probabilistic dietary exposure assessment to pesticide residues
TRANSCRIPT
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PROBABILISTIC DIETARY EXPOSURE ASSESSMENT TO PESTICIDE RESIDUES
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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
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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
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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
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Exposure assessmentExposure assessment
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PESTICIDE CONCEPTUAL MODEL
PESTICIDE RESIDUE INTAKE
FOOD
SURVEY
PESTICIDE RESIDUE MONITORING PROGRAMME
CONSUMPTIO OF RAW AGRICULTURAL COMMODITY (RAC)
ADJUSTED
RESIDUE (PAC)
Bodyweight
oncocentratiPesticidenconsumptioFoodIntake
__
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No Food Group
RACconsum ption
RAW conversionfactor
Edible portion
Recipe fraction
Food Group
Exam ine food code
RAW AGRICULTURALCOMMODITY CONSUMPTION
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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
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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
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ACUTE EXPOSURE ASSESSMENTACUTE EXPOSURE ASSESSMENT
PESTICIDE:
Chlorpyrifos
POPULATION:
Infants of the Basque Country 8 to 12 months old
PERIOD: 1 day
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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
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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
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UNIT-TO-UNIT VARIABILITYUNIT-TO-UNIT VARIABILITY
Composite
sample
MEANANALYSIS
ACUTE EXPOSURE ?
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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
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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
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MEDIANMEAN
sd
95th p
Minimun
99th p
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1 5 5090
95 97.598
99
99.5
99.9
2.5
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97.5th p99th p
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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
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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
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97.5th P
No proc factors
Reference model
LOR = 0
MRL = 0
No variability
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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%