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Spray drift: impact of requirements to protect the environment
Crop Protection 19 (2000) 623}627
Spray drift: impact of requirements to protect the environment A.J. Hewitt Stewart Agricultural Research Services, Inc., P.O. Box 509, Macon, MO 63552, USA
Abstract Spray drift studies in the US have evaluated the e!ects of application, meteorological and tank mix variables on spray drift. The data have been incorporated into models to predict drift from aerial applications, and to evaluate worst-case drift from ground rig (boom) and orchard airblast applications. An atomisation model has also been developed to predict droplet size for applications of tank mixes with user-de"ned or reasonable worst-case physical properties through a wide range of hydraulic nozzles applicable to aerial applications. The database and models help provide the exposure risk input to risk assessments for developing appropriate labelling based on exposure and toxicity risk to non-target sensitive areas. This needs to be balanced with allowing crop protection using careful risk/bene"t assessments. Bu!ers or no spray zones may be based on spray quality, release height and other variables such as wind speed where necessary for protecting speci"c sensitive areas. The impact of protection measures aimed at minimising the incidence and impact of spray drift is discussed in the present paper. 2000 Elsevier Science Ltd. All rights reserved. Keywords: Spray drift; Deposition; Pesticide; Label; Droplet size; Risk assessment
1. Introduction The US National Coalition On Drift Minimisation (NCODM) considers pesticide drift to be the movement of pesticide through the air at the time of pesticide application or soon thereafter from the target site to any non- or o!-target site, excluding pesticide movements by erosion, migration, volatility, or wind-blown soil particles after application. EPA considers drift a concern because it can a!ect human health and the environment; it can cause pesticide exposure to farm workers, children playing outside, and wildlife and its habitat, or contaminate a home garden or crops, causing illegal pesticide residues and/or plant damage (EPA, 1999). EPA is most concerned with protecting aquatic environments from drift. Spray drift is a signi"cant concern in the US, with thousands of reported complaints every year (EPA, 1999). The atomisation, transport and deposition of sprays are generic phenomena that can be modelled based on tank mix physical properties, atomiser type and operation, air #ow "elds and other parameters. However, the e!ect of a given amount of active ingredient is product and species-speci"c (Hewitt et al., 2000). Thus, the risk assessment process includes generic processes for exposure and product/species speci"c toxicity assessments. The present paper explains the development of databases and models on spray drift deposition, and their use
and impact when used for labelling and regulatory activities in the US.
2. Spray drift task force studies In the 1980s, EPA de"ned data requirements for the registration of over 2000 existing and future pesticides. These requirements included the provision of data on spray drift and atomisation droplet size spectra. Several registrant companies decided to conduct the necessary studies jointly, so formed the spray drift task force (SDTF). There are currently 40 member companies in the SDTF. The studies have been completed and submitted to EPA, and subjected to an extensive review procedure by scientists from government, academic and industrial sources who had not been involved in the studies. Although not common in many European countries, aerial spray applications are widely used for the rapid treatment of large and/ or inaccessible areas in the US. Therefore, the SDTF database includes extensive analyses of the factors a!ecting drift from aircraft. The development of the aerial application database was described in detail by Hewitt et al. (2000). The use of this database for development and veri"cation of a spray drift deposition model, AgDRIFT威, was described by Teske et al. (2000a) and Bird et al. (2000). The SDTF ground rig studies were
0261-2194/00/$ - see front matter 2000 Elsevier Science Ltd. All rights reserved. PII: S 0 2 6 1 - 2 1 9 4 ( 0 0 ) 0 0 0 8 2 - X
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A.J. Hewitt / Crop Protection 19 (2000) 623}627
summarised by Hewitt et al. (2001). Details of the orchard and chemigation studies have not been published, although the droplet/size spectra for these applications were described by Hewitt et al. (1996, 1999). The SDTF aerial "eld studies involved 180 "eld trials, half with the same application equipment to provide a standard treatment for comparison with a paired variable treatment. Comparisons of the standard treatment from this covariate approach revealed the e!ect of meteorological variables such as wind speed, temperature and relative humidity on drift, while the variable treatments revealed the e!ects of the application, tank mix and canopy variables on drift. The studies showed that spray quality, boom height and wind speed were most important in a!ecting drift from aerial spraying. The SDTF 46 ground rig studies involved applications of sprays through four nozzle types (producing Fine, Medium, Coarse and Very Coarse sprays) with two boom heights (51 and 127 cm) at di!erent wind speeds. Most of the wind speeds were between 16 and 35 km/h, which caused wind speed not to be identi"ed statistically as a major variable a!ecting o!-target deposition rates. However, a wind speed trend of lower drift at lower wind speeds was evident from the entire SDTF database. Other studies (e.g. Ganzlemeier et al., 1995) have shown that at lower wind speeds, wind speed is a signi"cant variable a!ecting drift. Another reason why wind speed did not have a signi"cant e!ect on the SDTF ground rig studies, but was identi"ed as important for the aerial studies and for studies conducted elsewhere was that the "rst sample distance for the SDTF "eld studies was 8 m from the edge of the "eld. For aerial applications where the release height is greater than ground applications, 8 m is su$ciently close to reveal near-"eld trends. However, for ground applications where boom heights are lower than most aerial applications, signi"cant di!erences in deposition rates might be expected at near-"eld distances. While the SDTF drift studies did not evaluate deposition rates at distances very close to the edge of the "eld (i.e. (8 m), they did measure drift at extended distances up to 792 m from the edge of the "eld, twice as far as many previous drift studies. Analyses of the SDTF ground rig database showed that at least two spray quality groupings ("ne and medium- very coarse) (BCPC/ ASAE spray quality schemes, Anon, 1999, Southcombe et al., 1997) could be paired with each of the boom heights for drift assessments (Hewitt et al., 2001). The SDTF orchard airblast studies showed that canopy characteristics such as tree height and tree row volume had important e!ects on drift. Three sprayers were evaluated, all producing "ne to medium sprays (#owweighted mean D values of 92}173 lm and spray volume in droplets (141 lm"36}75%, Hewitt et al., 1999). Given the small range of droplet size assessments and the importance of canopies in intercepting sprays
that were released within canopy (as opposed to abovecanopy for the aerial and ground applications), droplet size did not have a major e!ect on spray drift for the SDTF orchard studies. If escaping from the canopy, smaller droplets would be expected to have greater drift potential as with other application types. For such droplets, the e!ective release height and wind speed might also be important. The o!-target movement of smaller droplets was seen in the SDTF studies with dormant apple trees. The SDTF studies showed that most drift occurs from the most downwind swath that is sprayed. Therefore, swath adjustment is an important drift reduction strategy. Up to two swaths are sometimes not sprayed to compensate for higher wind speeds and/ or "ner spray applications with aerial equipment (Kidd, 1994). In orchard applications, signi"cant decreases in drift potential occur when not spraying the outside row on the downwind orchard side. Spray release height and the use of end guns were major factors a!ecting drift in the SDTF chemigation studies. Chemigation sprinklers generally produce extra coarse sprays (Anon, 1999), so droplet size is not a major factor a!ecting drift of such sprays. A review of the SDTF and other aerial drift studies was provided by Bird et al. (1996).
3. Spray modeling Hewitt (2000) described the SDTF AgDRIFT威 and DropKick威 models. AgDRIFT威 (Teske et al., 2000a) is a Lagrangian model that can predict o!-target deposition rates for user-de"ned aerial application conditions. It is based on a previous model, AGDISP, developed by the US Department of Agriculture (USDA) Forest Service (Bilanin et al., 1989), NASA and US Army. AgDRIFT威 was developed under a co-operative research and development agreement by the SDTF, EPA and USDA. The Canadian Pesticide Management Regulatory Agency (PMRA) has also been involved in the development of AgDRIFT威, and was one of the "rst regulatory agencies to commence use of the model for pesticide risk assessment and registration purposes. AgDRIFT威 is structured as a three-tiered model, with higher tier levels o!ering greater options for speci"cation of the various input variables. Tier I was developed as the primary risk exposure level, where the major variables that could be considered for labelling are included: spray quality for aerial applications, spray quality (version 2.0 of model) and boom height for ground rig applications, and canopy type for orchard airblast applications. The risk exposure process at Tier I is based on reasonable worst-case values for the model inputs. If the output from this analysis is too restrictive (e.g. if the suggested bu!er zones are excessively large, or if the default inputs such as
A.J. Hewitt / Crop Protection 19 (2000) 623}627
wind speed are too restrictive), then a tier II analysis can be conducted giving access to more input variables. Tier III allows access to all inputs, for investigations. AgDRIFT威 1.0 (Teske et al., 1997) includes generic deposition curves for ground rig and orchard airblast applications at all tier levels. Attempts will be made to include predictive models for these applications at a future time, to expand the range of conditions encompassed. The SDTF also developed a model to estimate spray quality produced by many agricultural nozzles at a wide range of aerial application operating conditions with di!erent tank mixes. This model, DropKick威 (Esterly, 1998; Hermansky, 1998) is linked with the AgDRIFT威 model to expand the options for inputting spray quality to the assessments. DropKick威 is dynamic since it o!ers considerable scope for modi"cation as additional data become available for modelling the relationship between atomisation and tank mix physical properties. Recent insights into the breakup of emulsion sheets (Butler Ellis et al., 1999; Dexter, 2001) may facilitate enhancements in predictions if such e!ects are signi"cant in atomisation and drift processes. AgDRIFT威 and DropKick威 are not the only models that can predict spray drift and atomisation, respectively. Other models are available such as the Forest Service/NASA/US Army model AGDISP and the Forest Service models AGDISP (Bilanin et al., 1989) and SpraySafe Manager威 (developed jointly with the New Zealand Forest Research Institute, Ray et al., 1998). For modelling atomisation, it should be noted that some nozzle types and uses are beyond the range covered by DropKick威. For example, since the initiation of the SDTF studies, a new range of nozzles was introduced by CP Products, Inc. (Mesa, Arizona). These include de#ector and solid stream variable setting nozzles where the user selects the most appropriate de#ector and ori"ce size for his application. The USDA has measured droplet size spectra for various CP nozzle settings and developed predictive models for aerial use conditions (Kirk, 1997, 1998). The USDA Forest Service has decided to incorporate the major components from AGDISP and FSCBG into a version of AgDRIFT威 that will include three standard tiers (Teske et al., 1997) and two additional tiers (Tier II/FS and Tier III/FS) (Teske, 1999). Many other groups are also considering AgDRIFT威 and other models for their own applications. The incorporation of extensive atomisation databases into future modelling activities has been facilitated through the development of a conversion between spray measurement systems o!ered by Particle Measurement Systems optical array probe and Malvern laser di!raction instruments (Teske et al., 2000b). AgDRIFT威 currently includes libraries of atomisation data measured by the SDTF. The addition of libraries such as those of the
625
Forest Service would provide alternative droplet size data sources to those of the current library, DropKick model and worst-case spray quality options.
4. Extending SDTF databases and models The SDTF databases included assessments of drift from reasonable worst-case conditions, as well as analyses of a few drift mitigation options such as the use of coarser sprays, lower release heights and shorter boom lengths. However, the studies did not include an in-depth investigation of drift reduction techniques, and mostly excluded evaluations of the e!ects of drift control adjuvants and specialised sprayers such as `low drifta nozzles and electrostatic systems. Such systems have been evaluated elsewhere (e.g. Carlton et al., 1995; Piggott and Matthews, 1999), and will continue to be evaluated for drift reduction capabilities by researchers from academia, the USDA and elsewhere. Some possible drift reduction techniques such as wing tip sails have been investigated for drift reduction potential using theoretical considerations (Parkin and Spillman, 1980), point-vortex calculations (Teske and Valcore, 1999) and "eld evaluations (Ho!man, 1999). Drift reduction options that are already adequately covered by some models include assessments of drop size, release height and meteorological e!ects within appropriate limits. Current limits might be extended through the conduct of appropriate studies. Electrostatic systems have been tested in the "eld (Carlton et al., 1995), while `low drifta nozzles can be tested in wind tunnels (Walklate et al., 1998).
5. Risk assessment and labelling Risk assessment (Anon, 1983) involves using the available information on exposure risk (e.g. from AgDRIFT威) and toxicity to speci"c non-target sensitive organisms. A balance is needed between obtaining good pest control and e$cacy while providing adequate environmental protection from the agricultural chemicals being applied. Hewitt (1997) described the con#ict often encountered with droplet size in agricultural spraying * smaller droplets are often the most e$cacious and may o!er better coverage, but also are generally more prone to drift under unfavourable conditions. The local environmental risk assessment for pesticides (LERAP) (Gilbert, 2000) in the UK allows bu!ers to be reduced when meeting certain requirements for drift reduction technology, water body speci"cations and/ or dose rates. Similar schemes are considered in other countries in Europe. Several researchers have recognised the importance of barriers for reducing spray drift (e.g. literature review by Ucar and Hall, 1999). EPA acknowledges the importance of such measures, as shown by the following list of
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A.J. Hewitt / Crop Protection 19 (2000) 623}627
possible drift reduction requirements in its drift fact sheet: `Restrictions may include prohibiting the use of certain pesticides under certain conditions; prohibiting certain methods of application; requiring use of a foliage barrier; or requiring a bu!er zone distance between the site of application and areas to be protecteda (EPA, 1999). Such restrictions may or may not appear on new pesticide labels. A discussion of future labels was given by Hewitt (2000). Drift management options that may be speci"ed on many new labels include spray quality, release height and wind speed restrictions. De"nitions of sensitive areas are being discussed in the US. 6. Impact of measures to prevent drift Considerable debates have taken place in the US and other countries on approaching drift management. On the one hand, the regulatory position is often biased toward not allowing any spray drift with considerations of label language such as `do not allow drifta. On the other extreme, bu!ers are sometimes seen as completely unacceptable in any form. Large bu!ers are not desirable because they result in a loss of land that can be protected from pests and diseases, while some bu!er size might be needed to protect certain sensitive areas. Where necessary, bu!ers should be based on scienti"c assessments using reasonable assumptions and the best available data and/or models. The impact of zero drift tolerance could be signi"cant. In its fact sheet on spray drift, EPA acknowledges that drift is an almost inevitable occurrence with any spray application. This is explained as follows: `We recognise that some degree of drift of spray particles will occur from nearly all applicationsa (EPA, 1999). The fact sheet explains that all available steps must be taken to avoid spray drift where the label or regulations prohibit such drift; however, it also explains that `EPA uses its discretion to pursue violations based on the unique facts and circumstances of each drift situationa (EPA, 1999). It is interesting to note that di!erent states in the US have historically had di!erent opinions and regulations for spray drift. In the future, there will hopefully be more consistency in the way that drift is addressed in di!erent areas; however, it is recognised that some geographical areas may pose unique considerations for drift management. It is hoped that measures to minimise or prevent drift will provide incentive for applications to be made using the best available equipment and with careful observation of application practices such as spray release position and local environmental and meteorological conditions. Acknowledgements Thanks are due to all involved in minimising the incidence and impact of drift described in this paper. In
particular, thanks are due to the SDTF and NCODM for data and activities for the goal of a!ording protection to the environment using the best available science, while ensuring the vital provision of crop protection for adequate food supplies.
References Anon, 1983. National research council, committee of the institutional means for assessment of risk to public health. Risk assessment in the federal government: managing the process. National Academy Press, Washington, DC. Anon, 1999. S572, Spray nozzle classi"cation by droplet spectra, American Society of Agricultural Engineers, Niles, MI. Bilanin, A.J., Teske, M.E., Barry, J.W., Ekblad, R.B., 1989. AGDISP: the aircraft spray dispersion model, code development and experimental validation. Trans. ASAE 32, 327}334. Bird, S.L., Esterly, D.M., Perry, S.G., 1996. O!-target deposition of pesticides from agricultural aerial spray applications. J. Environ. Quality 25, 1095. Bird, S.L., Perry, S.G., Ray, S., Teske, M.E., 2000. An evaluation of AgDRIFT 1.0 for use in aerial applications. J. Env. Toxicology and Chemistry, submitted for publication. Butler Ellis, M.C., Tuck, C.R., Miller, P.C.H., 1999. Dilute emulsions and their e!ect on the breakup of the liquid sheet produced by #at-fan spray nozzles. Atomization Sprays 9 (4), 385}398. Carlton, J.B., Bouse, L.F., Kirk, I.W., 1995. Electrostatic charging of aerial spray over cotton. Trans. ASAE 38 (6), 1641}1645. Dexter, R., 2001. Fluid properties and spray quality. In: Viets, A.K., Tann, R.S., Mueningho!, J.C. (Eds.), Pestic. Formulations and Appl. Syst.: 20th Vol., STP 1400. American Society for Testing & Materials, West Conshohocken, PA. EPA, 1999. Spray drift of pesticides. EPA Publication No.735F99024, Environmental Protection Agency, Washington, DC. Esterly, D.M., 1998. Neural network analysis of spray drift task force DROPKICK II2+. ASAE Paper 981014. Ganzlemeier, H., Rautmann, D., Spangenberg, R., Streloke, M., Herrmann, M., Wenzelburger, H., Walter, H., 1995. Studies on the spray drift of plant protection products. Blackwell Wissenschafts-Verlag GmbH Berlin/Wien. Gilbert, A.J., 2000. Local environmental risk assessment for pesticides (LERAP) in the UK. Aspects Appl. Biol. 57, 83}90. Hermansky, C., 1998. A regression model for estimating spray quality from Nozzle, Application Physical Property Data. Proceedings of the ILASS-Americas, 1998, Sacramento, CA, 60}64. Hewitt, A.J., 1997. The importance of droplet size in agricultural spraying. Atomiz. Sprays 7 (3), 235}244. Hewitt, A.J., 2000. Spray drift modelling, labelling and management in the US Aspects Appl. Biol. 57. Hewitt, A.J., Valcore, D.L., Bryant, J.E., 1996. Spray drift task force atomization droplet size spectra measurements. Proceedings of the ILASS-Americas 96. Hewitt, A.J., Valcore, D.L., Young, B., 1999. Measuring spray characteristics for agricultural orchard airblast sprayers, Proceedings ILASS-Americas, Indianapolis, IN. Hewitt, A.J., Johnson, D.R., Fish, J.D., Hermansky, C.G., Valcore, D.L., 2000. The development of the spray drift task force database on pesticide movements for aerial agricultural spray applications. J. Env. Toxicology and Chemistry, submitted for publication. Hewitt, A.J., Valcore, D.L., Barry, T., 2001. Analyses of equipment, meteorology and other factors a!ecting drift from applications of sprays by ground rig sprayers, Pestic. Formulations & Appl. Syst.: 20th Vol., STP 1400, Viets, A.K., Tann R.S., Mueningho!, J.C. (Eds.), American Society for Testing Materials, US.
A.J. Hewitt / Crop Protection 19 (2000) 623}627 Ho!man, C., 1999. E!ects of AG-TIPS on swath width and drift. ASAE paper No. AA99-002. Kidd, F.A., 1994. SDTF survey of aerial applicators. SDTF Report L92-001. Kirk, I.W., 1997. Application Parameters for CP Nozzles. ASAE Paper AA97-006. Kirk, I.W. 1998 Spray quality from CP straight stream nozzles. ASAE Paper No. AA98-002. Parkin, C.S., Spillman, J.J., 1980. The use of wing-tip sails on a spraying aircraft to reduce the amount of material carried o!-target by a crosswind. J. Agric. Engng. Res. 25, 65}74. Ray, J.W., Richardson, B., Schou, W.C., Teske, M.E., Vanner, A.L., Coker, G.W.R., 1998. Validation of spray safe manager, an aerial application decision support system. Proceedings of the Third International Conference on Forest Vegetation Management, Sault Ste Marie, Canada. Piggott, S., Matthews, G.A., 1999. Air induction nozzles: a solution to spray drift? Int. Pest Control 41, 24}28. Southcombe, E.S.E., Miller, P.C.H., Ganzelmeier, H., Van de Zande, J.C., Miralles, A., Hewitt, A.J., 1997. The international (BCPC) spray classi"cation system including a drift potential factor. Proceedings of the British Crop Protection Conference Vol. 5A-1, pp. 371}380.
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Teske, M.E., 1999. FSCBG 5.0: The inclusion of the USDA forest service aerial application model into AgDRIFT 3.0. Report No. 99-05, Continuum Dynamics, Inc., Princeton, US. Teske, M.E., Bird, S.L., Esterly, D.M., Ray, S.L., Perry, S.G., 1997. A user's guide for AgDRIFT威 1.0: a tiered approach for the assessment of spray drift of pesticides. Technical Note No. 95-10, CDI, Princeton, NJ, US. Teske, M.E., Valcore, D.L., 1999. An initial examination of winglet vortical e!ects. ASAE Paper No. 991031, Toronto, Canada. Teske, M.E., Bird, S.L., Esterly, D.M., Curbishley, T.B., Ray, S.L., Perry, S.G., 2000a. AgDRIFT: an update of the aerial spray model AGDISP, J. Env. Toxicology and Chemistry, submitted for publication. Teske, M.E., Thistle, H.W., Hewitt, A.J., 2000b. Conversion of droplet size distributions from PMS optical array probe to Malvern laser di!raction, Proc. ICLASS 2000, US. Ucar, T., Hall, F.R., 1999. Recent studies on pesticide spray drift reduction with arti"cial and natural barriers. Proceedings of the Agricultural Engineering, Turkey. Walklate, P.J., Miller, P.C.H., Richardson, G.M., Baker, D.E., 1998. A similarity scaling principle for risk assessment of spray drift. 14th Conference on Liquid Atomisation and Spray Systems, ILASS Europe 98, pp. 499}504.
Spray drift: impact of requirements to protect the environment A.J. Hewitt Stewart Agricultural Research Services, Inc., P.O. Box 509, Macon, MO 63552, USA
Abstract Spray drift studies in the US have evaluated the e!ects of application, meteorological and tank mix variables on spray drift. The data have been incorporated into models to predict drift from aerial applications, and to evaluate worst-case drift from ground rig (boom) and orchard airblast applications. An atomisation model has also been developed to predict droplet size for applications of tank mixes with user-de"ned or reasonable worst-case physical properties through a wide range of hydraulic nozzles applicable to aerial applications. The database and models help provide the exposure risk input to risk assessments for developing appropriate labelling based on exposure and toxicity risk to non-target sensitive areas. This needs to be balanced with allowing crop protection using careful risk/bene"t assessments. Bu!ers or no spray zones may be based on spray quality, release height and other variables such as wind speed where necessary for protecting speci"c sensitive areas. The impact of protection measures aimed at minimising the incidence and impact of spray drift is discussed in the present paper. 2000 Elsevier Science Ltd. All rights reserved. Keywords: Spray drift; Deposition; Pesticide; Label; Droplet size; Risk assessment
1. Introduction The US National Coalition On Drift Minimisation (NCODM) considers pesticide drift to be the movement of pesticide through the air at the time of pesticide application or soon thereafter from the target site to any non- or o!-target site, excluding pesticide movements by erosion, migration, volatility, or wind-blown soil particles after application. EPA considers drift a concern because it can a!ect human health and the environment; it can cause pesticide exposure to farm workers, children playing outside, and wildlife and its habitat, or contaminate a home garden or crops, causing illegal pesticide residues and/or plant damage (EPA, 1999). EPA is most concerned with protecting aquatic environments from drift. Spray drift is a signi"cant concern in the US, with thousands of reported complaints every year (EPA, 1999). The atomisation, transport and deposition of sprays are generic phenomena that can be modelled based on tank mix physical properties, atomiser type and operation, air #ow "elds and other parameters. However, the e!ect of a given amount of active ingredient is product and species-speci"c (Hewitt et al., 2000). Thus, the risk assessment process includes generic processes for exposure and product/species speci"c toxicity assessments. The present paper explains the development of databases and models on spray drift deposition, and their use
and impact when used for labelling and regulatory activities in the US.
2. Spray drift task force studies In the 1980s, EPA de"ned data requirements for the registration of over 2000 existing and future pesticides. These requirements included the provision of data on spray drift and atomisation droplet size spectra. Several registrant companies decided to conduct the necessary studies jointly, so formed the spray drift task force (SDTF). There are currently 40 member companies in the SDTF. The studies have been completed and submitted to EPA, and subjected to an extensive review procedure by scientists from government, academic and industrial sources who had not been involved in the studies. Although not common in many European countries, aerial spray applications are widely used for the rapid treatment of large and/ or inaccessible areas in the US. Therefore, the SDTF database includes extensive analyses of the factors a!ecting drift from aircraft. The development of the aerial application database was described in detail by Hewitt et al. (2000). The use of this database for development and veri"cation of a spray drift deposition model, AgDRIFT威, was described by Teske et al. (2000a) and Bird et al. (2000). The SDTF ground rig studies were
0261-2194/00/$ - see front matter 2000 Elsevier Science Ltd. All rights reserved. PII: S 0 2 6 1 - 2 1 9 4 ( 0 0 ) 0 0 0 8 2 - X
624
A.J. Hewitt / Crop Protection 19 (2000) 623}627
summarised by Hewitt et al. (2001). Details of the orchard and chemigation studies have not been published, although the droplet/size spectra for these applications were described by Hewitt et al. (1996, 1999). The SDTF aerial "eld studies involved 180 "eld trials, half with the same application equipment to provide a standard treatment for comparison with a paired variable treatment. Comparisons of the standard treatment from this covariate approach revealed the e!ect of meteorological variables such as wind speed, temperature and relative humidity on drift, while the variable treatments revealed the e!ects of the application, tank mix and canopy variables on drift. The studies showed that spray quality, boom height and wind speed were most important in a!ecting drift from aerial spraying. The SDTF 46 ground rig studies involved applications of sprays through four nozzle types (producing Fine, Medium, Coarse and Very Coarse sprays) with two boom heights (51 and 127 cm) at di!erent wind speeds. Most of the wind speeds were between 16 and 35 km/h, which caused wind speed not to be identi"ed statistically as a major variable a!ecting o!-target deposition rates. However, a wind speed trend of lower drift at lower wind speeds was evident from the entire SDTF database. Other studies (e.g. Ganzlemeier et al., 1995) have shown that at lower wind speeds, wind speed is a signi"cant variable a!ecting drift. Another reason why wind speed did not have a signi"cant e!ect on the SDTF ground rig studies, but was identi"ed as important for the aerial studies and for studies conducted elsewhere was that the "rst sample distance for the SDTF "eld studies was 8 m from the edge of the "eld. For aerial applications where the release height is greater than ground applications, 8 m is su$ciently close to reveal near-"eld trends. However, for ground applications where boom heights are lower than most aerial applications, signi"cant di!erences in deposition rates might be expected at near-"eld distances. While the SDTF drift studies did not evaluate deposition rates at distances very close to the edge of the "eld (i.e. (8 m), they did measure drift at extended distances up to 792 m from the edge of the "eld, twice as far as many previous drift studies. Analyses of the SDTF ground rig database showed that at least two spray quality groupings ("ne and medium- very coarse) (BCPC/ ASAE spray quality schemes, Anon, 1999, Southcombe et al., 1997) could be paired with each of the boom heights for drift assessments (Hewitt et al., 2001). The SDTF orchard airblast studies showed that canopy characteristics such as tree height and tree row volume had important e!ects on drift. Three sprayers were evaluated, all producing "ne to medium sprays (#owweighted mean D values of 92}173 lm and spray volume in droplets (141 lm"36}75%, Hewitt et al., 1999). Given the small range of droplet size assessments and the importance of canopies in intercepting sprays
that were released within canopy (as opposed to abovecanopy for the aerial and ground applications), droplet size did not have a major e!ect on spray drift for the SDTF orchard studies. If escaping from the canopy, smaller droplets would be expected to have greater drift potential as with other application types. For such droplets, the e!ective release height and wind speed might also be important. The o!-target movement of smaller droplets was seen in the SDTF studies with dormant apple trees. The SDTF studies showed that most drift occurs from the most downwind swath that is sprayed. Therefore, swath adjustment is an important drift reduction strategy. Up to two swaths are sometimes not sprayed to compensate for higher wind speeds and/ or "ner spray applications with aerial equipment (Kidd, 1994). In orchard applications, signi"cant decreases in drift potential occur when not spraying the outside row on the downwind orchard side. Spray release height and the use of end guns were major factors a!ecting drift in the SDTF chemigation studies. Chemigation sprinklers generally produce extra coarse sprays (Anon, 1999), so droplet size is not a major factor a!ecting drift of such sprays. A review of the SDTF and other aerial drift studies was provided by Bird et al. (1996).
3. Spray modeling Hewitt (2000) described the SDTF AgDRIFT威 and DropKick威 models. AgDRIFT威 (Teske et al., 2000a) is a Lagrangian model that can predict o!-target deposition rates for user-de"ned aerial application conditions. It is based on a previous model, AGDISP, developed by the US Department of Agriculture (USDA) Forest Service (Bilanin et al., 1989), NASA and US Army. AgDRIFT威 was developed under a co-operative research and development agreement by the SDTF, EPA and USDA. The Canadian Pesticide Management Regulatory Agency (PMRA) has also been involved in the development of AgDRIFT威, and was one of the "rst regulatory agencies to commence use of the model for pesticide risk assessment and registration purposes. AgDRIFT威 is structured as a three-tiered model, with higher tier levels o!ering greater options for speci"cation of the various input variables. Tier I was developed as the primary risk exposure level, where the major variables that could be considered for labelling are included: spray quality for aerial applications, spray quality (version 2.0 of model) and boom height for ground rig applications, and canopy type for orchard airblast applications. The risk exposure process at Tier I is based on reasonable worst-case values for the model inputs. If the output from this analysis is too restrictive (e.g. if the suggested bu!er zones are excessively large, or if the default inputs such as
A.J. Hewitt / Crop Protection 19 (2000) 623}627
wind speed are too restrictive), then a tier II analysis can be conducted giving access to more input variables. Tier III allows access to all inputs, for investigations. AgDRIFT威 1.0 (Teske et al., 1997) includes generic deposition curves for ground rig and orchard airblast applications at all tier levels. Attempts will be made to include predictive models for these applications at a future time, to expand the range of conditions encompassed. The SDTF also developed a model to estimate spray quality produced by many agricultural nozzles at a wide range of aerial application operating conditions with di!erent tank mixes. This model, DropKick威 (Esterly, 1998; Hermansky, 1998) is linked with the AgDRIFT威 model to expand the options for inputting spray quality to the assessments. DropKick威 is dynamic since it o!ers considerable scope for modi"cation as additional data become available for modelling the relationship between atomisation and tank mix physical properties. Recent insights into the breakup of emulsion sheets (Butler Ellis et al., 1999; Dexter, 2001) may facilitate enhancements in predictions if such e!ects are signi"cant in atomisation and drift processes. AgDRIFT威 and DropKick威 are not the only models that can predict spray drift and atomisation, respectively. Other models are available such as the Forest Service/NASA/US Army model AGDISP and the Forest Service models AGDISP (Bilanin et al., 1989) and SpraySafe Manager威 (developed jointly with the New Zealand Forest Research Institute, Ray et al., 1998). For modelling atomisation, it should be noted that some nozzle types and uses are beyond the range covered by DropKick威. For example, since the initiation of the SDTF studies, a new range of nozzles was introduced by CP Products, Inc. (Mesa, Arizona). These include de#ector and solid stream variable setting nozzles where the user selects the most appropriate de#ector and ori"ce size for his application. The USDA has measured droplet size spectra for various CP nozzle settings and developed predictive models for aerial use conditions (Kirk, 1997, 1998). The USDA Forest Service has decided to incorporate the major components from AGDISP and FSCBG into a version of AgDRIFT威 that will include three standard tiers (Teske et al., 1997) and two additional tiers (Tier II/FS and Tier III/FS) (Teske, 1999). Many other groups are also considering AgDRIFT威 and other models for their own applications. The incorporation of extensive atomisation databases into future modelling activities has been facilitated through the development of a conversion between spray measurement systems o!ered by Particle Measurement Systems optical array probe and Malvern laser di!raction instruments (Teske et al., 2000b). AgDRIFT威 currently includes libraries of atomisation data measured by the SDTF. The addition of libraries such as those of the
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Forest Service would provide alternative droplet size data sources to those of the current library, DropKick model and worst-case spray quality options.
4. Extending SDTF databases and models The SDTF databases included assessments of drift from reasonable worst-case conditions, as well as analyses of a few drift mitigation options such as the use of coarser sprays, lower release heights and shorter boom lengths. However, the studies did not include an in-depth investigation of drift reduction techniques, and mostly excluded evaluations of the e!ects of drift control adjuvants and specialised sprayers such as `low drifta nozzles and electrostatic systems. Such systems have been evaluated elsewhere (e.g. Carlton et al., 1995; Piggott and Matthews, 1999), and will continue to be evaluated for drift reduction capabilities by researchers from academia, the USDA and elsewhere. Some possible drift reduction techniques such as wing tip sails have been investigated for drift reduction potential using theoretical considerations (Parkin and Spillman, 1980), point-vortex calculations (Teske and Valcore, 1999) and "eld evaluations (Ho!man, 1999). Drift reduction options that are already adequately covered by some models include assessments of drop size, release height and meteorological e!ects within appropriate limits. Current limits might be extended through the conduct of appropriate studies. Electrostatic systems have been tested in the "eld (Carlton et al., 1995), while `low drifta nozzles can be tested in wind tunnels (Walklate et al., 1998).
5. Risk assessment and labelling Risk assessment (Anon, 1983) involves using the available information on exposure risk (e.g. from AgDRIFT威) and toxicity to speci"c non-target sensitive organisms. A balance is needed between obtaining good pest control and e$cacy while providing adequate environmental protection from the agricultural chemicals being applied. Hewitt (1997) described the con#ict often encountered with droplet size in agricultural spraying * smaller droplets are often the most e$cacious and may o!er better coverage, but also are generally more prone to drift under unfavourable conditions. The local environmental risk assessment for pesticides (LERAP) (Gilbert, 2000) in the UK allows bu!ers to be reduced when meeting certain requirements for drift reduction technology, water body speci"cations and/ or dose rates. Similar schemes are considered in other countries in Europe. Several researchers have recognised the importance of barriers for reducing spray drift (e.g. literature review by Ucar and Hall, 1999). EPA acknowledges the importance of such measures, as shown by the following list of
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possible drift reduction requirements in its drift fact sheet: `Restrictions may include prohibiting the use of certain pesticides under certain conditions; prohibiting certain methods of application; requiring use of a foliage barrier; or requiring a bu!er zone distance between the site of application and areas to be protecteda (EPA, 1999). Such restrictions may or may not appear on new pesticide labels. A discussion of future labels was given by Hewitt (2000). Drift management options that may be speci"ed on many new labels include spray quality, release height and wind speed restrictions. De"nitions of sensitive areas are being discussed in the US. 6. Impact of measures to prevent drift Considerable debates have taken place in the US and other countries on approaching drift management. On the one hand, the regulatory position is often biased toward not allowing any spray drift with considerations of label language such as `do not allow drifta. On the other extreme, bu!ers are sometimes seen as completely unacceptable in any form. Large bu!ers are not desirable because they result in a loss of land that can be protected from pests and diseases, while some bu!er size might be needed to protect certain sensitive areas. Where necessary, bu!ers should be based on scienti"c assessments using reasonable assumptions and the best available data and/or models. The impact of zero drift tolerance could be signi"cant. In its fact sheet on spray drift, EPA acknowledges that drift is an almost inevitable occurrence with any spray application. This is explained as follows: `We recognise that some degree of drift of spray particles will occur from nearly all applicationsa (EPA, 1999). The fact sheet explains that all available steps must be taken to avoid spray drift where the label or regulations prohibit such drift; however, it also explains that `EPA uses its discretion to pursue violations based on the unique facts and circumstances of each drift situationa (EPA, 1999). It is interesting to note that di!erent states in the US have historically had di!erent opinions and regulations for spray drift. In the future, there will hopefully be more consistency in the way that drift is addressed in di!erent areas; however, it is recognised that some geographical areas may pose unique considerations for drift management. It is hoped that measures to minimise or prevent drift will provide incentive for applications to be made using the best available equipment and with careful observation of application practices such as spray release position and local environmental and meteorological conditions. Acknowledgements Thanks are due to all involved in minimising the incidence and impact of drift described in this paper. In
particular, thanks are due to the SDTF and NCODM for data and activities for the goal of a!ording protection to the environment using the best available science, while ensuring the vital provision of crop protection for adequate food supplies.
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