Abstract:
University of Washington Abstract Real-Time Particle Monitoring of Pesticide Drift from Two Different Orchard Sprayers Magali N. Blanco Chair of Supervisory Committee: Professor Richard A. Fenske Department of Environmental & Occupational Health Sciences Pesticide drift from agricultural spraying is a significant public health concern, affecting workers and surrounding communities. In Washington State, a majority of pesticide-related illnesses and application-related complaints involve drift. This study employed real-time particle monitors to characterize off-target spray drift during a series of orchard spray trials. The study was nested within a larger study that used micronutrients as tracers, and both active and passive sampling methods. Sections of an orchard block were randomly sprayed by alternating two orchard spray technologies – axial fan airblast (AFA) and multi-head fan tower (MFT) – while ten Dylos DC1100 Pro real-time particle counters sampled aerosols generated by the sprayers from various locations in a neighboring block, ranging from 0-122 meters (0-400 ft) downwind. Two meteorological stations collected wind speed, wind direction, temperature and relative humidity throughout the study period. Measurable aerosol drift levels were found at all downwind sampling locations for both sprayers. Significantly greater drift was associated with the AFA than the MFT sprayer below the canopy and at closer distances. Controlling for wind speed and height, the 75th drift percentiles were 123.5 and 43.3 µg/m3 for the AFA and MFT sprayers respectively. Independent of sprayer type and wind speed, the 75th drift percentiles were 29.3 and 17.7 µg/m3 above and below the canopy respectively. In a restricted analysis looking at spray periods and controlling for sprayer type, wind speed and height, every additional foot (0.305 m) away from the sprayer was associated with 0.1 µg/m3 of reduced drift. These results were consistent with results determined by passive sampling methods. Our findings indicate that real-time particle monitoring for pesticide aerosols can serve as an accurate and relatively inexpensive approach to characterizing pesticide drift. URI http://hdl.handle.net/1773/40103