","title":"Create decline time series for multiple applications — sawtooth","text":"application pattern specified applications, n disregarded.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/sawtooth.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create decline time series for multiple applications — sawtooth","text":"","code":"sawtooth( x, n = 1, i = 365, applications = data.frame(time = seq(0, (n - 1) * i, length.out = n), amount = 1) )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/sawtooth.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create decline time series for multiple applications — sawtooth","text":"x one_box object n number applications. applications specified, n ignored interval applications. applications specified, ignored applications data frame holding application times first column corresponding amounts applied second column.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/sawtooth.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create decline time series for multiple applications — sawtooth","text":"","code":"applications = data.frame(time = seq(0, 14, by = 7), amount = c(1, 2, 3)) pred <- one_box(10) plot(sawtooth(pred, applications = applications)) m_2 <- mkinmod(parent = mkinsub(\"SFO\", \"m1\"), m1 = mkinsub(\"SFO\")) #> Temporary DLL for differentials generated and loaded fit_2 <- mkinfit(m_2, FOCUS_2006_D, quiet = TRUE) #> Warning: Observations with value of zero were removed from the data pred_2 <- one_box(fit_2, ini = 1) pred_2_saw <- sawtooth(pred_2, 2, 7) plot(pred_2_saw, max_twa = 21, max_twa_var = \"m1\") max_twa(pred_2_saw) #> $max #> parent m1 #> 0.7834481 0.8617049 #> #> $window_start #> parent m1 #> 0.00 26.85 #> #> $window_end #> parent m1 #> 21.00 47.85 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2015.html","id":null,"dir":"Reference","previous_headings":"","what":"Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015","title":"Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015","text":"Properties predefined scenarios used Tier 1, Tier 2A Tier 3A concentration soil given EFSA guidance (2015, p. 13/14). Also, scenario model adjustment factors p. 15 p. 17 included.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2015.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015","text":"data frame one row scenario. Row names scenario codes, e.g. CTN Northern scenario total concentration soil. Columns mostly self-explanatory. rho dry bulk density top soil.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2015.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015","text":"EFSA (European Food Safety Authority) (2015) EFSA guidance document predicting environmental concentrations active substances plant protection products transformation products active substances soil. EFSA Journal 13(4) 4093 doi:10.2903/j.efsa.2015.4093","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2015.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015","text":"","code":"if (FALSE) { # This is the code that was used to define the data soil_scenario_data_EFSA_2015 <- data.frame( Zone = rep(c(\"North\", \"Central\", \"South\"), 2), Country = c(\"Estonia\", \"Germany\", \"France\", \"Denmark\", \"Czech Republik\", \"Spain\"), T_arit = c(4.7, 8.0, 11.0, 8.2, 9.1, 12.8), T_arr = c(7.0, 10.1, 12.3, 9.8, 11.2, 14.7), Texture = c(\"Coarse\", \"Coarse\", \"Medium fine\", \"Medium\", \"Medium\", \"Medium\"), f_om = c(0.118, 0.086, 0.048, 0.023, 0.018, 0.011), theta_fc = c(0.244, 0.244, 0.385, 0.347, 0.347, 0.347), rho = c(0.95, 1.05, 1.22, 1.39, 1.43, 1.51), f_sce = c(3, 2, 2, 2, 1.5, 1.5), f_mod = c(2, 2, 2, 4, 4, 4), stringsAsFactors = FALSE, row.names = c(\"CTN\", \"CTC\", \"CTS\", \"CLN\", \"CLC\", \"CLS\") ) save(soil_scenario_data_EFSA_2015, file = '../data/soil_scenario_data_EFSA_2015.RData') } # And this is the resulting dataframe soil_scenario_data_EFSA_2015 #> Zone Country T_arit T_arr Texture f_om theta_fc rho f_sce #> CTN North Estonia 4.7 7.0 Coarse 0.118 0.244 0.95 3.0 #> CTC Central Germany 8.0 10.1 Coarse 0.086 0.244 1.05 2.0 #> CTS South France 11.0 12.3 Medium fine 0.048 0.385 1.22 2.0 #> CLN North Denmark 8.2 9.8 Medium 0.023 0.347 1.39 2.0 #> CLC Central Czech Republik 9.1 11.2 Medium 0.018 0.347 1.43 1.5 #> CLS South Spain 12.8 14.7 Medium 0.011 0.347 1.51 1.5 #> f_mod #> CTN 2 #> CTC 2 #> CTS 2 #> CLN 4 #> CLC 4 #> CLS 4"},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2017.html","id":null,"dir":"Reference","previous_headings":"","what":"Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017","title":"Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017","text":"Properties predefined scenarios used Tier 1, Tier 2A Tier 3A concentration soil given EFSA guidance (2017, p. 14/15). Also, scenario model adjustment factors p. 16 p. 18 included.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2017.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017","text":"data frame one row scenario. Row names scenario codes, e.g. CTN Northern scenario total concentration soil. Columns mostly self-explanatory. rho dry bulk density top soil.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2017.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017","text":"EFSA (European Food Safety Authority) (2017) EFSA guidance document predicting environmental concentrations active substances plant protection products transformation products active substances soil. EFSA Journal 15(10) 4982 doi:10.2903/j.efsa.2017.4982","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2017.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017","text":"","code":"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"},{"path":"https://pkgdown.jrwb.de/pfm/reference/twa.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate a time weighted average concentration — twa","title":"Calculate a time weighted average concentration — twa","text":"moving average built using values past, earliest possible time maximum time series returned one window passed.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/twa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate a time weighted average concentration — twa","text":"","code":"twa(x, window = 21) # S3 method for one_box twa(x, window = 21)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/twa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate a time weighted average concentration — twa","text":"x object type one_box window size moving window","code":""},{"path":[]},{"path":"https://pkgdown.jrwb.de/pfm/reference/twa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate a time weighted average concentration — twa","text":"","code":"pred <- sawtooth(one_box(10), applications = data.frame(time = c(0, 7), amount = c(1, 1))) max_twa(pred) #> $max #> parent #> 0.9537545 #> #> $window_start #> parent #> 0 #> #> $window_end #> parent #> 21 #>"}] +[{"path":"https://pkgdown.jrwb.de/pfm/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Johannes Ranke. Author, maintainer.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Johannes Ranke (2023). pfm: Utilities Pesticide Fate Modelling. R package version 0.6.0, https://github.com/jranke/pfm, https://pkgdown.jrwb.de/pfm.","code":"@Manual{, title = {pfm: Utilities for Pesticide Fate Modelling}, author = {{Johannes Ranke}}, year = {2023}, note = {R package version 0.6.0, https://github.com/jranke/pfm}, url = {https://pkgdown.jrwb.de/pfm}, }"},{"path":"https://pkgdown.jrwb.de/pfm/index.html","id":"pfm","dir":"","previous_headings":"","what":"Utilities for Pesticide Fate Modelling","title":"Utilities for Pesticide Fate Modelling","text":"R package pfm provides utilities fate modelling, including dealing FOCUS pesticide fate modelling tools, (currently TOXSWA cwa files), made available GNU public license.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Utilities for Pesticide Fate Modelling","text":"easiest way install package probably use drat: Alternatively can install package using devtools package. Using quick = TRUE skips docs, multiple-architecture builds, demos, vignettes.","code":"install.packages(\"drat\") drat::addRepo(\"jranke\") install.packages(\"pfm\") library(devtools) install_github(\"jranke/pfm\", quick = TRUE)"},{"path":"https://pkgdown.jrwb.de/pfm/index.html","id":"use","dir":"","previous_headings":"","what":"Use","title":"Utilities for Pesticide Fate Modelling","text":"Please refer reference.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/index.html","id":"examples","dir":"","previous_headings":"","what":"Examples","title":"Utilities for Pesticide Fate Modelling","text":"One recent nice example usage package visualisation time weighted average sawtooth curve obtained several overlays mkinfit predictions shown .","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_GW_interception_2014.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014","title":"Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014","text":"Subset EFSA crop interception default values groundwater modelling","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_GW_interception_2014.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014","text":"matrix containing interception values, currently selected crops","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_GW_interception_2014.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014","text":"European Food Safety Authority (2014) EFSA Guidance Document evaluating laboratory field dissipation studies obtain DegT50 values active substances plant protection products transformation products active substances soil. EFSA Journal 12(5):3662, 37 pp., doi:10.2903/j.efsa.2014.3662","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_GW_interception_2014.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Subset of EFSA crop interception default values for groundwater modelling — EFSA_GW_interception_2014","text":"","code":"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 #> 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 #> Peas 0 0.35 0.55 0.55 0.85 0.85 0.85 0.85 0.85 0.85 #> Summer oilseed rape 0 0.40 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.90 #> Winter oilseed rape 0 0.40 0.80 0.80 0.80 0.80 0.80 0.80 0.80 0.90 #> Tomatoes 0 0.50 0.70 0.70 0.80 0.80 0.80 0.80 0.80 0.50 #> Spring cereals 0 0.00 0.20 0.80 0.90 0.90 0.90 0.80 0.80 0.80 #> Winter cereals 0 0.00 0.20 0.80 0.90 0.90 0.90 0.80 0.80 0.80"},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_washoff_2017.html","id":null,"dir":"Reference","previous_headings":"","what":"Subset of EFSA crop washoff default values — EFSA_washoff_2017","title":"Subset of EFSA crop washoff default values — EFSA_washoff_2017","text":"Subset EFSA crop washoff default values","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_washoff_2017.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Subset of EFSA crop washoff default values — EFSA_washoff_2017","text":"matrix containing wash-factors, currently selected crops","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_washoff_2017.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Subset of EFSA crop washoff default values — EFSA_washoff_2017","text":"European Food Safety Authority (2017) EFSA guidance document predicting environmental concentrations active substances plant protection products transformation products active substances soil. EFSA Journal 15(10) 4982 doi:10.2903/j.efsa.2017.4982","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/EFSA_washoff_2017.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Subset of EFSA crop washoff default values — EFSA_washoff_2017","text":"","code":"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 #> 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 #> Peas NA 0.40 0.60 0.60 0.65 0.65 0.65 0.65 0.65 0.35 #> Summer oilseed rape NA 0.40 0.50 0.50 0.60 0.60 0.60 0.60 0.60 0.50 #> Winter oilseed rape NA 0.10 0.40 0.40 0.55 0.55 0.55 0.55 0.55 0.30 #> Tomatoes NA 0.55 0.75 0.75 0.70 0.70 0.70 0.70 0.70 0.35 #> Spring cereals NA 0.40 0.50 0.50 0.65 0.65 0.65 0.65 0.65 0.55 #> Winter cereals NA 0.10 0.40 0.60 0.55 0.55 0.55 0.60 0.60 0.40"},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_GW_scenarios_2012.html","id":null,"dir":"Reference","previous_headings":"","what":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","title":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","text":"Currently, scenario names acronyms small subset soil definitions provided. soil definitions page 46ff. FOCUS (2012).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_GW_scenarios_2012.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","text":"","code":"FOCUS_GW_scenarios_2012"},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_GW_scenarios_2012.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","text":"object class list length 2.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_GW_scenarios_2012.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","text":"FOCUS (2012) Generic guidance Tier 1 FOCUS ground water assessments. Version 2.1. FOrum Co-ordination pesticde fate models USe. http://focus.jrc.ec.europa.eu/gw/docs/Generic_guidance_FOCV2_1.pdf","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_GW_scenarios_2012.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"A very small subset of the FOCUS Groundwater scenario definitions — FOCUS_GW_scenarios_2012","text":"","code":"FOCUS_GW_scenarios_2012 #> $names #> Cha Ham Jok Kre Oke #> \"Châteaudun\" \"Hamburg\" \"Jokioinen\" \"Kremsmünster\" \"Okehampton\" #> Pia Por Sev Thi #> \"Piacenza\" \"Porto\" \"Sevilla\" \"Thiva\" #> #> $soils #> location horizon number pH_H2O perc_clay perc_oc rel_deg #> 1 Cha Ap 1 8.0 30.0 1.39 1.0 #> 2 Cha B1 2 8.1 31.0 0.93 0.5 #> 3 Cha B2 3 8.2 25.0 0.70 0.5 #> 4 Cha II C1 4 8.5 26.0 0.30 0.3 #> 5 Cha II C1 5 8.5 26.0 0.30 0.0 #> 6 Cha II C2 6 8.5 24.0 0.27 0.0 #> 7 Cha M 7 8.3 31.0 0.21 0.0 #> 8 Ham Ap 1 6.4 7.2 1.50 1.0 #> 9 Ham BvI 2 5.6 6.7 1.00 0.5 #> 10 Ham BvII 3 5.6 0.9 0.20 0.3 #> 11 Ham Bv/Cv 4 5.7 0.0 0.00 0.3 #> 12 Ham Cv 5 5.5 0.0 0.00 0.3 #> 13 Ham Cv 6 5.5 0.0 0.00 0.0 #> 14 Jok Ap 1 6.2 3.6 4.06 1.0 #> 15 Jok Bs 2 5.6 1.8 0.84 0.5 #> 16 Jok BC1 3 5.4 1.2 0.36 0.3 #> 17 Jok BC2 4 5.4 1.7 0.29 0.3 #> 18 Jok BC2 5 5.4 1.7 0.29 0.0 #> 19 Jok Cg 6 5.3 1.9 0.21 0.0 #> 20 Kre <NA> 1 7.7 14.0 3.60 1.0 #> 21 Kre <NA> 2 7.0 25.0 1.00 0.5 #> 22 Kre <NA> 3 7.1 27.0 0.50 0.5 #> 23 Kre <NA> 4 7.1 27.0 0.50 0.3 #> 24 Kre <NA> 5 7.1 27.0 0.50 0.0 #> 25 Oke A 1 5.8 18.0 2.20 1.0 #> 26 Oke Bw1 2 6.3 17.0 0.70 0.5 #> 27 Oke BC 3 6.5 14.0 0.40 0.3 #> 28 Oke C 4 6.6 9.0 0.10 0.3 #> 29 Oke C 5 6.6 9.0 0.10 0.0 #> 30 Pia Ap 1 7.0 15.0 1.26 1.0 #> 31 Pia Ap 2 7.0 15.0 1.26 0.5 #> 32 Pia Bw 3 6.3 7.0 0.47 0.5 #> 33 Pia Bw 4 6.3 7.0 0.47 0.3 #> 34 Pia 2C 5 6.4 0.0 0.00 0.3 #> 35 Pia 2C 6 6.4 0.0 0.00 0.0 #> 36 Por <NA> 1 4.9 10.0 1.42 1.0 #> 37 Por <NA> 2 4.8 8.0 0.78 0.5 #> 38 Por <NA> 3 4.8 8.0 0.78 0.3 #> 39 Por <NA> 4 4.8 8.0 0.78 0.0 #> 40 Sev <NA> 1 7.3 14.0 0.93 1.0 #> 41 Sev <NA> 2 7.3 13.0 0.93 1.0 #> 42 Sev <NA> 3 7.8 15.0 0.70 0.5 #> 43 Sev <NA> 4 8.1 16.0 0.58 0.3 #> 44 Sev <NA> 5 8.1 16.0 0.58 0.0 #> 45 Sev <NA> 6 8.2 22.0 0.49 0.0 #> 46 Thi Ap1 1 7.7 25.3 0.74 1.0 #> 47 Thi Ap2 2 7.7 25.3 0.74 0.5 #> 48 Thi Bw 3 7.8 29.6 0.57 0.5 #> 49 Thi Bw 4 7.8 31.9 0.31 0.3 #> 50 Thi Ck1 5 7.8 32.9 0.18 0.3 #> 51 Thi Ck1 6 7.8 32.9 0.18 0.0 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_Step_12_scenarios.html","id":null,"dir":"Reference","previous_headings":"","what":"Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios","title":"Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios","text":"data extracted scenario.txt file using R code shown . text file included package licence clear.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_Step_12_scenarios.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios","text":"list containing scenario names character vector called 'names', drift percentiles matrix called 'drift', interception percentages matrix called 'interception' runoff/drainage percentages Step 2 calculations matrix called 'rd'.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOCUS_Step_12_scenarios.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator — FOCUS_Step_12_scenarios","text":"","code":"if (FALSE) { # This is the code that was used to extract the data scenario_path <- \"inst/extdata/FOCUS_Step_12_scenarios.txt\" scenarios <- readLines(scenario_path)[9:38] FOCUS_Step_12_scenarios <- list() sce <- read.table(text = scenarios, sep = \"\\t\", header = TRUE, check.names = FALSE, stringsAsFactors = FALSE) FOCUS_Step_12_scenarios$names = sce$Crop rownames(sce) <- sce$Crop FOCUS_Step_12_scenarios$drift = sce[, 3:11] FOCUS_Step_12_scenarios$interception = sce[, 12:15] sce_2 <- readLines(scenario_path)[41:46] rd <- read.table(text = sce_2, sep = \"\\t\")[1:2] rd_mat <- matrix(rd$V2, nrow = 3, byrow = FALSE) dimnames(rd_mat) = list(Time = c(\"Oct-Feb\", \"Mar-May\", \"Jun-Sep\"), Region = c(\"North\", \"South\")) FOCUS_Step_12_scenarios$rd = rd_mat save(FOCUS_Step_12_scenarios, file = \"data/FOCUS_Step_12_scenarios.RData\") } # And this is the resulting data FOCUS_Step_12_scenarios #> $names #> [1] \"cereals, spring\" \"cereals, winter\" #> [3] \"citrus\" \"cotton\" #> [5] \"field beans\" \"grass / alfalfa\" #> [7] \"hops\" \"legumes\" #> [9] \"maize\" \"oil seed rape, spring\" #> [11] \"oil seed rape, winter\" \"olives\" #> [13] \"pome / stone fruit, early applns\" \"pome / stone fruit, late applns\" #> [15] \"potatoes\" \"soybeans\" #> [17] \"sugar beets\" \"sunflowers\" #> [19] \"tobacco\" \"vegetables, bulb\" #> [21] \"vegetables, fruiting\" \"vegetables, leafy\" #> [23] \"vegetables, root\" \"vines, early applns\" #> [25] \"vines, late applns\" \"appln, aerial\" #> [27] \"appln, hand (crop < 50 cm)\" \"appln, hand (crop > 50 cm)\" #> [29] \"no drift (incorp or seed trtmt)\" #> #> $drift #> 1 2 3 4 5 6 #> cereals, spring 2.759 2.438 2.024 1.862 1.794 1.631 #> cereals, winter 2.759 2.438 2.024 1.862 1.794 1.631 #> citrus 15.725 12.129 11.011 10.124 9.743 9.204 #> cotton 2.759 2.438 2.024 1.862 1.794 1.631 #> field beans 2.759 2.438 2.024 1.862 1.794 1.631 #> grass / alfalfa 2.759 2.438 2.024 1.862 1.794 1.631 #> hops 19.326 17.723 15.928 15.378 15.114 14.902 #> legumes 2.759 2.438 2.024 1.862 1.794 1.631 #> maize 2.759 2.438 2.024 1.862 1.794 1.631 #> oil seed rape, spring 2.759 2.438 2.024 1.862 1.794 1.631 #> oil seed rape, winter 2.759 2.438 2.024 1.862 1.794 1.631 #> olives 15.725 12.129 11.011 10.124 9.743 9.204 #> pome / stone fruit, early applns 29.197 25.531 23.960 23.603 23.116 22.760 #> pome / stone fruit, late applns 15.725 12.129 11.011 10.124 9.743 9.204 #> potatoes 2.759 2.438 2.024 1.862 1.794 1.631 #> soybeans 2.759 2.438 2.024 1.862 1.794 1.631 #> sugar beets 2.759 2.438 2.024 1.862 1.794 1.631 #> sunflowers 2.759 2.438 2.024 1.862 1.794 1.631 #> tobacco 2.759 2.438 2.024 1.862 1.794 1.631 #> vegetables, bulb 2.759 2.438 2.024 1.862 1.794 1.631 #> vegetables, fruiting 2.759 2.438 2.024 1.862 1.794 1.631 #> vegetables, leafy 2.759 2.438 2.024 1.862 1.794 1.631 #> vegetables, root 2.759 2.438 2.024 1.862 1.794 1.631 #> vines, early applns 2.699 2.496 2.546 2.499 2.398 2.336 #> vines, late applns 8.028 7.119 6.898 6.631 6.636 6.431 #> appln, aerial 33.200 33.200 33.200 33.200 33.200 33.200 #> appln, hand (crop < 50 cm) 2.759 2.438 2.024 1.862 1.794 1.631 #> appln, hand (crop > 50 cm) 8.028 7.119 6.898 6.631 6.636 6.431 #> no drift (incorp or seed trtmt) 0.000 0.000 0.000 0.000 0.000 0.000 #> 7 8 >8 #> cereals, spring 1.578 1.512 1.512 #> cereals, winter 1.578 1.512 1.512 #> citrus 9.102 8.656 8.656 #> cotton 1.578 1.512 1.512 #> field beans 1.578 1.512 1.512 #> grass / alfalfa 1.578 1.512 1.512 #> hops 14.628 13.520 13.520 #> legumes 1.578 1.512 1.512 #> maize 1.578 1.512 1.512 #> oil seed rape, spring 1.578 1.512 1.512 #> oil seed rape, winter 1.578 1.512 1.512 #> olives 9.102 8.656 8.656 #> pome / stone fruit, early applns 22.690 22.241 22.241 #> pome / stone fruit, late applns 9.102 8.656 8.656 #> potatoes 1.578 1.512 1.512 #> soybeans 1.578 1.512 1.512 #> sugar beets 1.578 1.512 1.512 #> sunflowers 1.578 1.512 1.512 #> tobacco 1.578 1.512 1.512 #> vegetables, bulb 1.578 1.512 1.512 #> vegetables, fruiting 1.578 1.512 1.512 #> vegetables, leafy 1.578 1.512 1.512 #> vegetables, root 1.578 1.512 1.512 #> vines, early applns 2.283 2.265 2.265 #> vines, late applns 6.227 6.173 6.173 #> appln, aerial 33.200 33.200 33.200 #> appln, hand (crop < 50 cm) 1.578 1.512 1.512 #> appln, hand (crop > 50 cm) 6.227 6.173 6.173 #> no drift (incorp or seed trtmt) 0.000 0.000 0.000 #> #> $interception #> no interception minimal crop cover #> cereals, spring 0 0.00 #> cereals, winter 0 0.00 #> citrus 0 0.80 #> cotton 0 0.30 #> field beans 0 0.25 #> grass / alfalfa 0 0.40 #> hops 0 0.20 #> legumes 0 0.25 #> maize 0 0.25 #> oil seed rape, spring 0 0.40 #> oil seed rape, winter 0 0.40 #> olives 0 0.70 #> pome / stone fruit, early applns 0 0.20 #> pome / stone fruit, late applns 0 0.20 #> potatoes 0 0.15 #> soybeans 0 0.20 #> sugar beets 0 0.20 #> sunflowers 0 0.20 #> tobacco 0 0.20 #> vegetables, bulb 0 0.10 #> vegetables, fruiting 0 0.25 #> vegetables, leafy 0 0.25 #> vegetables, root 0 0.25 #> vines, early applns 0 0.40 #> vines, late applns 0 0.40 #> appln, aerial 0 0.20 #> appln, hand (crop < 50 cm) 0 0.20 #> appln, hand (crop > 50 cm) 0 0.20 #> no drift (incorp or seed trtmt) 0 0.00 #> average crop cover full canopy #> cereals, spring 0.20 0.70 #> cereals, winter 0.20 0.70 #> citrus 0.80 0.80 #> cotton 0.60 0.75 #> field beans 0.40 0.70 #> grass / alfalfa 0.60 0.75 #> hops 0.50 0.70 #> legumes 0.50 0.70 #> maize 0.50 0.75 #> oil seed rape, spring 0.70 0.75 #> oil seed rape, winter 0.70 0.75 #> olives 0.70 0.70 #> pome / stone fruit, early applns 0.40 0.65 #> pome / stone fruit, late applns 0.40 0.65 #> potatoes 0.50 0.70 #> soybeans 0.50 0.75 #> sugar beets 0.70 0.75 #> sunflowers 0.50 0.75 #> tobacco 0.70 0.75 #> vegetables, bulb 0.25 0.40 #> vegetables, fruiting 0.50 0.70 #> vegetables, leafy 0.40 0.70 #> vegetables, root 0.50 0.70 #> vines, early applns 0.50 0.60 #> vines, late applns 0.50 0.60 #> appln, aerial 0.50 0.70 #> appln, hand (crop < 50 cm) 0.50 0.70 #> appln, hand (crop > 50 cm) 0.50 0.70 #> no drift (incorp or seed trtmt) 0.00 0.00 #> #> $rd #> Region #> Time North South #> Oct-Feb 5 4 #> Mar-May 2 4 #> Jun-Sep 2 3 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":null,"dir":"Reference","previous_headings":"","what":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"Actual maximum moving window time average concentrations FOMC kinetics","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"","code":"FOMC_actual_twa( alpha = 1.0001, beta = 10, times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100) )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"FOCUS (2014) Generic Guidance Estimating Persistence Degradation Kinetics Environmental Fate Studies Pesticides EU Registration, Version 1.1, 18 December 2014, p. 251","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"alpha Parameter FOMC model beta Parameter FOMC model times output times, window sizes time weighted average concentrations","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/FOMC_actual_twa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Actual and maximum moving window time average concentrations for FOMC kinetics — FOMC_actual_twa","text":"","code":"FOMC_actual_twa(alpha = 1.0001, beta = 10) #> actual twa #> 0 1.00000000 NaN #> 1 0.90908224 0.9530973 #> 2 0.83331814 0.9115995 #> 4 0.71426168 0.8411664 #> 7 0.58820408 0.7580202 #> 14 0.41663019 0.6253074 #> 21 0.32254415 0.5387324 #> 28 0.26312277 0.4767543 #> 42 0.19227599 0.3925054 #> 50 0.16663681 0.3583198 #> 100 0.09088729 0.2397608"},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":null,"dir":"Reference","previous_headings":"","what":"Groundwater ubiquity score based on Gustafson (1989) — GUS","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"groundwater ubiquity score GUS calculated according following equation $$GUS = \\log_{10} DT50_{soil} (4 - \\log_{10} K_{oc})$$","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"","code":"GUS(...) # S3 method for numeric GUS(DT50, Koc, ...) # S3 method for chent GUS( chent, degradation_value = \"DT50ref\", lab_field = \"laboratory\", redox = \"aerobic\", sorption_value = \"Kfoc\", degradation_aggregator = geomean, sorption_aggregator = geomean, ... ) # S3 method for GUS_result print(x, ..., digits = 1)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"... Included generic allow arguments later. Therefore also added specific methods. DT50 Half-life chemical soil. field half-life according Gustafson (1989). However, leaching sub-soil can completely excluded field dissipation experiments Gustafson refer normalisation procedure, says field study conducted use conditions. Koc sorption constant normalised organic carbon. Gustafson mention nonlinearity sorption constant commonly found usually described Freundlich sorption, therefore unclear reference concentration Koc observed (reference concentration soil porewater). chent chent given appropriate information present chyaml field, information used, defaults specified . degradation_value available degradation values used? lab_field laboratory field half-lives used? defaults lab implementation, order avoid double-accounting mobility. comparability original GUS values given Gustafson (1989) desired, non-normalised first-order field half-lives obtained actual use conditions used. redox Aerobic anaerobic degradation data sorption_value available sorption values used? Defaults Kfoc generally available European pesticide peer review process. values generally use reference concentration 1 mg/L porewater, means expected Koc values concentration 1 mg/L water phase. degradation_aggregator Function aggregating half-lives sorption_aggregator Function aggregation Koc values x object class GUS_result printed digits number digits used print method","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"list DT50 Koc used well resulting score class GUS_result","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"Gustafson, David . (1989) Groundwater ubiquity score: simple method assessing pesticide leachability. Environmental toxicology chemistry 8(4) 339–57.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/GUS.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Groundwater ubiquity score based on Gustafson (1989) — GUS","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_FOMC_accu_rel.html","id":null,"dir":"Reference","previous_headings":"","what":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","title":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","text":"Get relative accumulation FOMC model multiples interval","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_FOMC_accu_rel.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","text":"","code":"PEC_FOMC_accu_rel(n, interval, FOMC)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_FOMC_accu_rel.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","text":"n number applications interval Time applications FOMC Named numeric vector containing FOMC parameters alpha beta","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_FOMC_accu_rel.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Get the relative accumulation of an FOMC model over multiples of an interval — PEC_FOMC_accu_rel","text":"numeric vector containing n accumulation factors n applications","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate predicted environmental concentrations in soil — PEC_soil","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"basic calculation contaminant concentration bulk soil based complete, instantaneous mixing. interval given, attempt made calculating long term maximum concentration using concepts layed PPR panel opinion (EFSA PPR panel 2012 EFSA guidance PEC soil calculations (EFSA, 2015, 2017).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"","code":"PEC_soil( rate, rate_units = \"g/ha\", interception = 0, mixing_depth = 5, PEC_units = \"mg/kg\", PEC_pw_units = \"mg/L\", interval = NA, n_periods = Inf, tillage_depth = 20, leaching_depth = tillage_depth, crop = \"annual\", cultivation = FALSE, chent = NA, DT50 = NA, FOMC = NA, Koc = NA, Kom = Koc/1.724, t_avg = 0, t_act = NULL, scenarios = c(\"default\", \"EFSA_2017\", \"EFSA_2015\"), leaching = scenarios == \"EFSA_2017\", porewater = FALSE )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"rate Application rate units specified rate_units Defaults g/ha interception fraction application rate reach soil mixing_depth Mixing depth cm PEC_units Requested units calculated PEC. mg/kg currently supported PEC_pw_units mg/L currently supported interval Period deeper mixing. default NA, .e. deeper mixing. annual deeper mixing, set 365 degradation units days n_periods Number periods considered long term PEC calculations tillage_depth Periodic (see interval) deeper mixing cm leaching_depth EFSA (2017) uses mixing depth (ecotoxicological evaluation depth) calculate leaching annual crops tillage takes place. default, losses layer tillage depth taken account implementation. crop Ignored scenarios EFSA_2017. annual crops supported scenarios used. crops single cropping cycle per year currently supported. cultivation mechanical cultivation sense EFSA (2017) take place, .e. twice year depth 5 cm? Ignored scenarios EFSA_2017 chent optional chent object holding substance specific information. Can also name substance character string DT50 specified, overrides soil DT50 endpoints chent object DT50 specified available chent object, zero degradation assumed FOMC specified, named numeric vector containing FOMC parameters alpha beta. overrides degradation endpoints, degradation interval maximum PEC calculated using parameters without temperature correction Koc specified, overrides Koc endpoints chent object Kom Calculated Koc default, can explicitly specified Kom t_avg Averaging times time weighted average concentrations t_act Time series actual concentrations scenarios 'default', DT50 used without correction soil properties specified REACH guidance (R.16, Table R.16-9) used porewater PEC calculations. \"EFSA_2015\", DT50 taken modelling half-life 20°C pF2 ('chent' specified, DegT50 destination 'PECgw' used), corrected using Arrhenius activation energy 65.4 kJ/mol. Also model scenario adjustment factors EFSA guidance used. leaching leaching taken account? default FALSE, except EFSA_2017 scenarios used. porewater equilibrium porewater concentrations estimated based Kom organic carbon fraction soil instead total soil concentrations? Based equation (7) given PPR panel opinion (EFSA 2012, p. 24) scenarios specified EFSA guidance (2015, p. 13).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"predicted concentration soil","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"assumes complete load soil time specified 'interval' (typically 365 days) dosed . PPR panel opinion cited (EFSA PPR panel 2012), temperature correction using Arrhenius equation performed. Total soil porewater PEC values scenarios defined EFSA guidance (2017, p. 14/15) can easily calculated.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"time weighted average (TWA) concentrations given examples EFSA guidance 2015 (p. 80) reproduced, true TWA concentrations given example EFSA guidance 2017 (p. 92). According EFSA guidance (EFSA, 2017, p. 43), leaching taken account EFSA 2017 scenarios, using evaluation depth (mixing depth) depth layer leaching takes place. However, amount leaching evaluation depth (often 5 cm) partly mixed back tillage, default function use tillage depth calculation leaching rate. temperature information available selected scenarios, e.g. EFSA scenarios, DT50 groundwater modelling (destination 'PECgw') taken chent object, otherwise DT50 destination 'PECsoil'.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"EFSA Panel Plant Protection Products Residues (2012) Scientific Opinion science behind guidance scenario selection scenario parameterisation predicting environmental concentrations plant protection products soil. EFSA Journal 10(2) 2562, doi:10.2903/j.efsa.2012.2562 EFSA (European Food Safety Authority) 2017) EFSA guidance document predicting environmental concentrations active substances plant protection products transformation products active substances soil. EFSA Journal 15(10) 4982 doi:10.2903/j.efsa.2017.4982 EFSA (European Food Safety Authority) (2015) EFSA guidance document predicting environmental concentrations active substances plant protection products transformation products active substances soil. EFSA Journal 13(4) 4093 doi:10.2903/j.efsa.2015.4093","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate predicted environmental concentrations in soil — PEC_soil","text":"","code":"PEC_soil(100, interception = 0.25) #> scenario #> t_avg default #> 0 0.1 # This is example 1 starting at p. 92 of the EFSA guidance (2017) # Note that TWA concentrations differ from the ones given in the guidance # for an unknown reason (the values from EFSA (2015) can be reproduced). PEC_soil(1000, interval = 365, DT50 = 250, t_avg = c(0, 21), Kom = 1000, scenarios = \"EFSA_2017\") #> scenario #> t_avg CTN CTC CTS #> 0 19.76834 13.8619 10.53795 #> 21 19.59345 13.7169 10.39882 PEC_soil(1000, interval = 365, DT50 = 250, t_av = c(0, 21), Kom = 1000, scenarios = \"EFSA_2017\", porewater = TRUE) #> scenario #> t_avg CLN CLC CLS #> 0 0.5541984 0.6779249 0.9816693 #> 21 0.5484576 0.6693125 0.9609119 # This is example 1 starting at p. 79 of the EFSA guidance (2015) PEC_soil(1000, interval = 365, DT50 = 250, t_avg = c(0, 21), scenarios = \"EFSA_2015\") #> scenario #> t_avg CTN CTC CTS #> 0 21.96827 11.53750 9.145259 #> 21 21.78517 11.40701 9.017370 PEC_soil(1000, interval = 365, DT50 = 250, t_av = c(0, 21), Kom = 1000, scenarios = \"EFSA_2015\", porewater = TRUE) #> scenario #> t_avg CLN CLC CLS #> 0 0.7589401 0.6674322 0.9147861 #> 21 0.7506036 0.6590345 0.8987279 # The following is from example 4 starting at p. 85 of the EFSA guidance (2015) # Metabolite M2 # Calculate total and porewater soil concentrations for tier 1 scenarios # Relative molar mass is 100/300, formation fraction is 0.7 * 1 results_pfm <- PEC_soil(100/300 * 0.7 * 1 * 1000, interval = 365, DT50 = 250, t_avg = c(0, 21), scenarios = \"EFSA_2015\") results_pfm_pw <- PEC_soil(100/300 * 0.7 * 1000, interval = 365, DT50 = 250, t_av = c(0, 21), Kom = 100, scenarios = \"EFSA_2015\", porewater = TRUE)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil_mets.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets","title":"Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets","text":"Calculate initial accumulation PEC soil set metabolites","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil_mets.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets","text":"","code":"PEC_soil_mets(rate, mw_parent, mets, interval = 365, ...)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_soil_mets.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate initial and accumulation PEC soil for a set of metabolites — PEC_soil_mets","text":"rate Application rate units specified mw_parent molecular weight parent compound mets dataframe metabolite identifiers rownames columns \"mw\", \"occ\" \"DT50\" holding molecular weight, maximum occurrence soil soil DT50 interval interval accumulation calculations ... arguments passed PEC_soil","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"implements method specified UK data requirements handbook checked spreadsheet published CRC website","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"","code":"PEC_sw_drainage_UK( rate, interception = 0, Koc, latest_application = NULL, soil_DT50 = NULL, model = NULL, model_parms = NULL )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"rate Application rate g/ha interception fraction application rate reach soil Koc sorption coefficient normalised organic carbon L/kg latest_application Latest application date, formatted e.g. \"01 July\" soil_DT50 Soil degradation half-life, SFO kinetics used model soil degradation model used. Either one \"FOMC\", \"DFOP\", \"HS\", \"IORE\", mkinmod object model_parms named numeric vector containing model parameters","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"predicted concentration surface water µg/L","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"HSE's Chemicals Regulation Division (CRD) Active substance PECsw calculations (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 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","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drainage_UK.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate initial predicted environmental concentrations in surface water due to drainage using the UK method — PEC_sw_drainage_UK","text":"","code":"PEC_sw_drainage_UK(150, Koc = 100) #> [1] 8.076923"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"basic, vectorised form simple calculation contaminant concentration surface water based complete, instantaneous mixing input via spray drift.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"","code":"PEC_sw_drift( rate, applications = 1, water_depth = 30, drift_percentages = NULL, drift_data = c(\"JKI\", \"RF\"), crop = \"Ackerbau\", distances = c(1, 5, 10, 20), rate_units = \"g/ha\", PEC_units = \"µg/L\" )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"rate Application rate units specified applications Number applications selection drift percentile water_depth Depth water body cm drift_percentages Percentage drift values calculate PECsw. 'drift_data' 'distances' NULL. drift_data Source drift percentage data. 'JKI', drift_data_JKI included package used. 'RF', Rautmann formula used, implemented crop type number applications crop Crop name (use German names JKI data), defaults \"Ackerbau\" distances distances m get PEC values rate_units Defaults g/ha PEC_units Requested units calculated PEC. µg/L currently supported","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"predicted concentration surface water","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_drift.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate predicted environmental concentrations in surface water due to drift — PEC_sw_drift","text":"","code":"PEC_sw_drift(100) #> 1 m 5 m 10 m 20 m #> 0.92333333 0.19000000 0.09666667 0.05000000 # Alternatively, we can use the formula for a single application to \"Ackerbau\" from the paper PEC_sw_drift(100, drift_data = \"RF\") #> 1 m 5 m 10 m 20 m #> 0.92350000 0.19114149 0.09699222 0.04921742 # This makes it possible to also use different substances PEC_sw_drift(100, distances = c(1, 3, 5, 6, 10, 20, 50, 100), drift_data = \"RF\") #> 1 m 3 m 5 m 6 m 10 m 20 m 50 m #> 0.92350000 0.31512171 0.19114149 0.15990435 0.09699222 0.04921742 0.02007497 #> 100 m #> 0.01018678 # Using custom drift percentages is also supported PEC_sw_drift(100, drift_percentages = c(2.77, 0.95, 0.57, 0.48, 0.29, 0.15, 0.06, 0.03)) #> 2.77 % 0.95 % 0.57 % 0.48 % 0.29 % 0.15 % 0.06 % #> 0.92333333 0.31666667 0.19000000 0.16000000 0.09666667 0.05000000 0.02000000 #> 0.03 % #> 0.01000000"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"reimplementation calculation described Exposit 3.02 spreadsheet file, worksheet \"Konzept Drainage\". Although four groups compounds (\"Gefährdungsgruppen\"), one distinction made calculations, compounds low mobility (group 1) compounds modest high mobility (groups 2, 3 4). implementation, group derived Koc, given explicitly. details, see discussion function arguments .","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"","code":"PEC_sw_exposit_drainage( rate, interception = 0, Koc = NA, mobility = c(NA, \"low\", \"high\"), DT50 = Inf, t_drainage = 3, V_ditch = 30, V_drainage = c(spring = 10, autumn = 100), dilution = 2 )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"Excel 3.02 spreadsheet available https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"rate application rate g/ha interception fraction intercepted crop Koc sorption coefficient soil organic carbon used determine mobility. trigger value 550 L/kg used order decide Koc >> 500. mobility Overrides determined Koc. DT50 soil half-life days t_drainage time application drainage event, degradation occurs, days V_ditch volume ditch assumed 1 m * 100 m * 30 cm = 30 m3 V_drainage drainage volume, equivalent 1 mm precipitation 1 ha spring/summer 10 mm autumn/winter/early spring. dilution dilution factor","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"list containing following components perc_runoff runoff percentages dissolved bound substance runoff matrix containing dissolved bound input different distances PEC_sw_runoff matrix containing PEC values dissolved bound substance different distances. rate given g/ha, PECsw microg/L.","code":""},{"path":[]},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_drainage.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate PEC surface water due to drainage as in Exposit 3 — PEC_sw_exposit_drainage","text":"","code":"PEC_sw_exposit_drainage(500, Koc = 150) #> $perc_drainage_total #> spring autumn #> 0.2 1.0 #> #> $perc_peak #> spring autumn #> 12.5 25.0 #> #> $PEC_sw_drainage #> spring autumn #> 1.562500 4.807692 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"reimplementation calculation described Exposit 3.02 spreadsheet file, worksheet \"Konzept Runoff\".","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"","code":"PEC_sw_exposit_runoff( rate, interception = 0, Koc, DT50 = Inf, t_runoff = 3, exposit_reduction_version = c(\"3.02\", \"3.01a\", \"3.01a2\", \"2.0\"), V_ditch = 30, V_event = 100, dilution = 2 )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"Excel 3.02 spreadsheet available https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"rate application rate g/ha interception fraction intercepted crop Koc sorption coefficient soil organic carbon DT50 soil half-life days t_runoff time application runoff event, degradation occurs, days exposit_reduction_version version reduction factors used. \"3.02\" current version used Germany, \"3.01a\" version additional percentages 3 m 6 m buffer zones used Switzerland. \"3.01a2\" version introduced consistency previous calculations performed 3 m buffer zone Switzerland, reduction applied dissolved bound fraction. V_ditch volume ditch assumed 1 m * 100 m * 30 cm = 30 m3 V_event unreduced runoff volume, equivalent 10 mm precipitation 1 ha dilution dilution factor","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"list containing following components perc_runoff runoff percentages dissolved bound substance runoff matrix containing dissolved bound input different distances PEC_sw_runoff matrix containing PEC values dissolved bound substance different distances. rate given g/ha, PECsw microg/L.","code":""},{"path":[]},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_exposit_runoff.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate PEC surface water due to runoff and erosion as in Exposit 3 — PEC_sw_exposit_runoff","text":"","code":"PEC_sw_exposit_runoff(500, Koc = 150) #> $perc_runoff #> dissolved bound #> 0.248 0.001 #> #> $runoff #> dissolved bound total #> No buffer 1.240 0.00500 1.24500 #> 5 m 0.744 0.00300 0.74700 #> 10 m 0.496 0.00075 0.49675 #> 20 m 0.248 0.00025 0.24825 #> #> $PEC_sw_runoff #> dissolved bound total #> No buffer 4.769231 0.019230769 4.788462 #> 5 m 4.133333 0.016666667 4.150000 #> 10 m 3.542857 0.005357143 3.548214 #> 20 m 2.480000 0.002500000 2.482500 #> PEC_sw_exposit_runoff(600, Koc = 10000, DT50 = 195, exposit = \"3.01a\") #> $perc_runoff #> dissolved bound #> 0.037 0.159 #> #> $runoff #> dissolved bound total #> No buffer 0.21964521 0.94388078 1.16352600 #> 3 m 0.16473391 0.66071655 0.82545046 #> 5 m 0.13178713 0.56632847 0.69811560 #> 6 m 0.12080487 0.42474635 0.54555122 #> 10 m 0.08785809 0.14158212 0.22944020 #> 20 m 0.04392904 0.04719404 0.09112308 #> #> $PEC_sw_runoff #> dissolved bound total #> No buffer 0.8447893 3.6303107 4.4751000 #> 3 m 0.7844472 3.1462693 3.9307165 #> 5 m 0.7321507 3.1462693 3.8784200 #> 6 m 0.7106169 2.4985080 3.2091248 #> 10 m 0.6275578 1.0113008 1.6388586 #> 20 m 0.4392904 0.4719404 0.9112308 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"reimplementation FOCUS Step 1 2 calculator version 3.2, authored Michael Klein, R. Note results multiple applications compared corresponding results single application. current, done automatically implementation. Step 1 PECs calculated. However, input files generated suitable input also Step 2 used FOCUS calculator.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"","code":"PEC_sw_focus( parent, rate, n = 1, i = NA, comment = \"\", met = NULL, f_drift = NA, f_rd = 0.1, scenario = FOCUS_Step_12_scenarios$names, region = c(\"n\", \"s\"), season = c(NA, \"of\", \"mm\", \"js\"), interception = c(\"no interception\", \"minimal crop cover\", \"average crop cover\", \"full canopy\"), met_form_water = TRUE, txt_file = \"pesticide.txt\", overwrite = FALSE, append = TRUE )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"parent list containing substance specific parameters, e.g. conveniently generated chent_focus_sw. rate application rate g/ha. Overriden applications given explicitly n number applications application interval comment comment input file met list containing metabolite specific parameters. e.g. conveniently generated chent_focus_sw. NULL, PEC calculated compound, parent. f_drift fraction application rate reaching waterbody via drift. NA, derived scenario name number applications via drift data defined FOCUS_Step_12_scenarios f_rd fraction amount applied reaching waterbody via runoff/drainage. Step 1, assumed 10%, parent metabolite scenario name scenario. Must one scenario names given FOCUS_Step_12_scenarios region 'n' Northern Europe 's' Southern Europe. NA, Step 1 PECsw calculated season '' October February, 'mm' March May, 'js' June September. NA, step 1 PECsw calculated interception One 'interception' (default), 'minimal crop cover', 'average crop cover' 'full canopy' met_form_water metabolite formation water taken account? can switched check influence compare previous versions Steps 12 calculator txt_file name, potentially full path Steps.12 input text file specification run(s) written overwrite existing file location specified txt_file overwritten? takes effect append FALSE. append input text file appended?","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"formulas input waterbody via runoff/drainage parent subsequent formation metabolite water documented model description coming calculator. one expect, appears (get results) calculated multiplying application rate molar weight correction formation fraction water/sediment systems. Step 2 implemented.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"FOCUS (2014) Generic guidance Surface Water Scenarios (version 1.4). FOrum Co-ordination pesticde fate models USe. http://esdac.jrc.ec.europa.eu/public_path/projects_data/focus/sw/docs/Generic%20FOCUS_SWS_vc1.4.pdf Website Steps 1 2 calculator Joint Research Center European Union: http://esdac.jrc.ec.europa.eu/projects/stepsonetwo","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_focus.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate PEC surface water at FOCUS Step 1 — PEC_sw_focus","text":"","code":"# Parent only dummy_1 <- chent_focus_sw(\"Dummy 1\", cwsat = 6000, DT50_ws = 6, Koc = 344.8) PEC_sw_focus(dummy_1, 3000, f_drift = 0, overwrite = TRUE, append = FALSE) #> $f_drift #> [1] 0 #> #> $eq_rate_drift_s #> [1] 3000 #> #> $eq_rate_rd_s #> [1] 3000 #> #> $eq_rate_rd_parent_s #> [1] NA #> #> $input_drift_s #> [1] 0 #> #> $input_rd_s #> [1] 300 #> #> $f_rd_sw #> [1] 0.6850566 #> #> $f_rd_sed #> [1] 0.3149434 #> #> $PEC #> type #> Time PECsw TWAECsw PECsed TWAECsed #> 0 6.850566e+02 NA 2.362075e+03 NA #> 1 6.103161e+02 647.68635 2.104370e+03 2233.2225 #> 2 5.437298e+02 612.03420 1.874780e+03 2110.2939 #> 4 4.315586e+02 548.76030 1.488014e+03 1892.1255 #> 7 3.051580e+02 469.88375 1.052185e+03 1620.1592 #> 14 1.359325e+02 339.57370 4.686951e+02 1170.8501 #> 21 6.055102e+01 257.45458 2.087799e+02 887.7034 #> 28 2.697241e+01 203.47173 9.300089e+01 701.5705 #> 42 5.352005e+00 140.10377 1.845371e+01 483.0778 #> 50 2.123945e+00 118.24602 7.323361e+00 407.7123 #> 100 6.585062e-03 59.30629 2.270529e-02 204.4881 #> #> $PEC_sw_max #> [1] 685.0566 #> #> $PEC_sed_max #> [1] 2362.075 #> # Metabolite new_dummy <- chent_focus_sw(\"New Dummy\", mw = 250, Koc = 100) M1 <- chent_focus_sw(\"M1\", mw = 100, cwsat = 100, DT50_ws = 100, Koc = 50, max_ws = 0, max_soil = 0.5) PEC_sw_focus(new_dummy, 1000, scenario = \"cereals, winter\", met = M1) #> $f_drift #> [1] 0.02759 #> #> $eq_rate_drift_s #> [1] 0 #> #> $eq_rate_rd_s #> [1] 200 #> #> $eq_rate_rd_parent_s #> [1] 0 #> #> $input_drift_s #> [1] 0 #> #> $input_rd_s #> [1] 20 #> #> $f_rd_sw #> [1] 0.9375 #> #> $f_rd_sed #> [1] 0.0625 #> #> $PEC #> type #> Time PECsw TWAECsw PECsed TWAECsed #> 0 62.50000 NA 31.25000 NA #> 1 62.06828 62.28414 31.03414 31.14207 #> 2 61.63954 62.06890 30.81977 31.03445 #> 4 60.79093 61.64158 30.39547 30.82079 #> 7 59.53987 61.00800 29.76994 30.50400 #> 14 56.71995 59.56326 28.35997 29.78163 #> 21 54.03358 58.16414 27.01679 29.08207 #> 28 51.47444 56.80902 25.73722 28.40451 #> 42 46.71404 54.22460 23.35702 27.11230 #> 50 44.19417 52.81945 22.09709 26.40973 #> 100 31.25000 45.08422 15.62500 22.54211 #> #> $PEC_sw_max #> [1] 62.5 #> #> $PEC_sed_max #> [1] 31.25 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","title":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","text":"method 'percentage' equivalent used CRD spreadsheet PEC calculator","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","text":"","code":"PEC_sw_sed( PEC_sw, percentage = 100, method = \"percentage\", sediment_depth = 5, water_depth = 30, sediment_density = 1.3, PEC_sed_units = c(\"µg/kg\", \"mg/kg\") )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","text":"PEC_sw Numeric vector matrix surface water concentrations µg/L corresponding sediment concentration estimated percentage percentage sediment, used percentage method method method used calculation sediment_depth Depth sediment layer water_depth Depth water body cm sediment_density density sediment L/kg (equivalent g/cm3) PEC_sed_units units estimated sediment PEC value","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","text":"predicted concentration sediment","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/PEC_sw_sed.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate predicted environmental concentrations in sediment from surface\nwater concentrations — PEC_sw_sed","text":"","code":"PEC_sw_sed(PEC_sw_drift(100, distances = 1), percentage = 50) #> 1 m #> 2.130769"},{"path":"https://pkgdown.jrwb.de/pfm/reference/SFO_actual_twa.html","id":null,"dir":"Reference","previous_headings":"","what":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","title":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","text":"Actual maximum moving window time average concentrations SFO kinetics","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SFO_actual_twa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","text":"","code":"SFO_actual_twa(DT50 = 1000, times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100))"},{"path":"https://pkgdown.jrwb.de/pfm/reference/SFO_actual_twa.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","text":"FOCUS (2014) Generic Guidance Estimating Persistence Degradation Kinetics Environmental Fate Studies Pesticides EU Registration, Version 1.1, 18 December 2014, p. 251","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SFO_actual_twa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","text":"DT50 half-life. times output times, window sizes time weighted average concentrations","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SFO_actual_twa.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SFO_actual_twa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Actual and maximum moving window time average concentrations for SFO kinetics — SFO_actual_twa","text":"","code":"SFO_actual_twa(10) #> actual twa #> 0 1.0000000000 NaN #> 1 0.9330329915 0.9661297 #> 2 0.8705505633 0.9337803 #> 4 0.7578582833 0.8733416 #> 7 0.6155722067 0.7923030 #> 14 0.3789291416 0.6400113 #> 21 0.2332582479 0.5267498 #> 28 0.1435872944 0.4412651 #> 42 0.0544094102 0.3248093 #> 50 0.0312500000 0.2795222 #> 100 0.0009765625 0.1441286"},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":null,"dir":"Reference","previous_headings":"","what":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"implements method specified UK data requirements handbook checked spreadsheet published CRC website","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"","code":"SSLRC_mobility_classification(Koc)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"Koc sorption coefficient normalised organic carbon L/kg","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"list containing classification percentage compound transported per 10 mm drain water","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"HSE's Chemicals Regulation Division (CRD) Active substance PECsw calculations (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 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","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/SSLRC_mobility_classification.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Determine the SSLRC mobility classification for a chemical substance from its Koc — SSLRC_mobility_classification","text":"","code":"SSLRC_mobility_classification(100) #> $`Mobility classification` #> [1] \"Moderately mobile\" #> #> $`Percentage drained per mm of drain water` #> [1] 0.7 #> SSLRC_mobility_classification(10000) #> $`Mobility classification` #> [1] \"Non mobile\" #> #> $`Percentage drained per mm of drain water` #> [1] 0.008 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":null,"dir":"Reference","previous_headings":"","what":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"R6 class holding TOXSWA water concentration (cwa) data associated statistics. like maximum moving window average concentrations, dataframes holding events exceeding specified thresholds. Usually, instance class generated read.TOXSWA_cwa.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"R6Class generator object.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"public-fields","dir":"Reference","previous_headings":"","what":"Public fields","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"filename Length one character vector holding filename. basedir Length one character vector holding directory file came . zipfile null, giving path zip file file read. segment Length one integer, specifying segment cwa data read. substance TOXSWA name substance. cwas Dataframe holding concentrations. events List dataframes holding event statistics threshold. windows Matrix maximum time weighted average concentrations (TWAC_max) areas curve µg/day * h (AUC_max_h) µg/day * d (AUC_max_d) requested moving window sizes days.","code":""},{"path":[]},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"public-methods","dir":"Reference","previous_headings":"","what":"Public methods","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"TOXSWA_cwa$new() TOXSWA_cwa$moving_windows() TOXSWA_cwa$get_events() TOXSWA_cwa$print() TOXSWA_cwa$clone()","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"method-new-","dir":"Reference","previous_headings":"","what":"Method new()","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"Create TOXSWA_cwa object file","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"usage","dir":"Reference","previous_headings":"","what":"Usage","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"","code":"TOXSWA_cwa$new( filename, basedir, zipfile = NULL, segment = \"last\", substance = \"parent\", total = FALSE )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"filename filename basedir directory look zipfile Optional path zipfile holding file segment Either \"last\" number segment read data substance TOXSWA substance name (TOXSWA 4 higher) total total concentrations read ? FALSE, free concentrations read","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"method-moving-windows-","dir":"Reference","previous_headings":"","what":"Method moving_windows()","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"Add windows field described .","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"usage-1","dir":"Reference","previous_headings":"","what":"Usage","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"","code":"TOXSWA_cwa$moving_windows(windows, total = FALSE)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"arguments-1","dir":"Reference","previous_headings":"","what":"Arguments","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"windows Window sizes days total TRUE, total concentration including amount adsorbed suspended matter used.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"method-get-events-","dir":"Reference","previous_headings":"","what":"Method get_events()","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"Populate datataframe event information specified threshold value. resulting dataframe stored events field object.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"usage-2","dir":"Reference","previous_headings":"","what":"Usage","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"","code":"TOXSWA_cwa$get_events(thresholds, total = FALSE)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"arguments-2","dir":"Reference","previous_headings":"","what":"Arguments","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"thresholds Threshold values µg/L. total TRUE, total concentration including amount adsorbed suspended matter used.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"method-print-","dir":"Reference","previous_headings":"","what":"Method print()","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"Print TOXSWA_cwa object","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"usage-3","dir":"Reference","previous_headings":"","what":"Usage","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"","code":"TOXSWA_cwa$print()"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"method-clone-","dir":"Reference","previous_headings":"","what":"Method clone()","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"objects class cloneable method.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"usage-4","dir":"Reference","previous_headings":"","what":"Usage","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"","code":"TOXSWA_cwa$clone(deep = FALSE)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"arguments-3","dir":"Reference","previous_headings":"","what":"Arguments","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"deep Whether make deep clone.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TOXSWA_cwa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"R6 class for holding TOXSWA water concentration data and associated statistics — TOXSWA_cwa","text":"","code":"H_sw_R1_stream <- read.TOXSWA_cwa(\"00003s_pa.cwa\", basedir = \"SwashProjects/project_H_sw/TOXSWA\", zipfile = system.file(\"testdata/SwashProjects.zip\", package = \"pfm\")) H_sw_R1_stream$get_events(c(2, 10)) H_sw_R1_stream$moving_windows(c(7, 21)) print(H_sw_R1_stream) #> <TOXSWA_cwa> data from file 00003s_pa.cwa segment 20 #> datetime t t_firstjan t_rel_to_max cwa_mug_per_L #> 20 1978-10-01 00:00:00 0.000 273.0000 -55.333 0 #> 40 1978-10-01 01:00:00 0.042 273.0417 -55.291 0 #> 60 1978-10-01 02:00:00 0.083 273.0833 -55.250 0 #> 80 1978-10-01 03:00:00 0.125 273.1250 -55.208 0 #> 100 1978-10-01 04:00:00 0.167 273.1667 -55.166 0 #> 120 1978-10-01 05:00:00 0.208 273.2083 -55.125 0 #> cwa_tot_mug_per_L #> 20 0 #> 40 0 #> 60 0 #> 80 0 #> 100 0 #> 120 0 #> Moving window analysis #> window max_TWAC max_AUC_h max_AUC_d #> 1 7 days 2.3926551 401.9660 16.74859 #> 2 21 days 0.8369248 421.8101 17.57542 #> Event statistics for threshold 2 #> t_start cwa_max duration pre_interval AUC_h AUC_d #> 1 44.375 4.167238 0.208 44.375 17.77202 0.740501 #> 2 55.042 40.584010 0.583 10.459 398.21189 16.592162 #> Event statistics for threshold 10 #> t_start cwa_max duration pre_interval AUC_h AUC_d #> 1 55.083 40.58401 0.459 55.083 379.433 15.80971"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TSCF.html","id":null,"dir":"Reference","previous_headings":"","what":"Estimation of the transpiration stream concentration factor — TSCF","title":"Estimation of the transpiration stream concentration factor — TSCF","text":"FOCUS groundwater guidance (FOCUS 2014, p. 41) states reliable measured log Kow neutral pH must available order apply Briggs equation. clarified can regarded reliable, equation stated produced non-ionic compounds, suggesting compound ionogenic (weak acid/base) ionic.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TSCF.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Estimation of the transpiration stream concentration factor — TSCF","text":"","code":"TSCF(log_Kow, method = c(\"briggs82\", \"dettenmaier09\"))"},{"path":"https://pkgdown.jrwb.de/pfm/reference/TSCF.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Estimation of the transpiration stream concentration factor — TSCF","text":"log_Kow decadic logarithm octanol-water partition constant method Short name estimation method.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TSCF.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Estimation of the transpiration stream concentration factor — TSCF","text":"Dettenmaier equation given show views subject exist.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TSCF.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Estimation of the transpiration stream concentration factor — TSCF","text":"FOCUS (2014) Generic Guidance Tier 1 FOCUS Ground Water Assessments. Version 2.2, May 2014 Dettenmaier EM, Doucette WJ Bugbee B (2009) Chemical hydrophobicity uptake plant roots. Environ. Sci. Technol 43, 324 - 329","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/TSCF.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Estimation of the transpiration stream concentration factor — TSCF","text":"","code":"plot(TSCF, -1, 5, xlab = \"log Kow\", ylab = \"TSCF\", ylim = c(0, 1.1)) TSCF_2 <- function(x) TSCF(x, method = \"dettenmaier09\") curve(TSCF_2, -1, 5, add = TRUE, lty = 2) legend(\"topright\", lty = 1:2, bty = \"n\", legend = c(\"Briggs et al. (1982)\", \"Dettenmaier et al. (2009)\"))"},{"path":"https://pkgdown.jrwb.de/pfm/reference/chent_focus_sw.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","title":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","text":"Create chemical compound object FOCUS Step 1 calculations","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/chent_focus_sw.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","text":"","code":"chent_focus_sw( name, Koc, DT50_ws = NA, DT50_soil = NA, DT50_water = NA, DT50_sediment = NA, cwsat = 1000, mw = NA, max_soil = 1, max_ws = 1 )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/chent_focus_sw.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","text":"name Length one character vector containing name Koc Partition coefficient organic carbon water L/kg. DT50_ws Half-life water/sediment systems days DT50_soil Half-life soil days DT50_water Half-life water days (Step 2) DT50_sediment Half-life sediment days (Step 2) cwsat Water solubility mg/L mw Molar weight g/mol. max_soil Maximum observed fraction (dimensionless) soil max_ws Maximum observed fraction (dimensionless) water/sediment systems","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/chent_focus_sw.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a chemical compound object for FOCUS Step 1 calculations — chent_focus_sw","text":"list substance specific properties","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":null,"dir":"Reference","previous_headings":"","what":"Deposition from spray drift expressed as percent of the applied dose as\npublished by the JKI — drift_data_JKI","title":"Deposition from spray drift expressed as percent of the applied dose as\npublished by the JKI — drift_data_JKI","text":"Deposition spray drift expressed percent applied dose published German Julius-Kühn Institute (JKI).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Deposition from spray drift expressed as percent of the applied dose as\npublished by the JKI — drift_data_JKI","text":"list currently containing matrices spray drift percentage data field crops (Ackerbau), Pome/stone fruit, early late (Obstbau frueh, spaet).","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Deposition from spray drift expressed as percent of the applied dose as\npublished by the JKI — drift_data_JKI","text":"JKI (2010) Spreadsheet 'Tabelle der Abdrifteckwerte.xls', retrieved http://www.jki.bund.de/no_cache/de/startseite/institute/anwendungstechnik/abdrift-eckwerte.html 2015-06-11 Rautmann, D., Streloke, M Winkler, R (2001) New basic drift values authorization procedure plant protection products Mitt. Biol. Bundesanst. Land- Forstwirtsch. 383, 133-141","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Deposition from spray drift expressed as percent of the applied dose as\npublished by the JKI — drift_data_JKI","text":"data extracted spreadsheet cited using R code given example section. spreadsheet included package licence clear. Additional spray drift values taken publication Rautmann et al. (2001). Specifically, values early vines, values 3 m buffer incomplete spreadsheet. Note vegetables, ornamentals small fruit, values field crops used crops < 50 cm, vales late vines used crops > 50 cm. JKI spreadsheet, indicated values used spray applications handheld/knapsack equipment (tragbare Spritz- und Sprühgerate). Values non-professional use listed JKI spreadsheet included.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/drift_data_JKI.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Deposition from spray drift expressed as percent of the applied dose as\npublished by the JKI — drift_data_JKI","text":"","code":"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 #> [[1]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 2.77 NA NA NA NA #> 3 0.95 29.20 15.73 2.70 8.02 #> 5 0.57 19.89 8.41 1.18 3.62 #> 10 0.29 11.81 3.60 0.39 1.23 #> 15 0.20 5.55 1.81 0.20 0.65 #> 20 0.15 2.77 1.09 0.13 0.42 #> 30 0.10 1.04 0.54 0.07 0.22 #> 40 0.07 0.52 0.32 0.04 0.14 #> 50 0.06 0.30 0.22 0.03 0.10 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 4.440 NA #> 3 19.33 NA 0.018721696 #> 5 11.57 0.180 0.014363896 #> 10 5.77 0.050 0.010026007 #> 15 3.84 0.020 0.008124366 #> 20 1.79 0.012 0.006998158 #> 30 0.56 0.005 0.005670811 #> 40 0.25 0.003 NA #> 50 0.13 0.002 0.004350831 #> #> [[2]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 2.38 NA NA NA NA #> 3 0.79 25.53 12.13 2.53 7.23 #> 5 0.47 16.87 6.81 1.09 3.22 #> 10 0.24 9.61 3.11 0.35 1.07 #> 15 0.16 5.61 1.58 0.18 0.56 #> 20 0.12 2.59 0.90 0.11 0.36 #> 30 0.08 0.87 0.40 0.06 0.19 #> 40 0.06 0.40 0.23 0.03 0.12 #> 50 0.05 0.22 0.15 0.02 0.08 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 3.780 NA #> 3 17.73 NA NA #> 5 9.60 0.160 NA #> 10 4.18 0.040 NA #> 15 2.57 0.020 NA #> 20 1.21 0.011 NA #> 30 0.38 0.005 NA #> 40 0.17 0.003 NA #> 50 0.09 0.002 NA #> #> [[3]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 2.01 NA NA NA NA #> 3 0.68 23.96 11.01 2.49 6.90 #> 5 0.41 15.79 6.04 1.04 3.07 #> 10 0.20 8.96 2.67 0.32 1.02 #> 15 0.14 4.24 1.39 0.16 0.54 #> 20 0.10 2.01 0.80 0.10 0.34 #> 30 0.07 0.70 0.36 0.05 0.18 #> 40 0.05 0.33 0.21 0.03 0.11 #> 50 0.04 0.19 0.13 0.02 0.08 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 3.420 NA #> 3 15.93 NA NA #> 5 8.57 0.150 NA #> 10 3.70 0.040 NA #> 15 2.26 0.020 NA #> 20 1.05 0.010 NA #> 30 0.34 0.004 NA #> 40 0.15 0.003 NA #> 50 0.08 0.002 NA #> #> [[4]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 1.85 NA NA NA NA #> 3 0.62 23.61 10.12 2.44 6.71 #> 5 0.38 15.42 5.60 1.02 2.99 #> 10 0.19 8.66 2.50 0.31 0.99 #> 15 0.13 4.01 1.28 0.16 0.52 #> 20 0.10 1.89 0.75 0.10 0.33 #> 30 0.06 0.66 0.35 0.05 0.17 #> 40 0.05 0.31 0.20 0.03 0.11 #> 50 0.04 0.17 0.13 0.02 0.08 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 2.290 NA #> 3 15.38 NA NA #> 5 8.26 0.120 NA #> 10 3.55 0.030 NA #> 15 2.17 0.020 NA #> 20 0.93 0.009 NA #> 30 0.31 0.004 NA #> 40 0.14 0.002 NA #> 50 0.08 0.002 NA #> #> [[5]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 1.75 NA NA NA NA #> 3 0.59 23.12 9.74 2.37 6.59 #> 5 0.36 15.06 5.41 1.00 2.93 #> 10 0.18 8.42 2.43 0.31 0.98 #> 15 0.12 3.83 1.24 0.15 0.51 #> 20 0.09 1.81 0.72 0.09 0.33 #> 30 0.06 0.63 0.34 0.05 0.17 #> 40 0.05 0.30 0.20 0.03 0.11 #> 50 0.04 0.17 0.13 0.02 0.08 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 2.120 NA #> 3 15.12 NA NA #> 5 7.99 0.110 NA #> 10 3.36 0.030 NA #> 15 2.03 0.010 NA #> 20 0.88 0.008 NA #> 30 0.29 0.004 NA #> 40 0.14 0.002 NA #> 50 0.07 0.002 NA #> #> [[6]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 1.64 NA NA NA NA #> 3 0.56 22.76 9.21 2.29 6.41 #> 5 0.34 14.64 5.18 0.97 2.85 #> 10 0.17 8.04 2.38 0.30 0.95 #> 15 0.11 3.71 1.20 0.15 0.50 #> 20 0.09 1.75 0.68 0.09 0.32 #> 30 0.06 0.61 0.31 0.05 0.17 #> 40 0.04 0.29 0.17 0.03 0.11 #> 50 0.03 0.16 0.11 0.02 0.07 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 1.980 NA #> 3 14.90 NA NA #> 5 7.79 0.100 NA #> 10 3.23 0.030 NA #> 15 1.93 0.010 NA #> 20 0.83 0.008 NA #> 30 0.28 0.004 NA #> 40 0.13 0.002 NA #> 50 0.07 0.001 NA #> #> [[7]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 1.61 NA NA NA NA #> 3 0.55 22.69 9.10 2.24 6.33 #> 5 0.33 14.45 5.11 0.94 2.81 #> 10 0.17 7.83 2.33 0.29 0.94 #> 15 0.11 3.62 1.20 0.15 0.49 #> 20 0.08 1.71 0.67 0.09 0.31 #> 30 0.06 0.60 0.30 0.05 0.16 #> 40 0.04 0.28 0.17 0.03 0.10 #> 50 0.03 0.16 0.11 0.02 0.07 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 1.930 NA #> 3 14.63 NA NA #> 5 7.60 0.100 NA #> 10 3.13 0.030 NA #> 15 1.86 0.010 NA #> 20 0.81 0.008 NA #> 30 0.26 0.004 NA #> 40 0.12 0.002 NA #> 50 0.06 0.001 NA #> #> [[8]] #> crop #> distance Ackerbau Obstbau frueh Obstbau spaet Weinbau frueh Weinbau spaet #> 1 1.52 NA NA NA NA #> 3 0.52 22.24 8.66 2.16 6.26 #> 5 0.31 14.09 4.92 0.91 2.78 #> 10 0.16 7.58 2.29 0.28 0.93 #> 15 0.11 3.48 1.14 0.14 0.49 #> 20 0.08 1.65 0.65 0.09 0.31 #> 30 0.05 0.57 0.29 0.04 0.16 #> 40 0.04 0.27 0.16 0.03 0.10 #> 50 0.03 0.15 0.11 0.02 0.07 #> crop #> distance Hopfenbau Flaechenkulturen > 900 l/ha Gleisanlagen #> 1 NA 1.640 NA #> 3 13.53 NA NA #> 5 7.15 0.090 NA #> 10 3.01 0.020 NA #> 15 1.82 0.010 NA #> 20 0.78 0.007 NA #> 30 0.25 0.003 NA #> 40 0.12 0.002 NA #> 50 0.06 0.001 NA #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/endpoint.html","id":null,"dir":"Reference","previous_headings":"","what":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","title":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","text":"R6 class objects class chent represent chemical entities can hold list information loaded chemical yaml file chyaml field. information extracted optionally aggregated function.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/endpoint.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","text":"","code":"endpoint( chent, medium = \"soil\", type = c(\"degradation\", \"sorption\"), lab_field = c(NA, \"laboratory\", \"field\"), redox = c(NA, \"aerobic\", \"anaerobic\"), value = c(\"DT50ref\", \"Kfoc\", \"N\"), aggregator = geomean, raw = FALSE, signif = 3 ) soil_DT50( chent, aggregator = geomean, signif = 3, lab_field = \"laboratory\", value = \"DT50ref\", redox = \"aerobic\", raw = FALSE ) soil_Kfoc(chent, aggregator = geomean, signif = 3, value = \"Kfoc\", raw = FALSE) soil_N(chent, aggregator = mean, signif = 3, raw = FALSE) soil_sorption( chent, values = c(\"Kfoc\", \"N\"), aggregators = c(Kfoc = geomean, Koc = geomean, N = mean), signif = c(Kfoc = 3, N = 3), raw = FALSE )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/endpoint.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","text":"chent chent object get information medium medium information sought type information type lab_field NA, want laboratory field endpoints redox NA, looking aerobic anaerobic data value name value want. list given usage section exclusive aggregator aggregator function. Can mean, geomean, identity, example. raw number(s) returned stored chent object (character value) retain original information precision? signif many significant digits want values values returned aggregators named vector aggregator functions used","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/endpoint.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","text":"result applying aggregator function values converted numeric vector, rounded given number significant digits, , raw = TRUE, values character value, retaining implicit information precision may present.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/endpoint.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Retrieve endpoint information from the chyaml field of a chent object — endpoint","text":"functions soil_* functions extract soil specific endpoints. Freundlich exponent, capital letter N used order facilitate dealing data R. pesticide fate modelling, exponent often called 1/n.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/geomean.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the geometric mean — geomean","title":"Calculate the geometric mean — geomean","text":"Based posts thread Stackoverflow http://stackoverflow.com/questions/2602583/geometric-mean----built-function returns NA NA values present na.rm = FALSE (default). negative values present, gives error message. least one element vector 0, returns 0.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/geomean.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the geometric mean — geomean","text":"","code":"geomean(x, na.rm = FALSE)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/geomean.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the geometric mean — geomean","text":"x Vector numbers na.rm NA values omitted?","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/geomean.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the geometric mean — geomean","text":"geometric mean","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/geomean.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate the geometric mean — geomean","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/geomean.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the geometric mean — geomean","text":"","code":"geomean(c(1, 3, 9)) #> [1] 3 geomean(c(1, 3, NA, 9)) #> [1] NA if (FALSE) geomean(c(1, -3, 9)) # returns an error"},{"path":"https://pkgdown.jrwb.de/pfm/reference/get_vertex.html","id":null,"dir":"Reference","previous_headings":"","what":"Fit a parabola through three points — get_vertex","title":"Fit a parabola through three points — get_vertex","text":"inspired answer stackoverflow https://stackoverflow.com//717791","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/get_vertex.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fit a parabola through three points — get_vertex","text":"","code":"get_vertex(x, y)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/get_vertex.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fit a parabola through three points — get_vertex","text":"x Three x coordinates y Three y coordinates","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/max_twa.html","id":null,"dir":"Reference","previous_headings":"","what":"The maximum time weighted average concentration for a moving window — max_twa","title":"The maximum time weighted average concentration for a moving window — max_twa","text":"generate time series using sawtooth, need make sure length time series allows finding maximum. therefore recommended check using plot.one_box using window size argument max_twa.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/max_twa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"The maximum time weighted average concentration for a moving window — max_twa","text":"","code":"max_twa(x, window = 21)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/max_twa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"The maximum time weighted average concentration for a moving window — max_twa","text":"x object type one_box window size moving window","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/max_twa.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"The maximum time weighted average concentration for a moving window — max_twa","text":"method working directly fitted mkinfit objects uses equations given PEC soil section FOCUS guidance restricted SFO, FOMC DFOP models parent compound","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/max_twa.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"The maximum time weighted average concentration for a moving window — max_twa","text":"FOCUS (2006) “Guidance Document Estimating Persistence Degradation Kinetics Environmental Fate Studies Pesticides EU Registration” Report FOCUS Work Group Degradation Kinetics, EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics","code":""},{"path":[]},{"path":"https://pkgdown.jrwb.de/pfm/reference/max_twa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"The maximum time weighted average concentration for a moving window — max_twa","text":"","code":"pred <- sawtooth(one_box(10), applications = data.frame(time = c(0, 7), amount = c(1, 1))) max_twa(pred) #> $max #> parent #> 0.9537545 #> #> $window_start #> parent #> 0 #> #> $window_end #> parent #> 21 #> pred_FOMC <- mkinfit(\"FOMC\", FOCUS_2006_C, quiet = TRUE) max_twa(pred_FOMC) #> 21 #> 18.22124"},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":null,"dir":"Reference","previous_headings":"","what":"Create a time series of decline data — one_box","title":"Create a time series of decline data — one_box","text":"Create time series decline data","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create a time series of decline data — one_box","text":"","code":"one_box(x, ini, ..., t_end = 100, res = 0.01) # S3 method for numeric one_box(x, ini = 1, ..., t_end = 100, res = 0.01) # S3 method for character one_box(x, ini = 1, parms, ..., t_end = 100, res = 0.01) # S3 method for mkinfit one_box(x, ini = \"model\", ..., t_end = 100, res = 0.01)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create a time series of decline data — one_box","text":"x numeric, half-life used exponential decline. character string specifying parent decline model given e.g. FOMC, parms must contain corresponding parameters. x mkinfit object, decline calculated object. ini initial amount. x mkinfit object, ini 'model', fitted initial concentrations used. Otherwise, ini must numeric. length one, used parent initial values metabolites zero, otherwise, must give values observed variables. ... arguments passed methods t_end End time series res Resolution time series parms named numeric vector containing model parameters","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Create a time series of decline data — one_box","text":"object class one_box, inheriting ts.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/one_box.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create a time series of decline data — one_box","text":"","code":"# Only use a half-life pred_0 <- one_box(10) plot(pred_0) # Use a fitted mkinfit model require(mkin) fit <- mkinfit(\"FOMC\", FOCUS_2006_C, quiet = TRUE) pred_1 <- one_box(fit) plot(pred_1) # Use a model with more than one observed variable m_2 <- mkinmod(parent = mkinsub(\"SFO\", \"m1\"), m1 = mkinsub(\"SFO\")) #> Temporary DLL for differentials generated and loaded fit_2 <- mkinfit(m_2, FOCUS_2006_D, quiet = TRUE) #> Warning: Observations with value of zero were removed from the data pred_2 <- one_box(fit_2, ini = \"model\") plot(pred_2)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_exposit.html","id":null,"dir":"Reference","previous_headings":"","what":"Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit","title":"Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit","text":"table loss percentages used Exposit 3 twelve different Koc classes","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_exposit.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit","text":"data frame percentage values dissolved fraction fraction bound eroding particles, Koc classes used row names Koc_lower_bound lower bound Koc class dissolved percentage applied substance transferred adjacent water body dissolved phase bound percentage applied substance transferred adjacent water body bound eroding particles","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_exposit.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit","text":"Excel 3.02 spreadsheet available https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_exposit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Runoff loss percentages as used in Exposit 3 — perc_runoff_exposit","text":"","code":"print(perc_runoff_exposit) #> Koc_lower_bound dissolved bound #> 0-20 0 0.110 0.000 #> >20-50 20 0.151 0.000 #> >50-100 50 0.197 0.000 #> >100-200 100 0.248 0.001 #> >200-500 200 0.224 0.004 #> >500-1000 500 0.184 0.020 #> >1000-2000 1000 0.133 0.042 #> >2000-5000 2000 0.084 0.091 #> >5000-10000 5000 0.037 0.159 #> >10000-20000 10000 0.031 0.192 #> >20000-50000 20000 0.014 0.291 #> >50000 50000 0.001 0.451"},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_reduction_exposit.html","id":null,"dir":"Reference","previous_headings":"","what":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","title":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","text":"table runoff reduction percentages used Exposit 3 different vegetated buffer widths","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_reduction_exposit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","text":"","code":"perc_runoff_reduction_exposit"},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_reduction_exposit.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","text":"named list data frames reduction percentage values dissolved fraction fraction bound eroding particles, vegetated buffer widths row names. names list items Exposit versions values taken. dissolved reduction percentage dissolved phase bound reduction percentage particulate phase","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_reduction_exposit.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","text":"Excel 3.02 spreadsheet available https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html Agroscope version 3.01a additional runoff factors 3 m 6 m buffer zones received Muris Korkaric (published). variant 3.01a2 introduced consistency previous calculations performed Agroscope 3 m buffer zone.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/perc_runoff_reduction_exposit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Runoff reduction percentages as used in Exposit — perc_runoff_reduction_exposit","text":"","code":"print(perc_runoff_reduction_exposit) #> $`3.02` #> dissolved bound #> No buffer 0 0 #> 5 m 40 40 #> 10 m 60 85 #> 20 m 80 95 #> #> $`3.01a` #> dissolved bound #> No buffer 0 0 #> 3 m 25 30 #> 5 m 40 40 #> 6 m 45 55 #> 10 m 60 85 #> 20 m 80 95 #> #> $`3.01a2` #> dissolved bound #> No buffer 0 0 #> 3 m 25 25 #> #> $`2.0` #> dissolved bound #> No buffer 0.0 0.0 #> 20 m 97.5 97.5 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/pfm_degradation.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","title":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","text":"Calculate time course relative concentrations based mkinmod model","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/pfm_degradation.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","text":"","code":"pfm_degradation( model = \"SFO\", DT50 = 1000, parms = c(k_parent = log(2)/DT50), years = 1, step_days = 1, times = seq(0, years * 365, by = step_days) )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/pfm_degradation.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","text":"model degradation model used. Either parent model like 'SFO' 'FOMC', mkinmod object DT50 half-life. used simple exponential decline calculated (SFO model). parms parameters used degradation model years many years degradation predicted? step_days step size days output ? times output times","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/pfm_degradation.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/pfm_degradation.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate a time course of relative concentrations based on an mkinmod model — pfm_degradation","text":"","code":"head(pfm_degradation(\"SFO\", DT50 = 10)) #> Error in head(pfm_degradation(\"SFO\", DT50 = 10)): could not find function \"head\""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.TOXSWA_cwa.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","title":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","text":"Plot TOXSWA hourly concentrations chemical substance specific segment TOXSWA surface water body.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.TOXSWA_cwa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","text":"","code":"# S3 method for TOXSWA_cwa plot( x, time_column = c(\"datetime\", \"t\", \"t_firstjan\", \"t_rel_to_max\"), xlab = \"default\", ylab = \"default\", add = FALSE, threshold_factor = 1000, thin_low = 1, total = FALSE, LC_TIME = \"C\", ... )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.TOXSWA_cwa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","text":"x TOXSWA_cwa object plotted. time_column used time axis. \"t_firstjan\" chosen, time given days relative first January first year. xlab, ylab Labels x y axis. add add existing plot? threshold_factor factor data lower maximum order get thinned plotting (see next argument). thin_low integer greater 1, data close zero (smaller 1/threshold_factor maximum) series thinned factor order decrease amount data included plots total total concentration water plotted, including substance sorbed suspended matter? LC_TIME Specification locale used format dates ... arguments passed plot adding existing plot","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.TOXSWA_cwa.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.TOXSWA_cwa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot TOXSWA surface water concentrations — plot.TOXSWA_cwa","text":"","code":"H_sw_D4_pond <- read.TOXSWA_cwa(\"00001p_pa.cwa\", basedir = \"SwashProjects/project_H_sw/TOXSWA\", zipfile = system.file(\"testdata/SwashProjects.zip\", package = \"pfm\")) plot(H_sw_D4_pond) plot(H_sw_D4_pond, time_column = \"t\") plot(H_sw_D4_pond, time_column = \"t_firstjan\") plot(H_sw_D4_pond, time_column = \"t_rel_to_max\") H_sw_R1_stream <- read.TOXSWA_cwa(\"00003s_pa.cwa\", basedir = \"SwashProjects/project_H_sw/TOXSWA\", zipfile = system.file(\"testdata/SwashProjects.zip\", package = \"pfm\")) plot(H_sw_R1_stream, time_column = \"t_rel_to_max\")"},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.one_box.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot time series of decline data — plot.one_box","title":"Plot time series of decline data — plot.one_box","text":"Plot time series decline data","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.one_box.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot time series of decline data — plot.one_box","text":"","code":"# S3 method for one_box plot( x, xlim = range(time(x)), ylim = c(0, max(x)), xlab = \"Time\", ylab = \"Residue\", max_twa = NULL, max_twa_var = dimnames(x)[[2]][1], ... )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.one_box.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot time series of decline data — plot.one_box","text":"x object type one_box plotted xlim Limits x axis ylim Limits y axis xlab Label x axis ylab Label y axis max_twa numeric value given, maximum time weighted average concentration(s) /shown graph. max_twa_var Variable maximum time weighted average shown max_twa NULL. ... arguments passed methods","code":""},{"path":[]},{"path":"https://pkgdown.jrwb.de/pfm/reference/plot.one_box.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot time series of decline data — plot.one_box","text":"","code":"dfop_pred <- one_box(\"DFOP\", parms = c(k1 = 0.2, k2 = 0.02, g = 0.7)) plot(dfop_pred) plot(sawtooth(dfop_pred, 3, 7), max_twa = 21) # Use a fitted mkinfit model m_2 <- mkinmod(parent = mkinsub(\"SFO\", \"m1\"), m1 = mkinsub(\"SFO\")) #> Temporary DLL for differentials generated and loaded fit_2 <- mkinfit(m_2, FOCUS_2006_D, quiet = TRUE) #> Warning: Observations with value of zero were removed from the data pred_2 <- one_box(fit_2, ini = 1) pred_2_saw <- sawtooth(pred_2, 2, 7) plot(pred_2_saw, max_twa = 21, max_twa_var = \"m1\")"},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":null,"dir":"Reference","previous_headings":"","what":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"Read TOXSWA hourly concentrations chemical substance specific segment TOXSWA surface water body. Per default, data last segment imported. TOXSWA 4 reports values end hour (ConLiqWatLayCur) summary file, use value well instead hourly averages (ConLiqWatLay). TOXSWA 5.5.3 variable renamed ConLiqWatLay file.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"","code":"read.TOXSWA_cwa( filename, basedir = \".\", zipfile = NULL, segment = \"last\", substance = \"parent\", total = FALSE, windows = NULL, thresholds = NULL )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"filename filename cwa file (TOXSWA 2.x.y similar) file using FOCUS TOXSWA 4 (.e. TOXSWA 4.4.2) higher. basedir path directory cwa file resides. zipfile Optional path zip file containing cwa file. segment segment data read. Either \"last\", segment number. substance .files, default value \"parent\" leads reading concentrations parent compound. Alternatively, substance interested can selected code name. total Set TRUE order read total concentrations well. necessary .files generated TOXSWA 4.4.2 similar, .cwa files. .cwa files, total concentration always read well. windows Numeric vector width moving windows days, calculating maximum time weighted average concentrations areas curve. thresholds Numeric vector threshold concentrations µg/L generating event statistics.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"instance R6 object class TOXSWA_cwa.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"Johannes Ranke","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/read.TOXSWA_cwa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Read TOXSWA surface water concentrations — read.TOXSWA_cwa","text":"","code":"H_sw_D4_pond <- read.TOXSWA_cwa(\"00001p_pa.cwa\", basedir = \"SwashProjects/project_H_sw/TOXSWA\", zipfile = system.file(\"testdata/SwashProjects.zip\", package = \"pfm\"))"},{"path":"https://pkgdown.jrwb.de/pfm/reference/reexports.html","id":null,"dir":"Reference","previous_headings":"","what":"Objects exported from other packages — reexports","title":"Objects exported from other packages — reexports","text":"objects imported packages. Follow links see documentation. mkin set_nd_nq, set_nd_nq_focus","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/sawtooth.html","id":null,"dir":"Reference","previous_headings":"","what":"Create decline time series for multiple applications — sawtooth","title":"Create decline time series for multiple applications — sawtooth","text":"application pattern specified applications, n disregarded.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/sawtooth.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Create decline time series for multiple applications — sawtooth","text":"","code":"sawtooth( x, n = 1, i = 365, applications = data.frame(time = seq(0, (n - 1) * i, length.out = n), amount = 1) )"},{"path":"https://pkgdown.jrwb.de/pfm/reference/sawtooth.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Create decline time series for multiple applications — sawtooth","text":"x one_box object n number applications. applications specified, n ignored interval applications. applications specified, ignored applications data frame holding application times first column corresponding amounts applied second column.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/sawtooth.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Create decline time series for multiple applications — sawtooth","text":"","code":"applications = data.frame(time = seq(0, 14, by = 7), amount = c(1, 2, 3)) pred <- one_box(10) plot(sawtooth(pred, applications = applications)) m_2 <- mkinmod(parent = mkinsub(\"SFO\", \"m1\"), m1 = mkinsub(\"SFO\")) #> Temporary DLL for differentials generated and loaded fit_2 <- mkinfit(m_2, FOCUS_2006_D, quiet = TRUE) #> Warning: Observations with value of zero were removed from the data pred_2 <- one_box(fit_2, ini = 1) pred_2_saw <- sawtooth(pred_2, 2, 7) plot(pred_2_saw, max_twa = 21, max_twa_var = \"m1\") max_twa(pred_2_saw) #> $max #> parent m1 #> 0.7834481 0.8617049 #> #> $window_start #> parent m1 #> 0.00 26.85 #> #> $window_end #> parent m1 #> 21.00 47.85 #>"},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2015.html","id":null,"dir":"Reference","previous_headings":"","what":"Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015","title":"Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015","text":"Properties predefined scenarios used Tier 1, Tier 2A Tier 3A concentration soil given EFSA guidance (2015, p. 13/14). Also, scenario model adjustment factors p. 15 p. 17 included.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2015.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015","text":"data frame one row scenario. Row names scenario codes, e.g. CTN Northern scenario total concentration soil. Columns mostly self-explanatory. rho dry bulk density top soil.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2015.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015","text":"EFSA (European Food Safety Authority) (2015) EFSA guidance document predicting environmental concentrations active substances plant protection products transformation products active substances soil. EFSA Journal 13(4) 4093 doi:10.2903/j.efsa.2015.4093","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2015.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Properties of the predefined scenarios from the EFSA guidance from 2015 — soil_scenario_data_EFSA_2015","text":"","code":"if (FALSE) { # This is the code that was used to define the data soil_scenario_data_EFSA_2015 <- data.frame( Zone = rep(c(\"North\", \"Central\", \"South\"), 2), Country = c(\"Estonia\", \"Germany\", \"France\", \"Denmark\", \"Czech Republik\", \"Spain\"), T_arit = c(4.7, 8.0, 11.0, 8.2, 9.1, 12.8), T_arr = c(7.0, 10.1, 12.3, 9.8, 11.2, 14.7), Texture = c(\"Coarse\", \"Coarse\", \"Medium fine\", \"Medium\", \"Medium\", \"Medium\"), f_om = c(0.118, 0.086, 0.048, 0.023, 0.018, 0.011), theta_fc = c(0.244, 0.244, 0.385, 0.347, 0.347, 0.347), rho = c(0.95, 1.05, 1.22, 1.39, 1.43, 1.51), f_sce = c(3, 2, 2, 2, 1.5, 1.5), f_mod = c(2, 2, 2, 4, 4, 4), stringsAsFactors = FALSE, row.names = c(\"CTN\", \"CTC\", \"CTS\", \"CLN\", \"CLC\", \"CLS\") ) save(soil_scenario_data_EFSA_2015, file = '../data/soil_scenario_data_EFSA_2015.RData') } # And this is the resulting dataframe soil_scenario_data_EFSA_2015 #> Zone Country T_arit T_arr Texture f_om theta_fc rho f_sce #> CTN North Estonia 4.7 7.0 Coarse 0.118 0.244 0.95 3.0 #> CTC Central Germany 8.0 10.1 Coarse 0.086 0.244 1.05 2.0 #> CTS South France 11.0 12.3 Medium fine 0.048 0.385 1.22 2.0 #> CLN North Denmark 8.2 9.8 Medium 0.023 0.347 1.39 2.0 #> CLC Central Czech Republik 9.1 11.2 Medium 0.018 0.347 1.43 1.5 #> CLS South Spain 12.8 14.7 Medium 0.011 0.347 1.51 1.5 #> f_mod #> CTN 2 #> CTC 2 #> CTS 2 #> CLN 4 #> CLC 4 #> CLS 4"},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2017.html","id":null,"dir":"Reference","previous_headings":"","what":"Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017","title":"Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017","text":"Properties predefined scenarios used Tier 1, Tier 2A Tier 3A concentration soil given EFSA guidance (2017, p. 14/15). Also, scenario model adjustment factors p. 16 p. 18 included.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2017.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017","text":"data frame one row scenario. Row names scenario codes, e.g. CTN Northern scenario total concentration soil. Columns mostly self-explanatory. rho dry bulk density top soil.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2017.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017","text":"EFSA (European Food Safety Authority) (2017) EFSA guidance document predicting environmental concentrations active substances plant protection products transformation products active substances soil. EFSA Journal 15(10) 4982 doi:10.2903/j.efsa.2017.4982","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/soil_scenario_data_EFSA_2017.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Properties of the predefined scenarios from the EFSA guidance from 2017 — soil_scenario_data_EFSA_2017","text":"","code":"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"},{"path":"https://pkgdown.jrwb.de/pfm/reference/twa.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate a time weighted average concentration — twa","title":"Calculate a time weighted average concentration — twa","text":"moving average built using values past, earliest possible time maximum time series returned one window passed.","code":""},{"path":"https://pkgdown.jrwb.de/pfm/reference/twa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate a time weighted average concentration — twa","text":"","code":"twa(x, window = 21) # S3 method for one_box twa(x, window = 21)"},{"path":"https://pkgdown.jrwb.de/pfm/reference/twa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate a time weighted average concentration — twa","text":"x object type one_box window size moving window","code":""},{"path":[]},{"path":"https://pkgdown.jrwb.de/pfm/reference/twa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate a time weighted average concentration — twa","text":"","code":"pred <- sawtooth(one_box(10), applications = data.frame(time = c(0, 7), amount = c(1, 1))) max_twa(pred) #> $max #> parent #> 0.9537545 #> #> $window_start #> parent #> 0 #> #> $window_end #> parent #> 21 #>"}] diff --git a/man/EFSA_washoff_2017.Rd b/man/EFSA_washoff_2017.Rd index e153fbe..3ec7987 100644 --- a/man/EFSA_washoff_2017.Rd +++ b/man/EFSA_washoff_2017.Rd @@ -9,10 +9,10 @@ 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. \emph{EFSA Journal} \bold{15}(10) 4982 - doi:10.2903/j.efsa.2017.4982 +predicting environmental concentrations of active substances of plant +protection products and transformation products of these active substances +in soil. \emph{EFSA Journal} \bold{15}(10) 4982 +doi:10.2903/j.efsa.2017.4982 } \description{ Subset of EFSA crop washoff default values diff --git a/man/FOCUS_GW_scenarios_2012.Rd b/man/FOCUS_GW_scenarios_2012.Rd index 53d1d3c..302aa75 100644 --- a/man/FOCUS_GW_scenarios_2012.Rd +++ b/man/FOCUS_GW_scenarios_2012.Rd @@ -11,15 +11,15 @@ An object of class \code{list} of length 2. FOCUS_GW_scenarios_2012 } \description{ -Currently, only scenario names with acronyms and a small subset of the soil definitions are provided. The +Currently, only scenario names with acronyms and a small subset of the soil definitions are provided. The soil definitions are from page 46ff. from FOCUS (2012). } \examples{ FOCUS_GW_scenarios_2012 } \references{ -FOCUS (2012) Generic guidance for Tier 1 FOCUS ground water assessments. Version 2.1. - FOrum for the Co-ordination of pesticde fate models and their USe. - http://focus.jrc.ec.europa.eu/gw/docs/Generic_guidance_FOCV2_1.pdf +FOCUS (2012) Generic guidance for Tier 1 FOCUS ground water assessments. Version 2.1. +FOrum for the Co-ordination of pesticde fate models and their USe. +http://focus.jrc.ec.europa.eu/gw/docs/Generic_guidance_FOCV2_1.pdf } \keyword{datasets} diff --git a/man/FOCUS_Step_12_scenarios.Rd b/man/FOCUS_Step_12_scenarios.Rd index 02963bf..fca98e3 100644 --- a/man/FOCUS_Step_12_scenarios.Rd +++ b/man/FOCUS_Step_12_scenarios.Rd @@ -6,9 +6,9 @@ \title{Step 1/2 scenario data as distributed with the FOCUS Step 1/2 calculator} \format{ A list containing the scenario names in a character vector called 'names', - the drift percentiles in a matrix called 'drift', interception percentages in - a matrix called 'interception' and the runoff/drainage percentages for Step 2 - calculations in a matrix called 'rd'. +the drift percentiles in a matrix called 'drift', interception percentages in +a matrix called 'interception' and the runoff/drainage percentages for Step 2 +calculations in a matrix called 'rd'. } \description{ The data were extracted from the scenario.txt file using the R code shown below. diff --git a/man/FOMC_actual_twa.Rd b/man/FOMC_actual_twa.Rd index a0c7284..dd8e4d3 100644 --- a/man/FOMC_actual_twa.Rd +++ b/man/FOMC_actual_twa.Rd @@ -5,8 +5,8 @@ \title{Actual and maximum moving window time average concentrations for FOMC kinetics} \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 +Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1, +18 December 2014, p. 251 } \usage{ FOMC_actual_twa( @@ -36,14 +36,14 @@ be conducted under use conditions.} \item{Koc}{The sorption constant normalised to organic carbon. Gustafson does not mention the nonlinearity of the sorption constant commonly -found and usually described by Freundlich sorption, therefore it is +found and usually described by Freundlich sorption, therefore it is unclear at which reference concentration the Koc should be observed (and if the reference concentration would be in soil or in porewater).} \item{chent}{If a chent is given with appropriate information present in its chyaml field, this information is used, with defaults specified below.} -\item{degradation_value}{Which of the available degradation values should +\item{degradation_value}{Which of the available degradation values should be used?} \item{lab_field}{Should laboratory or field half-lives be used? This @@ -70,7 +70,7 @@ be Koc values at a concentration of 1 mg/L in the water phase.} } \value{ A list with the DT50 and Koc used as well as the resulting score - of class GUS_result +of class GUS_result } \description{ The groundwater ubiquity score GUS is calculated according to diff --git a/man/PEC_soil.Rd b/man/PEC_soil.Rd index e7efd6c..391e25b 100644 --- a/man/PEC_soil.Rd +++ b/man/PEC_soil.Rd @@ -127,16 +127,16 @@ true for the TWA concentrations given for the same example in the EFSA guidance from 2017 (p. 92). According to the EFSA guidance (EFSA, 2017, p. 43), leaching should be - taken into account for the EFSA 2017 scenarios, using the evaluation depth - (here mixing depth) as the depth of the layer from which leaching takes - place. However, as the amount leaching below the evaluation depth - (often 5 cm) will partly be mixed back during tillage, the default in this function - is to use the tillage depth for the calculation of the leaching rate. +taken into account for the EFSA 2017 scenarios, using the evaluation depth +(here mixing depth) as the depth of the layer from which leaching takes +place. However, as the amount leaching below the evaluation depth +(often 5 cm) will partly be mixed back during tillage, the default in this function +is to use the tillage depth for the calculation of the leaching rate. If temperature information is available in the selected scenarios, as - e.g. in the EFSA scenarios, the DT50 for groundwater modelling - (destination 'PECgw') is taken from the chent object, otherwise the DT50 - with destination 'PECsoil'. +e.g. in the EFSA scenarios, the DT50 for groundwater modelling +(destination 'PECgw') is taken from the chent object, otherwise the DT50 +with destination 'PECsoil'. } \examples{ PEC_soil(100, interception = 0.25) @@ -166,22 +166,22 @@ results_pfm_pw <- PEC_soil(100/300 * 0.7 * 1000, interval = 365, DT50 = 250, t_a } \references{ EFSA Panel on Plant Protection Products and their Residues (2012) - Scientific Opinion on the science behind the guidance for scenario - selection and scenario parameterisation for predicting environmental - concentrations of plant protection products in soil. \emph{EFSA Journal} - \bold{10}(2) 2562, doi:10.2903/j.efsa.2012.2562 - - 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. \emph{EFSA Journal} \bold{15}(10) 4982 - doi:10.2903/j.efsa.2017.4982 - - EFSA (European Food Safety Authority) (2015) EFSA guidance document for - predicting environmental concentrations of active substances of plant - protection products and transformation products of these active substances - in soil. \emph{EFSA Journal} \bold{13}(4) 4093 - doi:10.2903/j.efsa.2015.4093 +Scientific Opinion on the science behind the guidance for scenario +selection and scenario parameterisation for predicting environmental +concentrations of plant protection products in soil. \emph{EFSA Journal} +\bold{10}(2) 2562, doi:10.2903/j.efsa.2012.2562 + +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. \emph{EFSA Journal} \bold{15}(10) 4982 +doi:10.2903/j.efsa.2017.4982 + +EFSA (European Food Safety Authority) (2015) EFSA guidance document for +predicting environmental concentrations of active substances of plant +protection products and transformation products of these active substances +in soil. \emph{EFSA Journal} \bold{13}(4) 4093 +doi:10.2903/j.efsa.2015.4093 } \author{ Johannes Ranke diff --git a/man/PEC_sw_drainage_UK.Rd b/man/PEC_sw_drainage_UK.Rd index 98aa868..f3d6169 100644 --- a/man/PEC_sw_drainage_UK.Rd +++ b/man/PEC_sw_drainage_UK.Rd @@ -42,13 +42,13 @@ PEC_sw_drainage_UK(150, Koc = 100) } \references{ HSE's Chemicals Regulation Division (CRD) Active substance - PECsw calculations (for UK specific authorisation requests) - \url{https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/active-substance-uk.htm} - accessed 2019-09-27 +PECsw calculations (for UK specific authorisation requests) +\url{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 - \url{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 +Drainage PECs Version 1.0 (2015) Spreadsheet published at +\url{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 diff --git a/man/PEC_sw_drift.Rd b/man/PEC_sw_drift.Rd index 92e0f77..9fd733e 100644 --- a/man/PEC_sw_drift.Rd +++ b/man/PEC_sw_drift.Rd @@ -26,7 +26,7 @@ PEC_sw_drift( \item{drift_percentages}{Percentage drift values for which to calculate PECsw. 'drift_data' and 'distances' if not NULL.} -\item{drift_data}{Source of drift percentage data. If 'JKI', the [drift_data_JKI] +\item{drift_data}{Source of drift percentage data. If 'JKI', the \link{drift_data_JKI} included in the package is used. If 'RF', the Rautmann formula is used, if implemented for the crop type and number of applications} diff --git a/man/PEC_sw_exposit_drainage.Rd b/man/PEC_sw_exposit_drainage.Rd index 5a543c8..e2294bf 100644 --- a/man/PEC_sw_exposit_drainage.Rd +++ b/man/PEC_sw_exposit_drainage.Rd @@ -5,7 +5,7 @@ \title{Calculate PEC surface water due to drainage as in Exposit 3} \source{ Excel 3.02 spreadsheet available from - \url{https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3} +\url{https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3} } \usage{ PEC_sw_exposit_drainage( @@ -43,12 +43,12 @@ autumn/winter/early spring.} } \value{ A list containing the following components - \describe{ - \item{perc_runoff}{The runoff percentages for dissolved and bound substance} - \item{runoff}{A matrix containing dissolved and bound input for the different distances} - \item{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.} - } +\describe{ +\item{perc_runoff}{The runoff percentages for dissolved and bound substance} +\item{runoff}{A matrix containing dissolved and bound input for the different distances} +\item{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.} +} } \description{ This is a reimplementation of the calculation described in the Exposit 3.02 spreadsheet file, diff --git a/man/PEC_sw_exposit_runoff.Rd b/man/PEC_sw_exposit_runoff.Rd index a415a63..03dbb4b 100644 --- a/man/PEC_sw_exposit_runoff.Rd +++ b/man/PEC_sw_exposit_runoff.Rd @@ -5,7 +5,7 @@ \title{Calculate PEC surface water due to runoff and erosion as in Exposit 3} \source{ Excel 3.02 spreadsheet available from - \url{https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3} +\url{https://www.bvl.bund.de/DE/04_Pflanzenschutzmittel/03_Antragsteller/04_Zulassungsverfahren/07_Naturhaushalt/psm_naturhaush_node.html#doc1400590bodyText3} } \usage{ PEC_sw_exposit_runoff( @@ -45,12 +45,12 @@ and the bound fraction.} } \value{ A list containing the following components - \describe{ - \item{perc_runoff}{The runoff percentages for dissolved and bound substance} - \item{runoff}{A matrix containing dissolved and bound input for the different distances} - \item{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.} - } +\describe{ +\item{perc_runoff}{The runoff percentages for dissolved and bound substance} +\item{runoff}{A matrix containing dissolved and bound input for the different distances} +\item{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.} +} } \description{ This is a reimplementation of the calculation described in the Exposit 3.02 spreadsheet file, diff --git a/man/PEC_sw_focus.Rd b/man/PEC_sw_focus.Rd index f23423b..973b1fa 100644 --- a/man/PEC_sw_focus.Rd +++ b/man/PEC_sw_focus.Rd @@ -26,7 +26,7 @@ PEC_sw_focus( } \arguments{ \item{parent}{A list containing substance specific parameters, e.g. -conveniently generated by [chent_focus_sw].} +conveniently generated by \link{chent_focus_sw}.} \item{rate}{The application rate in g/ha. Overriden when applications are given explicitly} @@ -38,20 +38,20 @@ applications are given explicitly} \item{comment}{A comment for the input file} \item{met}{A list containing metabolite specific parameters. e.g. -conveniently generated by [chent_focus_sw]. If not NULL, +conveniently generated by \link{chent_focus_sw}. If not NULL, the PEC is calculated for this compound, not the parent.} \item{f_drift}{The fraction of the application rate reaching the waterbody via drift. If NA, this is derived from the scenario name and the number of applications via the drift data defined by the -[FOCUS_Step_12_scenarios]} +\link{FOCUS_Step_12_scenarios}} \item{f_rd}{The fraction of the amount applied reaching the waterbody via -runoff/drainage. At Step 1, it is assumed to be 10%, be it the +runoff/drainage. At Step 1, it is assumed to be 10\%, be it the parent or a metabolite} \item{scenario}{The name of the scenario. Must be one of the scenario -names given in [FOCUS_Step_12_scenarios]} +names given in \link{FOCUS_Step_12_scenarios}} \item{region}{'n' for Northern Europe or 's' for Southern Europe. If NA, only Step 1 PECsw are calculated} @@ -86,11 +86,11 @@ to be used with the FOCUS calculator. } \note{ The formulas for input to the waterbody via runoff/drainage of the - parent and subsequent formation of the metabolite in water is not - documented in the model description coming with the calculator. As one would - expect, this appears to be (as we get the same results) calculated by - multiplying the application rate with the molar weight - correction and the formation fraction in water/sediment systems. +parent and subsequent formation of the metabolite in water is not +documented in the model description coming with the calculator. As one would +expect, this appears to be (as we get the same results) calculated by +multiplying the application rate with the molar weight +correction and the formation fraction in water/sediment systems. Step 2 is not implemented. } @@ -107,10 +107,10 @@ PEC_sw_focus(new_dummy, 1000, scenario = "cereals, winter", met = M1) } \references{ FOCUS (2014) Generic guidance for Surface Water Scenarios (version 1.4). - FOrum for the Co-ordination of pesticde fate models and their USe. - http://esdac.jrc.ec.europa.eu/public_path/projects_data/focus/sw/docs/Generic%20FOCUS_SWS_vc1.4.pdf +FOrum for the Co-ordination of pesticde fate models and their USe. +http://esdac.jrc.ec.europa.eu/public_path/projects_data/focus/sw/docs/Generic\%20FOCUS_SWS_vc1.4.pdf Website of the Steps 1 and 2 calculator at the Joint Research - Center of the European Union: - http://esdac.jrc.ec.europa.eu/projects/stepsonetwo +Center of the European Union: +http://esdac.jrc.ec.europa.eu/projects/stepsonetwo } diff --git a/man/SFO_actual_twa.Rd b/man/SFO_actual_twa.Rd index bdf4c4d..1652b82 100644 --- a/man/SFO_actual_twa.Rd +++ b/man/SFO_actual_twa.Rd @@ -5,8 +5,8 @@ \title{Actual and maximum moving window time average concentrations for SFO kinetics} \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 +Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1, +18 December 2014, p. 251 } \usage{ SFO_actual_twa(DT50 = 1000, times = c(0, 1, 2, 4, 7, 14, 21, 28, 42, 50, 100)) diff --git a/man/SSLRC_mobility_classification.Rd b/man/SSLRC_mobility_classification.Rd index 797332b..43de457 100644 --- a/man/SSLRC_mobility_classification.Rd +++ b/man/SSLRC_mobility_classification.Rd @@ -11,7 +11,7 @@ SSLRC_mobility_classification(Koc) } \value{ A list containing the classification and the percentage of the - compound transported per 10 mm drain water +compound transported per 10 mm drain water } \description{ This implements the method specified in the UK data requirements handbook and was @@ -23,13 +23,13 @@ SSLRC_mobility_classification(10000) } \references{ HSE's Chemicals Regulation Division (CRD) Active substance - PECsw calculations (for UK specific authorisation requests) - \url{https://www.hse.gov.uk/pesticides/topics/pesticide-approvals/pesticides-registration/data-requirements-handbook/fate/active-substance-uk.htm} - accessed 2019-09-27 +PECsw calculations (for UK specific authorisation requests) +\url{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 - \url{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 +Drainage PECs Version 1.0 (2015) Spreadsheet published at +\url{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 diff --git a/man/TOXSWA_cwa.Rd b/man/TOXSWA_cwa.Rd index de83ec2..0923f10 100644 --- a/man/TOXSWA_cwa.Rd +++ b/man/TOXSWA_cwa.Rd @@ -94,7 +94,7 @@ Create a TOXSWA_cwa object from a file \if{html}{\out{<a id="method-TOXSWA_cwa-moving_windows"></a>}} \if{latex}{\out{\hypertarget{method-TOXSWA_cwa-moving_windows}{}}} \subsection{Method \code{moving_windows()}}{ -Add to the `windows` field described above. +Add to the \code{windows} field described above. \subsection{Usage}{ \if{html}{\out{<div class="r">}}\preformatted{TOXSWA_cwa$moving_windows(windows, total = FALSE)}\if{html}{\out{</div>}} } @@ -115,7 +115,7 @@ suspended matter will be used.} \if{latex}{\out{\hypertarget{method-TOXSWA_cwa-get_events}{}}} \subsection{Method \code{get_events()}}{ Populate a datataframe with event information for the specified -threshold value. The resulting dataframe is stored in the `events` +threshold value. The resulting dataframe is stored in the \code{events} field of the object. \subsection{Usage}{ \if{html}{\out{<div class="r">}}\preformatted{TOXSWA_cwa$get_events(thresholds, total = FALSE)}\if{html}{\out{</div>}} @@ -136,7 +136,7 @@ suspended matter will be used.} \if{html}{\out{<a id="method-TOXSWA_cwa-print"></a>}} \if{latex}{\out{\hypertarget{method-TOXSWA_cwa-print}{}}} \subsection{Method \code{print()}}{ -Print a `TOXSWA_cwa` object +Print a \code{TOXSWA_cwa} object \subsection{Usage}{ \if{html}{\out{<div class="r">}}\preformatted{TOXSWA_cwa$print()}\if{html}{\out{</div>}} } diff --git a/man/TSCF.Rd b/man/TSCF.Rd index e4cefdc..71cd692 100644 --- a/man/TSCF.Rd +++ b/man/TSCF.Rd @@ -31,7 +31,7 @@ legend("topright", lty = 1:2, bty = "n", } \references{ FOCUS (2014) Generic Guidance for Tier 1 FOCUS Ground Water Assessments. - Version 2.2, May 2014 +Version 2.2, May 2014 Dettenmaier EM, Doucette WJ and Bugbee B (2009) Chemical hydrophobicity and uptake by plant roots. Environ. Sci. Technol 43, 324 - 329 } diff --git a/man/endpoint.Rd b/man/endpoint.Rd index 2b66c21..41c6a24 100644 --- a/man/endpoint.Rd +++ b/man/endpoint.Rd @@ -53,10 +53,10 @@ soil_sorption( \item{redox}{If not NA, are we looking for aerobic or anaerobic data} -\item{value}{The name of the value we want. The list given in the +\item{value}{The name of the value we want. The list given in the usage section is not exclusive} -\item{aggregator}{The aggregator function. Can be mean, +\item{aggregator}{The aggregator function. Can be mean, \code{\link{geomean}}, or identity, for example.} \item{raw}{Should the number(s) be returned as stored in the chent @@ -71,10 +71,10 @@ about precision?} } \value{ The result from applying the aggregator function to - the values converted to a numeric vector, rounded to the - given number of significant digits, or, if raw = TRUE, - the values as a character value, retaining any implicit - information on precision that may be present. +the values converted to a numeric vector, rounded to the +given number of significant digits, or, if raw = TRUE, +the values as a character value, retaining any implicit +information on precision that may be present. } \description{ R6 class objects of class chent represent chemical entities diff --git a/man/max_twa.Rd b/man/max_twa.Rd index 0a8dcca..43ad50e 100644 --- a/man/max_twa.Rd +++ b/man/max_twa.Rd @@ -32,10 +32,10 @@ max_twa(pred_FOMC) } \references{ FOCUS (2006) \dQuote{Guidance Document on Estimating Persistence and - Degradation Kinetics from Environmental Fate Studies on Pesticides in EU - Registration} Report of the FOCUS Work Group on Degradation Kinetics, - EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, - \url{http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics} +Degradation Kinetics from Environmental Fate Studies on Pesticides in EU +Registration} Report of the FOCUS Work Group on Degradation Kinetics, +EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, +\url{http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics} } \seealso{ \code{\link{twa}} diff --git a/man/perc_runoff_exposit.Rd b/man/perc_runoff_exposit.Rd index 0bd2827..a3d19a6 100644 --- a/man/perc_runoff_exposit.Rd +++ b/man/perc_runoff_exposit.Rd @@ -5,18 +5,18 @@ \title{Runoff loss percentages as used in Exposit 3} \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 - \describe{ - \item{Koc_lower_bound}{The lower bound of the Koc class} - \item{dissolved}{The percentage of the applied substance transferred to an - adjacent water body in the dissolved phase} - \item{bound}{The percentage of the applied substance transferred to an - adjacent water body bound to eroding particles} - } +bound to eroding particles, with Koc classes used as row names +\describe{ +\item{Koc_lower_bound}{The lower bound of the Koc class} +\item{dissolved}{The percentage of the applied substance transferred to an +adjacent water body in the dissolved phase} +\item{bound}{The percentage of the applied substance transferred to an +adjacent water body bound to eroding particles} +} } \source{ Excel 3.02 spreadsheet available from - \url{https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html} +\url{https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html} } \description{ A table of the loss percentages used in Exposit 3 for the twelve different Koc classes diff --git a/man/perc_runoff_reduction_exposit.Rd b/man/perc_runoff_reduction_exposit.Rd index 93016b7..b9ea059 100644 --- a/man/perc_runoff_reduction_exposit.Rd +++ b/man/perc_runoff_reduction_exposit.Rd @@ -9,17 +9,17 @@ 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. - \describe{ - \item{dissolved}{The reduction percentage for the dissolved phase} - \item{bound}{The reduction percentage for the particulate phase} - } +\describe{ +\item{dissolved}{The reduction percentage for the dissolved phase} +\item{bound}{The reduction percentage for the particulate phase} +} } \source{ Excel 3.02 spreadsheet available from - \url{https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.html} +\url{https://www.bvl.bund.de/EN/04_PlantProtectionProducts/03_Applicants/04_AuthorisationProcedure/08_Environment/ppp_environment_node.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. +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. } \usage{ perc_runoff_reduction_exposit diff --git a/man/soil_scenario_data_EFSA_2015.Rd b/man/soil_scenario_data_EFSA_2015.Rd index dfad4aa..0e7f374 100644 --- a/man/soil_scenario_data_EFSA_2015.Rd +++ b/man/soil_scenario_data_EFSA_2015.Rd @@ -5,20 +5,20 @@ \alias{soil_scenario_data_EFSA_2015} \title{Properties of the predefined scenarios from the EFSA guidance from 2015} \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. \code{rho} is the dry bulk density of the top soil. +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. \code{rho} is the dry bulk density of the top soil. } \source{ EFSA (European Food Safety Authority) (2015) - EFSA guidance document for predicting environmental concentrations - of active substances of plant protection products and transformation products of these - active substances in soil. \emph{EFSA Journal} \bold{13}(4) 4093 - doi:10.2903/j.efsa.2015.4093 +EFSA guidance document for predicting environmental concentrations +of active substances of plant protection products and transformation products of these +active substances in soil. \emph{EFSA Journal} \bold{13}(4) 4093 +doi:10.2903/j.efsa.2015.4093 } \description{ -Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the -concentration in soil as given in the EFSA guidance (2015, p. 13/14). Also, the +Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the +concentration in soil as given in the EFSA guidance (2015, p. 13/14). Also, the scenario and model adjustment factors from p. 15 and p. 17 are included. } \examples{ diff --git a/man/soil_scenario_data_EFSA_2017.Rd b/man/soil_scenario_data_EFSA_2017.Rd index f6de290..626ada3 100644 --- a/man/soil_scenario_data_EFSA_2017.Rd +++ b/man/soil_scenario_data_EFSA_2017.Rd @@ -5,20 +5,20 @@ \alias{soil_scenario_data_EFSA_2017} \title{Properties of the predefined scenarios from the EFSA guidance from 2017} \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. \code{rho} is the dry bulk density of the top soil. +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. \code{rho} is the dry bulk density of the top soil. } \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. \emph{EFSA Journal} \bold{15}(10) 4982 - doi:10.2903/j.efsa.2017.4982 +EFSA guidance document for predicting environmental concentrations +of active substances of plant protection products and transformation products of these +active substances in soil. \emph{EFSA Journal} \bold{15}(10) 4982 +doi:10.2903/j.efsa.2017.4982 } \description{ -Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the -concentration in soil as given in the EFSA guidance (2017, p. 14/15). Also, the +Properties of the predefined scenarios used at Tier 1, Tier 2A and Tier 3A for the +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. } \examples{ |
