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%