Transactions of the ASABE

Vol. 54(2): 403-408 � 2011 American Society of Agricultural and Biological Engineers ISSN 2151-0032 403

DRIFT FROM FIELD CROP SPRAYERS USING AN INTEGRATED APPROACH:RESULTS OF A FIVE‐YEAR STUDY

D. Nuyttens, M. De Schampheleire, K. Baetens, E. Brusselman, D. Dekeyser, P. Verboven

ABSTRACT. Spray drift continues to be a major problem in applying agricultural pesticides. This article summarizes the resultsof a five‐year study of drift from field crop sprayers using a unique integrated approach. Indirect (spray quality and windtunnel measurements) and direct (field) drift experiments were performed, and drift models were developed to study the effectof spray application technique, droplet characteristics, buffer zones, meteorological conditions, spray liquid properties,border structures, and crop characteristics on drift from field crop sprayers. It was found that indirect drift measurements canbe a valuable alternative to field drift experiments. A validated 3‐D computational fluid dynamics (CFD) mechanistic driftmodel was developed, which can be used for a systemic study of different influencing factors. This model was reduced to afast 2‐D diffusion advection model, which is useful as a hands‐on drift prediction tool. From the experiments as well as fromthe models, the fraction of small droplets and the spray boom height were found to be the most influential spray applicationfactors. Moreover, meteorological conditions as well as crop characteristics have an important effect on the amount of spraydrift, which can be reduced significantly using intercepting screens or buffer zones. From this study, drift protocols, data, andmodels are made available, which help to understand and reduce the complex phenomena of spray drift.

Keywords. Drift mitigation, Drift model, Field crop sprayer, Spray application technology, Spray drift.

pray drift from agricultural pesticides can causecrop protection chemicals to be deposited in unde‐sirable areas. This can have serious consequences,such as damage to sensitive adjoining crops (Byass

and Lake, 1977; Yates et al., 1978; Reddy et al., 2010), dam‐age to susceptible off‐target areas (Kleijn and Snoeijing,1997; Marrs and Frost, 1997), environmental contamination,illegal pesticide residues, pesticide resistance (Londo et al.,2010), lower yield results (Kjaer et al., 2006), and health risksto animals (Longley and Sotherton, 1997; de Snoo and deWit, 1998; Otto et al., 2009) and people (Rull et al., 2009;Butler Ellis et al., 2010). The above concerns are why spraydrift and risks connected with application of pesticides inagriculture are receiving increased attention from the generalpublic as well as the scientific community.

Submitted for review in August 2010 as manuscript number PM 8718;approved for publication by the Power & Machinery Division of ASABEin March 2011. Presented at the 2010 ASABE Annual Meeting as Paper No.1009541.

The authors are David Nuyttens, ASABE Member Engineer,Post‐Doctoral Agricultural Engineer, Technology and Food Science Unit -Agricultural Engineering, Institute for Agricultural and Fisheries Research(ILVO), Merelbeke, Belgium; Mieke De Schampheleire, Chemist,Department of Crop Protection, Ghent University, Ghent, Belgium;Katrijn Baetens, Biologist, Department of Biosystems, CatholicUniversity of Leuven, Leuven, Belgium; Eva Brusselman, AgriculturalEngineer, and Donald Dekeyser, Agricultural Engineer, Technology andFood Science Unit-Agricultural Engineering, ILVO, Merelbeke, Belgium;and Pieter Verboven, Post‐Doctoral Agricultural Engineer, Department ofBiosystems, Catholic University of Leuven, Leuven, Belgium.Corresponding author: David Nuyttens, Technology and Food ScienceUnit-Agricultural Engineering, Institute for Agricultural and FisheriesResearch (ILVO), Burg. Van Gansberghelaan 115, bus 1, 9820 Merel-beke, Belgium; phone: +32‐9‐272‐27‐82; e‐mail: david.nuyttens@ilvo.vlaanderen.be.

Drift from pesticides is affected by many factors, such asweather conditions (Craig et al., 1998; Miller et al., 2000;Thistle, 2000), spray liquid properties (Reichard et al., 1996;Combellack et al., 1996; Lan et al., 2008), drift interceptingstructures (Davis et al., 1994; Raupach et al., 2001; Lazzaroet al., 2008), spray application technique (Ozkan et al., 1997;Teske and Thistle, 1999; Sidahmed et al., 2004), and sprayquality (Fietsam et al., 2004; Yarpuz‐Bozdogan and Bozdo‐gan, 2009). Many spray drift studies have been performed us‐ing indirect (Bayat and Bozdogan, 2005; Guler et al., 2007;Qi et al., 2008) and direct drift measurements (Ravier et al.,2005; Wolters et al., 2008, Rimmer et al., 2009) as well asdrift models (Holterman et al., 1997; Smith et al., 2000;Teske et al., 2002, 2009; Wang and Rautmann, 2008) .

Because of the importance of spray drift and its complex‐ity (Gil and Sinfort, 2005), a five‐year research project wasconducted focusing on drift and drift reduction from fieldcrop sprayers and using an integrated approach. This articlesummarizes the results of this study, which was a collabora‐tion between the Institute for Agricultural and Fisheries Re‐search (ILVO), Ghent University, and Catholic University ofLeuven.

MATERIALS AND METHODSIn this project, indirect drift experiments (spray quality

and wind tunnel measurements) and direct drift experiments(in the field) were performed, and drift models were devel‐oped in an integrated approach. For the experiments as wellas the models, a reference spray application was defined asa Hardi ISO F 110 03 standard flat‐fan nozzle at a pressure of3.0 bar with a boom height and nozzle distance of 0.50 m anda driving speed of 8 km h‐1 (180 L ha‐1) on grassland. Theseconditions were used for a comparative assessment of the dif‐

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404 TRANSACTIONS OF THE ASABE

ferent factors related to spray drift. The driving speed andgrassland condition were only applicable for the field mea‐surements and the drift models. The effects of spray applica‐tion technology, spray liquid properties, meteorologicalconditions, border structures, crop characteristics, and bufferzones on drift from field crop sprayers were studied.

INDIRECT DRIFT ASSESSMENT METHODS

Indirect drift measurement were performed with differentnozzle types (standard flat fan, low drift, and air inclusion),sizes (ISO 02, 03, 04, and 06), and spray pressures (2.0, 3.0,and 4.0 bar) (Nuyttens et al., 2007a, 2009a, 2009b). Sprayquality measurements (droplet size and droplet velocity) ofthe different nozzle and pressure combinations were mea‐sured using an Aerometrics phase Doppler particle analyzer(Aerometrics, Inc., Sunnyvale, Cal.), as described in detailby Nuyttens et al. (2006, 2007a, 2007b, 2009a). Surface ten‐sion, viscosity, evaporation rate, and density of different for‐mulation types were measured to evaluate the effect of sprayliquid properties on drift (De Schampheleire et al., 2009a).Wind tunnel experiments were carried out in the Silsoe Re‐search Institute wind tunnel facility (Wrest Park, Silsoe, Bed‐ford, U.K.) (Nuyttens et al., 2009b) and the Ghent Universitywind tunnel (De Schampheleire et al., 2009a, 2009b) to mea‐sure drift fallout and airborne drift deposits.

DIRECT DRIFT ASSESSMENT METHOD

Field drift measurements to measure absolute drift valuesunder field conditions for different spraying techniques andweather conditions were carried out as described by Nuyttenset al. (2007b) according to ISO Standard 22866 (ISO, 2005).A validated drift prediction equation was set up to predict thepercentage of spray drift on grassland for the reference sprayapplication as a function of meteorological conditions (windspeed, temperature, and humidity). Other authors have con‐firmed the effect of temperature, humidity (Goering and But‐ler, 1975; Smith et al., 1982), and wind speed (Maybank et al.,1978; Phillips and Miller, 1999) on spray drift.

Using this equation, drift results for other spraying tech‐niques and conditions were compared with the referencespray application, taking into account variations in weatherconditions and expressed in terms of drift reduction potential.Various spray application factors were evaluated, such asspray boom height (0.30, 0.50, and 0.75 m), air assistance,nozzle type (standard flat fan, low drift, and air inclusion) andsize (ISO 02, 03, 04, and 06), spray pressure (2.0, 3.0, and4.0�bar), and driving speed (4, 6, 8, and 10 km h‐1). The samenozzle and pressure combinations were tested as for the indi‐rect drift assessment methods.

With the reference spray application technique, artificialborder structures with different heights (1.0, 1.5, and 2 m) andscreen open areas (16%, 36%, and 63%) and a row of Fagussylvatica trees with a height of 1.5 m (LAI = 1.12 m2 m‐2)were tested (De Schampheleire et al., 2009b) as well as dif‐ferent crop types (potatoes, wheat, grassland, and unculti‐vated). Figure 1 illustrates the indirect (spray quality andwind tunnel) and direct (field) experiments.

COMPARISON BETWEEN INDIRECT AND DIRECT DRIFT

ASSESSMENT METHODS

Measuring the proportion of the total volume of dropletssmaller than 75 �m diameter was best suited to represent the

Figure 1. (top to bottom) Spray quality, wind tunnel, and field drift experi‐ments.

drift reduction potential in the field with different nozzle andpressure combinations. This was followed by the wind tunnelapproach and numerically integrating the measured falloutdeposit curve. Based on these indirect drift measurementsand the statistical drift prediction equation for the referencespray application from the direct drift assessments (Nuyttenset al., 2007b), it was possible to obtain a realistic estimate offield drift data at a driving speed of 8 km h‐1 and a boom

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height of 0.50 m. Both wind tunnel approaches measuringairborne drift were less suited to represent the field drift re‐duction potential of different nozzle and pressure combina‐tions. Hence, droplet size measurements, as well as windtunnel experiments measuring fallout spray deposits, aresuitable for relative assessments of sedimenting drift riskwith different spray qualities, but it is difficult to investigateeffects such as driving speed, boom height, and air assistancewith these indirect drift assessment methods (Nuyttens,2007; Nuyttens et al., 2010).

DRIFT MODELS3‐D COMPUTATIONAL FLUID DYNAMICS MODEL

A validated 3‐D computational fluid dynamics (CFD)mechanistic drift model was developed, which calculates theindividual droplet track as a function of atmospheric, field,and operating conditions. This model was used to systemati‐cally study the effect of spray application technology, sprayliquid properties, meteorological conditions, crop character‐istics, and buffer zones, and was reported by Baetens et al.(2007) and Baetens (2009). The model consists of two sub‐models, an airflow model (Blocken et al., 2007) and a particletracking model, which are reciprocally coupled. The model'saccuracy was validated with the field drift experiments.

2‐D DIFFUSION ADVECTION MODEL

The 3‐D CFD mechanistic drift model was reduced to afast, comprehensive, and accurate 2‐D diffusion advection

Figure 2. Visualizations of the (top) 3‐D computational fluid dynamicsmodel (Baetens et al., 2007) and (bottom) 2‐D diffusion advection model(Baetens et al., 2009).

model (fig. 2), which can be a useful hands‐on drift predictiontool (Baetens et al., 2009). This model was calibrated basedon simulations with the 3‐D CFD model and validated withthe field drift experiments. The reduced‐order model demon‐strated the distinct and combined effects of important vari‐ables affecting drift, such as boom height, wind speed, andnozzle type. The model showed that the effect of droplet di‐ameter distribution on the amount of drift can be evaluatedby a single parameter, i.e., the volume fraction of small drop‐lets, which corresponds with the conclusions of the drift mea‐surements. As the model is about 104 faster than the 3‐D CFDmodel, it has a high potential for use as a hands‐on drift pre‐diction tool while providing meaningful relationships for ex‐plaining the observed effects.

RESULTS AND DISCUSSIONUsing the integrated approach described above, the effect

of spray application technology, spray liquid properties, me‐teorological conditions, border structures, crop characteris‐tics, and buffer zones on drift from field crop sprayers wasstudied, as reported in detail by Baetens et al. (2007, 2009),De Schampheleire et al. (2008, 2009a, 2009b), and Nuyttenset al. (2007a, 2007b, 2007c, 2009b, 2010).

SPRAY APPLICATION TECHNOLOGY

Larger nozzle tips, lower spray pressures, and lower sprayboom heights significantly reduced spray drift, which is inaccordance with results of Derksen et al. (1999) and Teskeand Thistle (1999). The effect of driving speed was ratherlimited within the tested speed range from 4 to 10 km h‐1, al‐though there was a general trend for an increase in spray driftwith increasing travel speed, as confirmed by Miller andSmith (1997) and van de Zande et al. (2005).

Concerning nozzle types, air‐inclusion nozzles have thehighest drift reduction potential, followed by low‐driftnozzles and standard flat‐fan nozzles (Baetens et al., 2007;De Schampheleire et al., 2008; Nuyttens et al., 2007b,2009b). Drift results were linked with droplet size, as well asdroplet velocity characteristics of the sprays. In accordancewith Sidahmed (1996) and Sidahmed et al. (1999), a clearrelationship between droplet size and velocity was found.Drift values decreased with increasing values of droplet di‐ameter and droplet velocity characteristics, and increasedwith increasing percentages of small droplets. The propor‐tion of the total volume of small droplets was the best indica‐tor for establishing the amount of sedimenting spray driftfound in the field, explaining about 94% of the total variationin drift values (Baetens et al., 2009; Nuyttens et al., 2007b,2010). Other researchers also found droplet size to be one ofthe most influential factors related to drift (Bird et al., 1996;Carlsen et al., 2006) and considered droplets smaller than 75�m (Hobson et al., 1993), 150 �m (Combellack et al., 1996),or 200 �m (Bouse et al., 1990; Zhu et al., 1994; Baetens et al.,2009) to be the most drift‐prone.

Air assistance reduced spray drift and had the highest im‐pact for the finer sprays by increasing droplet velocities(Nuyttens et al., 2007c). The observed drift reduction poten‐tials were generally lower than the values found in the litera‐ture (Piché et al., 2000a, 2000b; van de Zande et al., 2000)because the experiments were carried out on a flat mowedmeadow, which is different from a developed crop.

406 TRANSACTIONS OF THE ASABE

SPRAY LIQUID PROPERTIESDynamic surface tension was the major spray liquid factor

that determined drift. The addition of a polymer drift retar‐dant significantly reduced drift by increasing the spray liquidviscosity. Drift reduction was found to be less effective withspray liquids of emulsifiable and suspendable formulationtypes than with spray liquids of water‐dispersible granulesand powders (De Schampheleire et al., 2009a).

METEOROLOGICAL CONDITIONSThe important effect of meteorological conditions on the

amount of near‐field sedimenting spray drift was quantifiedfrom the drift models and the field drift experiments. De‐creasing wind speed and temperature and increasing absolutehumidity decreases the amount of spray drift (Baetens et al.,2007; Nuyttens et al., 2007b).

BORDER STRUCTURES

Artificial border structures with different heights (1.0, 1.5,and 2 m) and screen open areas (16%, 36%, and 63%) and arow of Fagus sylvatica trees with a height of 1.5 m (LAI =1.12 m2 m‐2) were tested (De Schampheleire et al., 2009b).The type of border structure, as well as screen open area andscreen height, had an important effect on the amount of spraydrift. It was found that total drift reductions from about 40%to 85% could be achieved using border structures. The high‐est overall drift reduction was found with a 1.5 m artificialscreen with a 16% open area, which corresponds with thefindings of Lazarro et al. (2008). This confirms that the bor‐der structure must be sparse enough to allow some particlesto flow through and be trapped (Raupach et al., 2001). In gen‐eral, the drift deposition at short distances ranging from 0 to2 m behind the natural hedge was higher than deposition be‐hind artificial structures. Conversely, peaks in depositionwere not created behind this natural hedge at greater down‐wind distances. With the natural border structure, a total driftreduction percentage of around 60% was found (De Scham‐pheleire et al., 2009b).

CROP CHARACTERISTICS

All experiments were performed at a constant boomheight of 0.50 m above the crop. Under these conditions, cropheight had an important effect on drift values because of itseffect on boom height above the soil (Baetens, 2009). Driftvalues when spraying wheat or potatoes were 150% and250% higher, respectively, compared with grassland. On theother hand, spraying uncultivated land resulted in drift valuesthat were about 50% higher compared with spraying grass‐land because of the absence of the effect of canopy filteringand interception (Hoffman, 2006). From the drift models, thedifferences were less pronounced, but the same trends werefound.

BUFFER ZONES

Based on the drift curves of the different evaluated sprayapplication techniques, average drift reductions of 32%,48%, 65%, and 81% were found, respectively, for buffer zonewidths of 1, 2, 5, and 10 m. These average values are usefulto estimate the overall effect of the introduction of bufferzones on drift contamination in a certain area.

CONCLUSIONSThis project resulted in drift measuring protocols and ad‐

vanced measuring techniques, a unique drift database usefulfor spray drift risk assessments, and spray drift models. Wedeveloped measures to minimize the negative effects of sprayapplications on the environment. The results indicated thatindirect drift measurements can be a valuable alternative tofield drift experiments. These measures will raise farmer'sand manufacturer's awareness of good agricultural practices.

The experiments and the models revealed the most in‐fluential spray application factors to be the fraction of smalldroplets and the spray boom height. Meteorological condi‐tions and crop characteristics significantly affect the amountof spray drift. Drift can be greatly reduced by using intercept‐ing screens or buffer zones. The protocols, data, and modelsnow available will help to further understand and reduce thecomplex phenomenon of spray drift. This information isavailable for manufacturers, farmers, and policymakers.

ACKNOWLEDGEMENTS

This research was funded by the Flemish Agency for In‐novation through Science and Technology (IWT‐Vlaan-deren).

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