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Crop Protection 42 (2012) 116e123

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Crop Protection

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Risk assessment of pesticide spray drift from citrus applications with air-blastsprayers in Spain

João Paulo Cunha a, Patricia Chueca b, Cruz Garcerá b, Enrique Moltó b,*

a Instituto de Ciências Agrárias, Universidade Federal de Uberlândia, 38400-902 Uberlândia, Minas Gerais, BrazilbCentro de Agroingeniería, Instituto Valenciano de Investigaciones Agrarias, Ctra. Moncada-Náquera km 4.5, 46113 Moncada, Valencia, Spain

a r t i c l e i n f o

Article history:Received 28 December 2011Received in revised form25 May 2012Accepted 1 June 2012

Keywords:Buffer zoneEnvironmental riskBystander exposureDrift models

* Corresponding author. Tel.: þ34 963424000; fax:E-mail address: molto_enr@gva.es (E. Moltó).

0261-2194/$ e see front matter � 2012 Elsevier Ltd.http://dx.doi.org/10.1016/j.cropro.2012.06.001

a b s t r a c t

There have been no previous risk assessment studies on citrus pesticides in Spain. The aim of this workwas to estimate the risks caused by worst-case drift scenarios of the principal pesticides used on thecrop, assessing possible damage to the environment and human health. A field survey was carried out,characterizing the specific conditions of plant protection product applications to citrus crops in Spain. Sixtargets were identified as being the most affected by droplet spray drift in Spain, and more broadly inmost Mediterranean conditions: aquatic organisms, earthworms, bees, adult bystanders, childbystanders and residents. Three drift estimation models were used to assess the amount of drift atspecific distances downwind of a field in order to calculate Risk Indicators. These showed safe conditionsfor earthworms and residents, but also indicated that some pesticides may pose a risk to aquaticorganisms, even with a 20 m buffer zone, and also to bees, and adult and child bystanders. In general,results generated similar consequences of hazard risk independent of the drift prediction model used,indicating that toxicological data are more relevant for predicting risks.

� 2012 Elsevier Ltd. All rights reserved.

1. Introduction

Drift is recognised as being the most important source of diffuseenvironmental contamination caused by pesticide application(Jong et al., 2008; Maski and Durairaj, 2010). Spray drift is definedas the quantity of plant protection product that is carried out of thesprayed (treated) area by the action of air currents during theapplication process (ISO, 2005). Driftingmaterial may take the formof droplets, dry particles or vapour and has potential effects onliving organisms in areas adjacent to treatment, particularly watersurfaces, affecting nearby residents, bystanders, fauna and flora (Giland Sinfort, 2005; Tsai et al., 2005). Thus, this should be minimizedas much as possible (Salyani and Farooq, 2004).

In order to avoid undesirable effects of pesticides, the EuropeanUnion adopted Regulation 1107/2009 (EC, 2009b) that regulates theuse and marketing of plant protection products. Accordingly,environmental pesticide damage should be assessed by means ofenvironmental risk indicators. Conventionally the risk posed byplant protection products is estimated by a risk indicator (RI),which is the ratio of the estimated human exposure or predicted

þ34 963424001.

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environmental concentration (PEC) to a toxicological referencevalue.

Pesticide Occupational and Environmental Risk (POCER) indica-tors were developed by Vercruysse and Steurbaut (2002) followingthe OECD principles (OECD,1997) for typical agricultural conditionsin Flanders (Belgium). The procedure ismade up of one RI for each ofthe 10 targets described in Directive 91/414/EC (operators, workers,bystanders, aquatic organisms, birds, earthworms, bees, beneficialarthropods, persistence in soil and leaching to groundwater) (EC,2009b). More recently, at European level, HArmonised environ-mental Indicators for pesticide Risk (HAIR) have been developed,adding more modules and using different toxicological referencevalues (Garreyn et al., 2007; Kruijne et al., 2011).

RI aims to combine information on pesticide risk (hazard andexposure) with information on the quantity and conditions ofpesticide use. Moreover, Ramos et al. (2000) demonstrated theimportance of using region specific information when assessingpesticide risks to improve the accuracy of such environmental riskassessment.

In order to estimate the exposure of a target to a particulardrifted product, it is necessary to assess the amount of driftgenerated during treatment. This depends on the physicochemicalproperties of the sprayed product and its a.s. (Holterman, 2003a,2003b; Stainier et al., 2006; De Schampheleire et al., 2009), thecharacteristics and geometry of the culture (foliage, density,

J.P. Cunha et al. / Crop Protection 42 (2012) 116e123 117

dimensions, etc.) (Belcher et al., 2003; Farooq and Salyani, 2004; DaSilva et al., 2006; Yi, 2008), the machinery setup (sprayed volume,use of fans, tractor speed, etc.) (Walklate, 1992; Farooq and Salyani,2002; Delele et al., 2005; Derksen et al., 2007; Nuyttens et al., 2011),meteorological conditions (wind, humidity, temperature, etc.)(Miller et al., 2000; Thistle, 2000; Gil et al., 2007; Wang andRautmann, 2008; Endalew et al., 2010), soil and water properties,number of treatments, etc. All of these vary from country to countryand must be taken into account.

Estimation of the amount of spray drifted from a pesticideapplication is often based on German models (Ganzelmeier et al.,1995; Rautmann et al., 2001). These are based on experimentaldata obtained in different crops grown in Central Europe (cereals,vines, fruit trees, etc) and describe worst-case drift measurementsin field crop applications in Germany in terms of percentage oftreatment deposited on the ground as a function of downwinddistance to the edge of the field. Similarly, Holterman and van deZande (2003) developed the so-called IMAG drift calculator,working with potatoes, flower bulbs, sugar beets, cereals, bare soil,fruit trees in leaf and leafless fruit trees grown in Dutch conditions.However, both drift models have been established under NorthernEuropean conditions, which differ greatly from Mediterraneanconditions, and particularly from fruit crops other than citrus.

Accurate risk assessment of citrus treatments in Spain mustadapt to the specificities and practices of growers in such condi-tions, which substantially differ from other crops and countries. Inthis sense, Meli et al. (2003) estimated drift produced by treat-ments of citrus in the conditions in Catania (Italy) and concludedthat Ganzelmeier’s tables overestimated drift in these conditions.More research on drift from citrus applications had been conductedbut in North American conditions (Salyani and Cromwell, 1992;Salyani and Farooq, 2004; Salyani et al., 2007).

Citrus production is economically significant in Spain, being thesixth major producer in the world and the first exporter of wholefruit for the fresh (non-juice) market (FAO, 2008). More than318,385 ha of citrus were grown and more than 6.3 million tonswere produced in 2009 (MARM, 2009), which indicates theimportance of accurate pesticide risk assessment under ourconditions. However, there are no published works on assessmentof risks caused by pesticide spray drift in this context.

What is more, European Directive 2009/128 (EC, 2009a) paysparticular attention to the avoidance of pollution of surface waterand groundwater by taking appropriate measures, particularly theestablishment of buffer zones to reduce exposure of water bodies tospray drift. Buffer zones are adjacent strips of vegetation that do notreceive pesticide applications. The width of buffer zones can bebased on the distances where acceptable risk indices are achieved(De Schampheleire et al., 2007).

We also have to take into account that citrus production in Spainand other Mediterranean countries are mostly cultivated far awayfrom surface water bodies but close to residential areas, so in thesecases it is important to emphasize the risks to bystanders, childbystanders and residents.

This work was aimed at estimating risks caused specifically bydrift in Spanish citrus groves, and thus focused on ground foliarapplications, these being the main sources of drift when comparedto direct soil applications. Aerial applications are not consideredbecause they are not employed in this area.

In the first part of this work, spraying practices in Spain arecharacterized from data obtained from a survey. The second partassesses exposure to drift caused by such practices. Finally, riskscaused to fauna, flora, adult bystanders, child bystanders (childrenare more vulnerable than adults so the risks are different) andresidents are estimated. As a consequence, acceptable width ofbuffer zones is estimated.

2. Materials and methods

2.1. Characterization of foliar pesticide applications in Spanishcitrus regions

To characterize current foliar pesticide applications in Spanishcitrus growing regions, 175 surveys were performed by interviewingfarmers and technicians of associations of farmers or service compa-nies in the more important Spanish citrus regions in 2004/2005.

The area sampled was approximately 18,000 ha, predominatelyplanted with oranges (71.2%), followed by tangerines (26.1%) andlemons (2.7%).

The survey was divided into two parts. The first part containedquestions as to the characteristics of the farm, the equipment usedfor the applications and its set-up. The second part recorded eachtreatment during the season (plant protection products used, bio-logical problems encountered, dates, spray volumes, operatingparameters of each application, etc.).

2.2. Estimation of the amount of drift

In this study, German drift curves (Ganzelmeier et al., 1995;Rautmann et al., 2001), the Dutch IMAG drift calculator (Holtermanand van de Zande, 2003) and the model proposed by Meli (Meliet al., 2003) were used to predict the amount of pesticide drift atspecific distances downwind from a given field.

German drift models do not target citrus cultivation, only dis-tinguishingbetweenearlyapplicationsof fruit trees, late applications,grape vine, hops and field crops.We took into account data from lateapplications to fruit trees because we assumed that they would becloser to those of citrus. Dutch drift values distinguish betweenpotatoes, flower bulb, sugar beets, cereals, bare soil, fruit trees in leafand leafless fruit trees, so we used ‘fruit trees in leaf’ for our calcula-tions.Meli’smodel is specific forcitrusandair-blast sprayer.However,testswereconducted from1.5upto7.5mandthenextrapolatedout to15m by the authors. Consequently, the resulting curve is limited andalmost constant at distances greater than 10 m.

All of these models represent the percentage of applied dosethat has drifted (%drift) as a function of the downwind distancefrom the end of the field (z). We assumed that all of them take thelast row of trees as the initial reference point.

Equations (1)e(4) summarize these models:German model

%drift ¼ 60:36� z�1:2243 ðz < 15 mÞ (1)

%drift ¼ 298:83� z�1:8672 ðz>15 mÞ (2)

IMAG model

%drift ¼ 48� e�z=2:7 þ 0:45� e�z=0:091 (3)

Meli model

%drift ¼ 11:542� z�0:4026 (4)

It can be deduced that all of them assume that in the first 5 mdrift decreases sharply and then decrease much more slowly(Fig. 1). Moreover, drift values significantly differ from model tomodel in these first 5 m. The German model assumes the highestvalues followed by IMAG and then the Meli curves.

2.3. Assessment of risks

We assumed that drift from pesticide application mainly causesrisks to neighbouring fields and residential areas, water surfaces or

0

10

20

30

40

50

60

70

0 2 4 6 8 10 12 14 16 18 20

Distance from the edge of the treated orchard (m)

German IMAG Meli

Fig. 1. Spray drift prediction based on different methodologies used for the pesticiderisk assessment.

J.P. Cunha et al. / Crop Protection 42 (2012) 116e123118

nature reserves. Therefore, we focused on targets that may beaffected by droplet drift: aquatic organisms, earthworms in adja-cent fields, bees, adult bystanders, child bystanders and residents.We did not take into account birds, because indicators are based ondamage caused by ingestion, nor beneficial arthropods, because RIsare based on direct application of pesticides.

RIs were individually calculated for every a.s. These differeddepending on the country and crop.We used the survey to generatea list which was then checked against the official list of registeredsubstances in Spain (MARM, 2011). The next step was to obtain thetoxicological data from the European Commission Database (DGSANCO, 2011).

The total amount of a.s. per unit surface is one of the parametersrequired to estimate the Predicted Environmental Concentration(PEC) and the bystander exposure. This is the result of the sprayedvolume (from the surveys) times product concentration and a.s.percentage content. In all cases the combination of plant protectionproduct concentration and percentage of a.s. that produced themaximum value was taken into account.

2.3.1. Aquatic organismsAccording to the POCER indicator, the predicted environmental

concentration (PECInitial, mg/l) for aquatic organisms is estimated byEquation (5) (Vercruysse and Steurbaut, 2002). The factor 1000 isa conversion factor for the units.

PECInitial ¼ ðAR� %driftÞðdditch � 1000Þ (5)

where AR is the application rate (kg a.s./ha), %drift the drift depo-sition (in %) and dditch the ditch depth (0.5 m is the typical value forthe area).

The RI for aquatic organisms was calculated as the quotient of thePECInitial and the endpoint for aquatic organisms. This endpoint wascalculated from acute toxicity data of the three groups of organisms.The lowest of the following three quotients was used as the endpoint:

* Fish: LC50/100

where LC50 (mg/l) is the median lethal concentration, i.e. the concen-tration of a.s. that causes death of 50% of a test fish population.

* Daphnia: EC50/100

where EC50 (mg/l) is the median effect concentration, i.e. theconcentration of a.s. that affects 50% of a Daphnia (Daphnia spp.Leydig) test population.

* Algae: NOEC/10

where NOEC (mg/l) is the no observed effect concentration, whichis the highest concentration of a.s. that causes no observableadverse effects on an algae test population.

The safety factors used in the three previous equations aredefined in the Uniform Principles (EC, 2009b).

2.3.2. EarthwormsIn this case, PECInitial in soil (mg/kg soil) was estimated by

Equation (6). To estimate this, pesticide is assumed to accumulatehomogeneously in the top 5 cm of the soil (Vercruysse andSteurbaut, 2002) and the drift deposition was added to the equa-tion to take into account the risk outside the applied area.

PECInitial ¼ ðAR� %drift � ð1� f ÞÞðd� rÞ (6)

where AR is the application rate (kg a.s./ha), %drift the drift depo-sition (in %), f the fraction of deposited a.s. intercepted by crops (weconsidered the worst case scenario which is an area without crop,0), d the soil layer depth (0.05 m, as stated before), and r the soildensity (the typical value for the Spanish citrus area is 1350 kg/m3).

Then, RI for earthworms was calculated using Equation (7).

RIEarthworms ¼ PECInitialLC5010

(7)

where LC50 is the acute median lethal concentration for earth-worms (mg/kg soil). The factor 10 is a safety factor set by UniformPrinciples (EC, 2009b).

2.3.3. BeesA hazard quotient, defined as the ratio of the application rate of

a pesticide’s a.s. (g a.s./ha) to the acute LD50 (median lethal dose)(mg a.s./bee) was used according to Vercruysse and Steurbaut (2002).RIwas then calculated using Equation (8). Drift depositionwas addedin the equation to take into account the risk outside the applied area.The factor 50 is the criteria set by Uniform Principles (EC, 2009b).

RIBees ¼AR� %drift

100ðLD50 � 50Þ � 1000 (8)

where AR is the application rate (kg a.s./ha), %drift the drift depo-sition (in %) and LD50 is the minimum between LD50 oral andLD50 contact (mg a.s./bee).

The factor 1000 is used to convert the application rate fromkg a.s./ha to g a.s./ha, used for calculation of the hazard quotient.This quotient used here is different from the exposure toxicity ratioused in other indicators, since exposure and effect concentrationsare not expressed in the same units (Kruijne et al., 2011). Thesevalues cannot be compared to each other.

2.3.4. Adult bystandersAdult bystanders are people located within or directly adjacent

to the areawhere pesticide application or treatment is in process orhas taken place. Adult bystander exposure results from contactwith spray drift during pesticide treatment.

J.P. Cunha et al. / Crop Protection 42 (2012) 116e123 119

According to POCER, adult bystander dermal and inhalationexposure is estimated using Equations (9) and (10). It is assumedthat bystanders are located 8 m downwind from the treated field,according to EUROPOEM (1996), that only ordinary clothing is wornand the total uncovered skin area (EA) amounts to 0.4225 m2

(Vercruysse and Steurbaut, 2002).

DEBystander ¼ AR� %drift � EA (9)

where DEBystander is the adult bystander dermal exposure (mg/person/day), AR the application rate (kg a.s./ha), %drift the driftdeposition (in %) and EA the exposed area (0.4225 m2/person/day).

IBystander ¼ Ia � AR� DEDST

(10)

where IBystander is the adult bystander inhalation exposure (mg/person/day), Ia the applicator inhalation exposure (0.018 mg/kg a.s.according to Garreyn et al. (2007)), AR the application rate (kg a.s./ha), ST the spraying time (min/ha) and DED is the daily exposureduration (min/day).

Daily exposure for applicators can be set at 6 h per day, whileinhalation exposure for adult bystanders is calculated at only 1 minbecause they usually have only brief exposure to pesticide spraydrift (Vercruysse and Steurbaut, 2002). Spraying time was obtainedfrom the above mentioned interviews with farmers.

Adult bystander risks were assessed by comparing this exposurewith AOEL (acceptable operator exposure level). RI for adultbystander is calculated using Equation (11). Body weight wasassumed to be 70 kg according to international standards.

RIBystander ¼ ðDE � AbDE þ I � AbIÞðBW � AOELÞ (11)

where RIBystander is the risk indicator for adult bystanders, DE thedermal exposure (mg/person/day), AbDE the dermal absorptionfactor (0.1 according to Garreyn et al. (2007)), I the inhalationexposure (mg/person/day), AbI the inhalation absorption factor (1.0according to Garreyn et al. (2007)), BW the body weight (70 kg bydefault) and AOEL the acceptable operator exposure level (mg/kg body weight/day).

2.3.5. Child bystandersThe RI for child bystanders is a special case of the acute RI for

adult bystanders because children are more vulnerable.The total dermal exposure is calculated, according to Garreyn

et al. (2007), by adding together the different types of dermalexposure (dermal exposure resulting fromdirect contact with spraydrift, dermal exposure resulting from contact with a lawncontaminated by spray drift, dermal exposure resulting fromingestion of turf residues (hand-mouthing activity) and dermalexposure resulting from ingestion of turf residues (object-to-mouthexposure)) using Equations (12)e(15). All values in brackets arefrom Garreyn et al. (2007).

DEChild; direct ¼ AR� %drift � EAChild (12)

where DEChild, direct is the dermal exposure to direct spray drift (mg/person/day), AR the application rate (kg a.s./ha), %drift the driftdeposition at 8 m of distance (in %) and EAChild the exposed area ofa child (0.2 m2/person/day).

DEChild; lawn ¼ 10�4 � AR� %drift � TTRTurf � TF � DEDChild

(13)

where DEChild, lawn is the dermal exposure of a child by contact withdrift reaching lawn (mg/person/day),AR the application rate (kg a.s./

ha), %drift thedrift deposition at 8mofdistance (in%), TTRTurf the turftransferable residue value (0.05), TF the transfer factor (5200 cm2/h)and DEDChild the daily exposure duration (2 h/day).

DEChild;turf ¼ 10�4 � AR� %drift � TTRTurf � SE � EAFingers

� NEvents � DEDChild ð14Þwhere DEChild, turf is the dermal exposure of child resulting fromhandemouth activity with turf (mg/person/day), AR the applicationrate (kg a.s./ha), %drift the drift deposition at 8 m of distance (in %),TTRturf the turf transferable residue value (0.05), SE the salivaextraction factor (0.50), EAFingers theexposed area offingers (20 cm2),Nevents the number of hand-to-mouth exposure events per hour (20events/hour) and DEDChild the daily exposure duration (2 h/day).

DEChild;object ¼ 10�4 � AR� %drift � TTRObject � IgR (15)

DEChild, object is the dermal exposure of child resulting from ingestionof turf residues (mg/person/day), AR the application rate (kg a.s./ha), %drift the drift deposition at 8 m of distance (in %), TTRObject theobject transferable residue value (0.20) and IgR the ingestion rate(25 cm2 grass/day).

Inhalation exposure and risk indicator of children exposed asbystanders are assessed in the way outlined for bystanders (Equa-tions (10) and (11)). Body weight is assumed to be 15 kg.

2.3.6. ResidentsThe RI for residents describes the exposure of people living in

nearby fields. Exposure near a field occurs through dermal exposureto spray drift (Equation (16)) and through inhalation of vapour orig-inating in the field (Equation (17)). Residents are assumed to belocatedat50mdownwind fromthe treatedfield (Garreynet al., 2007;Kruijneet al., 2011). Thedrift valueswere takenonly fromtheGermantables, because the other two models do not predict drift at thisdistance. Only for assessing resident risks, the 77th percentile wasused for drift value for three applications per year, the 82thpercentilewas used for two applications per year and 90th percentile for oneapplicationper year, accordingGarreyn et al. (2007). The indicator forresidents is calculated for multiple applications, and is thereforechronic in nature. The frequency of applications yearly for each a.s.and spraying time were obtained in the field survey. The maximumnumber of applications per year was used.

DEResidents ¼ AR� %drift � FA� EA� RD365

(16)

where DEResidents is the dermal exposure (mg/person/day), AR theapplication rate (kg a.s./ha), %drift the drift deposition at 50 m ofdistance (in %), FA the frequency of applications, EA the exposedarea (0.4225 m2/person/day) and RD the residence days (90 daysaccording to Garreyn et al. (2007)).

IResidents ¼ Ia � AR� DEDST

� EF � YED (17)

where IResidents is the inhalation exposure (mg/person/day), AR theapplication rate (kg a.s./ha), ST the spraying time (min/ha) and thefollowing data in brackets are from Garreyn et al. (2007): Ia is theapplicator inhalation exposure (0.018 mg/kg a.s.), DED the daily expo-sure duration (480min/day), EF the exposure frequency (3 months/12months¼ 0.25) and YED the yearly exposure duration (1.0).

Residence risks were assessed by comparing exposure withAOEL (acceptable operator exposure level) (Equation (18)).

RIResidents ¼ ðDEResidents � AbDE þ IResidents � AbIÞðBW � AOELÞ (18)

Table 1Operational characteristics of applications with air-blast sprayers in the citrusregions of Spain.

Oranges Tangerines Lemons

Operating pressurea (MPa) 1.5e3.0 1.2e2.5 2.0e3.0Velocitya (km/h) 3e6 3e5 5e15Time to treat 1 haa (min) 35e60 45e90 60e90Time to prepare the solutiona (min) 10e15 10e15 15e25Spray volumea (l/ha) 1000e2400 1000e2400 1000e1000

a 25th percentilee75th percentile.

J.P. Cunha et al. / Crop Protection 42 (2012) 116e123120

where RIResidents is the RI for residents, DEResidents the dermal expo-sure (mg/person/day), AbDE the dermal absorption factor (0.1according to Garreyn et al. (2007)), IResidents the inhalation exposure(mg/person/day), AbI the inhalation absorption factor (1.0 accord-ing to Garreyn et al. (2007)), BW the body weight (70 kg) and AOELthe acceptable operator exposure level (mg/kg body weight/day).

Because the last tree row is typically placed at 3 m distance fromthe field edge in order to allow tractor displacement, we calculatedrisk indicators for water organisms, earthworms and bees at 3 mdownwind, this representing the worst-case scenario. By consid-ering risk indices at different distances downwind from the field, itwas possible to define the minimumwidth of a buffer zone neededto avoid the risk of pesticide drift.

3. Results and discussion

3.1. Characterization of foliar pesticide applications in the Spanishcitrus regions

Interviews showed that farms between 1 and 10 ha area pre-vailed and were basically managed by their owners. However,technicians managed larger farms, especially those of more than50 ha. In any case, trees were around 6e20 years old and spacingwas 4.5e6 m by 3e6 m.

Air-blast sprayers were the most common machines employed(58%) in foliar applications, followed by hand-held gun hydraulicsprayers (42%). With regard to the age of the equipment, 65% of theair-blast sprayers were less than 5 years old while 75% of gunsprayers were over 5 years old. This difference is due to increasinglabour costs, which result in farmers relying progressively on moremechanised applications. Because this trend has been accentuatedin the last few years, and air-blast sprayers produce more drift thangun sprayers (Meli et al., 2003), we used only data from air-blastsprayer treatments in the risk assessment part of this work.

The main operational characteristics of air-blast sprayers areshown in Table 1. According to the interviews, foliar applicationsfrom air-blast sprayers covered 7.4 ha per day. An average sprayingtime of 70 min per hectare was used to calculate pesticide inhala-tion risk. Applications are normally made in spring and in the endof summer. Some applications for lemon trees are also scheduled inJuly. Insecticides were the most widely used products for orangeand tangerine units and accounted for 50% of all treatments, fol-lowed by foliar fertilizers and plant growth regulators (20%), acar-icides (10%) and fungicides (10%). For lemons, insecticideapplications made up 60% of treatments and the remaining 40%were acaricide applications.

Table 2Use and toxicity data of the pesticides commonly used in the citrus regions of Spain.

Active substance Usea Numberof applicationsper year

Spray volume(l/ha)

Applied do(kg a.s./ha)

2,4-D P 1e2 1977 0.024Abamectin I 1e2 3500 0.025Chlorpyrifos I 1e3 4016 4.016Copper oxychloride F 0e2 1977 1.977Fosetyl-aluminium F 1e3 1977 4.745Gibberellic acid P 0e2 1977 0.016Hexythiazox A 0e1 4016 0.094Mancozeb F 1e2 1977 5.190Pyriproxyfen I 0e1 4016 0.301Tebufenpyrad A 0e1 4016 0.281

a A: acaricide; F: fungicide; I: insecticide; P: plant growth regulator.b Min(NORMwater): the toxicological reference used for water organisms.c Vu: value unknown.d AOEL: acceptable operator exposure level.

Table 2 lists the primary a.s. used in citrus areas of Spain.The 90th percentile values of spray volumes reported in the

questionnaires were calculated to be used in risk assessment, giventhat they provide theworst-case scenario. Following this reasoning,a spray volume of 1977 l/hawas considered for fungicides and plantgrowth regulators, and 4016 l/ha for insecticides and acaricidas. Forabamectin, a spray volume of 3500 l/ha was used, because this isthe maximum permitted by Spanish legislation. These regulationsdo not specify a maximum spray volume for the other products.

In Spain, labels indicate the concentration of plant protectionproduct in the tank, but farmers and technicians determine sprayvolume, and consequently, the amount of product applied per unitarea. Increasing spray volume while maintaining pesticideconcentration leads to significant increases in risk given that theamount of chemical applied per unit area is an important compo-nent in predictive models of environmental risk.

3.2. Assessment of risks

3.2.1. Aquatic organisms, earthworms and beesRIs corresponding to water organisms, earthworms and bees

that are calculated using predicted drift at 3 m, resulted in the sameconclusion independently of the drift model chosen (Tables 3 and4) although predicted drift percentages are different. This is dueto the fact that toxicological data have more weight in the calcu-lation of RIs than drift values. This indicates the importance forpesticide manufacturing industry to investigate new products withlow risks and farmers to seek safer pesticides.

According to Vercruysse and Steurbaut (2002), RI values lessthan one are considered safe while values greater than one indicaterisk. Aquatic organisms 3 m away from the field may be at riskwhen applying abamectin, chlorpyrifos, cooper oxychloride, man-cozeb, pyriproxyfen or tebufenpyrad as the values of RI were higherthan one. Moreover, even with a 20 m buffer zone, aquatic organ-isms may be still at risk, except for pyriproxyfen in the three drift

se Min(NORMwater)b

(mg/l)LC50 earthworms

(mg/kg soil)LD50 bees

(mg a.s./bee)AOELd

(mg/kg/day)

1.9 350 100 0.150.00012 16.5 0.002 0.0030.001 129 0.059 0.010.008 489.6 12.1 0.07229.6 1000 462 5143 Vuc 5 60.36 105 112.2 0.0090.073 299.1 140.6 0.0350.27 1000 74 0.040.019 20.5 6.7 0.01

Table 3Assessment of risks for the aquatic organisms and earthworms for pesticides commonly applied in the citrus regions of Spain, based onworst-case scenario doses and differentdrift models.

Active substance Based on German model Based on IMAG model Based on Meli model

RIw3a BZRI ¼ 1

b RIe3c RIw3 BZRI ¼ 1 RIe3 RIw3 BZRI ¼ 1 RIe3

2,4-D 0.039 ed 0.0002 0.039 e 0.0002 0.019 e 0.0001Abamectin 660.479 >20 m 0.004 663.653 >20 m 0.004 311.488 >20 m 0.002Chlorpyrifos 21,051.456 >20 m 0.072 21,152.625 >20 m 0.073 9928.063 >20 m 0.034Copper oxychloride 777.242 >20 m 0.009 780.978 >20 m 0.009 366.555 >20 m 0.004Fosetyl-aluminium 0.504 e 0.011 0.507 e 0.011 0.238 e 0.005Gibberellic acid 0.0003 e Vue 0.0003 e Vu 0.0002 e VuHexythiazox 0.821 e 0.002 0.825 e 0.002 0.387 e 0.001Mancozeb 223.590 >20 m 0.040 224.665 18 m 0.041 105.447 >20 m 0.019Pyriproxyfen 3.509 9 m 0.001 3.525 7 m 0.0007 1.655 11 m 0.0003Tebufenpyrad 46.535 >20 m 0.032 46.758 14 m 0.032 21.946 >20 m 0.015

a RIw3: Risk indicator for water organisms at 3 m.b BZRI ¼ 1: Buffer zone at which the risk index for water organisms equals one.c RIe3: Risk indicator for earthworms at 3 m.d Buffer zone not required.e Value unknown.

J.P. Cunha et al. / Crop Protection 42 (2012) 116e123 121

models and mancozeb and tebufenpirad in the IMAG model. Inthese cases, it would be necessary to employ drift mitigationtechniques, such as low-drift nozzles, adjuvants, etc. Preciseadjustment of spray volumes may also be helpful. On the otherhand, fosetyl-aluminium, gibberellic acid, hexythiazox and 2,4-Dwould not require the establishment of buffer zones.

Ansara-Ross et al. (2008) also reported that abamectin is highlytoxic to aquatic organisms. Concentrations in water, however, areexpected to be lowmainly due to photodegradation and adsorptionof this pesticide by sediments. Abamectin It is also rapidly degradedby soil micro-organisms and becomes less toxic to aquatic organ-isms. In addition, Hernández-Hernández et al. (2007) discussed thehigh risk of mancozeb drift for aquatic life. The United StatesEnvironmental Protection Agency (EPA, 2002) also cites the risk ofchlorpyrifos for aquatic life and suggests constant monitoring inareas where it is used. This high risk is due to the low concentra-tions at which Daphnia spp. are affected and the high doses used inthe study area. Copper-based fungicides have been shown to affecta variety of aquatic organisms (Oliveira-Filho et al., 2004).

Calculated RIs indicate that buffer zones differ in size dependingon the model used to estimate drift for pyriproxyfen. Its applicationcould be considered safe if a 7e11 m buffer zone is kept.

When RIs are very high it is not possible to define the minimumwidth of a buffer zone, because this zone is not sufficient tomitigatethe risks. It would be important to have a specific citrus drift modelusable to at least 20 m downwind from a field.

It can be seen that RIs for earthworms at 3 m are lower than 1,regardless of the model used. This means that none of the products

Table 4Assessment of risks for bees, adult bystanders and child bystanders for pesticides commdifferent drift models.

Active substance Based on German model Based on

RIbee3a RIb8b RIc8c RIbee3

2,4-D 0.0007 0.0005 0.001 0.0007Abamectin 36.026 0.0288 0.081 36.199Chlorpyrifos 214.083 1.1484 3.231 215.111Copper oxychloride 0.514 0.0785 0.221 0.516Fosetyl-aluminium 0.032 0.003 0.008 0.033Gibberellic acid 0.0099 0.000 0.000 0.010Hexythiazox 0.003 0.030 0.0840 0.003Mancozeb 0.116 0.424 1.1927 0.117Pyriproxyfen 0.013 0.022 0.0606 0.013Tebufenpyrad 0.132 0.080 0.2261 0.133

a RIbee3: Risk indicator for bees at 3 m.b RIb8: Risk indicator for adult bystanders at 8 m.c RIc8: Risk indicator for child bystanders at 8 m.

seem to constitute a hazard for earthworms in the surroundingfields.

According to all three drift models bees at 3 m have RIs higherthan 1 for abamectin and chlorpyrifos. We highlight this becausehoney bees are also a source of income to some growers. Moreover,these pollinators are considered essential for almost all terrestrialecosystems including those dominated by agriculture and areexcellent indicators of environmental pollution (Thompson, 2003).Chlorpyrifos is acutely toxic to honey bees, consequently, itsapplication would be expected to pose a risk to bees and beneficialinsects in the area under application (EPA, 2002).

3.2.2. Human exposureCalculated RIs for the majority of the products are lower than 1

for adult bystanders and child bystanders (Table 4), and areconsidered safe. The exceptions are Mancozeb, which may posea risk to child bystanders in German and Meli models (RI > 1), andChlorpyrifos which produced RIs higher than 1 for child bystandersin all models and for adult bystanders, in German and Meli models.It is important to remark that exposure levels of child and adultbystanders can be significantly higher due to measurement posi-tions set closer than 8 m (Butler Ellis et al., 2010).

RIs for residents at 50 m are lower than 1, regardless of themodel employed (Table 5). Compared to the occupational exposureof applicators and bystanders, post-application resident exposureto pesticides used around their home is much lower. This is due tothe greater distance to the citrus grove. However, resident exposuredepends on a wider range of factors. Apart from exposure to

only applied in the citrus regions of Spain, based on worst-case scenario doses and

IMAG model Based on Meli model

RIb8 RIc8 RIbee3 RIb8 RIc8

0.0002 0.0007 0.0004 0.0005 0.00130.015 0.043 16.990 0.030 0.0860.602 1.696 100.963 1.213 3.4110.041 0.116 0.242 0.083 0.2330.001 0.004 0.015 0.003 0.0080.000 0.000 0.005 0.000 0.0000.016 0.044 0.001 0.032 0.0890.222 0.626 0.055 0.448 1.2590.011 0.032 0.006 0.023 0.0640.042 0.119 0.062 0.085 0.239

Table 5Resident risk assessment of pesticides commonly applied inthe citrus regions of Spain, based on worst-case scenariodoses.

Active substance RIResidentsa

2,4-D 0.0001Abamectin 0.0042Chlorpyrifos 0.1726Copper oxychloride 0.0114Fosetyl-aluminium 0.0004Gibberellic acid 0.0000Hexythiazox 0.0042Mancozeb 0.0617Pyriproxyfen 0.0030Tebufenpyrad 0.0114

a RIResidents: Risk indicator for residents at 50 m (Spray driftbased on German model).

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pesticide drift, residents are exposed to pesticides into their homeson clothing or shoes after walking over treated surfaces (Garreynet al., 2007). Moreover, RIs are calculated for each pesticide indi-vidually and there are not any procedure to assess risk associated tothe combination of all applied products.

In conclusion, De Schampheleire et al. (2007) did similar work byevaluating various pesticides used on winter barley, potatoes, sugarbeet and dwarf apples in Flanders. They did not find risks for earth-wormsandadult bystanders, but theydid foraquaticorganisms.Theirresults were similar to ours on citrus crops. We did not find risks forearthworms in our study, but some pesticide formulations used infruit orchards posed risks to aquatic organisms (abamectin, chlor-pyrifos, copper oxychloride, mancozeb, pyriproxyfen and tebu-fenpyrad). Moreover, we have also studied risk to child bystanders,residents and bees that were not considered by these authors, sincethey aremore important in applications to citrus in Spain.We did notfind risks for residents, but child andadult bystander andbeesmaybeat risk when applying chlorpyrifos, and child bystanders may also beat riskwithmancozeb, and also beeswith abamectin. For this reason,the present work reaches the objective of providing RI valuesspecifically produced by drift of the most commonly used pesticidesin Spanish citrus orchards and serves as a first step to determineacceptablewidths of buffer zones in Spain that can be extrapolated tomany other Mediterranean regions.

This approach could be also useful to farmers as a rapidscreening tool to help evaluate the environmental impact levels ofpest management strategies and pesticide choices. Furthermore,this study highlights the necessity of developing new low riskproducts and using drift reduction techniques.

Acknowledgements

This work was partially funded by the Ministerio de Ciencia eInnovación de España (Project AGL2010-22304-C04-01). Capes(Fundação Coordenação de Aperfeiçoamento de Pessoal de NívelSuperior), a Brazilian funding agency, is acknowledged for thefellowship (Project no.4211/10-3) given to the first author.

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