Dietary exposures tiers

Overview

Table 94 Tier overview for module Dietary exposures.

Name	EFSA 2012 Optimistic	EFSA 2012 Pessimistic - Acute	EFSA 2012 Pessimistic - Chronic	EC 2018 Tier 1	EC 2018 Tier 2
Total diet study concentration data	false		false	false	false
Sample based	true	true	true	true	true
Consumptions on the same day come from the same sample	false	true	true	false	false
Apply processing factors	true	true	true	true	true
Use distribution	false	false	false	false	false
Ignore processing factors less than 1	false	true	true	false	false
Use unit variability	false	true		true	true
Unit variability model	NoUnitVariability	BetaDistribution		BetaDistribution	BetaDistribution
Model type	OIM		OIM	OIM	OIM
Model-then-add	false		false	false	false
Covariate modelling	false	false	false	false	false
Iterate survey	false	false	false	false	false
Report consumptions and exposures per individual instead of per kg body weight	false	false	false	false	false
Default concentration model	Empirical	NonDetectSpikeLogNormal	NonDetectSpikeLogNormal	Empirical	Empirical
Include MRL fallback model	false	true	true	false	false
Censored values replacement	ReplaceByZero	ReplaceByLOR	ReplaceByLOR	ReplaceByLOR	ReplaceByLOR
Impute missing values from available values (if unchecked, missing values are imputed with 0)	false	true	true	true	true
Correlate imputed values with sample potency	false	true	true	true	false
Use occurrence frequencies for imputation	false			true	true
Parametric uncertainty	false	true	false	false	false
Risk type		Acute	Chronic
Estimates nature		Realistic		Realistic	Realistic
Unit variability parameter		VariabilityFactor		VariabilityFactor	VariabilityFactor
Restrict LOR imputation to authorised uses		false	false	false	false
Factor f (f x LOR or f x LOD or LOD + f x (LOQ - LOD)		1	1	0.5	0.5
MRL Factor (f x MRL)		1	1
Apply occurrence pattern percentages				false	true
Substance conversion method				UseMostToxic	DrawRandom
Retain all allocated substances after active substance allocation				true	true
Account for substance authorisations in substance conversions				false	true
Fix duplicate substance allocation inconsistencies				false	false
Use extrapolation rules				true	true
Threshold for extrapolation				10	10
Restrict extrapolations to equal MRLs				true	true
Restrict extrapolations to authorised uses				true	true
Impute water concentrations				true	true
Water concentration value (µg/kg)				0.1	0.05
Restrict water imputation to the five most toxic substances				true	true
Restrict water imputation to authorised uses				false	false
Scale up use frequency to 100%					true
Restrict use percentage up-scaling to authorised uses					true

EFSA 2012 Optimistic

Use the optimistic model settings according to the EFSA Guidance 2012. Concentration values are sampled using a sample-based empirical distribution. Available processing factors are applied. No unit variability model should be applied.

Table 95 Tier definition for EFSA 2012 Optimistic.

Name	Setting	From input tier	In module
Total diet study concentration data	false
Sample based	true
Consumptions on the same day come from the same sample	false
Apply processing factors	true
Use distribution	false
Ignore processing factors less than 1	false
Use unit variability	false
Unit variability model	NoUnitVariability
Model type	OIM
Model-then-add	false
Covariate modelling	false
Iterate survey	false
Report consumptions and exposures per individual instead of per kg body weight	false
Default concentration model	Empirical	EFSA 2012 Optimistic	Concentration models
Include MRL fallback model	false	EFSA 2012 Optimistic	Concentration models
Censored values replacement	ReplaceByZero	EFSA 2012 Optimistic	Concentration models
Sample based	true	EFSA 2012 Optimistic	Concentration models
Impute missing values from available values (if unchecked, missing values are imputed with 0)	false	EFSA 2012 Optimistic	Concentration models
Correlate imputed values with sample potency	false	EFSA 2012 Optimistic	Concentration models
Use occurrence frequencies for imputation	false	EFSA 2012 Optimistic	Concentration models
Parametric uncertainty	false	EFSA 2012 Optimistic	Concentration models

EFSA 2012 Pessimistic - Acute

Acute probabilistic exposure assessment using the pessimistic model settings according to the EFSA Guidance 2012. Only processing factors > 1 are applied. For unit variability, the Beta distribution is applied.

Table 96 Tier definition for EFSA 2012 Pessimistic - Acute.

Name	Setting	From input tier	In module
Risk type	Acute
Sample based	true
Consumptions on the same day come from the same sample	true
Apply processing factors	true
Use distribution	false
Ignore processing factors less than 1	true
Use unit variability	true
Unit variability model	BetaDistribution
Estimates nature	Realistic
Unit variability parameter	VariabilityFactor
Covariate modelling	false
Iterate survey	false
Report consumptions and exposures per individual instead of per kg body weight	false
Default concentration model	NonDetectSpikeLogNormal	EFSA 2012 Pessimistic - Acute	Concentration models
Include MRL fallback model	true	EFSA 2012 Pessimistic - Acute	Concentration models
Restrict LOR imputation to authorised uses	false	EFSA 2012 Pessimistic - Acute	Concentration models
Censored values replacement	ReplaceByLOR	EFSA 2012 Pessimistic - Acute	Concentration models
Factor f (f x LOR or f x LOD or LOD + f x (LOQ - LOD)	1	EFSA 2012 Pessimistic - Acute	Concentration models
MRL Factor (f x MRL)	1	EFSA 2012 Pessimistic - Acute	Concentration models
Sample based	true	EFSA 2012 Pessimistic - Acute	Concentration models
Impute missing values from available values (if unchecked, missing values are imputed with 0)	true	EFSA 2012 Pessimistic - Acute	Concentration models
Correlate imputed values with sample potency	true	EFSA 2012 Pessimistic - Acute	Concentration models
Parametric uncertainty	true	EFSA 2012 Pessimistic - Acute	Concentration models

EFSA 2012 Pessimistic - Chronic

Chronic probabilistic exposure assessment using the pessimistic model settings according to the EFSA Guidance 2012. Only processing factors > 1 are applied.

Table 97 Tier definition for EFSA 2012 Pessimistic - Chronic.

Name	Setting	From input tier	In module
Risk type	Chronic
Total diet study concentration data	false
Sample based	true
Consumptions on the same day come from the same sample	true
Apply processing factors	true
Use distribution	false
Ignore processing factors less than 1	true
Model type	OIM
Model-then-add	false
Covariate modelling	false
Iterate survey	false
Report consumptions and exposures per individual instead of per kg body weight	false
Default concentration model	NonDetectSpikeLogNormal	EFSA 2012 Pessimistic - Chronic	Concentration models
Include MRL fallback model	true	EFSA 2012 Pessimistic - Chronic	Concentration models
Restrict LOR imputation to authorised uses	false	EFSA 2012 Pessimistic - Chronic	Concentration models
Censored values replacement	ReplaceByLOR	EFSA 2012 Pessimistic - Chronic	Concentration models
Factor f (f x LOR or f x LOD or LOD + f x (LOQ - LOD)	1	EFSA 2012 Pessimistic - Chronic	Concentration models
MRL Factor (f x MRL)	1	EFSA 2012 Pessimistic - Chronic	Concentration models
Sample based	true	EFSA 2012 Pessimistic - Chronic	Concentration models
Impute missing values from available values (if unchecked, missing values are imputed with 0)	true	EFSA 2012 Pessimistic - Chronic	Concentration models
Correlate imputed values with sample potency	true	EFSA 2012 Pessimistic - Chronic	Concentration models
Parametric uncertainty	false	EFSA 2012 Pessimistic - Chronic	Concentration models

EC 2018 Tier 1

Table 98 Tier definition for EC 2018 Tier 1.

Name	Setting	From input tier	In module
Total diet study concentration data	false
Sample based	true
Consumptions on the same day come from the same sample	false
Apply processing factors	true
Use distribution	false
Ignore processing factors less than 1	false
Use unit variability	true
Unit variability model	BetaDistribution
Estimates nature	Realistic
Unit variability parameter	VariabilityFactor
Model type	OIM
Model-then-add	false
Covariate modelling	false
Iterate survey	false
Report consumptions and exposures per individual instead of per kg body weight	false
Default concentration model	Empirical	EC 2018 Tier 1	Concentration models
Include MRL fallback model	false	EC 2018 Tier 1	Concentration models
Restrict LOR imputation to authorised uses	false	EC 2018 Tier 1	Concentration models
Censored values replacement	ReplaceByLOR	EC 2018 Tier 1	Concentration models
Factor f (f x LOR or f x LOD or LOD + f x (LOQ - LOD)	0.5	EC 2018 Tier 1	Concentration models
Sample based	true	EC 2018 Tier 1	Concentration models
Impute missing values from available values (if unchecked, missing values are imputed with 0)	true	EC 2018 Tier 1	Concentration models
Correlate imputed values with sample potency	true	EC 2018 Tier 1	Concentration models
Use occurrence frequencies for imputation	true	EC 2018 Tier 1	Concentration models
Parametric uncertainty	false	EC 2018 Tier 1	Concentration models
Apply occurrence pattern percentages	false	EC 2018 Tier 1	Occurrence patterns
Substance conversion method	UseMostToxic	EC 2018 Tier 1	Concentrations
Retain all allocated substances after active substance allocation	true	EC 2018 Tier 1	Concentrations
Account for substance authorisations in substance conversions	false	EC 2018 Tier 1	Concentrations
Fix duplicate substance allocation inconsistencies	false	EC 2018 Tier 1	Concentrations
Use extrapolation rules	true	EC 2018 Tier 1	Concentrations
Threshold for extrapolation	10	EC 2018 Tier 1	Concentrations
Restrict extrapolations to equal MRLs	true	EC 2018 Tier 1	Concentrations
Restrict extrapolations to authorised uses	true	EC 2018 Tier 1	Concentrations
Impute water concentrations	true	EC 2018 Tier 1	Concentrations
Water concentration value (µg/kg)	0.1	EC 2018 Tier 1	Concentrations
Restrict water imputation to the five most toxic substances	true	EC 2018 Tier 1	Concentrations
Restrict water imputation to authorised uses	false	EC 2018 Tier 1	Concentrations

EC 2018 Tier 2

Table 99 Tier definition for EC 2018 Tier 2.

Name	Setting	From input tier	In module
Total diet study concentration data	false
Sample based	true
Consumptions on the same day come from the same sample	false
Apply processing factors	true
Use distribution	false
Ignore processing factors less than 1	false
Use unit variability	true
Unit variability model	BetaDistribution
Estimates nature	Realistic
Unit variability parameter	VariabilityFactor
Model type	OIM
Model-then-add	false
Covariate modelling	false
Iterate survey	false
Report consumptions and exposures per individual instead of per kg body weight	false
Default concentration model	Empirical	EC 2018 Tier 2	Concentration models
Include MRL fallback model	false	EC 2018 Tier 2	Concentration models
Restrict LOR imputation to authorised uses	false	EC 2018 Tier 2	Concentration models
Censored values replacement	ReplaceByLOR	EC 2018 Tier 2	Concentration models
Factor f (f x LOR or f x LOD or LOD + f x (LOQ - LOD)	0.5	EC 2018 Tier 2	Concentration models
Sample based	true	EC 2018 Tier 2	Concentration models
Impute missing values from available values (if unchecked, missing values are imputed with 0)	true	EC 2018 Tier 2	Concentration models
Correlate imputed values with sample potency	false	EC 2018 Tier 2	Concentration models
Use occurrence frequencies for imputation	true	EC 2018 Tier 2	Concentration models
Parametric uncertainty	false	EC 2018 Tier 2	Concentration models
Apply occurrence pattern percentages	true	EC 2018 Tier 2	Occurrence patterns
Scale up use frequency to 100%	true	EC 2018 Tier 2	Occurrence patterns
Restrict use percentage up-scaling to authorised uses	true	EC 2018 Tier 2	Occurrence patterns
Substance conversion method	DrawRandom	EC 2018 Tier 2	Concentrations
Retain all allocated substances after active substance allocation	true	EC 2018 Tier 2	Concentrations
Account for substance authorisations in substance conversions	true	EC 2018 Tier 2	Concentrations
Fix duplicate substance allocation inconsistencies	false	EC 2018 Tier 2	Concentrations
Use extrapolation rules	true	EC 2018 Tier 2	Concentrations
Threshold for extrapolation	10	EC 2018 Tier 2	Concentrations
Restrict extrapolations to equal MRLs	true	EC 2018 Tier 2	Concentrations
Restrict extrapolations to authorised uses	true	EC 2018 Tier 2	Concentrations
Impute water concentrations	true	EC 2018 Tier 2	Concentrations
Water concentration value (µg/kg)	0.05	EC 2018 Tier 2	Concentrations
Restrict water imputation to the five most toxic substances	true	EC 2018 Tier 2	Concentrations
Restrict water imputation to authorised uses	false	EC 2018 Tier 2	Concentrations

EFSA 2012 Pessimistic

Note

This tier is deprecated and has been replaced by separate acute/chronic tiers.

Probabilistic exposure assessment using the pessimistic model settings according to the EFSA Guidance 2012. Only processing factors > 1 are applied. For unit variability, the Beta distribution is applied.

Table 100 Tier definition for EFSA 2012 Pessimistic.

Name	Setting	From input tier	In module
Total diet study concentration data	false
Sample based	true
Consumptions on the same day come from the same sample	true
Apply processing factors	true
Use distribution	false
Ignore processing factors less than 1	true
Use unit variability	true
Unit variability model	BetaDistribution
Estimates nature	Realistic
Unit variability parameter	VariabilityFactor
Model type	OIM
Model-then-add	false
Covariate modelling	false
Iterate survey	false
Report consumptions and exposures per individual instead of per kg body weight	false
Default concentration model	NonDetectSpikeLogNormal	EFSA 2012 Pessimistic	Concentration models
Include MRL fallback model	true	EFSA 2012 Pessimistic	Concentration models
Restrict LOR imputation to authorised uses	false	EFSA 2012 Pessimistic	Concentration models
Censored values replacement	ReplaceByLOR	EFSA 2012 Pessimistic	Concentration models
Factor f (f x LOR or f x LOD or LOD + f x (LOQ - LOD)	1	EFSA 2012 Pessimistic	Concentration models
MRL Factor (f x MRL)	1	EFSA 2012 Pessimistic	Concentration models
Sample based	true	EFSA 2012 Pessimistic	Concentration models
Impute missing values from available values (if unchecked, missing values are imputed with 0)	true	EFSA 2012 Pessimistic	Concentration models
Correlate imputed values with sample potency	true	EFSA 2012 Pessimistic	Concentration models
Parametric uncertainty	true	EFSA 2012 Pessimistic	Concentration models