2006 - belgium · 2016. 2. 15. · 3333: unité de phytopathologie, université catholique de...

Programme de Réduction des Pesticides et des Biocides

Programma voor de Reductie van Pesticiden en Biociden

Program for Reduction of Pesticides and Biocides

Health and environmental effects of pesticides and type 18 biocides (HEEPEBI)

2006

TASK 3

Contract / Contrat P05/21(461)-C05/37

Vergucht, S.1; de Voghel, S.2; Misson, C.3 (until 31/01/06); Vrancken, C.3 (from 01/02/06); Callebaut, K.4; Steurbaut, W.1;

Pussemier, L.2 ; Marot, J.3 ; Maraite, H.3 ; Vanhaecke, P.4

1 : Department of Crop Protection, Ghent University

2: Veterinary and Agrochemical Research Centre (VAR), Tervuren 3: Unité de Phytopathologie, Université catholique de Louvain (UCL)

4: Environmental Consultancy & Assistance (Ecolas)

Health and environmental effects of Health and environmental effects of Health and environmental effects of Health and environmental effects of pesticides and type 18 biocides pesticides and type 18 biocides pesticides and type 18 biocides pesticides and type 18 biocides

(HEEPEBI)(HEEPEBI)(HEEPEBI)(HEEPEBI) Report from the contract AP/02/05A between theReport from the contract AP/02/05A between theReport from the contract AP/02/05A between theReport from the contract AP/02/05A between the Belgian Science Policy and Department Belgian Science Policy and Department Belgian Science Policy and Department Belgian Science Policy and Department of Crop Protection Chemistry, Ghent University; Veterinary and Agrochemical Research of Crop Protection Chemistry, Ghent University; Veterinary and Agrochemical Research of Crop Protection Chemistry, Ghent University; Veterinary and Agrochemical Research of Crop Protection Chemistry, Ghent University; Veterinary and Agrochemical Research Centre (VAR), Tervuren; Centre (VAR), Tervuren; Centre (VAR), Tervuren; Centre (VAR), Tervuren; Unité deUnité deUnité deUnité de Phytopathologie, Université catholique de Louvain (UCL)Phytopathologie, Université catholique de Louvain (UCL)Phytopathologie, Université catholique de Louvain (UCL)Phytopathologie, Université catholique de Louvain (UCL) and Environmental Consultancy & Assistance and Environmental Consultancy & Assistance and Environmental Consultancy & Assistance and Environmental Consultancy & Assistance (Ecolas)(Ecolas)(Ecolas)(Ecolas) Vergucht, S.Vergucht, S.Vergucht, S.Vergucht, S.1111; de Voghel, S.; de Voghel, S.; de Voghel, S.; de Voghel, S.2222; Misson, C.; Misson, C.; Misson, C.; Misson, C.3 3 3 3 (until 31/01/06); Vrancken, C.(until 31/01/06); Vrancken, C.(until 31/01/06); Vrancken, C.(until 31/01/06); Vrancken, C.3 3 3 3 (from 01/02/06); (from 01/02/06); (from 01/02/06); (from 01/02/06); Callebaut, K.Callebaut, K.Callebaut, K.Callebaut, K.4444; Steurbaut, W.; Steurbaut, W.; Steurbaut, W.; Steurbaut, W.1111; Pussemier, L.; Pussemier, L.; Pussemier, L.; Pussemier, L.2222 ; Marot, J.; Marot, J.; Marot, J.; Marot, J.3333 ; Maraite, H.; Maraite, H.; Maraite, H.; Maraite, H.3333 ; Vanhaecke, P.; Vanhaecke, P.; Vanhaecke, P.; Vanhaecke, P.4444 1 1 1 1 : Department of Crop Protection, Ghent University: Department of Crop Protection, Ghent University: Department of Crop Protection, Ghent University: Department of Crop Protection, Ghent University 2222: Vete: Vete: Vete: Veterinary and Agrochemical Research Centre (VAR), Tervurenrinary and Agrochemical Research Centre (VAR), Tervurenrinary and Agrochemical Research Centre (VAR), Tervurenrinary and Agrochemical Research Centre (VAR), Tervuren 3333: Unité de Phytopathologie, Université catholique de Louvain (UCL): Unité de Phytopathologie, Université catholique de Louvain (UCL): Unité de Phytopathologie, Université catholique de Louvain (UCL): Unité de Phytopathologie, Université catholique de Louvain (UCL) 4444: Environmental Consultancy & Assistance (Ecolas): Environmental Consultancy & Assistance (Ecolas): Environmental Consultancy & Assistance (Ecolas): Environmental Consultancy & Assistance (Ecolas)

September 2006September 2006September 2006September 2006

HealthHealthHealthHealth and environmental effects of pesticides and type 18 biocides (HEEPEBI) and environmental effects of pesticides and type 18 biocides (HEEPEBI) and environmental effects of pesticides and type 18 biocides (HEEPEBI) and environmental effects of pesticides and type 18 biocides (HEEPEBI)

TTTTABLE OF CONTENTSABLE OF CONTENTSABLE OF CONTENTSABLE OF CONTENTS TASK 3: TASK 3: TASK 3: TASK 3: RISK ASSESSMENT AND RISK ASSESSMENT AND RISK ASSESSMENT AND RISK ASSESSMENT AND CONSTRAINTSCONSTRAINTSCONSTRAINTSCONSTRAINTS

1 Impact of the behaviour of farmers and non-agricultural users in environmental

contamination and health hazards.................................................................................... 1

1.1 Constraints in the adaptation of good pesticide use practices................................... 1

1.2 Analysis of the impact of decision-supporting elements for responsible pesticide

use 4 1.2.1 Aims of the decision supporting systems.................................................................................. 4 1.2.2 Use of the decision support systems by the Belgian farmers.................................................... 4 1.2.3 Impact of the main decision support systems used in field crops on a responsible pesticide use

5 1.2.4 Impact of the main decision support systems used in fruit and vegetable crops on a

responsible pesticides use ...................................................................................................................... 8

1.3 Decision support software systems............................................................................... 9

1.4 Products labeling ........................................................................................................... 9 1.4.1 Integrated production (Belgian examples)................................................................................ 9

1.5 Conclusion.................................................................................................................... 18

2 Pesticide risk evaluation of the Belgian situation ................................................... 20

2.1 Different types of indicators for measuring the impact of pesticides...................... 20 2.1.1 “Use”-indicator (e.g. Use) ...................................................................................................... 20 2.1.2 Single-impact- indicator (e.g. Seq) ............................................................................... 20 2.1.3 Multi-impact indicator (e.g. the Dutch Environmental Indicator)............................ 21 2.1.4 Risk indicators for consumers ................................................................................................ 22 2.1.5 HArmonised environmental Indicators for pesticide Risk: HAIR (Luttik, 2004)................... 25

2.2 Evaluation of the Belgian situation for applicators and consumers with PRIBEL25 2.2.1 Risk calculations..................................................................................................................... 25 2.2.2 Data sources............................................................................................................................ 26 2.2.3 Five pesticide groups .............................................................................................................. 26 2.2.4 Nine crop groups .................................................................................................................... 27 2.2.5 PRIBEL results for the applicator on the Belgian level.......................................................... 27 2.2.6 PRIBEL results for the consumer on the Belgian level .......................................................... 41 2.2.7 Evaluation of the impact on consumers from alternative scenarios........................................ 54 2.2.8 Organic farming and Integrated Pest Management (Greenlabels) .......................................... 56

3 Biocide risk evaluation of the Belgian situation ..................................................... 60

3.1 Selection of the risk indicator..................................................................................... 60

3.2 Description of the indicator ........................................................................................ 60 3.2.1 Applicator exposure assessment ............................................................................................. 60 3.2.2 Secondary exposure assessment ............................................................................................. 70 3.2.3 Effect assessment.................................................................................................................... 74 3.2.4 Risk assessment ...................................................................................................................... 75

3.3 Uncertainties in the application of risk assessment indicator ................................. 80 3.3.1 Exposure assessment .............................................................................................................. 80 3.3.2 Effect assessment.................................................................................................................... 82

4 References ................................................................................................................. 84

HealthHealthHealthHealth and environmental effects of pe and environmental effects of pe and environmental effects of pe and environmental effects of pesticides and type 18 biocides (HEEPEBI)sticides and type 18 biocides (HEEPEBI)sticides and type 18 biocides (HEEPEBI)sticides and type 18 biocides (HEEPEBI) 1

TASK 3: TASK 3: TASK 3: TASK 3: RISK ASSESSMENT AND RISK ASSESSMENT AND RISK ASSESSMENT AND RISK ASSESSMENT AND CONSTRAINTSCONSTRAINTSCONSTRAINTSCONSTRAINTS

1111 IIIIMPACT OF THE BEHAVIOMPACT OF THE BEHAVIOMPACT OF THE BEHAVIOMPACT OF THE BEHAVIOUR OF FARMERS AND NOUR OF FARMERS AND NOUR OF FARMERS AND NOUR OF FARMERS AND NONNNN----AGRICULTURAL USERS IAGRICULTURAL USERS IAGRICULTURAL USERS IAGRICULTURAL USERS IN N N N

ENVIRONMENTAL CONTAMENVIRONMENTAL CONTAMENVIRONMENTAL CONTAMENVIRONMENTAL CONTAMINATION ANINATION ANINATION ANINATION AND HEALTH HAZARDSD HEALTH HAZARDSD HEALTH HAZARDSD HEALTH HAZARDS

1.1 Constraints in the adaptation of good pesticide use practices The following table 3-1 presents the stages in the approach of good pesticide use practices and the associated constraints (+: increase the impact, -: diminish the impact or no impact). The evaluation of the constraints is mainly based on experts' judgements and on a critical analysis of the following publications: (PHYTOFAR; Marot, Godfriaux et al. 2003; OECD 2003; CRP 2004; Hovan 2004; Maraite, Steurbaut et al. 2004; Marot 2004; OECD 2004; INRA and CEMAGREF 2005). For each measure, it is also indicated on which compartment (s) (Compt) greater impacts are expected: * Environmental compartments EC: - groundwater GW; - water organisms W; - soil S; - earthworms E; - birds BI; - bees BE; - beneficial arthropods BA; - air A. * Human compartments HC: - bystanders BY; - consumers C; - farm workers F; - applicator A. * Global (all the above cited compartments) G.


Table 3Table 3Table 3Table 3----1: different stages in the approach of good pesticide use practices and the associated 1: different stages in the approach of good pesticide use practices and the associated 1: different stages in the approach of good pesticide use practices and the associated 1: different stages in the approach of good pesticide use practices and the associated constraintsconstraintsconstraintsconstraints

Constraints Stages Economic Non-economic

Before application Direct cost Risk of yield

��

Risk of harvest

quality �� Need of

equipment Time / Work Need of training

Need of information Discomfort

Need of institutions Others Compt

Prophylactic measures climate, outlets

Rotation + - - + G

Elimination of infection sources + - - + G

Healthy plant material + - - supplying G

Resistant or tolerant varieties + +/- +/- + (on varieties) + (varieties'

assessment) supplying

G

Sowing densities, manuring… +/- +/- + + (crop needs) G

Alternative methods

Integrated pest management + + +/- + + + + + G

Organic pest management + + +/- + + + + + G

Products

Storage legal norms + + + (obligations) A, F, W

Storage recommendations + + + A, F, W

Choice - toxicity +/- +/- +/- + + (on product) + (products' assessment)

HC

Choice - ecotoxicity +/- +/- +/- + + (on product) + (products' assessment)

EC

Choice - adapted to crop phenology, pest resistances, weather…

+/- - + + (phenology,

weather forecast…)

+ (products' assessment)

G

Diagnostic / Decision making

Pest reconnaissance +

(observations) + + (on pests) +

G

Field knowledge +

(observations) + + (on plots)

G

Intervention thresholds - (� application

frequency)

+ (observations)

+

+ (economic, counting, weather

forecast…)

+

G

Weather +

(observations) +

+ (weather forecast)

+ G

Preparation

Label reading and respect - + + G

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Doses (calculation, respect) - + + (calculation) + (label) G

Individual protection + + + + A

Mixtures (possibilities and order)

+ + (label,

compatibilities) A

Tank filling (place, volume, surveillance)

- (� spillage) + (place) + (surveillance) + (volume

calculation) A, F, W, S

Application

Good equipment + good state + (purchase, maintenance)

- (losses and drift �)

+

(maintenance) +

(maintenance) + (on sprayer specifications)

+ (sprayers'

control) G

Constraints Stages Economic Non-economic

Application Direct cost

Risk of yield ��

Risk of harvest

quality �� Need of

equipment Time / Work Need of training

Need of information Discomfort

Need of institutions Others Compt

Individual protection + + + + A

Weather +/- + + (weather forecast)

+ G

Non-treated zones (water...) - +/- + +/- + W

After application

Good tank bottom management + +/- + + + W, S

Good sprayer rinsing and cleaning

+ +/- + + A, W, S

Good container management + + + A, W, S

Individual protection cleaning + + A

Individual washing + A

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1.2 Analysis of the impact of decision-supporting elements for

responsible pesticide use

1.2.11.2.11.2.11.2.1 Aims of the decision supporting systemsAims of the decision supporting systemsAims of the decision supporting systemsAims of the decision supporting systems For several years, tools have been developed to help the farmers to reason their treatments decisions. These tools take various forms, but have generally as main goal to better reason the pesticides use. They are, for the majority, based on the coupling of biological models forecasting the diseases' or pests populations' evolution in function of the climatic conditions, and rules of treatment triggering in function of noxiousness thresholds. In other words, the warning networks make it possible to foresee the probability of pests attacks, to advise the farmers in their control strategies, to optimize the interventions and reason the protection. The most adapted treatments are thus positioned at the most convenient moments. Some negative effects such as the resistances appearance must also be taken into account in the treatment strategies. To preserve the efficiency of the active substances families, some general directives (alternation with other families) or specific directives (for instance, limited number of treatments) must be implemented. These precaution measures are reminded by the decision support systems services in order to avoid or delay the appearance of these phenomena (CRP 2004); (INRA and CEMAGREF 2005). In practice, the preventive or curative treatments should not be systematic, but result from observations and reasoning carried out for each field. The observed pressure of pests, diseases or weeds must be confronted with the treatment threshold indicated by the decision support services. The treatments must also be adapted to the climatic conditions. The models forecasting the diseases and pests' evolution in function of the climatic conditions are increasingly close to reality and help the farmers to better position their treatments (if they are proved to be necessary). Concerning the herbicides, they must be applied by taking account of the field characteristics (flora, soil, resistances prevention...), the climatic conditions and the phenology stages (CRP 2004). For the farmers, the interests of the decision support systems are multiple (CRP 2004); (INRA and CEMAGREF 2005): - Reduction of ppp application (by reduction of application frequency or application targeting) � Costs reduction; � Reduction of the environmental impact. - Application of the most adapted ppp at the most convenient times � Maximum efficiency; � Best performance. However, it is important to note that according to the situation, the pest pressure, the climate, ect , following the advices released by these decision supporting elements will or not reduce the ppp applications. Indeed, in some worst cases, following the warnings will not lead to a ppp use reduction compared to systematic treatments.

1.2.21.2.21.2.21.2.2 Use of the decision support systems by the Belgian farmersUse of the decision support systems by the Belgian farmersUse of the decision support systems by the Belgian farmersUse of the decision support systems by the Belgian farmers As mentioned in Task 2, a survey showed that, for spraying decision, the Belgian farmers regularly consult two principal sources: the company sales representative and the decision

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support system but the company sales representative stays the most important information source. Indeed, if farmers consult regularly the crop-specific decision support systems published in newspapers or available by fax or on the Internet (depending on the crop), they do not follow their recommendations strictly. The company representatives’ advice is seen as more important. For example, only 33% of the farmers planting potatoes and 57% of the farmers planting sugar beet follow the recommendations of decision support system on when and how to spray their fields. These services are viewed as a source of information rather than a tool for deciding on treatment specifications. According to some farmers, the usefulness of these systems is restricted because the time to carry out the treatment is too short. It was also noticed that the use of decision support systems for winter wheat and sugar beet is related to the type of training a farmer had (agricultural / not agricultural). If the farmers had agricultural training they are more likely to use the decision support systems (Maraite, Steurbaut et al. 2004); (Marot, Godfriaux et al. 2003). Table 3-2 shows the evolution of the number of cereal growers which have subscribed to the CADCO warnings (see below) by fax or e-mail (CADCO). In 2005, respectively 30 and 70% of the subscribers received the warnings by e-mail and fax (Bertel, personal commentary).

Table 3Table 3Table 3Table 3----2: 2: 2: 2: Evolution of the number of cereal growers that have subscribed to the CADCO warnings by Evolution of the number of cereal growers that have subscribed to the CADCO warnings by Evolution of the number of cereal growers that have subscribed to the CADCO warnings by Evolution of the number of cereal growers that have subscribed to the CADCO warnings by fax or efax or efax or efax or e----mail (figures from CADCO and INS)mail (figures from CADCO and INS)mail (figures from CADCO and INS)mail (figures from CADCO and INS)

1999199919991999 2000200020002000 2001200120012001 2002200220022002 2003200320032003 2004200420042004 2005200520052005

462 514 827 1200 1450 1604 (16% of the Walloon cereal growers)

1815 (17% of the Walloon cereal growers)

1.2.31.2.31.2.31.2.3 Impact of the main decision support systems used in field crops on a Impact of the main decision support systems used in field crops on a Impact of the main decision support systems used in field crops on a Impact of the main decision support systems used in field crops on a responsible pesticide useresponsible pesticide useresponsible pesticide useresponsible pesticide use

In field crops, the integrated pest management remains an extremely theoretical concept. Even when the bases of reasoning exist, few farmers really seek to measure the risks related to the pests to define a technical itinerary for the protection of their cultures. For instance, the reasoning of the insecticide interventions is often extremely elementary and the treatments are still too often guided by the fear rather than by the reason. However, if well exploited, the current knowledges on pests and pesticides allow a crop protection which combines efficiency, low costs and respect of the environment (CRA-W a). To receive the warnings from these decision support systems, the farmers must generally pay an annual subscription which gives right to other personalized services. 1.2.3.11.2.3.11.2.3.11.2.3.1 CCCCEREALSEREALSEREALSEREALS

The decision support system used for cereals is coordinated by the CADCO for Wallonia (1815 members in 2005) and the LCG for Flanders (420 members in 2005). These warnings consist in official statements regularly updated by scientists on basis of observations collected in fields distributed on the whole territory. They are broadcasted by fax, e-mail, agricultural press and Internet (CADCO); (LCG); (Bertel, pers. comm.); (Wittouck, pers. comm.). Concerning the fight against Septoria, the CADCO recommend to do only one fungicide treatment positioned with the help of the PROCULTURE mechanistic interactive disease forecasting system. The Phytopathology Unity of UCL develops this software, accessible on

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the Net. With the aim of costs minimization and environment safeguarding, the software, which integrates meteorological data from PAMESEB (CRA-W) and field specific data such as sowing date, precise growth stage and one disease observation at a critical moment indicated by the system, permit to adjust the treatment strategy in function of the parasitic context of the year and the field. Experimentations performed by the Phytopathology Unity of UCL, since 2000-2001, have demonstrated the economic interest of an only well positioned fungicide treatment compared to the usual pattern with two treatments. On average, following these warnings allows to achieve a reduction of 0,6 fungicide treatment (as other diseases than Septoria must be taken into account) (CADCO); (PROCULTURE). However, it is important to note that in some worst cases, following the warnings will not lead to a ppp use reduction compared to systematic treatments. The LCG uses another stochastic disease forecasting system called EPIPRE. This model also integrates several field observations, field characteristics and meteorological data. The gain losses due to possible damages are compared with the costs of treatment. An advice of treatment is given or not in function of the application profitability (LCG). In experimentations performed in 2001 and 2002 by the POVLT, for both years, the EPIPRE system had recommended two fungicide treatments during the crop growth (Wittouck, Boone et al. 2001); (Wittouck, Boone et al. 2002). Concerning insect pests (aphids, maggots…), population counts and virological analyses are made in reference fields distributed on the whole territory. This permit to deduce the epidemic level reached in each field and to evaluate the appropriateness of a treatment. During the last thirty years, different models estimating the aphids population evolution were built but. However, despite in depth research, none proves to be really reliable. Indeed, the interactions between the factors of the aphids' proliferation are very complex. So the observations carried out in a network of reference fields aim to describe the situation in real time and to give short-term forecasts on the probable evolution (CRA-W a). In case of occasional slugs or rodents' proliferation, the warnings can also integrate advices concerning the fight against these pests in function of observations made in the fields (CRA-W a). 1.2.3.21.2.3.21.2.3.21.2.3.2 PPPPOTATOESOTATOESOTATOESOTATOES

Several organizations such as CRA-W, CARAH and PCA emit warnings for potato growers. These warnings are broadcasted by e-mail, fax, automatic telephone answering machine or in a weekly letter. In 2005, more than 1000 potato growers had subscribed to the PCA warnings, 618 potato growers to the CARAH potatoes warnings and about 250 potato growers to the CRA-W potatoes warnings (CRA-W b); (Ducatillon 2003); (PCA); (Ducatillon, personal commentary); (Dupuis, personal commentary). From the survey performed in Walloon Brabant in 2003, it was inferred that only about 33% of the potato growers follow the recommendation of decision support system (Maraite, Steurbaut et al. 2004). All the decision support systems for potato late blight use the Guntz-Divoux climatic model that was adapted in the 60's by the CRA-W. Thanks to climatic data of PAMESEB (CRA-W), this model allows to determine the optimal date for treatment that is to say one day before the outbreak of spots, in order to protect the healthy foliage from new potential contaminations while reducing the risk of product leaching or loss of product activity if it had been applied too early. Other factors will modulate the delivered warnings: spraying conditions, foliar growth, disease pressure, resistance level of the cultivated varieties and the evolution of sources of infection. Compared to a strategy of systematic weekly treatments, the warnings make it possible to carry out an effective protection of the crops while avoiding useless treatments. The farmers receive precise information concerning the epidemic situation in their region and thus can, if necessary, accelerate the spraying rhythm during periods of active growth accompanied by high pluviometry and in presence of

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sources of infection in the close environment (Michelante, Haine et al. 2002). For the period 1999-2002, the CRA-W carried out experimentations to compare the efficiency obtained by following of the warnings with the usual weekly systematic spraying pattern. This showed that it was possible to reduce the number of fungicide application to 80% while getting better results (Figure 3-1) (Michelante cited by CRP 2004).

Figure 3Figure 3Figure 3Figure 3----1111: Efficiency of the warnings system compared to the weekly systematic spraying system in : Efficiency of the warnings system compared to the weekly systematic spraying system in : Efficiency of the warnings system compared to the weekly systematic spraying system in : Efficiency of the warnings system compared to the weekly systematic spraying system in the fight against potato late blight (Michelante cited by (CRP 2004)the fight against potato late blight (Michelante cited by (CRP 2004)the fight against potato late blight (Michelante cited by (CRP 2004)the fight against potato late blight (Michelante cited by (CRP 2004)

In another study concerning organic potatoes production, the CRA-W highlighted that the application of the cupric fungicide following CRA-w warnings allows a reduction in the treatment's frequency (8 treatments for strategy following warnings to 10 for strategy of systematic weekly treatments) and a reduction in the total applied amounts (5,4 kg for strategy following warnings to 6 kg for strategy of systematic weekly treatments) while achieving a more efficient protection (Michelante, Codron et al. 2004). However, it is important to note that in some worst cases, following the warnings will not lead to a ppp use reduction compared to systematic treatments. Concerning the aphids, sources of viral infections, the services do not diffuse an advice of treatment. The given information only consists in informing the producer of a high risk or not for viral transmissions. This is based on the intensity of aphid flights measured thanks to traps, on aphids types and on crop phenology (CRA-W b). 1.2.3.31.2.3.31.2.3.31.2.3.3 SSSSUGAR BEETS AND INULIUGAR BEETS AND INULIUGAR BEETS AND INULIUGAR BEETS AND INULINE CHICORIESNE CHICORIESNE CHICORIESNE CHICORIES

The decision support system used for sugar beets and inuline chicories is coordinated by the IRBAB/KBIVB. Reference fields for observations are distributed on the whole area of beet and chicory crops of the country. On the basis of weekly observations carried out in these fields, it is possible to conclude about the suitability of carrying out (or not as it is often the case) a treatment against the observed weeds, pests or diseases. If treatment is proved to be justified, an advice of treatment is diffused to the attention of the growers, by the sugar refineries, e-mail, fax, automatic telephone answering machine, agricultural press and Internet (IRBAB/KBIVB). From the survey performed in Walloon Brabant in 2003, it was inferred that about 57% of the farmers planting sugar beet follow the recommendation of decision support system (Maraite, Steurbaut et al. 2004).

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Since 2000, sugar beets areas treated once with a fungicide vary between 60 and 80%, 3 to 4% of the areas being treated twice (Figure 3-2). This treatment can be very profitable in case of important and early contaminations by foliar diseases. However, it is very often systematically applied while not always necessary. For efficiency, profitability and respect of the environment, the fungicide treatment must be well positioned thanks to IRBAB/KBIVB warnings and personal observations in the fields (Hermann 2005); (Hermann 2003).

Figure 3Figure 3Figure 3Figure 3----2222: Fungicide treatments in Belgian sugar beet crops for the period 2000: Fungicide treatments in Belgian sugar beet crops for the period 2000: Fungicide treatments in Belgian sugar beet crops for the period 2000: Fungicide treatments in Belgian sugar beet crops for the period 2000----2003 (Hermann, 2003 (Hermann, 2003 (Hermann, 2003 (Hermann, 2005)2005)2005)2005)

Information concerning insecticide treatments during the crop growth is very difficult to obtain. However, it is estimated that less than 10% of the areas are treated once and less than 1% of the areas are treated twice. These treatments are sometimes justified in case of absence of adequate insecticide protection at sowing time. However, in most cases, that is to say with an adequate insecticide protection at sowing time (about 80% of the sowings), insecticide treatments, which are often applied during the crop growth, are totally unnecessary (Hermann 2005). Concerning herbicide application, most of the fields (about 80%) are treated before and after emergence. In post-emergence, most of the fields (40-60%) are treated tree times. The number of treatments has increased but the total applied doses have decreased since the ever more widespread use of the FAR system. This system determines specific treatment and specific product in function of the present flora (Hermann 2005). In this frame, the on-line FAR-CONSULT software gives to the farmers advices concerning date and products for treatment in function of the flora characteristics of each field (IRBAB/KBIVB).

1.2.41.2.41.2.41.2.4 Impact of the main decision support systems used in fruit and vegetable Impact of the main decision support systems used in fruit and vegetable Impact of the main decision support systems used in fruit and vegetable Impact of the main decision support systems used in fruit and vegetable crops on a responsible pesticides usecrops on a responsible pesticides usecrops on a responsible pesticides usecrops on a responsible pesticides use

The various decision support systems for vegetable and fruit crops are generally used in the frame of integrated pest management (see below). Several organizations linked to specific crops diffuse warnings based on diseases observations and pest countings made in

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growers' fields. We can cite among others PCFRUIT for fruit crops, GAWI for orchards, LAVA for some fruit and vegetable crops, PCG, CIM, CMH for some vegetable crops. In this case too, to receive the warnings from these decision support systems, the farmers must generally pay an annual subscription which gives right to other personalized services. The warnings are diffused by mail, e-mail or fax.

1.3 Decision support software systems In Belgium, different decision support software systems do already exist. These are available on CD's or on Internet. They can take various forms:

- Models of prediction of the disease or pest population evolution such as PROCULTURE. These models are used for the release of general warnings but can also be used in a personalized way by each farmer (for more details on PROCULTURE, see higher "Impact of the main decision support systems – cereals").

- Personalized models that integrate among others economic data and release advice of treatment or not in function of its economic profitability (i.e. ECO-Beta developed by the IRBAB/KBIVB).

- Systems which aim to help the farmer in the identification of the weeds, pests or diseases (i.e. Beta-Sana and FAR-Consult developed by the IRBAB/KBIVB).

The impacts of these decision support software systems on ppp's impact reduction are difficult to assess since the advices released can widely vary according to the situation and the input data.

1.4 Products labeling

1.4.11.4.11.4.11.4.1 Integrated production (Belgian examples)Integrated production (Belgian examples)Integrated production (Belgian examples)Integrated production (Belgian examples)

Integrated crop management (ICM) can be thought of as a concept defining ideals and goals which then have to be ‘translated’ into strategies which can be implemented by producers. At a basic level, the concept is simply to integrate the management tools of individual crops in order to benefit from the interactions between them. In many respects, integrating crop production strategies to provide benefits such as pest control, maintain soil fertility, etc. is an ancient technique. However, ICM also takes advantage of modern technology to improve on the system (Agra-CEAS-Consulting 2002). In other words, integrated crop management offers a way of reducing the need for pesticides. It aims to reduce costs and improve the quality of the product and of the production methods, while maintaining soil fertility and the quality of the environment. Prevention of diseases and pests has high priority. If diseases or pests are present, non-chemical control methods are preferred and chemical control is based on economic criteria and the monitoring of the soil and crops (van Loon 1992). Although ICM is a relatively new concept in Belgium, it is considered by many within the Belgian industry to be preferable to organic production as a way forward for farming. ICM in Belgium is essentially limited to fruit and glasshouse production and could probably be more accurately described as Integrated Pest Management (IPM) as a result, not least because pest control by minimization of pesticide use is one of the main objectives (Agra-CEAS-Consulting 2002).

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Currently, a report concerning the impacts of different Belgian greenlabels is under way at Ugent, ULG and CODA/CERVA (financed by the Belgian Science Policy). The main objective is to have an overview of existing labels with respect to pesticide reduction in Belgium. Originally, it was postulated to assess the sustainability of greenlabels by developing algebraic equations such as the POCER-indicator. An attempt was made, but because of the lack of data representative for the labelled/certified farming systems, it was impossible to use this methodology. Therefore a semi-quantitative method was developed to evaluate ecologic sustainability of the different labels. This method is based on a detailed assessment of the impact on sustainability of each particular rule written in the different certification books (Van Huylenbroeck, Mondelaers et al. 2006 (in press)). The selection procedure of the rules related to environmental sustainability consisted of three phases. In the first phase the rules that are obligatory according to the law were put aside. Thus only rules that give a surplus to legislation were included in the further analysis. Secondly all the rules with no significant impact on any sustainability impact item were not considered by the researchers of this study. In the third phase each of the rules was submitted to experts. They selected only those criteria that had a positive impact on a specific environmental sustainability item. For each item a maximum score was calculated. Therefore a mandatory level of 100% was attributed to all the criteria. The label scores were calculated by multiplying the mandatory level coefficient with the weight attributed to each criterion by the experts in the different disciplines. By adding the scores of the individual criteria a total score for each sustainability item was obtained The graphs shown in the following paragraphs reflect these scores (Van Huylenbroeck, Mondelaers et al. 2006 (in press)). This score represent thus the precision level in the specifications definition. This is not a quality judgement. 1.4.1.11.4.1.11.4.1.11.4.1.1 EUREPGAP EUREPGAP EUREPGAP EUREPGAP LABELLABELLABELLABEL

One of the most widespread applications of an ICM-type scheme is controlled by the Euro-Retailer Produce Working Group (EUREP), which is made up of several European food retailers with suppliers and associate members drawn from four continents. Whilst the schemes run under the auspices of this organization are not necessarily pure ICM systems (usually these schemes are considered to be less comprehensive, although some schemes may in fact be more comprehensive than ICM in some ways by including such elements as worker welfare), their development and application is relatively widespread, and as such are important. The EUREP objective has primarily been to raise standards for the production of fresh fruit and vegetables. A first draft protocol for Good Agricultural Practice (named EUREP-GAP) was discussed with growers, producer marketing organizations, verification bodies, agrochemical companies, farmer organizations and scientific institutes in 1999 and the official GAP Version 2000 subsequently released (Agra-CEAS-Consulting 2002). Concerning ecologic sustainability, the scores obtained by EUREPGAP are comparable to those of FLANDRIAGAP for most of the items. But for Noise Quantity Reduction, Climate and Rare Resource Spillage FLANDRIAGAP does score much higher. For the item Worker Safety EUREPGAP scores slightly better compared to FLANDRIAGAP. As showed in Figure 1-3, different specifications concerning pesticides have an impact on the ecologic sustainability (Van Huylenbroeck, Mondelaers et al. 2006 (in press)):

- Regarding Water quality, EUREPGAP scored average. Relevant criteria for this aspect of ecologic sustainability are among others following the correct handling and filling procedures when mixing crop protection products, keeping the application equipment in good condition and testing it yearly.

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- With respect to Waste reduction and management a rather low score was obtained. Relevant measures taken up in the certification book are the identification and secure storage of obsolete crop protection products and the disposal of them by authorized or approved channels.

- EUREPGAP does not demand a reduction in quantity of the applied amounts of pesticides, but registration is obligatory.

For each item of sustainability a maximum score was calculated based on the weights of the criteria taken up in the ideal checklist. In this respect a mandatory level of 100% was attributed to all of the rules. The label scores were calculated by multiplying the mandatory level coefficient with the weight attributed to each criterion by the experts in the different disciplines. By adding the scores of the individual criteria a total score for each sustainability item was obtained. In using the sum it is assumed that among the different technical actions compensation exists (Girardin, 2002). While calculating the label sustainability scores, several corrections had to be made. First of all a label, for example Organic farming can comply with criteria that are not explicitly mentioned in its certification book, but are taken up in one or several of the other standards. Thus Organic farming should receive an appropriate quotation for these criteria, although they cannot be found in the standard. Secondly criteria can contain only one or several elements. In the different standards the same elements can be mentioned in a single rule or in several rules. This had to be taken into account while calculating the label scores. The graphs shown in the following paragraphs reflect the scores of the different certification standards for the various sustainability items in terms of percentage. These percentages were then multiplied with a weight factor to give a visual representation of the impact of each sustainability item with respect to overall ecologic sustainability. Table 3-3 gives an overview of the weights attributed by the experts to the various sustainability items.

Table 3Table 3Table 3Table 3----3: Attributed weights for the selected items of ecologic sustainability3: Attributed weights for the selected items of ecologic sustainability3: Attributed weights for the selected items of ecologic sustainability3: Attributed weights for the selected items of ecologic sustainability

Sustainability itemSustainability itemSustainability itemSustainability item Attributed WeightAttributed WeightAttributed WeightAttributed Weight

Noise Quantity Reduction 2,54 Food Safety 8,88 Water Quality 14,04

Pest Pressure Reduction 6,24 Air Quality 13,81 Climate 11,82

Biodiversity 8,95 Landscape 8,95 Soil Fertility 9,48 Worker Safety 6,24

Waste Reduction and Management 7,87 Rare Resource Spillage 10,13

The weight factors that were attributed to the selected items were determined by applying the revised Simos’ procedure. Thereto a ranking of the environmental sustainability items had to be made. This was achieved by expert judgment. These weights can be questioned. Subjectivity plays an important role in determining these weights.

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Figure 3Figure 3Figure 3Figure 3----3333: Performance of EUREPGAP concerning ecologic sustainability (Van Huylenbroeck, : Performance of EUREPGAP concerning ecologic sustainability (Van Huylenbroeck, : Performance of EUREPGAP concerning ecologic sustainability (Van Huylenbroeck, : Performance of EUREPGAP concerning ecologic sustainability (Van Huylenbroeck, Mondelaers et al. 2006 (in press))Mondelaers et al. 2006 (in press))Mondelaers et al. 2006 (in press))Mondelaers et al. 2006 (in press))

1.4.1.21.4.1.21.4.1.21.4.1.2 FLANDRIA/FLANDRIAGAP FLANDRIA/FLANDRIAGAP FLANDRIA/FLANDRIAGAP FLANDRIA/FLANDRIAGAP LABELLABELLABELLABEL

Since 1995, the "FLANDRIA Family", part of EUREP-GAP is a Belgian quality concept for vegetables with consumer labelling and is the result of co-operation between producers, auctioneers, retailers and exporters, scientists and research stations and the Agricultural Marketing Board in Flanders. Producer organizations co-ordinate the scheme through LAVA, a group of 7 auction houses. More than 30 crops are now covered by this label with the most important being tomatoes, peppers, cucumbers, leek, cauliflower, eggplants, courgettes, fruit, lettuce and Belgian endives. The objective is to produce crops to ICM standards as far as possible in other words to use as few chemical ppp as possible so as to minimize the impact of residues on man and the environment. The scheme specifications contain thus restrictions on use of plant protection products and strict record keeping requirements (Agra-CEAS-Consulting 2002); (INTEGRA); (Van Huylenbroeck, Mondelaers et al. 2006 (in press)). The specifications also include requirements for ppp application and manipulation. In order to meet the trade and legal requirements, the auctions "Mechelse Veilingen" and "Veiling Hoogstraten" decided to extend the content of the quality label FLANDRIA by adding the FLANDRIAGAP Specifications. As a result of these specifications, the strict standards applying to FLANDRIA for hygiene, planet-friendly planting and sustainable horticulture are now set even higher. Extra attention was paid to food safety, care for the environment and the labour. The auctions "Mechelse Veilingen" and "Veiling Hoogstraten" switched over completely to the FLANDRIAGAP Specifications in 2004 (Van Huylenbroeck, Mondelaers et al. 2006 (in press)).

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Concerning ecologic sustainability of FLANDRIA and FLANDRIAGAP, it is clear that FLANDRIA does not perform well and that the new specifications added in the FLANDRIAGAP certification book were necessary. For FLANDRIA, none of the eleven sustainability items reaches a score higher than fifty percent of the maximum attainable score. As showed in figure 3-4, through the introduction of FLANDRIAGAP, most progress was made on the aspects of Worker Safety, Waste Reduction and Management and Pest Pressure Reduction. More stringent specifications for hygiene, environmentally-friendly production methods and sustainable horticulture were set. Extra attention was paid to food safety and traceability, but also to the care for the environment and the workforce. Different specifications concerning pesticides have an impact on the ecologic sustainability (Van Huylenbroeck, Mondelaers et al. 2006 (in press)):

- In the field of Pest Pressure, FLANDRIAGAP scored well. Specific to these standards is the use of the DRC cards. It is advised to only use the crop protection products mentioned on these cards. These products are considered safe for use by the POCER indicator. This indicator takes into account human, environmental and toxicity aspects. The standards also advise the use of biological pesticides in the first instance before switching to chemical alternatives. FLANDRIAGAP stimulate the farmers to use less pesticides.

- In FLANDRIAGAP the progress in the field Waste reduction and management is noticeable. Waste streams have to be located at a secure distance from water catchment areas and vegetable raw materials, below the product shelves collecting tanks have to be installed, and empty crop protection products have to be adequately stored, labelled and handled.

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Figure 3Figure 3Figure 3Figure 3----4444: Performance of FLANDRIA and FLANDRIAGAP concerning ecologic sustainability (Van : Performance of FLANDRIA and FLANDRIAGAP concerning ecologic sustainability (Van : Performance of FLANDRIA and FLANDRIAGAP concerning ecologic sustainability (Van : Performance of FLANDRIA and FLANDRIAGAP concerning ecologic sustainability (Van HuyleHuyleHuyleHuylenbroeck, Mondelaers et al. 2006 (in press))nbroeck, Mondelaers et al. 2006 (in press))nbroeck, Mondelaers et al. 2006 (in press))nbroeck, Mondelaers et al. 2006 (in press))

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1.4.1.31.4.1.31.4.1.31.4.1.3 PERFECT CPERFECT CPERFECT CPERFECT CHARTERHARTERHARTERHARTER

The PERFECT Charter (trade mark of the CMH) integrates all the requirements of the EUREP-GAP reference frame and the lawful regulations defined in the Royal Decree relating to the self-checking, the traceability and the obligatory notification. Its objective is to reach total quality in order to guarantee the safety of the product, the health of the consumer and the safeguard of the environment. Indeed, the PERFECT Charter is based on the "Integrated Crop Management System" concept which aims to increase the guarantees for the environment protection. For the season 2004, the PERFECT Charter certification concerned a hundred farms. The principal crops concerned with certification are carrots, beans, spinaches, Brussels sprouts, peas and potatoes. For each crop, a cultural form clearly defines the authorized ppp. The choice of these products is based on their ecotoxicological profile and the restrictions imposed by the customer (CMH). Concerning ecologic sustainability, on five of the eleven considered items, namely Climate Conservation, Air Quality, Food Safety, Water Quality and Rare Resource Spillage, PERFECT Charter obtained the highest score of all the certification standards under study. These high scores can partly be explained by the high degree of detail of the PERFECT Charter standard. As showed in figure 3-5, different specifications concerning pesticides have an impact on the ecologic sustainability (Van Huylenbroeck, Mondelaers et al. 2006 (in press)):

- It is specified that pesticide applicators must take off and clean their clothes on returning to the farm, workers have to attend an annual collective instruction session about hygiene and the emergency facilities have to be accessible and close by, so PERFECT Charter pays reasonable attention to the aspect of Worker Safety.

- Rules relating to the appropriate storage of pesticides and fertilisers, the correct calculation of the application rates, taking into account label instructions, application speed and application pressure, and rules concerning the registration of crop protection products are considered to have a major positive impact on the item Water Quality. Registration of the amounts of pesticides used is considered important, because through registration farmers are stimulated to develop methods aiming at reducing the applied amounts.

- For Pest Pressure Reduction item, an average score was obtained. The pest management plan promotes the principle of alternation of products. The adoption of crop rotations is also considered important for the reduction of pest pressure.

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Figure 3Figure 3Figure 3Figure 3----5555: Performance of the PERFECT Charter standard concerning ecologic sustainability (Van : Performance of the PERFECT Charter standard concerning ecologic sustainability (Van : Performance of the PERFECT Charter standard concerning ecologic sustainability (Van : Performance of the PERFECT Charter standard concerning ecologic sustainability (Van Huylenbroeck, Mondelaers et al. 2006 (in press))Huylenbroeck, Mondelaers et al. 2006 (in press))Huylenbroeck, Mondelaers et al. 2006 (in press))Huylenbroeck, Mondelaers et al. 2006 (in press))

1.4.1.41.4.1.41.4.1.41.4.1.4 LLLLEGAL SYSTEM FOR INTEGAL SYSTEM FOR INTEGAL SYSTEM FOR INTEGAL SYSTEM FOR INTEGRATED PRODUCTION OEGRATED PRODUCTION OEGRATED PRODUCTION OEGRATED PRODUCTION OF APPLES AND PEARSF APPLES AND PEARSF APPLES AND PEARSF APPLES AND PEARS

In 1996, a legal basis was established for integrated pipfruit production in Belgium. The specifications, containing all standards to be met by integrated production fruit farmers, were recorded in the Royal Decree of 22 January 1996 (INTEGRA). The IOBC defines the integrated fruit production as a high quality economic fruit production giving the priority to the ecologically surer methods, minimizing the undesirable side effects and the use of the agrochemical products, in order to improve the environmental and human health protection (Royal Decree of 22 January 1996). The specifications concerning pesticides mention that ppp can only be used as a last resort. The authorized ppp are classified in three lists in function of their toxicity for the environment and the health. The green list contains ppp that can be used when their use is justified. The yellow list contains ppp that can be used when none ppp of the green list are proved to be satisfactory for a justified and efficient use. The orange list contains ppp that can be used only after demonstration of their necessity and authorization of the certification organism. The ppp that are not included in one of these three lists can not be used. The specifications also include requirements for ppp application and manipulation (Royal Decree of 22 January 1996). Table 3-4 shows the evolution of the integrated pipfruit production in Belgium since 1998. We can see that a great majority (about 3/4) of the Belgian apples and pears are now produced under an integrated production scheme.

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Table 3Table 3Table 3Table 3----4444: Importance (in %) of integrated pipfruit production compared to total pipfruit production in : Importance (in %) of integrated pipfruit production compared to total pipfruit production in : Importance (in %) of integrated pipfruit production compared to total pipfruit production in : Importance (in %) of integrated pipfruit production compared to total pipfruit production in Belgium for the period 1998Belgium for the period 1998Belgium for the period 1998Belgium for the period 1998----2004 (figures from MRW2004 (figures from MRW2004 (figures from MRW2004 (figures from MRW----DGA and INS)DGA and INS)DGA and INS)DGA and INS)

YearYearYearYear Integrated apple Integrated apple Integrated apple Integrated apple crocrocrocrops areas ps areas ps areas ps areas

Integrated pear crops Integrated pear crops Integrated pear crops Integrated pear crops areasareasareasareas

1998 22% 31% 1999 29% 35% 2000 40% 45% 2001 65% 73% 2002 74% 75% 2003 77% 77% 2004 75% 76%

1.4.1.51.4.1.51.4.1.51.4.1.5 FRUITNET FRUITNET FRUITNET FRUITNET LABELLABELLABELLABEL

FRUITNET is a private organization which had already established specifications for integrated apple and pear production as early as 1991. The content of these specifications corresponds largely to the standards set in the legal system, but at various points these specifications go even further. Framers working in accordance with FRUITNET specifications therefore comply automatically with the legal system's standards (INTEGRA). Concerning pesticide application, the FRUITNET specifications also mention that ppp can only be used as a last resort. The classification of the products is based on the same principle as the legal system: the authorized ppp are classified in three lists in function of their toxicity for the environment and the health. However, the list of FRUITNET is more restrictive than the legal system (GAWI); (Marc, personal commentary):

- in the classification: green, yellow or orange; - in the exclusion of some active substances (the FRUITNET specifications avoid the

most toxic pesticides for the environment); - in the number of applications per annum and per hectare; - in the times of application; - within the times before harvest.

Concerning ecologic sustainability, FRUITNET certainly imposes more stringent specifications than the legal system standard (as said above). As showed in figure 3-6, different specifications concerning pesticides have an impact on the ecologic sustainability (Van Huylenbroeck, Mondelaers et al. 2006 (in press)):

- For the item Pest Pressure Reduction, results of FRUITNET and legal system are comparable. The comparable scores for this item can easily be explained since the main goal of integrated farming is to reduce the quantities of pesticides applied. Integrated farmers make use of the regulating force of nature, only intervening when really necessary. Observation systems in the orchard are used to detect the presence of pests, especially to determine the extent of their population.

- Regarding the item Air quality, FRUITNET performs relatively well, legal system slightly less. Especially the use of integrated production techniques (use of plates to catch insects, use of pheromone traps, mechanical weed treatments), the requirement of competence of the fertiliser and pesticide applicator and the reliance on an epidemiological forecast service contribute to the improvement of air quality.

- FRUITNET was ranked at first place for the item Water quality. Important to mention is that all the rules relating to this topic have a mandatory level of 100 percent. This is also the case for the legal system certification scheme. Rules considered important by the experts are the correct calculation of the pesticide dose, the

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application of pesticides in suitable weather conditions (reducing drift to watercourses), the planting of hedges along waterways to capture drift and the treatment of rinsing water after use on the farm.

- Next to PERFECT Charter, FRUITNET scored the best on the aspect of Waste reduction and management. Rules specific to FRUITNET are the establishment of an inventory of all waste products and sources of pollution, the drawing up and implementation of an action plan in order to reduce waste production and the promoting of recycling. Also required is the use of spraying systems, supplied with a system for rinsing the packages of pesticides. In comparison to FRUITNET, the legal system performed less well. Only rules related to the reduction of pesticide mixture excesses are mentioned.

The high score of FRUITNET for the items Food Safety and Worker Safety opposed to the scores of the legal system can be explained by the fact that EUREPGAP approval is a mandatory obligation required of each fruit grower wishing to market his fruit under the “FRUITNET” trademark. Technical advisers give aid by means of group sessions, individual visits and warning bulletins. FRUITNET employs the most appropriate techniques for the preservation of the environment, prohibiting the most toxic pesticides to the environment and nature and classifying products in a green, yellow and orange list in function of their degree of toxicity with respect to the environment, humans and beneficial fauna. In case of a risk of major economic damage (treatment threshold was exceeded) the grower must choose a control method. Naturally, priority must be given to natural enemies of the pest in question, but when these are insufficient the grower will have to opt for a more appropriate biological or chemical treatment. The most selective, least toxic, least persistent product, which is as safe as possible to humans and the environment, must be selected.

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Figure 3Figure 3Figure 3Figure 3----3333: Performance of legal system fo: Performance of legal system fo: Performance of legal system fo: Performance of legal system for integrated pipfruit production and FRUITNET concerning r integrated pipfruit production and FRUITNET concerning r integrated pipfruit production and FRUITNET concerning r integrated pipfruit production and FRUITNET concerning ecologic sustainability (Van Huylenbroeck, Mondelaers et al. 2006 (in press))ecologic sustainability (Van Huylenbroeck, Mondelaers et al. 2006 (in press))ecologic sustainability (Van Huylenbroeck, Mondelaers et al. 2006 (in press))ecologic sustainability (Van Huylenbroeck, Mondelaers et al. 2006 (in press))

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1.4.1.61.4.1.61.4.1.61.4.1.6 TERRA NOSTRA TERRA NOSTRA TERRA NOSTRA TERRA NOSTRA LABELLABELLABELLABEL

In 1998, the first TERRA NOSTRA potatoes were put on the market. Terra Nostra is a generic quality label being increasingly used by Walloon potato growers. The label aims to give consumers guarantees concerning quality, traceability and respect for the environment. In order to be sold under the TERRA NOSTRA brand, potatoes must be grown in Wallonia and the grower must respect the particular specifications based on good agricultural practice (integrated pest control, ppp use restricted to a positive list…) , traceability and respect for the environment. This cultivation technique enables a reduction by 30 % to 40% in the quantity of fertilisers and pesticides used (Van Huylenbroeck, Mondelaers et al. 2006 (in press)); (APAQ-W 2006). As showed in figure 3-7, various specifications concerning pesticides have an impact on the ecologic sustainability. However, the overall performance of TERRA NOSTRA on the different items of sustainability is not very good. For the item Pest Pressure Reduction, TERRA NOSTRA obtained an average score. Pest pressure reduction is achieved by using certified seed, subscribing in an epidemiologic forecast service and respecting the minimum intercrop period of three years, among other things (Van Huylenbroeck, Mondelaers et al. 2006 (in press)).

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Figure 3Figure 3Figure 3Figure 3----4444: Performance of TERRA NOSTRA concerning ecolog: Performance of TERRA NOSTRA concerning ecolog: Performance of TERRA NOSTRA concerning ecolog: Performance of TERRA NOSTRA concerning ecologic sustainability (Van Huylenbroeck, ic sustainability (Van Huylenbroeck, ic sustainability (Van Huylenbroeck, ic sustainability (Van Huylenbroeck, Mondelaers et al. 2006 (in press))Mondelaers et al. 2006 (in press))Mondelaers et al. 2006 (in press))Mondelaers et al. 2006 (in press))

1.5 Conclusion The "reasoned use of pesticides" (following warnings, models and personal observations…) makes it possible to avoid systematic applications, and especially, to reduce the applied amounts and the potential impacts, by choice of the more adapted product and moment and respect of the conditions which ensure the best efficiency.

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The interest of these techniques depends on the cultivation methods. For the European field crops, the interest lies in the economy of useless treatments. However, in the case of the most intensive cultivation methods, the frequency of potentially detrimental infestations can be relatively high and the farmer will be little incited to use decision support systems which will give him in fact little occasions to save treatments. Moreover, the agronomic durability of such a system in absence of any measure aiming at reducing the plant health risks seems to be limited. Indeed, for instance, the maintenance of pest populations right below the thresholds of noxiousness for the crops does not prevent the constitution of residual populations (weeds seeds, pathogenic fungal spores...) detrimental for the following crops. This may quickly lead to a requirement of more important treatments. Therefore, the well-build thresholds of noxiousness must take this point into account. So, the possibilities of reduction appear limited as long as one remains in farming systems that generate important plant health risks. In addition, the costs of these practices are relatively high: frequent fields' monitoring requires preliminary training in which all the farmers are not ready to invest and an important qualified working time. Such a follow-up is perhaps not very compatible with an implementation on large surfaces. This can also lead to important risks of losses in the event of diagnosis error. Indeed, the survey (Maraite, Steurbaut et al. 2004); (Marot, Godfriaux et al. 2003) showed that farmers who had not changed their practices for more pesticides sparing practices say that those practices are too costly in money, time and labour and that they fear for the external quality of their products (INRA and CEMAGREF 2005). Concerning the models used for decision support systems, they generally do not include parameters related to the farming practices. The thresholds of noxiousness or intervention are generally given under and for "intensive" farming conditions. Currently, an effort is carried out to adapt these thresholds to the agronomic situations' diversity, in particular by integrating risk factors related to farming practices and field's history. Nevertheless, most of these tools remain based on the realization of a technical optimum and thus lead to consumption behaviours. Moreover, they generally consider only the couple "one culture – one pest" and thus neglect the interactions between the various pests. Lastly, they very seldom take into account the environmental impacts of the treatments (INRA and CEMAGREF 2005) In the duration, it seems probably more effective to initially seek to reduce the plant health risks in a prophylactic way, and then, in a second time, to reason the chemical fight. In this frame, "integrated production" is a necessary step. This consists in an "alternative strategy" for crop protection, which rests on personalized implementation of some principles among which figures prevention of the plant health risks. The "integrated production" reinstates, on renewed scientific and technical bases, the management of the pests in the context of the crop systems. This management is then rather viewed as the "health of the farming systems" than as a "fight against the crops' pests". Unlike other approaches, it takes into account the diversity of the situations of production and the interactions between the different techniques (INRA and CEMAGREF 2005).

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2222 PPPPESTICIDE RISK EVALUAESTICIDE RISK EVALUAESTICIDE RISK EVALUAESTICIDE RISK EVALUATION OF THE TION OF THE TION OF THE TION OF THE BBBBELGIAN SITUATION ELGIAN SITUATION ELGIAN SITUATION ELGIAN SITUATION

2.1 Different types of indicators for measuring the impact of

pesticides Three different kinds of indicators can be distinguished: “use”-indicators, “single-impact”-indicators and “multi-impact”-indicators. In the following paragraphs, one example of each type of indicator is explained. The PRIBEL-indicator, which will be worked out in the following chapter and will be used to calculate the impact in Belgium, is an example of a multi-impact indicator.

2.1.12.1.12.1.12.1.1 “Use”“Use”“Use”“Use”----indicator (e.g. Use)indicator (e.g. Use)indicator (e.g. Use)indicator (e.g. Use)

The Use is the amount of active substance applied per hectare on a yearly basis. The underlying thought is simple: the greater the amount of pesticide applied, the greater the risk. The Use-indicator was adopted in the Dutch ‘Meerjarenplan Gewasbescherming’ (Long-range Plan Crop Protection) which postulated a reduction of 56% of the amount of pesticides applied by the year 2000 by comparison with the average amount of pesticides used in the period 1984-1988 (http://www.gewasbescherming.nl). The Use-indicator is user-friendly, but rather simplistic. It only indicates, based on the applied dose, whether or not there is a great environmental risk. However, it is not because a certain active substance is applied to a lesser extent than another active substance, that the first substance is less harmful for the environment. This substance can for instance be twice as toxic as the other one, so there is no clear interrelationship. The Use-indicator does not enable the assessor to estimate the exact potential impacts resulting from the pesticides applied. It only gives a first impression of the possible effects, and may consequently not be used as a sole instrument to assess the risk due to pesticide usage. 2.1.22.1.22.1.22.1.2 SingleSingleSingleSingle----impactimpactimpactimpact---- indicator (e.g. Seq) indicator (e.g. Seq) indicator (e.g. Seq) indicator (e.g. Seq)

The Seq-indicator is used in Belgium to visualize the evolution of the environmental impact due to pesticide use. The Seq-value, expressed in terms of distribution equivalents, is based on an exposure-effect ratio. The Seq-value describes the detrimental impact pesticides have on water organisms. Three parameters are needed to calculate the Seq-value:

- the annual amount of pesticides sold; - the degradation rate; - the maximum tolerated environmental concentration.

These three parameters are expressed in a formula used to calculate the Seq-value:

MTC

DTuseSeq 50*

=

with: use = annual applied amount of pesticide (this is derived from the annual sales figures by means of distribution code) (kg/yr) DT50 = half-life of the pesticide under consideration (yr) MTC = maximum tolerable concentration

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The Seq-indicator only takes the persistence of the pesticides in soil (by means of the DT50-value) and the risk to water life, namely algae, Crustacea and fish, into consideration. By determining the annual applied amount of pesticides (input) and the amount of that degrades (output), the amount of pesticide present in the environment is obtained. This is the concentration exposing water organisms. The Predicted No Effect Concentration (PNEC), the concentration that causes no adverse effect to the environment, is reflected by the MTC. The MTC is derived from the toxicity figures NOEC and L(E)C50 by taking extrapolation factors into account. The Seq-value indicates how many environmental-unities, expressed as a million litres, can be polluted annually up to MTC-level. Aggregation is possible by summing the different

obtained Seq-values. The Seq∑ reflects the annual distribution equivalents for a certain

pesticide. The Seq-indicator is quite easy to use, yet has some major drawbacks. The indicator takes ecotoxicological effects into account and is used to examine the global impact pesticides exert on the environment even though only the effect on water organisms is investigated. This implies that insecticides, which generally act on the nervous system, will mostly end up with an unfavourable Seq-score, because as they act on the nervous system of insects it is not inconceivable that they will exert a similar effect on water organisms (Crustacea). It should also be noted that the Seq-score is strongly depending on the size of the toxicity database. The fewer number of toxicity figures available, the higher the extrapolation factors are chosen, which results in a bigger safety margin. This, in turn, can result in wrongly considering a less toxic substance as being more toxic. As the Seq-indicator does not represent all known risks due to pesticide use (e.g. risk for human health, birds, bees, …), there was a growing need to develop a multi-impact indicator which comprises more risks as a result of pesticide use. Such approach better reflects the real situation and allows to better assess the potential risks. However, this requires much larger datasets than those needed to calculate a single-impact or Seq-indicator. 2.1.32.1.32.1.32.1.3 MultiMultiMultiMulti----impact indicator (e.g. the Dutch Environmental Indicator)impact indicator (e.g. the Dutch Environmental Indicator)impact indicator (e.g. the Dutch Environmental Indicator)impact indicator (e.g. the Dutch Environmental Indicator)

The Dutch Environmental Indicator is developed by the CLM (Centrum voor Landbouw en Milieu) in Utrecht (http://www.milieumeetlat.nl). The environmental indicator is a grading system, based on the exposure-effect ratio, which gives an idea of how damaging/harmful a product is for the environment. It is a multi-impact indicator which estimates the environmental impacts, expressed as environmental impact points, for three different impact categories: risk for water life, risk for terrestrial life and risk for ground water. The environmental indicator pursues a threefold aim:

- develop an indicator which clearly reflects the environmental load related to a certain pesticide;

- encourage farmers to take into account the environmental profile of the active substance on deciding on which product to apply;

- evaluation of the current reduction policy regarding the use of crop protection products and the achieved progress.

The environmental indicator does not assess the risk for other related impact categories (e.g. birds, beneficial arthropods, bees, …) or human health risk.

22

The general formula used to calculate the environmental score is:

Environmental impact points = dards

PEC

tan

100*

So the environmental indicator calculates the ratio of the expected environmental concentration (PEC) and the prevailing standard multiplied by 100. Environmental impact points can be calculated for every application and every impact category. Different environmental impact scores within a certain impact category can be summed. For example, by summing the scores for every insecticide applied, the total impact exerted by insecticides on water organisms can be obtained.

2.1.42.1.42.1.42.1.4 Risk indicators for consumers Risk indicators for consumers Risk indicators for consumers Risk indicators for consumers

Pesticide risk indicator can help to detect active substances and/or crops that are harmful for the health of consumers. The aim of risk indicator is to give the most precise and scientifically based information. Both qualitative and quantitative aspects of pesticide use and toxicological data are taken into account to calculate a risk. Using pesticide risk indicators allow to produce comparable information and therefore orientate a comparison. One has to see clearly here the difference between hazard and risk. Hazard is an intrinsic property that can cause adverse effects whereas the concept of risk combine the magnitude of adverse effects with the probability that such effects occur. 2.1.4.12.1.4.12.1.4.12.1.4.1 HAPERITIFHAPERITIFHAPERITIFHAPERITIF

The EU financed Harmonized environmental Indicators for pesticide Risk (HAIR) project was launched in order to provide a harmonised European approach for risk indicators. Another goal of the programme was to help governments to track temporal risk trends resulting from agricultural pesticide use at different scale (regional or national levels) and to monitor the progress in meeting their pesticide risk reduction goals. One of the indicators created in HAIR is the Harmonized Pesticide Risk Trend Indicator for Food (HAPERITIF). For the moment this indicator does not consider other sources of potential risk than those coming from the consumption of primary agricultural products such as vegetable and fruits. HAPERITIF combines and aggregates in a unique result the sum of the consumer risk values obtained for all active ingredient residues present in a particular typology of consumer diet. HAPERITIF consists in a stepwise approach (Trevisan et al., 2004):

� Quantification of pesticide residues on crops. If existing, monitoring data on primary crops are used as it is the most realistic scenario, otherwise prediction models or MRL can be used to calculate crop residues.

� Prediction of pesticide residues on foods. This second step for the calculation of the indicator will be applied only on crops that are further transformed after the harvesting. To avoid overestimation of exposure, it is necessary to include a factor accounting for the effects of crop processing techniques like hydrolysis due to pasteurization, baking, brewing, boiling etc. If such information are lacking, the indicator adopt a worst case approach, considering that no losses of pesticide occur during the transformation processes.

� Determination of consumer exposure. Chronic and acute intakes are determined on the basis of the guidelines and diets lists of the World Health Organisation. The indicator for consumer can be computed as :

23

WeightBody

nConsumptio FoodDaily x ionConcentrat Chemical FoodExposureDietary =

where Food Chemical Concentration is either same as MRL or weighted average of monitoring results ; Daily Food Consumption is the individual or averaged ingested amount of food (g/day), regional or national estimate ; Body Weight is standard/estimate (e.g. adults 60 kg, children 15 kg). Two different approaches lead to the Estimated Short Term Intake (ESTI, acute exposure) ant to the Estimated Daily Intake (EDI, chronic exposure).

Calculation of the indicator HAPERITIF based on the ratio between the exposure and the toxicological endpoint. Chronic exposure is compared to ADI, whereas acute exposure is compared to the ARfD. The indicator HAPERITIF is the ratio between EDI and ADI, or ESTI and ARfD. If the indicator has to be given for several residues in several commodities, the risk is the 95thpercentile of the sum of the ratios Exposure/Toxicity for each residues present in each commodity. 2.1.4.22.1.4.22.1.4.22.1.4.2 HERPHERPHERPHERP

The ranking scale developed by Ames et al. (1987) does not suit for calculating a risk, but it does serve to point out carcinogenic compounds that may be of greater concern than others. The Human Exposure Rodent Potency (HERP) ratio is based on human exposure to pesticide and carcinogenic data. As most of the data available is for rodent carcinogens, the ratio does not include human carcinogenic data. The greater the human exposure to the rodent carcinogen or the greater the potency of the carcinogen in rodents, the higher the Human Exposure/Rodent Potency ratio. This ranking suggests that carcinogenic hazards from current levels of pesticide residues or water pollution are likely to be of minimal concern relative to the background levels of natural substances, though one cannot say whether these natural exposures are likely to be of major or minor importance. The HERP index, indicates what percentage of the rodent carcinogenic dose (TD50 in mg/kg/day) a human receives from a given average daily exposure for a life time (mg/kg/day) (Gold et al., 2001). As an example, for coffee, the HERP index equals to 0,1.

� Average daily exposure : 13,3g � Human dose of rodent carcinogen : Caffeic acid – 23,9mg � Potency TD50 (mg/kg/day) for rats : 297

2.1.4.32.1.4.32.1.4.32.1.4.3 QSTARQSTARQSTARQSTAR

For carcinogenic pesticides US Environmental Protection Agency determines a quantitative estimate of a pesticide's carcinogenic potency, called a "Q*" (or Q star). To calculate a "Q*," EPA uses evidence of cancer incidence in lifetime chronic animal feeding studies (US EPA, 2004). EPA also assumes:

� that human health effects would correspond to health effects observed in animals; � that there is a linear dose-response (no threshold model) relationship at low doses,

so that the mathematical models used to extrapolate from high dose to low dose correctly predict the odds that the chemical will cause cancer in humans.

This means that any dose above zero engenders some level of risk. To cope with uncertainties, the odds are expressed with a 95 percent confidence level. This means that

24

from animal data, usually based on three dose levels, the maximum dose-effect relationship is calculated. Then another slope, called the Q*, is calculated. This Q* is generally the upper 95 percent confidence interval, which is interpreted to mean that the probability is 0.95 that the actual value is not greater than this estimate. The Q* is then used to determine the concentrations of the chemical in the diet that are associated with theoretical upper-bound excess lifetime cancer risks of 1 in 10,000, 1 in 100,000, and 1 in 1,000,000 (10-4, 10-5, 10-6 respectively) individuals over a lifetime of exposure. In the list of "Chemicals Evaluated for Carcinogenic Potential", some pesticides have a Q* value when the pesticide is suspected to be carcinogenic. These products were evaluated and classified by either the Office of Pesticide Programs (OPP) Cancer Assessment Review Committee (CARC) or OPP Hazard Identification Assessment Review Committee (HIARC). 2.1.4.42.1.4.42.1.4.42.1.4.4 MOEMOEMOEMOE

In its opinion, the Scientific Committee (SC) of the European Food Safety Authority (EFSA) recommends a harmonized concept using the “Margin Of Exposure” (MOE), a methodology that does enable the comparison of the risks posed by different genotoxic and carcinogenic substances (EFSA, 2005b). The margin of exposure (MOE) is the ratio between a defined point on the dose-response curve for the adverse effect and the human intake, and therefore it makes no implicit assumptions about a “safe” intake. This approach allow the determination of possible impact on human health. The MOE approach uses a reference point, often taken from an animal study and corresponding to a dose that causes a low but measurable response in animals. This reference point is then compared with various dietary intake estimates in humans, taking into account differences in consumption patterns. Therefore the following steps need to be taken to calculate MOE :

� selection of an appropriate reference point from the dose-response curve for comparison with human intake

� estimation of human dietary exposure � calculation of an MOE

MOEs are calculated by dividing the reference point, e.g. BMDL10 or T25, by the estimated human intakes. The Scientific Committee recommends the use of the benchmark dose (BMD) to obtain the MOE (lower 95% confidence interval on dose giving a 10% response). The benchmark dose is a standardised reference point derived from the animal data by mathematical modelling within the observed range of experimental data. In general, the Scientific committee consider that an MOE of 10,000 or higher, if it is based on the BMDL10 from an animal study, would be of low concern from a public health point of view and might be considered as a low priority for risk management actions. 2.1.4.52.1.4.52.1.4.52.1.4.5 % % % % OF OF OF OF ADIADIADIADI

This simple parameter compares Theoretical Maximum Residue Contributions (TMRCs) with the ADI (mg/kg b.w./day). This can be done for some selected pesticides, calculating the percentage of the ADI reached by the TMRC. This parameter was used by Winter (2001) to conduct the assessment of the dietary risks from pesticide residues.

25

2.1.52.1.52.1.52.1.5 HArmonised environmental Indicators for pesticide Risk: HAIR (Luttik, HArmonised environmental Indicators for pesticide Risk: HAIR (Luttik, HArmonised environmental Indicators for pesticide Risk: HAIR (Luttik, HArmonised environmental Indicators for pesticide Risk: HAIR (Luttik, 2004)2004)2004)2004)

Harmonised environmental Indicators for pesticide Risk (HAIR) is an EU funded specific targeted research project for the development of harmonised indicators for the risk of pesticides. This project will support Community policies for sustainable agriculture by providing a harmonised European approach for indicators of the overall risk of pesticides. It will integrate European scientific expertise on the use, emissions and environmental fate of pesticides and their impact on agro-ecosystems and human health, in order to learn and understand the limitations of existing approaches and develop improved indicators. The main deliverable of the project is a set of harmonised environmental and human health risk indicators, implemented in an easy to use software package. The proposed tool will include methods to predict environmental fate and exposure, and the resulting acute and chronic risks for aquatic and terrestrial organisms, for groundwater, for public health (including pregnant women) and for pesticide applicators. Consistent database structures will be developed for soil, climate, land use, agricultural practice, pesticide use and ecotoxicological data, to enable the harmonised use of the indicators at the distinguished scales. State-of-the-art methods will be used to extrapolate from test animals to humans and wildlife, and the indicators will include chronic risks based on sub-lethal effects as well as acute risks. The project will use existing data sets to systematically evaluate the validation status of the indicators, including information gathered by regional and national organisations. The indicator outputs will be available on different scales, providing high resolution results at the catchment/regional level, taking account of local conditions of soil, climate etc., and also aggregated and integrated results at the national and European level. The indicators will provide new and powerful assessment tools for monitoring and managing the overall risks of pesticides. This will contribute directly to Agenda 2000 aims for sustainable agriculture, and to the 6th Environment Action Programme’s Thematic Strategy on the Sustainable Use of Plant Protection Products.

2.2 Evaluation of the Belgian situation for applicators and consumers

with PRIBEL For the two compartments applicator and consumer, the formulas of the POCER (Pesticide Occupational and Environmental Risk Indicator) are used (Vercruysse, 2002). The POCER-indicator is based on the acceptance criteria formulated in Annex VI of the European Council Directive 91/414/EC. In Annex VI, the Uniform Principles for the evaluation and acceptance of plant protection products are set. When no data are available, default values will be used. Generation of specific higher tier scenarios can only be performed when data from product specific exposure studies and dermal penetration studies are available.

2.2.12.2.12.2.12.2.1 Risk calculationsRisk calculationsRisk calculationsRisk calculations

Within the framework of HEEPEBI, we decided to apply the PRIBEL-indicator for the Belgian context. The year 2001 is used as reference year, to comply with the Federal Reduction Programme for Pesticides. From all indicators presented previously, PRIBEL-indicator is the one for which we have a complete access to databases and tools required to use the

26

indicator. Since the indicator uses Belgian data (eg. pesticide sales, type of pesticide applications), its outputs can be useful to give an idea of what may be the risky pesticide applications for Belgian applicators and consumers. Special attention will be given to the riskiest pesticide/commodity combination as well as the contribution of each crop group to the total risk in Belgium. Basically the PRIBEL is given by:

PRIBEL value = RI * F

With the PRIBEL value being the total risk for Belgium, calculated by multiplying the pure risk index RI with the frequency F. The RI values come from calculations of the software PRIBEL using the formulas for calculating the risk for applicators and consumers considering the physico-chemical and ecotoxicological data, whereas the frequency is derived from national Belgian sales data coupled with the used amount of pesticide per crop (Vergucht et al, 2006). First some preliminary results are given, followed by the results per pesticide group and per crop group.

2.2.22.2.22.2.22.2.2 Data sourcesData sourcesData sourcesData sources

To calculate the results with PRIBEL a lot of inputdata were required. They are collected in a database owned by UGent and are obtained from the following sources:

� Kg of active substance yearly applied in Belgium: Studies Van Lierde � Sales of active substances per year in Belgium: FOD VVVL, pers. comm. � Ecological and toxicological values: these data are collected in the database of

UGent, and obtained from the following sources (in order of importance): 1. European Union 2. CTB – The Netherlands (http://www.ctb-wageningen.nl/) 3. Pandora’s Box (Linders et al., 1994) 4. The Pesticide Manual (Tomlin, 2004) 5. Extoxnet (http://extoxnet.orst.edu/) 6. Toxnet (http://toxnet.nlm.nih.gov/) 7. Other sources

2.2.32.2.32.2.32.2.3 Five pesticide groupsFive pesticide groupsFive pesticide groupsFive pesticide groups

Five pesticide groups can be distinguished: insecticides, fungicides, herbicides, soil disinfectants and non plant protection products. The last category has been made up but the results were not satisfying due to a lack of correct and complete data. Therefore the authors of this report ask the risk managers of the federal authorities to drop the results of the non plant protection products until more ecotoxicological information about these substances is available. In table 3-5 the composition of the different pesticide groups is listed.

27

Table 3Table 3Table 3Table 3----5: Composition of the different pesticide groups5: Composition of the different pesticide groups5: Composition of the different pesticide groups5: Composition of the different pesticide groups

Pesticide groupPesticide groupPesticide groupPesticide group CompostionCompostionCompostionCompostion

Insecticides Acaricides, insecticides, rodenticides, molluscicides, moleicides

Fungicides Fungicides, bactericides Herbicides Herbicides, defoliants, antimosses, growth

regulators, germ inhibitors Soil desinfectants Soil desinfectants, nematicides,

desinfectants Non plant protection products Additives, repellents, bandages, emulsions,

curing agents

2.2.42.2.42.2.42.2.4 Nine crop groupsNine crop groupsNine crop groupsNine crop groups

A distinction has been made between nine crop groups, according to the available data and the importance of the culture for the Belgian situation. The exact composition of the different groups is mentioned in the table below (table 3-6).

Table 3Table 3Table 3Table 3----6: Composition of the different crop grou6: Composition of the different crop grou6: Composition of the different crop grou6: Composition of the different crop groupspspsps

Crop groupCrop groupCrop groupCrop group CompositionCompositionCompositionComposition

Potato Potato Orchard Apple, pear, nursery Cereal Barley, wheat Sugarbeet Sugarbeet Maize Maize, corn Fodder Temporary grassland, permanent grassland Vegetables Chicory, leek, bean, spinach, carrot,

cabbage, pea Industrial Flax, colza Greenhouse Tomato, lettuce

2.2.52.2.52.2.52.2.5 PRIBEL results for the applicator on the Belgian levelPRIBEL results for the applicator on the Belgian levelPRIBEL results for the applicator on the Belgian levelPRIBEL results for the applicator on the Belgian level

The POCER-indicator contains formulas for the pesticide operator, the farm worker and the bystander. The PRIBEL-indicator only calculates the risk for the pesticide operator. The three compartments are discussed below to give a complete overview, but the calculations and graphs created further on in this study consider only the risk for the pesticide operator, as the calculations are executed with PRIBEL. 2.2.5.12.2.5.12.2.5.12.2.5.1 FFFFORMULASORMULASORMULASORMULAS

2.2.5.1.12.2.5.1.12.2.5.1.12.2.5.1.1 PPPPESTICIDE OPERATORESTICIDE OPERATORESTICIDE OPERATORESTICIDE OPERATOR

Pesticide operators are persons who mix, load and apply the pesticides. The risk index for pesticide operators (RIoperator) is calculated as the quotient of the internal exposure (IEoperator) and the acceptable operator exposure level (AOEL), both expressed in mg/kg body weight/workday). The internal exposure (IEoperator) is calculated using the EUROPOEM model.

28

AOEL

IERI

operator

operator =

The internal exposure (IEoperator) is calculated using the approach described below.

napplicatioloadingmixingoperator IEIEIE += /

• [ ])**()(/ DhandhandIIIloadmix AbPPELAbPPELIE +∗∗=

• [ ])()**()( DbodybodyDhandhandIIInapplicatio AbPPELAbPPELAbPPELIE ∗∗++∗∗=

( ), /( )

op acute mix load application treated

ARRI IE IE Area

BW AOEL= + ∗ ∗

∗

With:

� LI, Lhand, Lbody (mg a.s./kg a.s.): data on exposure

1. If field data on exposure are available for the different routes of exposure, these values should be used to calculate the internal exposure. These field data should be expressed as mg a.s./kg a.s. These data should be used to calculate the indicator for the real situations for particular locations.

2. If field data on exposure are not available for a given crop and a given active substance, surrogate exposure values from the EUROPOEM database are used. The appropriate surrogate exposure values for mixing/loading and application dependent on application equipment and formulation type are selected.

Annex 3.1 gives an overview of the surrogate exposure values used in the EUROPOEM model.

� PPEI, PPEhand, PPEbody: personal protective equipment coefficients

If there are no specific data available regarding the reducing effect of Personal Protective Equipment, the default factors used in EUROPOEM should be applied. These factors are given in Annex 3.1.

� AbI, AbD: respectively inhalation and dermal absorption factors

If there are data available regarding the dermal absorption of a specific active substance, these data should be used. For a great deal of active substances European endpoints are available regarding dermal absorption. If not, the default value of 10% should be used. For the inhalation absorption factor a default value of 100% is assumed.

� AR: application rate (kg/ha)

29

� Area treated (ha/d)

� BW: body weight (kg)

� AOEL: Acceptable Operator Exposure Level (mg a.s./(kg b.w. d)) Seed treatment, application of granules, dipping into pesticide solution or pouring pesticide solution onto plants are other ways of pesticide application for which operator exposure is normally not assessed by the human exposure models. In these cases some assumptions have to be made.

• When treated seed is used no exposure of the operator is expected, since seeding is mostly done mechanically.

• Operator exposure during application of granules is only expected during mixing and loading, it will be estimated by assuming exposure during mixing and loading of a water dispersible granule (WG) formulation.

• Operator exposure during the use of a pesticide solution for dipping or pouring is estimated by assuming exposure during mixing and loading of a certain formulation (WG, WP or liquid).

2.2.5.1.22.2.5.1.22.2.5.1.22.2.5.1.2 FFFFARM WORKERARM WORKERARM WORKERARM WORKER

Workers who come into contact with the crop will be contaminated by contact with pesticides that are still available on the crop after application. Exposure during re-entry tasks, such as harvesting, bending and tying up of the crop is likely in the case of ornamentals, vegetables and fruits. Inhalation exposure is very low compared to the dermal exposure, therefore only the dermal exposure of the worker is estimated. DE = 0.01 * (AR/LAI) * TF * T * P

� DE : dermal exposure (mg/day) � 0.01: conversion factor for the units � AR : application rate (kg a.s./ha) � LAI: leaf area index (m²/m²) � TF: transfer factor (cm²/person/h) � T: duration of re-entry (h) � P: factor for PPE (no PPE: 1; with PPE: 0.1)

The internal exposure is calculated as the dermal exposure (DE) multiplied by the dermal absorption factor (AbDE) and must be divided by the body weight (BW, default: 70 kg) of the worker.

BW

AbDEIE DE

wor

*ker =

For risk assessment the internal exposure is compared with the AOEL.

AOEL

IERI wor

worker

ker =

30

2.2.5.1.32.2.5.1.32.2.5.1.32.2.5.1.3 BBBBYSTANDERYSTANDERYSTANDERYSTANDER

Exposure of bystanders can only occur during application via drift. Bystanders, walking alongside a field which is being treated, are exposed only for a few seconds when the sprayer moves along the person. Repeated exposure is unlikely, since the sprayer is considered to only pass along the edge of a field for each spraying swathe. It is assumed that only ordinary clothing is worn; the total uncovered area amounts to 0.4225 m². Bystanders are assumed to be located at 8m distance downwind from the treated field. The default drift values are taken from the Ganzelmeier tables (Ganzelmeier et al, 1995). The exposure will occur by dermal and inhalatory route. It can be postulated that the dermal exposure is directly correlated to the amount of active substance applied per area, the area of the uncovered body surface contaminated and the drift distance. DE = AR * drift * EA

� DE = dermal exposure (mg/person/day) � AR = application rate (mg a.s./m²) � Drift = downwind pesticide ground deposits at 8m distance from the field

(Ganzelmeier tables) � EA =exposed area (m²/person/day) (default: 0.4225)

The inhalation exposure is calculated as for the operator (using the EUROPOEM model but only considering inhalation exposure) but the exposure time is only 1 minute instead of the total exposure time of the applicator. I = Ia * WR * AR / (WR * ST)

� I = bystander inhalation exposure (mg/person/day) � Ia = applicator inhalation exposure (mg/kg a.s.) � WR = work rate (ha/day) � AR = application rate (kg a.s./ha) � ST = spraying time (min/ha)

For risk assessment of bystanders, the internal exposure of the bystander has to be compared with the AOEL. The risk index for bystanders is calculated with the following formula

AOELBW

AbIAbDERI IDE

derbys*

**tan

+=

� DE = dermal exposure (mg/person/day) � AbDE = dermal absorption factor (%/100) (default : 10) � I = bystander inhalation exposure (mg/person/day) � AbI = inhalation absorption factor (%/100) (default : 100) � BW = body weight (kg) (default : 70)

Bystander exposure when spraying greenhouse crops and when applications are performed with treated seed, granules, dipping a plant in a pesticide solution or pouring a pesticide solution to a plant is considered negligible. In these cases the RIbystander is equal to zero.

31

2.2.5.22.2.5.22.2.5.22.2.5.2 PPPPRELIMINARY RESULTSRELIMINARY RESULTSRELIMINARY RESULTSRELIMINARY RESULTS

The data for estimating the risk for the applicators in Belgium are calculated for the year 2001, which is the reference year established in the Federal Pesticide Reduction Programme. Out of the 1016 different application cases included in PRIBEL (pesticide-crop combinations):

• 926 have a PRIBEL quantified value for the applicator compartment

• None have a NR value, which would mean that the application case is not relevant for the applicator.

• 90 have a “/” as PRIBEL value, which means that some ecotoxicological data were missing for these application cases. It concerns mostly non plant protection products (nppp), such as oils and acids.

2.2.5.32.2.5.32.2.5.32.2.5.3 OOOOVERALL RESULTSVERALL RESULTSVERALL RESULTSVERALL RESULTS

2.2.5.3.12.2.5.3.12.2.5.3.12.2.5.3.1 PPPPESTICIDE GROUP AGGREESTICIDE GROUP AGGREESTICIDE GROUP AGGREESTICIDE GROUP AGGREGATIONGATIONGATIONGATION

In the table below (table 3-7) an overview is given of the total risk (RI*F) of the 5 different pesticide groups (fungicides “FUNG”, herbicides “HERB”, insecticides “INSE”, non plant protection products “NPPP” and soil disinfectants “SODE”). Concerning the total risk per group (without taking the frequency into consideration), the soil disinfectants seem to be the riskiest group for the applicator, moreover because the number of application cases is very low (only 9). Hence, (one or some of) the active substances within the SODE group must have very high risk indices. This will be clear when discussing the individual pesticide groups. The total PRIBEL sum (RI*F) is the highest for the fungicides, while the total risk RI is stuck on the third place after SODE and INSE. Hence the high PRIBEL sum for the FUNG is due to the high frequency of use of those products. The values of the third column “PRIBEL sum” are converted into percentages in the fourth column “% of total risk”. The last column provides the number of application cases, which is the highest for the herbicides. Figure 3-8 shows the percentages of each pesticide group to the total risk in a pie chart (equal to column 4).

Table 3Table 3Table 3Table 3----7: Overview7: Overview7: Overview7: Overview of the results obtained per pesticide group of the results obtained per pesticide group of the results obtained per pesticide group of the results obtained per pesticide group

Total risk RITotal risk RITotal risk RITotal risk RI PRIBEL (sum)PRIBEL (sum)PRIBEL (sum)PRIBEL (sum) % of total risk% of total risk% of total risk% of total risk n° of application n° of application n° of application n° of application casescasescasescases

FUNG 3.87E+03 7.09 E+077.09 E+077.09 E+077.09 E+07 39.5939.5939.5939.59 288 HERB 1.96E+03 3.11 E +07 17.38 397397397397 INSE 2.01E+04 6.88 E+07 38.43 274 NPPP 1.87E+01 1.72 E+06 0.96 48 SODE 4.57E+044.57E+044.57E+044.57E+04 6.52 E+06 3.64 9 total 7.17E+04 1.79 E+08 100 1016

32

Contribution of the pesticide groups to the total risk on

applicator in Belgium in 2001

insecticides (38.43%)

fungicides (39.59%)

herbicides (17.38%)

soil desinfectants (3.64%)

nppp (0.96%)

Figure 3Figure 3Figure 3Figure 3----8: Contributions of the different pesticide groups to the total risk for applicator in Belgium, 8: Contributions of the different pesticide groups to the total risk for applicator in Belgium, 8: Contributions of the different pesticide groups to the total risk for applicator in Belgium, 8: Contributions of the different pesticide groups to the total risk for applicator in Belgium, 2001200120012001

Another interesting way to analyze the situation in Belgium for the risk for applicators is to observe the bubble chart (Figure 3-9). This figure consists of 3 important parameters: on the X-axis the frequency of the pesticide groups, on the Y-axis the median risk linked with each group, and the size of the bubbles gives the PRIBEL sum (risk index * frequency). Because of a too low number of applications the median risk could not be calculated for the soil disinfectants. There is no bubble for the NPPP as well, because of a too small number of valid risk values (a lot of “/” appear in the case of NPPP due to missing data). The HERB bubble lies on the right side of the X-axis, which corresponds with a high frequency. The size of the blue (INSE) and the red (FUNG) bubbles is more or less the same and much bigger then the yellow one (HERB), which complies with a higher total risk for fungicides and insecticides. The median risk of the three pesticide groups is situated in the same range (E+00).

33

-1.00E+00

1.00E+00

3.00E+00

5.00E+00

7.00E+00

9.00E+00

0 1000000 2000000 3000000 4000000 5000000

Frequency

Ri m

ed

ian

insecticides fungicides herbicides

Figure 3Figure 3Figure 3Figure 3----9: Median risk (Y9: Median risk (Y9: Median risk (Y9: Median risk (Y----axis) and sum of frequencies (Xaxis) and sum of frequencies (Xaxis) and sum of frequencies (Xaxis) and sum of frequencies (X----axis) of each pesticide grouaxis) of each pesticide grouaxis) of each pesticide grouaxis) of each pesticide group and p and p and p and contribution of each group to the total risk (size of bubble, sum (RI*F)) for applicator in Belgium, contribution of each group to the total risk (size of bubble, sum (RI*F)) for applicator in Belgium, contribution of each group to the total risk (size of bubble, sum (RI*F)) for applicator in Belgium, contribution of each group to the total risk (size of bubble, sum (RI*F)) for applicator in Belgium, 2001200120012001

2.2.5.3.22.2.5.3.22.2.5.3.22.2.5.3.2 CCCCROP GROUP AGGREGATIOROP GROUP AGGREGATIOROP GROUP AGGREGATIOROP GROUP AGGREGATIONNNN

In terms of crop groups pesticide applications in greenhouse crops show the highest total risk (without frequency taken into consideration). The PRIBEL value (RI*F) is the highest for potato, followed by sugarbeet, maize and cereal. The highest number of application cases can be perceived in orchards. The high value of the total risk for greenhouse crops is due to the fact that the soil disinfectant methyl bromide is used in greenhouse crops. This is explained further on in this part. The reason why greenhouse crops do not manifest a high PRIBEL value is their low frequency. Whereas potatoes have the highest PRIBEL sum, due to a relatively high total risk RI combined with a high frequency. These conclusions can be found in table 3-8. Figure 3-10 gives the contribution of the crop groups to the total risk on applicator in Belgium in the year 2001.

Table 3Table 3Table 3Table 3----8: Overview of the 8: Overview of the 8: Overview of the 8: Overview of the results obtained per crop groupresults obtained per crop groupresults obtained per crop groupresults obtained per crop group

Total risk RITotal risk RITotal risk RITotal risk RI PRIBEL (sum)PRIBEL (sum)PRIBEL (sum)PRIBEL (sum) % of total risk% of total risk% of total risk% of total risk n° of application n° of application n° of application n° of application casescasescasescases

Potato 5.54E+03 7.45E+077.45E+077.45E+077.45E+07 41.6341.6341.6341.63 95 Orchard 8.61E+02 1.00E+06 0.56 229229229229 Cereal 5.67E+03 1.97E+07 10.99 188 Sugarbeet 4.82E+03 3.70E+07 20.69 118 Maize 3.18E+03 2.90E+07 16.19 85 Fodder 8.53E+02 5.45E+06 3.04 57 Vegetables 4.61E+03 5.45E+06 3.04 127

34

Industrial crops 9.56E+01 3.64E+05 0.20 20 Greenhouse crops 4.60E+044.60E+044.60E+044.60E+04 6.55E+06 3.66

97

total 5.54E+03 1.79E+08 100.00 1016

Contribution of the crop groups to the total risk on applicator

in Belgium in 2001

Potato (41.63%)

Orchard (0.56%)

Cereal (10.99%)

Sugar (20.69%)

Maize (16.19%)

Fodder (3.04%)

Vegetables (3.04%)

Industrial (0.20%)

Greenhouse (3.66%)

Figure 3Figure 3Figure 3Figure 3----10: Contributions of 10: Contributions of 10: Contributions of 10: Contributions of the different crop groups to the total risk in Belgium, 2001the different crop groups to the total risk in Belgium, 2001the different crop groups to the total risk in Belgium, 2001the different crop groups to the total risk in Belgium, 2001

Figure 3-11 shows the frequency of use of the pesticides in the different crop groups (X-axis), the median risk (Y-axis) and the PRIBEL (RI*F) value (bubble size). Cereals show the highest frequency of pesticide use, followed by potatoes and fodder. This is mainly due to the high number of hectares of cereals, potatoes and fodder in Belgium. Maize, potato and greenhouse have the highest median risk. The highest bubble size is observed for potato, sugarbeet, maize and cereals, meaning that the highest total risk for Belgium (frequency included) is caused by the use of pesticides in those specific crop groups. This could also be noticed in the fourth column of table X and in the pie chart above.

35

0.01

0.1

1

10

100

1000

0 500000 1000000 1500000 2000000 2500000 3000000

Frequency

RI

me

dia

n

potato orchard cereal sugarbeet maizefodder vegetables industrial greenhouse

Figure 3Figure 3Figure 3Figure 3----11: Median risk (Y11: Median risk (Y11: Median risk (Y11: Median risk (Y----axis) and sum of frequencies (Xaxis) and sum of frequencies (Xaxis) and sum of frequencies (Xaxis) and sum of frequencies (X----axis) of each crop group and contribution axis) of each crop group and contribution axis) of each crop group and contribution axis) of each crop group and contribution of each group to the total risk (size of bubble, sum (RI*F)) for applicator in Belgium, 2001of each group to the total risk (size of bubble, sum (RI*F)) for applicator in Belgium, 2001of each group to the total risk (size of bubble, sum (RI*F)) for applicator in Belgium, 2001of each group to the total risk (size of bubble, sum (RI*F)) for applicator in Belgium, 2001

2.2.5.42.2.5.42.2.5.42.2.5.4 RRRRISKIEST APPLICATION ISKIEST APPLICATION ISKIEST APPLICATION ISKIEST APPLICATION CASESCASESCASESCASES

When ranked with regard to the risk index RI, methylbromide seems to be the active substance that causes the highest risk to the applicator. Lindane is mentioned 5 times in the list of the 10 riskiest application cases (above the 95th percentile of the total risk), applied in cereals (winterbarley), sugarbeet, potatoes, maize (corn) and chicory. All the active substances listed in table 3-9 belong to the insecticides and soil disinfectants. The PRIBEL value for methylbromide used in greenhouse crops is not the highest due to a low frequency. The highest PRIBEL sum for the 10 riskiest application cases is occupied by lindane in sugarbeet, because of a high RI for the applicators combined with a high frequency. That application case covers 17.42% of the total risk based on total PRIBEL values (RI*F).

Table 3Table 3Table 3Table 3----9: The 10 riskiest application cases (above the 959: The 10 riskiest application cases (above the 959: The 10 riskiest application cases (above the 959: The 10 riskiest application cases (above the 95thththth percentile of the total risk) percentile of the total risk) percentile of the total risk) percentile of the total risk)

A.S. nameA.S. nameA.S. nameA.S. name CropCropCropCrop Crop groupCrop groupCrop groupCrop group Pesticide Pesticide Pesticide Pesticide groupgroupgroupgroup

RI RI RI RI applicatorsapplicatorsapplicatorsapplicators

PRIBEL sumPRIBEL sumPRIBEL sumPRIBEL sum % of % of % of % of total total total total PRIBELPRIBELPRIBELPRIBEL

methylbromide Greenhouse crop Greenhouse SODE >40 000 3 815 453.60 2.13

lindane Winterbarley Cereal INSE >1 000 811 889.05 0.45 1.3-dichloropropene

Greenhouse crop Greenhouse SODE

>1 000

2 518 964.95 1.41 lindane Sugarbeet Sugarbeet INSE >1 000 31 731 333,00 17.72 lindane Potato Potato INSE >1 000 909 539.34 0.51 lindane Corn Maize INSE >1 000 3 846 581.66 2.15

36

sulfotep Greenhouse crop Greenhouse SODE

>1 000

32 755.27 0.02 omethoate Leek Vegetables INSE >1 000 654 095.96 0.37 ethoprop Potato Potato INSE >1 000 3 754 823.31 2.10 lindane chicory Sugarbeet INSE >1 000 317 296.05 2.13

2.2.5.4.12.2.5.4.12.2.5.4.12.2.5.4.1 RRRRESULTS PER PESTICIDEESULTS PER PESTICIDEESULTS PER PESTICIDEESULTS PER PESTICIDE GROUP GROUP GROUP GROUP

The riskiest application cases (RI above the 95th percentile) are given for each of the five pesticide groups. These active substances are classified by their risk index, without taking the frequency into account. FungicidesFungicidesFungicidesFungicides The riskiest application cases (above the 95th percentile) in the fungicides group are fentinhydroxide (in sugarbeet and potato) and fenpropimorph (in potato). This is mainly due to relatively small AOEL-values of those active substances. Fentinhydroxide in potato has a much higher PRIBEL sum than fentinhydroxide in sugarbeet, meaning that the frequency of the first application case is higher. This is due to the fact that there are a lot more hectares where potato is cultivated in Belgium than where sugarbeet grows, and also to the fact that there are more applications per hectare in one year in potato than there are in sugarbeet.

Table 3Table 3Table 3Table 3----10: Riskiest application cases for fungicides (above the 95th percentile)10: Riskiest application cases for fungicides (above the 95th percentile)10: Riskiest application cases for fungicides (above the 95th percentile)10: Riskiest application cases for fungicides (above the 95th percentile)

A.S. nameA.S. nameA.S. nameA.S. name CropCropCropCrop Crop groCrop groCrop groCrop groupupupup RI applicatorsRI applicatorsRI applicatorsRI applicators PRIBEL sumPRIBEL sumPRIBEL sumPRIBEL sum

fentin hydroxyde SugarBeet Sugar >100 277 739.42 fenpropimorph Potato Potato >100 8 833.90 fentin hydroxyde Potato Potato >100 44 521 212.50

HerbicidesHerbicidesHerbicidesHerbicides Twelve application cases have a risk index above the 95th percentile for herbicides. The use of propachlor on cabbage and corn stands on top of the list. The main reason is a relatively high application dose. Isoproturon, mcpa, metoxuron, dimethenamide, paraquat and monalide make the list complete.

Table 3Table 3Table 3Table 3----11: Riskiest a11: Riskiest a11: Riskiest a11: Riskiest application cases for herbicides (above the 95th percentile)pplication cases for herbicides (above the 95th percentile)pplication cases for herbicides (above the 95th percentile)pplication cases for herbicides (above the 95th percentile)

A.S. nameA.S. nameA.S. nameA.S. name CropCropCropCrop Crop groupCrop groupCrop groupCrop group RI applicatorsRI applicatorsRI applicatorsRI applicators PRIBEL sumPRIBEL sumPRIBEL sumPRIBEL sum

propachlor Cabbage Vegetables >50 266 770.68 propachlor Corn Maize >50 162.64 isoproturon Winterbarley Cereal >10 716 809.46 isoproturon Winterwheat Cereal >10 4 963 110.95 mcpa Winterbarley Cereal >10 181 365.04 metoxuron Carrot Vegetables >10 122 693.69 mcpa Potato Potato >10 239 073.19 dimethenamid Leek Vegetables >10 1 957.04 propachlor Leek Vegetables >10 25 283.61 paraquat Chicory Sugar >10 39 692.63 monalide Carrot Vegetables >10 215.43 paraquat Winterbarley Cereal >10 754.26

37

InsecticidesInsecticidesInsecticidesInsecticides It is not surprising that lindane is on top of the list with application cases that have a risk above the 95th percentile for insecticides. The combination of a small AOEL and a very high dermal absorption results in a high risk index for the applicator. The use of lindane in winterbarley is responsible for a risk that is much higher than for the other application cases. The reason is the application dose, which is 1.5 kg/ha for lindane in winterbarley, whereas it is 0.9 kg/ha, 0.9 kg/ha and 0.7 kg/ha for lindane in respectively sugarbeet, potato and corn.

Table 3Table 3Table 3Table 3----12: Riskiest application cases for insecticides (above the 95th percentile)12: Riskiest application cases for insecticides (above the 95th percentile)12: Riskiest application cases for insecticides (above the 95th percentile)12: Riskiest application cases for insecticides (above the 95th percentile)

A.A.A.A.S. nameS. nameS. nameS. name CropCropCropCrop Crop groupCrop groupCrop groupCrop group RI applicatorsRI applicatorsRI applicatorsRI applicators PRIBEL sumPRIBEL sumPRIBEL sumPRIBEL sum

lindane Winterbarley Cereal >3 000 811 889.06 lindane Sugarbeet Sugar >1 000 31 731 332.96 lindane Potato Potato >1 000 909 539.34 lindane Corn Maize >1 000 3 846 581.66 omethoate Leek Vegetables >1 000 654 096.00 ethoprop Potato Potato >1 000 3 754 823.31

Soil disinfectantsSoil disinfectantsSoil disinfectantsSoil disinfectants Concerning the soil disinfectants, it is clear that methylbromide causes the highest risk and is responsible for a huge part of the total risk of the soil disinfectants. It must also be noticed that all the soil disinfectants are applied in greenhouses, which causes a higher risk for the applicator because of the fact that it is an “indoor” situation. The high risk value for methylbromide is due to a small AOEL in combination with an extremely high application dose, namely 441 kg/ha.

Table 3Table 3Table 3Table 3----13: Riskiest application cases for soil desinfectants (above the 95th percentile)13: Riskiest application cases for soil desinfectants (above the 95th percentile)13: Riskiest application cases for soil desinfectants (above the 95th percentile)13: Riskiest application cases for soil desinfectants (above the 95th percentile)

A.S. nameA.S. nameA.S. nameA.S. name CropCropCropCrop Crop groupCrop groupCrop groupCrop group RI RI RI RI applicatorsapplicatorsapplicatorsapplicators

PRIBEL sumPRIBEL sumPRIBEL sumPRIBEL sum

methylbromide Greenhouse crops Greenhouse >40 000 3 815 453.60 1.3-dichloropropene Greenhouse crops Greenhouse >1 000 2 518 964.95 sulfotep Greenhouse crops Greenhouse >1 000 32 755.27

Non plant protection productsNon plant protection productsNon plant protection productsNon plant protection products The riskiest application cases for non plant protection products are the use of chlorpropham in potatoes, anthraquinon in winterwheat and streptomycin in pear.

Table 3Table 3Table 3Table 3----14: Riskiest application cases for non plant protection products (above the 95th percentile)14: Riskiest application cases for non plant protection products (above the 95th percentile)14: Riskiest application cases for non plant protection products (above the 95th percentile)14: Riskiest application cases for non plant protection products (above the 95th percentile)

A.S. nameA.S. nameA.S. nameA.S. name CropCropCropCrop Crop groupCrop groupCrop groupCrop group RI applicatorsRI applicatorsRI applicatorsRI applicators PRIBEL sumPRIBEL sumPRIBEL sumPRIBEL sum

chlorpropham Potato Potato >10 951 192.18 anthraquinone Winterwheat Cereal >1 773 267.49 streptomycin pear Orchard >1 6.77

38

2.2.5.4.22.2.5.4.22.2.5.4.22.2.5.4.2 RRRRESULTS PER CROP GROUESULTS PER CROP GROUESULTS PER CROP GROUESULTS PER CROP GROUPPPP

In the same way as for the pesticide groups, the riskiest application cases (RI above the 95th percentile) are given for each of the nine crop groups. These active substances are classified by their risk index, without taking the frequency into account. PotatoPotatoPotatoPotato The four riskiest application cases in potato involve three insecticides (lindane, ethoprop and omethoate) and one fungicide (fenpropimorph). Those four active substances are also mentioned in the lists with the riskiest application cases of insecticides and fungicides respectively.

Table 3Table 3Table 3Table 3----15: Riskiest application cases used in potatoes (above the 95th percentile)15: Riskiest application cases used in potatoes (above the 95th percentile)15: Riskiest application cases used in potatoes (above the 95th percentile)15: Riskiest application cases used in potatoes (above the 95th percentile)

A.S. nameA.S. nameA.S. nameA.S. name CropCropCropCrop Pesticide groupPesticide groupPesticide groupPesticide group RI applicatorsRI applicatorsRI applicatorsRI applicators PRIBEL sumPRIBEL sumPRIBEL sumPRIBEL sum

lindane Potato INSE >1 000 909 539.34 ethoprop Potato INSE >1 000 3 754 823.31 omethoate Potato INSE >100 288 229.04 fenpropimorph Potato FUNG >100 8 833.90

OrchardOrchardOrchardOrchard Concerning orchard, there are 11 application cases that have a risk index above the 95th percentile. Table 3-16 encompasses seven insecticides, two fungicides and two herbicides. Omethoate used in pear is on top of the list, mainly because of a very small AOEL. Omethoate was, according to the inquiries of Van Lierde, not used in apple.

Table 3Table 3Table 3Table 3----16: Riskiest application cases used in orchard (above the 95th percentile)16: Riskiest application cases used in orchard (above the 95th percentile)16: Riskiest application cases used in orchard (above the 95th percentile)16: Riskiest application cases used in orchard (above the 95th percentile)


omethoate pear INSE >500 24 933.55 methidathion apple INSE >10 20 870.84 diuron apple HERB >10 82 628.94 diuron pear HERB >10 10 246.26 parathion apple INSE >10 59 420.58 sulphur apple FUNG >10 60 616.93 amitraz pear INSE >10 43 689.76 sulphur pear FUNG >1 7 135.80 dimethoate apple INSE >1 48 328.10 endosulfan pear INSE >1 12 710.94 methidathion pear INSE >1 2 353.39

CerealCerealCerealCereal The crop group cereal consists of winterbarley and winterwheat, and most of the active substances mentioned in Table X that have a high risk for one crop (barley/wheat) also manifest a high risk for the other crop (wheat/barley). For instance lindane, sulphur, parathion and isoproturon have a mention for both the crop groups barley and wheat. Nevertheless there can be a difference in the risk index for the applicators depending on the crop group. This is due to a different application rate, e.g. the dose for lindane in winterbarley is 1.5 kg/ha, whereas it is 0.5 kg/ha in winterwheat (Van Lierde).

39

Table 3Table 3Table 3Table 3----17: Riskiest application cases used in cereal (above the 95th percentile)17: Riskiest application cases used in cereal (above the 95th percentile)17: Riskiest application cases used in cereal (above the 95th percentile)17: Riskiest application cases used in cereal (above the 95th percentile)


lindane Winterbarley INSE >3 000 811 889.06 lindane Winterwheat INSE >1 000 2 499 316.58 sulphur Winterbarley FUNG >100 20 015.29 sulphur Winterwheat FUNG >100 440 376.94 parathion Winterbarley INSE >10 21 782.60 dimethoate Winterwarley INSE >10 201 994.61 parathion Winterwheat INSE >10 144 026.72 isoproturon Winterwheat HERB >10 716 809.46 isoproturon Winterbarley HERB >10 4 963 110.95

SugarbeetSugarbeetSugarbeetSugarbeet The list of the riskiest application cases in sugarbeet consists of 13 active substances among which 6 fungicides and 6 insecticides. The risk value for lindane is strongly higher than the value for the other active substances. The combination of a small AOEL and a very high dermal absorption of lindane results in such a high risk index for the applicator.

Table 3Table 3Table 3Table 3----18: Riskiest application cases used in sugarbeet (above the 95th percentile)18: Riskiest application cases used in sugarbeet (above the 95th percentile)18: Riskiest application cases used in sugarbeet (above the 95th percentile)18: Riskiest application cases used in sugarbeet (above the 95th percentile)


lindane Sugarbeet INSE >1 000 31 731 332.96 lindane chicory INSE >1 000 317 296.04 fentin hydroxyde Sugarbeet FUNG >100 277 739.41 sulphur Sugarbeet FUNG >100 86 333.94 parathion Sugarbeet INSE >50 593 518.01 fenpropimorph Sugarbeet FUNG >50 76 470.34 parathion chicory INSE >50 6 526.22 ziram chicory FUNG >50 9 032.14 spiroxamine Sugarbeet FUNG >10 9 647.99 dimethoate chicory INSE >10 307 986.47 paraquat chicory HERB >10 39 692.63 mancozeb Sugarbeet FUNG >10 104 635.42 diazinon Sugarbeet INSE >10 450 176.21

MaizeMaizeMaizeMaize Also in the list with the riskiest application cases that appear in maize, lindane is on top with a much higher risk than the other 3 active substances which also have a risk index above the 95th percentile (parathion, mancozeb (2x) and propachlor).

Table 3Table 3Table 3Table 3----19: Riskiest application cases used19: Riskiest application cases used19: Riskiest application cases used19: Riskiest application cases used in maize (above the 95th percentile) in maize (above the 95th percentile) in maize (above the 95th percentile) in maize (above the 95th percentile)


lindane Corn INSE >1 000 3 846 581.65 lindane Maize INSE >1 000 14 636 069.49 parathion Maize INSE >50 190 269.28 mancozeb Corn FUNG >50 8 609.35 propachlor Corn HERB >50 162.64 mancozeb Maize FUNG >10 31 590.68

40

FodderFodderFodderFodder Three insecticides and two herbicides are involved in the list of the riskiest application cases used in fodder. Lindane is on top, just as it is in maize, sugarbeet, cereal and potato.

TaTaTaTable 3ble 3ble 3ble 3----20: Riskiest application cases used in fodder (above the 95th percentile)20: Riskiest application cases used in fodder (above the 95th percentile)20: Riskiest application cases used in fodder (above the 95th percentile)20: Riskiest application cases used in fodder (above the 95th percentile)

A.S. nameA.S. nameA.S. nameA.S. name CropCropCropCrop Pesticide Pesticide Pesticide Pesticide groupgroupgroupgroup

RI applicatorsRI applicatorsRI applicatorsRI applicators PRIBEL sumPRIBEL sumPRIBEL sumPRIBEL sum

lindane PermanentGrassland INSE >500 2 249 556.69 parathion PermanentGrassland INSE >100 590 897.14 diazinon PermanentGrassland INSE >10 51 931.94 isoproturon PermanentGrassland HERB >10 9 320.29 mcpa Ley HERB >10 121 658.34

VegetablesVegetablesVegetablesVegetables Besides 7 insecticides there is also a soil disinfectant and a fungicide mentioned in the list with the riskiest applications in vegetables. Omethoate on leek has a high risk for the applicator caused by a small AOEL. Omethoate was on top in the list from orchard as well.

Table 3Table 3Table 3Table 3----21: Riskiest application cases used in vegetables (above the 95th percentile)21: Riskiest application cases used in vegetables (above the 95th percentile)21: Riskiest application cases used in vegetables (above the 95th percentile)21: Riskiest application cases used in vegetables (above the 95th percentile)

A.S. nameA.S. nameA.S. nameA.S. name CropCropCropCrop Pesticide Pesticide Pesticide Pesticide ggggrouprouprouproup

RI RI RI RI applicatorsapplicatorsapplicatorsapplicators

PRIBEL sumPRIBEL sumPRIBEL sumPRIBEL sum

omethoate Leek INSE >1 000 654 095.95 parathion Leek INSE >300 969 067.23 methidathion Leek INSE >300 15 295.36 dazomet Leek SODE >100 67 774.57 acephate Leek INSE >100 38 570.81 dimethoate Leek INSE >100 59 482.14 chlorfenvinphos Leek INSE >100 123 696.14 sulphur Carrot FUNG >100 665 256.28 heptenophos Carrot INSE >100 490 713.00

Industrial cropsIndustrial cropsIndustrial cropsIndustrial crops Only two active substances (bifenthrin and mcpa) are mentioned in table 3-22 as riskiest applications in industrial crops.

Table 3Table 3Table 3Table 3----22: Riskiest application cases used in industrial crops (above the 95th percentile)22: Riskiest application cases used in industrial crops (above the 95th percentile)22: Riskiest application cases used in industrial crops (above the 95th percentile)22: Riskiest application cases used in industrial crops (above the 95th percentile)


bifenthrin Flax INSE >10 18 578.96 mcpa Flax HERB <1 114 077.77

Greenhouse cropsGreenhouse cropsGreenhouse cropsGreenhouse crops The 4 active substances which are on top in the list with application cases that have a risk index above the 95th percentile are the soil disinfectants methyl bromide, 1,3-dichloropropene, sulfotep and oxamyl. This is due to the combination of a small AOEL and a huge application dose.

41

Table 3Table 3Table 3Table 3----23: Riskiest application cases used in greenhouse crops (above the 95th percentile)23: Riskiest application cases used in greenhouse crops (above the 95th percentile)23: Riskiest application cases used in greenhouse crops (above the 95th percentile)23: Riskiest application cases used in greenhouse crops (above the 95th percentile)

A.S. nameA.S. nameA.S. nameA.S. name CropCropCropCrop Pesticide Pesticide Pesticide Pesticide groupgroupgroupgroup

RI applicatorsRI applicatorsRI applicatorsRI applicators PRIBEL sumPRIBEL sumPRIBEL sumPRIBEL sum

methyl bromide Greenhouse crop SODE >40 000 3 815 453.6 1.3-dichloropropene Greenhouse crop SODE >1 000 2 518 964.94 sulfotep Greenhouse crop SODE >1 000 32 755.26 oxamyl Greenhouse crop SODE >100 36 546.57 chlorfenvinphos Greenhouse crop INSE >100 935.60 omethoate Greenhouse crop INSE >10 2 408.74

2.2.62.2.62.2.62.2.6 PRIBEL results for the consumer on thePRIBEL results for the consumer on thePRIBEL results for the consumer on thePRIBEL results for the consumer on the Belgian level Belgian level Belgian level Belgian level

2.2.6.12.2.6.12.2.6.12.2.6.1 FFFFORMULA AND ORMULA AND ORMULA AND ORMULA AND IIIIMPROVEMENT OF THE INMPROVEMENT OF THE INMPROVEMENT OF THE INMPROVEMENT OF THE INDICATORDICATORDICATORDICATOR

The indicator was calculated for the year 2001, considered as a reference year. Data obtained trough the initial configuration of the PRIBEL software led to the underestimation of the risks. Indeed, some application cases (297 out of 1016) lacked a RIconsumers value. Besides, application cases within crop groups “vegetables” and “greenhouse vegetables” were scarce. This problem was solved by adding in the software all the MRL default values for commodities for which the pesticides are not authorized. In addition, for the sake of simplicity and of pragmatism, the formula for the calculation of RIconsumers was slightly modified as follows: Where MRL (Maximum Residue Limit; mg as/kg food); EDI (Estimated Daily Intake; kg food/kg bw/day); ADI (Acceptable Daily Intake; mg as/kg bw/day). After modifications, no significant changes were noticed in the riskiest applications within each crop group, but far less applications did lack a RI value (3 out of 1016). These changes allowed crop groups like vegetables, greenhouse vegetables or maize to be better assessed since the number of application cases with a RIconsumers quantified value noticeably increased within these groups. 2.2.6.22.2.6.22.2.6.22.2.6.2 LLLLIMITS OF THE IMITS OF THE IMITS OF THE IMITS OF THE PRIBELPRIBELPRIBELPRIBEL---- INDICAINDICAINDICAINDICATORTORTORTOR

It is important to specify the limits of the indicator before going further into results analysis. Indeed, several points need to be explained to avoid misinterpretations. The PRIBEL-indicator is giving a risk at a national level. Thus, as the indicator is influenced by the frequency of use in Belgium, it reflects the risk associated to a certain amount of food produced. In other words, if the risk associated to a crop group is high, this may be due to the fact that the mean Rlconsumers is high and/or that the amount of foodstuffs produced is high. This implies that the risk is calculated for the whole amount of food units produced in Belgium and not for an individual consumer. In this later case, indeed, the risk is distributed over many foodstuffs that are not necessarily consumed in the same proportions than they are produced in Belgium. In addition, the PRIBEL-indicator is using in its database application of pesticides on crops, but does not consider the application of post-harvest pesticides. Another point is the fact that commodities entering the Belgian market are not taken into account since they are not produced on the Belgian territory. Indeed, these commodities

×=

ADI

EDIMRLRIconsumers

42

can contain pesticides that are not registered in Belgium and therefore not integrated in the Belgian scenario of pesticide applications used by PRIBEL. The total risk produced for Belgium is not only concerning the Belgian consumers. In reality, the amount of risk can be spread on other countries since we are exporting foodstuffs in other countries. 2.2.6.32.2.6.32.2.6.32.2.6.3 PPPPRELIMINARY RESULTS RELIMINARY RESULTS RELIMINARY RESULTS RELIMINARY RESULTS

Data were calculated for the year 2001. Out of the 1016 applications cases included in the PRIBEL :

• 630 have a PRIBEL quantified value for the consumer compartment

• 383 have a NR value, which means the application case is Not Relevant for the calculation of the Rlconsumers

• 3 have a ”/” as PRIBEL value, which means that some data were lacking for these application cases

2.2.6.42.2.6.42.2.6.42.2.6.4 OOOOVERALL RESULTSVERALL RESULTSVERALL RESULTSVERALL RESULTS

2.2.6.4.12.2.6.4.12.2.6.4.12.2.6.4.1 PPPPESTICIDE GROUP AGGREESTICIDE GROUP AGGREESTICIDE GROUP AGGREESTICIDE GROUP AGGREGATIONGATIONGATIONGATION

In terms of pesticide groups, fungicides (FUNG) appear to be the riskiest group for consumers (58% of the total risk), followed by herbicides (HERB) (31%) and insecticides (INSE) (10%) (table 3-24). Non plant protection products (NPPP) and soil disinfectant (SODE) represent a far more lower risk (less than 1% of the total risk).

Table 3Table 3Table 3Table 3----24: Overview of the results obtained per pesticide group24: Overview of the results obtained per pesticide group24: Overview of the results obtained per pesticide group24: Overview of the results obtained per pesticide group

Pesticide group Pesticide group Pesticide group Pesticide group

RIconsumersRIconsumersRIconsumersRIconsumers (mean)(mean)(mean)(mean)

PRIBELPRIBELPRIBELPRIBEL (sum)(sum)(sum)(sum)

% of total risk% of total risk% of total risk% of total risk # of # of # of # of

application application application application casescasescasescases

FUNGFUNGFUNGFUNG 0,059 72525 58 205

HERBHERBHERBHERB 0,012 39871 31 207

INSEINSEINSEINSE 0,027 12438 10 208

NPPNPPNPPNPPPPPP 0,001 103 0,1 2

SODESODESODESODE 0,017 9 0,01 8

TOTALTOTALTOTALTOTAL - 124945 100 630

43

Contributions of pesticide groups to the total riskContributions of pesticide groups to the total riskContributions of pesticide groups to the total riskContributions of pesticide groups to the total risk

58%32%

10%

0%

0%

FUNG

HERB

INSE

NPPP

SODE

Figure 3Figure 3Figure 3Figure 3----12: Contributions of pesticide groups to the total risk in Belgium, 200112: Contributions of pesticide groups to the total risk in Belgium, 200112: Contributions of pesticide groups to the total risk in Belgium, 200112: Contributions of pesticide groups to the total risk in Belgium, 2001

Another way to analyse the situation in Belgium is to observe the bubble chart (figure 3-12). The size of the each bubble, linked to a pesticide group, gives the importance of the PRIBEL value. Its position on the X-axis is giving the importance of the sum of the frequency of use whereas its position on the Y-Axis is related to the median of the RIconsumers values for the pesticide groups. As it is seen in figure 3-13, fungicides group is accounting for a high proportion to the total PRIBEL for Belgium, both because its frequency and the RIconsumers value are high. Whereas for herbicide, its importance is mainly due to the frequency of use. For insecticide pesticide group, the RIconsumers is the highest value of all pesticide groups, but the frequency is relatively low compared to fungicides and herbicides.

FUNG

HERB

INSE

NPPP

0,000

0,001

0,002

0,003

0,004

0,005

0,006

0,0E+00 5,0E+05 1,0E+06 1,5E+06 2,0E+06 2,5E+06 3,0E+06

Frequency

RIc

on

su

mers

(m

ed

ian

)

FUNG

HERB

INSE

NPPP

SODE

Figure 3Figure 3Figure 3Figure 3----13: Median Risk (Y) and Sum of Frequencie13: Median Risk (Y) and Sum of Frequencie13: Median Risk (Y) and Sum of Frequencie13: Median Risk (Y) and Sum of Frequencies (X) of each pesticide group and Contribution of s (X) of each pesticide group and Contribution of s (X) of each pesticide group and Contribution of s (X) of each pesticide group and Contribution of each group to the Total Risk (size of bubble, sum(RIxF)) on Consumers, Belgium, 2001each group to the Total Risk (size of bubble, sum(RIxF)) on Consumers, Belgium, 2001each group to the Total Risk (size of bubble, sum(RIxF)) on Consumers, Belgium, 2001each group to the Total Risk (size of bubble, sum(RIxF)) on Consumers, Belgium, 2001

44

2.2.6.4.22.2.6.4.22.2.6.4.22.2.6.4.2 CCCCROP GROUP AGGREGATIOROP GROUP AGGREGATIOROP GROUP AGGREGATIOROP GROUP AGGREGATIONNNN

In terms of crop groups, pesticide applications in cereal and orchard (fruits) groups show the higher risks of all groups (Table 2-14). Potato group accounts for 11% of the total risk whereas greenhouse vegetables, vegetables, and maize do not exceed 1 % of the total risk.

Table 2Table 2Table 2Table 2----11114: Overview4: Overview4: Overview4: Overview of the results obtained per crop group of the results obtained per crop group of the results obtained per crop group of the results obtained per crop group

Crop groupCrop groupCrop groupCrop group

RIconsumersRIconsumersRIconsumersRIconsumers (mean)(mean)(mean)(mean)

PRIBELPRIBELPRIBELPRIBEL (sum)(sum)(sum)(sum)

% of total % of total % of total % of total riskriskriskrisk

# of # of # of # of application application application application casescasescasescases

CerealCerealCerealCereal 0,038 54256 43,4 92

OrchardOrchardOrchardOrchard 0,067 52936 42,4 186

PotatoPotatoPotatoPotato 0,022 14454 11,6 80

Greenhouse veg.Greenhouse veg.Greenhouse veg.Greenhouse veg. 0,031 1263 1,0 85

VegetablesVegetablesVegetablesVegetables 0,004 1048 0,8 108

MaizeMaizeMaizeMaize 0,001 989 0,8 43

TOTALTOTALTOTALTOTAL - 124945 100 630

Contributions of crop groups to the total riskContributions of crop groups to the total riskContributions of crop groups to the total riskContributions of crop groups to the total risk

43%

42%

12%

1%

1%

1%

Cereal

Orchard

Potato

Greenhouse veg.

Vegetables

Maize

Figure 3Figure 3Figure 3Figure 3----14: Contributions of crop groups to the total risk in Belgium, 200114: Contributions of crop groups to the total risk in Belgium, 200114: Contributions of crop groups to the total risk in Belgium, 200114: Contributions of crop groups to the total risk in Belgium, 2001

The figure 3-15 gives a clear look on the importance of frequency of use for cereal and potato crop groups. Orchard and cereal crop group both have a high Riconsumers median value. Concerning greenhouse vegetables, one can notice that the frequency of used is relatively low but the Riconsumers is high, for a bubble of approximately the same size as maize, whose contribution to total PRIBEL is mainly due to the Frequency of use.

45

CerealOrchard

PotatoGreenhouse

veg.

VegetablesMaize

0,000

0,002

0,004

0,006

0,008

0,010

0,E+00 5,E+05 1,E+06 2,E+06 2,E+06

Frequency

RIc

on

su

mers

(m

ed

ian

)Cereal

Orchard

Potato

Greenhouse veg.

Vegetables

Maize

Figure 3Figure 3Figure 3Figure 3----15: Median Risk (Y) and Sum of Frequencies (X) of each crop group and Contribution of 15: Median Risk (Y) and Sum of Frequencies (X) of each crop group and Contribution of 15: Median Risk (Y) and Sum of Frequencies (X) of each crop group and Contribution of 15: Median Risk (Y) and Sum of Frequencies (X) of each crop group and Contribution of each group to the Total Risk (size of bubble, sum(RIxF)) on Consumers, Belgium, 2001each group to the Total Risk (size of bubble, sum(RIxF)) on Consumers, Belgium, 2001each group to the Total Risk (size of bubble, sum(RIxF)) on Consumers, Belgium, 2001each group to the Total Risk (size of bubble, sum(RIxF)) on Consumers, Belgium, 2001

2.2.6.52.2.6.52.2.6.52.2.6.5 RRRRISKIEST APPLICATION ISKIEST APPLICATION ISKIEST APPLICATION ISKIEST APPLICATION CASESCASESCASESCASES

If ranked with regards to the risk indicator and no matter the pesticides or crop groups, applications of sulphur on apples stand for 19% of the total risk (Table). Mainly apples in orchard and winter wheat in cereal account for a high proportion of the total risk. The 8 application cases with the highest PRIBEL value, belonging either to cereal crop group or orchard crop group, reach 60% of the total risk.

Table 3Table 3Table 3Table 3----25: Riskiest application cases (*=abov25: Riskiest application cases (*=abov25: Riskiest application cases (*=abov25: Riskiest application cases (*=above the percentile 99e the percentile 99e the percentile 99e the percentile 99thththth of total risk) of total risk) of total risk) of total risk)

A. S. NameA. S. NameA. S. NameA. S. Name CropCropCropCrop CropCropCropCrop GroupGroupGroupGroup

Pesticide Pesticide Pesticide Pesticide GroupGroupGroupGroup

RIRIRIRI consumersconsumersconsumersconsumers

PRIBELPRIBELPRIBELPRIBEL % of Total% of Total% of Total% of Total

Sulphur apple Orchard FUNG 1 – 10 *24062 19

Chlormequat W Wheat Cereal HERB 0,1 – 1 *19317 15

fenpropimorph W Wheat Cereal FUNG 0,1 – 1 *8257 7

Thiram apple Orchard FUNG 0,1 – 1 *7268 6

Deltamethrin W Wheat Cereal INSE 0,1 – 1 *4979 4

epoxyconazole W Wheat Cereal FUNG 0,01 – 0,1 *4633 4 copper hydroxide

apple Orchard FUNG 0,1 – 1 *3468 3

Mcpa W Wheat Cereal HERB 0,01 – 0,1 3315 3

46

2.2.6.5.12.2.6.5.12.2.6.5.12.2.6.5.1 RRRRESESESESULTS PER PESTICIDE GULTS PER PESTICIDE GULTS PER PESTICIDE GULTS PER PESTICIDE GROUPROUPROUPROUP

FungicidesFungicidesFungicidesFungicides Riskiest applications cases in fungicide pesticide group are for a major part concerning apples in orchards (table 3-26). Winter wheat is also among the riskiest crop within fungicide group. Sulphur and copper compounds are both above the percentile 99th value in apple applications. Epoxyconazole and fenpropimorph are used at a relatively high frequency and therefore have a high PRIBEL value. Despite its low RIconsumers value, mancozeb is also listed below as its frequency of use appear to be really high.

Table 3Table 3Table 3Table 3----26: Riskiest application cases for fungicides (*=above the percentile 99th)26: Riskiest application cases for fungicides (*=above the percentile 99th)26: Riskiest application cases for fungicides (*=above the percentile 99th)26: Riskiest application cases for fungicides (*=above the percentile 99th)

A. S. NameA. S. NameA. S. NameA. S. Name CropCropCropCrop Crop groupCrop groupCrop groupCrop group RI consumersRI consumersRI consumersRI consumers PRIBEL PRIBEL PRIBEL PRIBEL sumsumsumsum

sulphur apple Orchard 1 - 10 *24062

fenpropimorph WinterWheat Cereal 0,01 – 0,1 *8257

thiram apple Orchard 0,1 - 1 *7268

epoxyconazole WinterWheat Cereal 0,01 – 0,1 *4634

copper hydroxyde apple Orchard 0,1 - 1 *3468

captan apple Orchard 0,01 – 0,1 2375

dodine apple Orchard 0,01 – 0,1 2207

mancozeb Potato (storage) Potato 0,001 – 0,01 1770

flusilazole WinterWheat Cereal 0,1 - 1 1544

HerbicidesHerbicidesHerbicidesHerbicides As it is seen in table 3-27, application on winter wheat are quite risky when considered the high PRIBEL values associated. Diquat is contained in two different commercial pesticides for potato storage (one herbicide and one defoliant) and, therefore, these two types of usages have been taken into account (Harcz, 2006).

Table 3Table 3Table 3Table 3----27: Riskiest application cases for herbicides (*=above the percentile 99th)27: Riskiest application cases for herbicides (*=above the percentile 99th)27: Riskiest application cases for herbicides (*=above the percentile 99th)27: Riskiest application cases for herbicides (*=above the percentile 99th)

A. S. NameA. S. NameA. S. NameA. S. Name CropCropCropCrop Crop groupCrop groupCrop groupCrop group RI RI RI RI

consuconsuconsuconsumersmersmersmers PRIBEL PRIBEL PRIBEL PRIBEL sumsumsumsum

chlormequat WinterWheat Cereal 0,1 - 1 *19318

mcpa WinterWheat Cereal 0,01 – 0,1 3315

diquat Potato (storage) Potato 0,01 – 0,1 2355

glyphosate WinterWheat Cereal 0,01 – 0,1 1970

isoproturon WinterWheat Cereal 0,01 – 0,1 1092

linuron Potato (storage) Potato 0,01 – 0,1 1024

47

InsecticidesInsecticidesInsecticidesInsecticides Deltamethrin has a significantly high PRIBEL value for its application on winter wheat. But the second highest PRIBEL value for insecticide is also concerning deltamethrin, this time on potato (table 3-28). Other risky applications are linked to the orchard crop group, more specifically to apple.

Table 3Table 3Table 3Table 3----28: Riskiest application cases for insecticides (*=above the percentile 99th)28: Riskiest application cases for insecticides (*=above the percentile 99th)28: Riskiest application cases for insecticides (*=above the percentile 99th)28: Riskiest application cases for insecticides (*=above the percentile 99th)

A. S. NameA. S. NameA. S. NameA. S. Name CropCropCropCrop Crop groupCrop groupCrop groupCrop group RI consumersRI consumersRI consumersRI consumers PRIBEL PRIBEL PRIBEL PRIBEL sumsumsumsum

deltamethrin WinterWheat Cereal 0,1 - 1 *4980

deltamethrin Potato (storage) Potato 0,01 – 0,1 734

carbaryl apple Orchard 0,1 - 1 650

metasystox thiol apple Orchard 1 - 10 523

azocyclotin apple Orchard 0,1 - 1 372

lambda-cyhalothrin WinterWheat Cereal 0,01 – 0,1 349

thiometon PeaWithPod Vegetables 0,01 – 0,1 336

ethoprop Potato (storage) Potato 0,01 – 0,1 252

Non Plant Protection ProductsNon Plant Protection ProductsNon Plant Protection ProductsNon Plant Protection Products This pesticide group do not contribute to a significant part of the total risk, and the two application cases risky for the consumers are presented in the table 3-29. Chlorpropham on potato is the only application which can really be considered as risky for the consumer.

Table 3Table 3Table 3Table 3----29: Riskiest application cases (*=above the percentile 99th)29: Riskiest application cases (*=above the percentile 99th)29: Riskiest application cases (*=above the percentile 99th)29: Riskiest application cases (*=above the percentile 99th)

A. S. NameA. S. NameA. S. NameA. S. Name CropCropCropCrop Crop Crop Crop Crop groupgroupgroupgroup

RI consumersRI consumersRI consumersRI consumers PRIBEL PRIBEL PRIBEL PRIBEL sumsumsumsum

chlorpropham Potato (storage) Potato 0,001 – 0,01 103

streptomycin pear Orchard 0,00001 0

Soil disinfectantsSoil disinfectantsSoil disinfectantsSoil disinfectants The remark made for NPPP is also valid for the group of soil disinfectant pesticides, as the PRIBEL values that concern the different application cases are very low and stand in total for less than one percent of the total risk.


A. S. NameA. S. NameA. S. NameA. S. Name CropCropCropCrop Crop groupCrop groupCrop groupCrop group RI RI RI RI

ConsumersConsumersConsumersConsumers PRIBEL PRIBEL PRIBEL PRIBEL sumsumsumsum

sulfotep Greenhouse Vegetable

Greenhouse 0,1 - 1 3

oxamyl Potato (storage) Potato < 0,001 2

48

methyl bromide Greenhouse Vegetable

Greenhouse 0,001 – 0,01 1

1,3-dichloropropene

Greenhouse Vegetable

Greenhouse < 0,001 1

1,3-dichloropropene

Leek Vegetables < 0,001 1

oxamyl Greenhouse Vegetable

Greenhouse < 0,001 1

2.2.6.5.22.2.6.5.22.2.6.5.22.2.6.5.2 RRRRESULTS PER CROP GROUESULTS PER CROP GROUESULTS PER CROP GROUESULTS PER CROP GROUPPPP

CerealCerealCerealCereal For cereal crop group, crops for which the program PRIBEL contains data are winter wheat and winter cereal. For winter barley, the importance factor of the crop for the consumers has been judged not relevant. Therefore winter wheat crop encompass the totality of the risk linked with cereal crop group (table 3-31). The four riskiest application cases are above the percentile 99th and involve chlormequat, fenpropimorph, deltamethrin and epoxyconazole.


A. S. NameA. S. NameA. S. NameA. S. Name CropCropCropCrop Pesticide Pesticide Pesticide Pesticide groupgroupgroupgroup

RI RI RI RI consumersconsumersconsumersconsumers

PRIBEL PRIBEL PRIBEL PRIBEL sumsumsumsum

chlormequat WinterWheat HERB 0,1 - 1 *19318

fenpropimorph WinterWheat FUNG 0,1 - 1 *8257

deltamethrin WinterWheat INSE 0,1 - 1 *4980

epoxyconazole WinterWheat FUNG 0,01 – 0,1 *4634

mcpa WinterWheat HERB 0,01 – 0,1 3315

glyphosate WinterWheat HERB 0,01 – 0,1 1970

flusilazole WinterWheat FUNG 0,1 - 1 1544

isoproturon WinterWheat HERB 0,01 – 0,1 1092

mancozeb WinterWheat FUNG 0,01 – 0,1 979

prochloraz WinterWheat FUNG 0,01 – 0,1 850

azoxystrobine-isomer

WinterWheat FUNG 0,01 – 0,1 696

OrchardOrchardOrchardOrchard In orchard crop group, first three riskiest application cases are concerning active substances with a high RIconsumers value, especially for sulphur (table 3-32). In this crop group, most application cases are involving fungicides. Elements like sulphur and copper hydroxide are used in orchard have a high PRIBEL value, especially for sulphur due to its high RIconsumers value. Dithiocarbamates thiram and ziram are also contributing to the total risk for the crop group.

49





sulphur apple FUNG 1 - 10 *24062

thiram apple FUNG 0,1 - 1 *7268

copper hydroxyde apple FUNG 0,1 - 1 *3468

captan apple FUNG 0,01 – 0,1 2375

dodine apple FUNG 0,01 – 0,1 2207

thiram pear FUNG 0,01 – 0,1 1269

ziram apple FUNG 0,1 - 1 906

dithianon apple FUNG 0,01 – 0,1 797

carbendazim apple FUNG 0,01 – 0,1 741

carbaryl apple INSE 0,1 - 1 650

difenoconazole apple FUNG 0,01 – 0,1 602

PotatoPotatoPotatoPotato Linuron as well as dithiocarbamates mancozeb and fluazinam have a high PRIBEL value that can be explained more by the high frequency of the applications than by a high RIconsumers value (table 3-33). This can be better explained by their widespread use (high frequency of application) than by their value of RIconsumers (0,003 and 0,005 respectively).

Table 3Table 3Table 3Table 3----33: Riskiest application cases (*=above the 33: Riskiest application cases (*=above the 33: Riskiest application cases (*=above the 33: Riskiest application cases (*=above the percentile 99th)percentile 99th)percentile 99th)percentile 99th)

A. S. NameA. S. NameA. S. NameA. S. Name CropCropCropCrop Pesticide Pesticide Pesticide Pesticide GroupGroupGroupGroup



diquat Potato (storage) HERB 0,01 – 0,1 2355

mancozeb Potato (storage) FUNG 0,001 – 0,01 1770

linuron Potato (storage) HERB 0,01 – 0,1 1024

fluazinam Potato (storage) FUNG 0,001 – 0,01 923

deltamethrin Potato (storage) INSE 0,01 – 0,1 734

glufosinate ammonium salt (1:1)

Potato (storage) HERB 0,01 – 0,1 665

metribuzin Potato (storage) HERB 0,01 – 0,1 655

Greenhouse vegetablesGreenhouse vegetablesGreenhouse vegetablesGreenhouse vegetables The widely used seed-applied fungicide thiram is the riskiest application for the crop group greenhouse vegetables (table 3-34). Indeed the risk associated to this application stands for 85% of the total risk for the crop group. It is noteworthy to remind that the RI value for consumers reflects a potential exposure rather than an actual exposure. It seems thus evident that in the case of seed dressing with thiram the amount of residues left in the crop

50

at harvest will be very small and the question can be raised about the relevance to calculate RI values for non systemic fungicides applied as seed treatments. Although not frequently applied on greenhouse vegetables, sulphur is also part of the riskiest application for the crop group.


AAAA. S. Name. S. Name. S. Name. S. Name CropCropCropCrop Pesticide Pesticide Pesticide Pesticide groupgroupgroupgroup


thiram Greenhouse Veg. FUNG 0,1 - 1 1077

sulphur Greenhouse Veg. FUNG 1 - 10 57

ethephon Greenhouse Veg. HERB 0,01 – 0,1 15

diquat Greenhouse Veg. HERB 0,1 - 1 15

bitertanol Greenhouse Veg. FUNG 0,01 – 0,1 11

mancozeb Greenhouse Veg. FUNG 0,01 – 0,1 10

ziram Greenhouse Veg. FUNG 0,1 - 1 8

vinclozolin Greenhouse Veg. FUNG 0,01 – 0,1 7

iprodione Greenhouse Veg. FUNG 0,01 – 0,1 6

VegetablesVegetablesVegetablesVegetables Mainly fungicides and insecticides account for a major part to the risk in vegetables crop group (table 3-35). The riskiest application of the crop group is concerning thiometon on pea, followed by mancozeb on leek and on pea.


A. S. NameA. S. NameA. S. NameA. S. Name CCCCroproproprop Pesticide Pesticide Pesticide Pesticide groupgroupgroupgroup


thiometon PeaWithPod INSE 0,01 – 0,1 336

mancozeb Leek FUNG 0,01 – 0,1 103

mancozeb PeaWithPod FUNG 0,01 – 0,1 93

chlorothalonil PeaWithPod FUNG 0,01 – 0,1 91

lambda-cyhalothrin PeaWithPod INSE 0,01 – 0,1 86

simazine PeaWithPod HERB 0,001 – 0,01 57

copper hydroxyde Leek FUNG 0,01 – 0,1 34

iprodione PeaWithPod FUNG 0,001 – 0,01 26

fenpropimorph Leek FUNG 0,01 – 0,1 23

chlorothalonil Leek FUNG 0,01 – 0,1 19

51

MaizeMaizeMaizeMaize Mainly herbicide application cases account for a large proportion to the risk (table 3-36). It has to be noted that atrazine has been banned for use since 2001 when it is present as single active ingredient in the commercial preparation.

Table 3Table 3Table 3Table 3----36: Riskiest application cases (*=above the pe36: Riskiest application cases (*=above the pe36: Riskiest application cases (*=above the pe36: Riskiest application cases (*=above the percentile 99th)rcentile 99th)rcentile 99th)rcentile 99th)



atrazine Maize HERB 0,001 – 0,01 499

sulcotrione Maize HERB 0,001 – 0,01 213

bromoxynil Maize HERB 0,01 – 0,1 161

carbofuran Maize INSE 0,01 – 0,1 52

lindane Maize INSE 0,001 – 0,01 17

flufenacet Maize HERB 0,001 – 0,01 10

diquat Maize HERB 0,01 – 0,1 9

2.2.6.62.2.6.62.2.6.62.2.6.6 DDDDISCUSSIONISCUSSIONISCUSSIONISCUSSION

2.2.6.6.12.2.6.6.12.2.6.6.12.2.6.6.1 GGGGENERAL REMARKSENERAL REMARKSENERAL REMARKSENERAL REMARKS

The PRIBEL risk indicator is calculated on the basis of a worst-case approach. Indeed, consumer exposure is evaluated by the MRL and the EDI, no matter if residue concentrations are lower than the MRL value and if the food consumption is less important than the one used in the model. Risk is therefore calculated taking account of a potential exposure. For reasons cited above, real exposure can be considered lower than the one calculated by PRIBEL. Also not taken into account in the calculation, processing factors (eg. washing, peeling, heating,…) which tend to decrease pesticide residue concentrations in commodities (Timme et al., 2004).

2.2.6.6.22.2.6.6.22.2.6.6.22.2.6.6.2 CCCCROP GROUPSROP GROUPSROP GROUPSROP GROUPS

One can notice that pesticide applications of cereal and orchard crop groups account for 80 % of the total risk for consumers in Belgium. Regarding to this situation, it is interesting to note that results tends to show two types of profiles. First, most of risky pesticide applications in orchard carry a high RIconsumers value, which means in other words that active substance used to fight pest in orchards have a high potential toxic effects on consumers and that this effect can be magnified if these pesticides are frequently used. Indeed, the mean value for RIconsumers for orchard is the highest of all crop group (Table 2-1). For cereal crop group, the situation is different in a way that risk comes mostly from the widespread use of pesticides with a relatively low RI value. In the potato crop group, the frequency of use seems to be the most important factor that contribute to the high PRIBEL value of the riskiest application cases. If crop groups vegetables and greenhouse vegetables are added together, these crop groups are responsible for only 2% of the total risk. Indeed, if considered frequency of use and RIconsumers value, both groups tend to be low compare to orchard and cereal. Especially for vegetables crop group, for which the RIconsumers mean value of the different application cases is very low.

52

2.2.6.6.32.2.6.6.32.2.6.6.32.2.6.6.3 RRRRISKIEST APPLICATION ISKIEST APPLICATION ISKIEST APPLICATION ISKIEST APPLICATION CASESCASESCASESCASES

High PRIBEL values from the riskiest application cases can be explained differently in accordance with their frequency of use or their RIconsumers values. For the application of sulphur on apples, the riskiest one, it is clearly the high value of RIconsumers (4,36) that contribute mostly to the high PRIBEL value for consumers during the year 2001. Indeed, the exposure is calculated taking account of the MRL which reaches 50 mg/kg. Whereas for chlormequat on winter wheat, the frequency of use seems to contribute largely to the high PRIBEL value. 2.2.6.72.2.6.72.2.6.72.2.6.7 CCCCOMPARISON WITH RESULOMPARISON WITH RESULOMPARISON WITH RESULOMPARISON WITH RESULTS OBTAINED WITH NATTS OBTAINED WITH NATTS OBTAINED WITH NATTS OBTAINED WITH NATIONAL SURVEILLANCE PIONAL SURVEILLANCE PIONAL SURVEILLANCE PIONAL SURVEILLANCE PROGRAMROGRAMROGRAMROGRAM

Some active substances were identified as risky by the PRIBBEL indicator. It is interesting to see if these results match with data obtained through the national surveillance program. Comparison of risky active substances and pesticide residues has been done on the basis of the pesticides detected by the FASFC for the year 2001 which is the year chosen for the calculations with the PRIBEL indicator. In fruits and vegetables, one can notice that active substances were pointed out by the PRIBEL indicator and found into the national surveillance program by the FASFC (table 3-37). Those pesticide can be considered risky for the consumers as they occur to be found in samples of foodstuffs in concentration exceeding the reported level.

Table 3Table 3Table 3Table 3----37: Summary of active substances pointed out by PRIBEL and b37: Summary of active substances pointed out by PRIBEL and b37: Summary of active substances pointed out by PRIBEL and b37: Summary of active substances pointed out by PRIBEL and by monitoring data from y monitoring data from y monitoring data from y monitoring data from FASFC for fruits and vegetables (*=riskiest active substances ranked by Pribel value FASFC for fruits and vegetables (*=riskiest active substances ranked by Pribel value FASFC for fruits and vegetables (*=riskiest active substances ranked by Pribel value FASFC for fruits and vegetables (*=riskiest active substances ranked by Pribel value ≥ 700, **=most ≥ 700, **=most ≥ 700, **=most ≥ 700, **=most often found active substances, as reported by FASFC, 2001)often found active substances, as reported by FASFC, 2001)often found active substances, as reported by FASFC, 2001)often found active substances, as reported by FASFC, 2001)

Fruit and vegetablesFruit and vegetablesFruit and vegetablesFruit and vegetables

PRIBEL*PRIBEL*PRIBEL*PRIBEL* FASFC**FASFC**FASFC**FASFC** PRIBEL/FASFCPRIBEL/FASFCPRIBEL/FASFCPRIBEL/FASFC

Sulphur Chlormequat Dithiocarbamates

Deltamethrine Propamocarb Carbendazim

Fenpropimorph Bromide ion Prochloraz

Epoxyconazole Imazalil

Copper hydroxyde Chlorpropham

Captan Ipridione

Dodine Thiabendazole

Linuron

Fluazinam

Dithiocarbamates such as ziram, thiram, mancozeb, and maneb have been pointed out both by PRIBEL indicator and national surveillance programmed by the FASFC. The same situation has to be noticed for fungicides carbendazim and prochloraz. Deltamethrin has been evaluated risky by the PRIBEL indicator, but its presence in the food chain appear to be very limited since on the 530 samples tested, only 2 (0,4%) were containing residues above the reporting level (FASFC, 2001). On the 606 commodity samples tested for fenpropimorph, none was containing residues above the reporting level. For epoxyconazole too, no samples contained residues in concentration above the reporting level on the 418 samples tested. Captan was found in concentrations above reporting level in 8 samples out of 737 (1,1%). Fluazinam was sought for in 606 samples but was never detected. Linuron was not sought for in the national surveillance program.

53

Taking account of these figures, the situation seem to be positive in terms of health safety. What may raise some concerns is the absence of samples tested for dodine, that has been proved to be toxic at chronic doses and affecting the mechanism of the thyroid. In cereals, data obtained by the PRIBEL indicator and the national surveillance program differ significantly since none of the riskiest pesticide pointed out by the PRIBEL indicator were sought for by the FASFC (table 3-38). However, active substances (e.g. chlorpyriphos) detected in the national program were not considered risky. This could be explained by the fact that the substances detected within the official surveillance programmes are, in many cases, pesticides that can be used for post-harvest pest control. Such post harvest applications are not considered within the PRIBEL system (data on such pesticide applications are not available in the database).

Table 3Table 3Table 3Table 3----38: Summary of active substances pointed out by PRIBEL and by monitoring data from for 38: Summary of active substances pointed out by PRIBEL and by monitoring data from for 38: Summary of active substances pointed out by PRIBEL and by monitoring data from for 38: Summary of active substances pointed out by PRIBEL and by monitoring data from for cereals (*=riskiest active substances ranked by Pribel value cereals (*=riskiest active substances ranked by Pribel value cereals (*=riskiest active substances ranked by Pribel value cereals (*=riskiest active substances ranked by Pribel value ≥ 1000 , **=most often found active ≥ 1000 , **=most often found active ≥ 1000 , **=most often found active ≥ 1000 , **=most often found active substances, as reported by FASFC)substances, as reported by FASFC)substances, as reported by FASFC)substances, as reported by FASFC)

CerealsCerealsCerealsCereals

PRIBEL*PRIBEL*PRIBEL*PRIBEL* FASFC**FASFC**FASFC**FASFC** PRIBEL/FASFCPRIBEL/FASFCPRIBEL/FASFCPRIBEL/FASFC

Chlormequat Bromide ion /

Fenpropimorph Dichlorvos

Deltamethrine Malathion

Epoxyconazole Pirimiphos-methyl

Mcpa Chlorpyriphos-methyl

Glyphosate

Flusilazole

Isoproturon

We therefore would recommend to FASFC to consider the possibility of monitoring chlormequat in cereals. On the other hand, it appears quite relevant to consider post harvest treatments within the PRIBEL system since this kind of treatment is much more prone to left residues in commodities compared to seed coating or field spraying at an early stage of development of the crop. 2.2.6.82.2.6.82.2.6.82.2.6.8 CCCCONCLUSIONONCLUSIONONCLUSIONONCLUSION

In these risk calculations, it is striking to note the presence of sulphur and copper hydroxide in the riskiest application cases, mostly in orchards. Used as fungicides, the amount of expected residues is in fact high, as confirmed by the high MRL value. Both active substances are commonly used in organic farming too. For this reason, it seems important to have a closer look in the real toxicity of such compounds in order to make sure that the current relative high MRLs set for these compounds are still warranting the highest level of safety for the consumers. A thorough assessment of the toxicity of sulphur and copper derivatives should be done in parallel with surveys on their real uses and on the presence of residues left in foodstuffs. Another striking point is the fact that pesticides used in orchards are characterized by a high potential exposure of the consumers when considering both the relatively high levels of residues tolerated in harvest products and their toxicological properties (high RIconsumers values for many pesticides). Indeed, orchard crop group accounts for 43% of the total risk in Belgium, and its RIconsumers mean value is the highest of all groups.

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On the other hand, it is surprising to note that vegetables do not account for more than 2 % of the total risk. This could be due to the fact that special attention is given when setting MRLs for pesticides in vegetables because such foodstuffs can be consumed raw and without processing. But, then, it seems difficult to explain the apparently contrasting situation that has been depicted above for the fruit production. Fortunately, both vegetables and fruits are frequently tested in the various monitoring programmes in order to check if no MRL exceedings are to be noticed. According to the results obtained, some pesticides assessed risky by the PRIBEL indicator are well monitored and results from FASFC tend to show that risks are low since the tested samples were most of the time containing residue concentrations below the reporting level.

2.2.72.2.72.2.72.2.7 Evaluation of the impact on consumers from alternative scenarios Evaluation of the impact on consumers from alternative scenarios Evaluation of the impact on consumers from alternative scenarios Evaluation of the impact on consumers from alternative scenarios

2.2.7.12.2.7.12.2.7.12.2.7.1 GGGGENERAL REMARKENERAL REMARKENERAL REMARKENERAL REMARK

Within the framework of HEEPEBI, it is relatively out of scope to tackle separately all risky application cases in order to provide an alternative to reduce the impact of pesticides on consumers. Besides, it is not suitable to propose drastic measures about pesticides uses and their frequency. However, major trends of Integrated Crop Management (ICP), Integrated Pest management (IPM), and organic farming can be analysed and discussed in this part of the report. Also the alternatives suggested by working groups implemented within the framework of the Pesticide use reduction national programme can be presented to estimate impacts of these alternatives. The way alternative proposals should be seen is the promotion, when possible, of treatments and application schemes that minimize the impact of pesticide. Nevertheless, it is important to keep in mind that these proposals may some years not be applied, as pest development conditions can be variable over the years. 2.2.7.22.2.7.22.2.7.22.2.7.2 TTTTREATMENT SCHEMES PROREATMENT SCHEMES PROREATMENT SCHEMES PROREATMENT SCHEMES PROPOSED BY WORKING GROPOSED BY WORKING GROPOSED BY WORKING GROPOSED BY WORKING GROUPSUPSUPSUPS

2.2.7.2.12.2.7.2.12.2.7.2.12.2.7.2.1 WWWWORKING GROUP EXPERTIORKING GROUP EXPERTIORKING GROUP EXPERTIORKING GROUP EXPERTISESESESE

Within the framework of the development of PRIBEL indicator, the expertise provided by the different working groups1 for the main crops in Belgium has to be considered as an asset in the risk management. Indeed, these groups of professionals can bring a strong input by establishing various pesticide application treatments in order to test them. This was done for the potato working group. Different treatment schemes were proposed by the group to calculate their respective impacts on the different compartments, whom consumers, encompassed by PRIBEL.

2.2.7.2.22.2.7.2.22.2.7.2.22.2.7.2.2 RRRREEEESULTS OBTAINEDSULTS OBTAINEDSULTS OBTAINEDSULTS OBTAINED

Four main types of treatment schemes for potato were suggested, with different level of intensity of pesticide use in order to compare their impacts. All these treatments are suggested to cover a entire season of potato culture, from planting to harvesting. Another factor taken into account is the pesticide formulation, as pesticide products can be formulated in several ways. The first treatment scheme was done for a sensitive variety of storage potato where :

• conso1 = Treatment scheme on sensitive variety (12 treatments against blight)-Low pressure

1 Fourteen working groups were installed in Belgium in the framework of the Federal Programme for

Reduction of Pesticides and Biocides

55

• conso2 = Treatment scheme on sensitive variety (13 treatments against blight)-moderated pressure

• conso3 = Treatment scheme on sensitive variety (14 treatments against blight)-average pressure

• conso4 = Treatment scheme on sensitive variety (16 treatments against blight)-High pressure

• conso5 = Treatment scheme on sensitive variety (17 treatments against blight)-High pressure

The second treatment scheme dealing with the crop of seed potatoes where :

• plant1 = Treatment scheme-High pressure

• plant2 = Treatment scheme-Intermediate pressure

• plant3 = Treatment scheme-Low pressure The third treatment scheme was dedicated to organic farming system, where :

• bioplein1 = Treatment with copper hydroxide-Wettable powder

• bioplein2 = Treatment with copper hydroxide-Granule

• bioplein3 = Treatment with copper sulphate-Wettable powder

• bioplein4 = Treatment with copper oxychloride-Granule

• bioplein5 = Treatment with copper oxychloride-Wettable powder Each treatment scheme contains various pesticide applications with a proper Riconsumers value. For each treatment scheme, the sum of Riconsumers from each application has been summed and results obtained for each treatment are given in table 3-39.

Table 3Table 3Table 3Table 3----39: Sum o39: Sum o39: Sum o39: Sum of RIconsumers for each treatment scheme in Potato f RIconsumers for each treatment scheme in Potato f RIconsumers for each treatment scheme in Potato f RIconsumers for each treatment scheme in Potato

Treatment schemeTreatment schemeTreatment schemeTreatment scheme conso1conso1conso1conso1 conso2conso2conso2conso2 conso3conso3conso3conso3 conso4conso4conso4conso4 conso5conso5conso5conso5

RiconsumersRiconsumersRiconsumersRiconsumers 0,055 0,042 0,138 0,141 0,247

Treatment schemeTreatment schemeTreatment schemeTreatment scheme plant1plant1plant1plant1 plant2plant2plant2plant2 plant3plant3plant3plant3

RiconsumersRiconsumersRiconsumersRiconsumers 0,161 4,527 0,204

Treatment schemeTreatment schemeTreatment schemeTreatment scheme bioplein1bioplein1bioplein1bioplein1 biopleinbiopleinbiopleinbioplein2222 bioplein3bioplein3bioplein3bioplein3 bioplein4bioplein4bioplein4bioplein4 bioplein5bioplein5bioplein5bioplein5

RiconsumersRiconsumersRiconsumersRiconsumers 0,960 0,960 0,960 0,144 0,144

It is interesting to see that for the treatments “conso”, the sum of each RIconsumers related to each application is increasing with the number of applications during crop growth. Indeed the RIconsumers for conso5, the treatment with the highest number of applications, is more than 4 times higher than the treatment conso1. Between these two extreme values, the sum of RIconsumers increases except for the conso2 which has a lower value than conso1. This is due to the fact that some of the active substances used differ in the two treatments. For the treatments “plant”, the highest value is obtained for the treatment scheme plant2, mainly because of the presence of lambda-cyhalothrin and esfenvalerate in various applications, both active substances do have a high RIconsumers value For organic treatments “bioplein”, the three first treatments have a relatively high RIconsumers values compared to the other treatments suggested. This is due to the higher toxicity of copper hydroxide and copper sulphate. The two other treatments involved copper

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oxychloride. It is to be noted that the different formulations tested did not alter the RIconsumers value because the kind of formulation is not taken into account in the RIconsumers calculations. Therefore, on the basis of these calculations, it is recommended to focus on the risk assessment of chemicals allowed in organic agriculture. As the cereal crop group accounts for 43% of the total risk in Belgium, the same kind of exercise could be made in order to find adapted treatment schemes, responding both to harvest yield and consumers safety. In addition, it should be very important to assess the real relevance of chlormequat treatments by assessing the level of residues in harvested grains.

2.2.82.2.82.2.82.2.8 Organic farming and Integrated Pest Management (Greenlabels)Organic farming and Integrated Pest Management (Greenlabels)Organic farming and Integrated Pest Management (Greenlabels)Organic farming and Integrated Pest Management (Greenlabels)

2.2.8.12.2.8.12.2.8.12.2.8.1 IIIINTRODUCTIONNTRODUCTIONNTRODUCTIONNTRODUCTION

On the overall Belgian situation, an alternative would be to promote organic farming. Indeed, in organic farming no chemicals of synthetic origin are used during pre- and post- harvest. The consequence of this switch would decrease the frequency of use of chemical pesticides and further on diminish risks for consumers. Taken into account the meta-analysis in the literature related to organic farming, it is clear that pesticide residues will be found in lower quantity and lower frequency in foodstuffs commodities (Baker et al., 2002 ; Pussemier et al., 2006). But as it has been seen before, copper and sulphur compounds encompass high risks for the consumers according to the PRIBEL system. This issue should require additional attention. For the orchard crop group, accounting for 42% of the total risk in Belgium, alternatives to reduce the amount of pesticide residues in crop can be found. Indeed, the Danish Research Centre for organic farming has tried other fungicides than sulphur to reduce apple scab development (Lindhard et al., 2004). Products tested are extracts of grape fruit seeds, extract of the plant Quilllaja saponaria, and another synthetic product. In terms of efficiency, sulphur remains more efficient as the yield obtained after its application is higher than those obtained after application of the other tested products, but apple scab diseases were clearly reduced with the products tested. Organically grown food is perceived as healthier and safer. Relevant scientific evidence, however, is scarce. There is still an absence of adequate comparative data of food products of conventional and organic food. Organic fruits and vegetables can be expected to contain fewer agrochemical residues than conventionally grown alternatives: yet, the significance of this difference is questionable, as much as actual levels of contamination in both types of food are generally well below acceptable limits. With respect to other food hazards, such as endogenous plant toxins, biological pesticides and pathogenic microorganisms, available evidence is extremely limited preventing generalized statements. Also, results for mycotoxin contamination in cereal crops are variable and inconclusive; hence, no clear picture emerges. It is difficult, therefore, to weigh the risks and to pronounce upon the question whether conventional or organic farming is better concerning food safety (Magkos, F., 2006). Enforcements of principles from Integrated Pest Management (IPM) would also contribute to the reduction of pesticide residues. IPM is an ecosystem-based strategy that focuses on long-term prevention of pests or their damage through a combination of techniques such as biological control, habitat manipulation, modification of cultural practices, and use of resistant varieties. Pesticides are used only after monitoring indicates they are needed according to established guidelines, and treatments are made with the goal of removing only the target organism. Pest control materials are selected and applied in a manner that minimizes risks to human health, beneficial and nontarget organisms, and the environment

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A methodology was applied by Steurbaut and Garreyn (2006, in Press) to rank the different labels in Belgium. Three major steps of the method can be identified. The first phase consists in selecting different aspects of sustainability. Furthermore, a listing of the rules included in the certification book which are having an impact on these aspects of sustainability has been made. For the consumers, the item food safety is the more relevant. In the second phase, weights were attributed by experts to rules and aspects regarding to their impact on sustainability. Finally, the third phase consisted in scoring each label by multiplying weights of different rules with a factor that reflects the mandatory level of the rule. A total score for each aspect was achieved by adding individual criterion scores. The following part describes the different organic and IPM label, and further on their relevancy in terms of food safety. Their was also dealt with this topic in paragraph 1.4.

2.2.8.22.2.8.22.2.8.22.2.8.2 LLLLABELSABELSABELSABELS

2.2.8.2.12.2.8.2.12.2.8.2.12.2.8.2.1 BBBBIOGARANTIE IOGARANTIE IOGARANTIE IOGARANTIE ((((ORGANIC FARMINGORGANIC FARMINGORGANIC FARMINGORGANIC FARMING))))

The Biogarantie label was developed in Belgium for the inspection and auditing of organic products at different levels. Farmers, processors and distributors have to follow the specifications. Organic farming as it exists today is a cultivation method with strong agro-ecological foundations, exercised in a highly professional manner and refusing all pesticides and nutrients obtained by chemical synthesis. The European Commission has developed specific regulations for this environmentally friendly form of agriculture and stock-rearing (Council Regulation (EEC) no. 2092/91 24 June 1991 on organic production of agricultural products and indications referring thereto on agricultural products and foodstuffs). The Biogarantie quality label is only awarded after a positive control by an independent control body (Steurbaut and Garreyn, 2006, in press).

2.2.8.2.22.2.8.2.22.2.8.2.22.2.8.2.2 EEEEUREP UREP UREP UREP GGGGAPAPAPAP

By adhering to good agricultural practices, Eurep GAP strives since 1997 to reduce risks in agricultural production. EurepGAP provides the tools to objectively verify best practice in a systematic and consistent way. This goal is achieved through the protocol and compliance criteria. Eurep GAP's scope is concerned with practices on the farm, once the product leaves the farm they come under the control of other Codes of Conduct and certification schemes relevant to food packing and processing. That way the whole chain is assured right through to the final consumer. The technical and standards committees, consisting of producer and retail members, has a formal agenda to review emerging issues and carry-out risk assessments. This is a rigorous process, following the principles of HACCP, and involves experts in their field leading to revised versions of the protocol.

2.2.8.2.32.2.8.2.32.2.8.2.32.2.8.2.3 FFFFRUITNETRUITNETRUITNETRUITNET

In Belgium, Fruitnet is a label that guarantee for consumers apples and pears safety and quality since 1991. To attain this goal, Fruitnet follows guidelines of integrated agriculture, and controls rigorously the production in orchards, in stocking places and in the packaging of the fruits. Traceability in ensured by the label, allowing to respond rapidly to any problems. Guidelines are inspired from those used by the OILB (Organisation Internationale de Lutte Biologique et Intégrée contre les animaux et les plantes nuisibles). Indeed, guidelines for the production of fruit under Fruitnet encompass adoption of environmental measures, use of natural pesticides rather than chemical ones, and the control of the quality and the origin of fruits. Pesticide applications are kept to a minimum by adapting cultivation methods and fighting pests with natural enemies and traps to fight harmful insects.

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2.2.8.2.42.2.8.2.42.2.8.2.42.2.8.2.4 FFFFLANDRIALANDRIALANDRIALANDRIA/F/F/F/FLANDRIAGAP LANDRIAGAP LANDRIAGAP LANDRIAGAP

Flandria and FlandriaGap are integrated agriculture systems, both from the point of view of quality and food safety. Its main principles imply cultivation technology, sustainable horticulture, hygiene and traceability. FlandriaGap is an ameliorated version of Flandria, adopted in 2004, that draws special attention to food safety, environmental sustainability and to workers health. The document containing the guidelines for production is composed of 148 points divided in three main categories. The first category, called “major musts”, is containing important points concerning food safety. Producers have to comply to 100% of these points. The second category, called “minor musts”, is composed by guidelines that has to be respected at 80%. The last category, “shoulds”, are recommendations for the future and have to be considered in the present as advices.

2.2.8.2.52.2.8.2.52.2.8.2.52.2.8.2.5 TTTTERRA ERRA ERRA ERRA NNNNOSTRAOSTRAOSTRAOSTRA

The label Terra Nostra was created in Belgium by the ORPAH (Office Régional de la Promotion de l’Agriculture et l’Horticulture). Potato is the only commodity targeted by the label. Products issued from Terra Nostra are high quality potato produced in Walloon region and under integrated agriculture principles. Guidelines focus on soil analysis to reduce fertilizers and on the affiliation to an alert system focusing on mildew and aphids in order to diminish the use of pesticides. Products are controlled by an independent body and the cultivation technique allows a reduction by 30% to 40% in the quantity of fertilizers and pesticides used (Steurbaut and Garreyn, 2006).

2.2.8.32.2.8.32.2.8.32.2.8.3 AAAANALYSIS AND RESULTS NALYSIS AND RESULTS NALYSIS AND RESULTS NALYSIS AND RESULTS OBTAINEDOBTAINEDOBTAINEDOBTAINED

For each aspect of the study of Steurbaut and Garreyn (2006, in press), a maximum score corresponding to the best situation was calculated. For the consumers, it is possible to compare the performance in terms of food safety by comparing the “Food Safety” score obtained for each label and expressed in percent of the maximum score (Table ). At this level, it is important to understand that the results obtained for the different labels are reflecting the amount and the quality of the standards written in the guidelines of the labels. It cannot be assessed yet that foodstuffs from a label scoring high in this study are automatically safe food containing a low residue level. As for the consumers, the amount of pesticide residues and their concentration should be as low as possible, further tests need to be implemented to assess the real safety of the foodstuffs produced according to a given label. However, the fact that a label is scoring high in terms of food safety standards implies that many conditions are gathered to meet the ideal situation for food safety. In other words, the chance is higher to notice low pesticide residue concentrations.

Table 3Table 3Table 3Table 3----40: Food safety standards scores obtained for the different labels (% of the ideal situation) 40: Food safety standards scores obtained for the different labels (% of the ideal situation) 40: Food safety standards scores obtained for the different labels (% of the ideal situation) 40: Food safety standards scores obtained for the different labels (% of the ideal situation) (according to Steurbaut and Garreyn, 2006)(according to Steurbaut and Garreyn, 2006)(according to Steurbaut and Garreyn, 2006)(according to Steurbaut and Garreyn, 2006)

Charte Perfect

Terra Nostra

EurepGAP Flandria Flandria GAP

Fruitnet Organic Farming

71,03 40,58 52,6 42,53 55,53 54,13 42,69

With regard to the obtained results obtained, the label Charte Perfect appears to have the highest score concerning food safety. This can be linked to the fact that Charte Perfect is complementary with the HACCP. Indeed the Charte Perfect describes the risks, the critical control points, the hitherto corresponding limits and the means of surveillance in order to identify the most suited corrective actions in case a problem should occur (Steurbaut and

59

Garreyn, 2006). In terms of food safety, the label Terra Nostra did score average. However, the guidelines followed by producers are strictly confined to potato crops and therefore contain less criteria than other labels. The fact that Eurep Gap promote HACCP can explain why the score obtained is quite good. One can see the increase of the score between Flandria and FlandriaGap (12%). Regarding hygiene the FlandriaGAP specifications are stricter and more numerous. Moreover a strong point of FlandriaGAP is that the emphasis is on verifying whether the inspection points are effective in order to comply with the directives, whereas the emphasis of EurepGAP tends to be on registration. FlandriaGAP also puts a strong emphasis on the content of the specifications, which other certification schemes, such as Organic Farming and integrated Farming sometimes overlook. Given the fact that the auctions Mechelse Veilingen and Veiling Hoogstraten are certified for various systems (ISO, HACCP, BRC...), the standards are set quite high as far as the raw materials coming into the auctions are concerned. The grower, therefore, has to act as an extension of the quality label. That is why the ideology of the ISO and HACCP systems are incorporated into the FlandriaGAP system. FlandriaGAP's real asset is its residue monitoring programme. Every year, some 14,000 mostly carefully directed samples are taken at the LAVA auctions, and this at the most critical points. In the case of most other specifications, this sampling is not carefully directed. The high score obtained by Fruitnet for Food Safety can be explained by the fact that EurepGAP approval is a mandatory obligation required of each fruit grower wishing to market his fruit under the “Fruitnet” trademark. Fruitnet employs the most appropriate techniques for the preservation of the environment, prohibiting the most toxic pesticides to the environment and nature and classifying products in a green, yellow and orange list in function of their degree of toxicity with respect to the environment, humans and beneficial fauna. In case of a risk of major economic damage (treatment threshold was exceeded) the grower must choose a control method. Naturally, priority must be given to natural enemies of the pest in question, but when these are insufficient the grower will have to opt for a more appropriate biological or chemical treatment. The most selective, least toxic, least persistent product, which is as safe as possible to humans and the environment, must be selected. One can still raise the question of the safety of those pesticides included in the green and orange lists towards the consumers. It might be useful to check if the proposed pesticides are offering a better choice not only for the environment and the applicator but also in terms of residues left in the crop.

2.2.8.42.2.8.42.2.8.42.2.8.4 CCCCONCLUSION CONCERNINGONCLUSION CONCERNINGONCLUSION CONCERNINGONCLUSION CONCERNING THE USEFULLNESS OF THE USEFULLNESS OF THE USEFULLNESS OF THE USEFULLNESS OF GREENLABELSGREENLABELSGREENLABELSGREENLABELS

In the frame of the national pesticide reduction program, it is of utmost importance to find alternatives to reduce pesticide impacts on consumers. The study of Steurbaut and Garreyn (2006, in press) provides relevant information about performance of Belgian Greenlabels. Assessed mainly by evaluating the sustainability of the rules contained in certification books, greenlabels can represent a solution to reduce pesticide residues in foodstuffs as various precautions are taken to minimize uses of pesticides. The way pesticides are used, respecting doses and time of application is surely contributing to avoid contamination of foodstuffs. However, it is difficult to quantify the impacts of greenlabels on pesticide residue levels due to a lack of field results (pesticide monitoring data). But rules that have to be respected by certified farmers should help to decrease pesticide residues.

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3333 BBBBIOCIDE RISK EVALUATIIOCIDE RISK EVALUATIIOCIDE RISK EVALUATIIOCIDE RISK EVALUATION OF THE ON OF THE ON OF THE ON OF THE BBBBELGIAN SITELGIAN SITELGIAN SITELGIAN SITUATIONUATIONUATIONUATION

3.1 Selection of the risk indicator Worldwide, discussion is still ongoing on the ‘ideal’ indicator to quantify the impact of biocides on human health and the environment. In general, the indicator should comply with the following criteria:

• the indicator should represent a risk, combining exposure and effect;

• the indicator should not be too complex, since an annual recalculation might be required to follow impact trends;

• the indicator should represent the risk for the environment and for human health;

• the indicator should be composed of obvious parameters, reducing uncertainty due to lack of data.

Next to these criteria, some characteristics related to biocides should be taken into account:

• a great variety of formulation types implies the need for various emission scenarios;

• importance of human health aspect, seen from the variety of users (professionals/general public);

• effect data of active substances which are not authorized in PPP are often scarce;

• it is difficult to get an insight of the amount of biocidal products that are used. As mentioned earlier, the impact of PT18 biocides is most relevant for human health since these biocides are mainly used indoors. Taking into account the given timeframe of the HEEPEBI study, a pragmatic approach of the risk assessment is needed. Therefore it was decided to focus on human health when selecting the indicator to quantify the impact of PT18 biocides. A risk indicator should assess exposure and effect. Taking into account the use pattern of PT18 biocides, a specific exposure assessment of the applicator and the secondary exposed persons (e.g. playing children) is needed. The technical notes for guidance on human exposure to biocidal products (European Commission, 2002) and other European documents which are to be published (Steurbaut, pers. comm.) set database models for several formulation types (cf. task 2). These models allow for a calculation of the exposure of the applicator and the secondary exposed persons. In analogy with the European registration dossiers for plant protection products, the effect of a PT18 biocide on the applicator and the secondary exposed persons can be quantified by means of the Acceptable Operator Exposure Level. A detailed description of the different aspects of the indicator is given hereafter.

3.2 Description of the indicator

3.2.13.2.13.2.13.2.1 Applicator exposure assessmentApplicator exposure assessmentApplicator exposure assessmentApplicator exposure assessment

It is assumed that dermal and inhalatory exposure can occur during application of PT18 products. Chronic exposure is calculated from acute exposure as follows:

61

Chronic exposure (year averaged exposure) = yearNcont,

Nyear*tionEXPapplica

Where: EXPapplication = exposure during one event (mg/kg body weight/day) Nyear = number of events per year Ncont,year = number of contact days per year EXPapplication represents the acute exposure, which is calculated as follows:

EXPapplication = (EXPderm * PFderm) + (EXPinhal * PFinhal)

Where: EXPapplication = exposure during one event (mg/kg body weight/day)

• EXPderm = dermal exposure during application (mg/kg body weight/day)

• PFderm = penetration factor through skin

• EXPinhal = inhalatory exposure during application (mg/kg body weight/day)

• PFinhal = penetration factor through lungs by inhalation EXPderm = EXPderm/body + EXPderm/hand + EXPderm/feet

• EXPderm/body = dermal exposure on the body during application (mg/kg body weight/day)

• EXPderm/hand = dermal exposure on the hands during application (mg/kg body weight/day)

• EXPderm/feet = dermal exposure on the feet during application (mg/kg body weight/day)

EXPderm/body = ((Xbody * Texp * RPcloth / 100) * Conc) / BW

• EXPderm/body = dermal exposure on the body during application (mg/kg body weight/day)

• Xbody = product on clothing rate (mg/min)

• Texp = duration (min)

• RPcloth = relative penetration of clothing (%)

• Conc = concentration of active substance (g/kg)

• BW = body weight human (60 kg) EXPderm/hand = ((Xhand * Texp * RPgloves / 100) * Conc) / BW

• EXPderm/hand = dermal exposure on the hands during application (mg/kg body weight/day)

• Xhand = product on hands rate (mg/min)


• RPgloves = relative penetration of gloves (%)


• BW = body weight human (60 kg)

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EXPderm/feet = ((Xshoes * Texp * RPshoes / 100) * Conc) / BW

• EXPderm/feet = dermal exposure on the feet during application (mg/kg body weight/day)

• Xfeet = product on feet rate (mg/min)


• RPshoes = relative penetration of shoes (%)


• BW = body weight human (60 kg) EXPinhal = [(Xinhal * RR * Texp * RPinhal / 100) * Conc] / BW

• EXPinhal = inhalarory exposure during application (mg/kg body weight/day)

• Xinhal = product concentration in air (mg/m³)

• RR = respiratory rate (m³ / min)


• RPinhal = relative penetration of protective equipment (%)


• BW = body weight human (60 kg) The values of some exposure parameters depend on the application scenario, which is in turn depended of the type of the applicator (whether or not professional), the formulation type (ready to use liquid, powder, …), the application device (aerosol can, trigger, …) and the treatment type (flying insects, crawling insects, ectoparasites, …). These parameters were distinguished in task 2 (cf. Annex 9 of Task 2) for each product that is considered in this report. Subsequently, each of these products has been linked to a corresponding exposure scenario, using the following information sources in order of priority:

• European exposure scenarios from documents which are to be published (Steurbaut, pers. comm.);

• European exposure scenarios as described in the TnG (European Commission, 2002), completed by means of expert judgement.

Due to lack of information on the specific use of the product, the some assumptions had to be made. In general:

• Aerosol sprayer against flying insects and no label information: assumed to correspond with ‘consumer spraying and dusting model 1’;

• Aerosol sprayer against crawling insects and no label information: assumed to correspond with ‘consumer spraying and dusting model 2’;

• Powder against crawling insects and no label information: assumed to correspond with ‘consumer spraying and dusting model 2’;

• some products have various applications which correspond with different exposure scenarios (e.g. Ti-Tox Total: flying and crawling insects: consumer spraying and dusting model 1 and 2). For such products all exposure scenarios were calculated.

More specifically:

• Air Control (3497B): assumed to be air sprayed;

• Bayer Antiparasitical Powder (304B): pet treatment assumed;

• Bayer Antiparasitical Spray (104B): pet treatment assumed;

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• Baygon Powder against crawling insects (4479B): surface treatment assumed;

• Bolfo Powder (3079B pet treatment assumed;

• Canitex Powder (1582B): pet treatment assumed;

• Dalf Spray (1396B): pet treatment assumed;

• Defencare Spray (494B): pet treatment assumed;

• Detrans CIK (500B): air space treatment assumed;

• Detrans OB FIK (3004B): air space treatment assumed;

• Detrans WB FIK (2105B): air space treatment assumed;

• Insecticide Kaporex all crawling insects (1200B): surface treatment assumed;

• Insectivore vrac (4778B): surface treatment assumed;

• Insectstop (8887B): air space treatment assumed;

• Itec (1099B): air space treatment assumed;

• K.O. Spray against crawling insects (1501B): surface treatment assumed;

• Kapo flying insects with natural vegetable pyrethrins (3296B): air space treatment assumed;

• Kapo insecticide all flying insects (8687B): air space treatment assumed;

• Kaporex insecticide crawling insects spraying liquid (3396B): surface treatment assumed;

• Max insecticide powder (1698B): pet treatment assumed;

• Pybuthrin 33 (4486B): surface treatment assumed;

• Smash Killer CE10 (5305B): assumed that product is sprayed at low pressure (1 to 3 bar);

• Vitakraft Insecticide Spray (4701B): pet treatment assumed. An overview of the ‘formulation – application device – treatment’ combinations and their corresponding European scenarios (European Commission, 2002; Steurbaut, pers. comm.) are given in table 3-41. ‘Professionals-only’ scenarios (class A products) are indicated in boldboldboldbold. A short description of each European scenario involved, is given hereafter:

• Consumer product spraying and dusting model 1: air space spraying with pre-pressurised aerosol cans, trigger sprays and pumped sprays; non-professionals;

• Consumer product spraying and dusting model 2: surface spraying (soft furnishings, skirting boards, shelves) with pre-pressurised aerosol cans, trigger sprays and dust applicator packs; also vacuum cleaning dust deposits; non-professionals;

• Electrical evaporator for amateur use: p.m.;

• Spraying model 1: mixing and loading liquids and powders in compression sprayers or dusting applicators, and applying at 1 to 3 bar pressure as a coarse or medium spray, indoors and outdoors, overhead and downwards; low-pressure insecticide application; professionals principally;

• Spraying model 7: disinfection by spraying surfaces at up to 14 bar or with hand-held compression sprayer (up to 3 bar) – carpets, walls, ceiling voids. Duration 17 to 141 min (median at 47 min). No mixing or loading; professionals;

• Misting model 1: misting at low level using controlled droplet application (CDA) wand (CDA low level sprayer); no mixing or loading; professionals;

• Fogging model 3: fogging at mid level using fogging machine; no mixing or loading; professionals.

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The default parameter values to be used in the scenarios ‘Consumer product spraying and dusting model 1 (aerosol/trigger)’, ‘Consumer product spraying and dusting model 2 (trigger)’, ‘Electrical evaporator for amateur use’ and ‘Spraying model 1 - wasps’ are listed in table 3-42. These parameters are described in various European documents which are to be published. The degree of uncertainty of the Xbody, Xhand, Xshoes and Xinhal values are indicated by means of a letter (M: moderate, H: high) (Steurbaut, pers. comm.). The exposure from applying an electrical evaporator device was considered to be negligible, when the apparatus is properly installed. However, the secondary exposure through inhalation is calculated in analogy with the applicator inhalation exposure of the other scenarios. therefore, the secondary inhalatory exposure from electrical evaporators is given in table 3-42.

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Table 3Table 3Table 3Table 3----41: Relevant formulation types and corresponding European human exposure scenarios41: Relevant formulation types and corresponding European human exposure scenarios41: Relevant formulation types and corresponding European human exposure scenarios41: Relevant formulation types and corresponding European human exposure scenarios

FormulationFormulationFormulationFormulation Application deviApplication deviApplication deviApplication devicececece TreatmentTreatmentTreatmentTreatment European scenarioEuropean scenarioEuropean scenarioEuropean scenario

Aerosol Aerosol sprayer Flying insects, in and around the residence Consumer spraying and dusting model 1

Aerosol Aerosol sprayer Ectoparasites on domestic animals Consumer product spraying and dusting model 2

Aerosol Aerosol sprayer Crawling insects, in and around the residence

Consumer product spraying and dusting model 2

Aerosol "One shot" aerosol sprayer

Flying and crawling insects, no animals or persons present during application No corresponding scenario available

Bait Bait box Cockroaches No corresponding scenario available

Cardboard platelet Electrical evaporator Mosquitos Electrical evaporator for amateur use

Collar Collar Ectoparasites on cats and dogs No corresponding scenario available

Concentrated suspension

Spraying device for local application Crawling insects, local application Spraying model 1

Concentrated suspension in micro-capsules

Spraying device producing coarse droplets Crawling insects, local application


Gel Spraygun Cockroaches and crickets No corresponding scenario available

PastePastePastePaste SpraygunSpraygunSpraygunSpraygun Cockroaches and cricketsCockroaches and cricketsCockroaches and cricketsCockroaches and crickets No corresponding scenario availableNo corresponding scenario availableNo corresponding scenario availableNo corresponding scenario available

Liquid Trigger Crawling insects Consumer product spraying and dusting model 2

Liquid Electrical evaporator Mosquitos Electrical evaporator for amateur use

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Liquid to be dilutedLiquid to be dilutedLiquid to be dilutedLiquid to be diluted Pulverisation or thermoPulverisation or thermoPulverisation or thermoPulverisation or thermo----nebulation devicenebulation devicenebulation devicenebulation device

Flying and crawling insects, especially Flying and crawling insects, especially Flying and crawling insects, especially Flying and crawling insects, especially in poultry unitsin poultry unitsin poultry unitsin poultry units Spraying model 1Spraying model 1Spraying model 1Spraying model 1

Liquified gasLiquified gasLiquified gasLiquified gas Fumigation deviceFumigation deviceFumigation deviceFumigation device Crawling insectsCrawling insectsCrawling insectsCrawling insects No corresNo corresNo corresNo corresponding scenario availableponding scenario availableponding scenario availableponding scenario available

Plastic platelet Plastic platelet Ants in and around the residence No corresponding scenario available

Powder Canister

Ectoparasites on cats and dogs Crawling insects in and around the residence


PowderPowderPowderPowder Powder distributorPowder distributorPowder distributorPowder distributor Wasp nestsWasp nestsWasp nestsWasp nests Spraying model 1Spraying model 1Spraying model 1Spraying model 1

Product for hot or Product for hot or Product for hot or Product for hot or cold evaporationcold evaporationcold evaporationcold evaporation

Suitable nebulisation Suitable nebulisation Suitable nebulisation Suitable nebulisation devicedevicedevicedevice Flying (mainly) and crawling insectsFlying (mainly) and crawling insectsFlying (mainly) and crawling insectsFlying (mainly) and crawling insects Fogging model 3Fogging model 3Fogging model 3Fogging model 3

Ready to use solution Synthetic bottle

Ectoparasites on cats and dogs Flying and crawling insects in and around the residence No corresponding scenario available

Ready to use solution

Low pressure spraying device producing coarse droplets

Flying an crawling insects, local application in cracks and crevices


Ready to use Ready to use Ready to use Ready to use solutionsolutionsolutionsolution Brush Brush Brush Brush Lacquer against crawling insectsLacquer against crawling insectsLacquer against crawling insectsLacquer against crawling insects No corresponding scenario availableNo corresponding scenario availableNo corresponding scenario availableNo corresponding scenario available

Ready to use Ready to use Ready to use Ready to use solutionsolutionsolutionsolution SprayerSprayerSprayerSprayer Lacquer against crawling insectsLacquer against crawling insectsLacquer against crawling insectsLacquer against crawling insects Spraying model 1Spraying model 1Spraying model 1Spraying model 1

Ready to use Ready to use Ready to use Ready to use solutionsolutionsolutionsolution TriggerTriggerTriggerTrigger

Flying and crFlying and crFlying and crFlying and crawling insects, local awling insects, local awling insects, local awling insects, local application directly on walls and application directly on walls and application directly on walls and application directly on walls and objectsobjectsobjectsobjects No corresponding scenario availableNo corresponding scenario availableNo corresponding scenario availableNo corresponding scenario available

Ready to use solution Trigger

Ectoparasites at sleep and resting places of animals Flying and crawling insects (local


67


application)

Ready to use Ready to use Ready to use Ready to use solutionsolutionsolutionsolution

Misting or surface sprayingMisting or surface sprayingMisting or surface sprayingMisting or surface spraying Flying and crawling insectsFlying and crawling insectsFlying and crawling insectsFlying and crawling insects

Misting model 1Misting model 1Misting model 1Misting model 1 Spraying model 7Spraying model 7Spraying model 7Spraying model 7

Ready to use stick Stick Ants in and around the residence No corresponding scenario available

Tablet electrical evaporator Mosquitos Electrical evaporator for amateur use

Table 3Table 3Table 3Table 3----42: Overview of default parameter values for each European scenario (Steurbaut, pers. comm.)42: Overview of default parameter values for each European scenario (Steurbaut, pers. comm.)42: Overview of default parameter values for each European scenario (Steurbaut, pers. comm.)42: Overview of default parameter values for each European scenario (Steurbaut, pers. comm.)

EU scenarioEU scenarioEU scenarioEU scenario Consumer product spraying and Consumer product spraying and Consumer product spraying and Consumer product spraying and dusting model 1dusting model 1dusting model 1dusting model 1

Consumer product spraying and dusting Consumer product spraying and dusting Consumer product spraying and dusting Consumer product spraying and dusting modemodemodemodel 2l 2l 2l 2

Electrical Electrical Electrical Electrical evaporators evaporators evaporators evaporators (secondary (secondary (secondary (secondary exposure)exposure)exposure)exposure)

Spraying model 1Spraying model 1Spraying model 1Spraying model 1

Application aerosol trigger aerosol trigger hand-held dust

applicator

wasps professional

wasps amateur

Xbody (mg/min) 113/M 42.4/M 45.20 9.7/M 2.74 NR 92/M 92/M

Xhand (mg/min) 156/M 136/M 64.70 36.1/M 2.73 NR 10.7/M 181/H

Xshoes (mg/min) 0/M 0/M 0 0/M 0 NR 0/M 0/M

Xinhal (mg/m³) 234/M 90.2/M 35.90 10.5/M 2.47 * 104/M 104/M

Texp (min) 0.33 0.33 0.33 1.5 0.33 0.1 2 5

RR (m³/min) 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02

RPcloth (%) 50 50 50 50 50 50 10 50

RPgloves (%) 100 100 100 100 100 100 100 100

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EU scenarioEU scenarioEU scenarioEU scenario Consumer product spraying and Consumer product spraying and Consumer product spraying and Consumer product spraying and dusting model 1dusting model 1dusting model 1dusting model 1

Consumer product spraying and dusting Consumer product spraying and dusting Consumer product spraying and dusting Consumer product spraying and dusting modemodemodemodel 2l 2l 2l 2

Electrical Electrical Electrical Electrical evaporators evaporators evaporators evaporators (secondary (secondary (secondary (secondary exposure)exposure)exposure)exposure)


Application aerosol trigger aerosol trigger hand-held dust

applicator

wasps professional

wasps amateur

RPshoes (%) 100 100 100 100 100 100 100 100

RPinhal (%) 100 100 100 100 100 100 10 100

PFinhal (%) 100 100 100 100 100 100 100 100

PFderm (%) 10 10 10 10 10 1 10 10

Nday (number) 1 1 1 1 1 150 3 1

Nyear (number) 90(1) 90(1) 90(1) 9 90(1) 90(1) 5

*Xinhal = emission rate (mg/hour)*concentration a.s. (%) / volume room (m³) (1): it is assumed that insects are a nuisance during the summer months (3 months/year = 90 days) M: moderate degree of uncertainty H: high degree of uncertainty

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For some other applications, solely scenarios described in the TnG (European Commission, 2002) are available. It concerns: ‘Spraying model 1 (general professionals)’, ‘Spraying model 7’, ‘Misting model 1’ and ‘Fogging model 3’. TnG parameter values are given in Table 3-43. However, the information given in the TnG (European Commission, 2002) does not allow for a complete exposure assessment by means of the choosen indicator. The parameters indicated in italics in Table 3-24 were determined by means of expert judgement. The degree of uncertainty of the Xbody, Xhand, Xshoes and Xinhal values are indicated by means of a letter (M: moderate, H: high) (Steurbaut, pers. comm.).

Table 3Table 3Table 3Table 3----43: Overview of default parameters for each European scenario (European Commission, 43: Overview of default parameters for each European scenario (European Commission, 43: Overview of default parameters for each European scenario (European Commission, 43: Overview of default parameters for each European scenario (European Commission, 2002)2002)2002)2002)

Fogging model 3 Fogging model 3 Fogging model 3 Fogging model 3 (professionals)(professionals)(professionals)(professionals)

Misting model 1 Misting model 1 Misting model 1 Misting model 1 (professionals)(professionals)(professionals)(professionals)

Spraying model 1 Spraying model 1 Spraying model 1 Spraying model 1 (professionals)(professionals)(professionals)(professionals)

Spraying Spraying Spraying Spraying model 7 model 7 model 7 model 7 (professionals)(professionals)(professionals)(professionals)

Xbody (mg/min) 1.13/H 13.8/H 92/M 100

Xhand (mg/min) 0.33/H 0.12/M 10.7/M 0

Xshoes (mg/min) 0/H 0.26/H 0/M 0

Xinhal (mg/m³) 0/H 24/H 104/M 0

Texp (min) 40 40 *(1) 47

RR (m³/min) 0.02 0.02 0.02 0.02

RPcloth (%) 10 10 10 10

RPgloves (%) 100 100 100 100

RPshoes (%) 100 100 100 100

RPinhal (%) 10 10 10 10

PFinhal (%) 100 100 100 100

PFderm (%) 10 10 10 10

Nday (number) 1 1 1 1

Nyear (number) 150 150 150 150

(1): dependent of treatment type Scenarios for the treatment of pets were not encountered in the available literature. Scenarios were established by expert judgement, based on the scenarios that are provided by Steurbaut (pers. comm.) and the TnG (European Commission, 2002). The default parameters for these scenarios are given in table 3-44.

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Table Table Table Table 3333----44: Overview of default parameters for pet treatment scenarios (expert judgement)44: Overview of default parameters for pet treatment scenarios (expert judgement)44: Overview of default parameters for pet treatment scenarios (expert judgement)44: Overview of default parameters for pet treatment scenarios (expert judgement)

Consumer product Consumer product Consumer product Consumer product spraying and dusting spraying and dusting spraying and dusting spraying and dusting model 2 model 2 model 2 model 2 –––– aerosol aerosol aerosol aerosol (pets)(pets)(pets)(pets)

Consumer product Consumer product Consumer product Consumer product spraying and dusting spraying and dusting spraying and dusting spraying and dusting model 2 model 2 model 2 model 2 –––– trigger trigger trigger trigger (pets)(pets)(pets)(pets)

Consumer product Consumer product Consumer product Consumer product spraying and dusting spraying and dusting spraying and dusting spraying and dusting model model model model 2 2 2 2 –––– hand hand hand hand----held held held held dusting applicator dusting applicator dusting applicator dusting applicator (pets)(pets)(pets)(pets)

Xbody (mg/min) 45.2 9.7 2.74

Xhand (mg/min) 64.7 36.10 2.73

Xshoes (mg/min) 0 0 0

Xinhal (mg/m³) 35.9 10.50 2.47

Texp (min) 0.33 1.5 0.33

RR (m³/min) 0.02 0.02 0.02

RPcloth (%) 50 50 50

RPgloves (%) 100 100 100

RPshoes (%) 100 100 100

RPinhal (%) 100 100 100

PFinhal (%) 100 100 100

PFderm (%) 10 10 10

Nday (number) 1 1 1

Nyear (number) (1) 24 24 24

(1): it is assumed that pets are treated the whole year round (worst case scenario) and that a treatment lasts for 2 weeks

3.2.23.2.23.2.23.2.2 Secondary exposure assessmentSecondary exposure assessmentSecondary exposure assessmentSecondary exposure assessment

After the application of the product, people might be exposed through various pathways:

• Inhalation (e.g. aerosols, electrical evaporation devices, …);

• Dermal (e.g. cat/dog collars, contact with treated surfaces, …);

• Oral (e.g. ant powder, contact with treated surfaces, …). The proposed exposure models, which are discussed hereafter, are based on the principles of the EU Directive 98/8/EC (Steurbaut, pers. comm.). It can be assumed that dermal and oral secondary exposure is only relevant for children, except for products used on animals (pets and lifestock). Dermal exposure EXPdermal = Tappl * R * Conc * Dep * Disl * TC * Texp / Opp

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Where:

Tappl = duration of the application (min) R = amount of product released per time unit (kg/min)

Conc = concentration of a.s. in product (g/kg) Dep = amount of sprayed volume that is deposited on the floor (%)

Disl = amount of product that is dislodgeable (%) TC = transfer contact surface (m2/day)

Texp = exposure time (default 7 days: it is assumed that the surface is cleaned after 1 week)

Opp = exposed surface (m2) Oral exposure EXPoral = EXPderm * 10% Inhalatory exposure EXPinhalation = Cs * I / bw, with Cs =: p * MW * f / (R * T) Where:

Cs = saturated air concentration of the active substance I = respiration rate (adult 20 m3/day; child 4 m3/day) bw = body weight (adult 60kg; child 10 kg) p = vapour pressure of the active substance (Pa)1 MW = molecular weight of the active substance (g/mol) f = conversion factor from g to µg (106) R = gas constant (8.314 J/mol.K) T = temperature (293 K) Some parameter values are specific for each application scenario. Default values, given in tables 3-45 and 3-46, are set by expert judgement in analogy with European scenarios (Steurbaut, pers. comm.).

1 Conversion factors: 100 Pa = 1 mbar and 1 mbar = 0.750 mm Hg; 1 Torr = 1 mm Hg

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Table 3Table 3Table 3Table 3----45: Overview of default parameter values for secondary exposure (Steurbaut, pers. comm.)45: Overview of default parameter values for secondary exposure (Steurbaut, pers. comm.)45: Overview of default parameter values for secondary exposure (Steurbaut, pers. comm.)45: Overview of default parameter values for secondary exposure (Steurbaut, pers. comm.)

ParameterParameterParameterParameter Air sprays/triggers and Air sprays/triggers and Air sprays/triggers and Air sprays/triggers and electrical evaporatorselectrical evaporatorselectrical evaporatorselectrical evaporators (Consumer product (Consumer product (Consumer product (Consumer product spraying and dustispraying and dustispraying and dustispraying and dusting ng ng ng model 1, Electrical model 1, Electrical model 1, Electrical model 1, Electrical evaporator for evaporator for evaporator for evaporator for amateur use)amateur use)amateur use)amateur use)

Surface sprays Surface sprays Surface sprays Surface sprays (Consumer product (Consumer product (Consumer product (Consumer product spraying and dusting spraying and dusting spraying and dusting spraying and dusting model 2 model 2 model 2 model 2 aerosol/trigger)aerosol/trigger)aerosol/trigger)aerosol/trigger)


Rcrack and crevice

0.33 g formulation/sec

0.33 g/sec

Rgeneral surface 0.65 g formulation/sec

0.65 g/sec

Rair space application

0.35 g formulation/sec

Relectrical evaporator

50 mg/h

Dep 15% 80% 15% (air space), 80% (surface spraying)

Disl 30% 30% 30%

TC 2.3 m2/day 2.3 m²/day or 0.23 m²/day(1)

0.23 m2/day

Opp 20 m2 5 m² 2 m2

(1) For local applications such as cracks and crevices It is assumed that inhalatory exposure is negligible for powders used for dusting of wasps.

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Table 3Table 3Table 3Table 3----46: Overview of default parameter values for secondary exposure, determined by expert judgement46: Overview of default parameter values for secondary exposure, determined by expert judgement46: Overview of default parameter values for secondary exposure, determined by expert judgement46: Overview of default parameter values for secondary exposure, determined by expert judgement

ParameterParameterParameterParameter Sprays/triggers foSprays/triggers foSprays/triggers foSprays/triggers for pet r pet r pet r pet treatment (Consumer treatment (Consumer treatment (Consumer treatment (Consumer product spraying and product spraying and product spraying and product spraying and dusting model 2 dusting model 2 dusting model 2 dusting model 2 –––– pets) pets) pets) pets)

Powder for control of Powder for control of Powder for control of Powder for control of crawling insects crawling insects crawling insects crawling insects (Consumer product (Consumer product (Consumer product (Consumer product spraying and dusting spraying and dusting spraying and dusting spraying and dusting model 2 dust pack model 2 dust pack model 2 dust pack model 2 dust pack applicators)applicators)applicators)applicators)

Powder for control of Powder for control of Powder for control of Powder for control of ectoparasites ectoparasites ectoparasites ectoparasites (Consumer product (Consumer product (Consumer product (Consumer product spraying and dusting spraying and dusting spraying and dusting spraying and dusting mmmmodel 2 dust pack odel 2 dust pack odel 2 dust pack odel 2 dust pack applicators)applicators)applicators)applicators)

Fogging Fogging Fogging Fogging model 3 & model 3 & model 3 & model 3 & misting misting misting misting model 1model 1model 1model 1

Spraying Spraying Spraying Spraying model 7model 7model 7model 7

Rtargeted spot

Rcrack and crevice 10 g/min

Rgeneral surface 0.65 g /sec 10 g/min 0.65 g/sec

Rair space application 0.35 g/sec

Relectrical evaporator

Dep 80% 80% 80% 15% 80%

Disl 30% 30% 3% 30% 30%

TC 0.23 m²/day 0.23 m2/day 0.23 m²/day 2.3 m²/day 2.3 m²/day

Opp 2 m² 5.26 m2 2 m² (1) 20 m² 20m²

(1) For lifestock: 5m²

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The following assumptions were made when determining the parameters in Table:

• sprays/triggers for pet treatment: the exposure rate of the applicator, experimentally determined for surface spraying with pre-pressurised aerosol cans (TnG Consumer product spraying and dusting model 2), was used;

• powder for control of ectoparasites: the exposure rate of the applicator, experimentally determined for hand-held dust applicator packs for cracks and crevices (TnG Consumer product spraying and dusting model 2) was used. Parameters to calculate secondary exposure were assumed to be the same as those used for pre-pressurised aerosol cans, except for “release of product per unit of time”. The latter was taken from TnG Consumer product spraying and dusting model 2 - hand-held dust applicator packs for cracks and crevices.

3.2.33.2.33.2.33.2.3 EfEfEfEffect assessmentfect assessmentfect assessmentfect assessment

The indicator uses the Acceptable Operator Exposure Level (AOEL) to assess the effect of the active substance(s). An AOEL is a health-based exposure limit and is established on the basis of the toxicological properties of an active substance. The AOEL represents the internal (absorbed) dose available for systemic distribution from any route of absorption and is expressed as mg/kg bw/d. It is set on the basis of oral studies provided that no major route-specific differences are anticipated (Commission of the European Communities – DG SANCO, 2001). If the AOEL value is not available for an active substance, the Allowable Daily Intake (ADI) is used instead. An overview of the AOEL- and ADI-values used is given in table 3-47.

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Table 3Table 3Table 3Table 3----47: Overview of AOEL and ADI values for the relevant active substances47: Overview of AOEL and ADI values for the relevant active substances47: Overview of AOEL and ADI values for the relevant active substances47: Overview of AOEL and ADI values for the relevant active substances

Active substanceActive substanceActive substanceActive substance AOELAOELAOELAOEL ADIADIADIADI

(mg/kg bw/d)(mg/kg bw/d)(mg/kg bw/d)(mg/kg bw/d) (mg/kg bw/d)(mg/kg bw/d)(mg/kg bw/d)(mg/kg bw/d)

allethrin NR 0,02

bioresmethrin NR 0,03

chlorpyrifos NR 0,01

cyfluthrin 0,02

cypermethrin NR 0,05

deltamethrin 0,0075

diazinon NR 0,002

esdepallethrin (= S-bioallethrin) NR 0,02

fenoxycarb NR 0,055

methylbromide NR 1

permethrin NR 0,05

phenothrin (d-) NR 0,07

piperonyl butoxide NR 0,2

propuxur 0,03

pyrethrins NR 0,04

resmethrin NR 0,125

tetrachlorvinphos NR 0,05

tetramethrin NR 0,02

transfluthrin NR 0,2

Source: European dossiers for the evaluation of the inclusion of the active substance in Annex I of Directive 91/414/EEC

3.2.43.2.43.2.43.2.4 Risk assessmentRisk assessmentRisk assessmentRisk assessment

The indicator allows for an exposure assessment of the applicator, an assessment for secondary exposure and an assessment of the effect of the product. Distinction is made between various formulation types. The risk assessment is calculated as:

risk = effect

exposure

A risk quotient > 1 implies that the target group is at risk. Three target groups can be distinguished:

• risk for the professional applicator;

• risk for the non-professional applicator (application + secondary exposure): if the applicator is the same person as the secondary exposed person (e.g. as is usually the case for ‘Consumer product spraying and dusting model 1’), both risk quotients can be summed;

• risk from secondary exposure (e.g. children)

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The risk quotient was calculated for each of the products, listed in Annex 9 of Task 2. The results are presented in Table 3-48 grouped by exposure scenario. The ID number of professionally applied products (class A products) are indicated in boldboldboldbold. A risk quotient > 1 is indicated in red. Within each exposure scenario group, the products are listed in descending order of risk for the secondary exposed child. This was an arbirtrary choice. The detailed calculation sheets are available on a CD-rom, delivered together with this report. The following assumptions were made when applying the indicator:

• a nominal density of 1 g/ml is taken into account (cf. EU models);

• molecular weight pyrethrins: 316 – 374 g/mol, the arithmatic average of 345 g/mol was taken into account;

• Zerox P: product used to control fleas in lifestock. It was assumed that no secondary exposure of children occurs. The treated surface taken into account is larger than that for pets;

• Bieva Spray: no mixing/loading assumed. It is assumed that the product is applied by means of a trigger;

• Kadox Spray: product to control ectoparasites at places where pets rest and sleep: product release rate for general surfaces is taken into account;

• Perma Sid, Total Insecticide: products to control crawling insects (craks and crevices) but also used to control ectoparasites at places where pets rest and sleep. According to the precautionary principle, the product release rate for general surfaces is taken into account (worst case) instead of the product release rate for cracks and crevices;

• Aerosol cans to control crawling insects: it was assumed that all applications are local (cracks and crevices);

• Exposure to electrical evaporators whilst installing the apparatus was considered not to be relevant when the apparatus is properly installed. Therefore, no risk quotient was calculated for the applicator for the scenario ‘Electrical evaporator amateur’. Consequently, no ‘risk quotient applicator = secondary exposed person’ was calculated either;

• It was assumed that for professional applications, the applicator does not remain in the room after the application. Consequently, no ‘risk quotient applicator = secondary exposed person’ was calculated for professional applications;

• A default emission rate of 50 mg/h was used for electrical evaporators.

Table 3Table 3Table 3Table 3----48: Risk quotient of sele48: Risk quotient of sele48: Risk quotient of sele48: Risk quotient of selected products for the different target groupscted products for the different target groupscted products for the different target groupscted products for the different target groups

ProductProductProductProduct IDIDIDID RQ RQ RQ RQ applicatorapplicatorapplicatorapplicator

RQ RQ RQ RQ secondary secondary secondary secondary exposed exposed exposed exposed childchildchildchild

RQ secondary RQ secondary RQ secondary RQ secondary exposed exposed exposed exposed adultadultadultadult

RQ applicator RQ applicator RQ applicator RQ applicator = secondary = secondary = secondary = secondary exposed adultexposed adultexposed adultexposed adult

Consumer product spraying and dusting model 2 Consumer product spraying and dusting model 2 Consumer product spraying and dusting model 2 Consumer product spraying and dusting model 2 ---- aerosol aerosol aerosol aerosol

Bolfo Direct 5998B 0,004 0,42 0,33 0,34

Ti Tox Total with bioallethrin 4601B 0,002 0,1 0,01 0,01

Kaporex all crawling insects 1200B 0,002 0,01 0,003 0,01

Ti Tox Total 1187B 0,001 0,01 0,004 0,01

Topscore Spray 896B 0,003 0,01 0,003 0,006

77





Vapona Spray crawling insects 885B 0,001 0,01 0,0002 0,002

KO Spray crawling insects 1501B 0,0003 0,002 0,00003 0,0004

Consumer product spraying and dusting model 2 Consumer product spraying and dusting model 2 Consumer product spraying and dusting model 2 Consumer product spraying and dusting model 2 ---- trigger pets trigger pets trigger pets trigger pets

Dalf Spray 1396B 0,0003 0,3 0,18 0,3

Pinto 9387B 0,0003 0,08 0,0006 0,08

Consumer product spraying and dustinConsumer product spraying and dustinConsumer product spraying and dustinConsumer product spraying and dusting model 2 g model 2 g model 2 g model 2 ---- trigger trigger trigger trigger

Bieva Spray 793B 0,0003 0,89 0,71 0,89

Topscore Pal 2890B 0,0003 0,89 0,71 0,89

Kaporex all crawling insects liquid 3396B 0,0003 0,2 0,0004 0,2

Perma Sid 2401B 0,0001 0,18 0,0001 0,18

Total Insecticide 2301B 0,0001 0,18 0,0001 0,18

Kadox Spray 398B 0,0003 0,16 0,0003 0,16

Consumer product spraying and dusting model 1 Consumer product spraying and dusting model 1 Consumer product spraying and dusting model 1 Consumer product spraying and dusting model 1 ---- aerosol aerosol aerosol aerosol

Detrans OB FIK 3004B 0,002 26,94 22,45 22,46

Detrans WB FIK 2105B 0,002 26,94 22,45 22,46

Air Control 3497B 0,004 0,42 0,33 0,34

Vapona Anti Wasp 6989B 0,004 0,11 0,09 0,09

Ti Tox Total with Bioallethrin 4601B 0,01 0,09 0,08 0,09

Fly-Kill 401B 0,01 0,01 0,003 0,01

HGX Spray 1201B 0,01 0,01 0,003 0,01

Insect Stop 8887B 0,002 0,01 0,001 0,003

Itec 1099B 0,01 0,01 0,003 0,01

Kapo flying insects with natural vegetable pyrethrins 3296B 0,01 0,01 0,002 0,01

Kapo all flying insects 8687B 0,01 0,01 0,002 0,01

Ti Tox Total 1187B 0,004 0,01 0,004 0,01

Topscore Spray 896B 0,01 0,01 0,003 0,01

Zerox 3999B 0,01 0,01 0,003 0,01

Zerox PA 3579B 0,003 0,01 0,002 0,01

Diagnos Spray 1300B 0,01 0,007 0,001 0,008

Detrans CIK 500B 0,001 0,001 0,00002 0,001

Consumer product Consumer product Consumer product Consumer product spraying and dusting spraying and dusting spraying and dusting spraying and dusting model 1 model 1 model 1 model 1 ---- trigger trigger trigger trigger

Insectivor vrac 4778B 0,003 0,1 0,08 0,09

Consumer product spraying and dusting modelConsumer product spraying and dusting modelConsumer product spraying and dusting modelConsumer product spraying and dusting model 2 2 2 2 ---- aerosol pets aerosol pets aerosol pets aerosol pets

Bayer Antiparasitical Spray 104B 0,0003 0,21 0,16 0,16

Bolfo Spray 3279B 0,0003 0,1 0,08 0,08

Vermikill Insecticide Spray 3399B 0,001 0,02 0,0002 0,001

78





Vitakraft Insecticide Spray 4701B 0,001 0,02 0,0002 0,001

Defencare Spray 494B 0,001 0,01 0,0002 0,001

Consumer product spraying and dusting model 2 Consumer product spraying and dusting model 2 Consumer product spraying and dusting model 2 Consumer product spraying and dusting model 2 ---- dust canister pets dust canister pets dust canister pets dust canister pets

Bolfo Powder 3079B 0,0001 0,87 0,51 0,51

Permas D 2683B 0,00002 0,12 0,001 0,001

Bayer Antiparasitical Powder 304B 0,00001 0,1 0,08 0,08

Canitex Powder 1582B 0,00004 0,03 0,0002 0,0002

Max Insecticide Powder 1698B 0,00003 0,02 0,0002 0,0002

Antilouse Powder 5384B 0,000003 0,003 0,0002 0,0002

Zerox P 4383B 0,00002 NR 0,003 0,003

Consumer product spraying and dusting model 2 Consumer product spraying and dusting model 2 Consumer product spraying and dusting model 2 Consumer product spraying and dusting model 2 ---- dust canister dust canister dust canister dust canister

Baygon Powder crawling insects 4479B 0,0002 0,38 0,31 0,31

Almetex 877B 0,0001 0,01 0,001 0,001

Vespa 402B 0,0001 0,005 0,00005 0,0002

Baygon Ant Powder 3805B 0,00004 0,002 0,00003 0,0001

K-Othrine insect powder 599B 0,00004 0,002 0,00003 0,0001

Mirazyl D 501B 0,00004 0,002 0,00003 0,0001

Pokon Ant Stop 799B 0,00004 0,002 0,00003 0,0001

Vapona Ant Powder 599B 0,00004 0,002 0,00002 0,0001

Electrical evaporator amateurElectrical evaporator amateurElectrical evaporator amateurElectrical evaporator amateur

Vapona electrical evaporator 6797B NR 0,87 0,95 NR

Vapona Tablet 1680B NR 0,45 0,48 NR

Vlido electrical antimosquito 2095B NR 0,45 0,48 NR

Mafu electrical evaporator 4399B NR 0,43 0,46 NR

Baygon electrical evaporator 1181B NR 0,43 0,46 NR

Pynamin Forte Mat 40 290B NR 0,38 0,41 NR

Fogging model 3 (professionals)Fogging model 3 (professionals)Fogging model 3 (professionals)Fogging model 3 (professionals)

Pyretrex Fogger 1296B1296B1296B1296B 0,002 1,165 0,003 NR

Misting model 1 (professionals)Misting model 1 (professionals)Misting model 1 (professionals)Misting model 1 (professionals)

Pybuthrin 33 4486B4486B4486B4486B 0,2 3,37 0,002 NR


Empire 200 2597B 0,59 15,78 0,18 0,77

K-Othrine Flow 25 2584B 0,09 2,5 0,000002 0,09

K-Othrine Flow 7,5 3785B 0,03 0,54 0,000003 0,03

Smash Killer CE10 5305B5305B5305B5305B 0,33 0,53 0,00003 NR

Foxide 5782B5782B5782B5782B 0,01 0,001 0,0001 NR

Spraying model 7 (professionals)Spraying model 7 (professionals)Spraying model 7 (professionals)Spraying model 7 (professionals)

Integral Blat 1598B1598B1598B1598B 1,74 1603,93 102,68 NR

Pybuthrin 33 4486B4486B4486B4486B 0,07 62,4 0,02 NR

79





Integral Tox 4200B4200B4200B4200B 0,02 21,08 0,01 NR

From Table 3-48 it is clear that for most of the products, none of the target groups are at risk (risk quotient < 1). The products which, according to the indicator, pose a risk to one or more target groups are listed hereafter (risk quotients indicated in red in Table 3-29). The probable reason for the high risk quotients is also given:

• Consumer product spraying and dusting model 1 – aerosol: Detrans OB FIK and Detrans WB FIK: high risk quotients for secondary exposure due to the relatively high vapour pressure (44 mPa) of esdepallethrin;

• Fogging model 3 (professionals): Pyretrex Fogger: high risk quotients for secondary exposed child due to long duration of the treatment (40 minutes) which leads to a high deposited concentration and thus a high potential dermal contact risk for playing children;

• Misting model 1 (professionals): Pybuthrin 33: high risk quotients for secondary exposed child due to long duration of the treatment (40 minutes) which leads to a high deposited concentration and thus a high potential dermal contact risk for playing children;

• Spraying model 1: o Empire 200: the high risk quotient for secondary exposed child is due to a

relatively long duration of the treatment (5 minutes) and to a lesser extend to a deposition rate of 80%;

o K-Othrine Flow 25: the high risk quotient for secondary exposed child is due to a relatively long duration of the treatment (5 minutes) and to a deposition rate of 80%;

• Spraying model 7 (professionals): o Integral Blat: the high risk quotient for the applicator is due long duration of

the treatment (47 minutes), combined with a rather low AOEL-value (2 µg/kg BW.d) for diazinon. The high risk quotient for the secondary exposed persons is mainly due to the rather high vapour pressure of diazinon (12 mPa), which results in a rather high saturated air concentration and thus a high potential for inhalation exposure. A high potential for dermal exposure due to a treatment duration of 47 minutes and a deposition rate of 80% adds to the high risk quotient for the secondary exposed child;

o Pybuthrin 33: the high risk quotient for the secondary exposed child is due to the rather long duration of the treatment (47 minutes), combined with a deposition rate of 80%, which leads to a high dermal exposure potential of the playing child;

o Integral Tox: cf. Pybuthrin 33. No data for hand exposure were available for ‘Spraying model 7’ (professionals). Consequently, the risk quotients for that scenario are underestimated. The risk quotients, given in Table 3-48, represent the impact of the biocidal products on human health, in particular on the health of the applicator and the secondary exposed

80

persons. The relevance of each impact for Belgium in a certain year can be calculated by multiplying the risk quotient by the amount of the product sold in that year. The risk quotients can be used to identify hazardous products, which should be subject to reduction measures. However, several assumptions were made in the calculation of these risk quotients. To adequately interprete these figures, these uncertainties should be addressed. This is discussed hereafter.

3.3 Uncertainties in the application of risk assessment indicator

3.3.13.3.13.3.13.3.1 Exposure assessmentExposure assessmentExposure assessmentExposure assessment

The choice of an adequate exposure scenario is essential to accurately assess exposure. This requires a good insight of the treatment type and the application device. This may be hampered by:

• inaccessible information on use characteristics of the product;

• the specificity of the product use. As mentioned in task 2, it is not evident to reveal the application device for a product. Easy access to the authorisation dossiers, from which this kind of information can be retrieved (assuming that a product is not authorized if the information, needed to carry out a human exposure assessment, is not adequately provided), should be provided. This will resolve the inaccessibility of information on use characteristics of the product. The specificity of the product use can limit the availability of an adequate exposure scenario. From table 3-42 it is clear that adequate exposure scenarios are lacking for several of the identified formulation/application device combinations. For the following products, it can be assumed that no exposure scenario is needed for the applicator if properly used:

• Cat/dog collar

• Bait in bait box

• Gel/paste applied with spraygun

• Ready to use stick

• Plastic platelet Except for ‘bait in bait box’ and ‘gel/paste applied with spraygun’, secondary exposure might be significant for these products. The combination ‘liquified gas/fumigation device’ refers to the fumigation of spaces with methyl bromide. Exposure scenarios are probably available from the applicators. A thorough literature search is needed to identify the available data on the exposure scenarios which are indicated in Table 3-49. ‘Professional only’ combinations are indicated in boldboldboldbold. The available data should be completed to establish accurate exposure scenarios.

81

Table 3Table 3Table 3Table 3----49: Exposu49: Exposu49: Exposu49: Exposure scenarios to be developedre scenarios to be developedre scenarios to be developedre scenarios to be developed

FormulationFormulationFormulationFormulation Application deviceApplication deviceApplication deviceApplication device TreatmentTreatmentTreatmentTreatment ApplicatorApplicatorApplicatorApplicator Secondary Secondary Secondary Secondary exposureexposureexposureexposure

aerosol "one shot" aerosol sprayer

Flying and crawling insects, no animals or persons present during application X X

collar collar Ectoparasites on cats and dogs - X

liquified gasliquified gasliquified gasliquified gas fumigation devicefumigation devicefumigation devicefumigation device Crawling insectsCrawling insectsCrawling insectsCrawling insects XXXX XXXX

plastic platelet plastic platelet Ants in and around the residence - X

ready to use solution synthetic bottle

Ectoparasites on cats and dogs Ants in and around the residence Flying and crawling insects X X

ready to use solutionready to use solutionready to use solutionready to use solution brush brush brush brush Lacquer against crawling insectsLacquer against crawling insectsLacquer against crawling insectsLacquer against crawling insects XXXX XXXX

ready to use solutionready to use solutionready to use solutionready to use solution triggertriggertriggertrigger

Flying and crawling insects, local Flying and crawling insects, local Flying and crawling insects, local Flying and crawling insects, local application directly on walls and application directly on walls and application directly on walls and application directly on walls and objectsobjectsobjectsobjects XXXX XXXX

ready to use stick stick Ants in and around the residence - X


It should be born in mind that some of the scenarios proposed in the Technical notes for Guidance and referred to in Table 3-41, have limitations:

• Consumer product spraying and dusting model 1: the conditions of the simulation exercises may not be a true representation of the way a product is meant to be used. The selection of application period, followed by dwell period is the key determinant of predicted deposition and dose through inhalation;

• Spraying model 7: no data for hand exposure, values based on small database, possible mismatch between techniques and geometry of the buildings in the USA and Europe;

• Misting model 1: data collected from a survey of application of amenity herbicides by controlled droplet application. The data are specific to this type of activity.

These restrictions question the accuracy of the scenarios. Furthermore, the calculation of dermal secondary exposure is based on 1 application and an exposure time of 7 days. However, in some scenarios, more than 1 application/week is taken into account (e.g. ‘Consumer product spraying and dusting model 1’: 90 days/year). The accumulation of the product that occurs in those scenarios is not taken into account when calculating dermal secondary exposure. The secondary exposure through inhalation is calculated from the saturated air concentration of the active substance. This parameter is calculated from intrinsic characteristics such as vapour pressure of the active substance, molecular wieght of the active substance, the gas constant and the temperature. As such, the saturated air concentration is independent of the applied amount of product or the room volume. This makes the exposure scenario less accurate.

3.3.23.3.23.3.23.3.2 Effect assessmentEffect assessmentEffect assessmentEffect assessment

The AOEL values used in this study, originate from European dossiers for the evaluation of the inclusion of the active substance in Annex I of Directive 91/414/EEC. In that framework, the AOEL ensures that the presence of an active substance in a PPP, used in a manner consistent with the label instructions and good plant protection practice, has no harmful effects on the health of operators (users of the PPP, i.e. mixer/loader or applicator), workers (persons re-entering treated crops, etc.) or bystanders (other persons in vicinity of a pesticide application) (Commission of the European Communities – DG SANCO, 2001). The test conditions to determine the AOEL value thus represent an occupational exposure situation (8 hours exposure). However, such conditions are not always representative for secondary exposure. Consequently, the use of these conservative AOEL values to assess the risk for secondary exposed persons will overestimate the risk. This should be born in mind when proposing reduction measures, based on the risk quotients. The AOEL might not be established for every active substance. In that case the Acceptable Daily Intake (ADI) is considered. From Table it is clear that this was the case for a lot of the active substances. The AOEL takes into account the oral, dermal and inhalatory exposure route, whilst the ADI solely takes into account the oral exposure route. This implies that the ADI might underestimate the effect of active substances contained in products for which the dermal and/or inhalatory exposure is also significant. Furthermore, an unwanted effect of a biocidal product might also be provoked by an additive. For example methylene chloride in Ti-tox Total with Bioallethrin is responsible for

HealthHealthHealthHealth and environmental effects of pesticides and type 18 biocides (HEEPEBI) and environmental effects of pesticides and type 18 biocides (HEEPEBI) and environmental effects of pesticides and type 18 biocides (HEEPEBI) and environmental effects of pesticides and type 18 biocides (HEEPEBI) 83

the labelling of the product with R40 (‘irreversible effects are not excluded’). AOEL values for additive substances are rather scarce, which hampers the introduction of additives in the indicator. Not taking into account such additives misrepresents the actual risk of the product. Various PT18 biocides contain more than one active substance. In this report, the exposure/effect ratio for each of these active substances is calculated and the risk of the product is represented by the sum of these ratios. This implies that the active substances do not influence one another with regard to effects. It can be assumed that this is not always the case and that another aggregation of the AOEL values is required.


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