Real-time particle monitoring of pesticide drift from an axial fan airblast orchard sprayer

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Abstract

In Washington State, a majority of reported pesticide-related illnesses and application-related complaints involve drift. We employed real-time particle monitors (Dylos) during a series of experimental spray events investigating drift. Sections of an orchard block were randomly sprayed by an axial fan airblast sprayer, while monitors sampled particulate matter above and below the canopy at various downwind locations. We found elevated particle mass concentrations (PMC) at all distances (16–74 m). The 75th percentile PMC while spraying was significantly greater than the control periods by 107 (95% CI 94–121) μg/m3, after adjusting for sampler height and wind speed. The 75th percentile PMC below the canopy was significantly greater than above the canopy by 9.4 (95% CI 5.2–12) μg/m3, after adjusting for spraying and wind speed. In a restricted analysis of the spray events, the 75th percentile PMC significantly decreased by 2.6 (95% CI −3.2 to −1.7) μg/m3 for every additional meter away from the edge of the spray quadrant, after adjusting for canopy height and wind speed. Our results were consistent with a larger study that performed passive sampling during the same spray events, suggesting that real-time monitoring can be used as a screening tool for pesticide drift. Compared with traditional methods of drift sampling, real-time monitoring is overall an easily employed, affordable sampling technique, and it can provide minute-by-minute measurements that can be coupled with meteorological measurements to better understand how changes in wind speed and direction affect drift.

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Acknowledgements

This study would not have been possible without the Pacific Northwest Agricultural Safety and Health (PNASH) field team’s (Pablo Palmandez, Maria Negrete, Maria Tchong-French, Jane Pouzou, Jose Carmona, Ryan Babadi, Christine Perez Delgado) expertise and time on this project. We would also like to thank Gwen A. Hoheisel from the Center for Precision & Automated Agricultural Systems at Washington State University (WSU) for her contribution to the design of this study. The WSU Tree Fruit Research & Extension Center, Washington Tree Fruit Research Commission and Vine Tech & Equipment were also involved in the logistics of this study. This study was supported by the University of Washington’s (UW) Department of Environmental & Occupational Health Sciences (DEOHS), including their Pacific Northwest Agricultural Safety and Health (PNASH) Center (CDC/NIOSH Cooperative Agreement #5 U54 OH007544), Medical Aid and Accident Fund Initiative, Award Number 5P30 ES007033-23 from the National Institute of Environmental Health Sciences, Award Number 83618501-0 from the US Environmental Protection Agency and Russel L. Castner Endowed Student Research Fund. UW’s Graduate Opportunities Minority Achievement Program (GO-MAP) also supported this study.

Funding

This research would not have been possible without the support of the Graduate Opportunities and Minorities Achievement Program (GO-MAP); the University of Washington’s Department of Environmental and Occupational Health Sciences (DEOHS); the Pacific Northwest Agricultural Safety and Health Center (PNASH; CDC/NIOSH Cooperative Agreement #5 U54 OH007544); the DEOHS Washington Medical Aid and Accident Fund (MAAF) Award; and the Russel L. Castner Endowed Student Research Fund.

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Correspondence to Magali N. Blanco.

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Blanco, M.N., Fenske, R.A., Kasner, E.J. et al. Real-time particle monitoring of pesticide drift from an axial fan airblast orchard sprayer. J Expo Sci Environ Epidemiol 29, 397–405 (2019) doi:10.1038/s41370-018-0090-5

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Keywords

  • Pesticides
  • Particulate matter
  • Environmental monitoring
  • Exposure modeling
  • Empirical models
  • Statistical models

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