Technological Progress in Aerial Application of Pesticides - ACS

8 Technological Progress in Aerial Application of Pesticides ROBERT B. EKBLAD U.S. Department of Agriculture, Forest Service, Equipment Development Center, Missoula, MT 59802 JOHN W. BARRY

Downloaded by TUFTS UNIV on June 4, 2018 | https://pubs.acs.org Publication Date: January 16, 1984 | doi: 10.1021/bk-1984-0238.ch008

U.S. Department of Agriculture, Forest Service, Forest Pest Management, Davis, CA 95616

Previous analyses of problems i n applying pesticides to forests by aircraft are b r i e f l y reviewed. Emphasis i s on problems related to meteorological sciences. Several new developments that enhance efforts to minimize d r i f t are described. Models that predict near f i e l d effects of aircraft and mesoscale winds are available. The need for additional efforts to describe flow within canopy and description of conditions for i n e r t i a l deposition on target elements i s outlined. Problems of Wildland

Spraying

Let's begin with a brief review of the problems facing the aerial applicator and how we have organized the problems to solve them. The problems are i l l u s t r a t e d i n figures 1A through Forest spraying presents many problems not found in normal agricultural spraying: • Because of the concentrating effect of mountain valleys and canyons, significant concentrations of insecticides can be carried several miles (Figure 1A). • Instead of f a l l i n g a few feet as in the case of agricultural spraying, forest insecticides must travel 50 to 150 feet v e r t i c a l l y to reach a target. Losses, due to evaporation, become more significant both i n terms of greater d r i f t and loss of insecticide (Figure I B ) . • The dense forest foliage may capture a l l of the insecticide within a few feet, resulting in only one side of the tree being sprayed (Figure 1C). • On the other hand, the drops may be so small that they are deflected around the target by aerodynamic forces (Figure ID). • I f the lateral displacement of the spray i s excessive the applicator cannot predict where i t w i l l reach the forest and has lost effective control of the spray (Figure I E ) . • In his zeal to prevent excessive lateral displacement, the This chapter not subject to U.S. copyright. Published 1984, American Chemical Society

Garner and Harvey; Chemical and Biological Controls in Forestry ACS Symposium Series; American Chemical Society: Washington, DC, 1984.

CHEMICAL AND BIOLOGICAL CONTROLS IN FORESTRY

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applicator may select drops so large that too few numbers of drops are available for effective coverage (Figure IF). It i s d i f f i c u l t to f l y evenly spaced swaths over large, irregular tracts of forest having few roads or identifying boundaries (Figure 1G). Steep slopes present several problems. The actual surface area i s greater than shown on a map; the downhill side of the boom may be 30 feet higher above the trees than the uphill side of the boom. Flight path and direction are limited to terrain contours because the aircraft cannot climb steep slopes (Figure 1H). Rough irregular terrain i s usually associated with steep slopes. If the applicator f l i e s a level path his altitude above the terrain varies continuously; i f instead he follows the terrain, r o l l e r coaster fashion, his speed and application rate vary continuously (Figure I I ) . In an effort to obtain better coverage, the applicator may increase the volume of insecticide carried without giving adequate consideration to the lethal drop size, requiring hundreds of drops to k i l l a larva rather than one drop (Figure U ) . The aircraft wake has a major influence on spray behavior. Small drops are entrained i n this spray cloud and transported i n a manner similar to smoke ring movement. Other larger drops f a l l independently of the vortex but are not readily v i s i b l e . Thus, the applicator may be misled by observing the v i s i b l e cloud (Figure IK). In two hours of morning spraying, weather conditions usually vary from an inversion to neutral or unstable. The applicator may not be aware of these changes(Figure 1L).

An Approach to Organizing These Problems This i s a formidable array of problems, and i t i s a tribute to aerial applicators that they carry on successful spray projects despite these problems and lack of knowledge in some of the areas. We have devised a scheme to allow us to define each part of the problem separately, yet consider a l l parts simultaneously. The effect of a droplet being carried so far away that i t i s essentially beyond the applicator's control i s shown i n Figure 1. Here we have a plot of droplet diameters versus wind speed above the canopy. The shaded area to the l e f t i s where the drops would be carried too far. We have somewhat a r b i t r a r i l y chosen 1,000 feet as too far. in some curcumstances i t would be more and in some less. We see that there i s an area on the right within which the drops can be contained and an area to the l e f t that we want to avoid. Large droplets w i l l not penetrate the canopy (Figure 2 ) . That i s they w i l l be f i l t e r e d out by the f i r s t foliage encountered and cannot be uniformly deposited throughout the


Aerial Application of Pesticides


EKBLAD AND BARRY

DROP DIAMETER -

Figure 2.

MICRON

Drops too large to penetrate canopy.



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canopy. In this case the permissible area i s on the l e f t . The avoided area i s on the right. In Figure 3, we demonstrate the area i n -which sufficient drops are not available to provide adequate coverage. This i s based, of course, on some reasonable amount of total volume of material being delivered. The relationship between -wind speed and drop size for one value of turbulence i s shown i n Figure U. The area where drops w i l l not impinge on the target because the wind speed i s too low and the drops are too small i s shown in Figure 5. In this case the target could be either foliage or insect. In Figure 6 we show a l l of the curves on the same graph. In the center i s an area of useful drop sizes bounded by several areas that are not useful. The range of useful drops can be divided into two classes. The drops on the l e f t side are so small they are principally airborne. Their terminal f a l l i n g velocity i s so low that they are carried wherever the wind and aircraft wake take them. On the right side are the large drops that are affected by a i r movements, but their arrival at the target i s primarily through gravitational settling. This last figure demonstrates an approach to the entire problem of predicting spray behavior where a multitude of factors are involved and must be considered simultaneously. Other factors, such as evaporation, also can be shown by adding another axis or dimension to the graph. What i s also demonstrated i s the complicating fact that the physical behavior of the drops i n the optimum range are governed by two different sets of equations; one for the airborne particles; another for the large particles subject primarily to gravitational settling. This has led to the development of two simulation models: AGDISP and FSCBG. The AGDISP model i s based on actually tracking the motion of discrete particles. The dynamic equations governing the particle trajectory are developed and integrated. The equations include the influence of the aircraft dispersal system configuration, a i r c r a f t wake turbulence, atmospheric turbulence, gravity, and evaporation. The FSCBG model i s based on a line source that i s given an i n i t i a l disturbance by the a i r c r a f t . The line source develops into a spray cloud that i s treated as a t i l t e d Gaussian plume. The equations track the mean position of the plume as well as rate of change of i t s horizontal and v e r t i c a l variance. Evaporation effects are included. Both models can be used independently to track spray from the time of release u n t i l deposition. However, each model has a range within which i t provides the best accuracy and i s the most computationally e f f i c i e n t . To link the two models for a complete picture of potential spray behavior, a coupling code, AGLINE, has been developed.


BARRY



EKBLAD AND

DROP DIAMETER -

Figure k.

MICRON

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Lack of turbulence a f f e c t s d e p o s i t i o n .



C H E M I C A L AND BIOLOGICAL CONTROLS IN FORESTRY

Figure 5 . Drops are deflected around target.

Figure 6.

Envelope of optimum drop size.



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The AGDISP model i s run u n t i l the released material becomes a spray cloud. Then the FSCBG model uses the AGDISP predictions to create a Gaussian plume model. This gives a complete predictive code, accurate from the time of release u n t i l long after the released material can be treated as a cloud. A l l important forces influencing the evolution of the released material are accounted for and the increase i n computer time i s nominal. Again, the two simulation models, AGDISP and FSCBG, can be used independently or jointly with the coupling code, AGLINE. The principal outputs are deposition and d r i f t , but the models can be programmed to give intermediate information on drop velocity, evaporation, flow f i e l d s , and other factors. Inputs to the models describe the a i r c r a f t , nozzle, evaporation rate, meteorology, and biological environment. Obtaining sufficiently accurate model inputs i s as d i f f i c u l t and challenging as developing the models themselves. The inputs are estimated, measured, calculated, or selected. The relationship of the models' inputs and outputs are shown in Figure 7. Major inputs concerning aircraft are fixed wing or helicopter, speed, wing span, weight, wing loading, propeller characteristics, and wake characteristics. The major inputs for the spray system are nozzle, droplet distribution, number of nozzles, location of nozzles, and flow rate. Obtaining an accurate description of the droplet distribution at the aircraft has been d i f f i c u l t . Along with other groups, the USDA Forest Service sponsored the development of a wind tunnel and laser measuring device at the University of California, Davis, Agricultural Engineering Department (Figure 8). We can now routinely measure droplet size distribution at aircraft speeds, as shown i n Figure 9. The major evaporation inputs are temperature, relative humidity, velocity, and evaporation rate. The evaporation rate is estimated from mathematical models; for complex mixtures, solutions, or suspensions, i t i s measured. The Forest Service sponsored a project at Colorado State University s Aerosol Sciences Laboratory to develop a laboratory method to measure droplet evaporation rate. A schematic of the entire system i s shown i n Figure 10. It is controlled by a microprocessor and measures evaporation rate at controlled temperature and humidity while maintaining flow past the droplet at terminal velocity corresponding to i t s changing diameter. An example of results for three different mixtures i s shown i n Figure 11. The AGDISP and FSCBG models accept the following meteorological data: vertical wind speed and direction, temperature p r o f i l e , relative wind speed, turbulence, depth of mixing layer, vertical profile of wind speed, vertical profile of wind direction, effect of canopy, and effect of complex terrain. Information on the biological environment needed for the 1



INPUT



Figure 8 · Wind tunnel with rotary nozzle. WIND TUNNEL. D6-46. back, combo ' · o f 6/0/25-30 35 _ 30 . 25 . 111 CD 20 . Σ 15 . NU


EKBLAD AND BARRY

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Particle size distribution measured i n wind



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Computer s i m u l a t i o n with, crosswind.


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C H E M I C A L A N D BIOLOGICAL CONTROLS IN FORESTRY


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Figure l U . Computer simulation of small drops.





Figure 1 5 . Vertical drop velocity from wake effects.



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models includes details of the forest type, terrain c l a s s i f i c a tion, and pesticide toxicity. The FSCBG model i s the older of the two models and has been described in d e t a i l i n various publications (1). The AGDISP model i s i n the f i n a l stages of development and verification and w i l l be available this f a l l (2). A graphic output of the AGDISP model i s shown i n Figure 12. The t r a j e c t o r y of 300-micrometer d r o p l e t s released from 13 nozzle l o c a t i o n s of a Thrush 600 a i r p l a n e f l y i n g 105 mph at 50 f e e t above the t e r r a i n i s shown i n Figure 12A. The ground d e p o s i t i o n of spray across the a i r c r a f t f l i g h t path i s shown i n Figure 12B.

The same configuration with a 2-mph crosswind i s shown i n Figure 13.

The same c o n f i g u r a t i o n without

a crosswind but

with


150-micrometer droplets, half the diameter of the droplets i n Figure 12 i s given i n Figure ih. This shows the d r o p l e t entrainment i n the wing t i p v o r t i c e s t h a t aggravates the problem of d r i f t . An example of other information that i s available from the model i s the droplet*s v e r t i c a l v e l o c i t y (Figure 15).

We believe the major shortcoming of these models i s inadequate meteorological input. In particular we need better descriptions of flow within the canopy and v e r t i c a l flow profiles generated by drainage flow rather than mesoscale winds. We also need a f u l l y operational three dimensional, complex terrain winds model. In summary, we now have models that account for a l l important forces influencing the dispersion and deposit of aerial sprays. We have estimates of inputs to make the models useful to forest managers. Further improvement i n model results, particularly d r i f t estimation, depends on better meteorological input.

Literature Cited 1.

2.

Dumbauld, R.K., Rafferty, J.E., and Bjourklund, J.R., "Prediction of Spray Behavior Above and Within a Forest Canopy"; special report under contract 19-276. USDA For. Service, Pacific N.W. For. and Range Exp. Sta., Portland, Oreg., and For. Pest Management, Davis, Calif., 1977. Bilanin, A.J., Teske, M.E., and Morris, D.J., "Predicting Aerially Applied Deposition by Computer"; SAE Paper No. 810607, April 1981.

RECEIVED September 9,

1983


Technological Progress in Aerial Application of Pesticides - ACS

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