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<img src="" class="logo" alt=""><h1>Properties of the predefined scenarios from the EFSA guidance from 2017</h1>
<small class="dont-index">Source: <a href="https://github.com/jranke/pfm/blob/HEAD/R/soil_scenario_data_EFSA_2017.R" class="external-link"><code>R/soil_scenario_data_EFSA_2017.R</code></a></small>
<div class="d-none name"><code>soil_scenario_data_EFSA_2017.Rd</code></div>
</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
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>
</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>
</div>
<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="va">soil_scenario_data_EFSA_2017</span></span></span>
<span class="r-out co"><span class="r-pr">#></span> Zone Country T_arit T_arr Texture f_om theta_fc rho f_sce f_mod</span>
<span class="r-out co"><span class="r-pr">#></span> CTN North Estonia 5.7 7.6 Coarse 0.220 0.244 0.707 1.4 3</span>
<span class="r-out co"><span class="r-pr">#></span> CTC Central Poland 7.4 9.3 Coarse 0.122 0.244 0.934 1.4 3</span>
<span class="r-out co"><span class="r-pr">#></span> CTS South France 10.2 11.7 Medium 0.070 0.349 1.117 1.4 3</span>
<span class="r-out co"><span class="r-pr">#></span> CLN North Denmark 8.0 9.2 Medium 0.025 0.349 1.371 1.6 4</span>
<span class="r-out co"><span class="r-pr">#></span> CLC Central Austria 9.3 11.3 Medium 0.018 0.349 1.432 1.6 4</span>
<span class="r-out co"><span class="r-pr">#></span> CLS South Spain 15.4 16.7 Medium 0.010 0.349 1.521 1.6 4</span>
<span class="r-out co"><span class="r-pr">#></span> FOCUS_zone prec</span>
<span class="r-out co"><span class="r-pr">#></span> CTN Hamburg 639</span>
<span class="r-out co"><span class="r-pr">#></span> CTC Hamburg 617</span>
<span class="r-out co"><span class="r-pr">#></span> CTS Hamburg 667</span>
<span class="r-out co"><span class="r-pr">#></span> CLN Hamburg 602</span>
<span class="r-out co"><span class="r-pr">#></span> CLC Châteaudun 589</span>
<span class="r-out co"><span class="r-pr">#></span> CLS Sevilla 526</span>
</code></pre></div>
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