Report No. US0092

 Page 1 

Title

Updated (2010) Aldicarb Acute Dietary Risk Assessment 

Including Food and Drinking Water 

Data Requirement

Not Applicable 

Author(s)

Iain D. Kelly 

Jennifer L. Lantz 

Bruce M. Young 

Gary J. Mihlan 

Russell L. Jones 

Ann M. Blacker 

Tom Gould 

Report Completed On

July 27, 2010 

Submitted By

Bayer CropScience 

Product Safety Management 

2 T. W. Alexander Dr. 

Research Triangle Park, NC 27709 

USA 

Report Number

US0092 

Total Number of Pages 39

Confidential Business Information removed on August 19, 2010
 Report No. US0092

 Page 2 

STATEMENT OF NO DATA CONFIDENTIALITY CLAIMS 

No claim of confidentiality is made for any information contained in this study on the basis of its 

falling within the scope of FIFRA § l0(d)(l)(A), (B), or (C). 

The information contained herein is the property of Bayer CropScience and although subject to 

release to nonmultinationals pursuant to FIFRA Section 10, such information is considered trade 

secret for all other purposes. 

Company: Bayer CropScience Company 

Agent: 

 Iain D. Kelly 

 Product Safety Manager 

 Bayer CropScience 

Date: 27JUL2010 

The above statement supersedes all other statements of confidentiality that may occur elsewhere in 

this report. 
 Report No. US0092

 Page 3 

GOOD LABORATORY PRACTICE COMPLIANCE STATEMENT 

This report does not meet the requirements for EPA FIFRA Good Laboratory Practice Standards, 

40 CFR Part 160, and differs in the following way: 

(1) Good Laboratory Practice Standards are not required. 

Submitter: 27JUL2010 

 Iain D. Kelly Date 

 Product Safety Manager 

 Bayer CropScience 
 Report No. US0092

 Page 4 

TABLE OF CONTENTS 

TITLE PAGE ......................................................................................................................................... 1 

STATEMENT OF NO DATA CONFIDENTIALITY CLAIMS .......................................................... 2 

GOOD LABORATORY PRACTICE COMPLIANCE STATEMENT ................................................ 3 

TABLE OF CONTENTS ....................................................................................................................... 4 

SUMMARY ........................................................................................................................................... 6 

1. INTRODUCTION.......................................................................................................................... 8

2. OVERVIEW OF CURRENT AND PREVIOUS ASSESSMENTS INPUTS ............................... 9

3. SELECTION OF THE FQPA SAFETY FACTOR ..................................................................... 11

3.1 Determination of the FQPA Safety Factor from the PND 11, CCA Study ........................ 11

3.2 Relevance and Age Dependence of the FQPA Safety Factor............................................. 13

4. RESIDUE DATA......................................................................................................................... 14

4.1 Analytical Limit of Detection............................................................................................. 15

4.2 Oranges............................................................................................................................... 16

4.3 Orange Juice ....................................................................................................................... 17

4.4 Grapefruit ........................................................................................................................... 18

4.5 Sweet Potatoes.................................................................................................................... 19

4.6 Potatoes .............................................................................................................................. 20

5. PERCENT CROP TREATED...................................................................................................... 22

6. DRINKING WATER................................................................................................................... 24

6.1 Discussion of EPA Modeling Approach ............................................................................ 26

6.2 Parameterization of the Model ........................................................................................... 26

6.3 Calibration of the Model with Monitoring Data................................................................. 27

7. DIETARY (FOOD AND DRINKING WATER) ANALYSIS MODELS .................................. 27

7.1 Within Day Dietary (Food and Drinking Water) Assessment............................................ 27

7.2 Half-life Determination ...................................................................................................... 28

7.3 Event Based Exposure Distribution.................................................................................... 28

8. RESULTS AND DISCUSSION .................................................................................................. 29

8.1 Daily Dietary Food Assessment Results ............................................................................ 29

8.2 Aggregate (Food and Drinking Water) Assessment........................................................... 30

8.3 Contribution Analysis and Impact of 1⁄2 LOD Value on Dietary Food Only Assessments 31

8.3.1 Consumption Data ............................................................................................. 31

8.3.2 Residue Assignment........................................................................................... 34

8.3.3 Dietary Assessment Results Using Refined 1⁄2 LOD Values.............................. 35

8.4 Commodity Specific (Eater Only) Assessment.................................................................. 36

9. CONCLUSION ............................................................................................................................ 36

10. REFERENCES............................................................................................................................. 37
 Report No. US0092

 Page 5 

TABLE OF CONTENTS (continued) 

Tables

Table 1 Comparison Dietary Assessment by HED, 2006 Versus BCS, 2006........................... 8

Table 2 Data Changes in Dietary Risk Assessment between 2006 and 2010 ......................... 10

Table 3 USDA PDP Data Used in Aldicarb Dietary Assessment ........................................... 14

Table 4 Orange PDP Data ....................................................................................................... 16

Table 5 Orange Juice PDP Data .............................................................................................. 17

Table 6 Grapefruit PDP Data .................................................................................................. 18

Table 7 Sweet Potatoes PDP Data........................................................................................... 19

Table 8 Potatoes Fresh PDP Data............................................................................................ 20

Table 9 Potatoes Frozen PDP Data ......................................................................................... 21

Table 10 Current Percent Crop Treated Data ............................................................................ 22

Table 11 Changes in Percent Crop Treated Value in Dietary Risk Assessments...................... 23

Table 12 Trend of TEMIK® Use on Florida Citrus.................................................................. 23

Table 13 Percentile Distribution Comparison ........................................................................... 25

Table 14 Daily Dietary Food Risk Assessment Results for Various Scenarios ........................ 30

Table 15 Comparison of Daily vs. Within Day Exposure and Risk Determination.................. 30

Table 16 CSFII Records for Extreme Grapefruit Juice Consumption in Infants ...................... 32

Table 17 CSFII Records for High Orange Juice Consumption in Children 1-2 yrs old............ 33

Table 18 Daily Dietary Assessment Results Using Refined 1⁄2 LOD Values ............................ 36

Table 19 Commodity Specific (Eater Only) Assessment for Orange Juice and Indirect Water 36

TABLE OF CONTENTS (continued) 

Figures

Figure 1 Mean and 95% confidence intervals for RBC AChE in adult rats ............................. 12

Figure 2 Mean and 95% confidence intervals for RBC AChE in PND11 rats ......................... 12

Figure 3 Distribution of Aldicarb Residues in Oranges............................................................ 16

Figure 4 Distribution of Aldicarb Residues in Orange Juice.................................................... 17

Figure 5 Distribution of Aldicarb Residues in Grapefruit ........................................................ 18

Figure 6 Distribution of Aldicarb Residues in Sweet Potatoes................................................. 19

Figure 7 Distribution of Aldicarb Residues in Potatoes Fresh ................................................. 20

Figure 8 Distribution of Aldicarb Residues in Potatoes Frozen ............................................... 21

Figure 9 Percent Crop Treated For Use of Aldicarb in Florida Citrus ..................................... 24

Figure 10 Comparison of Ground Water Residue Data from Modeling and Monitoring........... 26

Figure 11 Hypothetical Exposure Profile ................................................................................... 29

Figure 12 Contribution Analysis at the 99.9th percentile for Infants and Children 1-2 yrs......... 31

Figure 13 Grapefruit Juice Consumption by Infants (< 1 yr old) ............................................... 32

Figure 14 Orange Juice Consumption by Children 1-2 yrs. old ................................................. 33

Figure 15 Orange Juice Residue Distribution............................................................................. 35
 Report No. US0092

 Page 6 

SUMMARY

Updated (2010) Aldicarb Acute Dietary Risk Assessment Including Food and Drinking 

Water 

Summary

Aldicarb is the sole active ingredient in Temik® brand Aldicarb Pesticide, sold and used almost 

exclusively as a 15% granule. It was first registered in 1970. The active ingredient aldicarb has been 

extensively tested to define both toxicological properties and pharmacokinetic behavior. Aldicarb 

residue levels have been monitored in food and drinking water for approximately 40 years, resulting 

in aldicarb having one of the most extensive monitoring data set of all registered insecticides. The 

combination of robust toxicology and residue data sets enables conduct of highly refined risk 

assessments. 

As part of the 2007 Registration Eligibility Decision (RED), EPA relied on a Health Effects Division 

(HED) 2006 risk assessment demonstrating that aldicarb uses met the required standard of reasonable 

certainty of no harm if subsequently implemented label changes were applied. Bayer CropScience 

(BCS) also conducted a risk assessment for consideration which pointed out that the HED assessment 

was still conservative and did not incorporate all the knowledge and data available on aldicarb. 

Since the 2006 assessments, new data has become available that is pertinent to the risk assessment for 

aldicarb, including a Comparative Cholinesterase Assay (CCA) for postnatal day 11 pups which 

modifies the FQPA Safety Factor. Both HED and BCS have conducted a risk assessment based on 

current data. Using all available data and fully accounting for the rapid reversibility of aldicarb 

effects, BCS has demonstrated based on an aggregate (food plus water) assessment for currently 

registered uses consume 60% and 50% of the acute Population Adjusted Dose (%aPAD) 99.9th

percentile for infants and children (1-2 years), respectively, thus meeting the standard of reasonable 

certainty of no harm. While the HED assessment indicates potential concerns, this document 

discusses credible scientific refinements that can be incorporated into the HED assessment to address 

these concerns. The following refinements are discussed and justified in the report: 

1. Using an FQPA safety factor for infants of 3.9 based on the most robust analysis of statistical 

data. 

2. Using an FQPA safety factor of 2 for children (> 1 years) based on a previous CCA study to 

more accurately reflect the comparative ontogeny of rats versus humans. 

3. Using a percent crop treated of 20% in oranges rather than the maximum due to a change in 

cultivation practices. 

4. Using appropriate distribution of water detects based on extensive monitoring rather than 

relying on highly inflated modeled values that are not predictive of field studies. 

5. Constructing exposure profiles by using all event based exposures within each day rather than 

using the worst case event from each day. 

6. Adjusting for treated non-detects in PDP monitoring data by considering only analytes that 

would be reasonably expected to be present. 
 Report No. US0092

 Page 7 

Furthermore, although not part of the formal safety assessment, BCS have conducted a Commodity 

Specific Analysis for orange juice and water, the consumption drivers for infants and children, using 

worst case assumptions and demonstrated acceptable Margins of Exposure. 

Bayer CropScience is confident that by applying scientifically credible dietary exposure refinements, 

it can conclude that there is reasonable certainty of no harm to any age or population subgroup 

exposed to aldicarb derived residues in food and drinking water based on currently registered uses. 
 Report No. US0092

 Page 8 

1. INTRODUCTION

In September 2007, EPA issued the Registration Eligibility Decision (RED) for aldicarb [1] which 

incorporated the Health Effects Division’s dietary risk assessment completed in 2006 [2]. While 

HED’s assessment met the required standard of reasonable certainty of no harm, Bayer CropScience 

(BCS) submitted a risk assessment [3] for consideration which pointed out that the HED assessment 

was still conservative and did not incorporate all the knowledge and data available on aldicarb. A 

comparison of HED’s and BCS’s risk assessment at that time is shown in Table 1. 

Table 1 Comparison Dietary Assessment by HED, 2006 Versus BCS, 2006

BCS, 2006 HED, 2006 

Population 

Subgroup Scenarioa 

Dose 

Metricb

Exposure 

(mg/kg) %aPADc 

Exposure 

(mg/kg) %aPADe 

Food Alone Daily 2.37E-04 36 2.68E-04 41

Food Alone Within Day 6.03E-05 10 2.68E-04 41

Food + Water Daily 4.29E-04 66 1.09E-03 168

All Infants 

(< 1 yr) 

Food + Water Within Day NDd NDd 5.72E-04 88

Food Alone Daily 4.78E-04 74 5.09E-04 78

Food Alone Within Day 1.08E-04 16 4.68E-04 72

Food + Water Daily 4.94E-04 76 6.36E-04 98

Children 

1-2 yrs 

Food + Water Within Day NDd NDd 5.20E-04 80

a

 Food Alone based on current registration for both HED and BCS assessments 

Food + Water based on groundwater monitoring data from South Carolina (BCS, 2006) 

Food + Water based on Georgia Peanut/Cotton model data with 500 ft setback (HED, 2006) b Daily used daily consumption x residue value. 

Within Day used 1.7 hr half-life using all minute exposure data (BCS, 2006) 

Within Day used 2 hr half-life using maximum daily value (HED, 2006) c aPAD = 0.00065 mg/kg for both HED and BCS assessments, although BCS [2] proposed a value of 

0.013 mg/kg. d Not determined. e HED, 2006 used aPAD = 0.00065 mg/kg. 

The most notable refinements that were not incorporated into the HED assessment were: 

1) Incorporation of aldicarb monitoring data, particularly BCS’s extensive ground water monitoring 

study conducted in 2005 (see Section 6). 

2) Constructing exposure profiles by using all event based exposures within each day rather than 

using the worst case event from each day (see Section 7). 

As part of the RED, BCS was required to conduct a Comparative Cholinesterase Assay (CCA) for 

PND 11 (postnatal day) pups for consideration in determining the FQPA SF. In February 2010, BCS 

completed and submitted the CCA dose-response study for PND 11 pups versus adults [4] and 

calculated an FQPA SF of 3.9 based on inhibition of RBC cholinesterase for both sexes combined [5]. 

Furthermore, since the 2006 assessments, there is new data available (percent crop treated values and 

PDP residue data) that is pertinent to the risk assessment for aldicarb. Additionally BCS have 

enhanced the CARES dietary aggregate model to fully account for the rate of reversibility of 

cholinesterase inhibition in conducting a population based risk assessment. 
 Report No. US0092

 Page 9 

Both HED and BCS have conducted new aggregate dietary assessments using the data that has 

become available since the 2006 assessments. This document lays out the BCS 2010 risk assessment 

with a justification of the inputs selected. Areas of differences between the previous assessments and 

the HED 2010 [6] and this BCS 2010 assessments are discussed. 

By credibly incorporating all available data, BCS have calculated that current aldicarb use utilizes 

60% and 50% of the aPAD for infants and children 1-2 years, respectively, the most sensitive subpopulations. 

2. OVERVIEW OF CURRENT AND PREVIOUS ASSESSMENTS INPUTS

HED and BCS have reassessed the dietary risk for aldicarb based on the most current data. Both of 

these assessments incorporated an FQPA safety factor based on the new CCA study, updated food 

monitoring data (USDA Pesticide Data Program) and recent percent crop treated values. However, 

the approach to accounting for drinking water residues varies significantly between EPA and BCS. 

Due to a re-interpretation by the Environmental Fate and Effects Division (EFED) of data that was 

available in 2006, a significant change has been made to the 2010 EPA assessment which has further 

exaggerated the already extremely conservative approach to incorporating drinking water into the 

aggregate assessment. This results in an extremely biased EPA assessment in which refined food 

residue values are aggregated with unrealistic water values from modeled estimates. BCS uses 

conservative distributions of drinking water residue values based on extensive monitoring data. 

EPA informed BCS in 2009 of the pending change in its water assessment. BCS voiced objections at 

that time and informed EPA that we could not reproduce its assessment and asked for pertinent 

information. Despite several requests, this has not been provided. BCS reminds the Agency that 

FQPA states that the best available data should be used for aggregate assessments. No other 

carbamate has the extensive amount of relevant monitoring data that is available for aldicarb. 

Additionally, aldicarb has a Health Advisory Level (HAL) for water which is protective of vulnerable 

subpopulations. Under FQPA’s mandate, the monitoring data and existence of the HAL should be 

considered in the risk assessment. 

Table 2 summarizes the differences between HED’s 2006 assessment, HED’s 2010 assessment, and 

BCS’s 2010 assessment. Each input parameter is discussed further in the sections following. 
 Report No. US0092

 Page 10 

Table 2 Data Changes in Dietary Risk Assessment between 2006 and 2010

Section 

for 

further 

comments 

Input EPA 2006 EPA 2010 BCS 2010 

3 FQPA SF 2.0 (brain for 

PND17 male 

pups) 

4.8 (RBC for PND11 

male pups) 

3.9 for infants 

(combined sexes) 

2.0 for Children 1-2 

and above. 

4 Residue data PDP data: 

1997 potato 

single serve. 

2000 citrus 

market basket. 

PDP data: 

>2000 PDP 

composite for potato 

and citrus 

PDP data: 

>2000 PDP 

composite for potato 

and citrus 

Percent crop treated 

(except oranges) 

Doanes data 

2001-2005 

Agrotrak data 

2005-2009. Rounded 

up beyond maximum 

values. 

Agrotrak data 

2005-2009 using 

maximum values. 

Potato fresh vs 

processed percent crop 

treated 

Based on 

percent of 

market that 

goes to fresh 

vs. processed 

Not used. 

Growers could not 

reliably differentiate 

fresh vs. processed at 

field level. 

Not used. 

Growers could not 

reliably differentiate 

fresh vs. processed at 

field level. 

5 

Orange percent crop 

treated 

12% 35%. Rounded up 

beyond 2007 peak 

value 

20%. Based on 

current disease 

control regimens 

None Processing GLP study 

values 

GLP study values GLP study values 

6 Drinking Water Modeled data 

–typical use 

rates 

Modeled data –

maximum use rates 

Monitoring data for 

surface and 

groundwater 

7 Model DEEM-FCID 

SHEDS 

DEEM-FCID 

SHEDS 

CARES 

DMM, WMM 

 Within day, event 

based exposure 

distribution 

Based on 

maximum 

event in a day 

(daily 

exposure 

distribution) 

Based on maximum 

event in a day (daily 

exposure distribution) 

Based on all events in 

the day (event 

exposure distribution)
 Report No. US0092

 Page 11 

3. SELECTION OF THE FQPA SAFETY FACTOR

3.1 Determination of the FQPA Safety Factor from the PND 11, CCA Study

In their assessment, EPA used an FQPA SF of 4.8 based on the ratio of the benchmark dose 

(BMD10) values for RBC from males only. BCS estimated an FQPA SF of 3.9 based on 

combined data from male and female pups, which was statistically more robust. BCS offers the 

following, further comments on the difference. In its documents, EPA’s decision to conduct 

separate BMD analyses for males and females appears to be based on two main considerations: 

1. The p-value for likelihood ratio test for male and female adult RBC which was significant for 

the BMDS exponential model (5) (p-value = 0.0180) with a non-constant variance model. 

2. The BMD10 values for RBC cholinesterase in male and female pups of 0.00477 and 0.00731 

mg/kg, respectively. 

These considerations taken in isolation ignore all of the other statistical analyses performed by 

Sielken [7] as well as EPA [8] which support the lack of any difference in response between the 

sexes. Further, examination of the dose-response curves from the most recent CCA study as well 

as the wealth of cholinesterase data available for aldicarb supports the lack of any biological or 

toxicological difference in the response between males and females at the expected exposure 

levels. 

In EPA’s Data Evaluation Record (DER) for the most recent CCA study, no significant 

TRT*SEX interactions were noted for PND11 RBC and brain cholinesterase results and adult 

RBC cholinesterase results and thus, for these parameters, EPA performed pairwise comparisons 

of treated versus control for both sexes combined. Similarly, Sielken’s analysis using a modelindependent two-sided t-test showed no significant differences between the sexes at any of the 

doses tested for pup RBC and brain or adult RBC. Only adult brain data showed a significant 

TRT*SEX interaction in EPA’s analysis, a finding consistent with Sielken’s evaluation which 

showed a statistical difference in adult brain at the highest dose tested of 0.3 mg/kg using a 

model-independent two-sided t-test analysis. Based upon the number of t-tests performed (26) 

and a 0.05 level of significance, the expected number of times the hypothesis that males and 

females are the same would be rejected (when in fact they are the same) is 26×0.05=1.3. Thus 

the finding of a single difference was probably found by chance due to conducting multiple ttests. Thus, both EPA’s and Sielken’s analyses demonstrate that the response in RBC and brain 

is similar for males and females within each age group. 

For adult RBC acetylcholinesterase activity, comparison of BMDS models fit individually to 

male and female data versus models fit to the combined sexes, the likelihood ratio test was 

significant with a non-constant variance model (Sielken, 2010 - Table 8) but was not significant 

with a constant variance model (Sielken, 2010 – Table 7). However Model 5 fit to the combined

sexes was found to adequately describe the data as the likelihood ratio test was not significant 

with both the constant and non-constant variance models (Sielken, 2010 – Tables 9 and 10). For 

adult brain acetylcholinesterase activity, comparison of BMDS models fit individually to male 

and female data versus models fit to the combined sexes, the likelihood ratio test was significant 

with a constant variance model but was not significant with a non-constant variance model. For 

PND11 pup RBC and brain acetylcholinesterase activity, comparison of BMDS models fit 

individually to male and female data versus models fit to the combined sexes, the likelihood ratio 

test was not significant regardless of the variance model used. The lack of consistency between 
 Report No. US0092

 Page 12 

the adult models suggests that the statistical differences are likely to be an artifact of the model 

parameters rather than a true difference in the biological response. Thus, the overall conclusion 

from the results of (Sielken, 2010 -Tables 5 to 8) is that there are no consistent differences 

between males and females. The lack of a biological difference in response between the sexes is 

supported by a comparison of the dose response data for RBC and the overlap of the 95% 

confidence intervals (Figure 1 and Figure 2). 

Figure 1 Mean and 95% confidence intervals for RBC AChE in adult rats 

0

500

1,000

1,500

2,000

2,500

3,000

0 0.05 0.1 0.15 0.2 0.25 0.3

AChE

Dose (mg/kg)

RBC ‐ Adult ‐ Male & Female

Females

Males

Figure 2 Mean and 95% confidence intervals for RBC AChE in PND11 rats 

0

1,000

2,000

3,000

4,000

5,000

6,000

0 0.02 0.04 0.06 0.08

AChE

Dose (mg/kg)

RBC ‐ PND11 ‐ Male & Female

Females

Males

Examining the dose-response, particularly in the linear part of the response range, the adult RBC 

data appear to be more disparate than the PND11 RBC data. However, the BMD10 values for 

each sex within these age groups would imply that pups have a more disparate response 

compared to adults. The difference in BMD10 values for PND11 pups is further surprising when 

considering the similarity in the percent inhibition for RBC observed at the two lowest dose 
 Report No. US0092

 Page 13 

levels tested (10.5 and 9% in males and females, respectively, at 0.005 mg/kg and 28.4 and 34% 

in males and females, respectively, at 0.01 mg/kg). 

 RBC BMD10 (mg/kg) Source 

Adult female 0.0242 CEB 

Adult male 0.0228 CEB 

Adult combined sexes 0.0223 Sielken 

PND11 female 0.00731 CEB 

PND11 male 0.00477 CEB 

PND11 combined sexes 0.00573 Sielken 

EPA states, “In general the BMDs tended to be similar between sexes within a compartment and 

age group ... with the exception PND11 pup RBC ChEI, which showed males to be more sensitive 

than females.” However, none of the tests, including those ran by EPA, show any statistically 

significant difference in RBC acetylcholinesterase activity between male and female pups to 

support this conclusion and a plot of the RBC data for pups (Figure 2) supports the lack of a 

substantial difference between males and females. 

In addition to the CCA studies, prior analyses of adult rats and human adults support a conclusion 

that there is no sex difference in the cholinesterase response to aldicarb. 

EPA’s analysis of the human volunteer aldicarb oral dosing study in the n-methyl carbamate 

cumulative risk assessment concluded that the BMD does not differ between sexes, and the 

recovery half life is homogeneous across doses and sexes (U.S. EPA. Revised N-Methyl 

Carbamate Cumulative Risk Assessment. U.S. Environmental Protection Agency. Office of 

Pesticide Programs. September 24, 2007). 

EPA’s analysis of the adult rat aldicarb oral gavage study from the n-methyl carbamate 

cumulative risk assessment concluded that the BMD does not differ between sexes, and the 

recovery half-life is homogeneous across dose groups and sexes. EPA concluded that it does not 

appear likely that the female-male differences found are solely due to interactions due to 

differences in different studies. In this BMD, half-life and confidence interval, there was no 

evidence that BMD differed between the sexes (U.S. EPA, 2007). 

Therefore, a preponderance of evidence evaluated by BCS and EPA supports the conclusion of a 

lack of any sex difference in the dose response for aldicarb. Combining the sexes is appropriate 

for calculation of the BMD values and forms more robust and more powerful dose-response data 

sets for modeling purposes. 

Based on the recent CCA study, the appropriate FQPA SF for infants is 3.9 using the ratio of the 

BMD10 for the combined sexes RBC data. 

3.2 Relevance and Age Dependence of the FQPA Safety Factor

For carbamates, the calculation of the factor for protection of infants and children, i.e. the FQPA 

SF, is based on a BMD analysis of cholinesterase results using a benchmark response of 10%. 

This level provides a conservative endpoint and is within the range of variability for baseline 

RBC cholinesterase which in humans has been reported to show fluctuations as high as 13 to 25% 

in the same unexposed individual [9]. This conservative endpoint of 10% for RBC is considered 
 Report No. US0092

 Page 14 

to be a biological marker for exposure not an adverse effect, thus providing an added level of 

safety inherently incorporated into the risk assessment for carbamates. RBC inhibition at 10% is 

well below levels at which any clinical signs are seen. 

The use of a conservative endpoint is further compounded by the requirement for direct dosing of 

neonates in the CCA study. However, bolus dosing does not reflect the normal consumption 

process, particularly for a newborn and underestimates the impact of rapid reversibility. 

Furthermore, the CCA study is conducted at dosing levels higher than actual exposure levels. 

This is likely to have a more pronounced effect on newborns as their lower levels of metabolism 

enzymes may begin to saturate while adult levels do not. At actual dietary exposure levels, it is 

probable that neither infant nor adult metabolizing enzymes experience saturation and differences 

in relative sensitivity would be lower. The limitations of the CCA study are discussed in detail in 

the BCS 2006 assessment. There is a large database of developmental studies, including the 

developmental neurotoxicity (DNT) study with aldicarb, which provides a reliable endpoint, 

under realistic exposure conditions for newborns. 

As part of the RED, BCS was required to conduct a CCA study for PND 11 (postnatal day) pups 

for consideration in determining the FQPA SF. Prior to this study, a PND 17 study conducted by 

EPA was available from which an FQPA SF of 2 was assessed based on inhibition of brain 

cholinesterase. In general development terms, a PND 11 rat shows similar developmental 

(ontogenic) characteristics to a newborn human (0-1 year) whereas a PND 17 rat is ontogenically 

similar to a human toddler (>1 year) [10],[11],[12]. In February 2010, BCS completed and 

submitted the CCA dose-response study for PND 11 pups versus adults and calculated an FQPA 

SF for infants of 3.9 based on inhibition of RBC cholinesterase for both sexes combined. 

Based on the available studies and the ontogenic relationships between rat and human, an FQPA 

SF for infants (0-1 year) of 3.9 is appropriate and protective while an FQPA SF for toddlers (>1 

year) of 2.0 is appropriate and protective. 

4. RESIDUE DATA

The HED, 2006 and BCS, 2006 assessments used 1997 data from USDA PDP when a special single 

serving potato study was conducted. For citrus commodities, data from the 2000 Carbamate Market 

Basket Survey (CMBS) [13] had been used (also single serving data). These data are over 10 years 

old and use patterns and market share for aldicarb in potatoes and citrus have since changed. It is 

appropriate, therefore, to use newer composite data. Since 2000 potatoes and many citrus 

commodities have been included in the annual PDP monitoring survey. Table 3 lists commodities 

and years. Both the HED, 2010 and the BCS, 2010 assessments, use the more recent residue data 

from the USDA Pesticide Data Program [14] as shown in Table 3. 

Table 3 USDA PDP Data Used in Aldicarb Dietary Assessment

Commodity Years of PDP Data Total No. of Samples Total No. of detects 

Potatoes 2000-2002, 2008 2216 57 

Frozen Potatoes 2006-2007 1544 93 

Sweet Potatoes 2003-2004, 2008 1657 17 

Oranges 2000-2001, 2004-2005 2972 9 

Orange Juice 2004-2006 1487 46 

Grapefruit 2005-2006 430 4 
 Report No. US0092

 Page 15 

4.1 Analytical Limit of Detection

Aldicarb residues of concern for dietary analysis consist of the parent, metabolite aldicarb 

sulfoxide and metabolite aldicarb sulfone. In this assessment, metabolite residue values measured 

in oranges, orange juice, grapefruits, potatoes, and sweet potatoes were converted to parent 

aldicarb equivalents and the total residue is reported in parent equivalents. For non-detectable 

parent or metabolites the average 1⁄2LOD (Limit of Detection) value for a given year was used, 

then converted to aldicarb equivalents before summing to give a total residue. The conversion to 

aldicarb equivalent residues is based on the following equation: 

Total residue (as aldicarb) = (aldicarb sulfone x 0.86) + (aldicarb) + (aldicarb sulfoxide x 0.92) 

It has been standard practice to combine average 1⁄2 LOD values for each of the three analytes to 

account for “treated non-detects” in aldicarb assessments. For samples where one (usually 

sulfoxide) or two metabolites (sulfoxide and sulfone) are detected 1⁄2 LOD for each of the 

metabolites not detected in the sample are added to the sample value. Although the parent 

aldicarb is rarely seen in any monitoring samples, this practice was considered to conservatively 

account for potential residues that might exist below the limit of detection. For certain 

commodities, the PDP data shows that the Limit of Detection (LOD) has decreased in more 

recent years for aldicarb and metabolites (0.02 ppm to 0.001 ppm) as analytical methodologies 

have improved. Likewise, there was a correlated increase in the number of detected residues due 

to the lower limit of detections. As the sensitivity of the assessment to citrus inputs increases 

because of the smaller risk cup, the appropriate handling of 1⁄2 LODs for non-detects becomes 

particularly important. If inappropriately applied, the standard procedure anomalously results in 

samples with non-detects having higher residues than samples with detects. For example, this can 

occur, if a sample from a lab with a low limit of detection has a detect for sulfoxide to which is 

added an average (from multiple labs over an extended period of time) of 1⁄2 LOD for both 

aldicarb and aldicarb sulfone that is higher than the lab’s detection limit. It is, however, not 

practical to correct for each lab individually. However, in some cases it must be recognized that 

this anomaly can significantly distort the risk assessment. Examination of the distribution of 

aldicarb equivalent values shows the drastic impact this has on commodities, such as, oranges 

(Figure 3), orange juice (Figure 4), sweet potatoes (Figure 6) and fresh potatoes (Figure 7). 

Several scenarios for dietary risk assessment were conducted to show the effects of using the 1⁄2 

LODs versus true zeroes for “treated non-detects in analytes” according to percent crop treated 

values per EPA policy [15] (see Section 8.3). 
 Report No. US0092

 Page 16 

4.2 Oranges

Data from the 2000-2001, 2004-2005 USDA PDP program were used to represent aldicarb 

residues on oranges, limes, and lemons. The dataset consists of 2972 samples with 9 detects. 

Table 4 summarizes all the values for oranges. The 1⁄2 LOD for total aldicarb equivalents was 

0.01492 mg/kg. Figure 1 illustrates the distribution of all the total residues as aldicarb 

equivalents for oranges used in the dietary assessment. 

Table 4 Orange PDP Data

 Average LOD Aldicarb 

Aldicarb 

Sulfoxide 

Aldicarb 

Sulfone 

Year Detects 

Number 

Samples 

Detect 

Rate Aldicarb 

Aldicarb

Sulfoxide 

Aldicarb

Sulfone 

1⁄2LODa

Comb. Min Max N Min Max N Min Max N 

2005 2 741 0.3 0.0091 0.00854 0.00971 0.0127 . . 0 0.008 0.025 2 . . 0 

2004 0 742 0 0.01058 0.01493 0.01556 0.0189 . . 0 . . 0 . . 0 

2001 4 745 0.5 0.012 0.00989 0.00817 0.0141 . . 0 0.005 0.017 4 . . 0 

2000 3 744 0.4 0.012 0.00994 0.0082 0.0141 . . 0 0.005 0.005 3 . . 0 a These values are expressed as aldicarb equivalents. 

Figure 3 Distribution of Aldicarb Residues in Oranges

586

2377

0

500

1000

1500

2000

2500

0 0.005 0.01 0.015 0.02 0.025 0.03 0.035

Aldicarb Equivalence (mg/kg)

Frequency (count)

Zeros

NonDetects 

= Average

1/2 LOD

Orange Residues

Non-Detects = 2963

Detects = 9

% Crop Treated = 20%
 Report No. US0092

 Page 17 

4.3 Orange Juice

Data from the 2004 to 2006 USDA PDP program were used to represent aldicarb residues on 

orange juice, grapefruit juice, lemon juice, and lime juice. The dataset consists of 1487 samples 

with 46 detects. Table 5 summarizes all the values for orange juice. The 1⁄2 LOD for total 

aldicarb equivalents was 0.01122 mg/kg. Figure 2 illustrates the distribution of all the total 

residues as aldicarb equivalents for oranges used in the dietary assessment. 

Table 5 Orange Juice PDP Data

 Average LOD Aldicarb 

Aldicarb Sulfoxide Aldicarb 

Sulfone 

Year Detects 

Number 

Samples 

Detect 

Rate Aldicarb 

Aldicarb

Sulfoxide 

Aldicarb

Sulfone 

1⁄2LODa

Comb. Min Max N Min Max N Min Max N 

2006 37 557 6.6 0.00496 0.00429 0.00545 0.0068 . . 0 0.002 0.005 37 . . 0 

2005 9 744 1.2 0.00913 0.00855 0.00971 0.01267 . . 0 0.008 0.008 9 . . 0 

2004 0 186 0 0.01058 0.01494 0.01319 0.01783 . . 0 . . 0 . . 0 a These values are expressed as aldicarb equivalents. 

Figure 4 Distribution of Aldicarb Residues in Orange Juice

9

252

22 33

1189

0

200

400

600

800

1000

1200

1400

0 0.002 0.004 0.006 0.008 0.01 0.012 0.014 0.016 0.018

Aldicarb Equivalence (mg/kg)

Frequency (count)

Orange Juice Residues

Non-Detects = 1441

Detects = 46

% Crop Treated = 20%

Non-Detects

= Average

1/2 LOD

Zeros
 Report No. US0092

 Page 18 

4.4 Grapefruit

Data from the 2005 to 2006 USDA PDP program were used to represent aldicarb residues on 

grapefruit. The original data for aldicarb, aldicarb sulfone, and aldicarb sulfoxide residues on 

grapefruit consisted of 1462 samples. However, in some cases there were no analyses for all 

three analytes. Excluding blanks, the dataset consisted of 430 samples with 4 detects. Table 6 

summarizes all the values for grapefruit. The 1⁄2 LOD for total aldicarb equivalents was 0.0106 

mg/kg. Figure 3 illustrates the distribution of all the total residues as aldicarb equivalents for 

grapefruit used in the dietary assessment. 

Table 6 Grapefruit PDP Data

 Average LOD Aldicarb 

Aldicarb 

Sulfoxide 

Aldicarb 

Sulfone 

Year Detects 

Number 

Samples 

Detect 

Rate Aldicarb 

Aldicarb

Sulfoxide 

Aldicarb

Sulfone 

1⁄2LODa

Comb. Min Max N Min Max N Min Max N 

2006 4 216 1.9 0.00707 0.005 0.009 0.01062 . . 0 0.008 0.063 4 . . 0 

2005 0 214 0 0.007 0.005 0.009 0.01058 . . 0 . . 0 . . 0 a These values are expressed as aldicarb equivalents. 

Figure 5 Distribution of Aldicarb Residues in Grapefruit

206

220

2 1 1

0

50

100

150

200

250

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07

Aldicarb Equivalence (mg/kg)

Frequency (count)

Grapefruit Residues

Non-Detects = 426

Detects = 4

% Crop Treated = 52% Zeros

Non-Detects

= Average

1/2 LOD
 Report No. US0092

 Page 19 

4.5 Sweet Potatoes

Data from the 2003 to 2004 and 2008 USDA PDP program were used to represent aldicarb 

residues on sweet potatoes. The dataset consists of 1657 samples with 17 detects. Table 7 

summarizes all the values for orange juice. The 1⁄2 LOD for total aldicarb equivalents was 0.0103 

mg/kg. Figure 3 illustrates the distribution of all the total residues as aldicarb equivalents for 

oranges used in the dietary assessment. 

Table 7 Sweet Potatoes PDP Data

 Average LOD Aldicarb 

Aldicarb 

Sulfoxide 

Aldicarb 

Sulfone 

Year Detects 

Number 

Samples 

Detect 

Rate Aldicarb 

Aldicarb

Sulfoxide 

Aldicarb

Sulfone 

1⁄2LODa

Comb. Min Max N Min Max N Min Max N 

2008 1 184 0.5 0.00912 0.00853 0.00971 0.01266 . . 0 0.041 0.041 1 0.027 0.027 1 

2004 8 739 1.1 0.00912 0.00259 0.00405 0.00749 . . 0 0.0027 0.077 8 0.003 0.06 7 

2003 8 734 1.1 0.0103 0.00897 0.00751 0.01251 . . 0 0.0027 0.083 8 0.003 0.023 4 a These values are expressed as aldicarb equivalents. 

Figure 6 Distribution of Aldicarb Residues in Sweet Potatoes

66

1574

0

400

800

1200

1600

2000

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

Aldicarb Equivalence (mg/kg)

Frequency (count)

Zeros

Non-Detects

= Average

1/2 LOD

Sweet Potatoes Residues

Non-Detects = 1640

Detects = 17

% Crop Treated = 5%
 Report No. US0092

 Page 20 

4.6 Potatoes

Data from the 2000 to 2002 and 2008 USDA PDP program were used to represent aldicarb 

residues on fresh potatoes. The dataset consists of 2216 samples with 57 detects. Table 8 

summarizes all the values for fresh potato data. The 1⁄2 LOD for total aldicarb equivalents was 

0.0313 mg/kg. Figure 5 illustrates the distribution of all the total residues as aldicarb equivalents 

for fresh potatoes used in the dietary assessment. 

Table 8 Potatoes Fresh PDP Data

 Average LOD Aldicarb 

Aldicarb Sulfoxide Aldicarb 

Sulfone 

Year Detects 

Number 

Samples 

Detect 

Rate Aldicarb 

Aldicarb

Sulfoxide 

Aldicarb

Sulfone 

1⁄2LODa

Comb. Min Max N Min Max N Min Max N 

2008 30 744 4 0.00357 0.00299 0.00415 0.00494 . . 0 0.002 0.34 30 0.002 0.062 14 

2002 12 370 3.2 0.01766 0.03444 0.03268 0.03873 . . 0 0.045 0.186 12 0.035 0.062 2 

2001 12 733 1.6 0.01771 0.03449 0.03502 0.03978 . . 0 0.045 0.43 12 0.035 0.11 9 

2000 3 369 0.8 0.0177 0.05274 0.05949 0.05869 . . 0 0.045 0.32 3 0.035 0.125 2 a

 These values are expressed as aldicarb equivalents. 

Figure 7 Distribution of Aldicarb Residues in Potatoes Fresh

0

500

1000

1500

2000

2500

0 0.1 0.2 0.3 0.4 0.5 0.6

Aldicarb Equivalence (mg/kg)

Frequency (count)

Potato Fresh Residues

Non-Detects = 2159

Detects = 57

% Crop Treated = 11%

Non-Detects

= Average

1/2 LOD

Zeros

187

1972
 Report No. US0092

 Page 21 

Data from the 2006 to 2007 USDA PDP program were used to represent aldicarb residues on 

frozen potatoes. The dataset consists of 1544 samples with 93 detects. Table 9 summarizes all the 

values for frozen potatoes. The 1⁄2 LOD for total aldicarb equivalents was 0.004 mg/kg. Figure 6 

illustrates the distribution of all the total residues as aldicarb equivalents for frozen potatoes used 

in the dietary assessment. 

Table 9 Potatoes Frozen PDP Data

 Average LOD Aldicarb 

Aldicarb Sulfoxide Aldicarb 

Sulfone 

Year Detects 

Number 

Samples 

Detect 

Rate Aldicarb 

Aldicarb

Sulfoxide 

Aldicarb

Sulfone 

1⁄2LODa

Comb. Min Max N Min Max N Min Max N 

2007 32 800 4 0.00282 0.00222 0.00343 0.00391 . . 0 0.002 0.021 31 0.002 0.004 14 

2006 61 744 8.2 0.00277 0.00284 0.00332 0.00412 . . 0 0.002 0.039 60 0.002 0.02 23 a These values are expressed as aldicarb equivalents. 

Figure 8 Distribution of Aldicarb Residues in Potatoes Frozen

0

200

400

600

800

1000

1200

1400

1600

0 0.01 0.02 0.03 0.04 0.05 0.06

Aldicarb Equivalence (mg/kg)

Frequency (count)

Potato Frozen Residues

Non-Detects = 1451

Detects = 93

Zeros % Crop Treated = 11%

Non-Detects

= Average

1/2 LOD

1374

77
 Report No. US0092

 Page 22 

5. PERCENT CROP TREATED

In the 2007 assessment, EPA and BCS used values from Dfr Kynetec Agrotrak® (previously known 

as Doane’s Market Research) from 2000-2004 or 2005. The newer assessment uses data from 2005-

2009 Agrotrak and NASS data (Table 10). EPA policy is to take the maximum value from the last 5 

years of data that is available [16]. This results in 11% for potatoes, 31% for oranges and 52% for 

grapefruit. The EPA analysis rounds these values up to 15%, 35% and 55% respectively. BCS used 

the actual values. Changes in percent crop treated used in dietary risk assessments are summarized in 

Table 11. 

Table 10 Current Percent Crop Treated Data

Source Commodity Percent Crop Treated 

Potatoes 2005 2006 2007 2008 2009 

Insecticide 7.3 8.7 5 7.5 5.4 

Nematicide 1.6 2.4 3.5 0.8 1.1 

Total 9 11.1 8.5 8.3 6.5 

Oranges 2005 2006 2007 2008 2009 

Insecticide 1 8.8 24 20.6 14.3 

Nematicide 1.9 2.8 6.8 9.6 9.8 

Total 2.9 11.6 30.8 30.2 24.1 

Grapefruit 2005 2006 2007 2008 2009 

Insecticide 27.8 36.8 46.2 35.1 38.5 

Nematicide 5.3 4.1 6 6 11.3 

Agrotrak 

Total 33.1 40.9 52.2 41.1 49.8 

Fall Potatoes 1999 2001 2003 2005 

Total 5 9 7 9 

Oranges excluding Temples 1995 1995 1999 2001 2003 

Total 4 8 8 10 7 

Grapefruit All 1997 1999 2001 2003 

NASS 

Total 7 14 8 20 
 Report No. US0092

 Page 23 

Table 11 Changes in Percent Crop Treated Value in Dietary Risk Assessments

Commodity EPA/BCS 2006 BCS 2008 EPA 2010 Maximum Agrotrak

Potatoes 

5 (Fresh) 

22 (Processed) 9 15 11.1

Oranges 12 12 35 30.8

Grapefruit 25 25 55 52.2

Prior to this assessment both BCS and EPA were applying the ratio of potatoes that went to fresh and 

processed markets to the percent crop treated values based on fresh and processed markets. 

Historically a smaller amount of potatoes are grown for the fresh market versus the processed market 

(i.e., frozen French fries, canned potatoes, etc.). While this is still the case, growers have indicated 

that it is not possible to fully segregate fresh and processed potatoes at the time of planting. The final 

destination will vary by market demand. Therefore, although conservative, one value of percent crop 

treated is now applied to fresh and processed potatoes. 

Additionally BCS ran a scenario which includes oranges at 20% crop treated. When Asian citrus 

psyllid disease became a serious issue in 2006-2007, many growers began using aldicarb as a 

preventative treatment in their citrus groves for the disease. This spike is reflected in the 2007-2008 

Agrotrak data for oranges. However, since then growers have switched from preventative treatments 

for Asian citrus psyllid to maintenance of other trees when Asian citrus psyllid is seen in a grove. The 

decline in percent crop treated can be seen in 2009 (Table 12, Figure 9). BCS marketing projects that 

in 2010 and beyond percent of crop treated values will return to 2006 levels (12% crop treated). 

Therefore scenarios were run which include oranges at 20% crop treated as a conservative value for 

future years. 

Table 12 Trend of TEMIK® Use on Florida Citrus

 

 

 

 

 
 Report No. US0092

 Page 24 

Figure 9 Percent Crop Treated For Use of Aldicarb in Florida Citrus

6. DRINKING WATER

A refined drinking water assessment for both surface water and ground water was conducted by 

Bayer CropScience [3]. The surface water assessment used water monitoring data from a 3 year 

study of raw and finished water in 38 different community water systems in aldicarb use areas in the 

United States [17]. The data from surface water in Florida and North Carolina were converted to 365 

day time series using a step function to fill in missing values. The ground water assessment used 

potable well monitoring data [18]. Samples were analyzed from 1673 drinking water wells in nine 

major use areas, which were within 1000 feet of fields treated at least once with TEMIK® Brand 15G 

Aldicarb pesticide. The ground water data were used in the CARES drinking water model by 

incorporating the probability of occurrence from the results of sampling by regions. The 365 day 

time series was held constant at the level detected from the ground water monitoring. 

Results from the drinking water assessment by Bayer CropScience in 2006 showed that the worst case 

ground water scenarios were more vulnerable than surface water scenarios when aggregated with the 

food exposures for all populations. Note that the distributions proposed for use for representing 

drinking water exposure are not merely a distribution of residues in rural wells in high use areas but 

instead represent the most vulnerable subset of these rural wells in high use areas. In the 2006 BCS 

report, the ground water monitoring data from South Carolina was the most sensitive to infants and 

children 1-2 yrs and has been used in the current risk assessment. 

In EPA drinking water assessments, the Agency continues to use PRZM modeling data rather than 

use the extensive water monitoring data that provides a more realistic representation of the potential 

for drinking water exposure. In the 2006 assessment EPA determined a distribution of residues for 

use in the dietary risk assessments based on inappropriately parameterized PRZM modeling (see 

Section 6.2) and typical use rates. As shown in (Figure 10) the blue line representing the PRZM 

modeling does not show any correlation with monitoring data (brown and green line) until beyond the 
 Report No. US0092

 Page 25 

99th percentile. EPA stated that their average concentrations were equal to the maximum of the 

monitoring data but as a probabilistic assessment depends on distributions of all probable exposures 

the modeling and monitoring data do not show appropriate correlation. 

Comparison of the modeled estimates and monitoring data are described in Figure 10 and Table 13. 

In the 2010 assessment, the distribution has been further distorted by using maximum label rates 

(black line in Figure 10). EPA used a comparison of label application rates that showed a 4-fold 

difference between the typical application rate and maximum application rate, therefore; the Agency 

multiplied the PRZM data from a “typical rate” by 4.04 to cover “maximum application rates”. The 

percentile distribution of all the PRZM data compared to actual measured ground water samples 

illustrates the conservatism in these data (Figure 10). There are approximately 7% of the modeled 

samples exceeding the Health Advisory Level of 10 ppb. The maximum modeled residue was 13 ppb 

while the highest residue ever observed in ground water monitoring (7,946 measured samples) was 

only 4.4 ppb. Less then 5% of the modeled values matched measured values in ground water 

monitoring, the minimum modeling value was 2.6 ppb. The Agency used these overly conservative 

water residues in the DEEM-FCID exposure model which will randomly assign a residue value from 

the distribution to each day of consumption for a 365 day period for each individual in a population. 

Table 13 Percentile Distribution Comparison

 Concentration (μg/L) 

Scenario Data Source

50th

%ile

75th

%ile

80th

%ile

90th

%ile

95th 

%ile 

99th 

%ile Maximum

PRZM Model 

Maximum 

Application 6.4 8.4 8.8 9.6 10.3 12.1 12.9 GA Coastal Plain 

Peanuts/Cotton PRZM Model 

Typical Application 1.9 2.4 2.5 2.8 3.0 3.5 3.7

Florida State 

Potable 

Well Monitoring 

Monitoring 

(6,273 measured 

samples) 0.50 0.50 0.50 0.50 0.50 0.50 4.4

BCS Potable Well 

Monitoring, 2005 

Monitoring 

(1,673 measured 

samples) 0.012 0.012 0.012 0.012 0.1 0.7 2.9
 Report No. US0092

 Page 26 

Figure 10 Comparison of Ground Water Residue Data from Modeling and Monitoringa

0

2

4

6

8

10

12

14

0 10 20 30 40 50 60 70 80 90 100

Percentile

Aldicarb Residue (ppb)

EPA PRZM Model (Maximum Rate)

EPA PRZM Model (Typical Rate)

FL Ground Water Monitoring (6,273 samples)

BCS Ground Water Monitoring (1,673 samples)

EPA PRZM Model (Typical Rate)

EPA PRZM Model (Maximum Rate)

13 ppb

10 ppb

3.7 ppb

4.4 ppb

2.9 ppb

Florida GW Monitoring

BayerCropScience GW Monitoring

EPA randomly samples 

value from this distribution 

each day in drinking water

exposure model.

Health Advisory Level

a Note that this does not reflect all available monitoring data. It was the most appropriate data set for risk assessment but is

consistent with a much larger database. 

6.1 Discussion of EPA Modeling Approach

The reason that the modeled distributions of residues do not reflect the monitoring data is a 

function of the parameters used in the model rather than the model itself. The modeling approach 

of EPA in calculating the potential movement of residues reflects a reasonable, conservative 

approach to estimating potential concentrations in potable wells. However, several of the 

parameters used in the modeling are beyond realistic worst case. The use of several exaggerated 

values for input parameters results in a highly distorted distribution. 

6.2 Parameterization of the Model

The values of four parameters used by EPA are overly conservative: degradation rates in surface 

soils, degradation rates in subsurface soils, degradation rates in ground water, and the speed of 

ground water flow. One of the parameters used by EPA is not always conservative enough is 

water table depth. 

Degradation Rate in Surface Soils. There are five field dissipation studies in these four states 

(AL, FL, GA, and SC) with half-lives of 0.3-0.6 months. Therefore, the longest half-life of 18 

days should have been used, while EPA used 55 days [19]. 

Degradation Rate in Subsoils. The extensive set of field studies conducted with aldicarb show 

no decrease in degradation rate in subsoils compared to the degradation rate in surface soils. A 

relevant exception is when subsoils are composed of acidic, coarse sand subsoils (coarse sand is 
 Report No. US0092

 Page 27 

an important distinction since degradation rates do not slow down in acidic, finer textured sand 

subsoils). Therefore, in these four states, the degradation rate in subsoils is the same as in surface 

soils, except on the Florida ridge. EPA assumed that below 25 cm degradation varied linearly to 

1 m and below 1 m a degradation rate of 500 days was assumed [19]. 

Degradation Rate in Ground Water. The degradation rate on the Florida ridge determined in 

field studies was 270 days. The degradation rate in flatwoods soils was much shorter and 

residues did not persist from year to year. Also field data has shown that degradation rates are 

faster in anaerobic conditions compared to aerobic conditions and as a result aldicarb degradation 

rates increase with increased depth into the water table. EPA assumed a degradation rate of 500 

days [20]. 

Speed of Ground Water Flow. EPA has assumed a value of 0.5 feet per day. This is a 

reasonable value for the Florida ridge, but not for the flatwoods areas of Florida, or the flat 

coastal plains. 

Water Table Depth. The ground water depth of 30 feet assumed by EPA is generally deeper 

than in areas in which residues have been found in Al, FL, GA, and SC, especially off the Florida 

ridge. However, this does not significantly influence model results since EPA assumed minimal 

degradation below 1 m. 

6.3 Calibration of the Model with Monitoring Data

A major failing of EPA’s parameterization of the model is that it does not predict the pattern of 

residues in more detailed monitoring studies that could be used for calibration. Combined soil 

and ground water monitoring studies were conducted at one location in South Carolina (Edisto) 

[21] and two in Florida outside the Florida ridge (Oviedo [22] and Fort Pierce [23]) and one 

ground water monitoring study without soil monitoring (Indiantown). Modeling using the EPA 

compound specific values for aldicarb combined with the site-specific environmental 

characteristics would not adequately represent the residues patterns observed at these 

experimental sites. 

7. DIETARY (FOOD AND DRINKING WATER) ANALYSIS MODELS

A description of the model used for the dietary risk assessments are described in this section. The 

Cumulative Aggregate Risk Evaluation System® (CARES®) was used to conduct dietary exposure 

based on the inputs previously described above. Daily exposure assessments were conducted with the 

CARES Production Version 3.0 (Build 1.2.4, date), while the within day exposure assessments were 

conducted with the CARES Evaluation Version 4.0 (Build 1.1.9, 02/16/2010). This evaluation 

version was developed and verified by Bayer CropScience to conduct both food and water within day 

exposure assessments. 

7.1 Within Day Dietary (Food and Drinking Water) Assessment

A basic principle of human risk assessment is that an individual’s exposure should be matched 

with relevant toxicological doses in terms of route, duration, and effect. This requirement is of 

particular importance when assessing aggregate or cumulative risk to populations or potentially 

sensitive sub-populations. Accumulation of common toxicity is not likely to occur if exposures 

and duration of effects are separated in time (and thus near-simultaneous exposures are necessary 
 Report No. US0092

 Page 28 

for cumulative effect to be seen) and if the common mechanism effect is reversible and recovery 

is rapid [24] 

Due to the rapid reversibility of ChE inhibition following exposure to aldicarb, the previous 

dietary (food) assessment developed the capability to conduct a within-day minute based 

exposure assessment. The CARES-Dietary Minute Module (DMM) version (Build 7.8.9, 

3/14/2006) was developed to use the time of eating event from the CSFII consumption database 

and incorporate reversibility in the exposure calculations. Recently a CARES-Water Minute 

Module (WMM) was developed to conduct a within-day exposure assessment for drinking water. 

The time of eating events for indirect water were taken from the CSFII consumption database. In 

order to establish the time of direct water consumption, there are two options: 1.) Use the Bayer 

Drinking Water Consumption Survey (BDWCS) [25] or 2.) Divide the daily direct water 

consumption based on user defined fixed interval. The daily sequence of consumption events 

from the BDWCS is assigned to a CARES individual and repeated for 365 days. 

BCS incorporated EPA’s method which is to divide the direct water consumption by fixed 

equally spaced intervals. For example, drinking water consumption starting at 6:00AM and 

ending at 9:00PM with 6 events would resulting 6 events spaced 3 hours apart (6:00AM, 

9:00AM, 12:00PM, 3:00PM, 6:00PM, and 9:00PM). The direct drinking water consumption data 

from the FCID consumption database would be divided by 6. 

7.2 Half-life Determination

The inhibition of RBC ChE by aldicarb is rapidly reversible with an estimated half-life (t1/2) of 

1.7 hours [26] based on the first-order elimination coefficient using ChE inhibition from a human 

volunteer study [27]. A lag interval was used in the present assessment as 1 hour since the first 

observation of the repeated observations obtained from each volunteer used to estimate the 

benchmark dose was obtained at 1 hour and is the same as used for the food within day 

assessments. 

7.3 Event Based Exposure Distribution

Dietary assessments have historically been conducted on either a chronic (one year to lifetime) or 

acute (one day) exposure time frame. Acute effects are summed for a day and each daily 

exposure value for the individuals in the population is placed in a probabilistic exposure 

distribution. In effect the distribution reflects the probability of a day long exposure occurring 

which is above the endpoint of concern. Regulatory decisions are then made for the exposure 

value at the 99.9th percentile, considered to be very conservative and protective. The daily 

exposure metric, however, is somewhat arbitrary, as multiple exposures may occur during a day. 

Until recently the capability for calculating exposure in increments less than a day has not been 

available in probabilistic dietary exposure models and thus a dose metric based on daily exposure 

has been used as the de facto standard. 

With aldicarb and other carbamates the half-life of cholinesterase inhibition is very short. Thus 

the time step of one day is not the appropriate time step for the exposure distribution. Since 

separate and distinct exposures could occur at each meal eaten or each occasion of water 

consumption (an eating or drinking event) then the proper time step would be less than a day and 

in this case would be an eating or drinking event. Events are typically two or more hours apart, 

but if they are not, the additive exposure of overlapping events would be captured by the decay 
 Report No. US0092

 Page 29 

factor (BCS uses the 1.7 hours derived from the appropriate study) incorporated in the minute by 

minute exposure distribution generated by the DMM or WMM. (Figure 11). Each eating / 

drinking event for the individuals in a population are then the basis for the exposure distribution 

and the exposure distribution reflects the probability of an exposure occurring above the level of 

concern for an event (meal or drinking water consumed). Thus route, effect, and duration have 

been properly matched to the toxicological effect which is being considered. 

EPA generates exposures at each eating occasion in a similar manner to BCS, but then chose to 

construct the exposure distribution by selecting the worst case event from each day. BCS 

constructs the exposure distribution by using all of the events from each day (Figure 11). 

Figure 11 Hypothetical Exposure Profile

01234567

Time (day)

Exposure 

Maximum Daily (EPA)

Maximum Event Based (BCS)

Minute Based Exposure Profile

Exposure Events

8. RESULTS AND DISCUSSION

8.1 Daily Dietary Food Assessment Results

Table 14 shows the results from daily dietary (food only) assessments and explores the impact of 

removing various food uses from the baseline dietary scenario. The baseline dietary scenario was 

conducted using all crops in the current registration based on the maximum percent crop treated 

values of 11%, 51%, and 31% for potatoes, grapefruits, and oranges, respectively. Based on 

differential FQPA safety factors based on ontogenic considerations of 3.9X for infants and 2X 

for children the %aPAD at the 99.9th percentile was 146, 135, and 112 for infants, children 1-2, 

and children 3-5, respectively. The removal of all potato uses from the baseline assessment and 

assigning 20% crop treated to citrus resulted in a decrease of the %aPAD utilization to 85 and 94 

for infants and children 1-2 yrs. old, respectively for a daily assessment. 
 Report No. US0092

 Page 30 

Table 14 Daily Dietary Food Risk Assessment Results for Various Scenarios

Scenario Populationa

Exposure @ 

99.9th %ile %aPADb

Infants 4.85E-04 146

Child 1-2 8.80E-04 135

Current Registration with maximum percent crop treated 

Potato (11%); Grapefruit (51%); Orange (31%)

Child 3-5 7.30E-04 112 

Current Registration with maximum percent crop treated Infants 3.44E-04 103

No Potatoes Child 1-2 7.05E-04 109 

Current Registration with maximum percent crop treated Infants 2.82E-04 85

No Potatoes; Orange = 20%CT Child 1-2 6.13E-04 94

a Population size for runs: Infants (5000); Children 1-2 (3367); and Children 3-5 (4985) b Infants based on FQPA safety factor = 3.9X. 

Children 1-2 yrs. old and children 3-5 yrs. old based on FQPA safety factor = 2X. 

The residue and consumption inputs are further discussed in Section 8.3. 

8.2 Aggregate (Food and Drinking Water) Assessment

When the within-day methodology to account for aldicarb reversibility is appropriately applied to 

the daily analysis scenarios that include all current registrations, an acceptable risk is obtained for 

the most sensitive populations of Infants (< 1 yr) and Children 1-2 yrs (Table 15). This 

demonstrates that a reasonable certainty of no harm results from the currently registered aldicarb 

uses when all available and sound scientific data is used. 

Table 15 Comparison of Daily vs. Within Day Exposure and Risk Determination

 Dailyc Within Dayc

Population Subgroupa Scenariob

Exposure @

99.9th %ile %aPADd

Exposure @ 

99.9th %ile %aPADd

Food Only 4.45E-04 134 2.06E-04 62

Water Only 3.26E-04 98 3.51E-05 11 Infants 

(< 1 yr old) Food + Water 5.29E-04 159 1.94E-04 58

Food Only 8.51E-04 131 3.55E-04 55

Water Only 1.32E-04 20 2.69E-05 4 Children 

1-2 yrs. old Food + Water 8.52E-04 131 3.07E-04 47

a Daily used population size = 1,000. 

Within Day used population size = 200 for infants and 100 for children 1-2 yrs. old. b

 Food Only = current registration with %CT = 11, 52, and 20 for potatoes, grapefruit, and citrus, respectively. 

Water Only = ground water monitoring data from South Carolina region. c Daily used daily consumption x residue value. 

Within Day incorporates elimination rate = 1⁄2 life based on 1.7 hrs or β3 = -0.90 h-1. 

Within Day water uses 6 equally spaced events 3 hrs apart starting at 6:00AM to 9:00PM. d Infants based on FQPA safety factor = 3.9X. 

Children 1-2 yrs. old based on FQPA safety factor = 2X. 
 Report No. US0092

 Page 31 

8.3 Contribution Analysis and Impact of 1⁄2 LOD Value on Dietary Food Only Assessments

Comparisons of the contribution analysis for dietary assessment with and without potatoes for 

infants and children 1-2 yrs old revealed specific commodities that are driving the exposure 

(Figure 12). For infants, the contribution analysis at the 99.9th percentile showed that potatoes 

and grapefruit juice contributed to 49% and 40% of the exposure, respectively. Removing 

potatoes increased the contribution of grapefruit juice and orange juice to 55% and 26%, 

respectively. It seemed unusual that grapefruit juice would be a commodity that is driving (40 to 

55%) the dietary risk assessment for infants. For children 1-2 yrs, the contribution analysis at the 

99.9th percentile showed that potatoes and orange juice contributed 45% and 43% of the exposure, 

respectively. Removal of potatoes resulted in orange juice as the only driver of exposure at 

99.7%. The assumption that children 1-2 yrs old would have high consumption of orange juice 

seemed reasonable, however; the drastic shift from 43% to 99.7% seemed to be unusual. A 

detailed analysis of the consumption and residue inputs at the high end was performed to 

determine if there were any confounding factors leading to overestimation of exposure. 

Figure 12 Contribution Analysis at the 99.9th percentile for Infants and Children 1-2 yrs.

7

26

55

5

49

1

4

40

0 10 20 30 40 50 60 70 80

Potato, tuber,

w/peel

Potato, tuber, w/o

peel

Orange, juicebabyfood

Orange, juice

Grapefruit, juice

% Contribution

Current Registration with Potatoes

Current Registration without Potatoes

Infants (< 1 yr)

12

45

43

99.7

0 20 40 60 80 100

Potato, tuber,

w/peel

Potato, tuber, w/o

peel

Orange, juice

% Contribution

Current Registration with Potatoes

Current Registration without Potatoes

Children 1-2 yrs. old

8.3.1 Consumption Data

Analysis of grapefruit juice consumption data (all food forms) for infants from the FCID 

database showed two extreme values of 60.2 and 69.8 g/kg (Figure 4). The third highest 

consumption value for grapefruit juice in infants was 1.4 g/kg which represents the 94th

percentile. The percentile distributions show little difference between daily and eating 

occasion consumptions meaning that individuals typically consume all grapefruit juice in 

single event (i.e. a glass of juice). 
 Report No. US0092

 Page 32 

Figure 13 Grapefruit Juice Consumption by Infants (< 1 yr old)

1.4 g/kg

60.2 g/kg

69.9 g/kg

0

10

20

30

40

50

60

70

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percentile

Consumption (g/kg)

Daily

By Event

Grapefruit Juice Consumption by Infants (< 1yr) 

based on CSFII/FCID

Further analysis for these individuals linked to the CSFII reveal the food and amount of 

food consumed during the day (Table 16). The maximum consumption of 69.8 g/kg is 

from an infant (8 month old) consuming 2003 grams of grapefruit juice drink that is made 

up of 30% grapefruit juice food form (2003 g * 0.30 = 600.9 g / 8.6 kg = 69.8 g/kg). The 

second highest consumption 60.2 g/kg is from an infant (8 month old) consuming 494 

grams of unsweetened grapefruit juice canned that is made up of 100% grapefruit juice 

food form (494 g / 8.2 kg = 60.2 g/kg). Assuming a density of 1 g/mL equivalent to 

water, consumption would be equivalent to an infant (19 lbs.) consuming 0.5 L and 2 L 

of juice in a single serving. 

Table 16 CSFII Records for Extreme Grapefruit Juice Consumption in Infants

Eating Time Food Code Food Consumed (g) Description 

800 11111000 61 MILK, COW'S, FLUID, WHOLE 

800 11710603 244 ENFAMIL W/ IRON, INFANT FORMULA, PREPARED FROM POWDER 

800 57348000 20 FROSTED CORN FLAKES, NFS 

800 92530810 2003 GRAPEFRUIT JUICE DRINK W/ VITAMIN C ADDED 

1200 11710603 244 ENFAMIL W/ IRON, INFANT FORMULA, PREPARED FROM POWDER 

1600 11710603 244 ENFAMIL W/ IRON, INFANT FORMULA, PREPARED FROM POWDER 

1730 25210110 28.5 FRANKFURTER, WIENER OR HOT DOG, NFS 

1730 41201040 31.63 BAKED BEAN W/ PORK & SWEET SAUCE 

2000 11710603 244 ENFAMIL W/ IRON, INFANT FORMULA, PREPARED FROM POWDER 

FCID/CSFII Household ID = 18411; Person Number = 2; Day = 2 

8 month old infant weighing 8.6 kg. 

Eating Time Food Code Food Consumed (g) Description 

800 57802000 15 HIGH PROTEIN CEREAL, BABY, DRY, INSTANT 

800 61201220 494 GRAPEFRUIT JUICE, CANNED, BOTTLED, CARTON, UNSWEET 

800 64104010 46.5 APPLE JUICE 

800 64104050 496 APPLE JUICE, W/ ADDED VITAMIN C 

1300 11710603 61 ENFAMIL W/ IRON, INFANT FORMULA, PREPARED FROM POWDER 

1900 53220000 32 COOKIE, FRUIT-FILLED 

FCID/CSFII Household ID = 25011; Person Number = 2; Day = 2 

8 month old infant weighing 8.2 kg. 
 Report No. US0092

 Page 33 

Analysis of orange juice consumption data (all food forms) for children 1-2 yrs old from 

the FCID database showed two maximum daily values of 119.7 and 107.7 g/kg and a 

maximum event value of 75 g/kg (Figure 14). The percentile distributions shows a slight 

difference between daily and eating occasion consumptions meaning that some 

individuals consume all orange juice in multiple events (i.e. a glass of juice with each 

meal). 

Figure 14 Orange Juice Consumption by Children 1-2 yrs. old

75.5 g/kg

107.7 g/kg

119.7 g/kg

0

20

40

60

80

100

120

140

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Percentile

Consumption (g/kg)

Daily

By Event

Orange Juice Consumption by Children 1-2 yrs. old

based on CSFII/FCID 

Further analysis for individuals linked to the CSFII reveal the food and amount of food 

consumed during the day (Table 17). Both the maximum daily values (119.7 and 107.7 

g/kg) were from the same individual (CSFII Household ID = 48112; Person = 1) on two 

different survey days. This child consumed orange juice 3 and 4 times during the day 

with the maximum consumption per event at 47.8 g/kg. The maximum consumption by 

event of 75.5 g/kg is from 1 yr old child consuming 996 grams of unsweetened, canned 

orange juice that is made up of 100% orange juice food form (996 g / 13.2 kg = 75.5 

g/kg). Assuming a density of 1 g/mL equivalent to water, consumption would be 

equivalent to an infant (29 lbs.) consuming 1 L of juice in a single serving. 

Table 17 CSFII Records for High Orange Juice Consumption in Children 1-2 yrs old

Eating Time Food Code Food Consumed (g) Description 

1000 11112110 244 MILK, COW'S, FLUID, 2% FAT 

1000 25221410 10.6 PORK SAUSAGE, FRESH, BULK, PATTY OR LINK, COOKED 

1000 31105000 20 EGGS, WHOLE, FRIED (INCL SCRAMBLED, NO MILK ADDED) 

1400 54202010 12 CRACKERS, SALTINE, LOW SODIUM 

1400 58403010 120.5 CHICKEN NOODLE SOUP (INCLUDE CHICKEN & STARS SOUP) 

1400 61210220 996 ORANGE JUICE, CANNED/BOTTLED/CARTON, UNSWEETENED 

1900 54202010 9 CRACKERS, SALTINE, LOW SODIUM 

1900 58403010 120.5 CHICKEN NOODLE SOUP (INCLUDE CHICKEN & STARS SOUP) 

2100 13150000 48.25 SHERBET, ALL FLAVORS 

FCID/CSFII Household ID = 25654; Person Number = 1; Day = 1 

1 yr. old child weighing 13.2 kg. 
 Report No. US0092

 Page 34 

These extreme consumption values for grapefruit juice and orange juice reflect why these 

commodities are driving the risk assessment for infants and children 1-2 yrs, respectively. 

8.3.2 Residue Assignment

As previously discussed in the Residue Section, the residue data from PDP was analyzed 

with a multi-residue analytical method that detects aldicarb, aldicarb sulfoxide, and 

aldicarb sulfone. As per EPA policy, all analytes are stoichiometrically converted to 

aldicarb and summed to represent aldicarb equivalents. If an analyte was not detected, 

then the 1⁄2 LOD value is used in the determination of aldicarb equivalents. This is 

summarized in the following equation: 

Total residue (as aldicarb) = (aldicarb sulfone x 0.86) + (aldicarb) + (aldicarb sulfoxide x 0.92) 

The presence of aldicarb parent has almost never been detected in PDP samples. 

Reviewing the last 10 years of PDP data from 1998 to 2008 encompassing more than 

75,000 samples on various commodities there have only been 1 detect of aldicarb parent: 

sweet corn in 2003 at 0.033 ppm (there is no tolerance on sweet corn). The current PDP 

data for citrus (oranges, orange juice, and grapefruit) reveals no detects for aldicarb 

parent or aldicarb sulfone. The approach of summing all three 1⁄2 LOD values results in 

assumed values where in some cases the 1⁄2 LOD value in citrus is greater than many of 

the detected values (Figure 15). For citrus PDP data, a more realistic approach would be 

to use only the aldicarb sulfoxide data converted to aldicarb equivalents to examine the 

sensitivity of the analysis to this parameter. 

Accounting solely for aldicarb sulfoxide non-detects in juice is consistent with the 

metabolic profile. In a 1996 metabolism study [28], lemon trees were treated with 

radiolabeled [14C]-aldicarb. The aldicarb was soil applied and the fruit were harvested 

153 days later. Aldicarb was found to be metabolized readily upon application to soil and 

uptake by lemon plants. Very low levels of radiocarbon were detected in the RAC 

components (peel, pulp and juice). These materials were quantitatively extracted with 

acetone and aqueous acetone suggesting minimal (if any) incorporation into plant 

components. The main metabolic pathway proceeded via sulfone intermediates to yield 

toxicologically non-relevant metabolites arising from oxidative and hydrolytic processes 

previously described for plant metabolism of aldicarb in the literature. No aldicarb, per 

se, was detected in the RAC indicating complete metabolism of the parent. Traces 

(<0.005 ppm) of aldicarb sulfone and sulfoxide were also detected. A supplemental 

study looked specifically for aldicarb residues in the lemon foliage, but found none [29]. 

Traces of aldicarb sulfoxide and aldicarb sulfone were detected in the peel and pulp, but 

not in the juice. 

A further consideration in not including aldicarb sulfone detects in the citrus residues is 

that is has been shown to be 20-fold less potent as a cholinesterase inhibitor than aldicarb 

[30]. 
 Report No. US0092

 Page 35 

Figure 15 Orange Juice Residue Distribution

9

22

33 33

2 2

9

0

10

20

30

40

50

60

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

0.018

Aldicarb Equivalence (mg/kg)

Frequency (Count)

1/2 LOD for all analytes

1/2 LOD for sulfoxide only

1440 1500 1440

8.3.3 Dietary Assessment Results Using Refined 1⁄2 LOD Values

The baseline daily dietary (food) assessment using 1⁄2 LOD from all three analytes with 

revised percent crop treated for citrus (20%) shows a %aPAD at the 99.9th percentile of 

144% and 131% for infants and children 1-2 yrs old, respectively (Table 18). Revising 

all citrus data to include only the aldicarb sulfoxide values decreased the %aPAD for 

food only to 91% and 98% for infants and children 1-2 yrs. old. Removing potatoes and 

sweet potatoes further reduced the exposure resulting in %aPAD of 26% and 33% for 

infants and children 1-2 yrs. The aggregate food and drinking water using worse case 

water monitoring data from South Carolina resulted in acceptable %aPAD for both 

sensitive populations in a daily assessment. These results are conservative in that they do 

not reflect the incorporation of reversibility into the analysis. 
 Report No. US0092

 Page 36 

Table 18 Daily Dietary Assessment Results Using Refined 1⁄2 LOD Values

Food Only 

Including potatoes 

Citrus 20% 

1⁄2 LOD all analytes 

Food Only 

Including potatoes 

Citrus 20% 

1⁄2 LOD sulfoxide 

Food Only 

No Potatoes 

Citrus 20% 

1⁄2 LOD sulfoxide 

Food + Water 

No Potatoes 

Citrus 20% 

1⁄2 LOD sulfoxide 

Population Exposure %aPAD Exposure %aPAD Exposure %aPAD Exposure %aPAD 

Infants 

(< 1 yr old) 4.79E-04 144 3.04E-04 91 8.80E-05 26 3.30E-04 99 

Children 

(1-2 yr old) 8.50E-04 131 6.35E-04 98 2.12E-04 33 2.37E-04 37 a Infants based on FQPA safety factor = 3.9X. 

Children 1-2 yrs. old based on FQPA safety factor = 2X. 

8.4 Commodity Specific (Eater Only) Assessment

Bayer CropScience conducted a commodity specific analysis for orange juice and indirect 

drinking water similar to the EPA 2010 dietary assessment (p. 23) [10]. Residue values were 

taken from worse case PDP monitoring data for orange juice and highest measured residue from 

ground water monitoring study in Florida for indirect drinking water. Margins of exposure were 

estimated for orange juice by children 1-2 yrs old and indirect drinking water by infants. The 

margins of exposure were greater than 39 for infants and 20 for children 1-2 yrs indicating these 

levels were not a concern (Table 19). 

Table 19 Commodity Specific (Eater Only) Assessment for Orange Juice and Indirect Water

Indirect Water 

Consumption by Infant 

Consumptiona

(g/kg BW/event)

Residueb

(ppm)

Exposure

(mg/kg)

NOAEL 

(mg/kg) MOE

50th percentile of Consumption 15.8 0.0044 6.95E-05 0.013 187

90th percentile of Consumption 29.2 0.0044 1.28E-04 0.013 101

 

Orange Juice 

Consumption by Child 1-2 yrs. 

Consumptionc

(g/kg BW/day)

Residued

(ppm)

Exposure

(mg/kg)

NOAEL 

(mg/kg) MOE

50th percentile of Consumption 14.1 0.00736 1.04E-04 0.013 125

90th percentile of Consumption 31.4 0.00736 2.31E-04 0.013 56 a Indirect water consumption based on CSFII/FCID data per eating occasion. b

 Highest ground water residue measured in Florida potable well monitoring program. 

c Orange juice consumption based on food form uncooked, fresh, not specified. d Highest orange juice detect in PDP 2006 of 0.008 ppm alicarb sulfoxide converted to aldicarb equivalence 

(x 0.86). 

9. CONCLUSION

Based on all available data, BCS consider that this assessment demonstrates that current registered 

uses of TEMIK® meet the EPA safety standard of “reasonable certainty of no harm”. 
 Report No. US0092

 Page 37 

10. REFERENCES

1. USEPA, 2007. Reregistraion Eligibility Decision (RED) for Aldicarb, List A Case Number 

0140. EPA, Washington D.C. September 2007. p. 191. 

2. USEPA, 2006. Aldicarb. List A Reregistration Case No. 0140/Chemical ID No. 098301. 

Revised Dietary Exposure Analyses for the HED Human Health Risk Assessment. DP 

Barcode No. D299882. EPA, Washington, D.C. November 1, 2006. p. 98. 

3 Lantz, J.; B. M. Young; R. L. Jones; G. J. Mihlan. 2006. Aldicarb Acute Dietary Risk 

Assessment Including Food and Drinking Water. Report Number: G201350. Bayer 

CropScience, RTP, NC. July 14, 2006. p. 219. MRID #46891402. 

4 Beck, M. 2009. A Comparative Dose Study of the Effects of Aldicarb on Red Blood Cell 

and Brain Cholinesterase in Adult and Juvenile Rats following oral (gavage) administration. 

Study Number: WIL-21210. WIL Research Laboratories, Ashland, OH. November 19, 

2009. p. 134. MRID #47994305. 

5 Blacker, A. 2010. Application of the FQPA Factor for Aldicarb. Report Number: G202153. 

Bayer CropScience, RTP, NC. February 25, 2010. p. 4. MRID #47994301. 

6 USEPA, 2010. Aldicarb. Acute Probabilistic Aggregate Dietary (Food and Drinking Water) 

Exposure and Risk Assessment Incorporating Revised FQPA Factor. PC Code: 098301. DP 

Barcode: 299874. EPA, Washington, D.C. July 15, 2010. p. 24 

7 Sielken R. L. 2010. Benchmark Doses for Brain and RBC Acetylcholinesterase in Adult and 

Pups Exposed to Aldicarb. Sielken & Associates Consulting, Inc., Bryan, TX 77802, 

February 18, 2010. p. 68. MRID #47994306. 

8 USEPA, 2010. Statistical Review of Sielken, R. (2010) Benchmark Doses for Brain and 

RBC Acetylcholinesterase in Adult and Pups Exposed to Aldicarb. Project Number: G202152 

Unpublished study prepared by Sielken, Inc. DP Barcode: 379831. EPA, Washington, D.C. 

p. 42. 

9 Hayes, W. 1982. Pesticide studies in man. Baltimore, MD: Williams & Wilkins. 

10 Benjamins, J. and McKhann, G. Eds. 1981. Development, regeneration, and aging of the 

brain. Basic Neurochemistry. Boston, Brown and Co. 

11 Davision, A.N. and Dobbing, J. 1966. Myelination as a vulnerable period in brain 

development. Br. Med. Bull. 22(1): 40-44. 

12 Dobbing, J. and Smart, J.L. 1974. Vulnerability of developing brain and behavior. Br. Med. 

Bull. 30(2): 164-168. 

13 Carringer, S.J. 2000. Carbamate Insecticide Market Basket Survey. The Carringer, Inc., 

Apex, NC 27502. Study No. TCI-99-001. Unpublished. 

14 USDP Pesticide Data Program (PDP). (http://www.ams.usda.gov/AMSv1.0/pdp) 
 Report No. US0092

 Page 38 

15 USEPA, 2000. Assigning Values to Non-detected/Non-Quantified Residues in Human 

Health Food Exposure Assessment. Office of Pesticide Programs, EPA, Washington, D.C. 

March 23, 2000. p. 33. 

16 Doucoure, C. 2007. Presentation: Percent Crop Treated (PC) and Projected Percent Crop 

Treated (PPCT): BEAD’s Approach at the Dietary Assessment Working Group. Biological 

and Economic Analysis Division (BEAD). May 15, 2007. 

17 Movassaghi, S, S. Daussin, J. P. Hanzas, Jr. 2005. Surface Water Monitoring for Residues of 

Aldicarb In High Use Areas in the United States. Bayer CropScience Study No. 00T30605, 

Report No. B004894. 1367 pages. MRID #46466401. 

18 Jones, R. L., and T. S. Ramanarayanan. 2006. TEMIK® brand15G Aldicarb Pesticide: 

Summary of Five Retrospective Ground Water Monitoring Studies conducted for Aldicarb 

and Its Metabolites in the Pacific Northwest, California, Texas, Mississippi Delta and the 

Southeast Regions of the United States in 2005. Bayer CropScience Study No. RAAVY010. 

MRID # 46793701. 

19 Jones, R. L. and T. L. Estes. 1995. Summary of Aldicarb Monitoring and Research 

Programs in the United States. Journal of Contaminant Hydrology 18:107-140. 

20 Jones and Estes, 1995, listed above and Carsel, R. F., R. L. Jones, J. L. Hansen, R. L. Lamb, 

and M. P. Anderson. 1988. A Simulation Procedure for Groundwater Quality Assessments 

of Pesticides. Journal of Contaminant Hydrology 2:125-138. 

21 Hegg, R. O., W. H. Shelley, R. L. Jones, and R. R. Romine. 1988. Movement and 

Degradation of Aldicarb Residues in South Carolina Loamy Sand Soil. Agriculture, 

Ecosystems, and Environment 

22 Jones, R. L., A. G. Hornsby, and P. S. C. Rao. 1988. Degradation and Movement of 

Aldicarb Residues in Florida Citrus Soils. Pesticide Science 23:307-325. Some of the 

ground water monitoring data is included in: Hornsby, A. G., P. S. C. Rao, W. B. Wheeler, 

P. Nkedi-kizza, and R. L. Jones. 1983. Fate of Aldicarb in Florida Citrus Soils: 1. Field and 

Laboratory Studies. paper presented at Characterization and Monitoring of the Vadose 

(Unsaturated) Zone, Las Vegas, December 8-10, pp. 936-958. 

23 Jones, R. L., J. L. Hansen, R. R. Romine, and T. E. Marquardt. 1986. Unsaturated Zone 

Studies on the Degradation and Movement of Aldicarb and Aldoxycarb Residues. 

Environmental Toxicology and Chemistry 5:361-372. 

24 Kelly, I.D., Lantz, J.L., Mihlan, G.J. and Young, B.M. 2006. CARES-compatible Dietary 

Minute Module (DMM) Version 2.2 Build 7.8.9 (3/14/2006) Technical Manual. Bayer 

CropScience Report Number G201504. MRID #46796602 

25 Barraj, L., Scrafford, C., Lantz, J., Daniels, C., and Mihlan, G. 2008. Within-day drinking 

water consumption patterns: Results from a drinking water consumption survey. J. Expo. Sci. 

Env. Epid. Advance online publication, 14 May 2008; doi:10.1038/jes.2008.28 pp. 1-14. 
 Report No. US0092

 Page 39 

26 Williams , R. L. , Mihlan , G. J. , and Tobia , A. J. ( 2008 ) . Modeling cholinesterase activity 

for human dietary risk assessment of carbamates insecticides. Risk Anal. 28 ( 4 ) , 1069 – 

1079 . 

27 Wyld, P.J., Watson, C.E., Nimmo W.S., Watson, N. 1992. A Safety and Tolerability Study of 

Aldicarb at Various Dose Levels in Healthy Male and Female Volunteers. Inveresk Clinical 

Research Report No. 7786. ICR Project No. 003237. MRID # 42373001. 

28 Hathcock, T.; Kimmel, E.C., Ruzo, L.O. 1996. A Metabolism Study with [l4C]-Aldicarb in 

Citrus (Lemon Trees). PTRL Report No. 478W-1. PTRL West, Inc., Richmond, CA. 

January 10, 1996. p. 234. MRID #43902401. 

29 Wells-Knecht, M. C.; Andrawes, N. R. 1996. (14C)-Aldicarb metobolism in citrus (lemon 

trees). Supplemental Study: Metabolism in citrus foliage (Supplemental report to MRID No. 

43902401). Report No. C046227. Rhone-Poulenc Ag Company, RTP, NC. March 11, 1996. 

p. 286. MRID #43970001. 

30 Blacker, A.; I.D. Kelly, J.L Lantz, G.J. Mihlan, R. L. Jones, B.M. Young. 2010. Aldicarb: 

Toxicity, Exposure and Risks to Humans In: R. Kreiger Ed. Hayes Handbook of Pesticide 

Toxicology, Elsevier Inc.