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authorJohannes Ranke <jranke@uni-bremen.de>2016-09-27 23:00:48 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2016-09-27 23:00:48 +0200
commit12a31f4c130c551f82232d9ef7dfb608bd52c53f (patch)
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parent0d958ab6f84b569b5437f231c56004890c4ae23b (diff)
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-<title>soil_scenario_data_EFSA_2015. pfm 0.3-7</title>
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-
- <h1>Properties of the predefined scenarios from the EFSA guidance from 2015</h1>
-
-<div class="row">
- <div class="span8">
-
- <div class="Format">
- <h2>Format</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>
-
- </div>
-
- <div class="Source">
- <h2>Source</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>
-
- </div>
-
- <div class="Description">
- <h2>Description</h2>
-
- <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>
-
- <h2 id="examples">Examples</h2>
- <pre class="examples"><div class='input'>## Not run:
-# # This is the code that was used to define the data
-# soil_scenario_data_EFSA_2015 &lt;- data.frame(
-# Zone = rep(c(&quot;North&quot;, &quot;Central&quot;, &quot;South&quot;), 2),
-# Country = c(&quot;Estonia&quot;, &quot;Germany&quot;, &quot;France&quot;, &quot;Denmark&quot;, &quot;Czech Republik&quot;, &quot;Spain&quot;),
-# 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(&quot;Coarse&quot;, &quot;Coarse&quot;, &quot;Medium fine&quot;, &quot;Medium&quot;, &quot;Medium&quot;, &quot;Medium&quot;),
-# 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(&quot;CTN&quot;, &quot;CTC&quot;, &quot;CTS&quot;, &quot;CLN&quot;, &quot;CLC&quot;, &quot;CLS&quot;)
-# )
-# save(soil_scenario_data_EFSA_2015, file = &#39;../data/soil_scenario_data_EFSA_2015.RData&#39;)
-# ## End(Not run)
-
-# And this is the resulting dataframe
-soil_scenario_data_EFSA_2015
-</div>
-<div class='output'> 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
-</div></pre>
- </div>
- <div class="span4">
- <!-- <ul>
- <li>soil_scenario_data_EFSA_2015</li>
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