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Wind tunnel experiment and regression model for spray drift
College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China.
Faculty of Science, The University of Queensland, Brisbane 4343, Australia.
College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China.
College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing 210037, China.
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2015 (Chinese)In: Transactions of the Chinese Society of Agricultural Engineering, ISSN 1002-6819, Vol. 31, no 3, 94-100 p.Article in journal (Refereed) Published
Abstract [en]

With greater environmental awareness, the movement of pesticides within and off of a spray target area is acritical public concern. Ideally, all of the material applied should be deposited within the targeted swath on the intendedpest or plant. But realistically, a portion of the spray remains airborne and is carried downwind to non-target areas.Airborne spray leaving the targeted area reduces the applied dosage, and could cause damage to neighboring plant andwater source or other detrimental environmental impacts. To study the influences of nozzle type, spray mixture and windspeed on spray drift, experiments were conducted using a wind tunnel. Spray drift risk was assessed by adding a tracer tothe spray mixture and measuring the quantities of spray deposited downwind from the nozzle on horizontal polythenelines with 2 mm diameter perpendicular to the wind direction in a vertical and a horizontal array. At a distance of 2 mdownwind from the static nozzle, five collector lines (V1 to V5) were positioned one above the other at the spacing of0.1 m to provide an estimate of the spray still airborne through this vertical profile. An additional five sampling collectorstrings (H1 to H5) were placed in a horizontal array with one-meter horizontal spacing at 0.1 m height to determine thefallout volumes and gradients of the spray from 2 to 6 m downwind. A water-soluble fluorescent tracer was dissolvedinto tap water as the spray liquid, and after the experiments, the collecting lines were washed with deionized water tomeasure deposit and drift. The results indicated that deposits on sampling collector decreased with increased verticalelevation and horizontal distance. Average fallout and airborne deposit resulting from the different spray applicationswere shown in the paper. These figures showed the expected fallout and airborne profiles for all tested nozzle types andsizes. The highest fallout deposits were measured at a position closest to the nozzle (H1) with a systematic decrease withthe distance from the nozzle. The highest airborne deposits were found at the lowest sampling collector (V1) with asystematic decrease with increasing height above the wind tunnel floor. Airborne spray drift was affected by wind speed.At all sample positions, deposits on collectors were reduced at lower wind speed. Nozzle’s structure was also found toinfluence droplet’s size, so injector/pre-orifice nozzle produced coarser droplets and reduced spray drift. The amount ofspray recovered is based on the amount of active ingredient of spray mixture within each droplet rather than the totaldroplet volume. On that basis, a multiple non-linear model for statistical drift prediction including four independent,non-correlated variables (target distance, wind speed, nozzle type and chemical type) was established. The regressionmodel provided a drift evaluation approach, and it was important in the interpretation of wind tunnel data for differentnozzle types, chemical types and sampling methodologies.

Place, publisher, year, edition, pages
Beijing, China: Chinese Society of Agricultural Engineering , 2015. Vol. 31, no 3, 94-100 p.
Keyword [en]
wind tunnels; spraying; nozzles; sampling collector; wind speed; chemical type; spray drift model
National Category
Agricultural Science Other Engineering and Technologies not elsewhere specified Probability Theory and Statistics
URN: urn:nbn:se:umu:diva-106893DOI: 10.3969/j.issn.1002-6819.2015.03.013ScopusID: 2-s2.0-84925854162OAI: diva2:845586
Available from: 2015-08-12 Created: 2015-08-12 Last updated: 2015-12-17Bibliographically approved

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Yu, Jun
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