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

    
    <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>
    

        
    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>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>
    
    <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>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>
    

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

<span class='co'># And this is the resulting dataframe</span>
<span class='no'>soil_scenario_data_EFSA_2015</span></div><div class='output co'>#&gt;        Zone        Country T_arit T_arr     Texture  f_om theta_fc  rho f_sce
#&gt; CTN   North        Estonia    4.7   7.0      Coarse 0.118    0.244 0.95   3.0
#&gt; CTC Central        Germany    8.0  10.1      Coarse 0.086    0.244 1.05   2.0
#&gt; CTS   South         France   11.0  12.3 Medium fine 0.048    0.385 1.22   2.0
#&gt; CLN   North        Denmark    8.2   9.8      Medium 0.023    0.347 1.39   2.0
#&gt; CLC Central Czech Republik    9.1  11.2      Medium 0.018    0.347 1.43   1.5
#&gt; CLS   South          Spain   12.8  14.7      Medium 0.011    0.347 1.51   1.5
#&gt;     f_mod
#&gt; CTN     2
#&gt; CTC     2
#&gt; CTS     2
#&gt; CLN     4
#&gt; CLC     4
#&gt; CLS     4</div></pre>
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    <h2>Contents</h2>
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      <li><a href="#format">Format</a></li>

      <li><a href="#source">Source</a></li>
      
      <li><a href="#examples">Examples</a></li>
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