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      <h1>Properties of the predefined scenarios from the EFSA guidance from 2015</h1>

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  <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>

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    <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>

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    <h2 id="examples">Examples</h2>
    <pre class="examples"><div class='input'><span class="comment">## Not run: ------------------------------------</span>
<span class="comment">#   # This is the code that was used to define the data</span>
<span class="comment">#   soil_scenario_data_EFSA_2015 &lt;- data.frame(</span>
<span class="comment">#     Zone = rep(c("North", "Central", "South"), 2),</span>
<span class="comment">#     Country = c("Estonia", "Germany", "France", "Denmark", "Czech Republik", "Spain"),</span>
<span class="comment">#     T_arit = c(4.7, 8.0, 11.0, 8.2, 9.1, 12.8),</span>
<span class="comment">#     T_arr = c(7.0, 10.1, 12.3, 9.8, 11.2, 14.7),</span>
<span class="comment">#     Texture = c("Coarse", "Coarse", "Medium fine", "Medium", "Medium", "Medium"),</span>
<span class="comment">#     f_om = c(0.118, 0.086, 0.048, 0.023, 0.018, 0.011),</span>
<span class="comment">#     theta_fc = c(0.244, 0.244, 0.385, 0.347, 0.347, 0.347),</span>
<span class="comment">#     rho = c(0.95, 1.05, 1.22, 1.39, 1.43, 1.51),</span>
<span class="comment">#     f_sce = c(3, 2, 2, 2, 1.5, 1.5),</span>
<span class="comment">#     f_mod = c(2, 2, 2, 4, 4, 4),</span>
<span class="comment">#     stringsAsFactors = FALSE,</span>
<span class="comment">#     row.names = c("CTN", "CTC", "CTS", "CLN", "CLC", "CLS")</span>
<span class="comment">#   )</span>
<span class="comment">#   save(soil_scenario_data_EFSA_2015, file = '../data/soil_scenario_data_EFSA_2015.RData')</span>
<span class="comment">## ---------------------------------------------</span>

<span class="comment"># And this is the resulting dataframe</span>
<span class="symbol">soil_scenario_data_EFSA_2015</span></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>
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