Predicting Pesticide Volatile Loss Following Application

1. Predicting Pesticide Volatile Loss Following Application Jeffrey J. Jenkins Environmental and Molecular Toxicology Oregon State University

2. wind erosion photodegradation volatilization wind wash off runoff microbial or chemical degradation Plant uptake sorption to soil particles leach toward groundwater Agrochemical Fate Processes

3. Volatilization

4. air soil water K soil particle h Chemical chemical in water in air K d Partitioning between soil compartments(soil, water air) Kh = water/air equilibrium constant Kd = soil/water equilibrium constant

5. x Frederico et. al, Predicting and Measuring Environmental Concentration of Pesticides in Air after Soil Application – JEQ 2003

6. EU Risk Assessment Environmental Fate Modeling - Volatile Loss From Soil

9. Transfer of agrochemicals to the target R. Pontzen, Pflanzenschutz-Nachrichten Bayer 59/2006, 1, p 63-72

10. Spray deposit of thiaclopridon a barley leaf (electron micrograph). R. Pontzen, Pflanzenschutz-Nachrichten Bayer 59/2006, 1, p 63-72

11. Agrochemical Spray deposit on the leaf surface R. Pontzen, Pflanzenschutz-Nachrichten Bayer 59/2006, 1, p 63-72

12. Agrochemical Volatile Loss from Foliar Surfaces

13. Fugacity Approach • Divide the environment into compartments • Chemical partitioning behavior due to Gibbs free energy differences between phases. • Partitioning behavior function of chemical properties and environmental compartment properties. • Compartment boundaries: where chemical transport between phases is at steady-state.

14. Adapted from R. P. Schwarzenbach et al., Science 313, 1072 -1077 (2006) Chemical FateBioavailability Exposure air xxx

15. Fugacity Approach • If a transport mechanism between phases is composed of a series of sequential steps, then • The rate of the entire process can be simplified in terms of the rate-limiting step (slowest rate or “bottleneck”)

16. Finding Fugacity Feasible1 for Pesticide Foliar Volatile Loss • Step 1: Assume a two phase system • (1) pesticide deposit on leaf surface, (2) pesticide in vapor above the deposit • Step 2: Volatile loss - two linked sequential processes • Vaporization/Sublimation – conversion of the pesticide deposit on the leaf to a vapor • Diffusion: transport of the pesticide vapor along a conc. gradient from the leaf surface to the atmosphere 1Mackay, D. 1979. Finding Fugacity Feasible. Environ. Sci. Technol. 13:12181223.

17. Fugacity Approach • Step 3: Determine the rate-limiting step, thereby justifying that volatile loss is a steady-state process. • Vapor pressure measured under conditions of static equilibrium: rate of condensation = rate of volatilization, volatilizing molecules reduce energy of remaining molecules. • At leaf surface, heat demand for evapotranspiration should supply sufficient heat to replenish vapor lost to diffusion (saturation vapor density not rate limiting).

18. Diffusion: Molecular and Eddy • Two generally accepted modes of transport in a fluid such as air: molecular diffusion and turbulent or eddy diffusion. • Molecular diffusion dominants over short distances and in cases when the air is still. • Transport occurs by brownian motion in a direction of decending concentration gradient (-dc/dz). • Movement of a chemical by this mechansim obeys Fick’s law.

19. Boundary Layer of a Flat Leaf Long arrows - originally nonturbulent air (u) Short arrows indicate the laminar sublayer Curved arrows indicate the turbulent region dbl is the effective boundary layer thickness (z)

20. Flux due to Molecular Diffusion Fmol - (ug/m2/hr) flux due to molecular diffusion along the z-axis. Da - (m2/s) molecular diffusion coefficient for a compound in air, Da f(fluid temperature, molar mass, and molar volume). dc/dz - (ug/m2) concentration gradient along the z-axis.

21. Pesticide Volatile Loss from Turfgrass • Simplified case for pesticide volatile loss from plant canopies. • Short height, lack of highly varied microclimate inside the canopy. • Transport mechanisms remain relatively consistent with changing wind speed and temperature. • Amenable to a two-compartment model consisting of the leaf surface and the air above it.

22. Displacement height (d) and roughness length (zO) for short and tall canopies. The roughness length zo determines the depth of the stagnant air layer above the canopy

23. Atmospheric Transport Zones Follows the concentration gradient: Leaf surface to atmosphere Atmospheric deposition to Leaf surface

24. Flux due to Turbulent (Eddy) Diffusion Fturb - (ug/m2/hr) flux due to turbulent diffusion or advection of fluid along the z-axis. E(z) - (m2/s) eddy (turbulent) diffusion coefficient at height z. f(turbulent structure and direction of fluid motion) dc/dz - (ug/m2) concentration gradient of the compound along the z-axis.

25. Atmospheric Boundary: region of air whose properties are affected by features of the surface below Boundary layer formation over a transition in roughness length. The internal boundary layer flow features are affected by the roughness features of the surface. The equilibrated boundary layer has fully adjusted to the roughness features of the surface

26. Theoretical Shape Profile method F0 - (ug/m2/hr) flux of pesticide vapor from the turf grass. cz - (ug/m3) airborne concentration of pesticide vapor at the sampling height, above the turf plot. uz - (m/s) the average cup wind speed at the sampling height during the air sampling interval. Q - normalized horizontal flux (unitless), estimated using the TPS method (Wilson et al, 1982) or the Backward-Time Lagrangian Stochastic Dispersion (BTLSD) method (Flesch et al., 1995); Sampling height chosen to minimize Q error (on the order of 20%)

27. Pendamethalin volatile loss from turfgrass Jenkins et al 1993

28. Plant-air partition coefficient • Log pendamethalin flux (normalized for wind speed) vs. 1/Temperature (K-1) is linear for two days following application (Jenkins et al, 1993). • Results suggest that the plant/air partition coefficient, KPA, varying with temperature, could be the primary factor determining volatile loss over short periods.

29. Plant-air partition coefficient Written in the form of the van 't Hoff equation thatrelates the change in temperature (T) to the change in the equilibrium constant (K) given the standard enthalpy change (ΔH) for the process. KPA is a measure of fugacity for pesticide foliar residues and their and vapor form.

30. KOA as a predictor of KPA • KOA – octanol/air partition coefficient has been used to predict chemical partitioning between foliar surfaces and the surrounding air. • For predicting pesticide volatile loss from foliar surfaces, KOA may be most useful when the pesticide residues are associated with the leaf surface wax layer and no longer volatilizing from self. Under these conditions KOA ~ KPA

31. air air water KOA K “Aged” Surface Deposit “Aged” Surface Deposit Chemical In water chemical In air h Chemical In air Kow K K describes the relationship between pesticide concentration describes the relationship between pesticide concentration h h Source Strength a function of Henry’s Law (Kh) or Octanol-air Partition Coefficient KOA

34. Theoretical Shape Profile method F0 - (ug/m2/hr) flux of pesticide vapor from the turf grass. cz - (ug/m3) airborne concentration of pesticide vapor at the sampling height, above the turf plot. uz - (m/s) the average cup wind speed at the sampling height during the air sampling interval. Q - normalized horizontal flux (unitless), estimated using the TPS method (Wilson et al, 1982) or the Backward-Time Lagrangian Stochastic Dispersion (BTLSD) method (Flesch et al., 1995); Sampling height chosen to minimize Q error (on the order of 20%)

35. Volatile Loss From Turfgrass as Percent Applied

37. Herbicides Commonly Used in Oregon OSU Extension Pesticide Properties Database EM 8709

38. Dicamba-amine complexes diglycolamine dimethylamine 1:1 complex – strongly hydrogen-bonded amine-benzoic acid adducts. Vapor pressure: dicamba acid >> dimethylamine >> diglycolamine. Dissociation of dicamba-amine complex not well characterized, likely pH dependent.