Consumption data |
Excluded data |
U1 |
Consumption data of animal commodities and plant commodities not in the list of the 35 selected commodities and their processed derivatives have not been considered in the assessment. |
Exposure |
Ambiguity |
U2 |
The consumption data do not always discriminate between different commodities of a same group as defined in part B of annex I to Regulation (EC) No 396/2005 (e.g. tomatoes and cherry tomatoes are considered as tomatoes). |
Exposure |
Accuracy |
U3 |
The accuracy of the reported amount of food consumed in surveys may be affected by methodological limitations or psychological factors. |
Exposure |
Sampling variability |
U4 |
The reliability of risk estimates at the 99.9th percentile of exposure in the 10 populations under consideration is affected by the sample size (number of consumers) of the respective surveys. |
Exposure |
Sampling bias |
U5 |
Selection bias of consumers in food consumption surveys affects the representativeness of consumption data of the respective populations. |
Exposure |
Use of fixed values |
U6 |
In the RPC model, one invariable recipe and conversion factor are used to convert the amount of food consumed into the respective amount of raw primary commodity. |
Exposure |
Occurrence data |
Missing data |
U7 |
The contribution of active substance/commodity combinations, for which occurrence data are missing and extrapolation from another commodity is not possible, was not accounted in the assessment. |
Exposure |
Excluded data |
U8 |
The contribution to the risk of metabolites and degradation products not included in the residue definition for monitoring has not been considered. |
Exposure |
Ambiguity |
U9 |
The occurrence data do not always discriminate between different commodities of a same group as defined in part B of annex I to Regulation (EC) No 396/2005 (e.g. tomatoes and cherry tomatoes are considered as tomatoes). |
Exposure |
Accuracy |
U10 |
The accuracy of the quantification of residue levels above the LOQ is affected by the laboratory analytical uncertainty. |
Exposure |
Sampling variability |
U11 |
The reliability of risk estimates at the 99.9th percentile of exposure in the 10 populations under consideration is affected by the sample size (number of occurrence data) for each pesticide/commodity combination. |
Exposure |
Sampling bias |
U12 |
Selection bias of lots of commodities to be controlled in official monitoring programmes affects the representativeness of occurrence data. See Section 2.2.2.4 on the extraction criteria applied to the monitoring data. |
Exposure |
Extrapolation uncertainty |
U13 |
In case of extrapolation of occurrence data between 2 commodities, it is uncertain that the residue profiles in the 2 commodities are actually identical. See Sections 2.2.3.3 and 2.2.4.1.3 regarding the extrapolation rules. |
Exposure |
Other uncertainty |
U14 |
It is uncertain whether the use of pooled occurrence data from all EU Member states is representative of the actual residue levels to which the 10 populations under consideration are actually exposed to. |
Exposure |
Assumption |
U15 |
The assumption used to assign occurrence data to active substances in case of unspecific residue definition for monitoring (see Sections 2.2.2.3 and 2.2.4.1.1) is subject to uncertainty. |
Exposure |
Assumption |
U16 |
In the handling of left‐censored data, the assumption about the authorisation status of the pesticide/commodity combinations under consideration (see Section 2.2.3.2) is subject to uncertainty. |
Exposure |
Assumption |
U17 |
In the handling of left‐censored data, the assumption about the use frequency for authorised pesticide/commodity combinations (see Section 2.2.4.1.3) is subject to uncertainty. |
Exposure |
Assumption |
U18 |
In the handling of left‐censored data, the assumption about the residue level (1/2 LOQ as imputed value) when an active substance is used, and its residues are below the LOQ, is subject to uncertainty. |
Exposure |
Assumption |
U19 |
The assumption about the occurrence of residues in drinking water (see Section 2.2.4.1.4) is subject to uncertainty. |
Exposure |
Processing factors |
Assumption |
U20 |
The assumption that pesticide residues are transferred without any loss to processed commodities when processing factors are not available is subject to uncertainty. |
Exposure |
Ambiguity |
U21 |
The assignment of processing factors, derived from a limited number of standardised studies, to food items of the EFSA food classification and description system (FoodEx) resulting from multiple processing techniques of the EFSA RPC‐model, is subject to uncertainty. See Section 2.2.3.4 for the principles of assignment of processing factors. |
Exposure |
Accuracy |
U22 |
In processing studies, the accuracy of the quantification of residue levels above the LOQ in raw and processed commodities is affected by the laboratory analytical uncertainty. |
Exposure |
Accuracy |
U23 |
Processing factors are overestimated when residue levels in the processed commodity are below the LOQ. |
Exposure |
Use of fixed values |
U24 |
The value of processing factors used in the calculations is the median value of a limited number of independent trials. |
Exposure |
Excluded data |
U25 |
Some processing factors are not considered in the assessment (e.g. peeling and washing of commodities with edible peel). |
Exposure |
NOAELs |
Adequacy of the CAG |
U26 |
It is uncertain whether the CAG contains all the OPs and NMC insecticides causing the effect. |
Toxicology |
Adequacy of the CAG |
U27 |
There is uncertainty about the contribution of pesticides other than OPs and NMCs to erythrocyte AChE inactivation through oxidative stress and further inhibition of enzyme activity. |
Toxicology |
Adequacy of the CAG |
U28 |
It is uncertain whether the CAG contains only the active substances causing the effect. |
Toxicology |
Accuracy |
U29 |
The accuracy of the NOAEL‐setting is affected by the original studies/data quality (e.g. study conducted under Good Laboratory Practice GLP or not, guidelines referred to or not, statistical analysis performed or not, overall quality of reporting). |
Toxicology |
Accuracy |
U30 |
The accuracy of the NOAEL‐setting is affected by the data collection methodology (interpretation of raw data by the assessors, transfer of information from original studies to source documents, and from source documents to working documents (excel spreadsheets). |
Toxicology |
Accuracy |
U31 |
The accuracy of the NOAEL‐setting is affected by the assessment methodology and principles (i.e. how the available information was assessed to derive NOAELs for erythrocyte AChE inhibition). |
Toxicology |
Accuracy |
U32 |
The accuracy of the NOAEL‐setting is affected by the study design of the critical study (e.g. dose selection and spacing, study duration, route of administration, analytical methods…). |
Toxicology |