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# A model of volatilization and subsequent dry deposition of pesticides to surface waters

Carole Bedos, Benjamin Loubet, Izzedine Sameut Bouhaik, Amir Ali Feiz, Enrique Barriuso

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Carole Bedos, Benjamin Loubet, Izzedine Sameut Bouhaik, Amir Ali Feiz, Enrique Barriuso. A model of volatilization and subsequent dry deposition of pesticides to surface waters. XIV Symposium on Pesticide Chemistry, Aug 2011, Piacenza, Italy. hal-04464336

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# A MODEL OF VOLATILIZATION AND SUBSEQUENT DRY DEPOSITION OF PESTICIDES TO SURFACE WATERS

BEDOS C.¹, LOUBET B.¹, SAMEUT BOUHAIK A., FEIZ A.¹, BARRIUSO E.¹

¹ INRA, Environment and Arable Crops Research Unit, F-78850, Thiverval-Grignon, France
e-mail: carole.bedos@grignon.inra.fr

## INTRODUCTION

* Contamination of surface waters by pesticides is widespread near agricultural areas (as in lakes, rivers, etc.).

* Dry deposition of volatilized pesticides (gaseous) may be higher than the drift mainly due to longer emission periods.

* Volatilization from soil depends on the thermodynamical properties of the pesticide (e.g. Henry's law constant), its persistence in the soil, environmental conditions (soil and air temperature, soil water content and soil organic matter) and agricultural practices.

* Dry deposition depends on atmospheric concentrations of the pesticide and hence on the volatilization rate, environmental conditions, distance from the source and pesticides characteristics, as well as the nature of the surface (water, plant, soil).

* In this study we use 2 models to estimate 1) the volatilization and 2) the local dispersion and dry deposition of pesticides to water bodies at the local scale (<1 km).

## MATERIAL AND METHODS

The approach couples 2 models (Figure 1):

* a mechanistic model for pesticide volatilization following application on bare soil (Volt'Air-Pesticides, Bedos et al., 2009) which gives the source strength and the surface boundary layer characteristics to

* a local-scale dispersion and deposition model (FIDES-2D, Loubet et al., 2001), adapted for pesticides (Sameut, 2010). Dry deposition to water is modeled using the resistance analogy approach (Liss and Slater, 1974 further applied to pesticides by Asman et al. 2003)

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$$R_b = \frac{1}{0.066 \cdot Sc_g^{-0.61} \cdot u_*}$$

$$R_{surf} = \frac{H(T_{\text{soil}})}{1.25 \cdot 10^{-6} \cdot \sqrt{600 / Sc_w} \cdot U(10)^{1.6}}$$

$R_b$ (s m⁻¹) : surface boundary layer resistance

$R_{surf}$ (s m⁻¹) : surface resistance

$Sc_g$ and $Sc_w$ : Schmidt numbers in air and water

$u$ (m s⁻¹) : friction velocity

$H$ : Henry's law constant

$T_{\text{water}}$ : water temperature

$U(10)$ (m s⁻¹) : wind speed at 10 m above ground

$$H = P_{\text{vap}} / S_w$$

A set of five pesticides were chosen to cover a wide range of chemical and physical properties, especially H, as a key property for the theoretical volatilization and deposition potential (Table 1).

The model was run over 13 days, from March 1, 2002 to March 13, 2002.

The soil and climatic conditions of the Picardie region in France was chosen.

The field was 100 m long and the application dose was 1 kg ha⁻¹.

<figure><img src="image_3.png" /><figcaption>Figure 1: Coupling Volt'Air-Pesticides and FIDES</figcaption></figure>

<table><caption>Table 1: Thermodynamic characteristics and surface resistances of the selected pesticides</caption><thead><tr><th>Substance</th><th>Henry's law constant H [-]</th><th>Vapour pressure P<sub>vap</sub> [Pa]</th><th>Water solubility S<sub>W</sub> [mg L<sup>-1</sup>]</th><th>Koc [m<sup>2</sup> kg<sup>-1</sup>]</th><th>DT50 soil [day]</th><th>R<sub>surf</sub> [s m<sup>-1</sup>]</th><th>R<sub>surf</sub> / R<sub>b</sub> [-]</th></tr></thead><tbody><tr><td>Bentazone</td><td>2.00E-13</td><td>1.70E-04</td><td>570</td><td>0.051</td><td>14.0</td><td>2.06E-3</td><td>2.22E-05</td></tr><tr><td>Ethofumesate</td><td>9.00E-08</td><td>6.50E-04</td><td>50</td><td>0.147</td><td>56.0</td><td>2.15E-2</td><td>2.31E-04</td></tr><tr><td>Acetochlor</td><td>8.64E-09</td><td>2.20E-05</td><td>282</td><td>0.156</td><td>12.1</td><td>1.31E-1</td><td>1.41E-03</td></tr><tr><td>Chlorothalonil</td><td>1.36E-05</td><td>7.60E-05</td><td>0.81</td><td>0.850</td><td>44.0</td><td>7.61E-1</td><td>8.18E-03</td></tr><tr><td>Fenpropimorph</td><td>5.50E-05</td><td>3.90E-03</td><td>4.32</td><td>2.401</td><td>25.5</td><td>8.95E-0</td><td>9.62E-02</td></tr></tbody></table>

## MAIN RESULTS

* The drift at 250 m amounted around 0.15% of the applied dose (Rautmann et al., 2001).

* The modelled dry deposition of Acetochlor, Chlorothalonil, and Fenpropimorph roughly amounted to 0.5%, 1% and 2%.

* The modelled gaseous dry deposition to water bodies was larger than the drift for 3 of the 5 pesticides (Figure 2).

* Under simulated conditions, and for the selected pesticides, the surface resistance to water $R_{surf}$ was negligible when compared to the water boundary layer resistance $R_b$ (Table 1).

* Under these conditions, the main driver of the dry deposition was therefore the atmospheric concentration and hence the volatilization rate.

## PERSPECTIVES

* This study should be extended to a larger range of conditions to check when $R_{surf}$ is negligible against $R_b$.

* Scenarios should be built to cover a large range of environmental conditions and pesticides.

* Running the model on these scenarios will allow quantifying surface water contamination by gaseous pesticides.

* These scenarios will be used to identify good agricultural practices to limit surface water contamination.

## LIMITATIONS

* Such a modelling study needs to be validated against experimental datasets.

* Volatilization from crop surfaces should also be considered in the future.

<figure><img src="image_4.png" /><figcaption>Figure 2: Cumulated dry deposition after 13 days and cumulated drift deposition of pesticides onto water. Curves are normalized by the amount of pesticides applied (1 kg ha⁻¹). The drift curve is from Rautmann et al. (2001).</figcaption></figure>

## REFERENCES

* Asman W., Jørgensen A., Jensen P. (2003) – Technical Report, Danish Environmental Protection Agency.

* Bedos C., Génermont S., LeCadre E., Barriuso E., Cellier P. (2009) – Atmos. Env., 43, 3630-3669.

* Bedos C., Loubet B., Feiz A., Barriuso E. (2010) – Progress Report, Onema project, 96 p.

* Liss P.S., Slater P.G. (1974) – Nature, 247, 181-184.

* Loubet B., Milford C., Sutton M. A., Cellier P. (2001) – JGR Atmospheres, 106, 24183-24195.

* Sameut Bouhaik A. (2010) – Internship Report, 39 p.

* Rautmann D., Streloke M., Winkler R. (2001) – Mittl. Biol. Bundesanst. Land- Forstwirtsch, 383, 133-141.

## ACKNOWLEDGEMENTS

The authors wish to thank the "Conseil Régional de Picardie" (regional council) and the French Ministries in charge of Environment and Agriculture who founded the PHAR project as well as the French National Institute for Industrial Environment and Risks (Ineris), especially A. Gouzy, who managed the project.

They also wish to thank the Office National de l'Éau et des Milieux Aquatiques, Onema (Onema – Inra 2010) for their contribution to the CEPAG Project.