Response of spray drift from aerial applications at a forest edge to atmospheric stability

Miller, David R.; Stoughton, Thomas E.

doi:10.1016/s0168-1923(99)00084-2

Cited by 31 publications

(16 citation statements)

References 8 publications

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“…Good agreement was demonstrated between the measurements and predictions of drift from a semi-dwarf apple orchard at full-dose application rates. LIDAR systems have been used successfully to observe spray dispersion in stable [22] and unstable atmospheric conditions [26]. The technique has also been used for monitoring dispersion of smoke from forest fires [27].…”

Section: Introductionmentioning

confidence: 99%

Use of a Terrestrial LIDAR Sensor for Drift Detection in Vineyard Spraying

Gil

Llorens

Casamada

et al. 2013

Sensors

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The use of a scanning Light Detection and Ranging (LIDAR) system to characterize drift during pesticide application is described. The LIDAR system is compared with an ad hoc test bench used to quantify the amount of spray liquid moving beyond the canopy. Two sprayers were used during the field test; a conventional mist blower at two air flow rates (27,507 and 34,959 m3·h−1) equipped with two different nozzle types (conventional and air injection) and a multi row sprayer with individually oriented air outlets. A simple model based on a linear function was used to predict spray deposit using LIDAR measurements and to compare with the deposits measured over the test bench. Results showed differences in the effectiveness of the LIDAR sensor depending on the sprayed droplet size (nozzle type) and air intensity. For conventional mist blower and low air flow rate; the sensor detects a greater number of drift drops obtaining a better correlation (r = 0.91; p < 0.01) than for the case of coarse droplets or high air flow rate. In the case of the multi row sprayer; drift deposition in the test bench was very poor. In general; the use of the LIDAR sensor presents an interesting and easy technique to establish the potential drift of a specific spray situation as an adequate alternative for the evaluation of drift potential.

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Section: Introductionmentioning

confidence: 99%

Use of a Terrestrial LIDAR Sensor for Drift Detection in Vineyard Spraying

Gil

Llorens

Casamada

et al. 2013

Sensors

View full text Add to dashboard Cite

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“…Significant contributions to the understanding of transition flows come from field experiments, which cover various aspects including flow adjustments and growth of the equilibrium layer at a transition (Bradley, 1968;Gash, 1986;Kruijt et al, 1995;Irvine et al, 1997;Flesch and Wilson, 1999a;Breugel et al, 1999;Morse et al, 2002), tree sway and wind loading (Gardiner, 1995;Flesch and Wilson, 1999b), static pressure distribution and effects (Nieveen et al, 2001), and the advection of scalars at a forest edge (Miller and Stoughton, 2000). Although most field measurements support established theories for the development of an IBL and an EL, the reported fetch factors for achieving equilibrium and flow adjustment rates are not consistent.…”

Section: Introductionmentioning

confidence: 99%

Large-eddy Simulation of Turbulent Flow Across a Forest Edge. Part I: Flow Statistics

Yang

Raupach

Shaw

et al. 2006

Boundary-Layer Meteorol

114

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The statistics of turbulent flow across a forest edge have been examined using large-eddy simulation, and results compared with field and wind-tunnel observations. The moorland-to-forest transition is characterized by flow deceleration in the streamwise direction, upward distortion of the mean flow, formation of a high pressure zone immediately in front of the edge, suppression of the standard deviations and covariance of velocity components, and enhancement of velocity skewnesses. For the selected forest density, it is observed that the maximum distortion angle is about 8 degrees from the horizontal. Instead of approaching a downwind equilibrium state in a monotonic manner, turbulence (standard deviations and covariances of velocity components) and mean streamwise velocity undershoot in the transition zone behind the edge. Evolution of flow statistics clearly reveals the growth of an internal boundary layer, and the establishment of an equilibrium layer downwind of the edge. It is evident that lower-order moments generally adjust more quickly over the new rough surface than do higher-order moments. We also show that the streamwise velocity standard deviation at canopy height starts its recovery over the rough surface sooner than does the vertical velocity standard deviation, but completes full adjustment later than the latter. Despite the limited domain size upstream of the edge, large-eddy simulation has successfully reproduced turbulent statistics in good agreement with field and wind-tunnel measurements.

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“…In another study [12], a scanning lidar system was used to obtain the backscatter coefficients of aerosols emitted by a pig farm. Lidar technology has also been applied in spray drift studies to assess the dynamics of aerially released pesticides [13][14][15], to study the influence of atmospheric stability over spray dispersal [16,17], and to quantify the spray plume concentration [18]. High correlations between lidar and collector measurements of spray drift have been obtained in recent studies [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Polarization Lidar Detection of Agricultural Aerosol Emissions

et al. 2018

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Agricultural aerosol emissions can significantly impact human and animal health as well as the environment. Therefore, it is essential to adopt new sensing techniques for real-time monitoring these emissions in high temporal and spatial resolution. In recent years, light detection and ranging (lidar) technology has been used for measuring the particulate matter emitted from agricultural operations. However, conventional nonpolarized lidar systems cannot discriminate between different types of aerosols, which can lead to misinterpretation of the results. To overcome this limitation, this study applies the polarization lidar technique to monitor agricultural aerosols. A 355 nm polarization lidar system was used to measure the emissions generated during pesticide spraying operations. The results showed that depolarization ratios due to field dust (0.220-0.268) and to road dust (0.385) are clearly higher than those caused by pesticide spray drift (0.028-0.043) or by diesel exhaust (0.099), which can be used to differentiate each type of aerosol. These results support the development of new polarization lidar systems specifically designed to study the impact of agricultural activities on air quality.

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Response of spray drift from aerial applications at a forest edge to atmospheric stability

Cited by 31 publications

References 8 publications

Use of a Terrestrial LIDAR Sensor for Drift Detection in Vineyard Spraying

Use of a Terrestrial LIDAR Sensor for Drift Detection in Vineyard Spraying

Large-eddy Simulation of Turbulent Flow Across a Forest Edge. Part I: Flow Statistics

Polarization Lidar Detection of Agricultural Aerosol Emissions

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