PROBABILISTIC DIETARY EXPOSURE ASSESSMENT TO PESTICIDE RESIDUES

STRUCTURESTRUCTURE

Applications of probabilistic exposure assessments

Pesticide conceptual model

Exposure assessment to chlorpyrifos

• Input data

• Model settings

• Results of assessment

• Information on uncertainty

• Contribution of food items

APPLICATIONS APPLICATIONS

Risk assessment for pesticide authorisation

Risk assessment of registered pesticides

Characterisation of variability and uncertainty

Identification of the main contributions to the intake

EXPOSURE ASSESSMENTEXPOSURE ASSESSMENT

N Iterations Freq

uenc

y Pear Residue

Apple Residue

Orange Residue

Exposure = Σ(Consumption * Residue) / Bodyweight

Con

sum

ptio

n

P A O

2

1

N

4

3

Exposure assessmentExposure assessment

PESTICIDE CONCEPTUAL MODEL

PESTICIDE RESIDUE INTAKE

FOOD

SURVEY

PESTICIDE RESIDUE MONITORING PROGRAMME

CONSUMPTIO OF RAW AGRICULTURAL COMMODITY (RAC)

ADJUSTED

RESIDUE (PAC)

Bodyweight

oncocentratiPesticidenconsumptioFoodIntake

__

No Food Group

RACconsum ption

RAW conversionfactor

Edible portion

Recipe fraction

Food Group

Exam ine food code

RAW AGRICULTURALCOMMODITY CONSUMPTION

Processing factor

Assigning residueto RAC

Variability factor

Random assignationresidue

Pesticide present

W ith analyses LOR or 0

No pesticide detected

Generation random num ber0<= R <= 1

No analytical resultsMRL or 0

ASSIGNINGRESIDUE TO RAC

RA C C O NS UM PT IO N A D JUS T EDRE SID UE IN RA C

T O T A L PE S T IC ID E INT A K ES ubjec t 1

A dding upa l l events intakes

D ivid ing bybodyw e ight

E a ting eventpes tic ide intake

C O NSUM PT IO NX

RE SID UE

ACUTE EXPOSURE ASSESSMENTACUTE EXPOSURE ASSESSMENT

PESTICIDE:

Chlorpyrifos

POPULATION:

Infants of the Basque Country 8 to 12 months old

PERIOD: 1 day

INPUT DATA

Food consumption data Food diary and recipes. Basque Country

Bodyweight Food diary and recipes. Basque Country

Pesticide residue data Monitoring programmes CCAA Spain MRLs spanish legislation

INPUT DATA

Observed data

Data(0.08,0.24,0.039,0.26,0.68,0.43,0.20,0.06,0.63,0.61,1.6,0.38,0.53,0.94)

Histogram

Parametric distribution M1

4.00

3.75

3.50

3.25

3.00

2.75

2.50

2.25

2.00

1.75

1.50

1.25

1.00

.75

.50

.25

Histograma

Fre

cue

nci

a

30

20

10

0

Desv. típ. = .71

Media = 1.41

N = 108.00

Lognorm(1.43,0.83)

0.0

0.4

0.8

0.3 1.0 1.7 2.4 3.2 3.9

Lognorm

UNIT-TO-UNIT VARIABILITYUNIT-TO-UNIT VARIABILITY

Composite

sample

MEANANALYSIS

ACUTE EXPOSURE ?

UNIT TO UNIT VARIABILITY UNIT TO UNIT VARIABILITY OPTIONSOPTIONS

No variability adjustment

Concentration = mean for all units

Variability GVDSP raw lab data

Laboratory data for individual units

Variability GVDSP lognormal

Concentration in units described by a lognormal distribution

Variability RIKILT No. Units in composite sample

Concentration in units described by a Bernouilli distribution

LOGNORMAL VARIABILITY

R

0.0

0.5

0 2 4 6 8Log(R,f(R, ))

Distribution residues units

x r1 + x r3x r2 +Intake =

0

1

0.0 1.3 2.5 3.8 5.0

Distribution of residues Composite samples

Consumption: 3 apples

MEDIANMEAN

sd

95th p

Minimun

99th p

1 5 5090

95 97.598

99

99.5

99.9

2.5

97.5th p99th p

CHLORPYRIFOS

Intake (mg/kg d)

Pe

rce

ntil

es

30

40

50

60

70

80

90

100

-0.005 0.095 0.195 0.295 0.395

DD_I

MODEL_I

CONS_I

STEP2

VALIDATION: Cumulative distributionsVALIDATION: Cumulative distributions

CHARACTERISING UNCERTAINTYCHARACTERISING UNCERTAINTY

Processing factors: with vs. without

No analysis MRL vs. 0

Samples < LOR LOR vs 0

Variability with vs. without

REFERENCE MODEL:

WITH PROCES. WITH VARIAB MRL LOR

97.5th P

No proc factors

Reference model

LOR = 0

MRL = 0

No variability

CONTRIBUTION OF FOOD ITEMSCONTRIBUTION OF FOOD ITEMS95th Percentile95th Percentile

Kiwi

27%

Car r ot

22%Or ange

9%

Spinach

8%

Banana

8%

Apple

6%

P ear

3%

Char d

3%

P umpkin

2%

Other s

10%P otato

2%