Revised N-Methyl 

Carbamate Cumulative 

Risk Assessment 

U.S. Environmental Protection Agency

Office of Pesticide Programs 

September 24, 2007 
-- 

_________________________________________ 

Revised N-Methyl Carbamate 

Cumulative Risk Assessment 

Technical Executive Summary 

With the passage of the FQPA (1996), EPA was required to consider available 

information concerning the cumulative effects on human health resulting from exposure 

to multiple chemicals that have a common mechanism of toxicity. In 2001, the Agency 

identified the N-methyl carbamate (NMC) pesticides as a group which shares a 

common mechanism and published a preliminary Cumulative Risk Assessment (CRA) 

in 2005. A cumulative risk assessment incorporates exposures from multiple pathways 

(i.e., food, drinking water, and residential/non-occupational exposure to pesticides in air, 

or on soil, grass, and indoor surfaces) for those chemicals with a common mechanism 

of toxicity. 

Since the release of the preliminary NMC CRA, the Agency has incorporated new 

hazard and exposure data, assigned FQPA safety factors, evaluated comments from 

the public, and addressed comments by the FIFRA Scientific Advisory Panel (SAP). In 

addition, since 2005, the Agency’s Office of Pesticide Programs (OPP) has completed 

several additional risk assessments for individual NMC pesticides (aldicarb, carbaryl, 

carbofuran, methomyl and propoxur) and, where necessary, established mitigation 

measures to be implemented to reduce exposure to these pesticides. These mitigation 

measures are reflected in this revised NMC CRA. 

The methodology used in this revised CRA is similar to that used in the 

preliminary CRA and supported by the SAP (USEPA, 2005a,b). Throughout the 

development of this CRA, EPA has relied on the SAP to peer-review guidance 

documents, methods, approaches, and pilot analyses to ensure that appropriate 

methods and sound science were applied. In addition to the SAP reviews, EPA has 

sought and considered public comments on these approaches as it developed these 

cumulative assessment methods. 

Background: 

A CRA begins with the identification of a group of chemicals, called a Common 

Mechanism Group (CMG), which induces a common toxic effect by a common 

mechanism of toxicity. Pesticides are determined to have a "common mechanism of 

toxicity" if they act the same way in the body--that is, the same toxic effect occurs in the 

same organ or tissue by essentially the same sequence of major biochemical events. 

The NMCs were established as a CMG by EPA in 2001 (USEPA, 2001a) based on the 

shared structural characteristics and similarities and their shared ability to inhibit 

acetylcholinesterase (AChE) by carbamylation of the serine hydroxyl group located in 

the active site of the enzyme. When AChE is inhibited, acetylcholine accumulates and 

cholinergic toxicity results due to continuous stimulation of cholinergic receptors 

throughout the central and peripheral nervous systems that innervate virtually every 

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organ in the body. An important aspect of NMC toxicity is the rapid nature of the 

onset and recovery of effects; following maximal inhibition of cholinesterase (typically 

between 15 and 45 minutes), recovery occurs rapidly (minutes to hours). 

Once a CMG is identified, it is important to determine which chemicals from that 

group should be included in the quantification of cumulative risk. The group of 

pesticides which is included in the quantification of cumulative risk -- and consequently 

incorporated into the CRA -- is termed the Cumulative Assessment Group (CAG). In 

determining the specific NMC pesticides to be included in the CAG, EPA considered 

risk mitigation decisions and exposure potential. EPA identified three exposure 

pathways of interest for these pesticides: food, drinking water, and residential/nonoccupational. Each of these pathways was initially evaluated separately, and -- in 

performing this portion of the analysis -- EPA determined which of the NMCs were 

appropriate to include for each given pathway. The cumulative assessment of potential 

exposure to NMCs in food includes those which are currently registered in the U.S. or 

have import tolerances. The drinking water exposure pathway includes NMC pesticides 

with registered uses in the U.S. that can potentially reach water bodies or ground water 

(i.e., outdoor uses). The revised NMC CRA evaluates the residential exposure pathway 

for three pesticides registered in the U.S. (carbaryl, methiocarb and propoxur) for home 

use, The current assessment reflects the most up-to-date and best available 

information for these chemicals. 

There are many steps involved in quantitatively assessing the potential human 

health risk associated with exposure to the NMC pesticides. The complex series of 

evaluations involve hazard and dose-response analyses; assessments of food, drinking 

water, residential/non-occupational exposures; combining exposures to produce a 

cumulative risk estimate; and risk characterization. These steps are described more 

fully in OPP’s Cumulative Guidance (USEPA, 2002a). The approach to each of these 

components and their results is briefly explained below: 

 Selection of an index chemical to use as the point of reference to standardize 

the toxic potencies of each NMC, determination of the relative toxic contribution of each 

NMC, and establishment of a value to estimate potential risk for the group (i.e. point of 

departure); 

 Evaluation of inter-species differences (i.e., extrapolation of rat responses to 

human responses) intra-species varability; and the potential sensitivity to infants and 

children; 

 Estimation of the risks associated with all pertinent pathways of exposure 

(i.e., food, drinking water, residential) in a manner that is both realistic and reflective of 

variability due to differences in location, time, and demographic characteristics of 

exposed groups; 

 Identification of the significant contributors to risk; and 

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 Characterization of the confidence in the results and the uncertainties 

associated with the assessment. 

Hazard and Dose-Response Assessment: 

EPA used the relative potency factor (RPF) method to determine the combined 

risk associated with exposure to NMCs. Briefly, the RPF approach uses an index 

chemical as the point of reference for comparing the toxicity of the NMC pesticides. 

RPFs are calculated as the ratio of the toxic potency of a given chemical to that of the 

index chemical and are used to convert exposures of all chemicals in the group into 

exposure equivalents of the index chemical. Because of its high quality dose response 

data for all routes of exposure, as well as high quality time-to-recovery data, EPA 

selected oxamyl as the index chemical for standardizing the toxic potencies and 

calculating relative potency factors for each NMC pesticide. 

Toxic potencies for the NMCs were determined using brain AChE inhibition 

measured at peak inhibition following gavage exposures in rats. Brain AChE inhibition 

is a direct measure of the mechanism of toxicity and thus does not have the uncertainty 

associated with using blood measurements of cholinesterase inhibition which serve as 

surrogates for cholinesterase inhibition in the peripheral nervous system. Furthermore, 

relative toxic potencies derived from brain data were shown in the preliminary 

assessment to be similar to those derived from red blood cell data but showed less 

variability, and thus less uncertainty, when comparing potency across the NMCs. 

The Agency used an exponential dose-time-response model to develop 

benchmark dose estimates at a level estimated to result in 10% brain cholinesterase 

inhibition (i.e., a benchmark dose or BMD10) to estimate relative potency. The Agency 

has also calculated the half-life to recovery for brain AChE inhibition. The Agency has 

used the lower confidence limit on the BMD10 (i.e., BMDL10) to develop points of 

departure (PoD) from the oral, dermal, and inhalation routes for oxamyl, the index 

chemical. A PoD is a point estimate on the index chemical’s dose-response curve from 

which risks associated with the exposure levels anticipated in the human population are 

extrapolated. EPA compares estimated exposures with the route-specific PoD values 

to calculate Margins of Exposure (MOE) and to estimate potential risk to humans. 

The Agency has used available comparative cholinesterase studies in juvenile 

(post-natal day 11 and/or 17) and adult rats to evaluate the FQPA 10X safety factor. 

These studies are available for six NMCs. For these NMCs, the Agency calculated the 

BMD10 in pups and adults—the ratio of these benchmark doses provides the chemicalspecific FQPA factor. For the remaining NMCs without comparative data, a 10X factor 

was applied. For the inter-species extrapolation factors, there are studies with human 

subjects with three NMCs (aldicarb, methomy and oxamyl) that were determined by 

EPA, after considering the advice of the Human Studies Review Board, to be ethically 

and scientifically acceptable for use in this risk assessment. These studies were used 

to derive the chemical-specific inter-species extrapolation factor for these three 

chemicals. For the remaining NMCs, the standard 10X factor was assigned for interES - Page 4 of 277 
species extrapolation. Since each NMC has been assigned its own inter-species 

and FQPA safety factors, the Agency has mathematically applied the value of these 

factors directly to the RPF for each NMC. In addition, the Agency has used the 

standard 10X factor for intra-species extrapolation for all the NMCs. Thus, to account 

for intra-species extrapolation, the target MOE for the revised NMC CRA is 10. 

Exposure Assessment: 

An important aspect of the exposure analyses is to develop exposure scenarios 

resulting from the uses for each NMC. Three key pathways of exposure to NMC 

pesticides -- food, drinking water, and residential and other non-occupational settings -- 

were included in this assessment. The factors EPA considered in the analysis of 

exposure by each of these three pathways included duration, frequency, and 

seasonality of exposure. Evaluation of chemical use profiles allows for the identification 

of exposure scenarios that may overlap, co-occur, or vary between chemicals, as well 

as for the identification of populations of concern. 

All of the hazard data, exposure data, and exposure scenarios must be combined 

in a manner designed to produce reasonable and realistic estimates of exposures likely 

to be encountered by the public in location and time of year. As was done in previous 

CRAs, EPA used CalendexTM software to integrate various pathways while 

simultaneously incorporating the time dimensions of the data. CalendexTM provides a 

focused, detailed profile of potential exposures to individuals across a calendar year. 

LifeLineTM software was also used to evaluate exposures through the food pathway and 

these results are presented and discussed in Appendix C. Exposures through 

residential uses and in drinking water are incorporated into cumulative exposure 

assessments on a regional basis. EPA conducted regional assessments for drinking 

water and joined these with generic residential exposure scenarios generally 

representative of regions in the Southern U.S. These regional assessments reflect the 

highest potential exposure scenarios for the U.S. and account for differing agronomic 

uses and reflect the differences in climate, soil conditions, and pest pressures across 

the country. Exposures that are represented in these generic residential exposure 

scenarios are not expected to be exceeded in any region in the U.S. Exposure to NMC 

pesticide residues in foods is considered to be uniform across the nation (i.e., there are 

no significant differences in food exposure due to time of year or geographic location). 

The assumption of nationally uniform food exposure is based on the understanding that, 

to a large extent, food is distributed nationally and food consumption is independent of 

geographic region and season. The single national estimate of food exposure was 

combined with region-specific exposures from residential uses and drinking water in 

three regions that represent the highest potential for exposure. 

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Table ES -1. Summary Information Regarding the NMC Pesticides and the Uses, and 

Pathways Included in the revised NMC Cumulative Risk Assessment 

Pesticide Pesticide Uses 

Pesticide Pathways 

Food Drinking Water Residential 

Carbaryl 

Ag Crops X X 

Lawn X 

Garden X 

Ornamentals X 

Fruit Trees X 

Pet Collar X 

Golfer Exposure X 

Aldicarb Ag Crops X X 

Oxamyl Ag Crops X X 

Formetanate HCl Ag Crops X X 

Methomyl Ag Crops X X 

Carbofuran Ag Crops X X 

Propoxur 

Food Uses X 

Pet Collars X 

Methiocarb Ag Crops X 

Ornamental X 

Thiodicarb Ag Crops X X 

Pirimicarb Ag Crops X 

 The approach for each pathway of exposure and results for the revised NMC 

CRA are explained below: 

Food: 

The food component of the revised NMC CRA is considered to be highly refined 

and to provide reasonable estimates of the distribution of exposures across the U.S. 

The exposure estimates for food are based on residue monitoring data from the USDA's 

Pesticide Data Program (PDP) supplemented qualitatively with information from the 

Food and Drug Administration’s (FDA) Pesticide Residue Monitoring Program and Total 

Diet Study. The PDP data provide a very reliable estimate of pesticide residues in the 

major children's foods and account -- directly or indirectly through the use of commodity 

surrogates -- for approximately 93% of food consumption by children. These data also 

provide direct measures of co-occurrence of NMC pesticides in the same sample. PDP 

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samples with non-detectable residues were treated in this assessment as "zero" 

values. Sensitivity analyses have determined that this approach does not significantly 

underestimate exposures at the upper percentiles for the NMCs (i.e., those percentiles 

which are of the greatest regulatory importance). For those foods not monitored in 

PDP, similar commodities that are measured by PDP served as surrogate data sources. 

This approach is considered to be reasonable and generally sound given that it is based 

on the concept that families of commodities with similar cultural practices and insect 

pests are likely to have similar pesticide use patterns and residue levels. Additionally, 

these surrogated commodities account for less than 1% of children’s diets. 

The reliability of the food component of this assessment is also supported by the 

use of the food consumption data from the USDA's Continuing Survey of Food Intakes 

by Individuals, (CSFII 1994-1996/1998). The CSFII surveyed more than 20,000 

individuals over two non-consecutive days and provides a detailed representation of the 

food consumption patterns of the U.S. public across all age groups, during all times of 

the year, and across all 50 states. Thus, EPA has confidence that the consumption 

estimates for food are well-established and consequently support reasonable risk 

estimates for the U.S. population. The NMC CRA focuses on the following age groups: 

children 1-2 years old; children 3-5 years old; adults 20-49 years old; and adults 50+ 

years old. These age groups were selected since they provide a broad representation 

of potential exposures and because they include age groups that are commonly shown 

to be the most highly exposed in single-chemical assessments. Details regarding 

estimated exposures of other age groups are presented in the appendices to this report. 

During the period since the issuance of the preliminary NMC CRA in August 2005, 

the Agency has further improved and refined its assessment of the cumulative risks 

associated with the NMC pesticides. These refinements include incorporating the most 

recent food residue data by including pesticide residue data through 2006 from USDA’s 

PDP Program and updating the assessment to reflect individual risk mitigation 

measures and other use pattern changes for individual NMC pesticides. Specifically, 

during this period, the Agency has imposed risk reduction measures on some of the 

major contributors to carbamate cumulative risk. The risk estimates presented in the 

revised NMC CRA reflect the risk mitigation measures taken on individual carbamates 

since FQPA was signed into law in August 1996. In general, EPA’s risk estimates 

contained in this CRA reflect mitigation measures that EPA determined to be warranted 

based on its assessment of the single chemical’s risks. Since the preliminary 

assessment, the Agency has received a request for voluntary cancellation for methomyl 

on grapes and strawberries, has determined that carbofuran is ineligible for 

reregistration, and will implement certain label restrictions for aldicarb that will increase 

drinking water well set-backs in the southeastern coastal plains when certain criteria are 

triggered. Therefore, these uses (and exposures) are not included and the aldicarb 

label restrictions have been accounted for in the revised NMC CRA. 

In evaluating exposure through the remaining uses on food, OPP concludes that a 

few uses of NMC pesticides on food crops generally play a larger role in contributing to 

the cumulative risks of the NMC pesticides. These include use of aldicarb on potato; 

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carbaryl on peach and strawberry; and methomyl on cantaloupe, watermelon, 

peach, spinach, and strawberry. However, evaluation of the total risk from exposure to 

NMCs in foods indicated that the cumulative MOEs from exposure to NMCs do not raise 

a concern. Specifically, the target MOE of 10 is reached at the 99.848th and 99.870th 

percentiles of exposure for the most highly exposed age groups, children 1-2 and 

children 3-5 years old, respectively. These percentiles are not considered meaningfully 

different from the 99.9th percentile. Associated MOEs range from 7.9 for the most 

exposed subgroup (children 1-2) to 42 for adults 20-49. 

When developing any risk assessment, assumptions must be made in areas 

where data are not available. In the revised NMC CRA, the Agency has made health 

protective assumptions in its baseline analysis, particularly with regard to the years of 

PDP data which are used (for which it used all years of PDP data except in cases 

where use patterns have changed or will change),the use of a 10x inter-species 

extrapolation factor for those NMCs without human data, and summing exposures over 

a 24-hour period. In an effort to characterize and understand the MOEs estimated in 

this assessment, four sensitivity analyses were performed by the Agency to evaluate 

the degree to which key areas of the risk assessment may under- or over-estimate 

cumulative risk. The sensitivity analyses demonstrate that the Agency has not underestimated exposures through food and associated risks to any significant degree since 

these sensitivity analyses result in only small changes in the percentile at which the 

target MOE of 10 is reached. The results of the sensitivity analyses using the most 

recent PDP data and inter-species factors of 3x instead of the standard 10x for certain 

pesticides provide added certainty that risks are below the Agency’s level of concern. 

Residential: 

Applications of NMC pesticides in and around homes, schools, offices, and other 

public areas may result in potential exposure via the oral (due to hand-to-mouth activity 

by children), dermal, and inhalation routes. There are three NMC pesticides with 

currently registered residential uses considered as part of the revised NMC CRA in the 

residential/non-occupational exposure pathway assessment. The residential uses 

considered in this assessment include the carbaryl uses on lawns, golf courses, fruit 

trees, and vegetable and ornamental gardens; the methiocarb snail and slug bait use; 

and the carbaryl and propoxur pet collar uses. In addition to the uses listed above, the 

preliminary NMC CRA also included an assessment of indoor spray uses of propoxur 

(crack and crevice). Since the preliminary assessment, the Agency has received a 

request for voluntary cancellation of all propoxur indoor spray uses that may result in 

non-occupational exposure for children. Therefore, these uses are not included in the 

revised NMC CRA. 

Another notable change since issuance of the preliminary NMC CRA is the 

revision of the methodology used to assess children’s hand-to-mouth exposure. The 

non-dietary ingestion pathway was the least refined of the residential exposure 

pathways modeled in the preliminary NMC CRA. The refined methodology used in this 

revised assessment is based on recommendations from the August 2005 FIFRA SAP, 

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and addresses limitations in the non-dietary oral pathway by modifying the 

probabilistic hand-to-mouth algorithm. This modified algorithm is a product of a 

collaborative effort between OPP scientists and the developers of the SHEDS 

(Stochastic Human Exposure and Dose Simulation) and CARES (Cumulative and 

Aggregate Exposure System) models. 

For the residential/non-occupational exposure pathway, several reliable data 

sources were used to define how pesticides are used, how quickly the residues 

dissipate, how people may come into contact with pesticides (e.g., via dermal or 

inhalation exposure), and the length of time people might be exposed based on certain 

activities (e.g., playing on a treated lawn). As with the drinking water assessment (see 

below), the residential exposure assessment considers seasonal applications and 

timing as well as regional differences. In the case of regional differences, the revised 

NMC CRA considered the Southeast Region of the United States. Due to longer 

periods of pesticide use, this assessment provides a worst case estimate of exposure. 

The results of the residential risk assessment indicate that remaining residential 

uses of NMCs -- as borne out by the analyses here -- are below OPP’s level of concern 

for all subpopulations. 

Drinking Water: 

The drinking water assessment focuses on areas where combined NMC exposure 

is likely to be among the highest within each region as a result of total NMC usage and 

vulnerability of drinking water sources. This analysis is based on a probabilistic 

modeling approach that considers the full range of drinking water consumption and 

concentration data and not single high-end estimates. EPA estimated NMC exposures 

in drinking water to individuals in the CRA for both ground water and surface water 

sources of drinking water in each of three regions. The regional drinking water 

exposure assessments represent exposures from vulnerable drinking water sources 

resulting from typical NMC usage and reflect seasonal variations as well as regional 

variations in cropping and NMC pesticide use. Each regional assessment focuses on 

areas where combined NMC exposure is likely to be among the highest within the 

region as a result of total NMC usage, adjusted for relative potencies, and vulnerability 

of the drinking water sources. For ground water, private wells extending through highly 

permeable soil and vadose zone materials into shallow, acidic ground water are 

expected to be most vulnerable. For surface water, drinking water reservoirs in small, 

predominantly agricultural watersheds are likely to be most vulnerable. The cooccurrence of NMC residues in water is estimated primarily from modeling since 

sufficient monitoring data are not available to be the sole basis for the assessment. 

However, monitoring data are used to corroborate the modeling results and have 

helped confirm locations of potentially vulnerable drinking water sources. 

In most of the country, NMC residues in drinking water sources are at levels that 

are not likely to contribute substantially to the multi-pathway cumulative exposure. 

Estimated NMC exposures from surface water sources of drinking water resulted in 

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MOEs well above 10. For most ground water sources of drinking water, NMC 

exposures were similarly low. Shallow private wells extending through highly 

permeable soils into shallow, acidic ground water represent what the Agency believes 

to be the most vulnerable drinking water sources for the NMCs based on available 

monitoring, current use patterns, and known soil and hydrologic conditions. Those 

instances where NMC concentrations resulted in MOEs of less than 10 are being 

addressed with mitigation measures in the single-chemical assessments – an increase 

in the well setback distance from 300 feet to 500 feet for aldicarb use on peanuts in the 

southern portion of the Coastal Plain and a notice of intent to cancel all domestic 

carbofuran uses. With these mitigation measures, NMC exposures from drinking water 

result in MOEs greater than 10. 

Combined Pathway (Cumulative) Assessment: 

EPA also evaluated total MOEs for all three pathways (food + water + residential) 

simultaneously. Evaluating exposures is significantly more complex when the analyses 

address the simultaneous exposures to more than one pesticide and when distributional 

inputs derived from data from surveys and monitoring studies – as opposed to default 

assumptions or point estimates – are used. The detailed multi-pathway graphical 

outputs presented in Part III of this report reflect individual and combined pathway 

MOEs at multiple percentiles of exposure over the course of an entire year and allow indepth analysis of interactions of data sets to evaluate potential risk concerns and 

identify the sources of exposures. The graphical outputs improve the ability to interpret 

the complete risk picture. Based on the simultaneous evaluation of all three exposure 

pathways and their associated routes using the Calendex software, the MOEs at the 

99.9th percentile are approximately 8 or greater for all populations. Generally, 

exposures through the food pathway dominate total MOEs, with residential exposures 

less throughout most of the year. Although still substantially less than exposures 

through food, dermal exposures from lawn uses of carbaryl dominate the residential 

pathway. Exposures through drinking water exposures are smaller than exposures 

through both the food and residential pathways with MOEs exceeding 15 for all 

scenarios. 

Conclusion: 

The Agency has developed a highly refined and complex cumulative risk 

assessment for the NMCs that represents the state of the science regarding existing 

hazard and exposure data and the models and approaches used. Interpretation of the 

risk estimates presented in this revised NMC CRA depends upon the synthesis and 

processing of a vast body of data on hazard and exposures. No single value in the 

assessment should be used to independently arrive at the interpretation of the risk 

estimates or results. EPA continues to have confidence -- as demonstrated by this 

assessment -- in the overall safety of our food supply. 

Sensitivity analyses performed by the Agency were designed to evaluate the 

degree to which key areas of the risk assessment may or may not under- or overES - Page 10 of 277 
estimate the cumulative risk in an effort to characterize and understand the MOEs 

estimated in this assessment. The sensitivity analyses demonstrate that the Agency 

has not under-estimated exposures and associated risks. Also, the Agency has elected 

to use 10% inhibition in brain AChE as the response level for the RPFs and PoDs. The 

10% response level is health protective in that no functional or behavioral effects have 

been noted at or below this level in adult or juvenile animals. Thus the 10% response 

level provides a point where functional or behavioral neurotoxicity is not expected. 

The Agency has undertaken extensive risk mitigation and risk reduction efforts 

over the last several years for many NMCs through the single-chemical aggregate risk 

assessments and notes that the risk mitigation efforts of the past several years have 

significantly reduced risk from exposures to the NMCs through food and drinking water 

and from residential use in the U.S. Based on these efforts, the cumulative risks from 

food, water, and residential exposure to NMCs do not exceed the Agency’s level of 

concern. Taking into account these reductions and acknowledging that several key 

assumptions are designed to minimize the potential for this cumulative assessment to 

underestimate exposure and risk, the Agency concludes that -- based on the results of 

the revised NMC CRA -- there is a reasonable certainty that no harm will result from 

exposure to the NMC pesticides covered by this assessment, taking into account the 

cumulative effects of such residues. Accordingly, the pesticide tolerances for the 

NMCs covered by this risk assessment are considered to be “safe” as defined in 

FFDCA section 408(b)(2)(A) and to be reassessed for purposes of FFDCA section 

408(g). 

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LIST OF ACRONYMS 

AChE Acetycholinesterase 

BMD Benchmark dose (or BMD10) 

BMDL Lower limit on the benchmark dose (or BMDL10) 

CAG Cumulative Assessment Group 

CARES Cumulative and Aggregate Risk Evaluation System 

CELs Comparative Effect Levels 

CFSAN Center for Food Safety and Applied Nutrition 

CGCM Center for Golf Course Management 

CHAD Consolidated Human Activity Database 

ChE Cholinesterase 

CMG Common Mechanism Group 

CNS Central Nervous System 

CRA Cumulative Risk Assessment 

CSFII USDA Continuing Survey of Food Intake by Individuals 

CWS Community Water Systems 

DEEM-FCID Dietary Exposure Evaluation Model 

DFR Dislodgeable Foliar Residue 

EFED Environmental Fate and Effects Division 

EFH Exposure Factors Handbook 

EPA Environmental Protection Agency 

FCID Food Commodity Intake Database 

FDA Food and Drug Administration 

FIFRA Federal Insecticide, Fungicide, Rodenticide Act 

FQPA Food Quality Protection Act 

FR Federal Register 

GoF Goodness of Fit 

HCl Hydrochloride 

HED Health Effects Division 

HSRB Human Studies Review Board 

IRED Interim Re-registration Eligibility Decision 

LCO Lawn Care Operator 

LN Lognormal 

LOAEL Lowest Observable Adverse Effect Level 

LOC Level of Concern 

LOD Limit of Detection 

LOQ Limit of Quantification 

MBS Market Basket Study 

MOE Margin of Exposure 

MRID Master Record Identification Number 

NASS National Agricultural Statistics Survey 

NHANES National Health and Nutrition and Examination Survey 

NHANES III Third National Health and Nutrition Examination Survey 

NAWQA USGS National Water-Quality Assessment Program 

NHEXAS National Human Exposure Assessment Survey 

NHGPUS National Home and Garden Pesticide Use Survey 

Page 12 of 277 
NMC N-Methyl Carbamate 

NMC CRA N-Methyl Carbamate Cumulative Risk Assessment 

NOAELs No-Observed-Adverse-Effect-Levels 

OPs Organophosphorus Pesticides 

OP CRA Organophosphorus Pesticide Cumulative Risk Assessment 

OPP EPA’s Office of Pesticide Programs 

ORETF Outdoor Residential Exposure Task Force 

ORD Office of Research and Development 

PBPK Physiologically Based Pharmacokinetic 

PCA Percent Crop Area 

PCO Pest Control Operator 

PCRA Preliminary Cumulative Risk Assessment 

PDP USDA’s Pesticide Data Program 

PoD Point of Departure 

PK Pharmacokinetic 

PNS Peripheral Nervous System 

PRZM-EXAMS Pesticide Root Zone Model- Exposure Analysis Modeling 

System 

RBC Red Blood Cell 

RED Re-registration Eligibility Decision 

REJV Residential Exposure Joint Venture 

RPF Relative Potency Factor 

RTU Ready-to-Use 

SAP Scientific Advisory Panel 

SHEDS Stochastic Human Exposure and Dose Simulation 

SLN Special Local Need 

SOP Standard Operating Procedure 

TC Transfer Coefficient 

TDS Total Diet Study 

TTR Turf Transferable Residues 

UE Unit Exposure 

USDA United States Department of Agriculture 

USEPA United States Environmental Protection Agency 

WOE Weight of the Evidence 

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TABLE OF CONTENTS

TECHNICAL EXECUTIVE SUMMARY .................................................................................................... 2

I. NMC CUMULATIVE UPDATE .......................................................................................................... 21

A. INTRODUCTION................................................................................................................................ 21

Background...................................................................................................................................................... 21

B. HAZARD RELATIVE POTENCY FACTORS.......................................................................................... 27

1. Introduction ............................................................................................................................... 27

2. Endpoints and Toxicology Studies .............................................................................................28

3. Determination of Toxic Potency ................................................................................................33

a. Empirical Modeling: Dose-Time Response Model and Benchmark Dose Estimation ...............................34

i. Dose-Time Response Model .................................................................................................................34

ii. Statistical Methodology.........................................................................................................................37

b. Results: Benchmark Dose and Potency Estimation ...................................................................................39

c. Results: Half Life Time to Recovery.........................................................................................................44

4. Selection of Relative Potency Factors: Brain ChE Inhibition .................................................. 45

5. Selection of the Index Chemical (Oxamyl)................................................................................. 46

a. Candidates for the Index Chemical.............................................................................................................46

b. Description of the Oxamyl Database ..........................................................................................................46

6. Relative Potency Factors for the Revised Cumulative Risk Assessment of the N-Methyl 

Carbamates 48

7. Intra-species Variability, Inter-species Extrapolation, and FQPA 10X Safety Factors............49

a. Inter-species Extrapolation Factor in the revised NMC CRA.....................................................................49

b. FQPA Safety Factor ...................................................................................................................................50

i. Background ...........................................................................................................................................50

8. Incorporation of Uncertainty/Extrapolation Factors and the Target Margin of Exposure .......54

9. Dose Additivity........................................................................................................................... 55

10. Summary .................................................................................................................................... 56

C. CUMULATIVE RISK FROM PESTICIDES IN FOODS ............................................................................. 58

1. Food Consumption Data............................................................................................................ 58

2. Pesticide Residue Data .............................................................................................................. 60

a. USDA-PDP ................................................................................................................................................60

b. NMC Market Basket Survey ......................................................................................................................61

c. FDA-CFSAN Pesticide Residue Monitoring Program ...............................................................................61

d. FDA-CFSAN Total Diet Study ..................................................................................................................62

3. NMC Pesticides Included in the Food Risk Assessment ............................................................ 63

4. Food Commodities Included in the Food Risk Assessment........................................................67

5. Method of Estimation of Cumulative Food Risk ........................................................................ 70

a. Overview of Single-Chemical Dietary Risk Assessment Process...............................................................70

b. NMC Food Residue Database ....................................................................................................................71

c. Manipulation of Residue Data for Exposure Assessment...........................................................................73

d. Assumptions ...............................................................................................................................................74

6. Estimation of Acute Exposure Using DEEM-FCIDTM Software................................................77

7. Results........................................................................................................................................ 77

8. Summary .................................................................................................................................... 81

D. RESIDENTIAL NMC CUMULATIVE RISK .......................................................................................... 83

1. Introduction ............................................................................................................................... 83

2. Scope of Regional Assessments.................................................................................................. 84

3. Residential Scenarios................................................................................................................. 85

a. Lawn Care ..................................................................................................................................................85

b. Vegetable Gardens......................................................................................................................................86

c. Ornamentals ...............................................................................................................................................86

d . Fruit Trees ..................................................................................................................................................87

e. Pet Collars ..................................................................................................................................................87

f. Golf Course ................................................................................................................................................88

4. Exposure Routes/Scenarios Considered ....................................................................................88

Page 14 of 277 
a. Oral Route of Exposure ..............................................................................................................................90

i. Modeling the Non-Dietary Ingestion Pathway ......................................................................................91

b. Dermal Route of Exposure .........................................................................................................................94

c. Inhalation Route of Exposure .....................................................................................................................94

5. Data Sources.............................................................................................................................. 95

 pesticide use data; .................................................................................................................................95

 residue concentration and dissipation/decay data;.................................................................................95

 exposure contact factor data..................................................................................................................95

a. Pesticide Use Data......................................................................................................................................95

i. Broadcast Lawn Scenarios ....................................................................................................................96

ii. Pet Collar Scenarios ..............................................................................................................................96

b. Residue Concentration Data .......................................................................................................................96

c. Exposure Factor (Contact) Data .................................................................................................................97

6. Exposure Scenarios.................................................................................................................... 97

a. Lawn Care Exposure Scenarios..................................................................................................................97

i. Lawn Applicator Exposure....................................................................................................................97

ii. Lawn Post-Application Dermal Exposure.............................................................................................99

iii. Lawn Non-Dietary Hand-to-Mouth Exposure....................................................................................102

b. Vegetable Garden Exposure Scenarios.....................................................................................................103

i. Applicator Exposure............................................................................................................................103

ii. Post-Application Dermal Exposure.....................................................................................................105

c. Ornamental Plants and Shrubs Exposure Scenarios..................................................................................105

i. Applicator Exposure............................................................................................................................106

ii. Post-Application Dermal Exposure.....................................................................................................106

d. Fruit Tree Exposure Scenarios..................................................................................................................107

i. Applicator Exposure............................................................................................................................107

ii. Post-Application Dermal Exposure.....................................................................................................108

e. Ornamental Garden - Snail and Slug Bait Scenarios ................................................................................108

i. Applicator Exposure............................................................................................................................109

ii. Post-Application Exposure..................................................................................................................109

f. Pet Collar Scenarios .................................................................................................................................110

i. Applicator Exposure............................................................................................................................110

ii. Post-Application Dermal Exposure.....................................................................................................110

iii. Oral (Hand-to-Mouth) Post-Application Exposure ............................................................................111

g. Golf Course Scenario ...............................................................................................................................112

i. Post-Application Dermal Exposure.....................................................................................................112

7. Risk .......................................................................................................................................... 113

8. Summary .................................................................................................................................. 113

E. CUMULATIVE RISK FROM NMC PESTICIDES IN DRINKING WATER ............................................... 129

1. Introduction ............................................................................................................................. 129

2. Problem Formulation .............................................................................................................. 130

a. Drinking Water Exposure Needs for the NMC Cumulative Assessment..................................................130

b. Nature of NMC Exposure in Drinking Water Sources .............................................................................131

c. Summary ..................................................................................................................................................136

3. Conceptual Model.................................................................................................................... 136

a. Regional Screening Approach for Vulnerable Sources of Drinking Water ..............................................137

b. Conceptual Model for Surface Water Sources of Drinking Water............................................................138

c. Conceptual Model for Vulnerable Ground Water Sources of Drinking Water.........................................140

4. Analysis Plan ........................................................................................................................... 142

a. NMC Properties........................................................................................................................................142

b. Identifying Regional Exposure Scenarios.................................................................................................143

c. Regional Usage.........................................................................................................................................145

d . Surface Water Exposure Assessment .......................................................................................................146

e. Ground Water Exposure Assessment .......................................................................................................148

5. NMC Concentrations in Surface Water Sources of Drinking Water........................................ 149

a. Individual NMC Levels in Surface Water ................................................................................................149

b. Cumulative NMC Levels in Surface Water..............................................................................................151

c. Spatial Extent of NMC Exposures in Surface Water................................................................................152

d. Sensitivity Analysis: Carbofuran in Surface Water .................................................................................154

6. NMC Concentrations in Ground Water Sources of Drinking Water ....................................... 156

a. Individual NMC Levels in Ground Water ................................................................................................157

Page 15 of 277 
b.Cumulative NMC Levels in Ground Water...................................................................................................................158

c.Spatial Extent of High NMC Exposures in Ground Water............................................................................................160

d.Sensitivity Analysis: Carbofuran in Ground Water ......................................................................................................162

7. Summary .................................................................................................................................. 166

F. THE MULTI-PATHWAY CUMULATIVE ASSESSMENT ...................................................................... 167

1. Basic Concepts......................................................................................................................... 167

2. Framing the Population-Based Assessment............................................................................. 168

3. Interpreting the Outputs........................................................................................................... 170

4. Attributes of the Revised N-Methyl Carbamate Cumulative Risk Assessment ......................... 170

a. Children, 1-2 years, Georgia Coastal Plain Ground Water.......................................................................172

b. Children 3-5 years, Georgia Coastal Plain Ground Water........................................................................173

c. Adults, 20-49 years, Georgia Coastal Plain Ground Water ......................................................................174

d. Adults, 50+ years, Georgia Coastal Plain Ground Water .........................................................................174

e. Children, 1-2 years, Florida Citrus Ground Water....................................................................................175

f. Children 3-5 years, Florida Citrus Ground Water.....................................................................................175

g. Adults, 20-49 years, Florida Citrus Ground Water...................................................................................176

h. Adults, 50+ years, Florida Citrus Ground Water......................................................................................177

i. Children, 1-2 years, North Carolina Coastal Plains Ground Water ..........................................................177

j. Children 3-5 years, North Carolina Coastal Plains Ground Water ...........................................................178

k. Adults, 20-49 years, North Carolina Coastal Plains Ground Water..........................................................179

l. Adults, 50+ years, North Carolina Coastal Plains Ground Water.............................................................179

G. RISK CHARACTERIZATION............................................................................................................. 181

1. Introduction ............................................................................................................................. 181

2. Hazard and Dose-Response Assessment.................................................................................. 181

a. Acetylcholinesterase Inhibition: Data Quality & Common Effect ...........................................................182

b. Dose-Response Analysis ..........................................................................................................................183

c. Selecting the Index Chemical ...................................................................................................................184

d. Assumption of Dose-Additivity................................................................................................................184

3. Food Assessment...................................................................................................................... 185

a. Consumption Data....................................................................................................................................185

b. PDP Monitoring Data in the Assessment..................................................................................................186

c. Data Translation from PDP ......................................................................................................................187

d. Other Sources of Residue Data.................................................................................................................187

e. Impact of Regulatory Actions...................................................................................................................188

f. Impact of Assumptions: Sensitivity Analyses .........................................................................................189

i. Limit of Detection in PDP: Use of ‘zero’ assumption for non-detectable residues ............................190

ii. Use of Recent PDP Data Only ............................................................................................................192

iii. Summing food exposures over 24 hours ............................................................................................193

iv. Consideration of Chemical Specific Adjustment Factor Approach for the Inter-species Uncertainty Factor...........197

g. Model Outputs & Discussion ...................................................................................................................200

4. Residential Assessment ............................................................................................................ 203

a. Pesticide Use Data....................................................................................................................................204

b. Pesticide Residue and Exposure Contact Data .........................................................................................204

i. Dermal Exposure.................................................................................................................................204

ii. Non-dietary ingestion..........................................................................................................................207

5. Drinking Water Assessment ..................................................................................................... 213

a. Ground Water Exposure ...........................................................................................................................213

i. Depth to ground water.........................................................................................................................214

ii. Setback distances between the well and the treated field ....................................................................215

iii. Hydraulic conductivity of the soil/vadose zone .................................................................................216

iv. Soil/vadose zone and ground water pH ..............................................................................................216

v. Other factors........................................................................................................................................216

b. Surface Water Exposure ...........................................................................................................................217

c. Usage Information....................................................................................................................................218

d. Timing of Exposure..................................................................................................................................219

6. FQPA 10X Factor for the Protection of Infants and Children................................................. 220

7. Physiologically-Based Pharmacokinetic Models..................................................................... 221

8. Conclusions.............................................................................................................................. 222

H. REFERENCES.................................................................................................................................. 227

Page 16 of 277 
II. APPENDICES ................................................................................................................................. 248

A. SUMMARY OF RISK MITIGATION FOR INDIVIDUAL N-METHYL CARBAMATES .............................. 248

B. HAZARD ........................................................................................................................................ 254

1. Data Spreadsheets of the NMC Pesticides............................................................................... 254

2. Dose-Response modeling of the NMC pesticides..................................................................... 255

3. N-M-Carbamate Dose Response.............................................................................................. 256

4. R-packages with file names...................................................................................................... 257

5. Summary AChE protocol evaluations, mixture experiments, motor activity measurements.... 258

6. Physiologically-Based Pharmacokinetic Modeling for the NMC CRA.................................... 259

C. FOOD............................................................................................................................................. 260

1. The Sources of Residue Inputs for the Assessment of the Cumulative Dietary Exposure to NMethyl Carbmate Pesticides on Foods...................................................................................................................... 260

2. Summary of PDP Residue Analyses of N-Methyl Carbamate Pesticides on Food Commodities 

Included in Revised NMC CRA ................................................................................................................................. 261

3. Processing Factors Used to Estimate Residues of N-Methyl Carbamate Pesticides in Food

Forms* 262

4. Translation of Residue Source Data to FCID Food Forms ..................................................... 263

5. Summary of Residue Distribution Inputs to DEEM-FCID for the Revised NMC CRA............ 264

6. Analysis of Chemicals and Foods in the Upper Portion of the Revised NMC CRA. Exposure 

Distribution for Children 1-2 Years Old ................................................................................................................... 265

7. Co-Occurrence of N-Methyl Carbamate Pesticides on PDP Samples, 1994-2006 ................. 266

8. Comparison of DEEM-FCID version 2.03 and Lifeline version 4.30 Exposure and Risk 

Estimates through the Food Pathway Only............................................................................................................... 267

D. RESIDENTIAL................................................................................................................................. 268

1. Residential Pesticide Use Inputs from REJV Survey Data....................................................... 268

2. Residential Exposure Scenarios Appendix............................................................................... 269

E. DRINKING WATER ......................................................................................................................... 270

1. Summary of Surface Water Monitoring Data for NMC Pesticides .......................................... 270

E-2 SUMMARY OF GROUND WATER MONITORING DATA FOR NMC PESTICIDES ........................................... 271

E-3 DRINKING WATER TREATMENT EFFECTS ON N-METHYL CARBAMATE PESTICIDES................................. 272

E-4 N-METHYL CARBAMATE USAGE ESTIMATES ........................................................................................... 273

E-5 CHEMICAL-SPECIFIC FATE AND TRANSPORT PROPERTIES USED FOR THE WATER EXPOSURE MODELS .. 274

E-6 NMC SURFACE WATER EXPOSURE ASSESSMENT METHODS ................................................................... 275

E-7 NMC GROUND WATER EXPOSURE ASSESSMENT METHODS................................................................... 276

III. MULTI-PATHWAY GRAPHS...................................................................................................... 277

Page 17 of 277 
Tables 

Table ES -1. Summary Information Regarding the NMC Pesticides and the Uses, and 

Pathways Included in the revised NMC Cumulative Risk Assessment .......................... 6

Table I.A-1. Summary Information Regarding the NMC Pesticides and the Uses, Routes 

Table I.B-2. List of toxicity studies used in the Revised N-Methyl Carbamate Risk 

Table I.B-3. Oral BMD10s and BMDL10s from rat brain and RBC ChE inhibition for the 

Table I.B-4. Dermal BMD10s, BMDL10s, and potency estimates from rat and rabbit brain 

Table I.B-5. Inhalation BMD10s, BMDL10s, and potency estimates from rat brain and 

RBC ChE inhibition for the N-methyl carbamates with residential/non-occupational uses44

Table I.B-7. Oral, dermal, and inhalation brain BMD10s and BMDL10s for oxamyl, the 

Table I.B-9. Inter-species uncertainty factors and corresponding rat and human 

Table I.B-10. Dose-response and recovery half-life estimates in juvenile and adult rats 

Table I.B-12. Adjusted oral relative potency factors for children and adults based on 

Table I.B-13. Adjusted dermal relative potency factors for children and adults based on 

Table I.B-14. Adjusted inhalation relative potency factors for children and adults based 

Table I.C-3. Summary of Probabilistic Analysis of Distribution of the Cumulative Dietary 

Table I.D-2. Lognormal Distributions of Unit Exposures Used for Carbaryl Lawn Care 

Table I.D-3. Lognormal Distributions of Unit Exposures Used for Carbaryl Garden, Fruit 

and Pathways Included in the NMC Cumulative Risk Assessment............................... 22

Table I.B-1. Test guidelines/studies that contain evaluations for ChE activity. ............ 30

Assessment. ................................................................................................................. 32

N-methyl carbamates.................................................................................................... 41

and RBC ChE inhibition for the N-methyl carbamates with residential/non-occupational 

uses1 ............................................................................................................................. 43

Table I.B-6. Half-life for time to recovery for adult rats from oral studies for brain ChE 

inhibition for the N-methyl carbamates1 ........................................................................ 45

index chemical .............................................................................................................. 48

Table I.B-8. Relative potency factors for oral, dermal, and inhalation routes1.............. 48

BMD10s and BMDL10s ................................................................................................... 50

from comparative cholinesterase studies...................................................................... 53

Table I.B-11. FQPA safety factors for the revised NMC CRA1...................................... 53

inter-species and FQPA specific factors ....................................................................... 54

inter-species and FQPA specific factors ....................................................................... 55

on inter-species and FQPA specific factors .................................................................. 55

Table I.C-1. N-methyl Carbamatesa and RPFs ............................................................ 63

Table I.C-2. Crop Translations for Pesticide Monitoring Data ...................................... 69

Exposures and Risk from Use of N-Methyl Carbamate Chemicals on Food Cropsa ..... 77

Table I.C-4. Relative Exposure Contribution from Foods for Children 1 to 2 Years Old 

(At 99.8th Percentile of Exposure and Above) ............................................................... 78

Table I.D-1. Specific Exposure Routes and Pathways/Scenarios ................................. 89

Scenarios...................................................................................................................... 98

Tree, and Ornamental Scenarios ................................................................................ 104

Table I.D-4. Summary of NMC Residental Exposure Scenarios ................................ 115

Table I.E-1. NMC use patterns and availability of national monitoring data ................ 131

Page 18 of 277 
Table I.E-2. Summary of carbamate detections in the USGS NAWQA study, 1991­

Table I.E-4. Regional drinking water exposure sites and dominant NMC pesticide uses144

Table I.E-5. Estimated peak concentrations for NMC residues for the regional surface 

Table I.E-6. Percentile concentrations for estimated NMC cumulative distributions in 

the surface water scenario sites (30-year period), adjusted for relative potency, interTable I.E-7. Estimated peak concentrations for carbofuran residues for the regional 

Table I.E-8. Percentile concentrations for estimated NMC cumulative distributions with 

and without carbofuran in the surface water scenario sites (30-year period), adjusted for 

Table I.E-9. Estimated concentrations for NMC residues for the regional ground water 

Table I.E-10. Percentile concentrations for estimated NMC cumulative distributions in 

the ground water scenario sites adjusted for relative potency and using safety factors 

Table I.E-11. Estimated concentrations for NMC and carbofuran for regional ground 

Table I.E-12. Percentile concentrations for estimated NMC cumulative distributions in 

the ground water scenario sites adjusted for relative potency and using safety factors 

Table I.G-1. Sensitivity Analyses for NMC Cumulative Food Assessment: Limit of 

Table I.G-2. Sensitivity Analyses NMC Cumulative Food Assessment: Recent PDP 

Table I.G-3. Sensitivity Analyses NMC Cumulative Food Assessment: 24 Hour Food 

Table I.G-4. Sensitivity Analyses NMC Cumulative Food Assessment: CSAF Approach 

Table I.G-7. Input Parameters Used in the Exposure Models: Bias, Assumptions, 

2001 (provisional data published by USGS in 2003)................................................... 133

Table I.E-3. Summary of N-methyl carbamate fate and transport properties ............. 142

water drinking water scenarios (30-year period) ......................................................... 150

species and FQPA safety factors for children ............................................................. 152

surface water drinking water scenarios (30-year period) ............................................ 154

relative potency, inter-species and FQPA safety factors for children .......................... 155

scenarios (25-year period) for ground water at 30 feet ............................................... 157

for children .................................................................................................................. 159

water scenarios (25-year period) for ground water at 30 feet ..................................... 162

for children .................................................................................................................. 165

Detection Assumptiona................................................................................................ 191

Data Assumption......................................................................................................... 193

Summation.................................................................................................................. 197

for Inter-species UF .................................................................................................... 199

Table I.G-5. Summary of NMC Cumulative Food Assessment: Baseline Estimates.. 200

Table I.G-6. Summary of NMC Cumulative Food Assessment: Sensitivity Analyses. 201

Uncertainties, and Strengths....................................................................................... 209

Page 19 of 277 
Table of Figures 

Figure I.B-1. Plot of BMD10s and the 95% confidence limits for rat brain ChE inhibition 

for the N-methyl carbamates......................................................................................... 41

Figure I.B-3. Plot of brain ChE measured in a seven chemical mixture of N-methyl 

Figure I.C-1. Relative Contribution of Crop/Chemical Pairs to Top 0.2 Percentile of 

Figure I.C-2. Relative Contribution of Crop/Chemical Pairs to Top 0.2 Percentile of 

Figure I.E-1. NMC CRA regions for drinking water exposure assessment showing high 

Figure I.E-2. Conceptual model for surface water sources of drinking water illustrating 

Figure I.E-3. Depiction of general ground water scenario concept used for estimating 

Figure I.E-4. Location of surface water intakes (blue dots) in relation to relative NMC 

pesticide usage (high use areas in dark orange) in the southeastern/south-central U.S.153

Figure I.E-5. Cumulative margins of exposure for drinking water from private wells in 

Figure I.E-6. Extent of high leaching potential soils in NMC use areas in the 

Figure I.E-7. Cumulative margins of exposure for drinking water from private wells in 

Figure I.F-1. Three-dimensional plot of the total MOE by day of the year and percentile 

Figure I.G-1. Number of Eating Events Contributing to Exposures at 99.8+ Percentile 

Figure I.G-2. Number of Eating Events Contributing to Exposures at 99.8+ Percentile 

Figure I.B-2. Plot of BMD10s and the 95% confidence limits for rat RBC ChE inhibition 

for the N-methyl carbamates1 ....................................................................................... 42

carbamates ................................................................................................................... 55

Cumulative Distribution for Children 1-2 ....................................................................... 79

Cumulative Distribution for Children 3-5 ....................................................................... 79

Figure I.D-1. Pesticide Cumulative Assessment Regions ............................................ 85

NMC use areas and regional drinking water exposure sites ....................................... 137

how multiple NMC uses are proportioned in the watershed........................................ 139

pesticide concentrations in drinking water .................................................................. 141

high leaching potential soils in the southern coastal plain (GA Peanuts), infants ....... 160

Southeastern U.S........................................................................................................ 162

high leaching potential scenarios, children 1-2 years old............................................ 165

of exposure ................................................................................................................. 169

for Children 1-2 ........................................................................................................... 195

for Children 3-5 ........................................................................................................... 195

Page 20 of 277 
I. NMC Cumulative Update 

A. Introduction 

Background 

The Food Quality Protection Act (FQPA) of 1996 significantly amended the 

Federal Insecticide, Fungicide, and Rodenticide Act (FIFRA) and the Federal Food, 

Drug, and Cosmetic Act (FFDCA). One of the major changes imposed by FQPA was to 

require EPA to consider the cumulative effects of chemicals with a common mechanism 

of toxicity in its tolerance reassessment decisions. 

In 2001, EPA concluded that the N-methyl carbamate (NMC) pesticides share a 

common mechanism of toxicity. This common mechanism group (CMG) was 

established based on the shared structural characteristics and similarity and their 

shared ability to inhibit acetylcholinesterase (AChE) by carbamylation of the serine 

hydroxyl group located in the active site of the enzyme (USEPA, 2001a). For this group 

of pesticides, recovery typically occurs rapidly (minutes to hours) following maximal 

inhibition of cholinesterase (ChE). In a February 4, 2004 Federal Register notice, EPA 

announced the members of the Common Assessment Group (CAG) (FR Vol.69, No.23, 

p. 5340-5344). These ten carbamates all display ChE-inhibiting activity, have current 

active registrations, and are expected to contribute to the carbamate cumulative risk 

through quantitatively meaningful exposure scenarios. The ten members of the CAG 

for the N-methyl carbamates and those chemicals which are included in the quantitative 

cumulative risk assessment are listed in ive risk assessment. 

Section 1.A - Page 21 of 277 
Table I.A. Summary Information Regarding the NMC Pesticides and the Uses, Routes 

and Pathways Included in the NMC Cumulative Risk Assessment 

Pesticide Pesticide 

Uses 

Pesticide Pathways Pesticide Routes 

Food Drinking 

Water 

Residential Oral Dermal Inhalation 

Ag Crops X X X 

Lawn X X X X 

Garden X X X 

Ornamentals X X X 

Fruit Trees X X X 

Carbaryl Pet Collar X X X 

Golfer 

Exposure 

X X 

Aldicarb Ag Crops X X X 

Oxamyl Ag Crops X X X 

Formetanate 

HCl Ag Crops X X X 

Methomyl Ag Crops X X X 

Carbofuran Ag Crops X X X 

Propoxur 

Food Uses X X 

Pet Collar X X X 

Methiocarb Ag Crops X X 

Ornamental X X X 

Thiodicarb Ag Crops X X X 

Pirimicarb Ag Crops X X 

To meet the requirements of FQPA, EPA developed methodologies for 

conducting cumulative risk assessments. As part of this process, EPA 

consulted with the FIFRA Scientific Advisory Panel (SAP) to obtain expert 

review, advice, and recommendations at each major step in the development of 

the underlying methodologies for cumulative risk assessments. EPA held 

numerous external peer-review meetings with the SAP and asked for comment 

on many issues, including its approaches to grouping chemicals based on a 

common mechanism of toxicity; Office of Pesticide Program’s (OPP) guidance 

for conducting cumulative risk assessment; methods and approaches for doseresponse and exposure assessment; and probabilistic exposure models for 

combining food, drinking water, and residential exposure pathways. In addition, 

the Agency also held numerous meetings with the FQPA Federal Advisory 

Committees TRAC (Tolerance Reassessment Advisory Committee) and 

CARAT (Committee to Advise on Reassessment and Transition), which were 

established under the Federal Advisory Committee Act (FACA). Various 

stakeholders including public interest groups, state agricultural agencies, 

pesticide industry representatives, growers, United States Department of 

Agriculture (USDA), and others were represented on these committees. In 

addition, numerous public technical briefings on each component of the 

cumulative methodology were held. In short, the Agency sought and received 

Section I.A – Page 22 of 277 
advice, comments, and recommendations on the methodologies and 

framework that were to guide the implementation of FQPA and tolerance 

reassessment. 

Based in part on the above consultations, OPP developed and published 

guidance on conducting cumulative risk assessments (“Guidance on 

Cumulative Risk Assessment of Pesticide Chemicals That Have a Common 

Mechanism of Toxicity”) which is available on EPA’s website at 

http://www.epa.gov/pesticides/trac/science/cumulative_guidance.pdf. This 

guidance has been reviewed by the FIFRA SAP and describes key principles 

for conducting these risk assessments. One such principle is the need to 

consider the time frame of both the exposure (e.g., When does exposure 

occur? What is the exposure duration?) and the toxic effect (e.g., What are the 

time-to-peak effects and the time to recovery? How quickly is the effect 

reversed?). Both should be adequately considered so that an individual's 

exposure is matched with relevant and appropriate toxicological values in terms 

of duration and timing. Inhibition of ChE caused by the N-methyl carbamates is 

followed by rapid recovery within minutes to hours. This rapid recovery is a 

unique characteristic of this group of pesticides and was considered and 

characterized as part of the risk assessment. Cumulative risk assessments 

should also account for temporal aspects of exposure, such as those related to 

the time of year during which applications resulting in exposures are likely to 

occur, the frequency of application, and the period of reapplication. Moreover, 

these assessments must appropriately consider age-dependent and 

demographic factors and patterns. The Agency’s approach to each of these 

challenges in the cumulative hazard, exposure, and risk assessment is 

described throughout the document. 

This cumulative assessment is intended to identify major sources of risk 

that could potentially accrue due to the use of a variety of pesticides which act 

through a common mechanism of toxicity. Regulatory decision making is based 

on the many detailed aspects of the single-chemical aggregate risk 

assessment. Because of the requirement that many data sets be combined into 

a single assessment, reducing the impact and likelihood of compounding 

conservative assumptions and over-estimation bias becomes very important in 

constructing the cumulative risk assessment. As a result, OPP has chosen to 

work with those data that most closely reflect likely exposures and not to 

incorporate those data that are inherently conservative by their nature (e.g., 

field trial data which incorporate maximum application rates and minimum preharvest intervals). These principles are fully described and laid out in the 

aforementioned guidance document. 

EPA previously released the “Estimation of Cumulative Risk from Nmethyl Carbamate Pesticides: Preliminary Assessment” in August 2005. During 

the period since the issuance of the preliminary cumulative risk assessment, the 

Agency has been working to further improve and refine its assessment of the 

cumulative risks associated with the NMC pesticides. These refinements 

Section I.A – Page 23 of 277 
include changes to: incorporate the most recent food residue data by 

including pesticide residue data through 2006 from USDA’s Pesticide Data 

Program; reflect the Agency’s review of new toxicity data in juvenile animals; 

and to incorporate human data for certain NMC pesticides. In addition, the 

Agency has updated the assessment to reflect individual risk mitigation 

measures and other use pattern changes for individual NMC pesticides since 

the preliminary NMC CRA was issued in August 2005. Specifically, during this 

period, the Agency imposed risk reduction measures on some of the major 

contributors to carbamate cumulative risk, as discussed below. The risk 

estimates presented in the revised NMC CRA reflect the risk mitigation 

measures taken on individual carbamates since FQPA was signed into law in 

August 1996. A table summarizing these mitigation measures is provided in 

Appendix II.A. In general, EPA’s risk estimates reflect risk mitigation measures 

that EPA determined to be warranted based on its assessment of the single 

chemical’s risks. For all of the risk mitigation measures that are reflected in this 

document, EPA has commenced the processes necessary to implement its 

selected risk mitigation, but may not yet have completed these processes. 

Having already determined that risk mitigation is warranted for the individual 

chemical, EPA has chosen to exclude it from this assessment to avoid any 

confusion that yet further mitigation might be warranted solely on that basis, 

either for the individual chemical or for other NMC chemicals. Rather, where 

the risks are adequately addressed by previously identified risk mitigation, it 

was considered to be unnecessary to confirm that here. To the extent that any 

risk mitigation measures are not subsequently implemented as envisioned in 

this assessment, the revised NMC CRA will be revised as necessary. The 

following summarizes the major mitigation actions that the Agency has recently 

or will be taking with respect to registration of uses which have been excluded 

from the revised NMC CRA: 

Carbofuran. In July 2006, the Agency issued its proposed decision to 

cancel all domestic uses of Carbofuran; only four import tolerances, 

(coffee, bananas, sugarcane, and rice) would remain. A Federal Register 

(FR) notice announcing this decision and soliciting public comments was 

published on August 30, 2006. 

Any cancellation hearing for EPA’s proposed decision on carbofuran 

would be scheduled to commence in 2008, which is after the issuance of 

this document. If all remaining uses of carbofuran are not cancelled after 

conclusion of a cancellation hearing, this assessment will be revised as 

necessary. 

Methomyl. The methomyl registrant submitted a letter requesting the 

voluntary cancellation of the strawberry use on January 4, 2007. A 

Federal Register notice announcing the receipt of this request to delete 

the methomyl strawberry use published on April 25, 2007 (72 FR 20541) 

(FRL-8125-6). The public comment period for this notice closes on 

October 22, 2007. 

Section I.A – Page 24 of 277 
A letter requesting voluntary cancellation of the use of methomyl on 

grapes was received from the registrant on September 14, 2007. A 

Federal Register notice announcing the receipt of this request will be 

published in October 2007. Based on these voluntary cancellations, the 

use of methomyl on grape and strawberry has been excluded from the Nmethyl carbamate cumulative risk assessment. 

Propoxur. In February 2007, the propoxur registrant submitted a letter 

requesting the voluntary cancellation of the all indoor spray uses that may 

result in non-occupational exposure for children. A Federal Register 

notice announcing this voluntary cancellation and soliciting public 

comments was published on April 25, 2007 (72 FR 20541) (FRL-8125-6). 

In July 2007, the Agency issued its Final Use Termination Order for 

Propoxur Residential Spray Use (EPA Registration Number 432-1288) for 

the use of propoxur, when formulated into a product that can be used as a 

spray on residential indoor use sites. The Agency has evaluated N-methyl 

Carbamate cumulative risks in a manner that excludes these crack and 

crevice-type residential uses so as to reflect the Agency’s final termination 

order. 

Aldicarb. In September 2007, EPA completed the Aldicarb Reregistration 

Eligibiility Decision (RED). The Agency identified potential human health 

risks of concern associated with the current registered uses of aldicarb 

from drinking water exposure, and potential environmental risks of 

concern to birds, mammals and fish. To reduce these potential exposures 

and to address current risks of concern, EPA -- in agreement with the 

technical registrant of aldicarb -- will implement certain label restrictions. 

To address groundwater contamination concerns, the Agency will increase 

drinking water well set-backs for applications to peanuts in the 

southeastern coastal plains when certain criteria are triggered. In 

addition, to reduce environmental concerns, the Agency will implement 

application rate reductions and restrictions, state limitations, label 

amendments, and cancellation of certain commodities. EPA is also 

requiring data to confirm the decisions presented in the Aldicarb RED 

which and will seek public comment on the decisions in the RED in 

October 2007. 

The current document is presented in three major parts: 

• Part I: Revised NMC Cumulative risk assessment 

• Parts II and III: Appendices which provide background material, 

additional graphs, and more technical and/or extensive details surrounding 

the analyses contained in Part I 

Section I.A – Page 25 of 277 
Part I is divided into eight chapters. Chapter A is this general 

introduction. The following chapter (I.B), presents the Hazard Assessment with 

specific discussion of the Relative Potency Factor approach and empirical 

dose-response and time course modeling used to estimate relative potency. 

The next three chapters (C, D, and E) focus on each of the major exposure 

pathways (food, residential, and drinking water, respectively), including a 

discussion of assumptions, data inputs, and interrelationships of exposure data. 

Each of these pathways has unique issues relating to availability of data, scale, 

and interpretation of results. Results of each aspect of the assessment are 

discussed in these chapters with particular attention given to how they reflect 

potential exposures to the population and what might be inferred with regard to 

significant exposure pathways/scenarios. Chapter F of the document examines 

the results of combining estimates of risk from all sources of exposure, in a 

multi-pathway, probabilistic cumulative assessment, and further discusses the 

interpretation of the outputs with respect to the most significant pathways and 

scenarios. The results in this chapter were generated by the DEEM/Calendex 

software. Chapter G of this document is a risk characterization, which further 

discusses and characterizes the inputs to the assessment as well as the 

resulting model exposure estimates. Chapter H of this document provides 

references for the material cited in Parts A through G. 

Section I.A – Page 26 of 277 
B. Hazard Relative Potency Factors 

1. Introduction 

OPP designated the NMC pesticides as a common mechanism group 

(USEPA, 2001a) based on the shared structural characteristics and similarities 

and their shared ability to inhibit AChE by carbamylation of the serine hydroxyl 

group located in the active site of the enzyme. Following maximal inhibition of 

cholinesterase, recovery typically occurs rapidly (minutes to hours). Pharmacokinetic data are only available for one NMC (i.e., carbaryl), Consequently, a 

multi-chemical, multi-pathway physiologically based pharmacokinetic (PBPK) 

model cannot be developed at this time for the NMC cumulative risk 

assessment (Appendix II.B.6). Therefore, the 2007 revised cumulative risk 

assessment relies on the relative potency factor (RPF) method for quantifying 

chemical potency. In the RPF approach, the toxic potency of each chemical is 

determined. A member of the cumulative assessment group (CAG) is selected 

as the index chemical which is used as the point of reference for standardizing 

the cholinesterase inhibiting potency of the other chemical members of the 

CAG. In the case of the NMC CRA, oxamyl is used as the index chemical. 

The FIFRA SAP supported the scientific approach employed in the NMC 

cumulative hazard in the February and August 2005 meetings. EPA has 

considered the comments collected from the SAP as well as the registrants’ 

error-only comment phase in July 2005 in the development of the current 

revised NMC CRA. The revised NMC CRA incorporates additional data 

available since the 2005 preliminary CRA in addition to uncertainty factors for 

the inter- and intra-species factor and FQPA 10X safety factor. Specifically, the 

Agency has included comparative cholinesterase data in juvenile (post-natal 

day 11 [PND 11] and PND17) and adult rats for six chemicals as well as 

cholinesterase inhibition and recovery data from human subjects for three 

chemcials. The comparative cholinesterase data are used here to inform the 

FQPA 10X factors while the cholinesterase data in human subjects has been 

used to form the inter-species factor in the revised CRA. It is noted that 

carbofuran has been ruled ineligible for reregistration and is undergoing the 

process of cancellation. However, for completeness and because tolerances 

for bananas, coffee, rice and sugarcane will continue for import purposes, the 

hazard chapter includes RPFs and uncertainty factor information for carbofuran. 

This cumulative hazard assessment represents the collaborative efforts of 

scientists from OPP and EPA’s National Health and Environmental Effects 

Research Laboratory (NHEERL) and National Center for Computational 

Toxicology (NCCT). The purpose of this hazard chapter is to describe EPA’s 

approach for: 

Section I.B – Page 27 of 277 
 Determination of the relative cholinesterase inhibiting potency and 

half-life to recovery used for each N-methyl carbamate in the CAG; 

 Selection of the index chemical used as the point of reference to 

standardize the potency of each N-methyl carbamate; 

 Establishment of a baseline or reference value (i.e., points of departure) 

used to estimate potential risk for the group for each route of interest; and 

 Identification of the intra-species, inter-species, and FQPA 10X safety 

factors used in this cumulative risk assessment. 

2. Endpoints and Toxicology Studies 

When using the RPF method and before the cumulative risk of exposure 

to the NMCs can be quantified, the relative toxic potency of each NMC must 

first be determined. The determination of relative toxic potency is calculated 

using a uniform basis of comparison, by using, to the extent possible, a 

common tissue, species, and sex for all the exposure routes of interest 

(USEPA, 2002a). NMCs exert their neurotoxicity by carbamylating the enzyme 

acetylcholinesterase (AChE) in both the central (brain) and peripheral nervous 

systems. Since cholinesterase (ChE) inhibition is the critical event in NMC 

toxicity, ChE inhibition provides the common endpoint for the revised NMC 

CRA. The available ChE activity measures provide a more uniform measure of 

toxicity compared to behavioral measures for performing cumulative risk 

assessment. Behavioral measures are often limited in terms of the scope of 

effects assessed and by the lack of standardization of laboratory equipment 

among laboratories. Moreover, behavioral changes in animal studies usually 

occur at similar or higher doses compared to doses needed to inhibit 

cholinesterase activity. In order to evaluate the concordance between ChE 

inhibition and behavioral endpoints, EPA has performed a series of doseresponse and time course studies with seven NMCs where RBC and brain ChE, 

along with clinical signs (‘tox’ score) and motor activity, were measured 

(Appendix II.B.5; McDaniel et al., 2007; Padilla et al., 2007). 

There are laboratory animal data on NMCs for cholinesterase activity in 

plasma, red blood cell (RBC), whole blood, and brain (whole brain and brain 

sections). Measures of ChE inhibition in the peripheral nervous system (PNS) 

are very limited for ChE inhibiting pesticides, in general. As a matter of science 

policy, blood cholinesterase data (plasma and RBC) are considered appropriate 

surrogate measures of potential effects on PNS acetylcholinesterase activity, 

and of potential effects on the central nervous system (CNS) when brain ChE 

data are lacking (USEPA, 2000a). Furthermore, when RBC ChE data are of 

adequate quality, as is the case for the NMCs, RBC ChE data are preferred 

over plasma ChE data. AChE is the target enzyme for this common 

mechanism group and is the primary form of ChE found in RBCs. 

Section I.B – Page 28 of 277 
Butylcholinesterase (BChE) is the primary form found in plasma. 

Inhibition of BChE is considered a measure of exposure, but has not been 

shown to be of toxicological significance. Some studies with NMCs provided 

whole blood ChE. Whole blood ChE represents a mixture of plasma and RBC 

ChE, and thus may not provide a uniform endpoint for comparison across 

chemicals. Consequently, whole blood ChE data were not used in this 

assessment. In the case of brain ChE inhibition, data are available for each 

NMC with whole brain (or half brain). In some studies, brains were dissected 

into different brain areas (e.g., cerebellum). Because the brain dissections 

provided are not standardized across the studies and brain section data are not 

available for each NMC, these data do not represent a uniform basis of 

comparison. RBC and brain (namely whole, half) ChE inhibition were 

considered potential endpoints for extrapolating risk to humans in the revised 

NMC CRA. As described in Section B.4 below, the Agency is using brain 

ChE data as the basis for RPFs and points of departure (PoD) in this 

assessment. 

Humans may be exposed to the NMCs through food and drinking water 

and in and around residences, schools, commercial buildings, etc. Therefore, 

the potency of NMCs needs to be determined for the oral, dermal, and 

inhalation routes of exposure. Under FIFRA, toxicity studies in various species 

(e.g., dog, mouse, rat, and rabbit) are submitted to OPP. For the NMCs, toxicity 

studies in the rat provide the most extensive and robust database of ChE 

inhibition data. Thus, the focus of this analysis was on ChE activity data 

derived from male and female (non-pregnant) rats. EPA used rabbit studies for 

pesticides with residential/non-occupational exposure potential when dermal 

toxicity data in rats were not available. 

Toxicological characteristics of the NMCs involve maximal ChE inhibition 

followed by the rapid recovery, typically in minutes to hours. As such, the 

critical duration of exposure for this common mechanism group is acute ChE 

inhibition measured at the peak time of effect. Characterizing chemical specific 

recovery is critical for characterizing overlapping exposures and thus 

cumulative risk. EPA has compiled data from several different kinds of studies: 

1. oral (gavage) studies quantifying the relationship between maximum 

inhibition from single or multiple administered dose(s) in adult rats; 

2. oral (gavage) studies quantifying the in vivo recovery time course, usually 

at several doses, and beginning at or around the time of maximum inhibition 

(which had typically been determined in preliminary studies) in adult rats; 

3. comparative cholinesterase assay (CCA) studies quantifying the ChE 

sensitivity of juvenile rats compared to adult rats; comparing dose-response and 

time to recovery in juvenile (PND11 and/or PND 17) and adult rats; and/or 

Section I.B – Page 29 of 277 
4. oral double blind ascending studies quantifying the dose-response 

and recovery time course of ChE in humans; and, 

5. inhalation and dermal studies for those pesticides with residential 

exposure. 

Data included in the revised NMC CRA were extracted from studies 

submitted by pesticide registrants and from dose-response and time course 

studies performed by EPA’s NHEERL. Table I.B-1 provides the list of various 

types of studies included in the analysis. Appendix II.B.1 contains the 

electronic spreadsheets of brain and RBC ChE data used. 

Table I.B-1. Test guidelines/studies that contain evaluations for ChE activity. 

Study Type Guideline Type 

Oral 

Acute oral toxicity study in rat OPPTS 870.1000 

Acute neurotoxicity in rat OPPTS 870.6200a 

Subchronic neurotoxicity in rat OPPTS 870.6200b 

Developmental neurotoxicity oral in rat OPPTS 870.6300 

Chronic oral toxicity in rat OPPTS 870.4100 

Range finding oral toxicity study in rat Not applicable 

Other/Special Studies Not applicable 

Dermal 

 21/28-Day dermal toxicity in rat or rabbit OPPTS 870.3200 

Inhalation 

Acute inhalation in rat OPPTS 870.1200 

Chronic inhalation in rat OPPTS 870.4100 

In toxicology studies submitted to EPA for pesticide registration, 

measurements of cholinesterase inhibition are typically performed using some 

variation of the Ellman spectrophotometric method (Ellman et al., 1961). Under 

standard conditions, this method usually involves extensive sample dilution, 

prolonged incubation, and temperatures around 37°C; all of which promote 

reversal of the enzyme inhibition. If precautions are not taken to prevent 

Section I.B – Page 30 of 277 
recovery using this method, then reported cholinesterase activities can 

underestimate actual cholinesterase inhibition (Winteringham and Fowler, 1966; 

Williams and Casterline, 1969; Nostrandt et al., 1993; Hunter et al., 1997) which 

could have an impact on the relative potency estimates. A radiometric method 

such as that reported by Johnson and Russell (1975) provides the most 

appropriate method for measuring cholinesterase inhibition due to NMC 

exposure because factors which promote reversibility are minimized. The 

dilution is minimized (1:30 vs. more than 1:1000 dilution for the standard Ellman 

method), and incubation time may be more rapid for the radiometric method 

(one to three minutes compared to 10 minutes or greater). Furthermore, the 

radiometric method may be conducted at lower temperatures. The Ellman 

method can be modified to minimize conditions promoting reactivation. 

Reducing the tissue dilution, shortening the time, and lowering the temperature 

of the assay all limit the amount of spontaneous decarbamalyation of the 

inhibited enzyme (Nostrandt et al., 1993). Although modifications to the Ellman 

method are not standardized, when performed with the appropriate care, the 

modified Ellman method can provide reliable cholinesterase data. 

To aid in the characterization of the cholinesterase data provided by the 

studies submitted for registration, scientists from EPA’s NHEERL have 

systematically evaluated cholinesterase inhibition following acute exposures of 

adult rats to seven N-methyl carbamates (carbaryl, carbofuran, formetanate 

HCl, methomyl, methiocarb, oxamyl and propoxur) using both the standard 

Ellman and radiometric techniques. This work has been published in the 

scientific literature (Padilla et al., 2007); the data from these experiments are 

also included in Appendix II.B.1. EPA’s issue paper presented to the FIFRA 

SAP in February, 2005 provided graphical comparisons of the data from 

selected registration studies and EPA’s radiometric experiments. These 

graphical comparisons showed good concordance between the registration 

data and EPA’s radiometric experiments. In the current revised cumulative risk 

assessment, these data have been analyzed statistically (see section I.B.3). 

Overall, the results provided by the EPA radiometric studies provide similar 

benchmark dose estimates to the registration studies. 

The laboratory protocols or standard operating procedures (SOPs) for 

some registration studies have been provided by the pesticide registrants. EPA 

has received protocols or SOPs for studies for nine of the ten NMCs. 

Methiocarb is the only chemical the Agency has not received a protocol or SOP 

for measuring cholinesterase activity. The protocols available indicate that the 

experimental conditions among laboratories vary but that dilutions are generally 

limited to approximately 1:20 and that samples are frozen immediately. 

Although information regarding the time of sample handling is more limited, the 

available information suggests that reasonable precautions were taken in these 

studies to reduce reactivation prior to analysis. The Agency considers the 

methods used to evaluate ChE activity in the laboratory to be a critical 

component of the hazard assessment for the NMCs and will continue to 

Section I.B – Page 31 of 277 
evaluate SOPs as new studies are submitted in the future. A summary 

of the information provided in these protocols can be found in Appendix II.B.5. 

A summary of the studies and endpoints included in the revised 

cumulative risk assessment for the NMCs are provided in Table Table I.B-2. 

This table includes studies recently submitted, such as comparative 

cholinesterase studies and human studies reviewed and found to be ethically 

conducted and scientifically valid by the Human Studies Review Board (HSRB) 

in 2006. 

Table I.B-2. List of toxicity studies used in the Revised N-Methyl Carbamate Risk 

Assessment. 

Oral Dermal Inhalation 

Chemical Study ID ChE Inhibition 

Data Study ID ChE Inhibition Data Study ID 

ChE 

Inhibition 

Data 

434423051 Brain, RBC 

434423022 RBC 

45079705 RBC 

43829601 Brain, RBC 

43829602 Brain, RBC 

450686013 

45150701 

46618001 

Brain 

Aldicarb 

42373001 Human RBC 

No residential uses, thus data are not needed 

43845202 Brain, RBC 

43845203 Brain, RBC 

44122601 Brain, RBC 

44393701 Brain, RBC 

47007001/ 

47143001 

Brain, RBC 

(NHEERL 

CCA) 

NHEERL 

Padilla et al., 

2007 

Brain, RBC 

Carbaryl 

NHEERL 

47143001 

Brain, RBC 

comparative 

45630601 

(47151902) 

Brain, RBC 

(In vitro 

dermal 

penetration) 

Inhalation data are not 

available 

45675701 RBC 

46688912-14 CCA Brain 

47143703-05 CCA 

Brain, RBC 

Moser CCA Brain, RBC 

Carbofuran 

Padilla et al., 

2007 Brain, RBC 

No residential uses, thus data are not needed 

46618901 CCA 

Brain, RBC Formetanate Padilla et al., 

2007 Brain, RBC 

No residential uses, thus data are not needed 

40922301 Brain, RBC Methiocarb Padilla et al., 

2007 Brain, RBC 41771701 Brain Data are not available 

Methomyl 44472001 Brain, RBC No residential uses, thus data are not needed 

Section I.B – Page 32 of 277 
Oral Dermal Inhalation 

44487501 Brain, RBC 

46646401 CCA 

Brain, RBC 

Padilla et al., 

2007 Brain, RBC 

44721401 Human RBC 

44254401 Brain, RBC 

44472001 Brain, RBC 40827601 

44420301 Brain 

46615301 CCA 

Brain, RBC 

Padilla et al., 

2007 Brain, RBC 

44751201 

Brain, RBC 45155801 Brain, RBC Oxamyl 

44912301 Human RBC 

44485301 Brain, RBC 

Pirimicarb 44233103 RBC

00113638 Brain, RBC 

No residential uses, thus data are not needed 

Propoxur Padilla et al., 

2007 Brain, RBC 41066001 Brain, RBC 42648001 Brain, RBC 

45138702 RBC Thiodicarb 45138703 Brain, RBC No residential uses, thus data are not needed 

1

Brain and RBC data for parent only used in the analysis; 2 Brain data at 24 hours not used in the analysis; 3MRIDs listed here are 

referenced in the Aldicarb oral rat brain ChE analysis in Appendix II.B.2 as: 1) 46618001 as Moser-1; 2) 45068601 as Moser-2; and 

3) 45150701 as Moser-3. 

3. Determination of Toxic Potency 

As described in the guidance document for cumulative risk assessment 

(USEPA, 2002a), dose-response modeling is preferred over the use of 

NOAEL/LOAELs (i.e., no- or lowest-observed-adverse-effect-levels) for 

determining relative toxicity potency. NOAELs and LOAELs do not necessarily 

reflect the relationship between dose and response for a given chemical, nor do 

they reflect a uniform response across different chemicals. In the present 

analysis, benchmark dose (BMD) modeling has been used to determine the 

toxic potency of the NMCs. EPA’s draft BMD guidance (USEPA, 2000d) 

suggests that the central estimate on the BMD provides an appropriate 

measure for comparing chemical potency and that the lower limit on the central 

estimate (i.e., BMDL) provides an appropriate measure for extrapolating risk. 

The 10% response level is generally at or near the limit of sensitivity for 

discerning a statistically significant decrease in ChE activity across the blood 

and brain compartments and is a response level close to the background ChE. 

As part of EPA’s Revised Cumulative Risk Assessment for the OPs, EPA 

performed a power analysis of brain ChE data available for more than 30 OPs 

(USEPA, 2002b). The results of the analysis indicated that most studies can 

reliably detect 10% brain ChE inhibition. Furthermore, in studies submitted to 

EPA for pesticide registration, clinical signs and behavioral effects have not 

been shown in studies with below 10% ChE inhibition. In this cumulative risk 

Section I.B – Page 33 of 277 
assessment, the central estimate of the BMD10 was selected as the 

response level for developing RPFs. The lower limit on the BMD10 (i.e., 

BMDL10) was selected for the points of departure (PoDs). A PoD is a point 

estimate on the index chemical’s dose-response curve that is used to 

extrapolate risk to the exposure levels anticipated in the human population. 

The following section describes the empirical dose-response modeling 

performed for the NMCs. BMD10 and BMDL10 estimates for the NMCs are 

provided in Tables 1.B-3 thru 5. Half-life time to recovery for each of the NMCs 

is provided in Table 1.B-6. Detailed information about the empirical modeling 

for each chemical can be found in Appendix II.B.2. 

a. Empirical Modeling: Dose-Time Response Model and Benchmark 

Dose Estimation 

i. Dose-Time Response Model 

Several features of the dose-time response for the N-methyl carbamates 

were to be captured in an empirical model: 

 The rapid decline of ChE activity with increasing dose, perhaps after a 

“shoulder” at the low-dose end of the dose-response curve; 

 A potential minimum level below which ChE activity will not drop, 

regardless of dose; 

 The rapid decline of ChE activity after dosing to a minimum level which 

depends upon dose, then returns to the background level over a period of 

minutes to hours, at a rate that may also depend upon dose; 

 Lack of early time points in most of the time course studies to accurately 

estimate the time of maximum effect, but instead start collecting data 

around a previously estimated time of maximum effect. 

The model described is the result of multiplying a dose-response model 

for inhibition that is closely related to the model that was successful at 

characterizing OP dose-response curves (USEPA, 2002b) and a time-course 

model for inhibition. Transformations of parameters were used to enforce 

constraints, since the statistical software used for estimating model parameters 

does not incorporate bounded estimation (for example, to require that half-life 

estimates remain positive). 

The model for inhibition, before parameters were transformed to enforce 

constraints, is 

Section I.B – Page 34 of 277 
⎛ log 

⎛ 1− − R P ⎞

⎜

⎛ d ⎟⎞

γ

⎞

() = g d( ; R, P, D R ,γ ) = (1− P)⎜

⎜

1− e 

⎜

⎝ 1−P ⎟⎠⎝ DR ⎠ ⎟

⎟ gd 

⎝ ⎠

(Eq. 1) 

where: 

 d is administered dose, and is part of the data set; 

 P is the minimum fraction of background ChE activity, and is 

constrained to fall between 0 and 1; 

 R is the inhibition fraction associated with the desired benchmark 

dose (that is, the benchmark dose is the dose expected to yield 

100×R% inhibition at the time of maximum effect), and is set to 0.10 

in this analysis; 

 DR is the benchmark dose, constrained to be greater than 0.0; 

 γ is a shape parameter to allow a shoulder at the low-dose end of 

the dose-response curve, and is constrained to be greater than 0.0. 

Two different time course models were used. One time course model is 

the difference of two exponential functions, scaled so that the maximum is 

always 1: 

ln 2 t ln 2 t ⎛ − ( ) − ( ) ⎞ R A h t( ) = h(; t T , T ) = C ⎜ e 

T − eT ⎟ A R 0 ⎜ ⎟ ⎝ ⎠

(Eq. 2) 

where: 

 TA is the half-life of the process that results in an increase in 

inhibition, and 

 TR is the half-life of the process that results in a decrease in 

inhibition (recovery or reactivation). 

The maximum of h(t) occurs at: 

TT (ln (T ) − ln (T )) T * = R A R A 

ln ( ) 2 (T R − T A )

(Eq. 3) 

Section I.B – Page 35 of 277 
so 

⎛ − ln * 

− 2 * ⎞ ( ) 2 T ln ( )T 

C 0 = 1 ⎜ e 

T R − e T A ⎟ ⎜ ⎟ ⎝ ⎠

With this scaling, h(t) is symmetric in the two parameters ( that is, h(t; a, b) 

= h(t; b, a) ), which complicates statistical estimation unless a constraint is 

added to keep TR > TA. Also, many data sets require that T* be specified (not 

estimated from the data), because the designs were inadequate for estimating 

T*. For these reasons, it is convenient to reparameterize the model in terms of 

T* and α = TR /TA and make sure α is constrained to be greater than 1.0. 

The design of most of the time-course datasets considered in this 

assessment did not allow clean estimation of both T* and α, and the 

reparameterization sometimes increased the difficulty of estimation. Thus, an 

alternative, much simpler, time-course model was used in all but one of the 

dose-time studies (aldicarb, brain ChE). In this simpler model, ChE activity is 

taken to be described by an exponential recovery time-course, beginning at a 

time δ after dosing. This gives the following recovery function: 

ln(2)( t−δ ) −

h t( ) = e 

TR 

(Eq. 4) 

where: 

TR is the half-life of recovery 

δ is the difference in time between dosing and the first ChE 

measurement. 

In this model, the only parameter to be estimated is TR. 

Multiplying g(d) and h(t) together gives a function for ChE inhibition as a 

function of dose and time. Thus, Equation 5 

f(t, d) = A×(1 – g(d)×h(t)) 

is a model for ChE activity as a function of dose and time, where A gives 

the background (that is, control) level of ChE activity. 

Section I.B – Page 36 of 277 
There were no time-course data for any of the dermal and 

inhalation data sets, so the above model was simplified for those sets, either by 

setting the time course parameters to a fixed value, or by fitting a linear model 

to the natural logarithm of ChE activity, which is equivalent to an exponential 

dose-response model when the variance is proportional to the square of the 

mean ChE activity level (that is, the coefficient of variation is constant across 

doses). 

The following transformations were used to ensure that parameters 

remained in their permitted range: 

 lA = ln(A), to force A > 0 

 lD = ln(DR), to force DR > 0 

 tz = -ln((1 – R – P)/P), to force 0 < P < 1 – R 

 lg = ln(γ), to force γ > 1 

 lTr = ln(TR), to force recovery half-life > 0 (in simplified time-course 

model) 

 ldT = ln(α), to force TR > TA 

 lTmax = ln(Tmax), to force Tmax > 0. 

ii. Statistical Methodology 

The statistical model fit to the dose or dose-time response data depended 

on whether the experimental design involved repeated measures (some RBC 

studies only) or not. The most general model fit to the ChE activity data was 

(for the simplified time course model), for individual j in study i, with sex s(j) at 

time tik: 

When there was more than one study, 

Section I.B – Page 37 of 277 
that is, the log BMD was taken to be normally distributed around a mean that 

possibly differed between sexes. 

When there were repeated observations on a subject, the logarithm of 

individual animals background ChE activity levels were assumed to be normally 

distributed about a mean that varied between sexes, studies, and, when there 

were controls at all times, among times (this latter allows for the possibility of 

variation among analytic batches, if samples from the same time post dosing 

were analyzed as a batch). 

When recovery time-course data were available, the recovery half-life was 

allowed to differ among the doses for which recovery data were available. 

Often for a chemical, some datasets were just dose response studies 

conducted around the time of maximum inhibition, and others included a 

recovery phase, with samples taken every few hours or more frequently. In this 

case, the range of doses in all the studies together was grouped so that one 

dose with a time-course was included in each group. This allowed the estimate 

of recovery half-life to change with dose when the right data were available. 

However, often a chemical had recovery time course data for only a single dose 

level, so only a single recovery half-life could be estimated. 

The process of estimating parameters proceeded in three steps. First, 

initial values for the parameters were arrived at using the R function 

getInitialValues (included in the library DRUtils). This function provides a 

graphical interface that allows the user to quickly arrive at reasonable estimates 

for the parameters, and allows a few iterations of an optimization algorithm to 

improve those initial estimates, using ordinary least squares as an objective 

function. Based on these initial estimates, the degree to which it would be 

possible to uniquely estimate the model parameters was determined, by 

analyzing the condition number of the matrix of gradient of the model with 

respect to the model parameters, and of the matrix of (unscaled) variances and 

covariances of the parameters, evaluated at the data points (times, doses, 

sexes) in all the data sets. At this point, it was often possible to simplify the 

model by noticing that it was impossible to determine a unique value for, for 

example tz, because doses did not go high enough for inhibition to approach its 

maximum value, or the maximum level of inhibition was 100%. 

The next step was to determine an appropriate model for the error 

variance. The options considered were either; a constant variance, a constant 

Section I.B – Page 38 of 277 
variance that differed among studies and sexes, or a variance that was 

proportional to a power of the mean ChE activity level, and whose constant of 

proportionality varied among studies and between sexes. This was determined 

by fitting either a cell mean model (with indicator functions identifying individual 

dose X time X sex X study groups) or, more commonly, fitting the full nonlinear 

dose-time model using generalized nonlinear least squares (Pinheiro and 

Bates, 2000). In either case, likelihood ratio tests were used to identify the 

variance model to use (Pinheiro and Bates, 2000). 

Using that variance model, a full version of the dose-time course model 

was fit to the data, and contrasts used to determine whether lD needed to differ 

among sexes. Pinheiro and Bates (2000) note that likelihood ratio tests for 

fixed effects in mixed effects models tend to reject the null hypothesis 

enthusiastically, whereas using contrasts to test parameter values comes close 

to the nominal type I error rates. 

Finally, a simplified model was fit to the data, and the resulting parameter 

estimates used to determine the values of lD and lTr and their standard errors. 

BMDs were calculated as exp(lD), and BMDLs were calculated by 

exponentiating the lower end of a two-sided 90% confidence interval for lD. 

All statistical analyses used the statistical software environment R (version 

2.0.1, patched version of 2005-01-26; R Development Core Team, 2004) and 

its associated packages. Appendix II.B.3 contains the computer code used in 

EPA’s analyses. 

b. Results: Benchmark Dose and Potency Estimation 

Results of the empirical dose-response modeling are provided below. 

Detailed descriptions of the analysis and results of empirical dose-response 

modeling for each chemical are provided in Appendix II.B.2. 

The oral BMD10s for the NMCs range across several orders of magnitude 

with aldicarb and pirimicarb representing the most and least potent pesticides, 

respectively, for both brain and RBC ChE inhibition. The number of studies 

available for analysis varies among the chemicals (Table 1. B-2). At least two 

studies containing RBC and whole brain ChE inhibition in male and female rat 

were available for eight of ten NMCs (aldicarb, carbaryl, carbofuran, 

formetanate HCL, oxamyl, methomyl, pirmicarb, and thiodicarb). At present 

time, the only RBC and whole brain ChE data for methiocarb and propoxur are 

from EPA’s NHEERL dose-response and time course studies in male rats 

(Padilla et al., 2007). 

For those chemicals that have data in male and female adult rats, EPA 

analyzed both sexes. When male and female data provided statistically similar 

BMD10s, the data were combined and analyzed jointly. This joint analysis 

Section I.B – Page 39 of 277 
provides a more robust analysis using all the available data. In cases 

where the BMD estimates were statistically different, sex specific BMD10s are 

presented (Table I.B-3, and Table 1.-5, below). As mentioned above, only male 

data are available for two NMCs (methiocarb, propoxur). Reliable BMD10 

estimates for RBC ChE inhibition from pirimicarb could not be calculated due to 

a lack of response even at the highest doses tested (110 mg/kg). 

ChE inhibition measured using both radiometric and modified Ellman 

techniques are available for aldicarb, carbaryl, carbofuran, formetanate HCl, 

methomyl, and oxamyl. RBC and brain ChE data from the two methods 

provided statistically similar BMD10 estimates for all of the chemicals and were 

combined in the analysis to provide a more robust potency estimate. As shown 

in Table I.B-3, for carbaryl, both methods provided similar BMD10 estimates for 

RBC ChE. However, for brain ChE in males, the BMD10 estimated from EPA’s 

radiometric study is larger than that estimated from the studies using modified 

Ellmans. Four registration studies were included in the analysis (MRID nos. 

43845202, 43845203, 44122601, 44393701). For all four studies, SpragueDawley rats were administered via gavage with an aqueous vehicle of 0.5% 

(w/v) carboxymethyl-cellulose (high viscosity)/0.1% (w/v) Tween 80 (10mL/kg). 

EPA’s experiments involved Long Evans rats dosed via gavage with corn oil (1 

mL/kg) as the administration vehicle. Given that each of the carbaryl studies 

provided valid and acceptable ChE data, there is no scientific support for 

removing any studies from the analysis. Thus, the Agency has decided to 

include all the available brain ChE data in the carbaryl BMD10 estimate used for 

potency determination (i.e., registration combined with Padilla data of 1.6 

mg/kg). 

Section I.B – Page 40 of 277 
Table I.B-3. Oral BMD10s and BMDL10s from rat brain and RBC ChE inhibition for the 

N-methyl carbamates 

Chemical 

Brain RBC 

BMD10 

(mg/kg) 

BMDL10 

(mg/kg) 

BMD10 

(mg/kg) 

BMDL10 

(mg/kg) 

Aldicarb F= 0.05 

M= 0.06 

F= 0.03 

M= 0.03 0.03 0.02 

Carbaryl 

Registration F= 1.60 

Registration M= 

1.21 

NHEERL M=5.46 

Combined M=1.58 

Moser = 2.63 

Registration F= 1.35 

Registration M= 

0.99 

NHEERL M= 4.15 

Combined M= 1.11 

Moser = 2.03 

Reg. =5.59 

Moser = 0.96 

Reg. = 3.41 

Moser = 0.73 

Carbofuran2 0.10 0.0873 0.03 0.01 

Formetanate 

HCl2 0.11 0.06 0.09 0.03 

Methiocarb2 1.31 0.56 3.18 0.81 

Methomyl 0.36 0.2677 0.20 0.11 

Oxamyl 0.24 0.18 0.28 0.16 

Pirimicarb 11.96 6.98 NA NA 

Propoxur

2 2.09 0.83 1.54 0.28 

Thiodicarb 0.27 0.23 1.39 0.90 

1

BMD estimates are presented as a single estimate when there are no differences between sexes and between 

the radiometric and modified Ellman methods, unless otherwise noted. 2

BMD estimates are for male only 

NA: No relationship between RBC ChE activity and pirimicarb dose. 

Figure I.B-1. Plot of BMD10s and the 95% confidence limits for rat brain ChE inhibition 

for the N-methyl carbamates 

Section I.B – Page 41 of 277 
br a ic ld A 

nar uf obr a C 

et anat e rmoF 

l y max O 

br a ic d io hT 

l y moht e M 

br ac io ht e M 

l yr abr a C 

r uxopor P 

br a ic imri P 

br a ic ld A 

nar uf obr a C 

et anat e rmoF 

l y moht e M 

l y max O 

br a ic d io hT 

r uxopor P 

br ac io ht e M 

l yr abr a C 

br a ic imri P 

Rat Brain ChE Inhibition 

100 

BMD10

(95% confidence limits)

10 

1 

0.1 

0.01 

Chemical Name 

Figure I.B-2. Plot of BMD10s and the 95% confidence limits for rat RBC ChE inhibition 

for the N-methyl carbamates1 

Rat RBC ChE Inhibition 

100 

BMD10

(95% confidence limits)

10 

1 

0.1 

0.01 

Chemical Name 

1

BMD10/ BMDL10 for RBC ChE were not developed for pirmicarb; no dose-response relationship 

was observed up to highest dose tested (110 mg/kg). 

Potency estimates (BMDs) used for calculating dermal and inhalation 

RPFs are provided in Tables 1.B-4 and 1.B-5. Dermal and inhalation RPFs are 

needed for carbaryl, methiocarb, and propoxur as these have residential uses. 

Sufficient dose-response data were available for carbaryl to calculate BMD10 

estimates for RBC and brain ChE via the dermal route. As for the dermal 

Section I.B – Page 42 of 277 
studies with methiocarb and propoxur, no ChE inhibition was observed 

up to the highest doses tested. The highest doses in the methiocarb and 

propoxur studies have been used to estimate dermal relative potency. 

Table I.B-4. Dermal BMD10s, BMDL10s, and potency estimates from rat and 

rabbit brain and RBC ChE inhibition for the N-methyl carbamates with 

residential/non-occupational uses1 

Chemical 

Brain RBC 

BMD10 

(mg/kg) 

BMDL10 

(mg/kg) 

BMD10 

(mg/kg) 

BMDL10 

(mg/kg) 

Carbaryl

2

 49.353 30.56 

F= 86.18 

M= 59.04 

F= 60.55 

M= 46.91 

Methiocarb4 3755 

Propoxur

4

 10005 

1

 See Table I.B.7 for brain BMD10s and BMDL10s for oxamyl; 2Data from rat studies; 3Comparative In vitro 

dermal penetration data were NOT used to refine the brain BMD; 4

Data from rabbit studies; 5Dermal endpoint is based 

on the highest dose tested in the dermal study; No ChE inhibition was observed at any dose. 

Rat inhalation data with propoxur were available to estimate a BMD10 for 

brain ChE. Inhalation studies with carbaryl and methiocarb are not available at 

this time. However, dose-response and time-course data via the inhalation 

route were requested for carbaryl as part of the carbaryl IRED. Route specific 

studies are preferred since they account for route specific kinetic characteristics 

which may impact chemical potency. In the absence of inhalation studies, oral 

data are being used in the revised cumulative risk assessment to estimate 

inhalation relative potency for carbaryl and methiocarb. This introduces 

uncertainty regarding the estimation of cumulative risk for the inhalation 

pathway. However, given that these chemicals do not have a port of entry 

effect, are expected to be rapidly absorbed, and do not require activation, ChE 

measured from oral studies are not expected to substantially underestimate 

potency. (Note: Data from dermal and inhalation studies with oxamyl are not 

provided here because oxamyl does not have residential uses. See Section 

II.B.5 for selection of index chemical [oxamyl]). 

Section I.B – Page 43 of 277 
Table I.B-5. Inhalation BMD10s, BMDL10s, and potency estimates from rat brain 

and RBC ChE inhibition for the N-methyl carbamates with residential/non-occupational 

uses 

Chemical 

Brain RBC 

BMD10 BMDL10 BMD10 BMDL10 

Carbaryl

1 1.58 mg/kg 1.11 mg/kg 5.59 mg/kg 3.41 mg/kg 

Methiocarb1 1.31 mg/kg 0.56 mg/kg 3.18 mg/kg 0.81 mg/kg 

Propoxur

2 

F= 0.0095 mg/L 

M= 0.016 mg/L 

(converted to 4.54 

mg/kg for RPF 

calculation) 

F= 0.0076 mg/L 

M= 0.011 mg/L NA NA 

1

No inhalation studies are available for carbaryl and methiocarb; potency estimates are from oral 

studies 2

Inhalation BMDs and BMDLs for propoxur were different between sexes, therefore are displayed 

separately. No apparent dose-response for RBC inhalation for propoxur and therefore no BMD. 

c. Results: Half Life Time to Recovery 

Half-lives for time to recovery from oral studies in adult rats are provided in 

Table I.B-6. Since brain ChE is the focus of this revised assessment and the 

preliminary assessment indicated similar recovery for brain and RBC ChE, 

Table I.B-6 provides only brain half-life estimates. For most of the NMCs, 

recovery half-life estimates for brain AChE inhibition range from <1 hour up to 4 

hours for adults. Recovery half-lives increased with dose for brain AChE in 

carbaryl studies. No significant sex differences were noted in brain AChE 

recovery half lives. At higher doses of carbaryl, recovery half-life for oral 

exposure was estimated to approximately 12 hours. However, at lower doses 

more relevant for risk assessment purposes, the half-life for carbaryl 

cholinesterase inhibition was estimated at 1 to 2 hours. 

For those NMCs which have data in male and female adult rats, the 

Agency analyzed both sexes. When male and female data provided statistically 

similar BMD10s, the data were combined and analyzed jointly. This joint 

analysis provides a more robust analysis using all the available data. However, 

female data are not available for methiocarb and propoxur while in vivo 

recovery time course data were not sufficiently robust to estimate brain 

cholinesterase half-lives for pirimicarb and thiodicarb. Overall, the half-life to 

recovery data support the use of acute, single day exposures in the NMC 

cumulative risk assessment. 

Section I.B – Page 44 of 277 
Table I.B-6. Half-life for time to recovery for adult rats from oral studies for brain 

ChE inhibition for the N-methyl carbamates1 

Brain 

Chemical Recovery Half-Life Estimate 

(hrs) 

Lower & Upper Confident 

Intervals (hrs) 

Aldicarb 1.52 1.16-1.99 

Carbaryl 1.83 1.23-2.72 

NHEERL 1.65 NHEERL 1.04-2.62 Carbofuran Registrant 0.68 Registrant0.54-0.86 

Formetanate HCL 4.26 3.32-5.460 

Methiocarb2 2.77 1.91-4.01 

Registrant (F) 0.67 Registrant (F) 0.55-0.98 

Methomyl Registrant (M) 1.05 Registrant (M) 0.91-1.23 

NHEERL (M) 0.70 NHEERL (M) 0.50-0.98 

(F) 0.93 (F) 0.78-1.11 Oxamyl (M) 0.70 (M) 0.58-0.856 

Pirimicarb NA3 NA 

Propoxur

2

 2.69 1.02-7.04 

Thiodicarb NA NA 

1

Recovery half-life estimates are presented as a single estimate when there are no differences 

between sexes and between radiometric and modified Ellman methods, unless otherwise noted; 2

 Half-life 

estimates are for males only; 3

NA: insufficient time course data to estimate brain cholinesterase half-life. 

4. Selection of Relative Potency Factors: Brain ChE Inhibition 

A key component of cumulative hazard assessment is to select an 

endpoint pertinent to the common mechanism of toxicity that can be used to 

quantify cumulative risk. EPA is quantifying cumulative risk to the NMCs using 

RPFs and PoDs from brain ChE data. As mentioned above, in cases where 

male and female rats provide similar BMD10 estimates, EPA has developed 

potency estimates jointly (methomyl, pirimicarb and thiodicarb). At the present 

time, only male data are available for methiocarb, and propoxur. For NMCs 

where the female and male data provided statistically different results (aldicarb, 

carbaryl), the male BMD10 has been used to calculate relative potency factors 

since it was the more health protective (i.e., lower) value. 

Section I.B – Page 45 of 277 
As shown in Table I.B-3, BMD10 estimates of brain ChE inhibition 

were generally similar to those for RBC ChE data. For nine of the ten NMCs 

(including the most potent NMCs), brain ChE is equally sensitive or more 

sensitive compared to RBC ChE inhibition. Thus, brain ChE inhibition data 

provides a health protective endpoint for estimating cumulative risk on both the 

central and peripheral nervous system. Compared to BMD10 estimates based 

on RBC ChE, BMD10 estimates based on brain ChE have tighter confidence 

intervals and therefore will confer less uncertainty on cumulative risk estimates. 

Moreover, brain ChE inhibition represents a direct measure of the common 

mechanism of toxicity as opposed to using surrogate measures (e.g., blood 

measures). 

5. Selection of the Index Chemical (Oxamyl) 

OPP’s cumulative risk assessment guidance document (USEPA, 2002a) 

states that the index chemical should be selected based on the availability of 

high quality dose-response data, preferably in each route of interest, for the 

common mechanism endpoint and that it acts toxicologically similar to other 

members of the common mechanism group. High quality dose-response data 

allows the calculation of PoDs for oral, dermal, and inhalation exposures with 

confidence. Because the PoDs for the index chemical are used to extrapolate 

risk to the exposure levels anticipated in the human population, any error or 

uncertainty in an index chemical’s PoD value will be carried forward in the 

cumulative risk estimates. 

a. Candidates for the Index Chemical 

When selecting the index chemical, EPA evaluated the availability of 

quality oral, dermal, and inhalation studies for all ten NMCs. Dermal toxicity 

studies that provided RBC and whole brain data were available for 4/10 NMCs 

(carbaryl, methiocarb, oxamyl, propoxur). Inhalation studies were available for 

only propoxur and oxamyl. At present time, the only NMCs with studies in all 

three routes of interest are oxamyl and propoxur. As shown in Table I.B-2, the 

oxamyl database of oral studies is more robust than propoxur. Moreover, the 

oxamyl dermal study in rabbits provides more robust dose-response data 

compared to the propoxur rabbit dermal study (Tables 1.B-4 and 1.B-7). 

Consequently, oxamyl has been selected as the index chemical for the revised 

cumulative risk assessment of the NMCs. 

b. Description of the Oxamyl Database 

Oxamyl has a robust oral database that includes 6 acute oral studies (4 

registration, 1 NHEERL, 1 human). Radiometric ChE data are available from 

EPA’s NHEERL dose-response and time course studies. A comparative 

cholinesterase study with juvenile (PND 11) and adult rats is also available 

(46615301). Doses in oral rat studies ranged from 0.005 to 15.3 mg/kg and 

Section I.B – Page 46 of 277 
thus provide a broad dose-response range. RBC ChE was measured at 

the time of peak effect in all six studies. Whole (or half) brain ChE data at peak 

inhibition are available from the five rodent studies. High quality ChE recovery 

data in adults and PND11 rats are also available. As shown in Table I.B-3, the 

brain BMD10s for male and female rats are similar. For both sexes, the 

confidence limits on the BMD10s also are narrow. Thus, the BMDL10s provide 

robust values for extrapolating cumulative risk. 

A double-blind, ascending, single oral dose, human study is also available 

for oxamyl (MRID 44912301). Mutliple RBC ChE sampling events provided the 

progression of ChE inhibition, maximum inhibition, as well as enzyme recovery 

for each volunteer. The human study was examined by the HSRB in April 2006 

and deemed scientifically robust and ethically sound for use in risk assessment 

(HSRB Final Report, June 2006). 

Two dermal studies were available for oxamyl, both in the rabbit. Oxamyl 

exhibited a robust dose-response relationship for assessing cholinesterase 

activity with RBC and brain. The effect of sex on dose was not significant in 

either study or compartment. RBC and brain (half-brain) ChE activities for both 

studies were measured once, at the end of the study. The dermal brain and 

RBC ChE BMD10s are 34.91 and 64.01 mg/kg, respectively. 

An acute (single day, 4 hours) inhalation toxicology study (MRID 

45155801) is available for oxamyl. Brain and RBC ChE inhibition were 

measured at the end of the study. The BMD analyses indicate a robust doseresponse relationship for assessing ChE activity with RBC and brain. ChE 

inhibition was similar for both RBC and brain compartments in both sexes. The 

inhalation brain and RBC ChE BMD10s are 0.005 mg/L and 0.002 mg/L, 

respectively. 

A detailed description of the benchmark dose analysis for dermal and 

inhalation studies in oxamyl can be found in Appendix II.B.2. Table I.B-7 

provides the brain BMD10s and BMDL10s for oxamyl. As the index chemical, it 

is used to calculate RPFs and PoDs: 

 Oxamyl brain BMD10s for oral, dermal, and inhalation routes have been 

used to calculate the oral, dermal, and inhalation RPFs for the revised 

cumulative risk assessment. 

 Oxamyl brain BMDL10s for oral, dermal, and inhalation routes have been 

used as the oral, dermal, and inhalation PoDs in the revised cumulative risk 

assessment. 

Section I.B – Page 47 of 277 
Table I.B-7. Oral, dermal, and inhalation brain BMD10s and BMDL10s for oxamyl, 

the index chemical 

Endpoint Oral Dermal Inhalation 

BMD10 0.24 mg/kg 34.91 mg/kg 0.0047 mg/L 

BMDL10 0.18 mg/kg 17.05 mg/kg 0.0038 mg/L 

(converted to 0.66 mg/kg) 

6. Relative Potency Factors for the Revised Cumulative Risk 

Assessment of the N-Methyl Carbamates 

RPFs were calculated from endpoints for brain ChE inhibition provided in 

Tables 1.B-3, 1.B-4, 1.B-5, and 1.B-7. An RPF is the ratio of the BMD10 of 

oxamyl divided by the BMD10 (or appropriate value) for each NMC. RPFs are 

listed in Table I.B-8. 

Table I.B-8. Relative potency factors for oral, dermal, and inhalation routes1 

Chemical Oral RPF Dermal RPF Inhalation RPF 

Aldicarb 4 

Aldicarb sulfone 

(Aldoxycarb)1 3.44 

Aldicarb sulfoxide1 3.68 

Carbaryl 0.15 0.71 0.51 

Carbofuran 2.4 

3 & 5-hyrdoxycarbofuran2 2.4 

Formetanate HCL 2.18 

Methiocarb 0.18 0.09 0.62 

Methomyl 0.67 

Oxamyl 1.00 1.00 1.00 

Pirimicarb 0.02 

Propoxur 0.11 0.03 0.18 

Thiodicarb 0.89 

1

 Aldicarb sulfone and sulfoxide were not modeled based on metabolite-specific data. Instead they 

were calculated based on molecular weight conversions from aldicarb assuming equipotent to aldicarb. 2 

Carbofuran and 3 and 5-hydroxycarbofuran assumed to be equipotent to carbofuran. 

Section I.B – Page 48 of 277 
7. Intra-species Variability, Inter-species Extrapolation, and 

FQPA 10X Safety Factors 

Typically, EPA applies standard 10X factors to account for inter-species 

extrapolation and intra-species variability. The FQPA (1996) also mandates 

that a 10X safety factor be applied to protect for infants and children unless 

there is sufficient data to support removal of the 10X. For the revised NMC 

CRA, the standard 10X intra-species factor is applied to each of the ten Nmethyl carbamates. The inter-species and FQPA 10X factors applied in the 

NMC CRA are described below. 

a. Inter-species Extrapolation Factor in the revised NMC CRA 

The rat provides the basis for the RPFs and PoDs in the cumulative risk 

assessment for the NMCs. As such, a consideration of inter-species 

extrapolation is necessary (i.e., animal to human). EPA typically applies a 10X 

factor to account for differences in animals and humans. In the revised NMC 

CRA, the Agency has retained the 10X inter-species factor for those seven 

NMCs with no reliable human cholinesterase data. Oral studies with adult 

human subjects with measurements of peak RBC ChE inhibition and recovery 

data are available for aldicarb (MRID 42373001), methomyl (MRID 44721401), 

and oxamyl (MRID 44912301) and provide the basis for refinement of the interspecies factor for these specific NMCs. These three human studies were 

evaluated by the HSRB in April, 2006 (HSRB Final Report, June 2006). The 

Board concluded the human intentional dosing studies were ethical and 

scientifically robust and appropriate for use by the Agency for purposes of risk 

assessment. It is noted that the carbofuran human oral study was presented to 

the HSRB in May 2006; however, the Board concluded that it was not 

scientifically robust and not useful for risk assessment (HSRB Final Report, July 

2006). The revised NMC CRA does not include ChE data from the carbofuran 

human study. For the acceptable human studies, the RBC ChE data were 

modeled in a consistent fashion with the rat data to calculate human RBC 

BMD10s and BMDL10s. The Agency then used the RBC BMD10 ratios for rats 

and humans for the pesticide-specific inter-species factor. A comparison of 

RBC ChE BMD10s and half-life estimates suggests humans are approximately 

2-5 times more sensitive than rats with half-life estimates similar between rats 

and humans (1-2 hours). The oral BMD10s and BMDL10s generated from the rat 

and human ChE data for aldicarb, methomyl, and oxamyl along with the 

corresponding inter-species factors are provided below in Table I.B-9. 

Section I.B – Page 49 of 277 
Table I.B-9. Inter-species uncertainty factors and corresponding rat and human 

BMD10s and BMDL10s 

Chemical 

Rat Human 

Interspecies 

UF 

Brain RBC RBC 

BMD10 

(mg/kg) 

BMDL10 

(mg/kg) 

1⁄2 

life 

(hrs) 

BMD10 

(mg/kg) 

BMDL10 

(mg/kg) 

1⁄2 

life 

(hrs) 

BMD10 

(mg/kg) 

BMDL10 

(mg/kg) 

1⁄2 

life 

(hrs) 

Aldicarb F=0.048 

M=0.056 

F=0.035 

M=0.035 1.5 0.031 0.020 1.1 0.016 0.013 1.7 2X 

Methomyl 0.486 0.331 1.0 0.204 0.112 0.8 0.040 0.028 1.6 5X 

Oxamyl F=0.145 

M=0.185 

F=0.111 

M=0.143 0.9 0.278 0.158 0.8 0.083 0.068 2.4 3X 

BMD estimates are presented as a single estimate when there are no differences between sexes. 

Human RBC data obtained from MRID 42373001 (aldicarb), MRID 44721401 (methomyl), MRID 44912301 (oxamyl). 

Rat brain and RBC ChE data obtained for aldicarb from MRIDs 43442302, 43442305, 43829601, 43829602, 

45068601; for methomyl from MRIDs 44472001, 44487501, 46646401, Padilla et al. 2007; and for oxamyl from 

MRIDs 44254401, 44472001, Padilla et al. 2007. 

b. FQPA Safety Factor 

i. Background 

The FQPA (1996) instructs EPA, in making its “reasonable certainty of no 

harm” finding, that in “the case of threshold effects, an additional tenfold 

margin of safety for the pesticide chemical residue and other sources of 

exposure shall be applied for infants and children to take into account potential 

pre- and post-natal toxicity and completeness of data with respect to 

exposure and toxicity to infants and children.” Section 408 (b)(2)(C) further 

states that “the Administrator may use a different margin of safety for the 

pesticide chemical residue only if, on the basis of reliable data, such margin will 

be safe for infants and children.” 

The FQPA requires that the Agency consider issues related to toxicity and 

exposure. The text contained in this chapter only considers potential sensitivity 

of infants and children with respect to toxicity. The risk characterization chapter 

(I.G) contains a more complete discussion of issues related to exposures from 

food, water, and in/around the home that could contribute to increased 

exposure to infants and children relative to adults. However, the Agency 

believes that there are quality data and scientifically supportable methods to 

account for specific exposure and behavioral patterns of children. Because 

characteristics of children are directly accounted for in the exposure 

assessment and the Agency’s methods are not expected to underestimate 

exposure to NMCs, evaluating the potential for increased toxicity of juveniles is 

the key component in determining the magnitude of the FQPA factors in the 

revised NMC CRA. 

Section I.B – Page 50 of 277 
As described in detail in OPP’s cumulative risk assessment 

guidance, determination of relative toxic potency should be calculated using a 

uniform basis of comparison, by using, to the extent possible, a common 

response derived from the comparable measurement methodology, species, 

and sex for all the exposure routes of interest (USEPA 2001a, 2002a). For the 

NMCs, estimates of relative potency are required for 10 pesticides. Toxicology 

studies in the adult rat provide the most extensive cholinesterase activity data 

for all routes, compartments, and both sexes and as a result provide the basis 

for the RPFs and PoDs in the NMC CRA. Since adult rat data have been used 

to derive the RPFs and PoDs, EPA has retained the 10X FQPA safety factor 

unless reliable data are available addressing the sensitivity of the young such 

that EPA can determine that a different safety factor value is protective of 

infants and children. Consistent with the mode of action for NMCs (i.e., 

neurotoxicity mediated through the inhibition of AChE via carbamylation of the 

active site), the comparative cholinesterase assays in juvenile and adults 

provide the most relevant data for evaluating potential sensitivity to infants and 

children to NMCs. 

The Agency has compared the sensitivity of NOAELs (No-ObservableAdverse- Effect-Level), LOAELs (Lowest-Observable-Adverse-Effect-Level), 

and BMDs from developmental neurotoxicity studies (DNTs) and comparative 

cholinesterase studies for OPs as well as NMCs. The Agency has three 

developmental neurotoxicity studies for the NMCs (aldicarb, carbaryl and 

carbofuran). For every OP and NMC evaluated, the comparative 

cholinesterase assays (CCA) provide a more sensitive (i.e., lower) endpoint 

than the respective DNT. In the case of NMCs, the CCA studies are 10-100 

fold more sensitive than the DNT studies. Thus, use of AChE inhibition as the 

endpoint for evaluating the FQPA 10X safety factor is expected to be protective 

of functional and behavioral effects. 

The Agency has focused its evaluation of the FQPA 10X safety factor on 

post-natal exposure to juvenile rats. In a detailed analysis provided in the OP 

CRA (USEPA 2006), the Agency showed that following in utero exposure to 

OPs, dams exhibit larger amounts of ChE inhibition compared to fetuses. In 

other words, protecting against inhibition in the pregnant dams is believed to 

protect against pup AChE inhibition in utero. In contrast to this in utero 

exposure, pups have been shown to be more sensitive than adults in post-natal 

studies. Thus, data from post-natal exposures in juvenile and adult rats provide 

the most robust toxicity data for determining the magnitude of the FQPA safety 

factor for the NMC CRA. The CCA studies provide sensitive and reliable 

results, and have been identified for use in the cumulative risk assessment as 

the most appropriate studies for developing the chemical-specific factor to 

address the potential susceptibility of infants and children to the effects of NMC 

exposure. Comparative ChE data are available and can be used to derive a 

chemical-specific factor for use in the cumulative risk assessment to reflect the 

Section I.B – Page 51 of 277 
differential sensitivity of children and infants compared to adults. For 

those NMCs without such data, the FQPA 10X safety factor is retained. 

As described in detail below, the Agency has used a dose response 

modeling approach for evaluating quantitatively the relative sensitivity between 

juvenile and adult rats. In this approach, a BMD was calculated for juvenile and 

adult brain ChE data. The ratio of the juvenile and adult BMDs from the specific 

CCA study was calculated—this ratio has been used mathematically as the 

data-derived, chemical-specific FQPA safety factor. This approach is similar to 

that used in the OP CRA but different from (although not inconsistent with) 

approaches used in the single chemical aggregate risk assessments. In single 

chemical, aggregate risk assessments, the mathematical calculations are more 

simple and straightforward as only one active ingredient is included. As such, 

in single chemical risk assessments, when available, data from young or 

juvenile animals can be (and have been) used directly as the PoD. When the 

data from the young are used directly in deriving a PoD and the PoD is 

established based on the most sensitive effects, the FQPA safety factor can be 

reduced or removed so long as there are no residual concerns regarding 

potential pre- and post-natal toxicity or concerns regarding the completeness of 

the toxicity or exposure databases. In the revised NMC CRA, the data-derived 

FQPA safety factor is used to adjust the chemical specific RPF to account for 

the potential increased sensitivity of the young. 

The Agency has relied primarily on CCA studies in juvenile and adult 

animals to evaluate the potential sensitivity of young animals to cholinesterase 

inhibition. Brain cholinesterase inhibition is the focus of this analysis as brain 

cholinesterase inhibition has been selected as the endpoint for derivation for 

RPFs and PoDs in the NMC CRA. For each individual NMC, the magnitude of 

the FQPA 10X safety factor was based on the ChE dose-response data 

comparing relative sensitivity of adult and juvenile animals. The Agency has 

also evaluated the recovery data in the young to evaluate the extent to which 

the young recover from NMC inhibition in comparison to adults (e.g., faster, 

slower, or similar to adults). If the Agency were to evaluate NMC exposure at 

shorter intervals than 24 hours (Chapter C), then the Agency would need to 

account for the half-life to recovery in young animals. The Agency has four 

CCA studies generated by registrants: carbofuran, formetanate, methomyl, and 

oxamyl. In addition, NHEERL has provided comparative sensitivity data for 

aldicarb and carbaryl. The brain BMD10 estimates for PND 11 pups span an 

order of magnitude and are generally 2-3 times lower than adult rats. The halflife estimates for brain inhibition in PND11 rats range from approximately 30 

minutes to almost 10 hours compared to 1 to 4 hours in adults. Table I.B-10 

displays the BMD10 values of both juvenile (PND11 or PND17) and adult rats 

specifically from the available CCA studies. It is noted that the adult BMD10 

estimates from the CCA study may be different than the more robust BMD10 

estimate based on the combined adult data. BMDL10 and half-life values for 

pups are provided for information purposes only. 

Section I.B – Page 52 of 277 
Table I.B-10. Dose-response and recovery half-life estimates in juvenile and adult rats 

from comparative cholinesterase studies 

PND11 Brain Adult Brain 

Chemical BMD10 

(mg/kg) 

BMDL10 

(mg/kg) 

Half-Life 

(hrs.) 

Adult BMD 

(mg/kg) 

Aldicarb1 0.017 0.016 NA2 0.033 

Carbaryl 1.459 1.135 5.43 2.627 

Carbofuran 0.039 0.030 3.0 0.109 

Formetanate 0.188 0.098 9.5 0.382 

Methomyl 0.104 0.070 0.4 0.317 

Oxamyl 0.051 0.025 1.5 0.177. 1

The juvenile rat data for aldicarb is based on a published acute oral neurotoxicity study in PND17 rats 

(MRID45068601)), 2

Time-course data in juvenile rats not available for aldicarb; 3The recovery half-life estimate for 

carbaryl is based on NHEERL data from PND17 pups. 

The resulting FQPA safety factor for each NMC is the ratio of the BMD10 

for adult/pup. Those NMCs without comparative cholinesterase data retain the 

10X FQPA safety factor. Since the FQPA safety factor is specific to protecting 

children and developed from juvenile rat data, it may be applied in the NMC 

CRA to scenarios specific to children’s exposure. The FQPA safety factor is 

therefore not applied to RPFs for adults. The resulting chemical specific FQPA 

safety factors for these six NMCs are listed in Table I.B-11. 

Table I.B-11. FQPA safety factors for the revised NMC CRA1 

Chemical FQPA Safety Factor 

Aldicarb 2.0 

Carbaryl 1.8 

Carbofuran 2.75 

Formetanate 2.03 

Methomyl 3.05 

Methiocarb 10 

Oxamyl 3.48 

Pirimicarb 10 

Propoxur 10 

Thiodicarb 10 1

Those NMCs without juvenile pup data retain the 10X FQPA safety factor 

Section I.B – Page 53 of 277 
8. Incorporation of Uncertainty/Extrapolation Factors and the 

Target Margin of Exposure 

In general, when performing a cumulative risk assessment using a RPF 

approach, like that done for the NMCs, uncertainty and extrapolation factors 

can be incorporated into the risk assessment in two different ways: 1) 

adjustment of the chemical-specific RPF or 2) incorporation into the target 

Margin of Exposure. Both ways are used in the NMC CRA. 

Adjustment of the Chemical Specific RPF: In cases where the uncertainty 

or extrapolation factor varies among the chemicals, the chemical-specific RPF 

is adjusted (i.e., multiplied) by the uncertainty or extrapolation factor. In the 

case of the NMCs, the FQPA and inter-species factors vary among the 

chemicals. As such, the Agency has multiplied the FQPA safety and interspecies factors by the RPFs to generate adjusted RPFs for each NMC (Table 

I.B-11). 

Incorporation into the Target Margin of Exposure (MOE): There may be 

assessments where the magnitude of an uncertainty or extrapolation factor is 

the same for each member of the common mechanism group. In these 

assessments, the target MOE identified addresses the total magnitude of the 

uncertainty or extrapolation factor(s). This is the situation for the intra-species 

factor in the NMC CRA where the standard 10-fold factor has been applied. As 

discussed above, both the FQPA safety and inter-species extrapolation factors 

are accounted for in the adjusted RPFs for the NMC CRA. As such, the target 

MOE for the NMC CRA is 10 accounting for intra-species variability. 

Table I.B-12. Adjusted oral relative potency factors for children and adults based on 

inter-species and FQPA specific factors 

Chemical Oral RPF Inter-species 

Factor 

FQPA Factor 

Children 

Only 

Adjusted 

RPF 

Children 

Adjusted RPF 

Adult 

Aldicarb 4 2 2 16 8 

Aldicarb sulfone 

(Aldoxycarb) 3.44 2 2 13.8 6.9 

Aldicarb sulfoxide 3.68 2 2 14.7 7.4 

Carbaryl 0.15 10 1.8 2.7 1.5 

Carbofuran 2.4 10 2.75 66 24 

5-hydroxycarbofuran 2.4 10 2.75 66 24 

Formetanate HCL 2.18 10 2.03 44 22 

Methiocarb 0.18 10 10 18 1.8 

Methomyl 0.67 5 3.05 10 3.3 

Oxamyl 1 3 3.48 10 3 

Pirimicarb 0.02 10 10 2 0.2 

Propoxur 0.11 10 10 11 1.1 

Thiodicarb 0.89 10 10 89 8.9 

Section I.B – Page 54 of 277 
Table I.B-13. Adjusted dermal relative potency factors for children and adults 

based on inter-species and FQPA specific factors 

Chemical 

Carbaryl 

Dermal 

RPF 

0.71 

Inter-species 

Factor 

10 

FQPA 

Factor 

Children 

Only 

1.8 

Adjusted RPF 

Children 

13 

Adjusted RPF 

Adults 

7.1 

Methiocarb 0.09 10 10 9 0.9 

Oxamyl 1.00 3 3.48 10 3 

Propoxur 0.03 10 10 3 0.3 

Table I.B-14. Adjusted inhalation relative potency factors for children and adults based 

on inter-species and FQPA specific factors 

Chemical Inhalation 

RPF 

Interspecies 

Factor 

FQPA Factor 

Children Only 

Adjusted RPF 

Children 

Adjusted RPF 

Adults 

Carbaryl 0.511 10 1.8 9 5.1 

Methiocarb 0.619 10 10 62 6.2 

Oxamyl 1.00 3 3.48 10 3 

Propoxur 0.178 10 10 18 1.8 

9. Dose Additivity 

A key assumption of the RPF method is dose additivity. While there are a 

few interaction studies of N-methyl carbamate and OP pesticides in the 

literature (e.g., Gupta and Dettbarn, 1993; Takahashi et al., 1987), no studies 

conducted using mixtures of more than two N-methyl carbamates and which 

use low dose levels (i.e., that do not produce lethality or profound toxicity) have 

been identified. To fill this data need, NHEERL scientists have conducted a 

mixture study using seven N-methyl carbamates (carbaryl, carbofuran, 

formetanate HCl, methiocarb, methomyl, oxamyl, and propoxur) (Padilla et al., 

2006). In the mixture study, a dose-additive experimental design was used and 

the proportion of the carbamates in the mixture was based on their potency 

using the individual-chemical benchmark dose values as the point of 

comparison. Five different dosage levels of the mixture were given, predicted 

to produce <5%, 10%, 25%, 45% or 60% brain ChE inhibition. Each NMC was 

given alone at a previously tested dosage to confirm the original dose-response 

data (7 single-chemical experimental groups). The effects on motor activity and 

RBC and brain ChE were measured. As can be seen from Figure I.B-3 below, 

increasing dosages of the mixture produced increasing decrements in brain 

ChE activity. Moreover, the dose-additive model predicted the degree of ChE 

inhibition within the 95% confidence limits of each predicted value. Additivity 

was also measured in the RBC ChE and motor activity evaluations (manuscript 

in preparation). 

Figure I.B-3. Plot of brain ChE measured in a seven chemical mixture of N-methyl 

carbamates 

Section I.B – Page 55 of 277 
Cholinestera

se activity (

% c

ontrol) 

120 

110 

100 

90 

80 

70 

60 

50 

40 

30 

20 

Expected Values (+ 95% confidence limits) 

Acutal Data (+ sem) 

Dose-Additive Design 

Equipotent Mixture 

Control 

0 2 4 6 8 10 12 14 16 

Dose of Mixture (mg/kg) 

10. Summary 

This chapter has described the application of the RPF method in the 

revised cumulative hazard assessment for the NMCs. Whole brain ChE is a 

sensitive, health protective endpoint representing the target tissue. The brain 

data provide the most appropriate dataset for extrapolating cumulative risk to 

this common mechanism group. Potency for the NMCs varies over several 

orders of magnitude. Analysis of recovery data for brain ChE in adults suggests 

that half-life time to recovery ranges from less than an hour up to 4 hours is 

chemical dependant, and for some chemicals, is dose dependant. For some 

NMCs, recovery of ChE activity in pups may be longer. Overall, the analysis of 

recovery data supports the Agency’s assumption that at the low concentrations 

found in the environment, the appropriate duration of exposure for the NMC 

cumulative risk assessment is acute exposure. Oxamyl has been selected as 

the index chemical based on the availability of high quality dose response data 

for the oral, dermal, and inhalation routes. BMDL10 estimates of brain ChE from 

oral, dermal, and inhalation studies with oxamyl represent the PoDs for the 

NMCs cumulative risk assessment. BMD10 estimates of brain ChE from oral, 

dermal, and inhalation studies were used to develop RPFs for the NMCs. 

The Agency has, when available, utilized ethically and scientifically valid 

human studies for refinement of the inter-species factor as well as comparative 

sensitivity rat data for refinement of the FQPA safety factor. These uncertainty 

Section I.B – Page 56 of 277 
factors apply to the oral, dermal, and inhalation RPFs, which result in 

adjusted RPFs for individual NMCs, specifically for adults and children. In 

instances where there is no human study or comparative sensitivity data for 

particular NMCs, the inter-species factor and/or FQPA safety factor remain(s) 

unchanged (i.e., 10x) and is/are used to adjust the RPF accordingly. As a 

result, the target MOE for the NMC CRA is 10 which accounts for the intraspecies 10x factor which is the same for all of the NMCs in the revised NMC 

CRA. 

Section I.B – Page 57 of 277 
C. Cumulative Risk from Pesticides in Foods 

This chapter discusses the cumulative risk associated with the food 

exposure pathway. As with previous cumulative assessments released 

by OPP, the data for this pathway are developed from two primary 

sources: dietary consumption data collected by USDA’s Continuing 

Survey of Food Intakes by Individuals (CSFII) and pesticide residue 

monitoring data collected by the USDA Pesticide Data Program (PDP). 

As described further in Chapter I.B of this document, oxamyl serves as 

the index chemical and the residue values for the other NMC pesticides 

were converted to oxamyl equivalents using the RPF approach. The 

exposure estimates presented in this chapter, therefore, are expressed 

in terms of the index chemical oxamyl. 

The purpose of this chapter is several-fold: (i) to describe and 

characterize the food consumption, pesticide residue, and other data 

sources used to develop the cumulative risk assessment for the food 

pathway; (ii) to describe how and the extent to which the PDP pesticide 

residue data on approximately 80 food commodities, including those 

most commonly consumed by children, was extended/translated to other 

foods in order to produce a more complete data set on pesticide residues 

that more nearly approximated the total diet; (iii) to describe the methods 

used to convert pesticide residue data from the PDP data program into 

index-chemical (i.e., oxamyl) equivalents in order to conduct a 

cumulative assessment; (iv) to describe how this cumulative residue data 

set was combined with USDA’s food consumption data and food 

processing data to produce a distribution of estimated cumulative 

exposures to the NMC group of pesticides; and (v) to provide information 

with respect to those crop-commodity combinations which contribute to 

exposure at the upper-ends of the exposure distribution. This chapter 

does not describe the extensive sensitivity analyses that were performed 

nor does it provide information on or discuss risk characterization. 

These are important -- indeed critical -- components of any risk 

assessment and are presented in Chapter G of this document. 

1. Food Consumption Data 

Data on food consumption are a necessary component for 

estimating pesticide exposure through the diet. For the revised NMC 

CRA, food consumption data were obtained from the USDA CSFII 1994­

96/1998 (USDA, 2007). The CSFII 1998 incorporated a supplemental 

children’s survey conducted in 1998 in which the food consumption of an 

additional 5,559 children (birth through 9 years old) were surveyed. The 

CSFII 1994-96/1998 is a nationally representative stratified, multi-stage 

area probability sample with a target population consisting of nonSection I.C – Page 58 of 277 
institutionalized individuals in all 50 states and Washington, DC. CSFII 

1994-96/1998 data are derived from information provided by 20,607 

individuals who participated in the survey. Individuals who took part in 

the survey were asked to provide two non-consecutive days of dietary 

data through the administration of in-person, 24-hour dietary recalls 

spaced 3–10 days apart. The USDA CSFII consumption survey data are 

included as an integral component of the DEEM-FCIDTM software used 

to conduct this cumulative risk assessment.1 

As in previous cumulative risk assessments produced by EPA, 

separate assessments were conducted on the various sub-populations 

as represented in the CSFII 1994-96/1998. The current assessment 

reports on the U.S. general population and the following standard age 

groups: 

‘ Infants less than 1 year old 

‘ Children 1-2 years old 

‘ Children 3-5 years old 

‘ Children 6-12 years old 

‘ Youths 13-19 years old 

‘ Adults 20-49 years old 

‘ Adults 50+ years old 

‘ Females 13-49 years old 

1

 It is important to note that the CSFII food diary information is expressed in 

terms of food as consumed (e.g., pizza, apple pie, lasagna, etc.) while OPP’s 

assessments are currently conducted in terms of food commodities (e.g., tomatoes, 

milk, wheat flour, beef, apples, etc.). OPP uses standard recipes to convert foods “as 

consumed” as reported in CSFII diaries into food commodities for use in OPP dietary 

risk assessments. The recipe information used to break down the foods was developed 

jointly by EPA and USDA and is one module in the EPA’s Food Commodity Intake 

(FCID) database which is available upon request. Thus, while this NMC CRA refers to 

“food” consumption from CSFII, the Agency’s calculations are performed in functionally 

equivalent “food commodity” terms from FCID. While often distinct, “food” and “food 

commodity” will be used interchangeably in this document. 

Section I.C – Page 59 of 277 
2. Pesticide Residue Data 

There are multiple sources of pesticide residue data (on food) 

available to EPA. However the sampling design and extent, intent, and 

representativeness of these various sources of pesticide residue data 

differ. USDA PDP provides the most comprehensive sampling design, 

and the most extensive and intensive sampling procedures for pesticide 

residues of the various data sources available to EPA. Additionally, the 

intent of PDP’s sampling design is to provide statistically representative 

samples of food commodities eaten by the U.S. population specifically 

for the purpose of performing dietary risk assessments for pesticides. As 

such, PDP serves as the only source of pesticide residue data used in 

quantitative manner in the dietary portion of this revised NMC CRA. The 

other sources of pesticide residue data are used in a qualitative manner 

to ensure that EPA is not significantly underestimating pesticide 

exposure through food. The various sources of pesticide residue data 

are discussed below. 

a. USDA-PDP 

As with the preliminary NMC CRA, this revised NMC CRA also 

relies exclusively on the PDP program for residue data that are used 

quantitatively. The USDA PDP is a cooperative effort by federal and 

state agencies to obtain statistically-reliable data on pesticide residues in 

food (USDA, 2007a). Federal funds support sampling, testing, and datareporting activities conducted by participating states. The participating 

states include California, Colorado, Florida, Maryland, Michigan, 

Minnesota, Montana, New York, Ohio, Texas, Washington, and 

Wisconsin. In addition, 13 of their neighboring states are in the direct 

distribution networks of the PDP participating states. Together, these 

states represent over 50% of the nation’s population and all 4 census 

regions of the U.S. These states also represent the major commercial 

production areas of fruit and vegetables in the U.S. 

The PDP sample collection procedures are specifically designed to 

produce dietary exposure estimates that closely approximate real world 

exposures. Samples are collected by USDA at terminal markets and 

warehouses immediately before these commodities are shipped to 

supermarkets and other retail establishments. Both domestically 

produced and imported foods are subject to sampling. Sampling is 

conducted in accordance with a statistically-based plan designed and put 

in place by USDA’s National Agricultural Statistics Service (NASS) to be 

representative of the U.S. food supply. Samples are prepared by the 

analytical laboratory as if for consumption (i.e., they are washed, peeled, 

and/or cored, as appropriate) and thus are more reflective of actual 

exposures than data typically available from field trials or FDA monitoring 

Section I.C – Page 60 of 277 
programs. Thus, measurements simulate as closely as possible dinnerplate exposures to consumers. 

The program focuses on high-consumption foods for children and 

reflects foods typically available throughout the year. A complete 

description of the PDP program and all data through 20052

 are available 

online (USDA, 2007b). The PDP data are available in downloadable 

electronic format from this site and can be easily transferred, imported, 

analyzed, and summarized. Appendix II.C.1 lists all of the FCID food 

commodities for which PDP residue data were used to estimate dietary 

exposure to NMC pesticides. The PDP residue data on NMC pesticides 

included in the revised NMC CRA are summarized in Appendix II.C.2. 

b. NMC Market Basket Survey 

The Carbamate Market Basket Survey Task Force sponsored a 

market basket survey (MBS) of NMC pesticide residues and their 

toxicologically relevant metabolites in single-serving samples of fresh 

fruits and vegetables collected in 1999-2000 (Carringer, 2000). The 

NMC pesticides analyzed in the MBS were aldicarb, carbaryl, 

carbofuran, methomyl, oxamyl, and thiodicarb. The food commodities 

sampled in the MBS were apple, banana, broccoli, grape, head lettuce, 

orange, peach, and tomato. However, not all NMC pesticides were 

analyzed in each type of commodity. For instance, aldicarb was 

analyzed in only one commodity, oranges; and carbaryl was the only 

NMC analyzed in all eight food commodities. Of the top ten pesticidecommodity combinations contributing to the exposure of young children 

as determined by this NMC CRA, only two (for children 1-2) and three 

(for children 3-5) of these significant contributors were sampled in the 

MBS. Comparing the residue data from the PDP program with the MBS, 

the top pesticide-commodity contributors common to both MBS and PDP 

have similar ranges of pesticide concentrations and frequencies of 

detects. Additionally, PDP has collected more recent data on the same 

commodities sampled in the MBS. Finally, all of the pesticide-commodity 

combinations analyzed in the MBS are data for which EPA already has 

adequate PDP data for the purpose of dietary risk assessment. 

Consequently, the MBS data have not been used directly in the revised 

NMC CRA. 

c. FDA-CFSAN Pesticide Residue Monitoring Program 

2

 Although the 2006 PDP data are not currently available for download from the 

PDP website, the new data are expected to be published and publicly available in 2007. 

Due to an active interagency MOU between USDA PDP and USEPA OPP, the 2006 

PDP data on NMC pesticides were given priority in PDP’s QA/QC process and released 

early to OPP upon request. 

Section I.C – Page 61 of 277 
The Food and Drug Administration’s (FDA’s) Center for Food 

Safety and Applied Nutrition (CFSAN) Pesticide Residue Monitoring 

Program is designed primarily for enforcement of EPA pesticide 

tolerances on imported foods and domestic foods shipped in interstate 

commerce (USFDA, 2007a). In this monitoring program, domestic 

samples are generally collected close to the point of production in the 

distribution system. Import samples are collected at the point of entry 

into U.S. commerce. The emphasis in sample collection is on the 

agricultural commodity which is analyzed as the unwashed, whole 

(unpeeled), raw commodity. Processed foods are also included in the 

program. Because the emphasis of this program is not on dietary 

exposure, it is being used in the current assessment mostly as a semiquantitative check on the potential for residues and as support for data 

from other sources. The program has extensive data available on eggs 

and fish, which support the judgment that NMC residues are negligible 

on these foods as consumed. Thus, the FDA data were used in a 

qualitative manner in this revised NMC CRA to support the decision to 

assign residue values of zero to the NMC residues on eggs and fish 

effectively removing these food commodities from the assessment. 

Appendix II.C.1 indicates the foods for which such decisions were 

supported by this program. 

d. FDA-CFSAN Total Diet Study 

The FDA’s CFSAN Total Diet Study (TDS) has provided data on 

concentrations of contaminants in a wide range of foods for about 46 

years (USFDA, 2007b). Foods are purchased at retail (from grocery 

stores and fast-food restaurants), generally 4 times a year, prepared and 

cooked for consumption, and analyzed by highly sensitive multi-residue 

methods. Between 1991 and 2004, there have been 48 market baskets 

collected. For each market basket, three samples of approximately 280 

different foods are collected and composited, and the composite samples 

are analyzed for – among other things – NMC pesticide residues. A 

disadvantage of these data is that only one composite sample of each 

food is analyzed in each market basket. For this reason, these data 

have been used primarily as semi-quantitative support for judgments on 

residues in foods. 

In previous cumulative risk assessments performed by EPA, 

conservative estimates of pesticide residue values for some highly 

consumed foods such as beef were based on the TDS data. However, 

beef, poultry, and pork are now sampled under the PDP program, being 

most recently sampled in 2002, 2005, and 2006, respectively. PDP data 

on these commodities serve as the primary source of residues of 

pesticides used by EPA in dietary risk assessments, replacing the 

corresponding FDA TDS data previously used. Both programs have 

Section I.C – Page 62 of 277 
found very few detects of low concentration NMC residues in these 

commodities supporting the previous understanding that beef, poultry, 

and pork are negligible contributors to dietary exposures to the NMC 

pesticides. The TDS data also includes samples of fish and eggs. The 

analytical results for these samples confirm those of the FDA 

surveillance monitoring program, namely, that fish and eggs contain 

negligible concentrations of NMC pesticides. 

3. NMC Pesticides Included in the Food Risk Assessment 

The N-methyl carbamate Cumulative Assessment Group (CAG) 

consists of 10 NMC pesticides. These 10 pesticides (along with their 

ChE—inhibiting metabolites and their associated RPFs) are listed in 

Table I.C-1. 

 Table I.C-1. N-methyl Carbamatesa and RPFs 

Chemical RPF (Oral) 

Carbaryl

b

 0.15 

Aldicarb 4 

Aldicarb sulfone (Aldoxycarb) 3.44 

Aldicarb sulfoxide 3.68 

Oxamyl 

(Index Chemical)b 1 

Formetanate hydrochloride 2.18 

Methomyl 0.67 

Carbofuran 

2.4 

3-Hydroxycarbofuran 

Propoxur 0.11 

Methiocarb 0.18 

Thiodicarb 0.89 

Pirimicarb 0.02 

a See “Carbamate Cumualtive Assessment Group: Availability” (USEPA, 

2004a).

b

 The carbaryl metabolite, 1-naphthol and the oxamyl metabolite, oxamyl 

oxime were analyzed by PDP, but not included in the dietary assessment 

since these compounds are not known to inhibit acetylcholinesterase. 

Section I.C – Page 63 of 277 
The above listed pesticides and metabolites were used as a 

“starting point” in determining which pesticides (and associated 

metabolites) would be considered in the food pathway of the NMC CRA. 

During the period since the issuance of the preliminary NMC CRA in 

August 2005, the Agency identified, and in some cases imposed, risk 

reduction measures on some of the major contributors to carbamate 

cumulative risk. The risk estimates presented in this revised NMC CRA 

reflect the risk mitigation measures identified for or taken on individual 

carbamates since FQPA was signed into law in August 1996. These 

mitigation measures generally reflect determinations of risk based on the 

single-chemical risk assessments. For all of the risk mitigation measures 

that are reflected in this document, EPA has either commenced the 

processes necessary to implement its selected risk mitigation or intends 

to commence the appropriate processes in the near future. Having 

already determined that the identified risk mitigations are warranted for 

the individual chemicals regardless of the cumulative assessment, EPA 

has chosen to reflect that mitigation in this assessment. Consequently 

pesticide-crop combinations that have been (or are being) cancelled or 

not considered eligible for reregistration3, do not have food uses, or have 

had significant and substantial label modifications were excluded from 

the 1994 to 2006 PDP residue data. As a practical matter, EPA 

determined that it would serve no purpose to include such uses in the 

cumulative assessment. Other than by adding a new issue that might 

delay action, adding these uses would not likely have any impact on the 

timing or substance of any cancellation decision relating to such uses. 

And given that the purpose of tolerance reassessment is to determine 

whether regulatory action should be initiated to modify or revoke 

tolerances that the Agency finds do not meet the safety standard of 

section 408, there seems to be little value in including uses in the 

assessment that will disappear regardless of their impact on cumulative 

risk, The critical issue for determining whether regulatory action will 

have to be initiated under section 408 is whether the uses that will 

remain result in unacceptable dietary risk. EPA recognizes, however, 

that to the extent that any risk mitigation measures are not subsequently 

implemented as envisioned in this revised NMC CRA, the cumulative 

assessment will have to be revised as necessary. 

Table in Appendix II.C.2 provides a summary of the PDP samples 

including the total number of laboratory analyses completed for the NMC 

pesticides and metabolites on each food commodity in the database. 

3

 Although residues resulting from uses that no longer exist were removed from 

this revised NMC CRA, EPA continues to incorporate violative residues in its cumulative 

risk assessments to reflect potential exposure to residue not consistent with registered 

label uses. These violative residues represent pesticide concentrations in PDP 

samples either above an already existing tolerance level (possibly due to agricultural 

practices not consistent with label instructions) or in a commodity for which no tolerance 

has been established. 

Section I.C – Page 64 of 277 
PDP analytical data for the above pesticides (and their associated 

metabolites4, where applicable) are being used in the NMC CRA 

assessment for the food pathway. Additional details regarding these 

pesticides and their inclusion in the assessment NMC CRA food pathway 

assessment are provided below. 

Aldicarb: Aldicarb or its sulfoxide and/or sulfone metabolites 

have been detected in more than 1% of the PDP samples of the 

following commodities: potato, sweet potato, grapefruit, and orange 

juice. It has been detected in less than 1% of the samples of the 

following commodities: green bean, cantaloupe, grape, orange, sweet 

corn, and poultry liver. PDP reports each of these compounds (all of 

which are acetylcholinesterase inhibitors) in terms of the parent or 

specific metabolite per se. The metabolites have higher molecular 

weights than the parent, but the RPF for aldicarb is based on the 

concentration of the parent chemical. Therefore, the metabolite RPFs 

were adjusted to account for the higher molecular weight of the 

metabolites compared to the parent chemical. The conversion of the 

metabolite concentrations to parent concentrations is important since the 

majority of detectable aldicarb residues found in PDP commodities are 

the metabolites. 

Carbaryl: Carbaryl has been detected in more than 1% of the 

PDP samples of the following commodities: apple, apple juice, apple 

sauce, peach, strawberry, pear, pear juice, grape, grape juice, green 

bean, orange, nectarine, cantaloupe, carrot, celery, cherry, cranberry, 

cucumbers, eggplant, grapefruit, orange, orange juice, pineapple, plum, 

prune, pork fat, pork meat, chicken meat, raisin, rice, spinach, sweet bell 

pepper, sweet pea, tomato (canned), and asparagus. It has been 

detected in less than 1% of the samples of the following commodities: 

banana, broccoli, cauliflower, heavy cream, lettuce, milk, sweet potato, 

tomato (fresh), watermelon, wheat, and winter squash. Significant label 

changes, primarily lengthened pre-harvest intervals and reduced 

application rates, occurred for apple, peach, and strawberry in the late 

1990’s (Lantz and Young, 2006). These label changes have resulted in 

lower residue levels for these three crops making only the 2000 and later 

PDP data relevant. Thus, for the revised NMC CRA, only PDP data for 

periods during 2000-2006 were used for apple, peach, and strawberry; 

whereas, the full PDP dataset (1994-2006) was used for all other 

commodities with carbaryl detects. 

Carbofuran: Carbofuran has been detected in more than 1% of 

the PDP samples of the following commodities: cucumber, kale greens, 

sweet bell pepper, and wheat. It has been detected in less than 1% of 

the samples of the following commodities: cantaloupe, grape, grape 

4

 The carbaryl metabolite, 1-naphthol and the oxamyl metabolite, oxamyl oxime, 

were analyzed by PDP, but not included in the dietary assessment since these 

compounds are not known to inhibit AChE. 

Section I.C – Page 65 of 277 
juice, green bean, spinach, watermelos, and winter squash. EPA has 

determined that all domestic carbofuran uses are ineligible for 

reregistration and this chemical is undergoing cancellation (USEPA, 

2006e). Thus, the revised NMC CRA includes only carbofuran uses on 

the following imported commodities for which tolerances are being 

retained: bananas, rice, sugarcane, and coffee5. 

Formetanate HCl: Formetanate has been detected in more than 

1% of the PDP samples of nectarines and pears. It has been detected in 

less than 1% of the samples of apples and oranges. Formetanate is 

analyzed by PDP using a single-residue method and not all PDP 

commodities have been analyzed using this method. The laboratory 

performing this analysis ceased participating in the PDP program after 

2001. Thus, PDP data are only available for formetanate on orange, 

pear, nectarine and apple through 2001. Late season uses on oranges, 

nectarines, and apples were cancelled and field trial data conducted by 

the registrant using only early-season applications demonstrate that no 

detectable residues are expected (USEPA, 2006f). Thus, formetanate 

residues on oranges, nectarines and apples are assumed to be 

negligible and were not considered in the revised NMC CRA. Only 

formetanate use on pear has been included in the assessment, and then 

only using data from 1997 and 1998. 

Methiocarb: Methiocarb has been detected in less than 1% of 

the PDP samples of cauliflower, cherries, cucumbers, and sweet bell 

peppers. Methiocarb has not been detected on any other PDP 

commodities. 

Methomyl: Methomyl has been detected in more than 1% of the 

PDP samples of the following commodities: apple, asparagus, broccoli, 

cantaloupe, cauliflower, celery, cucumbers, eggplant, grape, green bean, 

kale greens, lettuce, nectarine, peach, spinach, strawberry, summer 

squash, sweet bell pepper, and watermelon. It has been detected in less 

than 1% of the samples of the following commodities: carrot, orange, 

pear, tomato, and winter squash. PDP data for all crops except grape 

and strawberry were included in the revised NMC CRA. A voluntary 

cancellation request has been received by the Agency for methomyl use 

on grapes, and the strawberry use was voluntarily canceled by the 

registrant early in 2007. Thus methomyl residues on grapes and 

strawberries were not incorporated into the assessment. In an effort to 

better reflect NMC residues on foods as eaten, the PDP lettuce samples 

were divided into leaf and head where information regarding the lettuce 

variety was available. Separating the lettuce varieties ensured that leaf 

lettuce residues, which tend to be higher than head lettuce residues, 

5

 Sugarcane and coffee are not assumed to contain residues of carbofuran due 

to the extensive processing, purification, and refinement to which the commodities are 

subjected. 

Section I.C – Page 66 of 277 
were not inappropriately assigned to foods that contain head lettuce as 

an ingredient, as per the FCID recipe files. 

Oxamyl: Oxamyl (parent) has been detected in more than 1% of 

the PDP samples of the following commodities: cantaloupe, celery, 

cucumber, eggplant, lettuce, pear, potato, summer squash, sweet bell 

pepper, tomato and watermelon. It has been deteced in less than 1% of 

the samples of the following commodities: apples, green bean, orange, 

spinach, and winter squash. An oxamyl metabolite, oxamyl oxime, also 

detected in the PDP program, was not considered in the assessment 

since it does not inhibit acetylcholinesterase. 

Pirimicarb: Pirimicarb has been detected on less than 1% of the 

PDP samples of peach and sweet bell pepper. Pirimicarb has not been 

detected on any other PDP commodities. 

Propoxur: Propoxur has not been detected on any PDP 

commodities. 

Thiodicarb: Thiodicarb has been detected on less than 1% of 

PDP samples of pear. Thiodicarb has not been found on any other PDP 

commodities.6 

4. Food Commodities Included in the Food Risk Assessment 

The universe of foods included in the cumulative dietary exposure 

assessment is defined by the USDA CSFII 1994-96/1998. The CSFII 

food diary information is expressed in terms of food as consumed (e.g., 

pizza, apple pie, lasagna, etc.). These foods as reported in CSFII diaries 

are converted to food commodities (e.g., tomatoes, milk, wheat flour, 

beef, apples, etc.) using standard recipes. The recipe information used 

to break down the foods was developed jointly by EPA and USDA and is 

one module in the EPA’s Food Commodity Intake (FCID) database. 

Table in Appendix II.C.1 lists all of the FCID food commodities 

(translated from CSFII foods) in decreasing order of their relative per 

capita consumption by children 1-2 years old and children 3-5 years old 

while table in Appendix II.C.5 contains a complete listing of the FCID 

food commodities and food forms (e.g. “Cooked; Fresh or N/S; Cook 

Meth N/S”) in the DEEM-FCIDTM software that were included in this 

6

 Although the PDP analytical methods usually convert thiodicarb residues to 

methomyl, the majority of methomyl residues detected in PDP commodities are 

assumed to be the result of methomyl use rather than thiodicarb use. The basis for 

this assumption is that the number of registered uses for thiodicarb is much less than 

those for methomyl and pesticide usage information indicates very low thiodicarb use 

on food crops for which it is registered. Since methomyl residues resulting in the 

highest exposures are from food crops for which thiodicarb is not registered, the 

assumption that all PDP methomyl residues are due to methomyl use (rather than 

thiodicarb use) is not expected to significantly underestimate dietary exposure to 

thiodicarb. 

Section I.C – Page 67 of 277 
assessment. This table also includes summary information on the 

residue distributions that were prepared from the revised NMC CRA food 

residue database as input for each food form. The actual DEEM-FCIDTM 

input files and associated residue files will be made available on the 

internet or upon request via CD-ROM for any interested party. 

PDP has an extensive monitoring program that focuses on food 

commodities commonly consumed by children and includes a variety of 

fruits, vegetables, meat/poultry/pork products, dairy products, and grains. 

In all, 80 food commodities monitored by PDP are included in the revised 

NMC CRA. Food processing factors that reflect reduction or 

concentration of NMC pesticides in processed foods were applied to food 

commodities or specific pesticide-commodity pairs in the PDP program 

to extend these data for use on cooked and processed food/food forms 

in the analysis. Through the 80 foods commodities directly analyzed by 

PDP, the revised NMC CRA accounts for approximately 93% of the 

foods consumed by children 1-2 years of age. 

As mentioned previously, the PDP residue data were further 

extended to other commodities identified as reasonable for translation of 

pesticide residue data per Agency policy. That is, residue data on 

commodities which were analyzed by PDP were translated to similar 

food commodities with registered uses which were not analyzed by PDP. 

In this way, residues on foods accounting for an additional 1% of the per 

capita consumption of children 1-2 years of age were estimated using 

these translated PDP data. For example, cantaloupe melon residues 

are translated to honeydew melon and peach residues are translated to 

apricot. Translations were made using HED SOP 99.3 (USEPA, 1999b) 

as summarized in Table I.C-2. 

Section I.C – Page 68 of 277 
 Table I.C-2. Crop Translations for Pesticide Monitoring Data 

Commodity 

Analyzed Commodity translated to... Comments 

Potato Subgroup 1-C 

Carrot Subgroup 1-A or 1-C 

Head Lettuce Cabbage, Chinese cabbage 

Napa (tight headed varieties), 

Brussels sprouts, radicchio 

All have a head morphology best 

represented by lettuce. All are in 

Subgroup 5-A except radicchio (4-A). 

Broccoli Cauliflower, Chinese broccoli, 

Chinese cabbage bok choy, 

Chinese mustard, kohlrabi 

Broccoli better represents these 

heading, thickly stemmed and/or more 

branching cole crops than spinach 

does. 

Spinach Subgroup 4-A, Subgroup 5-B 

and Subgroup 4-B (except 

celery and fennel unless a 

strong case can be made) 

Celery and fennel typically are 

excluded since residues may be higher 

in these crops due to the whorled, 

overlapping petioles which may retain 

spray residues. 

Green Bean Subgroups 6-A and 6-B 

Soybean Subgroup 6-C 

Tomato or 

bell pepper 

Group 8 All are fruiting vegetables. 

Cucumber Subgroup 9-B All are cucurbit vegetables; residues in 

melon and pumpkin expected to be 

lower because of removal of rind 

Cantaloupe or 

Winter squash 

Subgroup 9-A and pumpkin 

Orange Group 10 Fruit will be peeled before analysis by 

PDP. 

Apple or Pear Group 11 All are pome fruits. 

Peach Group 12, except cherries 

(sweet and tart) 

All are stone fruits. 

Grape Kiwifruit Based on similar cultural practices. 

Wheat Group 15, except corn, rice, or 

wild rice 

All are small grain crops or closely 

related thereto, 

Milk Meat Metabolism study must indicate that 

residues in meat, fat, and meat-byproducts will likely be equal to or lower 

than residues in milk. If dermal use is 

allowed on beef cattle, then it must be 

permitted and used on dairy cattle as 

well. 

PDP has not analyzed eggs or fish, but surveillance monitoring 

data from FDA include extensive analysis of eggs and fish and indicate 

that NMC residues would not be expected to occur in significant amounts 

on these two foods. Consequently, residues in the revised NMC CRA 

were assumed to be zero. These foods account for about 2% of the per 

capita consumption of children 1-2 years old. 

Section I.C – Page 69 of 277 
PDP has analyzed high fructose corn syrup and found no NMC 

residues but has not analyzed any other sugar or syrup sources. The 

FDA TDS has analyzed refined sugar and maple sugar and found no 

NMC residues in 46 market baskets surveys (FDA, 2007b). Knowledge 

of the highly refined nature of sugars and syrups supported by the limited 

residue data mentioned above is the basis for assuming that negligible 

residues of NMC pesticides occur in sugars and syrups. Therefore, 

residues were assumed to be zero for those foods derived from 

sugarcane, sugar beet, and maple. These foods, in total, account for 

about 2% of the per capita consumption by children 1-2 years old. 

In summary, food forms, not included in the current assessment, 

account for only slightly more than 2% of the per capita consumption by 

children 1-2 years of age and the revised NMC CRA accounts for and 

incorporates almost 98% of the per capita food consumption by 1-2 year 

old children. No one single food form excluded from the assessment 

accounts for a significant portion of the consumption. Most of the foods 

that are not included in the assessment are considered very minor 

consumption items and include such commodities as mango, sunflower 

seed, peppermint, and pomegranate. 

5. Method of Estimation of Cumulative Food Risk 

The cumulative dietary exposure was estimated using the Dietary 

Exposure Evaluation Model-Food Commodity Index Database (DEEMFCIDTM) software (Exponent, 2007). Estimation of dietary exposure was 

accomplished by combining distributions of pesticide concentrations on 

foods from USDA PDP with distributions of food consumption from 

USDA CSFII. The primary advantage of using distributions of pesticide 

concentrations and consumption values to assess cumulative exposure 

is that distributions of exposure values are obtained that represent a 

distribution of realistic scenarios of exposure that describe both 

probabilities and magnitudes of multi-chemical cumulative exposure 

through the food pathway. 

a. Overview of Single-Chemical Dietary Risk Assessment 

Process 

The dietary exposure models currently used by the Agency for 

single-chemical assessments rely upon the food consumption data 

provided by CSFII consumption survey respondents. For any particular 

respondent’s reported consumption, a Monte-Carlo simulation is 

performed in which a series of randomly-drawn residue concentrations is 

selected for each food commodity. The exposure from each food 

commodity is calculated by multiplying each randomly-selected residue 

value by the amount consumed, and the total daily exposure is 

calculated by summing exposures within each individual across all 

Section I.C – Page 70 of 277 
commodities reported consumed by that individual, as depicted below in 

Equation (1). 

n 

Dietary Exposure =∑Consumptioni × Unit Conversion × Residuei (1) 

(mg ai/kg bwt) i 1 (gm food/kg bwt) (1kg food/1000 gm food) = (mg ai/kg food)

where n = number of unique foods (or food commodities) consumed

This repeated sampling of pesticide residues is performed 5,000 

times for each individual’s reported food consumption and produces a 

distribution of 5,000 potential exposure estimates for each individual 

respondent. The exposure software keeps track of the total daily 

exposures for each simulated person-day and applies the corresponding 

survey weights to project the simulated person-days to a per capita level. 

It is from this distribution of total daily exposures that the exposure at any 

given percentile (e.g., 95th, 99th, or 99.9th) can be estimated. 

b. NMC Food Residue Database 

Equation (1) above is, in principle, fairly basic: it is the task of 

performing and keeping account of these necessary calculations --

particularly for a multi-chemical, multi-pathway cumulative assessment -- 

that can be cumbersome, complex, and tedious. The residue data used 

in this assessment consist of nearly 790,000 records of analytical data 

and sample information. The processing factors account for several 

thousand additional records of information. Calculations and algorithms 

are complicated by the fact that they must be done in such a manner that 

the risk assessor can “work backward” from the cumulative assessment 

results to identify contributors -- and their relative contributions -- to the 

overall cumulative risk, and such contributors must be able to be 

identified on a crop, pesticide, or crop-pesticide combination basis. 

Because of these issues, all the data manipulations performed as part of 

this cumulative assessment were conducted outside of the DEEMFCIDTM exposure software using relational database techniques in MS 

Access. The database used to conduct these cumulative residue 

calculations consists of, among other things, four major data tables7,8 as 

follows: 

7 By maintaining all of the calculation inputs in separate tables in the database, 

it is possible to modify inputs or perform sensitivity analyses by simply replacing or 

adding data to the appropriate table. For example, a specific chemical can be omitted 

from the entire process by assigning it a value of zero in the RPF table. Specific 

chemical-commodity combinations can be selectively omitted by entering a zero value 

for that pair in the processing factor table. Specific food commodities can be eliminated 

from the assessment by removing the entries from the translation table. 

Section I.C – Page 71 of 277 
1) Residue Data: contains essentially all of PDP sample and 

analyses data for NMC pesticides for the years 1994-2006. The 

table in Appendix II.C.2 contains summary information of PDP 

residue data on the NMC pesticides. 

2) Processing Factors: contains all relevant processing factors 

for specific food form/chemical combinations. The table in 

Appendix II.C.3 is extracted from these data. 

3) Relative Potency Factors: contains the relative potency 

factors for all chemicals of interest. This table also contains the 

chemical-specific FQPA safety factor and inter-species uncertainty 

factor, which are also used to adjust the relative potencies of the 

NMC residues. 

4) Bridging (Translations): provides bridging links or 

translations between PDP commodity codes, such as AP (for 

“APple”) and all corresponding DEEM-FCIDTM food forms, such as 

Apple, fruit with peel; Uncooked; Fresh or N/S; Cook Meth N/S. 

This table also translates surrogate PDP commodities for other 

food forms, e.g., orange residue data are assigned to lemon food 

forms as described in the table found in Appendix II.C.4. 

These four tables are linked through common fields, including 

pesticide codes and commodity codes. Calculation queries are coded 

into the MS Access database so that all the pertinent PDP samples 

records can be extracted, each calculation outlined above can be 

performed, and the results can be sorted and output in various formats 

for further analysis. A cumulative residue calculation query performs the 

cumulative calculations (described in the next section), extracting the 

various parameters needed from the four tables described above. The 

calculation is performed on all of the food samples that are of interest 

and the results are compiled in text files containing the cumulative 

distributions for each food commodity of interest. Each text file contains 

a header with sample information (number of values, number of detects, 

number of zeros, average of residues) and all cumulative residue values 

for a single food form, sorted in descending order. This permits the 

complete history of each cumulative residue value in the exposure 

assessment to be traced back to its origins. In this way, all of the sample 

collection and analytical information associated with a given PDP sample 

and all arithmetic adjustments used to produce a cumulative residue 

estimate can be traced to permit sensitivity analyses or food commodity 

contribution analyses to be performed. 

8

 The NMC food residue database is based on the same design as the one used 

for the OP CRA (USEPA, 2006a). 

Section I.C – Page 72 of 277 
c. Manipulation of Residue Data for Exposure Assessment 

Equation (1) above describes the fundamental algorithm used to 

estimate exposure from dietary sources. In the case of a cumulative 

assessment in which it is important to account for multiple pesticides 

within a food commodity, the formula is modified to account for these 

multiple chemicals. As seen in Equation (2) below, the residues are 

expressed in (i.e., converted to) index-chemical equivalents and 

Equation (1) re-cast as follows: 

n 

Dietary Exposure = Consumptio n × Unit Conversion × Residue (2) IE ∑ i (1 kg food/1000 gm food) IE i 

(mg ai/kg bwt) i=1 (gm food/kg bwt) (mg ai/kg food) 

where n = number of unique foods (or food commoditie s) consumed 

Two changes in terms are evident in this equation which reflects a 

multi-chemical (cumulative) approach: the term “Residuei” is replaced 

with “ResidueIE,” (for index-equivalent residue, or residue expressed in 

terms of the index chemical oxamyl) and the term “Dietary Exposure” is 

replaced with the term “Dietary ExposureIE” (for index equivalent dietary 

exposure). More specifically: residues (and the resulting estimated 

dietary exposures) are represented in this new equation in terms of the 

index chemical (for the NMCs: oxamyl). This re-expression of residues 

in terms of index chemical equivalents is a fundamental principle of 

cumulative risk assessment and is used throughout this and all of OPP’s 

cumulative assessments. Such re-expression of residues in terms of the 

common index chemical is performed through the use of the Relative 

Potency Factor (RPF)9 described (and derived) in Chapter B of this 

document. More specifically: the concentration of each pesticide in a 

given PDP food commodity sample is adjusted by multiplying that 

concentration by a RPF to obtain the equivalent residue expressed in 

terms of the index chemical. This new calculated residue is the Index 

Equivalent Residue (ResidueIE) appearing in the above equation and 

the dietary exposure estimate resulting from combining ResidueIE and 

consumption is the Index Equivalent Exposure (Dietary ExposureIE)

The following two-step procedure provides additional detail with 

respect to how this calculation is performed for an individual PDP 

sample. This process is repeated for each and every PDP sample 

included in the food assessment. 

9

 The RPFs are also adjusted to account for the additional sensitivity of children 

compared to adults and humans compared to rats based on the chemical-specific 

FQPA and inter-species uncertainty factors, respectively. If additional toxicity data to 

quantify these safety factors are not available or lacking, a default value of 10 is 

assigned to each of these safety factors. Refer to Section B for details regarding the 

calculation of chemical-specific RPFs, FQPA safety factors, and inter-species 

uncertainty factors

Section I.C – Page 73 of 277 
Step 1: For each pesticide in the cumulative assessment group, an 

Index Equivalent Residue (ResidueIE) is calculated for every 

residue in a particular PDP sample by multiplying the residue value 

by the chemical-specific processing factor (PFi) for the food form of 

interest and the chemical-specific Relative Potency Factor (RPFi): 

ResidueIE i = Residue × PFi × RPFi (3) 

where i indicates an individual pesticide in the cumulative assessment group 

Step 2: The cumulative ResidueIE for an individual PDP sample is 

then calculated by summing the individual ResidueIEi of all the 

pesticides in the cumulative assessment group found in that 

sample: 

n 

Cumulative Residue IE = ∑ Residue IE i (4) 

i =1 

where n = the number pesticides in the cumulative assessment group 

The above-described procedure is critical in maintaining sample-bysample integrity. By summing residues expressed in index-chemical 

equivalent concentrations on a sample-by-sample basis, capturing the 

co-occurrence of residues on the same sample is assured, and the ability 

to appropriately account for certain pesticides to be used (or not be 

used) on the same commodity is concomitantly enhanced. 

These distributions of cumulative residues (expressed in terms of 

index chemical equivalents) are treated as distributions of representative 

residues and linked to all appropriate food forms. Finally, as described 

previously, these cumulative residues -- now expressed in terms of 

index-chemical equivalents -- are combined with a distribution of daily 

food consumption values via a probabilistic, Monte Carlo simulation 

using the DEEM-FCIDTM software. The probabilistic combination of food 

consumption distributions and food residue distributions produces 

distributions of estimated exposures for OPP’s standard age groups

(Infants < 1, children 1-2, children 3-5, children 6-12, youths 13-19, 

adults 20-49, adults 50+ years old, and females 13-49 years old). This 

process has been described in public documents and proceedings of the 

FIFRA Scientific Advisory Panel (FIFRA SAP, 2000a). 

d. Assumptions 

The input residue data were drawn from the PDP data base. The 

PDP program tests different commodities for various pesticides in 10 

states throughout the U.S. The residue data from 1994 to 2006 were 

Section I.C – Page 74 of 277 
used in this assessment unless otherwise noted. The assumptions in 

this revised NMC CRA, which are summarized below, are essentially 

identical to those used in the preliminary NMC CRA. 

1) Although PDP has conducted single-unit sampling for limited 

crops (e.g., individual apple and pear samples) since 1998, only the 

residue data from composite samples (e.g., 10 pounds of apples or 

pears) were utilized in this assessment. Since a single composite 

sample can contain several individual servings of some foods, it is 

implicitly assumed that all these single servings have residues no more 

or less than the composite residue (average value). For this revised 

NMC CRA, it is assumed that residues reported on composite 

homogenates adequately reflect the residues in any given single serving 

contained in that homogenate. Therefore, no attempt was made to 

“decomposite” residue values to simulate residues that might be present 

in the single servings contained in the PDP composite sample. 

2) PDP generally uses multi-residue methods to simultaneously 

analyze food commodity samples for several pesticides in single 

sample10. However, occasionally, for various reasons, not every sample 

is analyzed for every single pesticide. In instances where a pesticide is 

not analyzed in a sample, the pesticide is assumed to have a residue of 

zero. Although not every single pesticide is analyzed on every sample, 

PDP attempts to analyze for pesticides that are registered on the food 

commodity of interest. For each pesticide, generally only a small 

percentage (less than 10%) of the samples of a single commodity is not 

analyzed for all residues. 

3) All residue analyses are subject to the limitations of the 

sensitivity of the analytical methods. Many of the samples analyzed are 

reported as being below the limit of reliable detection of the analytical 

method. It is usual practice in Agency single chemical assessments to 

assume that residues in non-detectable samples are present at one-half 

the limit of detection (LOD) of the analytical method in samples that were 

potentially harvested from treated fields. Thus, for purposes of 

estimating residues in samples reported as less than the LOD, a 

proportion of the samples equal to the estimated percent crop treated is 

assigned a residue level of one-half LOD and the remaining samples, 

which are assumed to come from untreated crops, are assigned a 

residue value of zero. This procedure becomes problematic for a 

cumulative assessment. It is not enough to simply estimate the percent 

crop treated for each of the pesticides in the cumulative assessment; it is 

also important to consider the potential for co-occurrence of residues of 

multiple residues on the same crop. In the case of the NMC pesticides, 

10 The table in Appendix II.C.7 contains summary information with respect to the 

co-occurrence of NMC pesticide residues in the PDP commodity samples. 

Section I.C – Page 75 of 277 
we assessed the impact of incorporating one-half LOD values for nondetects in the cumulative assessment. The food portion of the NMC 

assessment was conducted using the two extreme default assumptions: 

all non-detects = 0, and all non-detects = 1⁄2LOD for the chemical most 

frequently detected in each PDP commodity. The most prevalent 

detected chemical was selected because it is reasonable to assume that 

chemical would also have the greatest number of residues below the 

LOD. The result of this comparison confirmed that the assumption of 

zero values for all non-detects did not significantly impact on the results 

at the higher end of the cumulative exposure distributions. For additional 

information regarding this sensitivity analyses, refer to the Risk 

Characterization chapter. 

4) The sample-by-sample method of summing residues relies 

on the PDP sampling procedures to adequately capture the temporal and 

geographic variations in agricultural practices and pesticide use. This 

procedure recognizes that the PDP sampling protocols are designed in 

such a way as to reflect the foods available to the public for consumption 

in different regions of the country throughout the year. 

5) This assessment uses PDP residue data collected over a 13 

year period, (1994-2006) to maximize the number of food commodities in 

the assessment and to minimize the sensitivity of exposure estimates to 

year-to-year variations in pesticide usage (e.g., atypical pesticide 

residues in a commodity due to unusual pest pressures). However, 

including pesticide residues over an extended period of time introduces 

an issue related to temporal correspondence of pesticide residues in 

various food commodities. Since PDP cannot sample every commodity 

every year, OPP relies upon residues in food samples collected in 

different years. In some cases, the residues in one food may be only 

one or two years older than residues in another food. In other cases, the 

food residues may have been sampled several years apart. Temporal 

correspondence of pesticide residues may be important to consider since 

acute dietary assessment consider foods eaten over relatively short time 

period, such as 24 hours. For example, it is not readily obvious if it is 

appropriate to model 24-hour dietary exposure based on pineapples 

grown in 2002 and cranberries grown in 2006. 

6) In chemical-specific dietary exposure assessments, OPP 

routinely translates residue data from one food commodity to related 

ones if the pesticide use patterns are similar on these commodities. For 

example, data on cantaloupe are often used as surrogate data for 

honeydew and other melons. For a cumulative assessment, in which a 

grower has a choice of several chemicals from the cumulative 

assessment group, these translations of data become more difficult. In 

the revised NMC CRA, translations of the residue data were made using 

Section I.C – Page 76 of 277 
the surrogation scheme in HED SOP 99.3 (USEPA, 1999b) to ensure 

representation of the maximum number of commodities possible. The 

cross walk between crops is presented in the table in Appendix II.C.4. 

6. Estimation of Acute Exposure Using DEEM-FCIDTM Software 

Residue distribution files were entered in the DEEM-FCIDTM 

software for a Monte Carlo analysis. The Monte Carlo analysis was 

conducted by an iterative process of multiplication of residue 

concentrations on foods, expressed in index chemical equivalents, by 

one-day consumption of these foods, as reported by all individuals in 

CSFII. This process used all individuals reporting in the consumption 

survey for both days of the survey and the exposures were calculated as 

mg/kg body wt/day. 

DEEM-FCIDTM uses publicly available USDA/EPA recipes for 

conversion of foods (e.g., lasagna) reported on an “as eaten” basis in the 

survey to the recipes’ component commodities (e.g., tomatoes, wheat, 

beef, milk, etc.) for which residue data are available. The use of DEEMFCIDTM for dietary exposure analysis has been described previously in 

public, technical briefings on pesticide risk assessments for pesticides in 

the re-registration process as well as to the FIFRA Scientific Advisory 

Panel (SAP). The detailed functioning of DEEM-FCIDTM has also been 

described in previous SAP presentations (FIFRA SAP, 2000a). 

7. Results 

Table I.C-3 summarizes the DEEM-FCIDTM-generated estimated 

dietary (food only) exposures from the revised NMC CRA. 

Table I.C-3. Summary of Probabilistic Analysis of Distribution of the Cumulative 

Dietary Exposures and Risk from Use of N-Methyl Carbamate Chemicals on 

Food Cropsa 

Population 

U.S. Population 

All infants < 1 yrs 

Children 1-2 yrs 

Children 3-5 yrs 

Children 6-12 yrs 

Youth 13-19 yrs 

Adults 20-49 yrs 

Adults 50+ yrs 

Females 13-49 yrs 

95th Percentile 

Exposure 

(mg/kg) MOE 

0.0004 404 0.0023 79 0.0115 15 >99.9 

0.0005 342 0.0024 74 0.0106 16 >99.9 

0.0013 141 0.0051 35 0.0229 7.9 99.848 

0.0010 185 0.0044 40 0.0209 8.6 99.870 

0.0006 323 0.0028 63 0.0145 12 >99.9 

0.0003 576 0.0017 106 0.0098 18 >99.9 

0.0001 1278 0.0008 236 0.0042 42 >99.9 

0.0002 1035 0.0009 193 0.0044 40 >99.9 

0.0004 505 0.0019 97 0.0101 17 >99.9 

99th Percentile 

Exposure 

(mg/kg) MOE 

99.9th Percentile 

Exposure 

(mg/kg) MOE 

Percentile 

at which 

MOE=10 

a

Exposure is in mg/kg/day of oxamyl equivalent residues. 

Section I.C – Page 77 of 277 
Exposures and MOEs (Margins of Exposures) are presented for 

the U.S. General population and the following sub-populations: infants < 

1 years, children 1-2 years, children 3-5 years, children 6-12 years, youth 

13-19 years, adults 20-49 years, adults 50+ years and females 13-49 

years. In addition, the percentile at which the MOE equals 10 is 

provided. The summary results are provided for three percentiles in the 

estimated distribution of exposures: the 95th percentile, 99th percentile, 

and 99.9th percentiles of exposure. The exposure values are expressed 

in terms of index-chemical equivalents. MOEs range from 7.9 (children 

1-2 years) to 42 (adults 20-49 years) at the 99.9th percentile of exposure. 

For children 1-2 years, an MOE of 10 is reached at the 99.848th 

percentile; for children 3-5 years, this MOE is reached at the 99.870th 

percentile. 

Table I.C-4, Figure I.C-1 (for children 1-2 years old) and Figure 1.C2 (for children 3-5 years old) provide additional information with respect 

to the contributors (in terms of crops, pesticides, and crop/pesticide 

pairs) to exposure. Appendix II.C.6 provides additional detailed 

information regarding the relative contribution of all crop/pesticide pairs 

for children 1-2 years old, the highest exposed sub-population. 

Table I.C-4. Relative Exposure Contribution from Foods for 

Children 1 to 2 Years Old (At 99.8th Percentile of Exposure and Above) 

Food Percent 

Potato 28.4% 

Peach 14.4% 

Strawberry 11.1% 

Spinach 10.4% 

Watermelon 6.7% 

Pear 5.3% 

Cucumber 3.4% 

Cantaloupe 3.2% 

Grape 3.0% 

Bean, snap 2.4% 

Nectarine 2.2% 

Orange 1.7% 

Apple 1.6% 

Lettuce, head 1.3% 

Total 94.8%a 

a

No single remaining commodity contributes more than 1% 

to the total exposure. 

Section I.C – Page 78 of 277 
Figure I.C-1. Relative Contribution of Crop/Chemical Pairs to Top 0.2 Percentile 

of Cumulative Distribution for Children 1-2 

Sum of H X F 30% 

25% 

PARENTPESTICIDE 

20% Thiodicarb 

Pirimicarb 

Oxamyl 

Methomyl 15% Methiocarb 

Formetanate hydrochloride 

Carbofuran 

10% Carbaryl 

Aldicarb 

5% 

0% 

Food 

Figure I.C-2. Relative Contribution of Crop/Chemical Pairs to Top 0.2 Percentile 

of Cumulative Distribution for Children 3-5 

Sum of H X F 30% 

25% 

PARENTPESTICIDE 

20% Thiodicarb 

Pirimicarb 

Oxamyl 

15% Methomyl 

Methiocarb 

Formetanate hydrochloride 

Carbofuran 

10% Carbaryl 

Aldicarb 

5% 

0% 

Potato

Strawberry

Peach

Watermelon

Cantaloupe

Cucumber

Spinach

Nectarine

Pear

Lettuce, head

Grape

Apple

Bean, snap

Lettuce, leaf

Cabbage

Orange

Cherry 

Potato

Peach

Strawberry

Spinach

Watermelon

Pear

Cucumber

Cantaloupe

Grape

Bean, snap

Nectarine

Orange

Apple

Lettuce, head

Apricot

Honeydew melon

Cabbage

Cherry

Pepper, bell

Lettuce, leaf 

Food 

Section I.C – Page 79 of 277 
In evaluating exposure through food, OPP concludes that a few 

uses of NMC pesticides on food crops generally play a larger role in the 

results of the assessment. These include aldicarb on potato; carbaryl on 

peach and strawberry; and methomyl on cantaloupe, watermelon, peach, 

spinach, and strawberry. However, evaluation of the total risk from 

exposure to NMCs in foods indicates that the cumulative MOEs from 

exposure to NMCs do not raise a concern. 

In addition to exposure estimates generated by DEEM-FCIDTM 

software, the Agency has conducted a similar assessment using LifeLine 

software which is also publicly available. Similar exposure estimates to 

those generated by DEEM-FCIDTM were obtained with this software. It is 

important to recognize that exposure estimates between DEEM-FCIDTM 

and LifeLine are not expected to be identical since there are important 

design differences relating to different reference populations, binning 

methodologies by which each model groups individuals, reference 

population bodyweights, and model (or sampling) weights. Never-theless, exposure estimates agree to within several percent. The operation 

of this software and the exposure estimates produced by LifeLine are 

described in Appendix II.C.8. 

Finally, it is important to note that the exposure estimates and 

associated MOEs presented in Table I.C-3 represent the Agency’s 

“baseline” assessment described in this on exposure through the food 

pathway. There are a number of assumptions that are reflected in this 

baseline assessment that might affect exposure and MOE estimates that 

are important to consider in evaluating risks associated with this 

pathway. Specifically: 

 The baseline assessment presented here represents 

virtually all available PDP data (1994-2006)11 and thus 

represents an average exposure over this time period. The 

Agency has performed an equivalent assessment using just 

the most recent years of PDP (2002-2006), the result of 

which are discussed in Chapter G. To the extent that more 

recent PDP pesticide residues more accurately reflect 

current (and future) conditions, exposure estimates 

conducted with only this more recent data might be more 

reflective of the current (and future) risk situation. 

 The baseline assessment presented here assumes that 

PDP samples with non-detectable residues do not contain 

11 Although additional PDP data are available for 1992 and 1993, these data 

represent the first years of the program which are limited in scope, completeness, and 

representativeness. 

Section I.C – Page 80 of 277 
residues (i.e., residues are zero). In reality, residues may be 

present and – to the extent they are – exposures presented 

in Table I.C-3 may be underestimates of actual exposure. 

 For the baseline assessment, carbofuran was assumed to 

be present only on commodities with import tolerances 

(banana, rice, coffee, and sugarcane) since the Agency has 

determined that all domestic uses are ineligible for 

reregistration (USEPA, 2006e). Pesticide residue 

concentrations on uses that are being cancelled were 

assumed to be zero to represent future carbofuran use. 

 The DEEM-FCIDTM model does not separate eating events 

by time and instead sums all eating (and thus exposure) 

events that occur over a 24-hour time frame. For this 

Revised NMC CRA, no account is made for the potential 

reversal of acetylcholinesterase inhibition that would be 

expected to occur if two or more exposure events are 

separated in time to such a degree that substantial recovery 

of AChE inhibition occurs. Such an assumption would be 

expected to over-estimate risk to the extent that some 

recovery of AChE activity would occur between exposure 

occasions. 

To account for and evaluate the effect of the above-listed factors on 

the baseline exposure and risk estimates, the Agency has performed 

additional analyses which represent “extensions” (sensitivity analyses) 

to this baseline assessment and permit the Agency to better evaluate 

how these assumptions and policy choices might affect its exposure and 

risk estimates. These activities and their results are more fully described 

in the Risk Characterization chapter of this document. 

8. Summary 

The cumulative dietary exposure due to the use of NMC pesticides 

on food crops was assessed using residue monitoring data collected by 

PDP. Oxamyl was selected as the index chemical and the residue 

values for the other NMC chemicals were converted to index chemical 

equivalents using the Relative Potency Factor method. Residue data 

were collected on approximately 80 food commodities monitored by PDP 

between the years of 1994 and 2006. Food processing factors were 

applied to specific chemical-commodity pairs to extend these data for 

use on more food forms (e.g. boiled, baked, fried, etc.). When 

appropriate, the PDP residue data were further extended to similar 

commodities which were not sampled in PDP. Food consumption data 

Section I.C – Page 81 of 277 
were obtained from the USDA Continuing Survey of Food Intakes by 

Individuals (CSFII), 1994-96/1998. 

The residue data were compiled as distributions of cumulative 

residues of index chemical equivalents that were, after adjustment for 

processing, summed on a sample-by-sample basis. These residue 

distributions were combined with a distribution of daily food consumption 

values via a probabilistic procedure to produce a distribution of potential 

exposures for the general U.S. population and various sub-populations. 

The estimated exposures (expressed in oxamyl-equivalents) are shown 

in Table I.C-3. An analysis of the relative exposure contribution from 

foods for children 1 to 2 years at or above the 99.8th percentile of 

exposure is presented in Table I.C-4. 

The results of the baseline assessment indicate that all 

subpopulations, except children 1-2 and 3-5 years of age, exceed an 

MOE of 10 at 99.9th percentile of exposure. However, an MOE of 10 was 

reached for children 1-2 and 3-5 at the 99.848th and 99.870th percentiles 

of exposure, respectively. EPA concludes that the cumulative MOEs 

from exposure to NMCs in foods do not raise a concern. (Refer to 

Chapter G on Risk Characterization for a complete discussion of the 

rationale for this conclusion.) 

Section I.C – Page 82 of 277 
D. Residential NMC Cumulative Risk 

1. Introduction 

The Office of Pesticide Programs (OPP) employed a calendarbased model (CalendexTM) to address the temporal aspects of the 

residential use of pesticides. A calendar-based approach provides the 

ability to estimate daily exposures from multiple sources over time to an 

individual and is in keeping with two key tenets of aggregate risk 

assessment: 1) that exposures -- when aggregated -- be internally 

consistent and realistic; and 2) that appropriate temporal and geographic 

linkages or correlations/associations between exposure scenarios be 

maintained. The CalendexTM software allows OPP to delineate the 

critical timing aspects of seasonal uses of NMC insecticides that result in 

exposure to pesticides during the year. Calendex also enables OPP to 

identify potential risks caused by co-occurrence of exposures from 

multiple routes and pathways (e.g., near simultaneous same-day 

exposures through drinking water and residential uses). This includes 

the exposure from home lawn and garden treatments and pesticides 

used on golf courses. 

In the revised NMC CRA, the temporal aspects of residential 

pesticide applications were evaluated by relying on information from a 

variety of sources including registered labels, survey data, and publicly 

available information provided by State Cooperative Extension Services. 

These information resources were comprehensively used to identify 

information such as frequency of applications and the seasonal 

appearance of target pests. OPP also relied on a national pesticide 

usage diary survey delineating day of application of registered pesticide 

products. This longitudinal survey also captures incidence of cooccurrence of residential uses of the same pesticide or similar pesticides 

on the same day. The survey was conducted by the National Family 

Organization on behalf of the Residential Exposure Joint Venture 

(REJV). Additional details regarding all use information used in the 

revised NMC CRA is presented in Appendix II.D.1. 

In addition to the use practice and timing information described 

above, information regarding residues, exposure and standard exposure 

factors (such as breathing rates and activity duration) are required. In 

nearly all cases, the residential exposure scenarios in this assessment 

were developed using proprietary residue and exposure data. Exposure 

factors such as breathing rates and durations of time spent outdoors 

were taken from various sources including Agency’s Exposure Factors 

Handbook (USEPA, 1997a). For the majority of residential uses 

Section I.D – Page 83 of 277 
considered in this assessment, the full range of exposure values – 

expressed as uniform, log-normal, empirical, or cumulative distributions – are used, where appropriate, rather than relying on point 

estimates. While the dietary and drinking water assessments address 

only the oral exposure route, the residential assessment considers the 

dermal and inhalation exposure routes as well as the oral route, which is 

based on the mouthing behavior of young children. 

2. Scope of Regional Assessments 

Three NMC pesticides in this cumulative assessment have 

residential uses: carbaryl, methiocarb, and propoxur. More specifically, 

the residential uses included in this assessment are: 

• carbaryl on turfgrass (residential lawns and golf courses); 

• carbaryl on fruit trees, vegetable and flower gardens, and 

ornamental trees and shrubs; 

• carbaryl impregnated pet collars; 

• propoxur impregnated pet collars; 

• methiocarb use in ornamental gardens as a snail and slug bait. 

All other N-methyl carbamate residential uses are considered minor 

contributors to exposure and therefore were not included in this 

assessment.12 Additionally, the Agency recently received voluntary 

cancellation of all propoxur indoor spray uses that may result in nonoccupational exposure for children (USEPA, 2007c). Therefore, the 

12 For example, propoxur is registered for several residential uses including; 

outdoor use as a crack and crevice and spot spray, and indoor uses as a containerized 

bait, paste, shelf paper, or strip. For the outdoor crack and crevice and spot spray 

uses, applications are typically made along window sills or in pavement cracks; to ant 

hills and wasp nests. Additionally, the labels for the shelf paper, paste, and strip 

products restrict use to inaccessible areas. For instance, the paste products are 

packaged in a pre-filled disposable syringe. Applications are made by pushing the 

syringe plunger into cracks and crevices in counters, tables, shelving, drawers, under 

sinks, and around pipes, stoves, and electrical boxes. The propoxur shelf paper 

products are used in sewers, cabinets, or storage areas around garbage, under sinks, 

in basements, or other secluded areas where insects congregate. The containerized 

bait, paste, strip, and shelf paper products, in addition to the outdoor spot uses, are 

expected to result in very low exposure and therefore are not included in this 

assessment. Specifically, since the shelf paper, paste and strips are used only to 

inaccessible areas; children’s dermal or hand-to-mouth exposure is not expected. 

Because the bait is packaged in a child-proof container, use in and around the home 

also is expected to result in negligible exposure. Additionally, the use of carbaryl for 

oyster beds in Washington State was assessed in the carbaryl RED. Since the oyster 

bed use is restricted to one area of the country, and since the assessment of this use 

indicated low exposure and risk, this use is considered to be a minor contributor to 

overall risk and therefore is not included in the revised NMC CRA. 

Section I.D – Page 84 of 277 
propoxur indoor crack and crevice scenario, included in the preliminary 

NMC CRA, has been removed from this assessment. 

In this revised NMC CRA assessment, only the Southeast region of 

the United States is considered (see Figure I.D-1 below). While insect 

growth may slow during the winter months in the South, unlike other 

regions of the country, there is no period of dormancy. Since the 

growing season is longer in the South and the associated pest pressures 

are therefore greater, this assessment provides a worst case estimate of 

exposure. 

Figure I.D-1. Pesticide Cumulative Assessment Regions 

3. Residential Scenarios 

The Residential Scenarios addressed in this document represent 

critical NMC uses that have the potential for significant exposure when 

considered in a cumulative assessment. A brief description of each of 

the use scenarios covered in this assessment is provided below. 

a. Lawn Care 

Carbaryl (adult applicator and adult and child postapplication exposures) 

Section I.D – Page 85 of 277 
Carbaryl may be applied by homeowners or professional lawn care 

operators (LCO). Granular, dust, and sprayable applications can be 

made by consumers using push-type spreaders, ready-to-use (RTU) 

shaker cans, and hose-end sprayers respectively. OPP has recently 

amended the use pattern of carbaryl (see Table II.A). The label changes 

restrict broadcast lawn application to granular formulations. However, 

spot treatments with the liquid formulations are permitted. Liquid 

products will be packaged in ready-to-dispense containers that treat 

areas of no more than 1000 square feet. The current assessment 

incorporates the recent label changes for the use of carbaryl on 

residential lawns. 

Dermal and inhalation exposure was assessed for homeowners 

loading, and applying carbaryl to residential lawns. This assessment also 

considered dermal post-application exposure for adults and children 

contacting treated lawns. Additionally, oral non-dietary exposure (handto-mouth) was considered for toddlers transferring treated-turf residues 

from their hands to their mouths. Post-application exposure was 

assessed for the granular broadcast use of carbaryl but not for the liquid 

spot treatment uses. 

b. Vegetable Gardens 

Carbaryl (adult applicator and adult and teenagers postapplication exposures) 

Dust, liquid, and granular formulations of carbaryl may be applied 

to garden vegetables using RTU shaker cans, handwands, trigger pump 

sprayers or hose-end sprayers. (Note that recent label changes require 

all home garden products formulated as either a dust or a granular to be 

packaged in ready-to-dispense containers (see Table II.A). Dermal and 

inhalation exposure was assessed for homeowners mixing, loading, and 

applying carbaryl to vegetable garden plants based on data for the liquid 

and dust formulations. The use of liquid and dust data for granular 

applications is conservative and results in higher estimated exposure. 

Post-application dermal exposure also was considered for adults and 

teenagers re-entering treated gardens to harvest vegetables or perform 

maintenance tasks (such as weeding). 

c. Ornamentals 

Carbaryl (adult applicator and adult and teenager postapplication exposures) 

Carbaryl may be applied as a dust to ornamental plants using a 

RTU shaker can. Note that recent label changes require all home 

garden products formulated as either a dust or a granular to be 

packaged in ready-to-dispense containers. Carbaryl may also be 

Section I.D – Page 86 of 277 
sprayed on ornamentals (flowers, trees and shrubs) using a small 

handwand or hose-end sprayer. The current assessment evaluated 

exposure for homeowners applying liquid formulations of carbaryl via the 

handwand sprayer since chemical-specific applicator data suggests that 

the handwand sprayer resulted in similar yet higher exposure than the 

hose-end sprayer. The data used to assess this scenario account 

for homeowners applying sprays below the waist as well as overhead. 

Dermal and inhalation exposure was assessed for homeowners mixing, 

loading, and applying carbaryl to ornamental garden plants. Postapplication dermal exposure also was considered for adults and 

teenagers performing ornamental garden maintenance tasks (such as 

pruning). 

Methiocarb (adult applicator exposure) 

Methiocarb may be applied to soil areas in and around ornamentals 

for the control of snails and slugs. This product is formulated as bait 

applied as a broadcast application over plant foliage or to the soil 

surrounding ornamental plants. Exposure from this use is expected to 

be minimal. Therefore, post-application exposure was not evaluated for 

this scenario. 

d. Fruit Trees 

Carbaryl (adult applicator and adult and teenager postapplication exposures) 

Carbaryl may be sprayed on fruit trees using a handwand or hoseend sprayer. The current assessment considers dermal and inhalation 

exposure for handwand applications only. Chemical specific applicator 

data for this use indicate greater exposure resulting from handwand 

applications than from hose-end sprayers, and therefore is considered to 

be worst case. Post-application dermal exposure was assessed for 

adults and teenagers harvesting fruit and performing fruit tree 

maintenance tasks (such as pruning). 

e. Pet Collars 

Carbaryl (adult and child post-application exposures) 

Propoxur (adult and child post-application exposures) 

Carbaryl and propoxur are formulated as impregnated pet collars. 

Post-application dermal exposure was considered for adults and children 

contacting (hugging, petting) treated pets. Oral non-dietary exposure 

also was assessed for toddlers contacting treated pets and transferring 

residues from their hands to their mouths. 

Section I.D – Page 87 of 277 
f. Golf Course 

Carbaryl (adult and teenager post-application exposures) 

Carbaryl is also used on golf course turf. Golf course workers may 

apply liquid or granular formulations of carbaryl as a broadcast 

application to fairways, greens and tees. Post-application exposure was 

assessed for adults and teenagers playing rounds of golf on courses 

treated with the sprayable formulations of carbaryl. 

4. Exposure Routes/Scenarios Considered 

The routes of exposure considered in this cumulative assessment 

varied depending on certain application and post-application exposure 

activities that were determined to be age group-specific. Since 

cumulative risk assessments do not include occupational risks, applicator 

exposure is not assessed for the golf course scenario. However, EPA 

does perform separate occupational risk assessments for such exposure 

scenarios. The specific exposure routes and pathways/scenarios are 

summarized and described in additional detail below in Table I.D-1: 

Section I.D – Page 88 of 277 
Table I.D-1. Specific Exposure Routes and Pathways/Scenarios 

Scenario Population 

Applicator Post Application 

Oral Dermal Inhalation Oral Dermal Inhalation 

Adults X X X 

Lawn/Turf 

Children 

1-2 X X 

Children 

3-5 X X 

Adults X X X 

Home Garden 

Youth 

13-17 X 

Children 

1-2 

Children 

3-5 

Adults X X X X 

Indoor 

(c&c) 

Children 

1-2 X X X 

Children 

3-5 X X X 

Adults X 

Pet Collars 

Children 

1-2 X X 

Children 

3-5 X X 

Adults X X X 

Ornamental Plants and 

Youth 

13- 17 X 

Trees Children 

1-2 

Children 

3-5 

Adults X X X 

Fruit Trees 

Youth 

13-17 X 

Children 

1-2 

Children 

3-5 

Golf Course 

Adults X 

Youth 

13-17 X 

Section I.D – Page 89 of 277 
a. Oral Route of Exposure 

Toddler ingestion via hand-to-mouth activity was the only oral route 

of exposure considered in the residential portion of this assessment. 

Specifically, oral hand-to-mouth ingestion was considered only for 

children 1-2 and 3-5 years old for the lawn care and pet collar scenarios. 

OPP acknowledges that there are very limited data on exposure to 

young children; in general, however, children ages six and older no 

longer exhibit mouthing behavior to the degree seen in younger children 

(Freeman et al, 2001). In addition,OPP recognizes that non-dietary 

exposure may occur not only from hand-to-mouth activities but also from 

activities such as ingestion of soil and mouthing of grass. However, the 

latter two pathways were not considered in this assessment because 

these types of non-dietary exposures are expected to be small 

contributors to overall risk from residential NMC products13. 

13 Typically, in single chemical human health risk assessment for pesticides, 

hand-to-mouth exposure is significantly higher than object-to-mouth (i.e., grass 

ingestion) exposure. However, in the carbaryl RED, the grass ingestion MOE for the 

lawn care scenario is 150 while the hand-to- mouth MOEs ranged from 71 to 720. 

Currently, the Agency does not have a methodology to assess grass ingestion 

exposure for granular lawn products. As a conservative assessment for granular turf 

products, the Agency used standard assumptions based on the use of surrogate liquid 

turf transferable (TTR) data. Specifically, the quantitative assessment of object-tomouth exposure in the carbaryl assessment relies upon the assumption that residues 

on grass will be between 3 and 5% of the application rate (HED Policy 12: Revised 

Residential SOP Assumptions, 2/2001). This assumption is derived from liquid DFR 

turf studies for multiple chemicals using the dislodgeable foliar residue (DFR) method. 

The use of this method had been considered by investigators in the past, but is no 

longer used due to its high between-investigator variability. In addition the method had 

been used for measuring turf that is uniformly sprayed resulting in most grass leaves 

being contacted by the sprays. The DFR method involves shaking grass leaves in a 

dislodging solution for 20 minutes. The method itself is likely to be more a exhaustive 

estimate of transfer than may be expected when children’s objects come in contact with 

turf treated with granular forms that are watered-in. Since all carbaryl liquid broadcast 

lawn products have been cancelled, the quantitative assessment for toddlers grass 

ingestion is highly conservative. Further, because the carbaryl hand-to-mouth MOEs 

for the lawn assessment were of concern when granular turf products were not 

watered-in, the Agency will modify all granular turf product labels to require watering-in 

after application. The target pests for the granular formulation are soil insects, 

consequently, it is important that the pesticide reach the soil for adequate control rather 

than remain on the grass. The Agency believes that watering-in, as demonstrated by 

the carbaryl handpress data, will significantly lower the residues of carbaryl on treated 

grass. However, the current methodology used to assess grass ingestion does not 

account for the reduction of residues following irrigation. For all of the above noted 

reasons, the Agency believes that grass ingestion exposure resulting from the use of 

carbaryl granular lawn products will result in minimal exposure and therefore was not 

included in the revised NMC CRA. 

Section I.D – Page 90 of 277 
i. Modeling the Non-Dietary Ingestion Pathway 

In the preliminary N-methyl carbamate cumulative risk assessment 

(preliminary NMC CRA), the non-dietary oral exposure pathway 

produced the lowest Margins of Exposure (MOEs), and would therefore 

be of greatest concern to the Agency. These low MOEs were mainly due 

to the incorporation of micro-activity data into our macro activity models 

(defined as human exposure models based on daily time step). The 

non-dietary ingestion pathway was the least refined of the residential 

exposure pathways modeled in the preliminary NMC CRA. This section 

highlights modifications made to the methodology used to assess this 

pathway. This refined methodology is based on comments and input 

from the FIFRA Scientific Advisory Panel, and the SHEDS and CARES 

developers. 

The Calendex model used in the preliminary and the revised NMC 

CRAs is a macro activity model. Specifically, this model simulates 

exposures by randomly drawing age-appropriate values for each of the 

various exposure factors (e.g., exposure duration, frequency of hand to 

mouth events, surface area of hand mouthed per event, etc.) then 

multiplying these values together per the OPP Standard Operating 

Procedures (SOPs) for Residential Exposure Assessment algorithm 

(USEPA, 1997b). The distributions for many of these exposure factors 

were obtained from micro-activity data. For example, the distribution for 

frequency of hand-to-mouth events was based on data from 

observational studies in which all hand contacts were recorded as handto-mouth events, regardless of the fraction of hand mouthed. For the 

fraction of hand mouthed, no adjustment was made for the duration of 

time the hand remained in the mouth. As the August 2005 SAP panel 

discussed, utilizing such micro-activity data with macro activity models 

poses many challenges. For example, if two variables are negatively 

correlated (e.g., more frequent mouthing is associated with smaller areas 

of hand mouthed), then “modeling the product of two jointly distributed 

variables as independent draws will overestimate the variances...or 

overestimate exposure at the high end.” Similarly, “fixing the residue on 

a child’s hands (and/or other exposure factors) for a two hour play 

period...will yield ‘greater variability in the modeled distribution of 

exposures than a run that updates the residue concentration hourly 

during the exposure”. (FIFRA SAP, 2005b). 

As recommended by the SAP, the Agency is exploring the use of 

SHEDS-Multimedia for future probabilistic risk assessments. In the 

revised NMC CRA, Agency staff addressed shortcomings in the nondietary oral pathway by modifying the probabilistic hand-to-mouth 

algorithm as discussed below. This modified algorithm is a product of a 

Section I.D – Page 91 of 277 
collaborative effort between OPP scientists, and the developers of the 

SHEDS-Multimedia (Dr. Valerie Zartarian and Dr. Jianping Xue) and 

CARES models (Dr. Jeffrey Driver and Dr. Muhilan Pandian). 

The refined algorithm for estimating daily hand-to-mouth ingestion 

in the revised NMC Calendex assessment is similar to the SHEDSMultimedia and CARES Mass Balance algorithms in the manner in which 

it addresses residue replenishment between hand-to-mouth contacts. 

Specifically, the new algorithm establishes a maximum amount of 

residue which can be on the hand, or a maximum dermal hand loading. 

The amount of non-dietary oral ingestion increases with the exposure 

duration, the frequency of hand-to-mouth events per hour, and the 

surface area mouthed per event, while the hand loading serves as an 

upper constraint on oral ingestion between replenishment events. 

New Hand-to-Mouth Algorithm 

The following equation is the algorithm used in the Revised NMC 

CRA: 

Exposure = HR * SAmouthed _ fraction * (N _ replen) *[1− (1− SE)]N _ events 

2 

HR/2 = initial residues available on one hand [mg/day] 

SA mouthed fraction = surface area of hand mouthed [unitless]. 

N_Replen = number of replenishment intervals per day. This is 

equivalent to the values used for Duration [hrs/day] in the 

preliminary NMC CRA since the residues are assumed to be 

"replenished" every hour of the exposure duration 

SE = saliva extraction factor (i.e., mouthing removal efficiency) 

[unitless]; 

N_Events = number of hand-to-mouth contacts events per 

replenishment interval; 

Each of these terms is discussed in detail below. 

Hand Loading 

Hand loading, or HR/2, is based on loading concepts used in 

SHEDS and CARES. The initial amount of residue available on the hand 

is determined as a percentage of total dermal exposure. The EPA Child 

Specific Exposure Factors Handbook indicates that the surface area of 

the hands is approximately 6% of the total surface area of the body for 

children age 4 and under; 5% for children age 5 and over (USEPA, 

Section I.D – Page 92 of 277 
2002c, table 8-3). The algorithm assumes mouthing one hand at a time; 

therefore, hand loading residues are divided by 2. 

Frequency of mouthing events and fraction of surface area 

mouthed 

The distributions for frequency of mouthing events (N_Events) 

and the fraction of surface area of hand mouthed (SA mouthed fraction), 

are based on observational studies (see scenario-specific discussions in 

section I.D.6 for more details on the information sources used for these 

parameters). This algorithm allows for only one draw (per simulated 

day), therefore, the interpretation is that this behavior continues at the 

same rate for the entire exposure duration selected. In reality, a highend mouthing frequency recorded over a short time interval (e.g., one 

hour) may not be likely to continue at the same intensity over a longer 

time period (e.g., 6 or 8 hours). 

Saliva extraction factor (i.e., mouthing removal efficiency) 

The saliva extraction factor (SE) indicates the fraction of residues 

that is removed during each mouthing event. The greater the removal 

efficiency (i.e.,SE), the less residue remains on the hand after each 

mouthing event. For example, if the initial loading is 1000 ug on the 

thumb (part of hand mouthed), and the removal efficiency is 20%, then 

after one event, 200 ug is removed and 800 ug remains on the thumb; 

after two events, an additional 160 ug is removed (=800x.2), or a total of 

360 ug (=1000x(1-(1-.2)2)) is removed and ingested, and 640 ug 

(=1000x((1-.2)2)) remains on the thumb. 

The SE term is used in combination with the mouthing frequency 

term (N_Events) in the above equation as: 

(1-SE) (N_Events) 

This portion of the new hand-to-mouth algorithm expresses the 

percent of initial loading remaining on hand after N hand-to-mouth events 

or, equivalently, the percent of initial loading mouthed that is ingested 

after N hand-to-mouth events. 

Replenishment Interval 

In the preliminary NMC CRA, the non-dietary ingestion algorithm 

assumed complete replenishment between each hand-to-mouth event. 

This new algorithm is more comparable to the SHEDS-Multimedia and 

the CARES Mass Balance algorithms in addressing the replenishment. 

The new algorithm assumes that replenishment occurs only once every 

Section I.D – Page 93 of 277 
fixed time interval (SHEDS uses the Consolidated Human Activity 

Database (CHAD) time interval; CARES uses a daily time interval). 

Within each replenishment interval, a fraction of the remaining residues 

are removed and ingested during each hand-to-mouth event. The total 

amount of residues removed and ingested increases with the SE, the 

number of events per interval, and with the number of replenishment 

intervals per day (or exposure duration). 

In this new algorithm, the hand is fully replenished with residues 

from a contaminated surface (e.g., the lawn, pet or hard flooring), on an 

hourly basis. The replenishment frequency (hrs/day) and the mouthing 

frequency per replenishment interval (events/hr) are expressed in the 

same time unit (hr). Therefore, the same distribution, total exposure 

duration (hrs/day) was used in the preliminary NMC CRA. This algorithm 

may be generalized to model replenishment at different (fixed) time 

intervals.14 

b. Dermal Route of Exposure 

The dermal route was assessed for adults applying 

consumer pesticide products to lawns, gardens, fruit trees, and 

ornamental plants. For both children and adults, post-application dermal 

exposure was assessed for the lawn and pet collar scenarios. The 

dermal route was also assessed for adults and teenagers reentering 

treated vegetable and ornamental garden to perform maintenance 

(weeding, pruning) and harvesting activities. Similarly, exposure was 

assessed for adults and teenagers involved in fruit tree cultivation. 

Dermal post-application exposure also was assessed for adults and 

teens playing golf on treated courses. 

c. Inhalation Route of Exposure 

The inhalation route of exposure was considered for adult 

populations only. Specifically, inhalation exposure was assessed for 

14 For example, if it is assumed that the hand is fully replenished every half hour, 

then both variables (N_Replen and N_Events) would be constructed using 30 minutes 

as the unit for duration. Similarly, if one replenishment per day (N_Replen=1) is 

assumed, this new algorithm reduces to the CARES Mass Balance equation. This is 

demonstrated by replacing the number of replenishment intervals per day 

(N_Replen=1/day), and the total mouthing events per replenishment interval 

(events/day) with the equivalent terms (N_Events = FREQEvents/hr x Duration hrs/day) 

in the following equation: 

HR Freqevents *Durationhrs Exposure= 2

*SAmouthed_ fraction *1*[1−(1−SE)] hr day 

Section I.D – Page 94 of 277 
adults applying pesticide formulations to lawns, vegetable gardens, 

ornamental plants and fruit trees. 

5. Data Sources 

Three basic types of data were considered in this assessment: 

 pesticide use data; 

 residue concentration and dissipation/decay data; 

 exposure contact factor data. 

These data are described in more detail below. 

a. Pesticide Use Data 

The probabilistic models require residential pesticide use 

inputs to aggregate exposure from multiple use scenarios. The percent 

of households applying the various products and the timing of those 

applications directly impact estimates of aggregate exposure. The REJV 

data can be used to generate empirically-based estimates to address 

those needs. Appendix II.D.1 provides further details regarding the 

REJV data. However, the REJV did not collect information on the 

purpose of use (pest treated), areas treated, or application rates. Since 

these factors may impact timing and frequency of application, REJV data 

was used in combination with professional judgment, product label 

information and pest pressure information from the Cooperative State 

Extension Services. The revised NMC CRA considered the Southeast 

Region of the United States for two reasons; 1) the growing season is 

longer in the South and the associated pest pressures are therefore 

greater, and 2) drinking water concentrations are highest in this region of 

the country. The residential and groundwater assessments are based on 

the most highly exposed localized areas within the southeastern region 

of the United States. Specifically, the drinking water exposure for 

Georgia was combined with residential exposure in Florida Pest pressure 

data for Florida are assumed to address pest pressure for other areas of 

the country where NMC water concentrations are high (such as Georgia 

and North Carolina). Due to longer periods of pesticide use coupled with 

higher concentrations of NMC in ground water, this assessment provides 

a worst case estimate of exposure. 

The revised NMC CRA focuses on post-application exposures for 

children, including the broadcast lawn and the pet collar scenarios. 

Examples of how pesticide use data were incorporated into these 

scenarios are discussed below. 

Section I.D – Page 95 of 277 
i. Broadcast Lawn Scenarios 

Current label revisions for carbaryl lawn care products restrict 

broadcast applications to granular formulations. Therefore, postapplication exposure for children was assessed only for granular 

applications of carbaryl to lawns. The major turf pests treated with 

carbaryl are grubs, mole crickets, caterpillars, cinch bugs, scales, ticks, 

and a variety of spiders, and ants. However, pests that would mostly 

likely be treated with granular applications are mole crickets and white 

grubs. The other pests listed are more likely to be treated with spray 

applications. Therefore, this assessment focused on timing of 

applications for residential lawns treated for white grubs and mole 

crickets. Information from the University of Florida Cooperative State 

Extension Service indicates that grubs actively feed in Florida from April 

through October, depending on species and weather conditions. 

Additionally, tawny mole crickets become active in March, and granular 

applications are typically made in August and September. For these 

reasons, the broadcast lawn assessment considered the season of use 

to be early spring through fall. OPP assumed two applications to the 

lawn per year (based on REJV). 

ii. Pet Collar Scenarios 

Propoxur and carbaryl product labels indicate that pet collars are 

effective for 180 days and 120 days, respectively. Additionally, season 

of use is considered to be year-round since flea lifecycle information 

shows that in humid climates, fleas may be active year-round. 

Therefore, the pet collar assessment assumed that pet collars would be 

used year-round in southern climates. 

b. Residue Concentration Data 

Residue concentration data and associated pesticide 

decay/dissipation parameters were used to define the sources and 

magnitude of exposure resulting from human contact with transferable 

residues. In many cases, chemical-specific data were used to assess 

homeowner applicator and post-application exposure resulting from the 

registered uses of carbaryl. For the lawn and garden scenarios, data 

from the Outdoor Residential Pesticide Use and Usage Survey and 

National Gardening Association Survey (Johnson et al, 1999) submitted 

by the Outdoor Residential Exposure Task Force (ORETF) were also 

used. Surrogate data were used to determine exposure resulting from 

the ornamental garden use of methiocarb. Appendix II.D.2 contains a 

summary of all residue data used in the revised NMC CRA, as well as 

the derivation of various distributional parameters. 

Section I.D – Page 96 of 277 
c. Exposure Factor (Contact) Data 

Exposure factors such as the amount of time spent in an area, 

frequency of hand-to-mouth contacts, size of area treated, and location 

of residue source (lawn, garden, or indoor surface) are critical for 

estimating exposures to a given substance. Appendix II.D.2 contains a 

summary of exposure factors used in the revised NMC CRA, as well as 

the derivation of various distributional parameters. Unless otherwise 

noted, all distributions were truncated at the 99th percentile in order to 

avoid a distribution which contained values that were well beyond those 

deemed reasonable. 

6. Exposure Scenarios 

This assessment considered a variety of exposure scenarios for 

consumer applicator and post-application exposures. Each of these is 

described in additional detail below. Since it is difficult to determine 

typical rates for homeowner products, OPP used the maximum 

application rate, as allowed by currently registered labels, to assess 

exposure for all scenarios. (8 lbs ai/A was used for lawns and fruit trees; 

and 2 lbs ai/A was used for vegetable gardens and ornamentals.) Table 

I.D-4 summarizes the selected inputs for all scenarios. 

a. Lawn Care Exposure Scenarios 

i. Lawn Applicator Exposure 

Only carbaryl has registered lawn care uses. Applicator exposure 

was assessed for homeowners mixing, loading, and applying a variety of 

carbaryl products to their lawns. There are two formulations of carbaryl 

that are available for lawn use: granular and liquid sprayable 

formulations. OPP has amended the use pattern of carbaryl and the 

current cumulative assessment incorporates these changes. The label 

changes restrict broadcast lawn application to granular formulations. 

However, spot treatments of the liquid formulation are permitted. All 

liquid products must be packaged in ready-to-dispense containers. Such 

formulations will limit spot treatments to areas of less than 1000 square 

feet. 

Total exposure is calculated as the product of the unit exposure 

(UE) (either dermal or inhalation), the application rate, and the lawn size. 

Unit Exposures: Both dermal and inhalation exposure routes 

were considered. ORETF studies were used for the granular broadcast 

and liquid spot treatment scenarios. 

Section I.D – Page 97 of 277 
The ORETF submitted a report (Klonne, 1999) in which a variety of 

products were used on turf. In these studies, both homeowners and 

lawn care operators (LCOs) were monitored following broadcast 

applications to turf. All of the data submitted in this report were 

completed in a series of studies. 

The two studies that monitored homeowner exposure resulting from 

granular spreader (Klonne, 1999/OMA003 Study) and hose-end sprayer 

(Klonne, 1999/OMA004 Study) applications were used in this 

assessment. Volunteers participating in these exposures studies were 

adult non-professionals who use pesticides on their own gardens and 

lawns. Many of the volunteers selected as subjects in these studies 

were members of garden clubs. All volunteers made their applications 

without specific instruction from the study investigators. Unit exposures 

estimated from these studies cover various clothing scenarios that range 

from wearing short pants and short-sleeved shirts, to long pants and 

long- sleeved shirts. 

All dermal and inhalation unit exposure were normalized and 

expressed as milligrams exposure per pound of active ingredient 

handled (mg/lb ai) (referred to as unit exposures, or UE). The lognormal 

distributions of the UEs for the lawn applicator scenarios are shown in 

Table I.D-2. 

Table I.D-2. Lognormal Distributions of Unit Exposures Used for Carbaryl Lawn 

Care Scenarios 

Application 

Method Exposure Route 

Unit Exposure 

Distribution 

(mg/lb ai) 

LN(μ, σ) 

Comments 

Granular Rotary 

Spreader 

Dermal 0.81, 0.57 This distribution was used for the broadcast 

lawn scenario Inhalation 0.0013, 0.0013 

Hose-end Sprayer 

on Turf 

Dermal 8.4, 26 This distribution was used for the lawn 

SPOT treatment scenario ONLY Inhalation 0.022, 0.040 

NOTES: 

LN(μ, σ) represents a lognormal distribution with μ = arithmetic mean and σ = arithmetic standard deviation. 

For lawn scenarios, information was derived from carbaryl-specific data and studies conducted by the ORETF. 

A more detailed explanation of the statistical analysis of this data is provided in Appendix II.D.2. 

Application Rates: For all scenarios assessed, OPP used the 

maximum application rate to assess exposure (8 lbs ai/A was used for 

the lawn care scenario). 

Section I.D – Page 98 of 277 
Area Treated: An important variable for estimating home-owner 

applicator exposure is the size of the lawn. OPP considered the average 

and median lawn sizes reported in a journal article by Vinlove and Torla 

(1995). The means and medians were ~13,000 ft2. However, the 

authors noted problems interpreting the data since it is based primarily 

on low income houses and consists of adjustments of the lot size by the 

house's foundation (footprint) only. The data do not consider other 

structures such as decks or other green space such as gardens, which 

can reportedly reduce the lot size by up to 50%. Similar lawn sizes were 

noted in the ORETF survey (Johnson et al, 1999) with similar problems 

encountered with respect to confounding variables such as decks and 

other green spaces. For this assessment, OPP used a uniform 

distribution for lawn size bounded by 1000 ft2 and 20,000 ft2. The lower 

end of this range considers smaller lawns for residences such as town 

houses. The upper bound of 20,000 ft2 (~ 1⁄2 acre) appears reasonable 

given the type of application equipment assumed to be used by 

residential applicators. Information from the ORETF survey also 

indicates that many pesticide users make spot treatments of insecticides. 

Similarly for spot treatments, OPP assumed a uniform distribution for 

treated area bounded by 100 ft2 and 1000 ft2. 

ii. Lawn Post-Application Dermal Exposure 

The fate of pesticides applied to turf, and subsequent human 

contact, is a key variable for assessing post-application dermal exposure 

and can be an important exposure pathway to consider as part of a 

cumulative assessment. This exposure pathway was evaluated here in 

the revised NMC CRA by using data from a number of available studies 

(described in more detail below). Briefly, post-application dermal 

exposure (mg pesticide) is calculated by multiplying the residue 

concentration on the lawn (mg/cm2) by the transfer coefficient (cm2/hour) 

derived from literature and other studies and the time spent on the lawn 

(hours/day). For this assessment, the transfer coefficient and the time 

spent on lawns were represented by a distribution of values while the 

residue concentration on the lawn was represented by a time series of 

concentration values (which accounted for residue degradation over time 

and incorporated the relevant half-lives or decay coefficients). Due to 

the label revisions, post-application exposure was considered for the 

granular broadcast treatments only. 

Residue Data: There are chemical-specific turf transferable 

residue (TTR) data for granular formulations of carbaryl (Krolski, 2005). 

This study was designed to determine transferable residues of carbaryl 

from both irrigated and non-irrigated turf treated with SEVIN® 2G (see 

Appendix II.D.2 for study summary). Measured carbaryl residues rapidly 

declined over the first 4 hours and then leveled off or rose slightly after 

12 hours. By the 24-hour sampling interval, the residues declined to 

Section I.D – Page 99 of 277 
approximately 10 percent of the corresponding 0-time residue value and 

then steadily dropped to below 1.0 percent of the corresponding 0-time 

residue values by 3- to 5-days after treatment. 

In order to provide a conservative estimate of exposure for the 

revised NMC CRA, only the samples in the above study from the nonirrigated site in Florida were used. This assessment assumes an initial 

concentration of 0.00021 mg/cm2. Dissipation is based on a 0.8 day halflife, with residues set to zero 14 days after application. Although the 

carbaryl TTR studies show residues below 1% of the initial residues by 

3- to 5-days after application, to provide a conservative estimate of 

exposure, it is assumed that carbaryl residues on the lawn would be 

available for up to 2 weeks after application. 

Transfer Coefficients (TC): The transfer coefficients used in this 

assessment were developed by dividing the hourly dermal exposure 

(μg/hr) obtained from a set of activities by the measurement commonly 

referred to as turf transferable residues (TTR) (μg/ cm2). Since none of 

the dermal exposure studies used to estimate hourly exposure permitted 

direct calculation of the TTR, the transfer coefficients for this assessment 

were developed by assuming a transfer efficiency of at least 0.5% for 

granular formulations. This was done for two reasons: 

� to make use of available dermal exposure measurements 

which are not influenced the methodology used to estimate 

TTR, and 

� to make use of the available residue dissipation data for 

which there are no corresponding dermal exposure 

measurements 

The 0.5% value is within the range of efficiency for the existing 

chemical specific TTR data described above. To account for the 

additional uncertainty of assuming a certain transfer efficiency to develop 

the transfer coefficients, TTR data having transfer efficiencies lower than 

0.5% (for granular applications) were adjusted upwards to make up the 

difference in efficiency. If the transfer efficiency of the TTR data was 

higher than 0.5% for granular formulations, it was not adjusted. 

For a more detailed discussion of the relationship of transfer 

coefficients and TTRs please refer to the “Overview of Issues Related to 

the Standard Operating Procedures for Residential Exposure 

Assessment” presented to the FIFRA Scientific Advisory Panel on 

September 21, 1999. 

Section I.D – Page 100 of 277 
Transfer Coefficients used to assess children’s exposure to 

treated turf: 

One study was used to assess children’s dermal exposure resulting 

from granular applications to residential turf (Vaccaro, 1996). In this 

study, a granular formulation of chlorpyrifos was applied, after which 

seven adults performed pre-choreographed activities intended to mimic a 

typical child’s behavior. 

The subjects performed these activities for a period of four hours 

beginning after the turf had dried. Turf had been treated earlier with a 

granular form of chlorpyrifos and exposure was estimated in the study by 

monitoring the amount of a chlorpyrifos metabolite – 3,4,5,6-TCP – 

excreted over the following period of 6 days. This method directly 

measures internal dose and was used to back-calculate a generic “to the 

skin” transfer coefficient by using chemical specific dermal absorption 

data for chlorpyrifos (Nolan et al., 1984). These data were further 

adjusted to account for differences in surface area of adults and children. 

The study data discussed above was fit to a lognormal distribution 

with an arithmetic mean of 1970 cm2/hr with a standard deviation of 1426 

cm2/hr. The lognormal distribution was truncated at the calculated 99th 

percentile of the distribution (i.e. 7224 cm2/hr for the granular application) 

in order to avoid a distribution which contained values that were wellbeyond those that are deemed reasonable. (See Appendix II.D.2 for 

study summary and details of the distributional analysis.) 

Transfer Coefficients used to assess adult exposure to 

treated turf: 

The Vaccaro study data discussed above were also used to assess 

exposure to adults following granular applications. 

The revised NMC CRA used a distribution of values for the transfer 

coefficient characterized by a lognormal distribution with an arithmetic 

mean of 5376 cm2

/hr and a standard deviation of 4717 cm2/hr for the 

granular application. The lognormal distribution was truncated at the 

calculated 99th percentile of the distribution (i.e., 23436 cm2

/hr) for the 

granular application. (See Appendix II.D.2 for study summary and 

details of the distributional analysis.) 

Duration: Another important variable for addressing postapplication exposure from home lawn treatment is the duration of time 

spent on lawns. In this revised NMC CRA, cumulative distributions of 

durations on lawns of up to two hours were used to address adult 

exposure on lawns. These data are presented in Table 15-64 of the 

Section I.D – Page 101 of 277 
Exposure Factor’s Handbook (EFH) (USEPA, 1997a); however, OPP 

notes that the percentiles above the 95th have the same values (121 

minutes). A similar cumulative distribution was given for children ages 

one to five. In order to be protective of children and to address the 

uncertainty in the upper percentiles of the exposure factor data, OPP 

selected an empirical distribution (which was expressed as a cumulative 

distribution function) from EPA’s EFH (Table 15-80) with a bound of 3.5 

hours for children. This distribution represents the amount of time spent 

outdoors rather than just on lawns. This adjustment allows for additional 

time that children may spend outdoors (such as parks and schools) 

where there is potential for additional contact with treated turf. 

iii. Lawn Non-Dietary Hand-to-Mouth Exposure 

The assessment also incorporates exposure resulting from toddler 

hand-to-mouth activity on lawns. The revised NMC CRA incorporates a 

new algorithm to estimate hand-to-mouth exposure. Details of this 

algorithm can be found in Section I.D.4.i of this document. 

Initial Hand Loading: Hand loading (HR/2) is based on loading 

concepts used in SHEDS and CARES. The initial amount of residue 

available on the hand is determined as a percentage of total dermal 

exposure. The EPA Child Specific EFH (USEPA, 2002c) indicates that 

the surface area of the hands is approximately 6% of the total surface 

area of the body for children age 4 and under; 5% for children age 5 and 

over. The algorithm assumes mouthing one hand at a time, therefore, 

hand loading residues are divided by 2. 

Frequency of Mouthing Behavior: For the revised NMC CRA, 

the frequency of hand-to-mouth events is based on Xue et al, 2007. The 

estimates of mouthing frequency were derived from several exposure 

studies and videotaping studies. Statistical analysis indicated that a 

Weibull distribution best fit the data. For the lawn care scenario, handto-mouth events per hour were based on outdoor frequencies as defined 

by a Weibull distribution (mean = 6 events/hour, standard deviation = 8). 

OPP believes that the meta-analysis cited above provides the best 

available data to assess children’s hand-to-mouth exposures. 

Surface Area of Hand Mouthed: The revised NMC CRA relied on 

Zartarian’s (2003) analysis of surface area of hand mouthed. The 

analysis used the Leckie, et al., 2000 data to determine the fraction of 

the hand mouthed. The fraction of hand mouthed values were fit with a 

beta distribution (mean = 0.13 events/hour, standard deviation = 0.06). 

Saliva Extraction Factor: To address the removal of residues 

from the hands by saliva during mouthing events, several studies were 

considered. The removal efficiency of residues on hands by saliva and 

Section I.D – Page 102 of 277 
other substances (e.g., ethanol) suggests a range of removal 

efficiencies (Geno et al., 1995; Fenske and Lu 1994; Wester and 

Maibach 1989). Based on the above studies, a uniform distribution of 

20% to 50% was used in this assessment for saliva extraction factors. 

Duration: The time spent on the lawn was estimated as a 

cumulative distribution ranging from 0 hours to 3.5 hours. To be 

protective of childrens’ exposure and to address the uncertainty of the 

upper percentiles of the exposure factor data, OPP selected a 

cumulative distribution from EFH (USEPA, 1997a) Table 15-80 with a 

bound of 3.5 hours for children 1 to 5 years old. This distribution 

represents the amount of time spent outdoors. This allows for the time 

that children spend outdoors not only at home but also in parks and near 

schools. 

Assessing exposure through the non-dietary ingestion pathway is 

difficult due, in part, to issues associated with measurement of the 

above-discussed variables as well as issues associated with the utility of 

using children’s hand-to-mouth frequencies based on indoor activities for 

outdoor exposure scenarios. There are also differences in mouthing 

behavior based on active and quiet play with increased mouthing likely to 

be during activities of quiet play. Limited data evaluated by Groot et al., 

1998 suggests that children aged six to 12 months can experience 

longer durations of mouthing activities (exceeding 160 minutes per day) 

than children 18 to 36 months (up to 30 minutes per day). However, 

children in this age group are not likely to be engaged in post-application 

lawn activities OPP is modeling that would result in higher estimated 

exposure. Additional data for very young children (under the age of two) 

are needed to delineate the frequency differences between hand-tomouth events for children engaged in active and quiet play. 

b. Vegetable Garden Exposure Scenarios 

Carbaryl has registered uses in home vegetable gardens. This 

assessment includes scenarios for applications of carbaryl using dust 

formulations (hand/shake), ready-to-use trigger sprayers, and hose-end 

sprayers. While there are other possible application methods for use on 

these sites, these application methods were selected based on use and 

exposure considerations. 

i. Applicator Exposure 

Dermal and inhalation exposures for homeowners applying carbaryl 

to their vegetable gardens were calculated in a manner similar to that 

used to assess applicator exposure for the lawn care scenario. Both are 

the product of the unit exposure (mg/lb ai handled), application rate (lbs 

ai/ft2), and area treated (ft2). 

Section I.D – Page 103 of 277 
Unit Exposure: Dermal and inhalation unit exposures were 

derived from chemical-specific data (Mester, 1998a) for dust 

(shake/pour), trigger pump sprayer, and liquid hose-end sprayer 

applications to vegetable gardens. The UE for all garden scenarios are 

based on lognormal distribution as listed in Table I.D-3. 

Application Rate: An application rate of 2 lbs ai/A was used for all 

liquid vegetable garden scenarios (hose-end sprayers and trigger pump 

sprayers) even though trigger pump sprayer rates are considerably 

lower. This assessment conservatively uses the 2 lb ai/A application rate 

for all liquid scenarios. Due to recent mitigation, the maximum 

application rate for dust formulations is 0.5 lbs ai/container (see Table 

II.A). The exposure assessment for dust formulation applied to home 

gardens assumes use of one entire container per treatment. 

Area Treated: For vegetable gardens, the area treated was 

entered as a lognormal distribution (mean = 4600 ft2, standard deviation 

=1500 ft2, and maximum = 8000 ft2); these dimensions are based on 

data from the National Gardening Association Survey (Johnson et al, 

1999). In these assessments, it is assumed that the entire garden is 

treated. Home gardens consist of many types of vegetables which all 

may not be treated since they tend to have different pest pressures (e.g. 

squash vine borer and corn earworm may not appear at the same time). 

Table I.D-3. Lognormal Distributions of Unit Exposures Used for Carbaryl 

Garden, Fruit Tree, and Ornamental Scenarios 

Application 

Method 

Exposure 

Route 

Unit Exposure 

Distribution(mg/lb ai) 

Comments 

Hose-End 

Sprayer 

Dermal (51, 58) This distribution used for the 

Inhalation (0.0024, 0.0015) vegetable garden scenario ONLY 

Liquid Handwand Dermal (74, 64) This distribution also used for the 

Inhalation (0.009, 0.010) ornamental and fruit tree scenarios 

Dust 

Shaker/Powder 

Dermal (250, 330) This distribution was used for 

vegetable garden and ornamental 

scenarios. This distribution was 

also used for the SPOT treatment 

on lawns. 

Inhalation (2.9, 9.5) 

RTU Trigger 

Pump Sprayer 

Dermal (86, 110) This distribution was used for the 

vegetable garden and ornamental 

scenarios. Inhalation (0.10, 0.14) 

NOTES: LN(μ, σ) represents a lognormal distribution with μ = mean and σ = standard deviation 

Studies for garden, fruit tree, and ornamental applications are carbaryl-specific. 

A more detailed explanation of the statistical analysis of this data is provided in Appendix II.D.2. 

Section I.D – Page 104 of 277 
ii. Post-Application Dermal Exposure 

Post-application exposure for adults and teenagers harvesting 

vegetables or performing post-application gardens maintenance were 

assessed using a range of transfer coefficients to account for the 

diversity of activities. Post-application exposure was estimated as the 

product of dislodgeable residue concentration (mg/ cm2) a transfer 

coefficient (cm2/hour), and time spent in the activity (hours). 

Residue Data: Chemical-specific dislodgeable foliar residue data 

on sunflowers (Klonne et al, 1999) were used to assess dermal postapplication exposure. Although OPP has additional information 

regarding carbaryl specific DFR data on cabbage (Klonne et al, 2000a) , 

the sunflower DFR data were used since the residues detected in the 

sunflower study were higher than those detected in the cabbage study. 

Statistical analysis of the carbaryl sunflower DFR data was performed. 

The initial residue concentrations and the half-life were determined to be 

0.0061 mg/cm2 and 5 days, respectively. 

Transfer Coefficient: For the vegetable garden scenario, transfer 

coefficients were characterized by a uniform distribution ranging from 

180 to 1000 cm2/hour, to reflect a range of gardening tasks for a variety 

of crops of differing heights and foliage development. The TCs used in 

this assessment were derived from studies on chrysanthemum pinching 

(Rotondaro, 2000) and tomato harvesting (USEPA, 2000e). All transfer 

coefficients are based on individuals wearing short sleeved shirts and 

short pants. A reduction factor was applied to account for body weights 

and surface area differences between adults and teenagers. 

Duration: The time spent harvesting or performing post-application 

maintenance activities was represented by a uniform distribution ranging 

from 0.17 hour/day to 1 hour/day. These estimates of time spent in the 

garden performing post application activities (as well as the frequency of 

applications) were based on the ORETF survey (Johnson et al, 1999). 

c. Ornamental Plants and Shrubs Exposure Scenarios 

Carbaryl also has registered uses on ornamental plants and 

shrubs. This assessment includes scenarios for the RTU dust 

formulations, RTU trigger pump sprayers, and liquid hand wand uses on 

ornamental plants. While there are other possible application methods 

for use on this site, these methods were selected based on use and 

exposure considerations. 

Section I.D – Page 105 of 277 
i. Applicator Exposure 

Dermal and inhalation exposures for homeowners treating 

ornamental plants were estimated as the product of the Unit Exposure 

(mg/lb ai handled), application rate (lbs ai/ft2), and area treated (ft2). 

Unit Exposure: Dermal and inhalation unit exposures were 

derived from chemical-specific data for carbaryl used on ornamental 

plants (Mester, 1998a; Merricks, 1998). The UE for all garden scenarios 

are based on lognormal distribution as listed in Table I.D.3. 

Application Rate: An application rate of 2 lbs ai/A was used for all 

liquid vegetable garden scenarios (hose-end sprayers and trigger pump 

sprayers) even though trigger pump sprayer rates are considerably 

lower. This assessment conservatively uses the 2 lbs ai/A application 

rate for all liquid scenarios. Due to recent mitigation, the maximum 

application rate for dust formulations is 0.5 lb ai/container. The exposure 

assessment for dust formulation applied to ornamental gardens assumes 

use of one entire container per treatment. 

Area Treated: The area treated was entered as a uniform 

distribution of 500 to 2000 ft2; these dimensions are based on data from 

the National Gardening Association Survey (Johnson et al,1999) and 

professional judgment. The ornamental bed size was determined by 

estimating the perimeter of 2200 ft2 house. It is assumed that the 

majority of ornamental beds are located around the perimeter of the 

house. 

ii. Post-Application Dermal Exposure 

Post-application exposure for adults and teenagers performing 

ornamental garden activities were assessed using a range of transfer 

coefficients to account for the diversity of activities. Post-application 

exposure was estimated as the product of dislodgeable residue 

concentration (mg/ cm2

), transfer coefficient (cm2/hour), and time spent 

in the activity (hours). 

Residue Data: Chemical-specific dislodgeable foliar residue data 

on sunflowers (Klonne et al, 1999) were used to assess dermal postapplication exposure from harvesting or performing maintenance 

activities in ornamental gardens. Although OPP has additional 

information regarding carbaryl specific DFR data on cabbage (Klonne et 

al, 2000a), the sunflower DFR data were used since the residues 

detected in the sunflower study were higher than those detected in the 

cabbage study. A statistical analysis of this data was performed and the 

Section I.D – Page 106 of 277 
initial concentration was estimated to be 0.0061 mg/ cm2

. Residue 

dissipation is based on the half-life of 5 days. The half-life used in this 

assessment was determined from the statistical analysis of the carbaryl 

sunflower DFR data. A more detailed explanation of the statistical 

analysis of this data is provided in Appendix II.D.2. 

Transfer Coefficient: For the ornamental garden scenario, a 

uniform distribution of transfer coefficients, ranging from 99 to 550 

cm2/hour, was used to reflect a range of gardening tasks. The TCs used 

in this assessment were derived from studies that evaluated 

chrysanthemum pinching (Rotondaro, 2000) and nursery stock pruning 

(Klonne et al, 2000b). All transfer coefficients are based on individuals 

wearing short-sleeved shirts and short pants. A reduction factor was 

applied to account for body weights and surface area differences 

between adults and teenagers. 

Duration: The time spent harvesting or performing postapplication maintenance activities was represented by a uniform 

distribution ranging from 0.17 hour/day to 1 hour/day. These estimates 

of time spent in the garden performing post-application activities (as well 

as the frequency of applications) were based on the ORETF survey 

(Johnson et al, 1999). 

d. Fruit Tree Exposure Scenarios 

Carbaryl also has registered uses on fruit trees. This assessment 

addresses exposure for homeowners applying sprayable formulations of 

carbaryl via handwands. While there are other possible application 

methods for use on these sites, this method was selected based on use 

and exposure considerations. 

i. Applicator Exposure 

As described for the lawn applicator scenario, exposure is the 

product of the unit exposure (mg/lb ai handled), application rate (lbs 

ai/ft2

), and area treated (ft2). 

Unit Exposure: The dermal and inhalation unit exposures were 

derived from chemical-specific data for liquid handwand applications to 

fruit trees (Merricks, 1998). These unit exposures are based on study 

data in which applications were made with handwands, spraying below 

the waist as well as overhead. The UEs for fruit tree scenario are based 

on lognormal distribution as listed in Table I.D.3. 

Section I.D – Page 107 of 277 
Application Rate: For all scenarios assessed, OPP used the 

maximum application rate to assess exposure (8 lbs ai/A was used for 

the fruit tree scenario). 

Area Treated: For fruit trees, most of which are of the dwarf 

variety and therefore occupy relatively small areas, the area treated was 

entered as a uniform distribution (minimum 500 ft2, maximum 1000 ft2). 

The maximum value in this distribution was based on label restriction for 

applications made at the maximum rate (8lbs ai/A) for fruit tree 

applications. 

ii. Post-Application Dermal Exposure 

Dermal post-application exposure for adults and teenagers 

harvesting or pruning fruit trees was assessed using TCs from an apple 

pruning study. Post- application exposure was estimated as the product 

of dislodgeable residue concentration (mg/ cm2), transfer coefficient 

(cm2/hour), and time spent in the activity (hours). 

Residue Data: Chemical specific dislodgeable foliar residue data 

on olive trees (Klonne et al, 2000c) were used to assess dermal postapplication exposure for this scenario. Statistical analysis of this data 

was performed and the initial residue concentrations were determined to 

be 0.0035 mg/ cm2. Residue dissipation is based on the half-life of 7 

days (as determined by the statistical analysis of the carbaryl olive DFR 

data). 

Transfer Coefficient: For the fruit tree scenario, the distribution of 

transfer coefficient was characterized as lognormal, with a mean of 940 

cm2/hour and a standard deviation of 260 cm2/hour. The TCs were 

based on an apple pruning study. All transfer coefficients are based on 

individuals wearing short-sleeved shirts and short pants. A reduction 

factor was applied to account for body weights and surface area 

differences between adults and teenagers. 

Duration: The time spent harvesting or performing postapplication maintenance activities was represented by a uniform 

distribution ranging from 0.17 hour/day to 1 hour/day. These estimates 

of time spent in the garden performing post application activities (as well 

as the frequency of applications) were based on the ORETF survey 

(Johnson et al, 1999). 

e. Ornamental Garden - Snail and Slug Bait Scenarios 

This assessment includes the bait use of methiocarb in 

ornamental gardens. Applicator exposure is calculated as the product of 

the unit exposure (mg/lb ai handled), application rate (lbs ai/ft2

), and area 

treated (ft2

). 

Section I.D – Page 108 of 277 
i. Applicator Exposure 

Unit Exposure: The dermal and inhalation UEs for the methiocarb 

snail and slug bait scenario were based on study data for disulfoton 

applications to residential shrubs and flower beds (Merricks, 2001). The 

surrogate data consist of dermal and inhalation measurements of 

individuals using granular products. Specifically, the field study was 

conducted in Vero Beach, Florida. A total of 15 volunteers were 

monitored using passive dosimetry (hand/forearm wash solutions and 

personal air monitors). Application of the product was made by pouring 

the granules into the measuring cup/lid attached to the product package, 

and then distributing the granules onto the soil around the base of a 

shrub or onto a flower bed. The granules were then soil-incorporated 

with a garden rake. Each volunteer applied granular disulfoton around 

shrubs while wearing gloves and then again without gloves. Exposure 

data from the 15 replicates who did not wear gloves were reported. A 

lognormal distribution with a mean of 0.23 mg/lb ai, a standard deviation 

of 5.8 mg/lb ai, and maximum value of 3.4 mg/lb ai (representing the 

estimated 99th percentile of the lognormal distribution) was used to 

assess dermal exposure. A single point estimate of 0.00001 mg/lb ai 

(1/2 LOQ) was used for the inhalation UE since all measured values for 

inhalation were non-detects. 

Application Rate: The application rate used in this assessment is 

based on the maximum label application rate of 0.2 lbs ai/1000 ft2. 

Area Treated: The area treated was entered as a uniform 

distribution of 10 to 2000 ft2; these dimensions are based on data from 

the National Gardening Association Survey (Johnson et al, 1999) and 

professional judgment. The low value of 10 sq ft was based on the label 

direction for treating small areas. The high value for ornamental bed size 

was determined by estimating the perimeter of 2200 ft2 house. It is 

assumed that the majority of ornamental beds are located around the 

perimeter of the house. 

ii. Post-Application Exposure 

Since this product is formulated as a bait and is applied as a 

broadcast application over plant foliage or to the soil surrounding 

ornamental plants, post-application exposure is expected to be minimal 

in comparison to the post-application exposure assessed for the 

ornamental use of carbaryl. Therefore, post-application exposure was 

not evaluated for the methiocarb snail and slug bait scenario. 

Section I.D – Page 109 of 277 
f. Pet Collar Scenarios 

The revised NMC CRA also considered exposures through the 

use of flea collar products for carbaryl and propoxur. These 

assessments rely on Agency default assumptions for pet fur transferable 

residues. The dermal contact factor(s) for post-application exposure is 

based on a shampoo and groomer exposure study for carbaryl (each 

groomer shampooed, brushed and groomed 8 dogs) (Mester,1998b). 

Each groomer shampooed the dogs, picked them up wet to be placed in 

crates until all the dogs were shampooed. The dogs were then dried and 

groomed. These activities are likely to result in higher contact factors 

than intermittent contact with a pet wearing a collar. 

i. Applicator Exposure 

Applicator exposure was not directly considered in this 

assessment since it is expected to be minimal when compared to the 

post-application exposure. 

ii. Post-Application Dermal Exposure 

Post-application dermal exposure scenarios were considered for 

both adults and children while post-application non-dietary oral exposure 

scenarios (oral hand-to-mouth) were assumed to apply only to children 

ages 1-5 years old. These data, as described below, were used to 

assess the pet collar uses of both carbaryl and propoxur. Frequency, 

timing, and probability of collar treatments are also incorporated in the 

revised NMC CRA. 

Dermal post-application exposure (to adults and children) was 

calculated as the product of residue concentration (mg/ cm2

), the transfer 

coefficient (in cm2/hour), and the duration of exposure (hours/day). A 

further description of each of these terms is presented below: 

Residue Concentration: The fur residue concentration for the pet 

collar assessment is based on the amount of active ingredient in the 

respective pet collars and Agency default assumptions from the OPP 

Standard Operating Procedures (SOPs) for Residential Exposure 

Assessment (USEPA, 1997b). The residue values for carbaryl and 

propoxur are 0.00012 and 0.000069 mg/ cm2

, respectively. Residues 

were assumed to be available on a daily basis since pet collar products 

are designed to emit residues throughout their active period (120 days 

for carbaryl and 180 days for propoxur). 

Transfer Coefficient: The transfer coefficients used in the dermal 

post-application exposure assessment were derived from a groomer 

Section I.D – Page 110 of 277 
exposure study (Mester, 1998b) in which sixteen different veterinary 

personnel treated/handled eight dogs each, over a two to five hour time 

period. In this assessment, the transfer coefficients for adults and 

children were derived assuming an average transfer efficiency of 2.97% 

from the previous OP pet fur residue transfer efficiencies. For the 

revised NMC CRA, the data were used directly to generate an empirical 

distribution for the dermal transfer coefficient. The selected TCs ranged 

from 180 to 4700 cm2/hour for adults and from 66 to 1800 cm2/hour for 

children. These empirical distributions were used for both pet collar 

scenarios. 

Duration: The time spent in this activity was assumed to follow a 

triangular distribution with a minimum value of 0.03 hours and a 

maximum value of 1.03 hours per day (Freeman et al, 2001). As part of 

this study, macroactivity and microactivity data were collected via 

questionnaires and videotaping of 19 children (aged 3 to 12) for a four 

hour period. The videotapes from the observational portion of this study 

were analyzed to determine frequency of contacts for several mouthing 

behaviors, as well as duration of time each child spent in various 

locations around the home. The results of this study include several 

measurements for the duration of time the observed children spent with 

their pets. 

In this assessment, the duration of exposure is assumed to be 

continuous contact rather than the intermittent contact normally 

associated with pet care (e.g. walking, feeding). Furthermore, dog collar 

residues are likely to be localized around the neck, and therefore, 

contact with other areas of the pet will result in little to no exposure. 

OPP is attempting to draw the distinction between direct contact with a 

treated pet and the time spent with a pet where there is limited contact. 

For example, time spent with pets in and around the house or sleeping in 

the same bed may not result in direct contact for the entire duration. 

The pet collar scenario assessed in the revised NMC CRA uses pet fur 

residues transferred to individuals at a rate found during a study of 

shampooing and grooming, for a duration of approximately 1 hour. Use 

of these data to represent residential exposure to pets is likely to 

encompass all other potential exposure scenarios involving direct or 

indirect contact with treated pets. 

iii. Oral (Hand-to-Mouth) Post-Application Exposure 

Post-application exposure through the oral (hand-to-mouth) route 

was also assessed for children ages 1-5 using the approach detailed in 

Section I.D.4.i of this document. 

Section I.D – Page 111 of 277 
The approach taken to assess hand-to-mouth exposure is the 

same as that used to assess the lawn scenario oral non-dietary 

exposure. The initial hand loading values were determined as a portion 

of total dermal exposure variable to the hands. Additionally, contact 

factors, fraction of surface area of hand mouthed (Zartarian, 2003), 

saliva extraction factor (Geno et al., 1995; Fenske and Lu 1994; Wester 

and Maibach 1989)) are the same as those used in the lawn care 

assessment. The estimates of mouthing frequency were derived from 

several exposure studies and videotaping studies. For the pet collar 

scenario, hand-to-mouth events per hour were based on indoor 

frequencies as defined by a Weibull distribution (mean = 13 events/hour, 

standard deviation = 18). The distribution for frequency of hand-tomouth events for indoor exposures, (provided by ORD’s Dr. Jiaping 

Xue), was calculated based on the same methodology for outdoor 

exposures in the lawn care assessment. OPP believes that this analysis 

provides the best available data to assess children’s hand-to-mouth 

exposures. The duration of exposure values used for the non-dietary 

exposure assessment are the same as those used in the dermal postapplication assessment for the pet collar scenarios presented above. 

. 

g. Golf Course Scenario 

i. Post-Application Dermal Exposure 

Carbaryl is also used on golf courses. The current assessment 

addresses dermal post-application exposure for adults and teens playing 

rounds of golf on treated courses. Post-application exposure was 

estimated as the product of turf-transferable residue (mg/ cm2), transfer 

coefficient (cm2/hour), and time spent in the activity (hours). 

The percent of the population playing golf and the percent of golf 

courses that are treated with carbaryl was also considered and 

incorporated into the assessment. The 1992 Golf Course Operations: 

Cost of Doing Business/Profitability survey conducted by the Center for 

Golf Course Management (CGCM) was used to establish the percent of 

individuals playing golf. The CGCM survey reported that an average of 

12% of the population plays golf. To determine the likelihood of playing 

golf on a treated golf course, percent of golf courses treated data 

provided by Doane’s GolfTrak (1998-1999) were used. These data 

indicated up to 25% of golf courses are treated with carbaryl, depending 

upon the region of use. 

Residue Data: Since liquid broadcast applications to golf course 

turf are permitted, the liquid TTR data (Mester, 1999) were used to 

assess post-application exposure for the golf course scenario. Statistical 

analysis of these data was performed and an initial concentration of 

Section I.D – Page 112 of 277 
0.00065 mg/ cm2

 was calculated and used in this assessment. 

Dissipation is based on a 3.6 day half-life. For details of the statistical 

analysis see Appendix II.D.2. 

Transfer Coefficients: The surrogate data used to derive transfer 

coefficients were based on two measurements of four individuals playing 

golf on two golf courses treated with chlorothalonil (Ballee, 1990), and 

the exposure of golfers (four volunteers) to flurprimidol (Moran et al, 

1987). For both studies, an assumed transfer efficiency of 1% was used 

to calculate the transfer coefficients, since the studies were conducted 

using sprayable formulations. Based on these two studies, a lognormal 

distribution with a mean of 480 cm2/hour and a standard deviation of 160 

cm2/hour was used to represent the transfer coefficient. This distribution 

was truncated at the calculated 99th percentile value of 960 cm2/hour. 

All transfer coefficients are based on individuals wearing short-sleeved 

shirts and short pants. A reduction factor was applied to account for 

body weight and surface area differences for adults and teenagers. 

Duration: The exposure duration for individuals playing golf was 

assumed to be a uniform distribution bounded at the low end by two 

hours and at the upper end at four hours. The four-hour value was 

obtained from the CGCM survey. 

7. Risk 

For all subpopulations, the MOEs are greater than 10 when all uses 

are considered, at the 95th, 99th, and 99.9th percentiles. Graphs for all 

percentiles of regulation and all subpopulations are described in more 

detail in the cumulative chapter (F), of this document. (See Appendix III 

for detailed graphs.) 

8. Summary 

This assessment relied upon the best available data from all 

sources that could be identified. Sources included chemical specific and 

task force-generated data, as well as data from the scientific literature. 

The revised NMC CRA assessment was performed for the 

Southeast region of the United States. While insect growth may slow 

during the winter months in the South, unlike other regions of the 

country, there is no period of dormancy. Since the growing season is 

longer in the South and the associated pest pressures are therefore 

greater, this assessment provides a worst case estimate of exposure. 

The residential assessment of the revised NMC CRA includes the 

carbaryl lawn and golf course use, the carbaryl vegetable and 

ornamental garden use, the methiocarb snail and slug bait use, the 

Section I.D – Page 113 of 277 
carbaryl fruit tree use, and the carbaryl and propoxur pet collar uses. All 

MOEs are greater than 10 and therefore not of concern. 

Section I.D – Page 114 of 277 
Table I.D-4. Summary of NMC Residental Exposure Scenarios 

Lawn Care Scenario 

Applicator Exposure Unit Exposure 

Both dermal and inhalation exposure routes were considered. ORETF studies were used for the granulatreatment scenarios.The ORETF (Outdoor Residential Exposure Task Force) submitted a report (Klonne, of products were used on turf. In these studies, both homeowners and lawn care operators (LCOs) were broadcast applications to turf. All of the data submitted in this report were completed in a series of studiemonitored homeowner exposure resulting from granular spreader (Klonne, 1999/OMA003 Study) and hos1999/OMA004 Study) applications were used in this assessment. Volunteers participating in these exposnon-professionals who use pesticides on their own gardens and lawns. Many of the volunteers selected studies were members of garden clubs. All volunteers made their applications without specific instruction investigators. Unit exposures estimated from these studies cover various clothing scenarios that range frand short-sleeved shirts, to long pants and long-sleeved shirts. All dermal and inhalation unit exposure wexpressed as milligrams exposure per pound of active ingredient handled (mg/lb ai) (referred to as unit exlognormal distributions of the UEs for the lawn applicator scenarios are shown in Table I.D.2. 

Application Rate For all scenarios assessed, OPP used the maximum application rate to assess exposure (8 lbs ai/A was 

scenario). 

Area Treated 

An important variable for estimating home-owner applicator exposure is the size of the lawn. OPP considmedian lawn sizes reported in a journal article by Vinlove and Torla (1995). The means and medians wethe authors noted problems interpreting the data since it is based primarily on low income houses and cothe lot size by the house's foundation (footprint) only. The data do not consider other structures such as dspace such as gardens, which can reportedly reduce the lot size by up to 50%. Similar lawn sizes were n(Johnson et al, 1999) with similar problems encountered with respect to confounding variables such as despaces. For this assessment, OPP used a uniform distribution for lawn size bounded by 1000 ft2 and 20this range considers smaller lawns for residences such as town houses. The upper bound of 20,000 ft2 (reasonable given the type of application equipment assumed to be used by residential applicators. Informsurvey also indicates that many pesticide users make spot treatments of insecticides. Similarly for spot tra uniform distribution for treated area bounded by 100 ft2 and 1000 ft2. 

Dermal Post-Application Exposure Residue 

There are chemical-specific turf transferable residue (TTR) data for granular formulations of carbaryl (Krowas designed to determine transferable residues of carbaryl from both irrigated and non-irrigated turf treaAppendix II.D.2 for study summary). Measured carbaryl residues rapidly declined over the first 4 hours a

Section I.D – Page 115 of 277 
slightly after 12 hours. By the 24-hour sampling interval, the residues declined to approximately 10 perce

time residue value and then steadily dropped to below 1.0 percent of the corresponding 0-time residue va

treatment. In order to provide a conservative estimate of exposure for the revised NMC CRA, only the samirrigated site in Florida were used. This assessment assumes an initial concentration of 0.00021 mg/ cm2

0.8 day half-life, with residues set to zero 14 days after application. Although the carbaryl TTR studies shthe initial residues by 3- to 5-days after application, to provide a conservative estimate of exposure, it is aresidues on the lawn would be available for up to 2 weeks after application. 

TC 

Transfer Coefficients used to assess children’s exposure to treated turf: 

One study was used to assess children’s dermal exposure resulting from granular applications to residen

In this study, a granular formulation of chlorpyrifos was applied, after which seven adults performed pre-cintended to mimic a typical child’s behavior. The subjects performed these activities for a period of four h

turf had dried. Turf had been treated earlier with a granular form of chlorpyrifos and exposure was estimamonitoring the amount of a chlorpyrifos metabolite – 3,4,5, 6-TCP – excreted over the following period of directly measures internal dose and was used to back-calculate a generic “to the skin” transfer coefficient 

specific dermal absorption data for chlorpyrifos (Nolan et al, 1984), These data were further adjusted to a

surface area of adults and children. The study data discussed above was fit to a lognormal distribution w1970 cm2/hr with a standard deviation of 1426 cm2/hr. The lognormal distribution was truncated at the ca

the distribution (i.e. 7224 cm2/hr for the granular application) in order to avoid a distribution which contain

beyond those that are deemed reasonable. (see Appendix II.D.2 for study summary and details of the dis

Transfer Coefficients used to assess adult exposure to treated turf: 

 The Vaccaro study data discussed above were also used to assess exposure to adults following granularevised NMC CRA used a distribution of values for the transfer coefficient characterized by a lognormal darithmetic mean, of 5376 cm2/hr and a standard deviation of 4717 cm2/hr for the granular application. Th

was truncated at the calculated 99th percentile of the distribution (i.e. 23436 cm2/hr for the granular applic

II.D.2 for study summary and details of the distributional analysis). 

Duration 

Another important variable for addressing post-application exposure from home lawn treatment is the durlawns. In this revised NMC CRA, cumulative distributions of durations on lawns of up to two hours were uexposure on lawns. These data are presented in Table 15-64 of the EPA’s Exposure Factor’s Handbook however, OPP notes that the percentiles above the 95th have the same values (121 minutes). A similar cgiven for children ages one to five. In order to be protective of children and to address the uncertainty in 

the exposure factor data, OPP selected an empirical distribution (which was expressed as a cumulative dEFH Table 15-80 with a bound of 3.5 hours for children (USEPA, 1997a). This distribution represents the 

outdoors rather than just on lawns. This adjustment allows for additional time that children may spend ouschools) where there is potential for additional contact with treated turf. 

Oral non-dietary Post-Application Exposure Initial Hand Loadings 

Hand loading (HR/2) is based on loading concepts used in SHEDS and CARES. The initial amount of reshand is determined as a percentage of total dermal exposure. The EPA EFH indicates that the surface aapproximately 6% of the total surface area of the body for children age 4 and under; 5% for children age 2002c). The algorithm assumes mouthing one hand at a time, therefore, hand loading residues are divide

Section I.D – Page 116 of 277 
Frequency of 

mouthing events 

For the revised NMC CRA assessment, the frequency of hand-to-mouth events is based on Xue et al, 20mouthing frequency were derived from several exposure studies and videotaping studies. Statistical anaWeibull distribution best fit the data. For the lawn care scenario, hand-to-mouth events per hour were bafrequencies as defined by a Weibull distribution (mean = 6 events/hour, standard deviation = 8). OPP beanalysis cited above provides the best available data to assess children’s hand-to-mouth exposures. 

Surface Area Mouthed 

The revised NMC CRA relied on Zartarian’s (2003) analysis of surface area of hand mouthed. The analy

2000 data to determine the fraction of the hand mouthed. The fraction of hand mouthed values were fit w

(mean = 0.13 events/hour, standard deviation = 0.06). 

Saliva Extraction Factor 

To address the removal of residues from the hands by saliva during mouthing events, several studies weremoval efficiency of residues on hands by saliva and other substances (e.g., ethanol) suggests a range (Geno et al., 1995; Fenske and Lu 1994; Wester and Maibach 1989). Based on the above studies, a unif50% was used in this assessment for saliva extraction factors. 

Duration 

The time spent on the lawn was estimated as a cumulative distribution ranging from 0 hours to 3.5 hours. childrens’ exposure and to address the uncertainty of the upper percentiles of the exposure factor data, O

distribution from EFH (USEPA, 1997a) Table 15-80 with a bound of 3.5 hours for children 1 to 5 years old

represents the amount of time spent outdoors. This allows for the time that children spend outdoors not oparks and near schools. 

Vegetable Garden Scenario 

Dermal and Inhalation Applicator Exposure Unit Exposure 

Dermal and inhalation unit exposures were derived from chemical-specific data (Mester, 1998a) for dust (sprayer, and liquid hose-end sprayer applications to vegetable gardens. The UE for all garden scenarios distribution as listed in Table I.D.3. 

Application Rate 

An application rate of 2 lbs ai/A was used for all liquid vegetable garden scenarios (hose-end sprayers an

even though trigger pump sprayer rates are considerably lower. This assessment conservatively uses th

for all liquid scenarios. Due to recent mitigation, the maximum application rate for dust formulations is 0.5 Table I.A). The exposure assessment for dust formulation applied to home gardens assumes use of one treatment. 

Area Treated 

For vegetable gardens, the area treated was entered as a lognormal distribution (mean = 4600 ft2, standa

Taximum = 8000 ft2); these dimensions are based on data from the National Gardening Association Surv

In these assessments, it is assumed that the entire garden is treated. Home gardens consist of many typ

may not be treated since they tend to have different pest pressures (e.g. squash vine borer and corn earw

the same time). 

Dermal Post-Application Exposure 

Residue 

Chemical-specific dislodgeable foliar residue data on sunflowers (Klonne et al, 1999) were used to assesexposure. Although OPP has additional information regarding carbaryl specific DFR data on cabbage (Ksunflower DFR data were used since the residues detected in the sunflower study were higher than those study. Statistical analysis of the carbaryl sunflower DFR data was performed. The initial residue concentrwere determined to be 0.0061 mg/ cm2 and 5 days, respectively. 

Section I.D – Page 117 of 277 
TC 

For the vegetable garden scenario, transfer coefficients were characterized by a uniform distribution rangcm2/hour, to reflect a range of gardening tasks for a variety of crops of differing heights and foliage develo

this assessment were derived from studies on chrysanthemum pinching (Rotondaro, 2000) and tomato haAll transfer coefficients are based on individuals wearing short-sleeved shirts and short pants. A reductioaccount for body weights and surface area differences between adults and teenagers. 

Duration 

The time spent harvesting or performing post-application maintenance activities was represented by a un

from 0.17 hour/day to 1 hour/day. These estimates of time spent in the garden performing post applicatiofrequency of applications) were based on the ORETF survey (Johnson et al, 1999). 

Ornamental Plants and Shrub Scenario 

Dermal and Inhalation Applicator Exposure 

Unit Exposure Dermal and inhalation unit exposures were derived from chemical-specific data for carbaryl used on orna

1998a; Merricks, 1998). The UE for all garden scenarios are based on lognormal distribution as listed in 

Application Rate 

An application rate of 2 lbs ai/A was used for all liquid vegetable garden scenarios (hose-end sprayers an

even though trigger pump sprayer rates are considerably lower. This assessment conservatively uses th

for all liquid scenarios. Due to recent mitigation, the maximum application rate for dust formulations is 0.5 Table II.A). The exposure assessment for dust formulation applied to ornamental gardens assumes use treatment. 

Area Treated 

The area treated was entered as a uniform distribution of 500 to 2000 ft2; these dimensions are based on 

Gardening Association Survey (Johnson et al, 1999) and professional judgment. The ornamental bed sizestimating the perimeter of 2200 ft2 house. It is assumed that the majority of ornamental beds are located 

the house. 

Dermal Post-Application Exposure 

Residue 

Chemical-specific dislodgeable foliar residue data on sunflowers (Klonne et al, 1999) were used to assesexposure from harvesting or performing maintenance activities in ornamental gardens. Although OPP haregarding carbaryl specific DFR data on cabbage (Klonne et al, 2000a), the sunflower DFR data were usedetected in the sunflower study were higher than those detected in the cabbage study. A statistical analyperformed and the initial concentration was estimated to be 0.0061 mg/ cm2 . Residue dissipation is base

The half-life used in this assessment was determined from the statistical analysis of the carbaryl sunflowedetailed explanation of the statistical analysis of this data is provided in Appendix II.D.2. 

TC 

For the ornamental garden scenario, a uniform distribution of transfer coefficients, ranging from 99 to 550 

reflect a range of gardening tasks. The TCs used in this assessment were derived from studies that evalpinching (Rotondaro, 2000) and nursery stock pruning (Klonne et al, 2000b). All transfer coefficients are 

wearing short-sleeved shirts and short pants. A reduction factor was applied to account for body weights differences between adults and teenagers. 

Section I.D – Page 118 of 277 
Duration 

The time spent harvesting or performing post-application maintenance activities was represented by a un

from 0.17 hour/day to 1 hour/day. These estimates of time spent in the garden performing post-applicatiofrequency of applications) were based on the ORETF survey (Johnson et al, 1999). 

Fruit Tree Scenario 

Dermal and Inhalation Applicator Exposure 

Unit Exposure 

The dermal and inhalation unit exposures were derived from chemical-specific data for liquid handwand a

(Merricks, 1998). These unit exposures are based on study data in which applications were made with hathe waist as well as overhead. The UEs for fruit tree scenario are based on lognormal distribution as liste

Application Rate For all scenarios assessed, OPP used the maximum application rate to assess exposure (8 lbs ai/A was 

scenario). 

Area Treated 

For fruit trees, most of which are of the dwarf variety and therefore occupy relatively small areas, the area uniform distribution (minimum 500 ft2, maximum 1000 ft2). The maximum value in this distribution was ba

applications made at the maximum rate (8lbs ai/A) for fruit tree applications. 

Dermal Post-Application Exposure Residue 

Chemical specific dislodgeable foliar residue data on olive trees (Klonne et al, 2000c) were used to asses

exposure for this scenario. Statistical analysis of this data was performed and the initial residue concentr

be 0.0035 mg/ cm2 . Residue dissipation is based on the half-life of 7 days (as determined by the statistic

olive DFR data). 

TC 

For the fruit tree scenario, the distribution of transfer coefficient was characterized as lognormal, with a m

standard deviation of 260 cm2/hour. The TCs were based on an apple pruning study. All transfer coefficie

individuals wearing short-sleeved shirts and short pants. A reduction factor was applied to account for bo

area differences between adults and teenagers. 

Duration 

The time spent harvesting or performing post-application maintenance activities was represented by a un

from 0.17 hour/day to 1 hour/day. These estimates of time spent in the garden performing post-applicatiofrequency of applications) were based on the ORETF survey (Johnson et al, 1999). 

Ornamental Garden - Snail and Slug Bait Scenario Dermal and Inhalation Applicator Exposure Unit Exposure 

The dermal and inhalation UEs for the methiocarb snail and slug bait scenario were based on study data to residential shrubs and flower beds (Merricks, 2001). The surrogate data consist of dermal and inhalatiindividuals using granular products. Specifically, the field study was conducted in Vero Beach, Florida. A were monitored using passive dosimetry (hand/forearm wash solutions and personal air monitors). Applicmade by pouring the granules into the measuring cup/lid attached to the product package, and then distri

Section I.D – Page 119 of 277 
the soil around the base of a shrub or onto a flower bed. The granules were then soil-incorporated with a 

volunteer applied granular disulfoton around shrubs while wearing gloves and then again without gloves. 15 replicates who did not wear gloves were reported. A lognormal distribution with a mean of 0.23 mg/lb 5.8 mg/lb ai, and maximum value of 3.4 mg/lb ai (representing the estimated 99th percentile of the lognor

to assess dermal exposure. A single point estimate of 0.00001 mg/lb ai (1/2 LOQ) was used for the inhalmeasured values for inhalation were non-detects. 

Application Rate The application rate used in this assessment is based on the maximum label application rate of 0.2 lbs ai/Area Treated 

The area treated was entered as a uniform distribution of 10 to 2000 ft2; these dimensions are based on d

Gardening Association Survey (Johnson et al, 1999) and professional judgment. The low value of 10 sq ft was direction for treating small areas. The high value for ornamental bed size was determined by estimating t

house. It is assumed that the majority of ornamental beds are located around the perimeter of the house

Pet Collar Scenarios 

Dermal Post-Application Exposure Residue 

The fur residue concentration for the pet collar assessment is based on the amount of active ingredient in and Agency default assumptions from the OPP SOPs for Residential Exposure Assessment (USEPA, 19

for carbaryl and propoxur are 0.00012 and 0.000069 mg/ cm2, respectively. Residues were assumed to b

basis since pet collar products are designed to emit residues throughout their active period (120 days for propoxur). 

TC 

The transfer coefficients used in the dermal post-application exposure assessment was derived from a gr(Mester, 1998b) in which sixteen different veterinary personnel treated/handled eight dogs each, over a twIn this assessment, the transfer coefficients for adults and children were derived assuming an average trafrom the previous OP pet fur residue transfer efficiencies. For the revised NMC CRA, the data were used empirical distribution for the dermal transfer coefficient. The selected TCs ranged from 180 to 4700 cm2/h

to 1800 cm2/hour for children. These empirical distributions were used for both pet collar scenarios. 

Duration 

The time spent in this activity was assumed to follow a triangular distribution with minimum value of 0.03 value of 1.03 hours per day (Freeman et al, 2001). As part of this study, macroactivity and microactivity d

questionnaires and videotaping of 19 children (aged 3 to 12) for a four hour period. The videotapes from tof this study were analyzed to determine frequency of contacts for several mouthing behaviors, as well as 

child spent in various locations around the home. The results of this study include several measurements 

the observed children spent with their pets. 

Oral non-dietary Post-Application Exposure Initial Hand Loadings 

Hand loading (HR/2) is based on loading concepts used in SHEDS and CARES. The initial amount of reshand is determined as a percentage of total dermal exposure. The EPA Exposure Factors Handbook ind

area of the hands is approximately 6% of the total surface area of the body for children age 4 and under; over (USEPA, 2002c). The algorithm assumes mouthing one hand at a time, therefore, hand loading res

Section I.D – Page 120 of 277 
Frequency of 

mouthing events 

The estimates of mouthing frequency were derived from several exposure studies and observational studscenario, hand-to-mouth events per hour were based on indoor frequencies as defined by a Weibull distrevents/hour, standard deviation = 18). The distribution for frequency of hand-to-mouth events for indoor eORD’s Dr. Jiaping Xue, was calculated using the same methodology used to determine the frequency of outdoor exposures that was used in the lawn care assessment. 

Surface Area Mouthed 

The revised NMC CRA relied on Zartarian’s (2003) analysis of surface area of hand mouthed. The analy

2000 data to determine the fraction of the hand mouthed. The fraction of hand mouthed values were fit w

(mean = 0.13 events/hour, standard deviation = 0.06). 

Saliva Extraction Factor 

To address the removal of residues from the hands by saliva during mouthing events, several studies weremoval efficiency of residues on hands by saliva and other substances (e.g., ethanol) suggests a range (Geno et al., 1995; Fenske and Lu 1994; Wester and Maibach 1989). Based on the above studies, a unif50% was used in this assessment for saliva extraction factors. 

Duration The duration of exposure values used for the non-dietary exposure assessment are the same as those us

application assessment for the pet collar scenarios presented above. 

Golf Course Scenario Dermal Post-Application Exposure Residue 

Since liquid broadcast applications to golf course turf are permitted, the liquid TTR data (Mester, 1999) usapplication exposure for the golf course scenario. Statistical analysis of this data was performed and an 0.00065 mg/ cm2 was calculated and used in this assessment. Dissipation is based on a 3.6 day half-life

statistical analysis see Appendix II.D.2. 

TC 

The surrogate data used to derive transfer coefficients were based on two measurements of four individucourses treated with chlorothalonil (Ballee, 1990), and the exposure of golfers (four volunteers) to flurprimFor both studies, an assumed transfer efficiency of 1% was used to calculate the transfer coefficients, sinconducted using sprayable formulations. Based on these two studies, a lognormal distribution with a mea

standard deviation of 160 cm2/hour was used to represent the transfer coefficient. This distribution was tr

99th percentile value of 960 cm2/hour. All transfer coefficients are based on individuals wearing short sle

pants. A reduction factor was applied to account for body weight and surface area differences for adults 

Duration The exposure duration for individuals playing golf was assumed to be a uniform distribution bounded at th

and at the upper end at four hours. The four-hour value was obtained from the CGCM survey. 

Applicator Exposure 

Section I.D – Page 121 of 277 
Unit Exposure 

Both dermal and inhalation exposure routes were considered. ORETF studies were used for the granulatreatment scenarios.The ORETF (Outdoor Residential Exposure Task Force) submitted a report (Klonne, of products were used on turf. In these studies, both homeowners and lawn care operators (LCOs) were broadcast applications to turf. All of the data submitted in this report were completed in a series of studiemonitored homeowner exposure resulting from granular spreader (Klonne, 1999/OMA003 Study) and hos1999/OMA004 Study) applications were used in this assessment. Volunteers participating in these exposnon-professionals who use pesticides on their own gardens and lawns. Many of the volunteers selected studies were members of garden clubs. All volunteers made their applications without specific instruction investigators. Unit exposures estimated from these studies cover various clothing scenarios that range frand short-sleeved shirts, to long pants and long- sleeved shirts. All dermal and inhalation unit exposure wexpressed as milligrams exposure per pound of active ingredient handled (mg/lb ai) (referred to as unit exlognormal distributions of the UEs for the lawn applicator scenarios are shown in Table I.D.2. 

Application Rate For all scenarios assessed, OPP used the maximum application rate to assess exposure (8 lbs ai/A was 

scenario). 

Area Treated 

An important variable for estimating home-owner applicator exposure is the size of the lawn. OPP considmedian lawn sizes reported in a journal article by Vinlove and Torla (1995). The means and medians we

the authors noted problems interpreting the data since it is based primarily on low income houses and cothe lot size by the house's foundation (footprint) only. The data do not consider other structures such as dspace such as gardens, which can reportedly reduce the lot size by up to 50%. Similar lawn sizes were n(Johnson et al, 1999) with similar problems encountered with respect to confounding variables such as despaces. For this assessment, OPP used a uniform distribution for lawn size bounded by 1000 ft2 and 20,

this range considers smaller lawns for residences such as town houses. The upper bound of 20,000 ft2 (~ 

reasonable given the type of application equipment assumed to be used by residential applicators. Informsurvey also indicates that many pesticide users make spot treatments of insecticides. Similarly for spot tra uniform distribution for treated area bounded by 100 ft2 and 1000 ft2 . 

Dermal Post-Application Exposure Residue 

There are chemical-specific turf transferable residue (TTR) data for granular formulations of carbaryl (Krowas designed to determine transferable residues of carbaryl from both irrigated and non-irrigated turf treaAppendix II.D.2 for study summary). Measured carbaryl residues rapidly declined over the first 4 hours aslightly after 12 hours. By the 24-hour sampling interval, the residues declined to approximately 10 perce

time residue value and then steadily dropped to below 1.0 percent of the corresponding 0-time residue va

treatment. In order to provide a conservative estimate of exposure for the revised NMC CRA, only the samirrigated site in Florida were used. This assessment assumes an initial concentration of 0.00021 mg/ cm2 

a 0.8 day half-life, with residues set to zero 14 days after application. Although the carbaryl TTR studies 

of the initial residues by 3- to 5-days after application, to provide a conservative estimate of exposure, it is residues on the lawn would be available for up to 2 weeks after application. 

Section I.D – Page 122 of 277 
TC 

Transfer Coefficients used to assess children’s exposure to treated turf: 

One study was used to assess children’s dermal exposure resulting from granular applications to residenIn this study, a granular formulation of chlorpyrifos was applied, after which seven adults performed pre-cintended to mimic a typical child’s behavior. The subjects performed these activities for a period of four h

turf had dried. Turf had been treated earlier with a granular form of chlorpyrifos and exposure was estimamonitoring the amount of a chlorpyrifos metabolite – 3,4,5, 6-TCP – excreted over the following period of directly measures internal dose and was used to back-calculate a generic “to the skin” transfer coefficient 

specific dermal absorption data for chlorpyrifos (Nolan et al, 1984). These data were further adjusted to a

surface area of adults and children. The study data discussed above was fit to a lognormal distribution w1970 cm2/hr with a standard deviation of 1426 cm2/hr. The lognormal distribution was truncated at the ca

the distribution (i.e. 7224 cm2/hr for the granular application) in order to avoid a distribution which contain

beyond those that are deemed reasonable. (See Appendix II.D.2 for study summary and details of the dis

Transfer Coefficients used to assess adult exposure to treated turf: 

 The Vaccaro study data discussed above were also used to assess exposure to adults following granularevised NMC CRA used a distribution of values for the transfer coefficient characterized by a lognormal darithmetic mean, of 5376 cm2/hr and a standard deviation of 4717 cm2/hr for the granular application. Th

was truncated at the calculated 99th percentile of the distribution (i.e. 23436 cm2/hr for the granular applic

II.D.2 for study summary and details of the distributional analysis.) 

Duration 

Another important variable for addressing post-application exposure from home lawn treatment is the durlawns. In this revised NMC CRA, cumulative distributions of durations on lawns of up to two hours were uexposure on lawns. These data are presented in Table 15-64 of the EPA’s Exposure Factor’s Handbook however, OPP notes that the percentiles above the 95th have the same values (121 minutes). A similar cgiven for children ages one to five. In order to be protective of children and to address the uncertainty in 

the exposure factor data, OPP selected an empirical distribution (which was expressed as a cumulative dEFH Table 15-80 with a bound of 3.5 hours for children (USEPA, 1997a). This distribution represents the outdoors rather than just on lawns. This adjustment allows for additional time that children may spend ouschools) where there is potential for additional contact with treated turf. 

Oral non-dietary Post-Application Exposure 

Initial Hand Loadings 

Hand loading (HR/2) is based on loading concepts used in SHEDS and CARES. The initial amount of reshand is determined as a percentage of total dermal exposure. The EPA EFH indicates that the surface aapproximately 6% of the total surface area of the body for children age 4 and under; 5% for children age 2002c). The algorithm assumes mouthing one hand at a time, therefore, hand loading residues are divide

Frequency of mouthing events 

For the revised NMC CRA assessment, the frequency of hand-to-mouth events is based on Xue et al, 20mouthing frequency were derived from several exposure studies and videotaping studies. Statistical anaWeibull distribution best fit the data. For the lawn care scenario, hand-to-mouth events per hour were bafrequencies as defined by a Weibull distribution (mean = 6 events/hour, standard deviation = 8). OPP beanalysis cited above provides the best available data to assess children’s hand-to-mouth exposures. 

Section I.D – Page 123 of 277 
Surface Area 

Mouthed 

The revised NMC CRA relied on Zartarian’s (2003) analysis of surface area of hand mouthed. The analy

2000 data to determine the fraction of the hand mouthed. The fraction of hand mouthed values were fit w

(mean = 0.13 events/hour, standard deviation = 0.06). 

Saliva Extraction Factor 

To address the removal of residues from the hands by saliva during mouthing events, several studies weremoval efficiency of residues on hands by saliva and other substances (e.g., ethanol) suggests a range (Geno et al., 1995; Fenske and Lu 1994; Wester and Maibach 1989). Based on the above studies, a unif50% was used in this assessment for saliva extraction factors. 

Duration 

The time spent on the lawn was estimated as a cumulative distribution ranging from 0 hours to 3.5 hours. childrens’ exposure and to address the uncertainty of the upper percentiles of the exposure factor data, O

distribution from EFH (USEPA, 1997a) Table 15-80 with a bound of 3.5 hours for children 1 to 5 years old

represents the amount of time spent outdoors. This allows for the time that children spend outdoors not oparks and near schools. 

Vegetable Garden Scenario 

Dermal and Inhalation Applicator Exposure Unit Exposure 

Dermal and inhalation unit exposures were derived from chemical-specific data (Mester, 1998a) for dust (sprayer, and liquid hose-end sprayer applications to vegetable gardens. The UE for all garden scenarios distribution as listed in Table I.D.3. 

Application Rate 

An application rate of 2 lbs ai/A was used for all liquid vegetable garden scenarios (hose-end sprayers an

even though trigger pump sprayer rates are considerably lower. This assessment conservatively uses th

for all liquid scenarios. Due to recent mitigation, the maximum application rate for dust formulations is 0.5 exposure assessment for dust formulation applied to home gardens assumes use of one entire container 

Area Treated 

For vegetable gardens, the area treated was entered as a lognormal distribution (mean = 4600 ft2, standa

maximum = 8000 ft2); these dimensions are based on data from the National Gardening Association Surv

In these assessments, it is assumed that the entire garden is treated. Home gardens consist of many typ

may not be treated since they tend to have different pest pressures (e.g. squash vine borer and corn earw

the same time). 

Dermal Post-Application Exposure Residue 

Chemical-specific dislodgeable foliar residue data on sunflowers (Klonne et al, 1999) were used to assesexposure. Although OPP has additional information regarding carbaryl specific DFR data on cabbage (Ksunflower DFR data were used since the residues detected in the sunflower study were higher than those study. Statistical analysis of the carbaryl sunflower DFR data was performed. The initial residue concentwere determined to be 0.0061 mg/ cm2 and 5 days, respectively. 

TC 

For the vegetable garden scenario, transfer coefficients were characterized by a uniform distribution rangcm2/hour, to reflect a range of gardening tasks for a variety of crops of differing heights and foliage develo

this assessment were derived from studies on chrysanthemum pinching (Rotondaro, 2000) and tomato haAll transfer coefficients are based on individuals wearing short-sleeved shirts and short pants. A reductioaccount for body weights and surface area differences between adults and teenagers. 

Section I.D – Page 124 of 277 
Duration 

The time spent harvesting or performing post-application maintenance activities was represented by a un

from 0.17 hour/day to 1 hour/day. These estimates of time spent in the garden performing post applicatiofrequency of applications) were based on the ORETF survey (Johnson et al, 1999). 

Ornamental Plants and Shrub Scenario 

Dermal and Inhalation Applicator Exposure Unit Exposure Dermal and inhalation unit exposures were derived from chemical-specific data for carbaryl used on orna

1998a; Merricks, 1998). The UE for all garden scenarios are based on lognormal distribution as listed in 

Application Rate 

An application rate of 2 lbs ai/A was used for all liquid vegetable garden scenarios (hose-end sprayers an

even though trigger pump sprayer rates are considerably lower. This assessment conservatively uses th

for all liquid scenarios. Due to recent mitigation, the maximum application rate for dust formulations is 0.5 exposure assessment for dust formulation applied to ornamental gardens assumes use of one entire con

Area Treated 

The area treated was entered as a uniform distribution of 500 to 2000 ft2; these dimensions are based on 

Gardening Association Survey (Johnson et al, 1999) and professional judgment. The ornamental bed sizestimating the perimeter of 2200 ft2 house. It is assumed that the majority of ornamental beds are located 

the house. 

Dermal Post-Application Exposure Residue 

Chemical-specific dislodgeable foliar residue data on sunflowers (Klonne et al, 1999) were used to assesexposure from harvesting or performing maintenance activities in ornamental gardens. Although OPP haregarding carbaryl specific DFR data on cabbage (Klonne et al, 2000a), the sunflower DFR data were usedetected in the sunflower study were higher than those detected in the cabbage study. A statistical analyperformed and the initial concentration was estimated to be 0.0061 mg/ cm2. Residue dissipation is based 

The half-life used in this assessment was determined from the statistical analysis of the carbaryl sunflowedetailed explanation of the statistical analysis of this data is provided in Appendix II.D.2. 

TC 

For the ornamental garden scenario, a uniform distribution of transfer coefficients, ranging from 99 to 550 

reflect a range of gardening tasks. The TCs used in this assessment were derived from studies that evalpinching (Rotondaro, 2000) and nursery stock pruning (Klonne et al, 2000b). All transfer coefficients are wearing short-sleeved shirts and short pants. A reduction factor was applied to account for body weights differences between adults and teenagers. 

Duration 

The time spent harvesting or performing post-application maintenance activities was represented by a un

from 0.17 hour/day to 1 hour/day. These estimates of time spent in the garden performing post applicatiofrequency of applications) were based on the ORETF survey (Johnson et al, 1999). 

Fruit Tree Scenario 

Section I.D – Page 125 of 277 
Dermal and Inhalation Applicator Exposure 

Unit Exposure 

The dermal and inhalation unit exposures were derived from chemical-specific data for liquid handwand a

(Merricks, 1998). These unit exposures are based on study data in which applications were made with hathe waist as well as overhead. The UEs for fruit tree scenario are based on lognormal distribution as liste

Application Rate For all scenarios assessed, OPP used the maximum application rate to assess exposure (8 lbs ai/A was 

scenario). 

Area Treated 

For fruit trees, most of which are of the dwarf variety and therefore occupy relatively small areas, the area uniform distribution (minimum 500 ft2, maximum 1000 ft2). The maximum value in this distribution was ba

applications made at the maximum rate (8lbs ai/A) for fruit tree applications. 

Dermal Post-Application Exposure Residue 

Chemical specific dislodgeable foliar residue data on olive trees (Klonne et al, 2000c) were used to asses

exposure for this scenario. Statistical analysis of this data was performed and the initial residue concentr

be 0.0035 mg/ cm2 . Residue dissipation is based on the half-life of 7 days (as determined by the statistic

olive DFR data). 

TC 

For the fruit tree scenario, the distribution of transfer coefficient was characterized as lognormal, with a m

standard deviation of 260 cm2/hour. The TCs were based on an apple pruning study. All transfer coefficie

individuals wearing short-sleeved shirts and short pants. A reduction factor was applied to account for bo

area differences between adults and teenagers. 

Duration 

The time spent harvesting or performing post-application maintenance activities was represented by a un

from 0.17 hour/day to 1 hour/day. These estimates of time spent in the garden performing post applicatiofrequency of applications) were based on the ORETF survey (Johnson et al, 1999). 

Ornamental Garden - Snail and Slug Bait Scenario 

Dermal and Inhalation Applicator Exposure Unit Exposure 

The dermal and inhalation UEs for the methiocarb snail and slug bait scenario were based on study data to residential shrubs and flower beds (Merricks, 2001). The surrogate data consist of dermal and inhalatiindividuals using granular products. Specifically, the field study was conducted in Vero Beach, Florida. A were monitored using passive dosimetry (hand/forearm wash solutions and personal air monitors). Applicmade by pouring the granules into the measuring cup/lid attached to the product package, and then distrithe soil around the base of a shrub or onto a flower bed. The granules were then soil-incorporated with a volunteer applied granular disulfoton around shrubs while wearing gloves and then again without gloves. replicates who did not wear gloves were reported. A lognormal distribution with a mean of 0.23 mg/lb ai, mg/lb ai, and maximum value of 3.4 mg/lb ai (representing the estimated 99th percentile of the lognormal assess dermal exposure. A single point estimate of 0.00001 mg/lb ai (1/2 LOQ) was used for the inhalati

Section I.D – Page 126 of 277 
values for inhalation were non-detects. 

Application Rate The application rate used in this assessment is based on the maximum label application rate of 0.2 lbs ai/Area Treated 

The area treated was entered as a uniform distribution of 10 to 2000 ft2; these dimensions are based on d

Gardening Association Survey (Johnson et al, 1999) and professional judgment. The low value of 10 sq ft was direction for treating small areas. The high value for ornamental bed size was determined by estimating t

house. It is assumed that the majority of ornamental beds are located around the perimeter of the house

Pet Collar Scenarios 

Dermal Post-Application Exposure Residue 

The fur residue concentration for the pet collar assessment is based on the amount of active ingredient in and Agency default assumptions from the OPP SOPs for Residential Exposure Assessment (USEPA, 19

for carbaryl and propoxur are 0.00012 and 0.000069 mg/ cm2, respectively. Residues were assumed to b

basis since pet collar products are designed to emit residues throughout their active period (120 days for propoxur). 

TC 

The transfer coefficients used in the dermal post-application exposure assessment was derived from a gr(Mester, 1998b) in which sixteen different veterinary personnel treated/handled eight dogs each, over a twIn this assessment, the transfer coefficients for adults and children were derived assuming an average trafrom the previous OP pet fur residue transfer efficiencies. For the revised NMC CRA, the data were used empirical distribution for the dermal transfer coefficient. The selected TCs ranged from 180 to 4700 cm2/h

to 1800 cm2/hour for children. These empirical distributions were used for both pet collar scenarios. 

Duration 

The time spent in this activity was assumed to follow a triangular distribution with minimum value of 0.03 value of 1.03 hours per day (Freeman et al, 2001). As part of this study, macroactivity and microactivity d

questionnaires and videotaping of 19 children (aged 3 to 12) for a four hour period. The videotapes from 

of this study were analyzed to determine frequency of contacts for several mouthing behaviors, as well as 

child spent in various locations around the home. The results of this study include several measurements 

the observed children spent with their pets. 

Oral non-dietary Post-Application Exposure Initial Hand Loadings 

Hand loading (HR/2) is based on loading concepts used in SHEDS and CARES. The initial amount of reshand is determined as a percentage of total dermal exposure. The EPA Exposure Factors Handbook ind

area of the hands is approximately 6% of the total surface area of the body for children age 4 and under; over (USEPA, 2002c). The algorithm assumes mouthing one hand at a time, therefore, hand loading res

Frequency of mouthing events 

The estimates of mouthing frequency were derived from several exposure studies and observational studscenario, hand-to-mouth events per hour were based on indoor frequencies as defined by a Weibull distrevents/hour, standard deviation = 18). The distribution for frequency of hand-to-mouth events for indoor eORD’s Dr. Jiaping Xue, was calculated using the same methodology used to determine the frequency of 

Section I.D – Page 127 of 277 
outdoor exposures that was used in the lawn care assessment. 

Surface Area Mouthed 

The revised NMC CRA relied on Zartarian’s (2003) analysis of surface area of hand mouthed. The analy

2000 data to determine the fraction of the hand mouthed. The fraction of hand mouthed values were fit w

(mean = 0.13 events/hour, standard deviation = 0.06). 

Saliva Extraction Factor 

To address the removal of residues from the hands by saliva during mouthing events, several studies weremoval efficiency of residues on hands by saliva and other substances (e.g., ethanol) suggests a range (Geno et al., 1995; Fenske and Lu 1994; Wester and Maibach 1989). Based on the above studies, a unif50% was used in this assessment for saliva extraction factors. 

Duration The duration of exposure values used for the non-dietary exposure assessment are the same as those us

application assessment for the pet collar scenarios presented above. 

Golf Course Scenario Dermal Post-Application Exposure Residue 

Since liquid broadcast applications to golf course turf are permitted, the liquid TTR data (Mester, 1999) usapplication exposure for the golf course scenario. Statistical analysis of this data was performed and an 0.00065 mg/ cm2 was calculated and used in this assessment. Dissipation is based on a 3.6 day half-life

statistical analysis see Appendix II.D.2. 

TC 

The surrogate data used to derive transfer coefficients were based on two measurements of four individucourses treated with chlorothalonil (Ballee, 1990), and the exposure of golfers (four volunteers) to flurprimFor both studies, an assumed transfer efficiency of 1% was used to calculate the transfer coefficients, sinconducted using sprayable formulations. Based on these two studies, a lognormal distribution with a mea

standard deviation of 160 cm2/hour was used to represent the transfer coefficient. This distribution was tr

99th percentile value of 960 cm2/hour. All transfer coefficients are based on individuals wearing short sle

pants. A reduction factor was applied to account for body weight and surface area differences for adults 

Duration The exposure duration for individuals playing golf was assumed to be a uniform distribution bounded at th

and at the upper end at four hours. The four-hour value was obtained from the CGCM survey. 

Section I.D – Page 128 of 277 
E. Cumulative Risk from NMC Pesticides in Drinking 

Water 

1. Introduction 

The Food Quality Protection Act (FQPA) of 1996 requires the 

Agency to assess the risks from different pesticides having a common 

mechanism of action, focusing on the likelihood that a person will be 

concurrently exposed to multiple pesticides from multiple sources (food, 

drinking water, and residential uses). Ideally, data to support the 

drinking water portion of this exposure assessment would consist of 

information on multiple pesticides and their transformation products, 

collected from sufficient drinking water sources throughout the U.S. and 

at a sufficient frequency to reflect the range in spatial and temporal 

patterns of pesticide occurrence in water. The great diversity of 

geographic-, climatic-, and time-dependent factors that affect the levels 

of pesticide residues in water creates unique challenges in characterizing 

drinking water exposure. EPA’s Office of Pesticide Programs (OPP) 

must rely on both available monitoring data and modeling to develop 

sufficient data for use in the exposure assessment. 

The Agency used the same methods for estimating surface water 

exposure in the revised NMC CRA as it did in the OP CRA (USEPA, 

2002b; FIFRA SAP, 2002) because of similarities in use (both NMCs and 

OPs are insecticides), hazard endpoints (ChE inhibition occurring in the 

acute- or short-term), and exposure requirements (estimates of peak 

concentrations and time-series distributions). 

Unlike the OP pesticides for which surface water is the likely source 

of concern for drinking water, the NMCs also are likely to reach groundwater sources of drinking water. The Agency presented a conceptual 

model for ground water exposure and a plan for evaluating the capability 

of three ground water models to estimate NMC concentrations to the 

FIFRA SAP in February, 2005. Based on feedback from the SAP 

(FIFRA SAP, 2005a), EPA followed up with a revised conceptual model 

and analysis plan using one of the models evaluated in the preliminary 

assessment (FIFRA SAP, 2005b). 

The revised NMC CRA follows the same approach as outlined in 

the preliminary assessment (USEPA, 2005b), and includes several 

additional ground water exposure scenarios to further capture the range 

of high leaching potential areas in high NMC use areas, as well as a 

more representative assumption for the depth to groundwater. Based on 

analysis of additional monitoring data, the Agency has been better able 

to identify the specific conditions that are likely to result in high NMC 

Section I.E – Page 129 of 277 
exposure in private drinking water wells and to better characterize the 

spatial extent of potential high NMC exposure areas. 

In addition, the reported cumulative NMC exposures in this section 

reflect the revised relative potency, inter-species, and FQPA safety 

factors documented in the Hazard chapter (I.B) of this revised 

assessment. 

2. Problem Formulation 

Pesticide concentrations found in drinking water are not random, 

but are in large part determined by the amount, method, timing and 

location of pesticide application, the physical characteristics of the 

watersheds and/or aquifers in which the community water supplies 

(CWS) or wells are located, and other environmental factors, such as 

rainfall, which can cause the pesticide to move from the location where it 

was applied. 

a. Drinking Water Exposure Needs for the NMC Cumulative 

Assessment 

For the NMC group, the toxicity endpoint of concern results from 

short-term exposure (acute effects). To adequately characterize the 

potential impacts of pesticide residues in drinking water, the estimated 

residue concentrations need to reflect a sufficient frequency in time to 

capture peak concentrations. Because pesticide loads in surface water 

tend to move in relatively quick pulses in flowing water, frequent 

sampling is necessary to reliably capture peak concentrations for surface 

water sources of drinking water. Pesticide concentrations in ground 

water are generally the result of longer-term processes and less frequent 

sampling can sufficiently characterize peak ground water concentrations. 

The drinking water exposure assessment needs to account for the 

potential for any or all of the NMC residues included in the cumulative 

assessment group (Table I.E-1) to occur together in drinking water 

sources. To realistically estimate exposures, the assessment must take 

into account those factors (crop uses, pest pressures, timing of 

application, etc.) that determine whether more than one NMC pesticide 

can occur together in time and place. Although multiple NMC pesticides 

may be registered for use on the same crop, they may not necessarily be 

used at the same time. Monitoring data could provide real-time 

estimates of co-occurrence but needs to account for all of the potential 

NMCs used in the monitoring area, be of sufficient frequency to capture 

short-term peaks in pesticide exposure, particularly in surface water, and 

span sufficient years to capture the impact of variability in use and 

weather patterns on pesticide transport. 

Section I.E – Page 130 of 277 
Table I.E-1. NMC use patterns and availability of national monitoring data 

Pesticide Use pattern likely to result in 

water exposure? 

Availability of national water 

monitoring data? 

Aldicarb (including 

sulfoxide, sulfone 

degradates) 

Yes (agricultural uses) Yes: NAWQA, Reservoir 

monitoring; state monitoring; 

registrant studies 

Carbaryl Yes (agricultural and residential 

uses) 

Yes: NAWQA, Reservoir 

monitoring; registrant studies 

Carbofuran (including 

3-hydroxycarbofuran) 

Yes1 (agricultural uses) Yes: NAWQA, Reservoir 

monitoring; state monitoring 

Formetanate HCl Yes (agricultural uses) No 

Methiocarb Insignificant impact from limited use Some limited NAWQA monitoring 

Methomyl Yes (agricultural uses) Yes: NAWQA, Reservoir 

monitoring 

Oxamyl Yes (agricultural uses) Yes: NAWQA, Reservoir 

monitoring 

Pirimicarb Insignificant impact from limited use No 

Propoxur No (indoor uses; voluntarily 

cancelled) 

Some limited NAWQA monitoring 

Thiodicarb (including 

methomyl degradate) 

Yes (agricultural uses) No 

1

 EPA proposed to cancel all domestic uses in 2006 IRED, in which case exposure would not be 

likely 

b. Nature of NMC Exposure in Drinking Water Sources 

This section briefly summarizes the nature of expected NMC 

exposure in drinking water sources based on individual chemical 

assessments, available water monitoring data, and published literature 

on the potential impact of conventional drinking water treatment 

processes on NMCs in water. 

Re-registration eligibility documents (REDs), interim REDs (IREDs), 

drinking water assessments, or ecological risk assessments are 

available for all of the NMC pesticides in Table I.E.1 except for pirimicarb 

(USEPA, 1997c. 1997d, 1999f, 2003a, 2005c, 2005d, 2005e, 2006c, 

2006d, 2007b, 2007d, 2007e). 

Seven NMC pesticides – aldicarb (including its sulfoxide and 

sulfone degradates), carbaryl, carbofuran, formetanate HCl, methomyl, 

oxamyl, and thiodicarb – have the potential to reach surface and/or 

ground water sources of drinking water based on use and chemical fate 

and transport properties. Propoxur has been detected in a few, 

predominantly non-agricultural monitoring sites in the US Geological 

Survey (USGS) National Water Quality Assessment (NAWQA) 

monitoring program (Appendix II.E.1). However, the current indoor uses 

are not expected to contribute to the NMC cumulative load in drinking 

water sources. When the Agency gathered usage information on the 

NMC pesticides for the regional cumulative drinking water exposures, 

Section I.E – Page 131 of 277 
usage of methiocarb and pirimicarb were of such a limited extent that 

they did not factor into the NMC cumulative exposure for drinking water 

(see Appendix II.E.4). These pesticides were not used in areas of high 

combined NMC use identified in the regional assessments described 

below. 

The individual chemical assessments indicate that the NMC 

pesticides are likely to reach surface water sources of drinking water via 

runoff or sediment transport, and have been detected in monitoring 

studies. Two carbamates – aldicarb and carbofuran – are likely to reach 

and persist in ground water sources of drinking water, especially in 

shallow, acidic aquifers. Three other carbamates – carbaryl, methomyl, 

and oxamyl – may also reach ground water, but are not likely to persist. 

The most extensive source of national water monitoring data for 

pesticides is the USGS NAWQA program, which includes seven of the 

carbamates in its list of pesticides (Table I.E-2). The NAWQA program 

focuses on ambient water rather on than on drinking water sources, is 

not specifically targeted to pesticide use areas, and is sampled at a 

frequency (generally weekly or bi-weekly during the use season) not 

sufficient to provide reliable estimates of peak pesticide concentrations in 

surface water. However, the program provides a good understanding on 

a national level of the expected occurrence of pesticides in flowing water 

bodies that may be representative of drinking water sources. The 

monitoring data are better indicators of the nature of occurrence of 

pesticides with widespread use rather than of pesticides that are limited 

to a few crops or pests. USGS (2004) provides a detailed description of 

the pesticide monitoring component of the NAWQA program. 

A summary of the first cycle of NAWQA monitoring from 1991 to 

2001 indicates that the seven NMC pesticides were not frequently 

detected in the NAWQA study units (Table I.E-2). Carbaryl and 

carbofuran were the most frequently detected NMC pesticides in streams 

and ground water, reflecting the broader use patterns of these particular 

insecticides. In most instances, maximum reported detections of the 

NMC pesticides were in the single parts per billion or sub-parts per billion 

range. 

As expected, co-occurrence of NMC pesticides in monitored water 

samples reflects use patterns and overall intensity of use. Carbaryl and 

carbofuran are the most common NMCs occurring together in the 

NAWQA sampling; up to three different NMCs have been detected in the 

same surface water samples in the NAWQA study units. Although less 

commonly observed, more than one carbamate was also detected in a 

small number of ground water samples. More detailed summaries of the 

Section I.E – Page 132 of 277 
USGS NAWQA monitoring data can be found in Appendices II.E.1 

(surface water monitoring) and II.E.2 (ground water monitoring). 

Table I.E-2. Summary of carbamate detections in the USGS NAWQA study, 1991­

2001 (provisional data published by USGS in 2003) 

Pesticide Agricultural Land Use Mixed Land Use Urban Land Use 

% 

detect 

Max 

ug/L 

95th 

%ile 

% 

detect 

Max 

ug/L 

95th 

%ile 

% 

detect 

Max 

ug/L 

95th 

%ile 

Surface Water Monitoring (Martin et al, 2003) 

Aldicarb 0.2% 0.5 nd 0% Nd nd 0% Nd nd 

Carbaryl 9.2% 5.2 nd 15.4% 0.5 nd 43.8% 5.2 0.3 

Carbofuran 9.6% 7.0 0.04 3.3% 0.7 nd 2.1% 0.1 nd 

Methiocarb 0.1% 0.1 nd 0% Nd nd 0% Nd nd 

Methomyl 1.6% 0.7 nd 0.3% 0.3 nd 0% Nd nd 

Oxamyl 0.8% 0.2 nd 0% Nd nd 0% Nd nd 

Propoxur 0.2% 0.1 nd 0.2% 0.2 nd 0.2% 0.3 nd 

Ground Water Monitoring (Koplin and Martin, 2003) 

Aldicarb 

(incl.degradates) 

0.3% 1.8 nd 0.1% 0.1 nd 0% Nd nd 

Carbaryl 0.4% 0.02 nd 0.8% 0.5 nd 1.6% 0.03 nd 

Carbofuran 1.6% 1.3 nd 0.4% 0.2 nd 0.7% 0.09 nd 

Methiocarb 0% nd nd 0.1% 0.03 nd 0% Nd nd 

Methomyl 0.1% 0.04 nd 0.1% 0.1 nd 0.2% 0.4 nd 

Oxamyl 0.8% 2.1 nd 0.1% 0.03 nd 0.2% 0.3 nd 

Propoxur 0.1% 0.06 nd 0.1% 0.06 nd 0.2% 0.3 nd 

NAWQA and other surface-water monitoring programs show that 

pesticide concentrations in surface water are highly variable in location 

and in time. This is particularly true for insecticides, such as the NMCs, 

where usage is often in response to specific pest pressures which are 

likely to be concentrated in some areas but not in others and in some 

years but not necessarily every year. In addition to variable use 

patterns, NMC concentrations in surface water are influenced by local 

soil, hydrology, and weather patterns and by the timing of rainfall events 

in relation to pesticide use. 

In 2001, The U.S. Department of Agriculture (USDA) expanded its 

Pesticide Data Program (PDP) to include drinking water. Over the 

following three years, between 21 and 36 surface water systems were 

monitored, the majority of which were located in California and New 

York. Sampling frequency varied from site to site, but was no more 

frequent than two times a month. Treated (finished) water samples were 

collected at different locations at different times; several NMC chemicals 

were included in the analyses. Several NMC compounds (carbaryl, 

carbofuran, and oxamyl) were found in finished drinking water at a 

number of sites. Concentrations found were low, none exceeding 80 ppt. 

The magnitude of these detections can be interpreted as a minimum 

exposure level at these sites, but cannot be interpreted to be 

representative of overall exposure. Given the site to site variability in 

Section I.E – Page 133 of 277 
factors associated with pesticide exposure, limited frequency of 

sampling, and limited number of sites, the study cannot be used to 

represent national exposure to pesticides in finished drinking water. 

Monitoring is most representative of sites sampled in California and New 

York. More information on the results can be found in Appendix II.E.1. 

Aldicarb is the NMC that has been the focus of the most extensive 

monitoring in water resources. While aldicarb has not been detected 

frequently or in high concentrations in ground water in the NAWQA 

program, extensive targeted monitoring by others (registrant, state and 

local governments, universities – see Appendix II.E.2) shows that, under 

certain conditions, aldicarb residues (parent and degradates) can occur 

in ground water and private wells at concentrations as high as several 

tens to several hundred parts per billion (μg/l). 

The frequency and magnitude of detection of aldicarb residues in 

ground water is dependent not only on pesticide use but also on the 

leaching potential of the overlying soil and vadose zone and, for the 

sulfoxide and sulfone transformation products, the pH of the soil and 

ground water. For example, while no aldicarb residues were detected in 

ground-water monitoring conducted by the USGS in the Biscayne and 

surficial aquifers of southern Florida (McPherson et al, 2000), roughly 

one-third of the monitoring wells located under citrus groves in the 

central ridge of Florida had detections of aldicarb residues (USGS, 

2006). Monitoring data for private wells collected by the state of Florida 

showed few detections of aldicarb residues (<2% of wells sampled). 

However, the detections, as high as 47μg/l were clustered along the 

central ridge in the vicinity of citrus groves (FLDEP, 2005). 

Label changes for aldicarb now restrict use from certain areas 

(such as the northeastern states and Wisconsin) and add well-setbacks 

in other areas. In addition, total aldicarb residues (primarily the sulfoxide 

and sulfone transformation products) can persist in ground water for 

years or decades after use. Twenty years after aldicarb use on Long 

Island, NY, was halted, aldicarb residues are still the most frequently 

detected pesticide compounds in ground water in Suffolk County (Suffolk 

County Dept. of Health Services, 2000). 

A recent survey of private wells by Bayer CropScience (MRIDs 

46793701, 46793702, 46793703, 46793704, 46793705, 46793706) 

found aldicarb residues – predominantly sulfoxide and sulfone 

metabolites – in 10 percent of the wells sampled, with the greatest 

frequencies of detections in the Southeastern US (16%, with a maximum 

detect of 2.9 ug/L) and the Mississippi Delta (9%, with a maximum detect 

of 2.6 ug/L) regions. Aldicarb detections showed a regional pattern, with 

this highest frequency of detects in Alabama (22%) and South Carolina 

Section I.E – Page 134 of 277 
(21%) in the Southeast region and southeastern Missouri/northeastern 

Arkansas (23%) in the Mississippi Delta region. Because the detections 

come from a single sample, the concentrations should be compared 

against median concentrations from a distribution of ground water 

concentrations over time (USEPA, 2007a). 

Carbofuran was another NMC for which extensive monitoring has 

occurred; however, the extent of ground water monitoring has decreased 

significantly in the last decade, so current impacts are not as well 

documented. Several inferences can be drawn from the body of 

available data on carbofuran. Targeted ground water monitoring studies 

show a clear pattern of carbofuran movement into ground water, with 

maximum detections in the same range as that reported for aldicarb. 

Because transport to ground water typically takes longer than transport 

to surface water, measured concentrations of carbofuran in ground 

water, especially in deep groundwater, may represent usage that 

occurred years before the samples were collected. As with aldicarb, 

carbofuran will also persist in ground water for long periods of time after 

use has been discontinued. This is particularly true for acidic ground 

water because carbofuran is stable to hydrolysis (the major route of 

degradation in ground water) at pH values of 6.0 or less. 

EPA’ s review of available laboratory studies and monitoring data 

indicates that conventional water treatment processes such as 

coagulation, sedimentation, and conventional filtration will not reliably 

remove or transform the NMCs in drinking water sources (Appendix 

II.E.3). This is further substantiated by USDA PDP monitoring that 

shows detections of NMC residues in finished/treated water samples 

(Appendix II.E.1). Lime softening and activated carbon filtration can be 

effective in removing the NMC pesticides. With the exception of parent 

aldicarb, lime softening processes will break down NMC pesticides 

through alkaline-catalyzed hydrolysis. Sorption on activated carbon by 

granular activated carbon (GAC) or powdered activated carbon (PAC) 

appears to be at least partially effective in removing NMCs from drinking 

water (percent removal ranges from 20 to 38% for aldicarb and oxamyl to 

60 to 80% for carbofuran, carbaryl, and methiocarb). Other treatment 

methods, such as chlorination, chloramination, chlorine dioxide, and 

potassium permanganate, are only effective in oxidizing NMC 

compounds containing a methylthio group (CH3-S-), e.g., methiocarb and 

aldicarb. These compounds are expected to oxidize to sulfoxide and 

sulfone carbamates that hydrolyze rapidly at alkaline pH values. The 

Agency estimates that lime softening is used on 7% or less of community 

ground water systems serving populations of 10,000 or less and less 

than a third of systems serving more than 10,000 people (USEPA, 

2001b). Carbon filtration is used on less than half of the large 

Section I.E – Page 135 of 277 
community water systems, with decreasing percentages of smaller 

systems using GAC or PAC (USEPA, 2001b). 

c. Summary 

The goal of the NMC drinking water exposure assessment is to 

provide estimates of distributions of NMC residues (concentrations in 

drinking water) that account for: 

• daily and seasonal variations in residues over time associated with 

time of application(s) and runoff/leaching events (surface water 

concentrations are expected to be more variable in time than ground 

water concentrations) 

• year-to-year variations related to weather patterns, pest pressures, and 

use 

• variability in residues from place to place, resulting from the source 

and nature of drinking water and from the regional / local factors (soil, 

geology, hydrology, climate, crops, pest pressures, usage) that affect 

the vulnerability of those sources 

• the potential for co-occurrence of more than one NMC in location and 

time only when this is likely to happen 

3. Conceptual Model 

Risk is a function of both hazard and exposure, and estimation of 

the exposure portion for drinking water requires data on concentrations 

of the pesticides in the drinking water and consumption of drinking water 

for different demographic populations. Drinking water is locally derived 

and concentrations of pesticides in source water fluctuate over time and 

location for a variety of reasons. Pesticide residues in water fluctuate 

daily, seasonally, and yearly as a result of the timing of the pesticide 

application, the vulnerability of the water supply to pesticide loading 

through runoff, spray drift and/or leaching, and changes in the weather. 

Concentrations are also affected by the method of application, the 

location and characteristics of the sites where a pesticide is used, the 

climate, and the type and degree of pest pressure. 

While monitoring data provide a picture of the occurrence of NMC 

pesticides in drinking water resulting from variable use in selected 

locations, monitoring data alone are not sufficient for the NMC 

cumulative drinking water exposure assessment, due to the spatial and 

temporal scale of monitoring networks. This section describes the 

approach used to estimate cumulative NMC residues in drinking water 

using models, to ensure that peak concentrations from registered uses 

are addressed and can be incorporated into the aggregate dietary risk 

Section I.E – Page 136 of 277 
Section I.E – Page 137 of 277 

O

P

P

s

e

l

e

c

t

e

d

assessment. The model estimates are evaluated against available 

monitoring data. 

Based on the needs of the probabilistic cumulative exposure 

assessment and the information from monitoring data, OPP designed a 

drinking water assessment that provides multiple years of daily residue 

concentrations from drinking water sources in regions where high NMC 

use coincides with vulnerable drinking water sources. While the 

available monitoring studies were not designed to provide data for a 

multi-chemical drinking water exposure assessment and were not of 

sufficient frequency to provide a time series for use in a probabilistic 

exposure assessment, the data were used to make sure that estimated 

exposures from modeling were within the same range or that any 

discrepancies could be explained. 

a. Regional Screening Approach for Vulnerable Sources of 

Drinking Water 

Drinking water exposure will vary locally as a result of pesticide 

use, agricultural practices, the nature and vulnerability of drinking water 

sources, and weather patterns. Thus, the water exposure assessment 

focused on specific geographic areas of relatively high NMC use in a 

manner that would be realistically protective of all NMC use areas. To 

facilitate the regional screening approach, the Agency adapted a 

modification of the USDA Farm Resource Region map (Heimlich, 2000) 

as a framework for identifying one or more locations which represent an 

area of the greatest concern for drinking water exposure in each region 

(Figure I.E-1). In this way, the Agency chose a set of locations to 

represent vulnerable drinking water sources throughout the U.S. 

Figure I.E-1. NMC CRA regions for drinking water exposure assessment 

showing high NMC use areas and regional drinking water exposure sites 
 Locations where NMC residues in drinking water sources are likely to be 

of greatest concern based on: 

•Relatively high NMC use: both total NMC use by county and 

relative potency-adjusted NMC use were considered; for ground 

water sources, EPA also looked at the areas with the highest 

aldicarb and carbofuran uses; 

•Nature and source of drinking water: EPA used the USGS 

report on water use in the U.S. (USGS, 1998, 1999) to identify the 

drinking water sources (public surface water, public ground water, 

domestic private) by county and information on surface water 

intake locations to identify the dominant drinking water sources in 

high NMC use counties; 

•Vulnerability of the drinking water sources: vulnerability of 

surface water sources was based on the relative runoff potential of 

the watershed area around surface water intakes; vulnerability of 

ground water sources was based on the leaching potential of the 

overlying soils and vadose zone. 

For each region, the Agency used the estimated NMC cumulative 

distribution from the vulnerable water source to represent the drinking 

water portion of the dietary exposure estimate for the entire region. If 

NMC levels in water from these vulnerable sites are not major 

contributors to the total regional cumulative exposure, then the Agency 

can reasonably conclude that drinking water exposures will not be a 

concern in other less vulnerable areas in that region. If drinking water 

exposure from one or more of these vulnerable sites is a significant 

contributor to the total cumulative exposure, then additional evaluations 

may be necessary to characterize the extent of the potential exposure. 

For the cumulative assessment, the Agency considered exposure 

from both surface- and ground-water sources of drinking water. In both 

cases, the Agency simulated potential exposure to sensitive populations 

in a geographic sense. Surface-water sources of water consisted of 

source water from small reservoirs in predominantly agricultural 

watersheds with high NMC use. Ground-water sources of water were 

shallow private wells located in highly permeable soils in high NMC use 

areas. 

b. Conceptual Model for Surface Water Sources of Drinking 

Water 

EPA identified regional surface water exposure scenarios where 

high NMC use areas coincided with potentially vulnerable surface water 

sources. The Agency bases its drinking water exposure assessment for 

Section I.E – Page 138 of 277 
surface-water sources on a small reservoir in an agricultural watershed. 

An analysis of available monitoring data indicates that such reservoirs 

are likely to be among the most vulnerable surface drinking water 

sources (FIFRA SAP, 1998; USEPA, 1999c, 2000b). The NMC CRA 

focused on watershed-scale impacts from multiple NMC uses occurring 

in multiple fields in a watershed (Figure I.E-2). 

Co-occurrence of NMC pesticides in surface water sources of 

drinking water is based on the amount and timing of pesticide use in the 

watershed. EPA used county- or multi-county level pesticide use 

information, based on agricultural chemical use surveys (Appendix 

II.E.4), to identify the potential for co-occurring NMC uses in the same 

location. The potential for co-occurrence of NMC residues in water at 

the same time depends upon application timing, pesticide persistence 

and transport characteristics. The relative proportions of each NMC 

used in the watershed are based on the amount applied in a given year 

(a function of the rate and frequency of application, combined with the 

crop area treated); pesticide fate and transport properties that affect the 

amount of pesticide available at the surface for runoff; the runoff 

susceptibility of the soil; and the timing, amount, and frequency of 

rainfall. 

Figure I.E-2. Conceptual model for surface water sources of drinking water 

illustrating how multiple NMC uses are proportioned in the watershed 

Non-Carbamate 

treated Ag 72.4% 

Land use in

watershed

Modeled

Watershed

Carbamate use 

In watershed 

Section I.E – Page 139 of 277 
For the watershed approach, OPP estimated pesticide 

concentrations over time (30-year simulation) for each crop-NMC 

combination. The temporal distributions allowed the Agency to 

determine the likelihood of co-occurrence of the NMCs in water over 

time. The Agency used regional crop areas based on USDA Ag Census 

data (USDA, 2002, as described in USEPA, 2000b) and acre treatments 

to adjust the estimated daily concentrations for each of the NMCs for the 

portion of the watershed that is treated by that particular NMC. These 

crop-adjusted concentrations are converted to a concentration equivalent 

for the index chemical (in this case, oxamyl) and combined into a single 

set of daily NMC cumulative concentrations (spanning multiple years) for 

each region. 

For exposure from surface water sources of drinking water, the 

Agency used estimated concentrations derived for the source water from 

a reservoir, assuming no treatment effects. As noted, available studies 

indicate that conventional drinking water treatment processes will not 

fully remove NMC residues from water. At the same time, the Agency 

has no reason to expect that the standard drinking water treatment 

process will result in more toxic transformation products (see Appendix 

II.E.3). 

c. Conceptual Model for Vulnerable Ground Water Sources of 

Drinking Water 

The potential for pesticide movement to ground water sources of 

drinking water depends on such factors as hydrologic properties of the 

overlying soil and vadose zone that affect downward movement of water 

and chemicals, travel time through the unsaturated zone to ground 

water, aquifer properties (conductivity, porosity, depth, type, location of 

recharge area), the leaching potential of the pesticide (persistence and 

mobility), and the type of well drawing water for drinking purposes 

(Focazzio et al, 2002). These factors vary geographically and cause 

certain wells in one region to be more vulnerable than those in another 

region. EPA based its ground water exposure assessment on private 

rural wells which draw water from a shallow, unconfined aquifer (also 

known as a water table aquifer). In general, such drinking water sources 

tend to be more vulnerable than public water supply wells and provide 

estimates of drinking water exposure representative of people living in 

agricultural areas and relying on shallow wells for drinking water. 

Figure I.E-3 illustrates the conceptual model used to estimate 

pesticide transport to private wells. The pesticide is applied to the soil 

surface or plant canopy and precipitation or irrigation moves the 

pesticide through the vadose zone into a saturated zone. 

Simultaneously, physical and chemical properties of the individual NMCs 

determine the degree to which they are degraded or sorbed to soils. 

Section I.E – Page 140 of 277 
Water Table

Lateral Groundwater

Movement

Depth to

Water

Table

EPA assumed a depth to the top of a shallow, surficial aquifer of 9.1 m 

(30 ft) in this revised assessment. While such information is not readily 

available, sources ranging from USGS NAWQA (Berndt et al, 1998; 

McPherson et al, 2000) and ground water atlases (USGS, 1990) to FL 

water management districts, suggest that 30- to 50-feet is representative 

of the depth to shallow ground water supplying private wells. The 

concentration in the well is the average saturated pore water 

concentration across a one-meter length of the screen, extending down 

from the top of the water table. 

Degradation occurs at different rates through the soil profile. 

Generally, faster degradation from microbial processes occurs in the top 

of the profile and decreases with depth. The model assumes that NMC 

degradation resulting from aerobic metabolism occurs in the top 25 cm, 

with rates declining linearly to 1 meter. Below a meter, only abiotic 

processes (in this case, hydrolysis) are simulated. 

For some pesticides, well setbacks (Figure I.E-3) are specified by 

state or federal labels. For such cases, the additional travel time for a 

pesticide to reach a drinking water well and the degradation that occurs 

during that time is taken into consideration by modeling lateral plug flow 

movement toward the well (see Appendix II.E.7 for details). 

Figure I.E-3. Depiction of general ground water scenario concept used for 

estimating pesticide concentrations in drinking water 

100 cm 

Set back distance 

100 cm 

Pesticide Application Area 

Potable Well 

Water Table 

Lateral Groundwater 

Movement 

100 cm

Set back distance

100 cm

Pesticide Application Area

Potable Well

Depth to 

Water 

Table 

Biodegradation

Zone

Abiotic

Degradation

Section I.E – Page 141 of 277 
Pesticide fate properties (persistence under acid hydrolysis) and 

available monitoring data (Suffolk Co. Dept. of Health, 2000; USGS, 

2006) indicate that several NMC residues are likely to persist in acidic 

ground waters. In addition, cumulative exposure in ground water is likely 

to reflect past as well as current uses, particularly for deep wells. 

Available monitoring data, primarily from the USGS NAWQA 

program, confirm that more than one NMC residue may occur together in 

ground water (Appendix II.E.2). Co-occurrence in ground water can 

result when more than one NMC pesticide is used at different times on 

the same crop, on different crops in rotation on the same fields, or on 

different crops grown on adjacent fields 

4. Analysis Plan 

This section provides a brief description of the methods of analysis 

EPA used in generating the cumulative NMC concentrations in drinking 

water sources for use in the cumulative dietary exposure assessment. 

The dietary baseline analysis assumes that all carbofuran uses other 

than import tolerances are removed. The impacts of currently registered 

domestic uses of carbofuran on drinking water sources were modeled in 

this assessment, but results are summarized separately in a sensitivity 

analysis. 

a. NMC Properties 

The predicted persistence and movement of each NMC pesticide in 

the environment are based on environmental fate and transport studies 

submitted by the registrants as a requirement of registration and/or reregistration. Inputs for the water models are based on environmental fate 

data reviewed by EPA and described in the individual chemical 

assessments. Table I.E-3 summarizes the dominant persistence and 

mobility characteristics of the NMCs included in the drinking water 

exposure assessment. Appendix II.E.5 provides detailed chemical inputs 

used in the water exposure models. For aldicarb and its sulfoxide and 

sulfone degradates included in the common assessment group, the 

Agency used half-life values for the combined aldicarb residues (parent 

plus degradates) and the sorption value for the most mobile of the 

degradates. 

Table I.E-3. Summary of N-methyl carbamate fate and transport properties 

Pesticide Persistence / Degradation Pathway Mobility / Sorption 

Aldicarb, including 

sulfoxide and sulfone 

degradates (USEPA, 

2006c, 2006d) 

Field: Aerobic soil metabolism (55 d half-life); 

pH-dependent hydrolysis for degradates (2-3 d @ 

pH9 for sulfoxide; 60-63 d @ pH7, 6 d @pH8, 1 

da @ pH9 for sulfone) 

Water: Aerobic aquatic metabolism (12 d halflife); pH-dependent hydrolysis for degradates 

Kd = 0.12 mL/g 

(Koc = 10 mL/g) 

Section I.E – Page 142 of 277 
Pesticide Persistence / Degradation Pathway Mobility / Sorption 

Carbaryl (USEPA, 

2003a, 2007b) 

Field: Aerobic soil metabolism (12 d half-life); 

hydrolysis (12 d @ pH7, 0.1 d @ pH9) 

Water: Aerobic aquatic metabolism (30 d halflife); pH-dependent hydrolysis 

Koc = 196 mL/g 

Carbofuran (USEPA, 

2005c, 2005d) 

Field: Hydrolysis (28 d @ pH7, 9 d @ pH7.5, 3 d 

@ pH8, <1 d @ pH9); aerobic soil metabolism 

(321 d half-life) 

Water: pH-dependent hydrolysis 

Koc = 36 mL/g 

Formetanate HCl 

(USEPA, 2005e) 

Field: Aerobic soil metabolism (6 d half-life); 

hydrolysis (24 d @ pH7,9) 

Water: Aerobic aquatic metabolism (13 d halflife); hydrolysis 

Koc = 340 mL/g 

Methomyl (USEPA, 

1997c, 2007d) 

Field: Aerobic soil metabolism (79 d half-life); 

alkaline hydrolysis (30 d @ pH9) 

Water: Aerobic aquatic metabolism (7 d half-life); 

hydrolysis 

Koc = 24 mL/g 

Oxamyl (USEPA, 

1999f, 2007e) 

Field: Hydrolysis (7 d @ pH7, 0.1 d @ pH9); 

aerobic soil metabolism (20 d half-life) 

Water: Hydrolysis; aerobic aquatic metabolism 

(40 d); anaerobic aquatic metabolism (7 d) 

Koc = 6 mL/g 

Thiodicarb, degrades 

to methomyl (USEPA, 

1997d) 

Field: Aerobic soil metabolism (2 d half-life); 

hydrolysis (32 d @ pH7, 0.5 d @ pH9) 

Water: Aerobic aquatic metabolism (3 d half-life); 

anaerobic aquatic metabolism (<1 d); pHdependent hydrolysis 

Koc = 485 mL/g 

Most of the NMC pesticides exhibit pH-dependent hydrolysis (Table 

I.E.3). They tend to be stable or degrade slowly under acidic conditions. 

As the pH increases to neutral and alkaline conditions, they hydrolyze 

more rapidly. Unless otherwise indicated, EPA used the hydrolysis rates 

for acidic conditions in modeling. These rates are generally slower and 

would result in likely overestimates of actual exposures in neutral to 

alkaline conditions. Where the Agency had information that showed that 

the dominant pH of the soil/vadose zone/groundwater system was 

neutral to alkaline, hydrolysis rates (appropriate to the pH) were used. 

b. Identifying Regional Exposure Scenarios 

The selection of specific locations for regional drinking water 

assessments involves several steps. First, the Agency identified the high 

NMC usage areas within each region. The Agency used data collected 

by Thelin and Gianessi (2000) for county-level estimates of NMC usage. 

EPA evaluated the relative high NMC use areas several different ways: 

• Summing total pounds of each NMC by county to calculate both 

total pounds of NMC pesticide per county and total pounds per 

acre; 

Section I.E – Page 143 of 277 
• Adjusting the county-level estimates of pounds of each NMC by 

their respective relative potency factors to identify areas of 

greatest use of the most potent of the NMCs; 

• In addition, for ground water exposure, identifying the aldicarb 

and carbofuran use areas, which were driving NMC exposure, to 

determine if additional scenarios were needed and for sensitivity 

analysis. 

Next, EPA identified the types of drinking water sources in each 

high usage area. The Agency used a spatial dataset that describes 

water use for all the counties in the continental US (USGS, 1999) to 

determine the dominant source of drinking water – (1) public supply 

served by surface water, (2) public supply served by ground water, or (3) 

domestic self-supplied drinking water (primarily private wells). For 

surface water exposures, the Agency overlaid the public surface water 

supply data, along with locations of drinking water intakes (based on 

SDWIS data), with the NMC use maps to identify counties in which high 

NMC use coincided with surface water sources of drinking water. For 

ground water exposures, the Agency focused on private wells, which are 

generally shallower than public supply wells and typically have no water 

treatment applied. The Agency overlaid the domestic drinking water 

supply data with NMC use to identify those counties where high NMC 

use coincided with populations drinking from private wells. 

The final step in choosing regional locations for modeling was to 

assess the vulnerability of drinking water sources within the high NMC 

usage areas. For surface water sources of drinking water, OPP 

compared relative vulnerabilities of the areas based on average annual 

runoff, average 2-month runoff (beginning of the growing season), and 

average soil loss, as developed by the USDA Natural Resources 

Conservation Service (Kellogg et al, 1997). The regional drinking water 

scenario sites are shown in Figure I.E-1 and summarized in Table I.E-4. 

Table I.E-4. Regional drinking water exposure sites and dominant NMC 

pesticide uses 

Region Exposure scenario 

sites (1) Dominant use crops NMC pesticides used (2) 

Southeast 

NC coastal plain (SW, 

GW), eastern GA (SW), 

southern GA (GW) 

Cotton, peanuts, 

tobacco, pecans 

Aldicarb, carbaryl, 

carbofuran, methomyl, 

oxamyl 

Florida 

South FL (SW), Central 

FL (GW, SW), 

Northeastern FL (GW) 

Citrus, sweet corn, 

sugarcane, cucumber, 

pepper, potato 

Aldicarb, carbaryl, 

carbofuran, methomyl, 

oxamyl, thiodicarb 

Mid-south Northeast LA (SW) Cotton, corn, sorghum 

Aldicarb, carbofuran, 

oxamyl, thiodicarb 

North / north South central PA (SW), Apples, corn, Carbaryl, carbofuran, 

Section I.E – Page 144 of 277 
Region Exposure scenario 

sites (1) Dominant use crops NMC pesticides used (2) 

central Central IL (SW), 

Delmarva (GW) (3) 

peaches, sweet corn, 

alfalfa, pumpkin, 

potato, beans, 

cucurbits 

formetanate HCl, 

methomyl, oxamyl, 

thiodicarb 

Lower Midwest Southern tip of TX (SW) Grapefruit, cotton, 

vegetables 

Aldicarb, carbofuran, 

formetanate HCl, 

methomyl, oxamyl 

Northern Great 

Plains Red River Valley (SW) Potatoes, sugar beets, wheat 

Aldicarb, carbaryl, 

carbofuran, oxamyl 

Northwest Central WA (SW, GW) 

Potatoes, apples, 

cherries, beans, 

carrots, onions 

Aldicarb, carbaryl, 

carbofuran, 

formetanate HCL, 

methomyl, oxamyl 

Southwest CA Central Valley (SW) 

Citrus, stone fruit 

trees, cotton, melons, 

grapes, tomatoes, 

various cole, root, 

tuber vegetables 

Aldicarb, carbaryl, 

carbofuran, 

formetanate HCl, 

methomyl, oxamyl 

(1) SW = surface water scenario site; GW = ground water scenario site 

(2) EPA proposed canceling all domestic uses of carbofuran; carbofuran model results are presented 

as separate sensitivity analysis. 

(3) The Delmarva scenario was used for the carbofuran sensitivity analysis only. 

For potentially vulnerable ground water sources of drinking water, 

EPA relied on a variety of sources, including Nolan et al (2002), USGS 

NAWQA reports and Ground Water Atlases, USDA/NRCS county soil 

datasets (SSURGO), and other state/local information. EPA also used 

monitoring data from Florida (FL DEP, 2005; USGS, 2006) to identify 

specific site, soil, and hydrologic properties that might serve as indicators 

of potential high NMC exposure conditions. Regional ground water 

exposure scenario sites are listed in. 

c. Regional Usage 

The regional exposure areas of interest consist of multi-county 

areas that encompass the vulnerable drinking water source in high NMC 

use areas. EPA collected information on the target crops, estimated 

NMC usage, and timing of application for these multi-county areas. 

The drinking water exposure assessments require information on 

crop use, pounds applied, application rate, number of applications, 

percent of crop treated, and application timing. Much of this information 

is not easily available or does not exist at the geographic scale needed 

for the exposure assessment. As a result, EPA used the best available 

information to provide the regional estimates for the NMC pesticide-crop 

combinations that actually occur in scenario areas. Because countylevel pesticide usage data is based on surveys and is uneven in quality, 

EPA created county clusters that surrounded the initial scenario areas 

Section I.E – Page 145 of 277 
shown in Figure I.E-1. EPA also used multiple data sources and multiple 

years of data to improve the robustness of the use data. 

For each regional scenario site, EPA used USDA National 

Agricultural Statistics Service (USDA NASS) and Doane’s databases to 

estimate usage (acres planted, total pounds used, percent of crop 

treated, application rate, and number of applications) for each NMC and 

crop reported in the use cluster. Usage was averaged for the years 1998 

through 2002. The Agency identified those NMC-crop uses that 

accounted for at least 95% of the total NMC usage in the scenario area. 

For the crop/chemical combinations identified in a given area, 

USDA crop profiles, typical planting/harvesting dates and various other 

sources were used to identify most likely windows of application for each 

use. Typically, all the NMC pesticides discussed here target multiple 

pests or pests that can occur multiple times during a given crop’s 

growing season, so applications often occur over a broad time period. 

EPA systematically selected the beginning of the most active window for 

the initial application date of each NMC. Where multiple applications 

were identified, the Agency spread those evenly over the most active 

window. Details of the methods and resulting regional usage information 

can be found in Appendix II.E.4. 

d. Surface Water Exposure Assessment 

The Agency estimated the daily drinking water exposure from 

surface water sources using the simulation models PRZM (Pesticide 

Root Zone Model) and EXAMS (EXposure Analysis Modeling System). 

With PRZM/EXAMS modeling for a drinking water reservoir, the Agency 

can: 

• Account for potential co-occurrence of NMC residues by modeling 

all uses in a region/area, as described in the conceptual model 

• Combine daily time series over multiple years (using 30 years of 

recorded weather data) to account for year-to-year variations in 

weather and to separate peak concentrations that are not likely to 

occur together in time 

• Estimate peak concentrations (on a daily time step); adjustments 

to pesticide use inputs (“typical” rates, frequencies) reflect 

estimated concentrations in a “typical” year 

• Model vulnerable surface water sources in regions to reflect 

spatial variations in crops, use, weather, soils, and hydrology 

Section I.E – Page 146 of 277 
• Adjust for crop area, acres treated in order to prevent doublecounting overlapping uses 

A detailed description of the models is available from the EPA OPP 

Water Models web site (USEPA, 2007f). 

The model estimates daily pesticide concentrations in surface water 

sources of drinking water (a reservoir) using local soil, site, hydrology, 

and weather characteristics along with pesticide application and 

agricultural management practices, and pesticide environmental fate and 

transport properties. The input parameters are specific for each NMCcrop scenario in each region. For example, in the eastern North Carolina 

exposure site representing the Southeast region of the US, the cotton, 

peanut, and tobacco scenarios consist of properties for soils on which 

the crops are grown in the coastal plain of North Carolina. The weather 

data used in the simulations come from 30 years of weather collected at 

a NOAA weather station in Raleigh/ Durham, just west of the scenario 

area. Appendix II.E.6 provides details on the site-specific inputs for the 

surface water exposure. 

The cumulative assessment focuses on the likelihood of concurrent 

exposure to multiple pesticides from food, water, and residential use. 

This involves using average application rates, average numbers of 

applications, and estimates of acres treated to adjust concentrations, and 

specific application windows so that only those NMC pesticides that have 

overlapping use periods may potentially occur together in water. The 

implications of these assumptions are discussed in the risk 

characterization chapter. 

PRZM is a field-scale model, while the cumulative water 

assessment focuses on watershed-scale impacts (i.e., the contributions 

of multiple NMC uses on multiple crops occurring in multiple fields in a 

watershed). The Agency used PRZM to model multiple fields in a 

watershed. While this approach provides a more realistic depiction of 

multiple chemical usage in a watershed, it provides no spatial context for 

those fields. It also assumes that the runoff from each of those fields 

goes into the reservoir. 

To adapt PRZM for this watershed approach, EPA adjusted the 

estimated pesticide concentrations generated for each crop-NMC 

combination to account for the portion of the watershed treated by a 

particular NMC pesticide: 

• The NMC-crop combination was modeled with PRZM/EXAMS, 

using the region-specific usage, application timing, soil, site, 

Section I.E – Page 147 of 277 
and weather data. The result is a time-series of daily pesticide 

concentrations in a reservoir spanning a 30-year period. 

• Each daily concentration is adjusted by the fraction of the 

watershed occupied by the crop being modeled. The fraction is 

calculated by dividing the acres of crop grown in the multicounty region by the total acres in that region (percent crop 

area). 

• The daily concentrations are then adjusted by the fraction of 

acres of the crop treated by the particular pesticide. The 

fraction is calculated by dividing the acres of crop treated by 

the total crop acres in the multi-county region (percent crop 

treated). 

The resulting concentrations for each crop-NMC combination must 

be converted to a concentration equivalent for an index chemical. The 

concentrations were normalized to an index equivalent by multiplying 

each of the daily concentrations by the relative potency and FQPA safety 

and inter-species factors for the respective NMC pesticide. The 

normalized outputs for each crop-NMC combination were summed dayby-day to give a daily time series of total NMC residues in water over 30 

years. 

e. Ground Water Exposure Assessment 

EPA used the Pesticide Root Zone Model (PRZM) to estimate NMC 

concentrations in ground water sources of drinking water. Specifically, 

the ground water exposure assessment must account for: 

• Variations in Residues Over Time: Pesticide residues in ground 

water are likely to fluctuate less drastically than residues in surface 

water; however, the dietary exposure estimates require a concentration 

time series for co-occurrence in time. 

• Variations in Residues Over Location: As with the surface water 

assessment, EPA focused on regional ground water sources of 

drinking water that are expected to be among the most vulnerable to 

NMC contamination based on soil, geology, hydrology, climate, crops, 

and usage. 

• Co-occurrence: USGS NAWQA monitoring shows that co-occurrence 

of NMC residues, though infrequent, does occur in ground water. 

Therefore, EPA estimated ground water concentrations for multiple 

NMC pesticides in ground water, based on regional usage data. 

Section I.E – Page 148 of 277 
The model simulates pesticide movement through the soil and 

underlying vadose zone to a saturated zone, representing the surficial 

aquifer, at a depth of 30 feet (see Figure I.E-3). The saturated zone can 

be created in PRZM by setting the field capacity input parameter equal to 

the porosity. Output concentrations are the average from the top of the 

saturated zone to a depth 1 meter below the water table. 

Because co-occurrence of NMC residues in ground water is likely 

to be more localized than for surface water, EPA considered cooccurrence based on the potential for more than one NMC to be used at 

different times on the same crop or on different crops in rotation on the 

same fields. This resulted in less crop-chemical combinations than for 

the surface water scenarios, which encompassed a larger area of 

contribution (watershed rather than fields). The Agency modeled 

multiple NMC uses on a crop at the same ratio of pounds used as that 

reported in the usage summary for the region. 

As with surface water, the concentrations for each crop-NMC 

combination was converted to a concentration equivalent for an index 

chemical based on the relative potency and FQPA safety and interspecies factors. The adjusted concentrations were summed day-by-day 

for a cumulative time series of NMC residues in ground water 

distribution.

 Appendix II.E.7 provides details on groundwater scenario 

development, model inputs, and comparisons with monitoring. It also 

provides site-specific inputs for the ground water model scenarios. 

5. NMC Concentrations in Surface Water Sources of Drinking 

Water 

The Agency estimated drinking water concentrations for individual 

and cumulative NMC load for each of the regional surface water scenario 

sites listed inTable I.E-4. Details and results of these exposure 

estimates can be found in Appendix II.E.6. 

a. Individual NMC Levels in Surface Water 

Estimated peak concentrations of the individual NMC pesticides in 

each of the regional surface water scenario sites were in the sub-parts 

per billion range (Table I.E-5), except for aldicarb, which had estimated 

peaks as high as a single part per billion in the NC coastal plain 

scenario. Aldicarb had the highest estimated peak concentrations in 4 

scenarios (NC coastal plain, GA coastal plain, central FL, northeast LA), 

methomyl in 5 scenarios (south FL, south-central PA, central WA, CA 

Central Valley, south TX tip), and carbaryl in 2 scenarios (central IL, Red 

River Valley, MN/ND). 

Section I.E – Page 149 of 277 
Table I.E-5. Estimated peak concentrations for NMC residues for the regional 

surface water drinking water scenarios (30-year period) 

Valley) 

Region / 

Scenario Pesticide Crops Concentration, ug/l (ppb) 

Max. 99th %ile 95th %ile 

SE: NC Aldicarb cotton, peanut, tobacco 1.26 0.28 0.06 

coastal plain Carbaryl cotton, peanut, cucumber, 

tobacco 

0.04 0.02 0.007 

Methomyl peanut, tobacco 0.03 0.004 0.001 

Oxamyl peanut 0.23 0.008 0.002 

SE: GA Aldicarb cotton, peanut, pecan 0.37 0.09 0.02 

coastal plain Carbaryl pecan 0.05 0.01 0.004 

Florida Aldicarb oranges, grapefruit 0.02 0.004 0.001 

(South) Carbaryl oranges, grapefruit 0.01 0.002 0.001 

Methomyl sweet corn, pepper, cucumber 0.63 0.18 0.08 

Oxamyl pepper, oranges, cucumber 0.14 0.02 0.006 

Thiodicarb sweet corn 0.06 0.007 0.003 

Florida 

(Central) 

Aldicarb oranges, grapefruit 0.46 0.07 0.01 

Carbaryl oranges, grapefruit 0.11 0.03 0.009 

Oxamyl oranges 0.05 0.008 0.002 

Midsouth 

(northeast 

LA) 

Aldicarb Cotton 0.70 0.14 0.02 

Methomyl thiodicarb degradate (cotton) 0.34 0.05 0.009 

Oxamyl cotton 0.19 0.01 0.001 

Thiodicarb cotton 0.08 0.003 0.001 

Northeast/ 

Central 

(south central 

PA) 

Carbaryl apple, peach, sweet corn 0.02 0.003 0.001 

Formetanate apple 0.001 <0.001 <0.001 

Methomyl apple, peach, potato, sweet corn 0.07 0.02 0.006 

Oxamyl apple 0.003 <0.001 <0.001 

Thiodicarb sweet corn <0.001 <0.001 <0.001 

Northeast/ 

Central 

(IL) 

Carbaryl corn, sweet corn 0.04 0.01 0.003 

Methomyl lima beans 0.02 0.002 0.001 

Lower 

Midwest 

(South TX tip) 

Aldicarb Grapefruit, cotton 0.07 0.02 0.005 

Formetanate Grapefruit 0.04 0.008 0.001 

Methomyl Onions, cucumber, spinach 0.21 0.03 0.01 

Oxamyl Cotton, carrots, onions, 

cucumber, cantaloupe, 

watermelon, peppers 

0.19 0.07 0.02 

Northern 

Great Plains 

(Red River 

Valley) 

Aldicarb Potatoes, sugar beets 0.004 0.001 <0.001 

Carbaryl Spring wheat 0.10 0.02 0.007 

Oxamyl Potatoes 0.003 0.001 <0.001 

Northwest Aldicarb Beans, potatoes 0.03 0.01 0.002 

(Central WA) Carbaryl Apples, Cherries 0.04 0.004 0.003 

Formetanate Apples <0.001 <0.001 <0.001 

Methomyl Beans, sweet corn 0.09 0.01 0.006 

Oxamyl Carrots, onions, potatoes 0.02 0.005 0.003 

Southwest 

(CA Central 

Aldicarb Cotton, beans/peas, potatoes 0.08 0.02 0.001 

Carbaryl Apples, cantaloupe, cotton, 0.02 0.005 0.002 

Section I.E – Page 150 of 277 
Region / Concentration, ug/l (ppb) 

Scenario Pesticide Crops Max. 99th %ile 95th %ile 

nectarine, oranges, peaches, 

pistachios, plums 

Formetanate Grapefruit, lemons, nectarine, 

oranges, plums, tangerines 

0.03 0.004 0.001 

Methomyl Alfalfa, asparagus, broccoli, 

cantaloupe, carrots, garlic, 

lettuce, nectarine, onions, 

oranges, peaches, potatoes, 

sugar beets, tomatoes, 

watermelon 

0.40 0.08 0.03 

Oxamyl Cantaloupe, cotton, garlic, 

oranges, peaches, tomatoes 

0.02 0.01 0.005 

A comparison with available surface water monitoring data 

(Appendix II.E.I) indicates that the estimated peak NMC residues are 

similar to or less than the maximum reported detections from NAWQA, 

with a couple of exceptions where reported NAWQA detections were 

greater. 

• Estimated maximum aldicarb residues (parent, sulfone, sulfoxide) are 

similar to maximum reported detections in the southeast (NC, GA, FL). 

Maximum and upper percentile estimates for total aldicarb residues for 

the Mid-South were less than the maximum detection reported in the 

region (Mississippi Embayment study unit) for aldicarb sulfoxide, but 

greater than the 99th percentile of detections. However, even if if the 

modeled peak was adjusted by the difference (2.5X), the resulting 

cumulative NMC exposures would still be below drinking water levels 

of concern. 

• Estimated carbaryl concentrations were less than reported detections 

in NAWQA, primarily because the NMC cumulative scenarios were not 

focused on the highest carbaryl use areas. However, the impact of this 

on overall NMC cumulative exposures is not expected to be significant 

because carbaryl has a lower adjusted RPF than do the other NMC 

pesticides estimated to dominate exposure in source drinking water. 

• Estimated methomyl and oxamyl concentrations were similar to 

maximum reported detections in NAWQA. 

Overall, the estimated NMC concentrations in surface water are 

similar to or less than reported peak concentrations from monitoring data 

in the same or similar regions. 

b. Cumulative NMC Levels in Surface Water 

The highest estimated cumulative NMC concentrations in surface 

water sources of drinking water occurred in the southern United States 

Section I.E – Page 151 of 277 
(Table I.E-6), with the highest estimated peak following the trend: 

Eastern NC > northeastern LA > south FL > central FL = central IL > 

southeast GA. The concentrations in Table I.E-6 reflect adjustments for 

individual chemical FQPA safety and inter-species factors in addition to 

relative potencies. Thus, the concentrations cannot be directly 

compared to measured values in the environment. 

Table I.E-6. Percentile concentrations for estimated NMC cumulative 

distributions in the surface water scenario sites (30-year period), adjusted for 

relative potency, inter-species and FQPA safety factors for children 

Region/Site 

Percentile concentration in ug/L (oxamyl 

equivalents, adjusted for uncertainty factors) Major contributors1 

Max 99th 95th 90th 75th 50th 

Florida / South 8.5 2.5 1.0 1.0 0.2 0.03 Methomyl, thiodicarb, 

oxamyl 

Lower Midwest / TX 2.8 1.0 0.4 0.3 0.1 0.03 Aldicarb, formetanate, 

methomyl, oxamyl 

Midsouth / LA 12.6 2.9 0.5 0.2 0.03 0.002 Aldicarb 

Southeast / NC 20.2 4.4 1.0 0.4 0.02 <0.001 Aldicarb 

Southwest / CA 4.3 1.0 0.4 0.2 0.1 0.03 Aldicarb, formetanate, 

methomyl 

Florida / Central 7.3 1.2 0.2 0.09 0.02 0.004 Aldicarb 

Northeast-central / IL 0.2 0.04 0.01 0.007 0.002 <0.001 Carbaryl, methomyl 

Southeast / GA 5.9 1.5 0.3 0.09 0.02 <0.001 Aldicarb 

Northeast-central / PA 0.7 0.2 0.06 0.04 0.02 0.006 Methomyl 

Northwest / WA 1.3 0.3 0.1 0.07 0.03 0.007 Aldicarb, methomyl, 

oxamyl 

N. Great Plains/ MNND 0.3 0.06 0.02 0.01 0.001 <0.001 Carbaryl 

1

Major contributors, after adjusting concentrations for relative potency and FQPA safety and interspecies factors. 

c. Spatial Extent of NMC Exposures in Surface Water 

Many surface water sources of drinking water in the southern 

portions of the US occur where total NMC pesticide use is relatively low 

(Figure I.E-4). The watersheds that are most vulnerable to runoff in the 

high NMC use areas tend to occur in areas where ground water is the 

dominant source of drinking water. For these southern regional 

scenarios (Southeast, Florida, Mid-south, Lower Midwest), the estimated 

exposures represent a few drinking water intakes located in relatively 

high NMC use watersheds. 

Section I.E – Page 152 of 277 
Figure I.E-4. Location of surface water intakes (blue dots) in relation to relative 

NMC pesticide usage (high use areas in dark orange) in the southeastern/southcentral U.S. 

The south Florida scenario represents a handful of community 

water systems (CWS) around the Everglades Agricultural Area (EAA). 

Dominant uses are sugarcane, vegetables (sweet corn, pepper, 

cucumber), and citrus. Drainage canals from sugarcane fields and other 

agricultural areas in and around the EAA are not used directly for 

drinking water, but eventually feed water bodies used in southern Florida 

for drinking water supply. Three community water systems (CWS) draw 

from the southern end of Lake Okeechobee. The city of West Palm 

Beach draws water from Clear Lake, which is fed in part by drainage 

water from the EAA. 

The North Carolina and Georgia surface water sites represent high 

NMC use areas within the coastal plain from southeastern Virginia to 

southeastern Alabama. The dominant NMC uses in the region are on 

cotton, peanuts, and tobacco. A few CWS occur in this area; many are 

located to the west, with watersheds draining relatively low NMC use 

areas. 

Section I.E – Page 153 of 277 
The high-use region around northeastern Louisiana and west 

central Mississippi has few surface water intakes, but represents the 

most vulnerable area in the Mid-south region in terms of NMC usage and 

runoff vulnerability. Transport of pesticides in surface water is 

complicated by levees on the Mississippi River and a system of drainage 

canals. Consequently, the surface water assessment scenario is likely to 

be health-protective for other CWS in lower NMC-use areas in the 

region. 

The scenario for the southern Texas tip represents a number of 

small CWS intakes that draw from channels in a highly-irrigated 

agricultural area. 

d. Sensitivity Analysis: Carbofuran in Surface Water 

Including carbofuran in regional surface water modeling would 

impact modeled surface water exposures, as carbofuran was a major 

contributor to cumulative NMC concentrations in a number of regions. 

The estimated peak concentrations of the carbofuran were in the same 

range as other individual NMC pesticides (the sub-parts per billion 

range). Table I.E-7 summarizes the estimated carbofuran 

concentrations in the regional scenarios. In comparison to the NMC 

concentrations in Table I.E-7, carbofuran had the highest estimated peak 

concentrations in 4 scenarios (south FL, south-central PA, central IL, 

south TX tip); when carbofuran was removed the NMC that replaced it 

was methomyl (3 scenarios) or carbaryl (1 scenario), with the maximum 

estimated concentration differing by less than 0.2 ppb. 

Table I.E-7. Estimated peak concentrations for carbofuran residues for the 

regional surface water drinking water scenarios (30-year period) 

Region / Scenario Crops1 

Concentration, ug/l (ppb) 

Max. 99th %ile 95th %ile 

SE: NC coastal plain Tobacco 0.002 0.001 <0.0001 

Florida (South) sugarcane, sweet corn, cucumber 0.82 0.18 0.08 

Midsouth (northeast LA) cotton, corn, sorghum 0.33 0.15 0.07 

Northeast/ Central (south 

central PA) 

alfalfa, corn, pumpkin, sweet corn 0.09 0.02 0.008 

Northeast/ Central (IL) alfalfa, corn, sweet corn 0.11 0.04 0.01 

Lower Midwest (South TX tip) Cotton, corn 0.35 0.17 0.07 

Northern Great Plains (Red 

River Valley) 

Potatoes, sugar beets, sunflowers 0.008 0.003 0.001 

Northwest (Central WA) Potatoes 0.04 0.02 0.005 

Southwest (CA Central Valley) Alfalfa, cotton, grapes 0.08 0.04 0.02 

1 The estimated exposures depicted here represent current uses for carbofuran. However, the Agency has proposed cancellation 

of all domestic carbofuran uses. 

A comparison with available surface water monitoring data 

(Appendix II.E.I) indicates that the estimated peak NMC residues are 

similar to or less than the maximum reported detections from NAWQA, 

Section I.E – Page 154 of 277 
with a couple of exceptions where reported NAWQA detections were 

greater. While estimated peak carbofuran concentrations reported 

above were similar to or greater than reported detections in most USGS 

NAWQA units, they were well below the maximum reported detections 

(3-32 ug/l) from Zollner Creek in the Willamette Valley study unit. The 

maximum detections reported for Zollner Creek are of the same 

magnitude as the upper percentile of estimated ground water 

concentrations for carbofuran (see the sensitivity analysis for carbofuran 

in ground water below), which resulted in MOEs of less than 10. While 

peak concentrations of carbofuran in surface water are not expected to 

remain elevated for as long as those estimated in ground water, peak 

exposures of the same magnitude found in the monitoring might result in 

an MOE of less than 10. The Agency’s analysis of potential carbofuran 

exposures in drinking water in the single chemical assessment includes 

scenarios with a use intensity similar to Zollner Creek but with greater 

rainfall. 

In the remaining NMC scenarios (Table I.E-8), the percentile 

concentrations increase, in some regions by almost an order of 

magnitude when currently registered carbofuran uses are incorporated. 

However, it did not result in NMC concentrations that resulted in MOEs 

of less than 10. 

Table I.E-8. Percentile concentrations for estimated NMC cumulative 

distributions with and without carbofuran in the surface water scenario sites (30­

year period), adjusted for relative potency, inter-species and FQPA safety factors 

for children 

Region/Site 

Percentile concentration in ug/L (oxamyl 

equivalents, adjusted for uncertainty factors) 

Major contributors1

Max 99th 95th 90th 75th 50th 

Florida / South 

 with carbofuran 

 without carbofuran 

54.5 

8.5 

12.1 

2.5 

5.3 

1.0 

2.6 

1.0 

0.8 

0.2 

0.3 

0.03 

Carbofuran 

Methomyl, thiodicarb, 

oxamyl 

Lower Midwest / TX 

 with carbofuran 

 without carbofuran 

24.5 

2.8 

11.7 

1.0 

5.0 

0.4 

3.0 

0.3 

1.1 

0.1 

0.2 

0.03 

Carbofuran 

Aldicarb, formetanate, 

methomyl, oxamyl 

Midsouth / LA 

 with carbofuran 

 without carbofuran 

21.9 

12.6 

7.5 

2.9 

2.4 

0.5 

1.1 

0.2 

0.3 

0.03 

0.03 

0.002 

Aldicarb, carbofuran 

Aldicarb 

Southeast / NC 20.2 4.4 1.0 0.4 0.02 <0.001 Aldicarb 

Southwest / CA 

 with carbofuran 

 without carbofuran 

7.4 

4.3 

3.2 

1.0 

1.5 

0.4 

0.9 

0.2 

0.4 

0.1 

0.2 

0.03 

Aldicarb, formetanate, 

methomyl, carbofuran 

Aldicarb, formetanate, 

methomyl 

Florida / Central 7.3 1.2 0.2 0.09 0.02 0.004 Aldicarb 

Northeast-central / IL 

 with carbofuran 

 without carbofuran 

7.2 

0.2 

2.5 

0.04 

0.9 

0.01 

0.5 

0.007 

0.1 

0.002 

0.02 

<0.001 

Carbofuran 

Carbaryl, methomyl 

Section I.E – Page 155 of 277 
Percentile concentration in ug/L (oxamyl 

equivalents, adjusted for uncertainty factors) 

Region/Site Max 99th 95th 90th 75th 50th Major contributors1 

Southeast / GA 5.9 1.5 0.3 0.09 0.02 <0.001 Aldicarb 

Northeast-central / PA 

 with carbofuran 5.7 1.7 0.6 0.3 0.1 0.03 Carbofuran 

 without carbofuran 0.7 0.2 0.06 0.04 0.02 0.006 Methomyl 

Northwest / WA 

 with carbofuran 3.6 1.3 0.4 0.3 0.2 0.03 

Aldicarb, carbofuran, 

methomyl, oxamyl 

 without carbofuran 1.3 0.3 0.1 0.07 0.03 0.007 

Aldicarb, methomyl, 

oxamyl 

N. Great Plains/ MNND 

 with carbofuran 0.6 0.3 0.1 0.07 0.03 0.005 Carbofuran, carbaryl 

 without carbofuran 0.3 0.06 0.02 0.01 0.001 <0.001 Carbaryl 

1 Major contributors, after adjusting concentrations for relative potency and FQPA safety and inter-species factors. 

6. NMC Concentrations in Ground Water Sources of Drinking 

Water 

Individual NMC risk assessments and monitoring data indicate that 

aldicarb (primarily its sulfoxide and sulfone degradates) and carbofuran 

are the two NMC pesticides most likely to reach and persist in ground 

water sources of drinking water, especially in shallow, acidic aquifers. 

Three other NMC pesticides – carbaryl, methomyl, and oxamyl – may 

also reach ground water, but are not as likely to persist. 

High NMC use areas occurred in counties where substantial 

portions of the population obtained their drinking water from private wells 

along the southeastern Coastal Plain, in Florida, and the Delmarva 

Peninsula. EPA also included a scenario in central Washington to 

represent potential exposures in the western US. Based on the 

conceptual model, the Agency focused on private wells drawing from the 

surficial aquifer in these regions. Details and results of these exposure 

estimates can be found in Appendix II.E.7. 

Section I.E – Page 156 of 277 
a. Individual NMC Levels in Ground Water 

The Agency estimated drinking water concentrations for individual 

NMC pesticides and for the cumulative NMC load based on high 

leaching potential scenarios representing specific high NMC uses in 

Florida, the southeastern coastal plain and the northwest (Tables I.E-4, 

I.E-9). Each ground water scenario reflects shallow wells in high 

leaching potential soils and vadose zones with ground water at a depth 

of 30 feet, with the exception of the northwestern scenario, which 

represents deeper groundwater. The estimated concentrations in Table 

I.E-9 reflect typical application rates for the NMC pesticides (Appendix 

II.E.4) and well setback distances specified on the existing label for 

aldicarb. 

Table I.E-9. Estimated concentrations for NMC residues for the regional ground 

water scenarios (25-year period) for ground water at 30 feet 

pesticide 

setback 

distance 

NMC Well 

Crop(s) Maximum 

99th 

%ile 

95th 

%ile 

Concentrations, ug/l 

90th 

%ile 

75th 

%ile 

50th 

%ile 

Florida Central Ridge, acidic ground water 

Aldicarb 1000 ft Citrus 3.0 2.8 2.6 2.5 2.0 1.7 

Oxamyl 0 ft Citrus 0.7 0.7 0.5 0.4 0.3 0.2 

Northeastern FL, neutral ground water 

Aldicarb 300 ft Potatoes 1.7e-05 1.3e-05 8.0e-06 5.7e-06 2.7e-06 9.9e-07 

Southern Coastal Plain - southern GA, acidic ground water 

Aldicarb 300 ft 1 Peanuts 6.5 6.0 5.1 4.8 4.1 3.1 

500 ft 1 Peanuts 3.7 3.4 2.9 2.7 2.4 1.8 

Eastern Coastal Plain - eastern NC, acidic ground water 

Aldicarb 300 ft Peanuts 1.3 1.2 1.1 1.0 0.8 0.6 

Oxamyl 0 ft Peanuts 0.01 0.01 0.01 0.01 <0.01 <0.01 

Northwestern US - Central WA, alkaline ground water, 15-foot well depth 

Aldicarb 300 ft Potatoes 0.001 0.001 <0.001 <0.001 <0.001 <0.001 

1 The current label for aldicarb specifies a 300-foot setback between the field of application and drinking water wells 

for use on peanuts. A proposed setback of 500 feet, based on the IRED (USEPA, 2006d), was modeled to determine 

the impact on exposure that would be expected from this modification to the label. Aldicarb use on peanuts is 

included in the dietary baseline assessment. 

This comparison of model estimates with monitoring relies heavily 

on aldicarb monitoring data, as it is the most extensive. Estimated 

concentrations of total aldicarb residues (the parent plus its sulfoxide and 

sulfone transformation products) are comparable to existing monitoring 

data from a number of studies: 

• Estimated concentrations with no setback distance between the well 

and field of application are similar to recent in-field monitoring 

concentrations from wells in and around citrus groves in the FL Central 

Ridge (Lake Wales Ridge) conducted by USGS and the Florida 

Department of Agriculture (USGS, 2006). 

Section I.E – Page 157 of 277 
• Estimated aldicarb concentrations with no well setbacks were also 

similar to monitoring detections from the early 1990’s from private wells 

in Florida (FL DEP, 2005). Those detections do not reflect subsequent 

label changes and required well setbacks. While aldicarb residues in 

recent years have been below the analytical limits of detection in the 

FL monitoring program, estimated concentrations modeled with a 

1000-foot well setback are also below those limits of detection. 

• A 2006 study by Bayer CropScience of private wells in selected 

aldicarb use areas (excluding FL) found detections of aldicarb residues 

in 10% of the wells, with detections as high as 2.9 ug/l (USEPA, 

2007a). Because the single samples represent a snapshot of aldicarb 

concentrations over time, they are best compared to the median 

concentrations of the estimated exposures. The highest detections in 

the monitoring study (2.6-2.9 ug/l range) are similar to the median 

concentrations estimated for the southern coastal plain scenario 

represented by peanut use in GA. 

Additional information on the monitoring studies for aldicarb is in 

Appendix II.E.2; more detail on monitoring-modeling comparisons can be 

found in Appendix II.E.7. 

b. Cumulative NMC Levels in Ground Water 

The cumulative NMC residues in the high-exposure ground water 

scenarios (Table I.E-10) represent the combined contributions of the 

individual NMC residues listed in Table I.E-9 weighted for relative 

potency and uncertainty factors and converted to oxamyl equivalents. 

For this NMC assessment, high-exposure conditions refer to shallow 

wells (30 ft to ground water) extending through soils with a high leaching 

potential rating (according to USDA NRCS ratings) into an unconfined 

aquifer. Except where noted, the ground water is acidic, an environment 

that favors persistence of the NMC chemicals. 

The greatest estimated cumulative NMC concentrations in ground 

water sources of drinking water occurred in the southern portions of the 

coastal plain (representing the coastal plain provinces of SC, GA, AL, 

and northern FL). Concentrations estimated in the Washington 

scenarios were substantially lower than those estimated in other areas. 

Because the concentrations in Table I.E.10 reflect adjustments for 

individual chemical FQPA safety and uncertainty factors in addition to 

relative potencies, they cannot be directly compared to measured values 

in the environment. 

Section I.E – Page 158 of 277 
Table I.E-10. Percentile concentrations for estimated NMC cumulative 

distributions in the ground water scenario sites adjusted for relative potency and 

using safety factors for children 

Percentile concentration in ug/L (oxamyl 

Region/Site equivalents, adjusted for uncertainty factors) 

Max 99th 95th 90th 75th 50th 

Major RPF/UF-adj 

contributor(s) 

NMC Cumulative Distributions incorporating FQPA factors for children 1 

Southern Coastal 

Plain / GA, 300-ft 

setback 

104.7 96.9 82.8 76.8 66.1 49.6 Aldicarb (peanuts) 

GA, 500-ft setback 59.6 55.2 47.1 43.7 37.6 28.2 Aldicarb (peanuts) 

FL Central Ridge, 

1000-ft setback 48.1 45.5 41.6 39.7 33.0 27.6 Aldicarb (citrus) 

Eastern Coastal Plain 

/ NC, 300-ft setback 21.6 20.0 17.5 15.7 13.5 10.3 Aldicarb (peanuts) 

Northeast FL, neutral 2.7E­ 2.0E­ 4.2E­ 1.6E­ 1.3E-04 9.2E-05 Aldicarb, (potatoes) GW 04 04 05 05 

NMC Cumulative Distributions incorporating FQPA factors for adults 1 

Southern Coastal 

Plain / GA, 300-ft 52.3 48.5 41.4 38.4 33.0 24.8 Aldicarb (peanuts) 

setback 

GA, 500-ft setback 29.8 27.6 23.6 21.9 18.8 14.1 Aldicarb (peanuts) 

FL Central Ridge, 

1000-ft setback 23.9 22.6 20.7 19.8 16.4 13.8 Aldicarb (citrus) 

Eastern Coastal Plain 

/ NC, 300-ft setback 10.8 10.0 8.8 7.8 6.8 5.2 Aldicarb (peanuts) 

Northeast FL, neutral 1.3E­ 1.0E­ 2.1E­ 7.9E­ 6.4E-05 4.6E-05 Aldicarb, (potatoes) GW 04 04 05 06 

1

 Concentrations have been adjusted for relative potency and inter-species factors in addition to children- or 

adult-specific FQPA factors. 

Figure I.E-5 illustrates the difference in exposure as a result of 

different well setbacks in the southern coastal plain scenario. The 

cumulative margin of exposure (MOE) for drinking water exposure for 

infants is less than 10 when the setback distance between the field and 

the well is 300 feet. Taking into account a larger (500-foot) well setback 

distance, the resulting drinking water exposure is greater than an MOE of 

10. The drinking water exposure concerns are being addressed in the 

single chemical assessment for aldicarb. For other scenarios modeled 

(representing high leaching potential) the cumulative exposures for 

drinking water are greater than an MOE of 10 (see Figure I.E-7). 

Section I.E – Page 159 of 277 
Figure I.E-5. Cumulative margins of exposure for drinking water from private 

wells in high leaching potential soils in the southern coastal plain (GA Peanuts), 

infants 

Cumulative MOEs for Drinking Water Exposures in a Daily Analysis - Infants 

1 

10 

100 

1000 

10000 

100000 

1 

15 

29 

43 

57 

71 

85 

99 

113 

127

141

155 

16

8

9

1

2

3

5

6

8

9

0

2

3

5

6

9

1 3

1 7 

2 1

2 5

2 9 

2 3

2 7 

2 1

2 5

3 9 

3 3

3 7

3 1 

3 5 

Julian Days 

M

OEs at the 99.9th Percentile 

GA Coastal Plain 300 ft Well Setback Infants 

GA Coastal Plain 500 ft Well Setback Infants 

c. Spatial Extent of High NMC Exposures in Ground Water 

The ground water exposure assessment focused on areas where 

combined NMC exposure is likely to be among the highest within the 

region as a result of total NMC usage, adjusted for relative potencies, 

and vulnerability of the drinking water sources. Based on the fate and 

transport characteristics of the NMC pesticides, interpretations of existing 

monitoring data, and results of exposure modeling, the following 

conditions are likely to result in elevated concentrations of NMC residues 

in ground water: 

• Shallow wells. Concentrations will vary with varying depths to ground 

water and well depths (the depth from which the well draws water). 

Higher concentrations would be expected in more shallow wells while 

lower concentrations would be likely in deeper wells. 

• High leaching potential soils as classified by the USDA Natural 

Resources Conservation Service (USDA NRCS, 2003), with similarly 

permeable conditions extending through the vadose zone to ground 

Section I.E – Page 160 of 277 
water. Such soils are well-drained, highly permeable, and have a low 

organic matter content. 

• Acidic soil and ground water, which favor the persistence of the 

NMC chemicals, particularly the sulfoxide and sulfone transformation 

products of aldicarb. 

In most of the country, NMC residues in drinking water sources are 

at levels that are not likely to contribute substantially to the multi-pathway 

cumulative exposure. However, some areas of the Delmarva Peninsula, 

the southeastern coastal plain, and Florida (primarily along the central 

ridge) and the southeastern coastal plain have conditions that could 

result in elevated NMC concentrations in ground water. These areas 

represent what the Agency believes to be the most vulnerable private 

well drinking water sources for the NMCs based on available monitoring, 

current use patterns, and known soil and hydrologic conditions. In those 

vulnerable areas, which represent a relatively small area of the country, 

the estimated ground water residues are reasonable estimates of 

drinking water exposure for residents who get their drinking water from 

private wells that draw water from shallow depths in unconfined aquifers. 

Figure I.E-6 illustrates the spatial extent of high leaching potential 

soils (shown in red) in the NMC use areas (shown in green) in the 

southeastern US. Although county-level soil information was not 

available for the entire region at the time of the spatial assessment, such 

soils can be identified. While the map includes acidic, high leaching 

potential soils, it does not reflect depth or pH of the ground water, or the 

relative permeability of the underlying vadose zone and aquifer. 

Information on the location or depth of private drinking water wells 

available is also not available. 

Anticipated exposures in other parts of the country are expected to 

be lower than surface water estimates in other regions of the country. In 

the north and north-central regions, total NMC use, particularly aldicarb, 

is relatively low. Aldicarb is no longer labeled for use in a number of 

northern and northeastern states because of a history of ground water 

contamination. In the mid-south, drinking water comes predominantly 

from a public ground water supply drawing from deep, protected 

aquifers. NMC contamination is not expected, except in an area around 

southeastern Missouri and northeastern Arkansas, which had several 

detections in the Bayer CropScience monitoring study (USEPA, 2007a). 

In the Great Plains and Lower Midwest, anticipated exposure is expected 

to be lower than surface water estimates because of low rainfall and 

deeper aquifers than in the southeast and Florida. 

Section I.E – Page 161 of 277 
Figure I.E-6. Extent of high leaching potential soils in NMC use areas in the 

Southeastern U.S. 

d. Sensitivity Analysis: Carbofuran in Ground Water 

Carbofuran was modeled in two NMC scenarios: one representing 

use on potatoes in Northeastern Florida, and the other representing 

cucurbits in the Delmarva Penninsula in the North/North central region 

(Table I.E-11). The Delmarva scenario was not included in the NMC 

assessment, but was developed specifically for the sensitivity analysis 

for carbofuran to represent a high-leaching potential area for cucurbit 

use. 

Table I.E-11. Estimated concentrations for NMC and carbofuran for regional 

ground water scenarios (25-year period) for ground water at 30 feet 

Section I.E – Page 162 of 277 
Section I.E – Page 163 of 277 

Concentrations, ug/l NMC 

pesticide 

Well 

setback 

distance 

Crop(s) Maximum 

99th 

%ile 

95th 

%ile 

90th 

%ile 

75th 

%ile 

50th 

%ile 

Northeastern FL, neutral ground water 

Aldicarb 300 ft Potatoes 1.7e-05 1.3e-05 8.0e-06 5.7e-06 2.7e-06 9.9e-07 

Carbofuran1 0 ft Potatoes 2.7e-11 1.7e-11 9.3e-12 4.8e-12 1.5e-12 1.5e-13 

Delmarva Peninsula, acidic ground water 

0 ft Cucurbits, 

high typ. rate 38.5 36.4 28.8 25.6 20.6 15.5 

Carbofuran1 

0 ft Cucurbits, low 

typ. rate 10.2 9.6 7.6 6.8 5.4 4.1 

1 The Agency has proposed a cancellation of all domestic carbofuran uses. The estimated exposures 

depicted here represent current uses for carbofuran. 

Carbofuran concentrations estimated in Northern Florida were six 

orders of magnitude lower than those estimated for aldicarb, and 

therefore would not be a significant contributor to the NMC in that region. 

However, carbofuran concentrations estimated on the Delmarva 

Peninsula are the highest estimated for any NMC. Estimated carbofuran 

concentrations in private wells in the Delmarva Peninsula are in line with 

monitoring data summarized in the 2006 Carbofuran IRED and suitable 

for human health exposure assessments (Appendix II.E.7). 

The greatest estimated cumulative NMC concentrations in ground 

water sources of drinking water occurred in the Delmarva Peninsula for 

carbofuran-driven NMC exposures ( 
Table I.E-12). The Delmarva Peninsula (carbofuran on cucurbits) would 

result in cumulative exposures for drinking water with a MOE of less than 

10 (Figure I.E-7). These drinking water exposure concerns are being 

addressed through cancellation of all domestic carbofuran uses. All 

other estimated exposures from high leaching potential ground water 

sites result in MOEs greater than the target of 10. 

Section I.E – Page 164 of 277 
1 

15 

29 

43 

57 

71 

85 

99 

113 

127

141

155 

169

183

197 

211

225

239 

253

267 

281

295

309 

323

337

351 

365 

Table I.E-12. Percentile concentrations for estimated NMC cumulative 

distributions in the ground water scenario sites adjusted for relative potency and 

using safety factors for children 

Percentile concentration in ug/L (oxamyl Major RPF/UF-adj Region/Site equivalents, adjusted for uncertainty factors) contributor(s) Max 99th 95th 90th 75th 50th 

NMC Cumulative Distributions incorporating FQPA factors for children (1) 

Delmarva / high-end Carbofuran 2540 2400 1898 1689 1357 1024 typical rate (cucurbit) 

Delmarva / low-end Carbofuran 670.6 633.8 501.2 445.9 358.3 270.5 typical rate (cucurbit) 

Northeast FL, neutral 2.7E­ 2.0E­ 4.2E­ 1.6E­ Aldicarb, carbofuran 1.3E-04 9.2E-05 GW 04 04 05 05 (potatoes) 

NMC Cumulative Distributions incorporating FQPA factors for adults (1) 

Delmarva / high-end Carbofuran 923.7 873.0 690.3 614.2 493.5 372.6 typical rate (cucurbit) 

Delmarva / low-end Carbofuran 243.9 230.5 182.2 162.2 130.3 98.4 typical rate (cucurbit) 

Northeast FL, neutral 1.3E­ 1.0E­ 2.1E­ 7.9E­ Aldicarb, carbofuran 6.4E-05 4.6E-05 GW 04 04 05 06 (potatoes) 

(1) Concentrations have been adjusted for relative potency and inter-species factors in addition to 

children- or adult-specific FQPA factors. 

. 

Figure I.E-7. Cumulative margins of exposure for drinking water from private 

wells in high leaching potential scenarios, children 1-2 years old 

Cumulative MOEs for Drinking Water Exposures in a Daily Analysis - Children 1-2 

Julian Days 

1 

10 

100 

1000 

10000 

100000 

MOEs at the 99.9th Percentile 

Delmarva Cucurbits (low-end typical rate for carbofuran) Children 1-2 

GA Coastal Plain 300 ft Well Setback Children 1-2 

GA Coastal Plain 500 ft Well Setback Children 1-2 

FL Citrus 1000-ft Well Setback Children 1-2 

NC Coastal Plain 300 ft Well Setback Children 1-2 

Section I.E – Page 165 of 277 
7. Summary 

The drinking water assessment focuses on areas where combined 

NMC exposure is likely to be among the highest within each region as a 

result of total NMC usage and vulnerability of drinking water sources. 

This analysis is based on a probabilistic modeling approach that 

considers the full range of data and not a single high-end estimate. EPA 

estimated NMC exposures in drinking water to individuals in the CRA for 

both ground water and surface water sources of drinking water by region. 

The regional drinking water exposure assessments are intended to 

represent exposures from vulnerable drinking water sources resulting 

from typical NMC usage and reflect seasonal variations as well as 

regional variations in cropping and NMC use. Each regional assessment 

focuses on areas where combined NMC exposure is likely to be among 

the highest within the region as a result of total NMC usage, adjusted for 

relative potencies, and vulnerability of the drinking water sources. For 

ground water, private wells extending through highly permeable soil and 

vadose zone materials into shallow, acidic ground water are expected to 

be most vulnerable. For surface water, drinking water reservoirs in 

small, predominantly agricultural watersheds are likely to be most 

vulnerable. The co-occurrence of NMC residues in water is primarily 

estimated from modeling. Monitoring data are not available consistently 

enough to be the sole basis for the assessment. However, monitoring 

data are used to corroborate the modeling results and have helped 

confirm locations of potentially vulnerable drinking water sources. 

In most of the country, NMC residues in drinking water sources are 

at levels that are not likely to contribute substantially to the multi-pathway 

cumulative exposure. Estimated NMC exposures from surface water 

sources of drinking water resulted in MOEs well in excess of 10. For 

most ground water sources of drinking water, NMC exposures were 

similarly low. Private wells in highly permeable soils that draw water at 

shallow depths in acidic, unconfined aquifers represent what the Agency 

believes to be the most vulnerable drinking water sources for the NMCs 

based on available monitoring, current use patterns, and known soil and 

hydrologic conditions. Those instances where NMC concentrations 

resulted in MOEs of less than 10 are being addressed with mitigation 

measures in the single chemical assessments – an increase in the well 

setback distance from 300 feet to 500 feet for aldicarb use on peanuts in 

the southern portion of the Coastal Plain and cancellation of all domestic 

carbofuran uses. With these mitigation measures, NMC exposures from 

drinking water result in MOEs that are greater than 10. 

Section I.E – Page 166 of 277 
F. The Multi-Pathway Cumulative Assessment 

The previous chapters of this document have described the 

development of the primary components of the risk assessment. They 

describe a highly complex process of combining multiple data sets to 

generate a description of the potential risks from NMC pesticides by 

each of the pathways described. OPP has had to generate new 

methods for each component of the assessment in order to produce an 

assessment, which presents as realistically as possible the potential 

exposure to NMC pesticides. The purpose of this chapter is to explain 

the concepts used to accumulate risk from each pathway into a total risk 

estimate, summarize some of the major revised findings, and to provide 

a basis for understanding the graphical temporal exposure profiles that 

are provided in the Appendices. 

1. Basic Concepts 

The definition of cumulative risk developed as a result of the 

passage of FQPA requires OPP to conduct a risk assessment for a 

group of pesticides with a common mechanism of toxicity that is multipathway, multi-route, and multi-chemical in scope and nature. As 

described in Chapter I.B of this revised cumulative assessment for the 

NMCs, the RPF method was used to address the issue of combining 

toxic responses from NMCs with varying propensities to inhibit acetyl 

cholinesterase. Exposure to each NMC was normalized to equivalent 

exposure to the index compound, oxamyl. The toxicity data currently 

available for conducting this analysis are estimates of response by routespecific dosing, and do not support estimating delivered dose to the 

target tissue. OPP decided to address this problem by comparing routespecific exposures to route-specific points of departure (PoD) to produce 

unitless margins of exposure for each route. Thus, each exposure route 

is associated with an MOE for that route. A total (or combined) MOE 

was calculated by taking the inverse of the MOE for each route, adding 

these together, and then taking the inverse of that sum. This process 

was used to produce a distribution of daily estimates of MOEs for the 

subpopulation of concern that reflects regional and seasonal variation15 

in the patterns of exposure that are likely to occur throughout the US 

across the year. OPP used a probabilistic assessment procedure to 

capture the full range of exposure possibilities from all sources analyzed. 

The intent was to produce an estimate of risk that is as realistic as 

possible. The NMC cumulative risk assessment is not a high end risk 

assessment for the specific situation, e.g., geographic location. OPP 

15 Note that seasonal variation was only considered for the residential and 

drinking water pathways. No seasonal variation was considered for the food pathway. 

Section I.F – Page 167 of 277 
believes it reflects the full range of likely exposures and exposure 

possibilities for consideration in a regulatory context and avoids 

developing exposure estimates based upon combination of exposure 

scenarios and assumptions that are not reasonable or are unlikely to cooccur in practice. This method has been standard practice for 

developing total MOE estimates for aggregate and cumulative 

assessments and is further described in OPP’s 2001 Aggregate 

guidance document 

http://www.epa.gov/pesticides/trac/science/aggregate.pdf 

2. Framing the Population-Based Assessment 

OPP used the above-described methodologies to develop a series 

of daily exposure distributions and array them as a distribution across 

time. The distribution of daily exposures and resulting MOEs are 

developed such that the exposures from NMCs in foods, drinking water 

and from residential uses are all calculated simultaneously for each 

hypothetical individual in the subpopulation. OPP used the Calendex 

software to develop the distributions and resulting MOEs. Calendex 

permits incorporation of time-course information with regard to residential 

uses of pesticides and exposures through drinking water, but does not 

permit specific allowance for regional variability. As described in Chapter 

I.E of this document, OPP addressed this issue by focusing on and 

developing separate assessments for regional locations that represent 

what is likely to be the most vulnerable drinking water sources in high 

NMC use areas. Based on a comparison of estimated drinking water 

exposures from surface- and ground-water sources in three regions as 

part of the preliminary NMC CRA, OPP selected drinking water 

exposures representing what have been determined to be the three most 

vulnerable areas –southern coastal plains (Georgia), Florida central 

ridge, and Eastern coastal plains (North Carolina) regions – for the multipathway assessment. NMC exposures in drinking water from the 

remaining parts of the country are expected to be substantially lower 

than from these three sites. 

To generate a daily distribution of exposure for the subpopulation of 

interest, a consumption record is selected from the CSFII that 

corresponds to the age group of interest. Calendex uses this 

consumption record to estimate NMC exposure from food commodity by 

randomly assigning a residue value for each food commonly included. 

After multiplying each amount of food commodity consumed by its 

selected residue value, the total exposure for this individual from food is 

summed. At the same time, all appropriate residential scenarios that 

may be encountered for the calendar day 1 (January 1) are reviewed. A 

probability-based decision is made as to whether or not that scenario will 

be encountered (e.g., a lawn treatment; not likely in January). If the 

Section I.F – Page 168 of 277 
scenario is assigned a "yes" answer, then the appropriate values defining 

the exposure are selected from the many distributions of input 

parameters for residential exposure scenarios. Dermal, oral and 

inhalation exposures are calculated for all selected residential scenarios. 

A drinking water value taken from the estimated distribution of water 

residues for January 1 is selected and paired with the water consumption 

reported in the CSFII consumption record. These values are used to 

calculate exposure from drinking water for that date. All of the exposures 

are converted to route-specific MOEs to define the total exposure to the 

hypothetical individual on January 1. The process is repeated for each 

consumption record for the age group in the CSFII one hundred times to 

build a distribution of exposures for January 1. This process is repeated 

for January 2, January 3 and so forth across the same year. 

The 365 daily exposure distributions are arrayed together in 

order to provide a profile of possible exposures by each route and in total 

as MOEs. A hypothetical example of such a distribution of distributions 

is presented in Figure I.F-1. In this figure, each daily distribution is 

arrayed on the yz plane of the plot. Day 365 can be clearly seen on the 

right side of the plot. This distribution of total risk is expressed as a 

cumulative distribution function of MOEs versus percentile of exposure. 

Percentile of exposure refers to that portion of the population that has 

less than or equal exposure. For example, 80 % of the population has 

an exposure level that is equal to or less than the 80th percentile. 

Figure I.F-1. Three-dimensional plot of the total MOE by day of the year and 

percentile of exposure 

Section I.F – Page 169 of 277 
3. Interpreting the Outputs 

The results of the final assessment are presented in graphical form 

in the appendices. They reflect year-long slices across the 3­

dimensional plot in Figure I.F-1. In that plot, dark lines can be seen 

across the total MOE surface. For instance, the top line in the 3­

dimensional plot represents the 99.9th percentile of exposure for the 

population. A slice through the surface parallel to the xy plane at the 99th 

percentile would look like the plot presented in Figure I.F.2. This plot 

presents the potential total MOE for the population exposed to NMCs by 

the exposure scenarios included in this assessment. In addition, the 

contributions from various pathways and routes of exposure are arrayed 

separately to assist the risk manager in identifying contributors to risk for 

further evaluation. Other percentiles of exposure may also be of interest. 

OPP will use the changes in graphical presentations of data such 

as these to evaluate the significance of various sources of exposure, 

considering the percentile at which the exposure becomes significant 

and the duration over which the exposure route and source remain 

dominant in the risk assessment results. 

4. Attributes of the Revised N-Methyl Carbamate Cumulative 

Risk Assessment 

The current revised assessment focuses on estimating the potential 

risk from exposure to ten NMC pesticides in food and drinking water and 

from residential uses. The assessment is limited in geographic scope to 

the Southern area of the U.S. This limitation was placed on the 

assessment to ensure that the water and residential components of the 

assessment would reflect what a coherent set of pesticide uses are likely 

to exist. Understanding the likelihood of co-occurrence of pesticide uses 

is critical to developing a reasonable estimate of total cumulative risk. In 

the absence of direct measures of co-occurrence, overlapping exposures 

must be extrapolated from use data. The residential and groundwater 

assessments are based on the most highly exposed localized areas 

within the southeastern region of the United States. 

As indicated previously in this report, Table I.B.7 for the food and 

residential components of the cumulative risk assessment, a PoD was 

used for the oral component of the total cumulative risk assessment. 

The estimated BMDL10 (0.18 mg/kg body wt/day) for brain AChE 

inhibition by the index compound (oxamyl) was used. The inhalation and 

dermal components of the assessment were compared to BMDL10s of 

0.66 and 17.05 mg/kg body wt/day, respectively. 

Section I.F – Page 170 of 277 
Integrated cumulated risk assessments were conducted for the 

following age groups: Children 1-2 years, Children 3-5 years, Adults 20­

49 years, and Adults 50+ years of age. These four groups were chosen 

to emphasize the effects of differences in behavior and food 

consumption patterns on estimating the risk from exposure to pesticides. 

The assessments reflect the same assumptions about use scenarios, 

timing of exposures, and exposures to pesticides in food and water as 

used in the previous pathway specific assessments. An entire year of 

exposure is simulated. Three different water scenarios from the south 

were matched with a residential scenario that used application timing 

patterns that are characteristic of the South. Three water scenarios 

simulated ground water sources in Georgia, Florida, and North Carolina. 

The food component of the cumulative risk assessment contains as 

many commodities as could reasonably be extrapolated from the 

available PDP and FDA monitoring data. This component of the 

assessment is regarded as highly refined and reflective of exposures 

likely to be encountered by the U.S. population. Because data on 

residential exposure are more limited, the residential component of the 

assessment was also designed to reflect some overestimation bias to 

ensure that risk from these sources of exposure were not likely to be 

underestimated. The water components of the assessment focused on 

what OPP believes are the most vulnerable drinking water sources. 

While the estimated drinking water concentrations are reasonable 

reflections of actual exposures in those particular areas, the rest of the 

country is expected to have substantially lower combined (or 

“cumulative”) NMC residue levels in its drinking water. 

As discussed earlier, exposure estimates are specific to the regions 

discussed; they take into account region-specific water and residential 

use practices and cannot – as a general matter – be necessarily 

extrapolated to different regions. The Florida central ridge groundwater 

scenario is specific to an area in Florida in which the use of NMC 

pesticides, particularly aldicarb, is high, soils are highly permeable, the 

depth to groundwater is shallow, and the soils and water are acidic. 

These conditions are favorable to potentially high levels of NMC residues 

in drinking water sources. The North Carolina and Georgia coastal plain 

groundwater scenarios represent another area where high NMC use 

(dominantly aldicarb), highly permeable soils, shallow ground water and 

acidic conditions are likely to favor potentially high combined NMC 

levels. Further description of these sites, conditions, and characteristics 

that led OPP to select these sites as high-end with respect to ground 

water concentrations for this cumulative assessment is in Chapter I.D of 

this document. OPP notes that drinking water concentrations from a 

combination of multiple NMCs in the much of the rest of the U.S. would 

be expected to be substantially lower than estimated for this 

Section I.F – Page 171 of 277 
assessment. It is possible, however, that the concentration of a single 

NMC in drinking water could be higher than that of the concentration of 

that single chemical's contribution to this cumulative exposure 

assessment. 

Estimates of cumulative risk from 10 NMCs associated with 

exposure through foods, drinking water, and residential uses are 

presented in Appendices III.F.1-24 for Children 1-2 years old, Children 3­

5 years old, Adults 20-49 years old and for Adults 50+. The contributions 

of each of the major routes of exposure and the likely sources of those 

exposures are discussed in previous chapters of this revised 

assessment. Graphical presentations are provided for the 95th, 97.5th, 

99.5th, 99th, and 99.9th percentiles but written characterizations are 

limited to the 95th, 99th, and the 99.9th because these percentiles capture 

the range of exposure which has traditionally been of most interest to the 

Agency. As described in the residential chapter of this document, 

exposures through the inhalation route were not assessed and are 

considered to be very small. Thus, this exposure route is not specifically 

discussed in each of the following descriptions. 

a. Children, 1-2 years, Georgia Coastal Plain Ground Water 

The results of the total cumulative assessment for Children 

1-2 years using the BMDL10 of the index chemical (oxamyl) for the 

PoD are presented in Appendix II.B.2. Temporal Exposure Profile 

Plots for Georgia Coastal Plain Ground Water appear in Figure 

III.F.2. 

95th Percentile – The significant source of pesticide risk from 

exposure to pesticides at this percentile of exposure is through both 

the drinking water pathway with MOEs ranging from 117 to 

approximately 125 and the food component with an MOE that is 

generally near 142 across the year (Figure III.F.1). Dermal 

exposure that is associated with residential use does not occur at 

this percentile because typically only a small percentage of the 

population uses such products. 

99th Percentile – The daily total MOEs ranged from 26 to 28. At this 

percentile, MOEs associated with food pathways were generally 

approximately 35 and comprise the major source for total exposure. 

The daily MOE values from drinking water sources ranged from 64 

to 70. MOEs from oral non-dietary ingestion which are associated 

with residential use (i.e., hand-to-mouth) were higher than drinking 

water exposure and generally the MOEs for oral non-dietary 

exposure pathway ranged from ca. 296 to greater than 350 (Figure 

Section I.F – Page 172 of 277 
III.F.1). MOEs associated with the dermal route are generally 

greater than 110 but as low as 99. 

99.9th Percentile – At the 99.9th percentile, the total cumulative risk 

(all pathways) was as low as ca. 7 for this age group and nearly all 

of the estimated exposure came through the oral route that 

included significant contributions from the food pathway (Figure 

III.F.1). Oral non-dietary exposure (hand-to-mouth) resulted in 

MOEs remaining consistent through the year between ca 76 and 

90. Dermal MOEs go down to 24 with an average MOE of 27. 

b. Children 3-5 years, Georgia Coastal Plain Ground Water 

The results of the total cumulative assessment for Children, 

3-5 years old using the estimated BMDL10 of the index chemical 

(oxamyl) for the PoD are presented in Appendix II.B.2. Temporal 

Exposure Profile Plots for Georgia Coastal Plain Ground Water 

appear in Figure III.3. 

95th Percentile – Total MOEs at this percentile range from 90 to 94 

throughout the year. The significant contributor to total cumulative 

exposure comes through the drinking water pathway (Figure III.F.3) 

with a range of MOEs of ca. 170 to ca. 180. The next most 

significant contributor to total cumulative exposure is through the 

food pathway; this pathway has fairly stable MOEs of slightly 

greater than 180. 

99th Percentile – At this percentile the total (cumulative) exposure 

resulted in MOEs from 32 to 34 MOEs associated with food were 

generally near 41. MOEs from drinking water sources generally 

remained in the 93 to 102 range. MOEs associated with the dermal 

route appear for the first time here and average ca. 160. 

Exposures from oral non-dietary ingestion (i.e., hand-to-mouth) was 

less than exposure from drinking water and food and MOEs for this 

source generally ranged from ca. 422 to greater than 480 (Figure 

III.F.3). . 

99.9th Percentile – At the 99.9th percentile, the total MOE (all 

pathways) was in the 7 to 9 range and this was nearly all 

contributed through food exposure (Figure III.F.3). Drinking water 

MOEs average 53. MOEs varied for oral non-dietary exposure 

around 115. MOEs from dermal exposures generally ranged 

between ca. 35 and 40. 

Section I.F – Page 173 of 277 
c. Adults, 20-49 years, Georgia Coastal Plain Ground Water 

The results of the total cumulative assessment for Adults, 

20-49 years using the BMDL10 for the PoD are presented in 

Appendix II.B.2. Temporal Exposure Profile Plots for Georgia 

Coastal Plain Ground Water appear in Figure III.F.6. 

95th Percentile – Total MOEs at this percentile are in the 290 to 340 

range with contributions from drinking water dominant and 

persistent throughout the year; exposures through the food 

pathway contribute a relatively small amount compared to total 

exposure, with MOEs for food above 1400 (Figure III.F.6). Dermal 

MOEs were all greater than 4,000. 

99th Percentile – Total MOEs are generally in the 100 to 150 range 

at this percentile. Exposure from drinking water results in MOEs 

between 220 and 240 (Figure III.F.6). MOEs associated with food 

are generally 230. Dermal exposures are associated with MOEs of 

approximately 280 to greater than 2,300. 

99.9th Percentile –Total MOEs at this percentile are generally in the 

30-43 range, with exposure from food dominant throughout the year 

(Figures III.F.1-9). MOEs associated with drinking water are 

generally about 115. Dermal exposures are associated with MOEs 

of approximately 50 to greater than 500. 

d. Adults, 50+ years, Georgia Coastal Plain Ground Water 

The results of the total cumulative assessment for Adults, 

50+ years using the BMDL10 for the PoD are presented in Appendix 

II.B.2. Temporal Exposure Profile Plots for Georgia Coastal Plain 

Ground Water appear in Figure III.F.7. 

95th Percentile – Total MOEs at this percentile are in the 220 to 260 

range with contributions from drinking water and food contributing 

all year long a relatively similar exposure resulting in MOEs above 

400 and dermal MOEs were all greater than 4,000 (Figure III.F.7). 

99th Percentile – Total MOEs are generally in the 71 to 90 range at 

this percentile, with food significantly contributing throughout the 

entire year with food MOEs of ca. 100 (Figure III.F.7). MOEs 

associated with drinking water are generally about 230. Dermal 

exposures are associated with MOEs of approximately 280 to 

greater than 2,300. 

Section I.F – Page 174 of 277 
99.9th Percentile –Total MOEs at this percentile are generally in the 

15 to 20 range, with exposure from food dominant throughout the 

year (Figure III.F.7). MOEs from exposure through the food 

pathway were in ca. 20. Drinking water exposure resulted in MOEs 

of approximately 110. Dermal exposures are associated with 

MOEs of generally ca. 56 to 543. 

e. Children, 1-2 years, Florida Citrus Ground Water 

The results of the total cumulative assessment for Children, 

1-2 years using the estimated BMDL10 of the index chemical 

(oxamyl) for the PoD are presented in Appendix II.B.2. Temporal 

Exposure Profile Plots for Florida Citrus Ground Water appear in 

Figure III.F.9. 

95th Percentile – Total MOEs at the 95th percentile ranged from 67 

to 74 (Figure III.F.9). One source of pesticide risk from exposure to 

pesticides at this percentile of exposure is through the drinking 

water pathway with total MOEs ranging from 121 to 143. The food 

component of the assessment was stable across time with an MOE 

that is generally near 140 across the year. 

99th Percentile – At this percentile, the daily MOE values from 

drinking water sources were ca. 75. Total MOEs averaged about 

27. Exposures from oral non-dietary ingestion which are 

associated with residential use (i.e., hand-to-mouth) were 

somewhat lower than drinking water exposure and generally the 

MOEs for oral non-dietary exposure pathway ranged from ca. 290 

to greater than 350 (Figure III.F.9). MOEs associated with food 

were generally around 35. MOEs associated with the dermal 

pathway are as low as ca. 99. 

99.9th Percentile – At the 99.9th percentile, the total cumulative risk 

(all pathways) generally was in the 6-8 range for this age group and 

nearly all of the estimated exposure came through the food 

pathway (Figure III.F.9). Drinking water exposures resulted in 

MOEs of about 40. Oral non-dietary exposure (hand-to-mouth) 

resulted in MOEs remaining consistent through the year between 

76 and 90. Dermal MOEs generally ranged between ca. 25 and 30. 

f. Children 3-5 years, Florida Citrus Ground Water 

The results of the total cumulative assessment for children, 

3-5 years old using the estimated BMDL10 of the index chemical 

(oxamyl) for the PoD are presented in Appendix II.B.2. Temporal 

Section I.F – Page 175 of 277 
Exposure Profile Plots for Florida Citrus Ground Water appear in 

Figure III.F.10. 

95th Percentile – Total MOEs at this percentile are approximately 95 

throughout the year. The significant contributor to total cumulative 

exposure comes through the drinking water and food pathways 

(Figure III.F.10) with a MOE of ca. 185 each 

99th Percentile – At this percentile, the MOE from food sources 

generally remained in the 40 range and are essentially equivalent 

to total (cumulative) exposure since the food pathway 

predominated. MOEs associated with drinking water were 

generally near 100. Exposures from oral non-dietary ingestion (i.e., 

hand-to-mouth) was less than exposure from drinking water and 

food and MOEs for this source generally ranged from ca. 420 to 

greater than 480 (Figure III.F.10). MOEs associated with the 

dermal route appear for the first time here and always exceed ca. 

140 

99.9th Percentile – At the 99.9th percentile, the total MOE (all 

pathways) was in the 7 to 10 range for this age group and this was 

nearly all contributed by food (Figure III.F.10). Dermal is next in 

importance with MOEs as low as 35. Drinking water MOEs 

averaged around 60. MOEs varied for exposure through oral nondietary exposure (hand-to-mouth) around 110. MOEs for dermal 

exposures generally ranged between 35 and 40. 

g. Adults, 20-49 years, Florida Citrus Ground Water 

The results of the total cumulative assessment for Adults, 

20-49 years using the BMDL10 for the PoD are presented in 

Appendix II.B.2. Temporal Exposure Profile Plots for Florida Citrus 

Ground Water appear in Figure III.F.14. 

95th Percentile – Total MOEs at this percentile are in the 420 to 500 

range with contributions from drinking water dominant and 

persistent throughout the year; exposures through the food 

pathway contribute a relatively small amount compared to total 

exposure, with MOEs for food above 1300 (Figure III.F.14). Dermal 

MOEs were all greater than 4,000. 

99th Percentile – Total MOEs are generally in the 110 to 160 range 

at this percentile, with exposure from food and drinking water 

dominating during the entire year. Drinking water MOEs were 

consistently about 250. MOEs associated with food are generally 

Section I.F – Page 176 of 277 
about 260 (Figure III.F.14). Dermal exposures are associated with 

MOEs of approximately 300 to greater than 2,000. 

99.9th Percentile –Total MOEs at this percentile are generally in the 

30 to 44 range, with exposure from food which was dominant 

throughout the year. Drinking water resulted in MOEs of 125 

(Figure III.F.14). Dermal exposures are associated with MOEs of 

generally ca. 50 to greater than 500. 

h. Adults, 50+ years, Florida Citrus Ground Water 

The results of the total cumulative assessment for Adults, 

50+ years using the BMDL10 for the PoD are presented in Appendix 

II.B.2. Temporal Exposure Profile Plots for Florida Citrus Ground 

Water appear in Figure III.F.15. 

95th Percentile – Total MOEs at this percentile are ca. 340 with 

contributions from drinking water all year long of MOEs around 500 

and food contributing a relatively small amount of exposure 

resulting in MOEs above 1000. Dermal MOEs were all greater than 

4,000 (Figure III.F.15). 

99th Percentile – Total MOEs were generally around 140 at this 

percentile, with exposure from food dominating during the entire 

year. MOEs associated with drinking water are generally about 300 

(Figure III.F.15). Dermal exposures are associated with MOEs of 

approximately 330 to greater than 2,000. 

99.9th Percentile –Total MOEs at this percentile are generally in the 

30 to 40 range, with exposure from food dominant throughout the 

year (Figure III.F.15). MOEs from exposure through the drinking 

water pathway were in ca. 160. Dermal exposures are associated 

with MOEs of generally ca. 80 to 550. 

i. Children, 1-2 years, North Carolina Coastal Plains Ground 

Water 

The results of the total cumulative assessment for Children, 1-2 

years using the estimated BMDL10 of the index chemical (oxamyl) 

for the PoD are presented in Appendix II.B.2. Temporal Exposure 

Profile Plots for North Carolina Coastal Plain Ground Water appear 

in Figure III.F.18. 

95th Percentile – The significant source of pesticide risk from 

exposure to pesticides at this percentile of exposure is through the 

food pathway with total MOEs ranging from 88 to 95 (Figure 

Section I.F – Page 177 of 277 
III.F.18). The food component of the assessment was stable 

across time with an MOE that is generally near 140 across the 

year. Drinking water exposure resulted in MOEs as low as ca. 300. 

Dermal exposures (associated with residential use) do not occur at 

this percentile because typically only a small percentage of the 

population uses such products. 

99th Percentile – MOEs associated with food were generally around 

35 and comprise the major source for total exposure. Exposures 

from oral non-dietary ingestion which are associated with 

residential use (i.e., hand-to-mouth) were somewhat lower than 

drinking water exposure and generally the MOEs for oral nondietary exposure pathway ranged from ca. 290 to greater than 350 

(Figure III.F.18). At this percentile, the daily MOE values from 

drinking water sources ranged from 166 to greater than 186. MOEs 

associated with the dermal pathway are generally greater than 100. 

99.9th Percentile – At the 99.9th percentile, the total cumulative risk 

(all pathways) generally was about 8 for this age group and was 

nearly all of the estimated exposure came through the oral route 

comprised mostly of food pathways (Figure III.F.18). Drinking 

water and oral non-dietary exposure (hand-to-mouth) is next in 

terms of magnitude of contribution with MOEs from about 70 to 

100. Dermal MOEs ranged between 24 and 30. 

j. Children 3-5 years, North Carolina Coastal Plains Ground 

Water 

The results of the total cumulative assessment for Children, 

3-5 years old using the estimated BMDL10 of the index chemical 

(oxamyl) for the PoD are presented in Appendix III.F.19 Temporal 

Exposure Profile Plots for North Carolina Coastal Plain Ground 

Water appear in Figure III.F.19. 

95th Percentile – Total MOEs at this percentile are approximately 

110 to 120 throughout the year. The significant contributor to total 

cumulative exposure comes through the food pathway (Figure 

III.F.19) with MOEs of ca. 185. The next most significant 

contributor to total cumulative exposure is through the drinking 

water pathway; this pathway has MOEs of greater than 400. 

Dermal exposures do not occur at this percentile because typically 

only a small percentage of the population uses such products. 

99th Percentile – The total (cumulative) exposure was ca. 35 with 

most of the exposure through exposure to food. At this percentile, 

the MOE from food sources generally remained between 39 and 

Section I.F – Page 178 of 277 
42. The drinking water pathway averaged in MOEs of ca. 250. 

MOEs for oral non-dietary ingestion (i.e., hand-to-mouth) generally 

ranged from ca. 420 to greater than 480 (Figure III.F.19). As with 

Children 1-2 years old dermal exposures do not occur at this 

percentile. 

99.9th Percentile – At the 99.9th percentile, the total MOE (all 

pathways) was in the 7 to 9 range for this age group and this was 

nearly all contributed by exposure through the oral route (drinking 

water, oral non-dietary and food pathways all contributed to these 

MOEs) (Figure III.F.19). Oral non-dietary exposure (hand-tomouth) resulted in MOEs generally in the 110 to 120 range 

throughout the year. MOEs varied for exposure through food 

around 9. MOEs for dermal exposures were above 30. 

k. Adults, 20-49 years, North Carolina Coastal Plains Ground 

Water 

The results of the total cumulative assessment for Adults, 

20-49 years using the BMDL10 for the PoD are presented in 

Appendix II.B.2. Temporal Exposure Profile Plots for North 

Carolina Coastal Plain Ground Water appear in Figure III.F.22. 

95th Percentile – Total MOEs at this percentile are around 600 with 

contributions from food a major contributor and persistent 

throughout the year with MOEs of around 1200; exposures through 

the drinking water pathway contribute a similar amount compared 

to total exposure, with MOEs for drinking water above 1100 (Figure 

III.F.22). Dermal MOEs were all greater than 4,000 

99th Percentile – Total MOEs are generally in the 120 to 210 range 

at this percentile, with exposure from food dominating during the 

entire year (Figure III.F.22). MOEs associated with food are 

generally about 230. Drinking water MOEs ranged from ca. 560 to 

greater than 600. Dermal exposures are associated with MOEs of 

approximately 280 to greater than 2,300. 

99.9th Percentile –Total MOEs at this percentile are generally in the 

30-50 range, with exposure from food dominant almost throughout 

the year (Figure III.F.22). Drinking water MOEs average ca. 300. 

Dermal exposures are associated with MOEs of generally ca. 50 to 

500. 

l. Adults, 50+ years, North Carolina Coastal Plains Ground Water 

Section I.F – Page 179 of 277 
The results of the total cumulative assessment for Adults, 

50+ years using the BMDL10 for the PoD are presented in Appendix 

II.B.2. Temporal Exposure Profile Plots for North Carolina Coastal 

Plain Ground Water appear in Figure III.F.23. 

95th Percentile – Total MOEs at this percentile are in the 480 to 630 

range with contributions from food all year long. Drinking water 

contributed a relatively similar amount of exposure as food, both 

resulting in MOEs above 1000. Dermal MOEs were all greater than 

4,000 (Figure III.F.23). 

99th Percentile – Total MOEs are generally in the 130 to 180 range 

at this percentile, with exposure from food dominating during the 

entire year. MOEs associated with drinking water range from 650 to 

greater than 700 (Figure III.F.23). Dermal exposures are 

associated with MOEs of approximately 300 to greater than 2,300. 

99.9th Percentile –Total MOEs at this percentile are generally in the 

40 range, with exposure from food dominant throughout the year 

(Figure III.F.23). MOEs associated with drinking water range from 

300 to greater than 400. Dermal exposures are associated with 

MOEs of generally ca. 80 to 550 

Section I.F – Page 180 of 277 
G. Risk Characterization 

1. Introduction 

Risk characterization is the interpretation phase of the assessment 

process. This chapter characterizes the risks identified as part of the revised 

NMC CRA. The intent is to note and discuss uncertainties and strengths in the 

hazard and exposure elements of risk estimates and to assess quantitatively 

(when possible) or qualitatively the potential impact of those uncertainties on 

the risk estimates. 

Proper and appropriate risk characterization is particularly important for an 

assessment as complex as the NMC CRA. Many types of data derived from a 

variety of sources have been combined to produce estimates of risk from 

exposure to multiple NMCs in food, drinking water, and from residential use. 

The outputs of the assessment should be evaluated in a variety of ways. 

Potential biases in input parameters, the direction of the bias, and the 

uncertainty surrounding the inputs and the exposure model must be considered 

with regard to their potential impact on the results of the assessment. 

Sensitivity analyses are important as is a description of how changes in input 

assumptions might – or might not—affect the assessment. 

This revised NMC CRA reflects the impacts on the risks from 

implementing the risk mitigation measures from the single chemical 

assessments. The current document presents the estimates of risks associated 

with exposures to NMCs in food, drinking water, and from residential uses. For 

the multi-pathway assessment, food, drinking water, and residential exposures 

are cumulated as a set of temporal or time-series plots of MOEs over a period 

of 365 days. Contributions from various pathways and routes of exposure are 

arrayed separately. The assessment presents and discusses results for the 1-2 

year old, 3-5 year old, 20-49 year old, and 50+ year old age groups for the three 

geographic regions of interest. While the results for infants, 6-12 year old 

children, 13-19 year old youths, and females 13-49 are not discussed in this 

chapter, these analyses were performed and are presented in Part III.F of this 

assessment with the other four age groups. 

No single value in the assessment should be used to independently arrive 

at the interpretation of the results. As discussed below, interpretation of the 

assessment depends upon the synthesis of a vast body of information about the 

input data and the processing of that data to determine whether estimated risk 

is below OPP’s level of concern. 

2. Hazard and Dose-Response Assessment 

The hazard and dose-response assessment is presented in detail in 

Chapter I.B. That chapter outlines the steps in developing the dose-response 

Section I.G - Page 181 of 277 
relationships for each pesticide based on inhibition of 

acetylcholinesterase via carbamylation of the active site. It includes a 

description of all of the data used in the dose-response analyses. Reasons for 

the selection of oxamyl as the index chemical for the NMC CRA are also 

discussed. In addition, Chapter I.B describes the dose-time-response model 

used to develop the dose response curves and half-life to recovery estimates 

that provided the basis for developing the RPF for each chemical, the PoDs for 

the index chemical for each route of exposure (i.e., oral, dermal, and 

inhalation), the FQPA 10X factors, and the inter-species extrapolation factors. 

a. Acetylcholinesterase Inhibition: Data Quality & Common Effect 

The first step in deciding that a cumulative risk assessment was needed 

was the determination that the NMCs were toxic by a common mechanism, i.e., 

AChE inhibition via carbamylation of the active site of the enzyme. Once a 

common mechanism was identified, the next step in the process was to select 

an appropriate method for combining the risks from exposures to several 

pesticides from more than one source/route. Data describing the inhibition of 

AChE in RBCs and brain has been generated for each registered NMC. 

Studies developed for registration along with studies performed by EPA’s 

NHEERL have been used in this risk assessment. OPP has elected to use the 

brain AChE data from adult rats as the basis for developing RPFs and PoDs for 

use in the assessment. Brain AChE inhibition was selected as it reflects a 

response in a target tissue of concern that is relevant to humans. Although 

RBC cholinesterase inhibition data do reflect exposure to NMCs and, therefore, 

the potential for adverse effects, brain AChE inhibition is an indication of direct 

effects upon the target tissue itself. Error due to the extrapolation between the 

response in a surrogate tissue (i.e., red blood cell and plasma) and a target 

tissue itself (brain) is eliminated. In addition, the data for the brain compartment 

have very narrow confidence limits when compared to those from the blood, 

suggesting that there is much less variability in this compartment across the 

data base. As described in Chapter I.B, human studies on RBC ChE are 

available for aldicarb, oxamyl, and methomyl. EPA has determined, after 

considering the advice of the HSRB, that these studies are ethically and 

scientifically acceptable and appropriate for use in this risk assessment. For 

these three chemicals, inter-species factors were derived by comparing this 

ChE data from human RBCs with similar RBC ChE data from rats: this 

comparison was used to replace the standard 10x inter-species uncertainty 

factor for the three NMC pesticides. 

Due to the nature of AChE inhibition with NMCs (i.e., rapid time-to-peak 

effect followed by recovery), accurate measurements of inhibition can be 

challenging in the laboratory. The Agency acknowledges this and also the 

importance of data quality on estimates of potency. As part of the cumulative 

risk assessment and in an effort to aid in the evaluation of data submitted for 

registration, ORD performed a series of dose-response studies where data on 

AChE inhibition derived from a radiometric method were compared with data 

Section I.G - Page 182 of 277 
derived from a standard Ellman method. When evaluating the toxicity of 

NMCs, data from the radiometric studies are considered the highest quality. 

The Agency has also compared results from modified Ellman assays from 

studies submitted for registration with the radiometric data and has requested 

and reviewed the SOPs for AChE measurements for NMCs. The review of 

these SOPs is provided in Appendix II.B.5. Overall, the Agency has concluded 

that the available database of AChE studies is high quality and appropriate for 

deriving relative potencies. The Agency is confident that the assessment, as 

performed, is scientifically and statistically sound and based upon a reliable 

data set. 

A BMD10 was selected as the basis for comparison of the dose-response 

curves for the NMCs. OPP's goal in selecting a point of comparison was to 

choose a point where the magnitude of the response (cholinesterase inhibition) 

was reliably distinguishable from background but still be protective of behavioral 

and functional effects. As described in detail in Chapter I.B, the response level 

of 10% from control provides this balance. A power analysis has shown that 

10% inhibition can be reliably detected in the majority of toxicity studies 

submitted to EPA. The Agency believes that the BMD10 is protective of 

functional and behavioral effects as none have been observed at levels at or 

below 10% inhibition. 

b. Dose-Response Analysis 

This assessment uses the RPF approach. Briefly, the RPF approach uses 

an index chemical as the point of reference for standardizing the common 

toxicity of the chemical members of the cumulative assessment group. RPFs 

(i.e., the ratios of the toxic potency of a given chemical to that of the index 

chemical) are then used to convert exposures of all chemicals in the cumulative 

assessment group into exposure equivalents of the index chemical. The RPF 

approach utilizes dose-response information to provide an estimate of each 

NMC's potency for the common toxicity, and thus allows for the quantification of 

exposure as it relates to the joint risk of the cumulative assessment group. 

OPP selected the RPF approach based upon the relatively rich toxicity data 

base on cholinesterase inhibition available for the NMCs. Although a biological 

or pharmacokinetic modeling approach would have advantages in determining 

the cumulative risk for these NMCs, the input parameters for such an approach 

are not available for most of the NMCs. Thus, OPP has applied simple dose 

addition and has used an empirical curve fitting model to determine RPFs and 

PoDs. OPP, in collaboration with ORD, has used an exponential model to 

describe the dose-time-response curves for each NMC. This dose-timeresponse model has been used to fit cholinesterase activity data from different 

studies to derive a BMD in addition to estimation of half-life to recovery. Use of 

the exponential model to describe cholinesterase data has been subjected to 

extensive public comment and peer review by the SAP (FIFRA SAP 2001b, 

2002, 2005a, 2005b). OPP believes that the model fitting procedure used in 

Section I.G - Page 183 of 277 
this assessment provides reliable estimates of relative potency and PoDs 

for all routes. 

c. Selecting the Index Chemical 

OPP selected oxamyl as the index chemical for the NMC CRA; this 

selection was supported by the FIFRA SAP (2005b). Certainty in the PoDs 

for risk extrapolation is considered to be of great importance in cumulative 

risk assessment as the PoDs impact the overall uncertainty in the entire risk 

assessment. Oxamyl has sufficient data for cholinesterase inhibition to 

support modeling of a BMD10 and BMDL10 in adult and juvenile rats and 

human subjects. Moreover, oxamyl studies in adult rats are available for all 

three routes of exposure (oral, dermal, inhalation) in addition to half-life to 

recovery in rats and humans. The high quality dose response data for oxamyl 

permit reliable estimates of PoDs for all routes. 

d. Assumption of Dose-Additivity 

The cumulative risk assessment for the NMCs is based on the assumption 

of dose-additivity. Dose-additivity is the Agency's assumption when evaluating 

the joint risk of chemicals that are toxicologically similar and act at the same 

target site (USEPA, 2001a). The SAP (FIFRA SAP, 2001a) indicated that 

substantial reliance would have to be placed on what is known about the 

mechanism of toxicity because it is very difficult to prove dose-additivity at 

human exposure levels. They further pointed out that studies available on 

individual chemicals were usually not designed to address the issue of doseadditivity. 

Although there are a few interaction studies of N-methyl carbamate and 

OP pesticides in the literature (e.g., Gupta and Dettbarn, 1993; Takahashi et al., 

1987), the Agency did not identify any studies conducted using mixtures of 

more than two N-methyl carbamates and which use low dose levels (i.e., that 

do not produce lethality or profound toxicity). NHEERL scientists have 

conducted a mixture study using seven N-methyl carbamates (carbaryl, 

carbofuran, formetanate HCl, methiocarb, methomyl, oxamyl, and propoxur) 

(Padilla et al., 2006). In the mixture study, a dose-additive experimental design 

was used and the proportion of the NMCs in the mixture was based on their 

potency using the individual-chemical benchmark dose values as the point of 

comparison. In general, increasing dosages of the mixture produced increasing 

decrements in brain ChE activity. Moreover, the dose-additive model predicted 

the degree of ChE inhibition (RBC and brain) and changes in motor activity 

within the 95% confidence limits of each predicted value (Padilla et al, 2006; 

Manuscript in preparation). 

The NMCs all act on the same target site– namely, the inhibition of 

acetylcholinesterase by carbamylation in nerve tissue, which elicits a variety of 

Section I.G - Page 184 of 277 
cholinergic effects. Dose addition is regarded as a reasonable and 

appropriate approach for estimating the cumulative risk associated with joint 

exposure to the NMC common mechanism group. 

3. Food Assessment 

The food component of the NMC cumulative risk assessment is based 

primarily upon two extensive, reliable data sets: 1) USDA's Continuing Survey 

of Food Intakes by Individuals, 1994-1996 and 1998 (CSFII) and 2) USDA's 

Pesticide Data Program (PDP). The CSFII provides a detailed representation 

of the food consumption patterns of the U.S. public across all age groups, 

during all times of the year, and across the U.S. The PDP data provide a very 

reliable sample of pesticide residues in the major children's foods, including 

fruits, vegetables, milk, grains and beef/poultry/pork. The PDP program utilizes 

multi-residue analytical methods such that co-occurrence of several pesticides 

in individual samples is captured, alleviating much of the uncertainty that 

otherwise might exist about co-occurrence in foods that are monitored in the 

program. These two sources of data – CSFII consumption data and PDP 

petisticide residue data -- provide a firm foundation upon which to assemble 

other data to develop the NMC cumulative risk assessment and are discussed 

in more detail below. 

a. Consumption Data 

As with the previous cumulative risk assessments performed by OPP, this 

revised NMC assessment is based on dietary consumption data obtained from 

the USDA’s CSFII 1994-96/98. This is an extensive, two-phase (1994-1996, 

and then 1998) survey and includes more than 20,000 individuals sampled over 

four years. The CSFII 1998 provided an additional 5,559 consumption diaries 

for children ages newborn through nine years of age, which supplemented the 

4,253 children sampled in the CSFII 1994-96. This additional, supplemental 

children’s survey was specifically requested of USDA by OPP in order to 

improve the means to assess exposures to children. In each year of the 

survey, approximately 5,500 participants in 62 geographical areas across the 

country were interviewed on their dietary consumption over two separate (nonconsecutive) days. The survey was designed to provide a nationally 

representative sample of non-institutionalized persons residing in the U.S. 

USDA also provides sampling weights, which allow the survey results to be 

projected to the U.S. population. 

The sampling procedure was designed to account for inter-individual 

variability in individual consumption patterns (e.g., types and amounts of foods 

eaten) due to differences in age, gender, ethnicity, regional location, and 

socioeconomic status. Also, survey respondents are interviewed on different 

days of the week throughout the year to account for seasonal and within week 

variability in consumption patterns. A number of other aspects of the survey are 

also controlled in order to maximize the prospect that the results are 

representative not only of the entire U.S. population, but also particular 

Section I.G - Page 185 of 277 
subgroups, including those for which OPP generates acute dietary food 

exposure distributions. 

While the USDA food consumption surveys are designed to be generally 

representative of the U.S. population, it is clear that some factors that can 

influence dietary choices are not addressed in the survey design. For example, 

the CSFII surveys do not purport to be representative of people in institutional 

living arrangements (colleges, nursing homes, etc.) or of different religions or 

health status. Specific subpopulations such as vegetarians, those on restricted 

diets, or those on specialized diets were not specifically surveyed. In addition, 

smaller specialized subpopulations such as Native Americans or subsistence 

fishermen are not specifically targeted16. Overall, however, the dietary 

information which OPP used for the cumulative assessment of NMC pesticides 

is the highest quality data available and is representative of many subgroups in 

the U.S. population. The consumption data available from the CSFII 1994­

96/1998 provide a reasonable basis for estimating NMC food exposure for the 

subpopulations surveyed. 

b. PDP Monitoring Data in the Assessment 

USDA PDP data are used for all of the measured pesticide residues in the 

revised NMC CRA. PDP samples fruits, vegetables, juices, meats, grains, and 

dairy products at central distribution centers and warehouses immediately prior 

to distribution to supermarkets or grocery stores. The samples are washed and 

inedible portions (e.g., cores, peels, etc.) are removed prior to analysis. PDP 

data, thus, closely reflect residues in foods, as consumed. OPP has applied 

factors, where available, to the PDP data to account for cooking and processing 

that might further reduce residues (e.g., cooked potatoes, canned beans). 

Thus, pesticide residue data used directly from PDP or adjusted with 

processing factors accurately represent pesticide concentrations to which 

consumers are exposed. 

The use of PDP as a source of residue data has a number of inherent 

benefits that minimize the need to incorporate conservative assumptions in the 

assessment and produces more realistic exposure estimates. The PDP 

sampling design and procedures provide OPP with a nationally representative 

sample of selected food commodities available to the U.S. population in grocery 

stores. OPP assumes a uniform distribution of these food commodities across 

the U.S. While the assumption of nationally uniform distribution of foods does 

not reflect highly localized consumption events that may be occur as a result of 

individuals obtaining foods at road side stands or local farmers markets and 

consuming it closer to the time of harvest than the foods available in larger 

grocery stores, it is believed that only a small percentage of food consumed is 

actually obtained from these sources and would be affected by this assumption. 

16 Although populations that rely primarily on fish consumption were not specifically 

targeted in CSFII, available residue data indicate that fish consumption is not a major source of 

pesticide exposure for currently registered pesticides in general, nor NMCs in particular. 

Section I.G - Page 186 of 277 
In addition, as noted above, PDP uses multi-residue methods and so 

provides a direct measure of the co-occurrence of multiple pesticides in each 

sample analyzed. Thus, the PDP data inherently reflect existing use patterns of 

pesticides. Given the size, scope, quality, and breadth of the PDP sampling 

program, these data provide the best available information regarding pesticide 

residues in the U.S. food supply. 

c. Data Translation from PDP 

Not all food commodities treated with NMC pesticides are monitored in 

PDP. OPP has developed a procedure by which commodities that are sampled 

by PDP serve as surrogate data sources for some commodities that are not. 

This approach is outlined in OPP/HED SOP 99.3 (USEPA, 1999b). It is based 

upon the concept that families of commodities with similar cultural practices and 

insect pests are likely to have similar insecticide use patterns. Although this 

approach is generally sound, it introduces uncertainty with regard to how similar 

the use patterns for a given pesticide are to those for even closely related 

commodities. 

For example, the same pesticide may be applied to several crops 

belonging to the same crop group (or family) on a similar time schedule. 

However, the application rates and/or the number of treatments may differ 

between the treated crops. Such issues should be taken into consideration 

when conducting sensitivity analyses of the results of the risk assessment. 

When such translations are done in a cumulative risk assessment, the 

assumption of similar agricultural practices is inherently applied to all the 

pesticides in the cumulative assessment group and the co-occurrence of 

pesticides on the surrogate commodity is extended to the commodities to which 

the residues are being translated if the translated commodity is a registered 

use. Whether any such potentially inappropriate translations overestimate or 

underestimate exposure will differ from one commodity to another. However, 

the impact of any such potential translation errors on total exposure is not likely 

to be significant since the commodities for which PDP data were translated 

represent less than 1% of the mean per capita consumption by small children. 

d. Other Sources of Residue Data 

The PDP program provides pesticide residue data for a variety of fruits, 

vegetables, juices, meats, grains, and dairy products. Never-the-less, PDP 

data -- and its associated surrogate data for translated commodities -- still do 

not cover all food commodities of interest. For example, PDP does not 

currently include data for seafood and eggs; for these commodities, FDA's Total 

Diet Study and FDA Monitoring data were reviewed. No NMC residues were 

found in seafood or eggs in either of these programs. Thus, the analytical 

results suggest that eggs and seafood contain negligible residues of NMCs and 

OPP used a zero to represent NMC pesticide concentrations in these 

Section I.G - Page 187 of 277 
commodities. OPP considers this factor neutral with regard to the impact 

on the results of the assessment. 

Approximately 3% of the foods consumed by children 1-2 years of age still 

remains unaccounted for after considering the PDP data, the FDA Total Diet 

Study data, and the FDA surveillance monitoring data. This includes sugar, 

molasses, and various oils and syrups which were assigned a residue value of 

zero. Evidence suggests that these commodities would have de minimis 

pesticide residues. These products are highly processed commodities that are 

unlikely to retain any significant residues following the intensive commercial 

processing they undergo. PDP has sampled high fructose corn syrup during 

1998 and 1999 and did not find residues of any pesticide. PDP has also 

sampled field corn during the 2006-2007 period and only found one sample 

containing an NMC pesticide (carbaryl) at a very low (ppb) concentration. The 

limited data from the Total Diet Study found no residues in pancake syrup or 

sugar. OPP believes that the assumption of zero residues for highly processed 

commodities such as those described above will not result in a significant 

under-estimation of exposure to NMC pesticides from food for children or any 

other subpopulation. 

No data are available for commodities such as dried beans, spices, seeds, 

nuts, and low consumption specialty crops (such as avocado, kiwi, raspberry, 

and mango). OPP believes that the omission of various low consumption and 

specialty foods from the assessment will not significantly under-estimate 

exposure to NMC pesticides from food for children or any other subpopulation. 

e. Impact of Regulatory Actions 

There has been significant mititgation measures implemented on many 

NMCs as a result of the individual chemical decisions, including canceling uses, 

lengthening pre-harvest intervals, and reducing the number and/or application 

rates. As a result, during the period since the issuance of the preliminary NMC 

CRA in August 2005, the Agency has identified, and in some cases imposed, 

risk reduction measures on some of the major contributors to carbamate 

cumulative risk, as discussed below. The risk estimates presented in the 

revised NMC CRA reflect the risk mitigation measures identified for or taken on 

individual carbamates since FQPA was signed into law in August 1996. A table 

summarizing these mitigation measures is provided in Appendix II.A. These 

mitigation measures generally reflect determinations of risk based on EPA’s 

assessment of the single chemical’s risks. For all of the risk mitigation 

measures that are reflected in this document, EPA has either commenced the 

processes necessary to implement its selected risk mitigation or intends to 

commence the appropriate processes in the near future. Having already 

determined that the identified risk mitigation is warranted for the individual 

chemical regardless of the cumulative assessment, EPA has chosen to reflect 

that mitigation in this assessment, and consequently has excluded uses that are 

Section I.G - Page 188 of 277 
slated for cancellation from this assessment.17 More specifically: in 

cases for which agreements have been signed or voluntary cancellations are 

being implemented or have been requested by the pesticide registrant, the uses 

have been excluded from the assessment. Examples include use of methomyl 

on strawberries and grapes. In addition, EPA has excluded all uses where 

specific mitigation measures such as cancellation have been identified and 

proposed based on single-chemical risk assessments. For example, EPA has 

excluded all carbofuran uses from the cumulative assessment except the few 

import tolerances that the Agency is not proposing to revoke. (See Chapter I.A 

for additional details regarding the specific cancellation actions that have taken 

place.) 

For other pesticides, pre-harvest intervals have been extended or 

application rates have been reduced. For example, pesticide use labels for 

commodities such as apples, peaches, pears, potatoes, nectarines, oranges, 

and strawberries were modified at various times in the past several years to 

reduce residues of a number of NMCs such as aldicarb, carbaryl, and 

formetanate HCl. To reflect the impact of these risk mitigation measures, EPA 

used residue data only from years after the measures had been implemented 

(i.e. the more recent years that reflect the changes in pesticide use practices). 

PDP data from prior years – that reflect older, discontinued use patterns – were 

not included. To the extent that the impacts of risk mitigation measures on 

residue level are not yet apparent in the available PDP monitoring data, the 

PDP residue data will not reflect the expected decrease in exposure and the 

assessment likely overestimates risk on this basis. 

f. Impact of Assumptions: Sensitivity Analyses 

The following section describes sensitivity analyses conducted on the 

cumulative food assessment. These analyses focus on four areas: 

• Limit of detection in PDP and the use of ‘zero’ assumption 

for non-detectable residues; 

• Comparison of exposure estimates using all available PDP 

data deemed appropriate for the CRA with those using only 

the PDP data from recent years; 

17 As a practical matter, EPA determined that it would serve no purpose to include 

such uses in the cumulative assessment. Other than by adding a new issue that might delay 

action, adding these uses would not likely have any impact on the timing or substance of any 

cancellation decision relating to such uses. Given that the purpose of tolerance 

reassessment is to determine whether regulatory action should be initiated to modify or 

revoke tolerances that the Agency finds do not meet the safety standard of section 408, there 

seems to be little value in including uses in the assessment that will disappear regardless of 

their impact on cumulative risk; the critical issue for determining whether regulatory action will 

have to be initiated under section 408 is whether the uses that will remain result in 

unacceptable dietary risk. EPA recognizes, however, that to the extent that any risk 

mitigation measures are not subsequently implemented as envisioned in this assessment, the 

N-methyl Carbamate cumulative assessment will have to be revised as necessary. 

Section I.G - Page 189 of 277 
• Summation of exposure over 24 hours instead of smaller 

time increments or individual eating events that would better 

account for rapid reversibility on NMCs; and 

• Consideration of a chemical-specific adjustment factor 

approach for the inter-species extrapolation factor 

Each of these sensitivity analyses is discussed below. 

i. Limit of Detection in PDP: Use of ‘zero’ assumption for nondetectable residues 

One of the important attributes of a cumulative risk assessment is that its 

scope and complexity, unless carefully considered, can potentially lead to 

inflated estimates of risk due to compounding conservatisms which would 

reduce the interpretability and ultimately the utility of the assessments. When 

little or no information is available to inform potential sources of exposure, a 

single chemical assessment may incorporate conservative assumptions to 

reflect reasonable worst case exposure estimates. In cumulative risk 

assessments, the incorporation of such conservative assumptions would imply 

multiple simultaneous reasonable worst case exposure estimates for each 

individual chemical. As such, some of the conservative assumptions 

appropriately used in the single chemical risk assessments are not appropriate 

or reasonable for use in a cumulative risk assessment. 

One example is the way in which assumptions for single chemical versus 

cumulative (multiple) chemical assessments differ for PDP samples with no 

detectable residues. For any analytical method, there is a minimum 

concentration at which a compound must be present in order for it to be reliably 

detected in the sample. This minimum level is referred to as the analytical 

method’s limit of detection (LOD). With respect to a specific pesticide, a sample 

having no detectable residue (i.e. a residue below the LOD) is referred to as a 

non-detect. A non-detect does not necessarily imply that no residues are 

present; instead, a non-detect simply indicates that residues, if present, are 

present at concentrations less than the LOD. In single chemical assessments, 

certain non-detects are assumed to be present at one-half the LOD of the 

analytical method (more specifically: those non-detects for which percent crop 

treated information suggests were actually treated with the pesticide of interest). 

In contrast, all PDP samples with non-detectable residues are assumed to be 

"zero" for this and other cumulative risk assessments. Although the result of 

replacing all non-detectable residues with "zero" values might intuitively suggest 

a bias toward under-estimation of risk, OPP has conducted a sensitivity 

analysis and determined that this assumption has little impact on the upper end 

of the exposure distribution for the NMCs covered by this assessment and upon 

which EPA has based its regulatory decisions. The most highly exposed 

individuals tend to be associated with relatively high consumption of high 

Section I.G - Page 190 of 277 
residue values, not residues below PDP’s limits of detections. The 

details of this sensitivity analysis are provided below. 

The sensitivity analysis is presented in Table I.G-1 and indicates that 

assuming residues of one-half LOD for all non-detects of the most frequently 

detected NMC pesticide on each commodity increased the estimated exposure 

by 4.2% for both groups of children ages 1-2 and 3-5 years at the 99.9th 

percentile. 

Table I.G-1. Sensitivity Analyses for NMC Cumulative Food Assessment: Limit of 

Detection Assumptiona 

Age Group 

Estimated Exposure 

at the 99.9th 

Percentile 

(mg/kg oxamyl 

equivalents) 

0.0229 

MOE at the 99.9th 

Percentile 

Percentile at which 

Target of 10 is 

Reached 

99.848th 7.9 Baseline CRA Children 1-2 

Children 3-5 0.0209 8.6 99.870th 

LOD of PDP: 

Replace 0s with 

one-half LOD 

Children 1-2 0.0238 7.6 99.833th 

Children 3-5 0.0217 8.3 99.859th 

a The sensitivity analyses performed here in the CRA with the LOD differ from those that are typically performed 

for LOD values in the single chemical assessments in two ways: (1) rather than assuming that every chemical in 

the assessment group is present on the non-detect samples, only the most frequently detected chemical on each 

commodity is assumed to be present at one-half the LOD. The rationale behind this approach is that the most 

commonly detected pesticide on each commodity is likely to be the most widely used pesticide on that particular 

commodity and thus most likely to be present at level lower than the PDP LOD; and (2) in contrast to single 

chemical assessments for which only treated commodities are assigned one-half LOD values, all non-detect 

samples of a particular commodity are given a value of one-half the LOD rather than only some of the non-detects 

in the cumulative assessment. 

As can be seen from the baseline analysis using zero residues for all PDP 

non-detect data, the calculated MOEs at the 99.9th percentile of exposure are 

7.9 and 8.6 for children 1-2 and 3-5, respectively, with MOEs reaching the 

target of 10 at the 99.848th and 99.870th percentiles of exposures18, 

respectively. After replacing the zero values with one-half LOD values in the 

manner described above, the calculated MOEs at the 99.9th percentile of 

exposure decrease to 7.6 and 8.3 for children ages 1-2 and 3-5 years, 

respectively, with MOEs reaching the target of 10 at the 99.833th and 99.859th 

percentiles of exposures, respectively. This indicates that the use of zero for 

PDP non-detect data has only a minimal effect on estimated high-end 

exposures. The results of this sensitivity analysis are not unexpected: 

18 In this table --and all subsequent tables which provide summary information regarding 

the Agency’s sensitivity analyses -- EPA has elected to express exposures to three significant 

digits and percentiles at which the target MOE of 10 is reached to 5 digits. The Agency fully 

recognizes that its exposure assessment tools are insufficient to produce this level of precision, 

but has chosen to display the results of its sensitivity analysis to this level in order to more 

effectively illustrate the changes that occur in the CRA when assumptions or other input 

parameters are modified. The reader should note that any perceived differences in exposure or 

risk at this level are well beyond the ability of the Agency to measure or detect. 

Section I.G - Page 191 of 277 
generally, the LODs for PDP data are very low (the average LOD for the 

entire data base is about 0.01 ppm) and the vast majority of exposures at the 

upper percentiles are derived from detectable residues in a single commodity 

rather than from multiple commodities having one-half LOD residue values. 

Therefore, it seems reasonable that the effect of assumptions related to 

estimation of values below the LOD would not significantly influence exposure 

estimates at the highest percentiles of exposure and this sensitivity analysis has 

demonstrated that the manner in which non-detects are handled in the dietary 

assessment does not significantly impact exposure estimates of the most highly 

exposed children. 

ii. Use of Recent PDP Data Only 

As described above, PDP data provide a critical component of the 

cumulative food risk assessment as this database provides reliable residue data 

for commonly consumed commodities sampled near their point of sale. As 

such, the PDP data provide a realistic estimate of pesticide residues actually 

consumed by the public. Except in cases where the Agency has mitigated 

exposures through modification of pesticide labels, has cancelled uses, and/or 

has revoked tolerances, essentially all available PDP data (1994-2006) have 

been used in the revised NMC CRA.19 The practice of incorporating all 

available PDP data is consistent with previous preliminary, revised, and 

updated cumulative risk assessments conducted by the Agency, including the 

OP CRA (USEPA, 2006a). Use of all relevant data takes advantage of more 

samples, and thus more data, for use in the Monte Carlo simulations. 

Moreover, incorporation of a wide range of years of PDP data may better 

capture the typical and ever-present transient shifts in pesticide use practices 

due to temporal variations in weather and/or pest pressures. Any of these 

changes may ultimately result in higher or lower pesticide residues or an 

increased or decreased frequency of residues found in food. On the other 

hand, it is possible that PDP data that are older than five years may not best 

represent current agricultural practices and expected dietary exposures. For 

example, changes in the pesticide market resulting in less expensive or more 

effective alternatives and/or gradual decline or shifts in use due to pesticide 

resistance may make older PDP pesticide data less representative of current 

and (expected) future conditions than more recent data (e.g., within 5 years). 

To evaluate the degree to which changes in pesticide use practices over 

time may or may not have affected the estimated exposures and risks, OPP 

performed a sensitivity analysis in which only the most recent PDP data (2002­

2006) were used. Specifically, OPP ran a second, supplemental analysis which 

used only the last five years of PDP data (except for a few commodities like 

frozen green beans, grape juice, and fresh cherries that were not sampled in 

any year from 2002 to 2006) instead of using all PDP data (1994-2006) that 

defines the baseline. The purpose of this analysis was to determine if the 

elimination of earlier (pre-2002) PDP data -- which might be considered less 

19 For reasons described in the food chapter, PDP data from 1992 and 1993 were not used. 

Section I.G - Page 192 of 277 
typical of current use patterns and practices -- would significantly affect 

the exposure and risk estimates. The details and results of this sensitivity 

analysis are provided in Table I.G-2. 

Table I.G-2. Sensitivity Analyses NMC Cumulative Food Assessment: Recent PDP 

Data Assumption 

Age Group 

Estimated Exposure 

at the 99.9th 

Percentile 

(mg/kg oxamyl 

equivalents) 

MOE at the 99.9th 

Percentile 

Percentile at which 

Target of 10 is 

Reached 

Baseline CRA Children 1-2 0.0229 7.9 99.848th 

Children 3-5 0.0209 8.6 99.870th 

Recent PDP Data 

Only 

Children 1-2 0.0185 9.8 99.895th 

Children 3-5 0.0170 10.6 N/A 

As can be seen in this table, the calculated MOEs at the 99.9th percentile 

of exposure are 7.9 and 8.6 for children ages 1-2 and 3-5 years, respectively, 

using all relevant PDP data (1994-2006). MOEs reach the target of 10 at the 

99.848th and 99.870th percentiles of exposures for children ages 1-2 and 3-5 

years, respectively. When using only the most recent PDP data (2002-2006), 

the calculated MOEs at the 99.9th percentile of exposure are 9.8 and 10.6 for 

children ages 1-2 and 3-5 years, respectively, with the MOE for children 1-2 

reaching the target of 10 at the 99.895th percentile of exposure. The results of 

this sensitivity analysis suggests that EPA has not significantly underestimated 

– and may have overestimated -- exposures by using all years of PDP instead 

of only the most recent years. To the extent that the most recent years of PDP 

data are more representative of present and future-expected exposures, an 

MOE of 10 was reached at the 99.895th percentile for children 1-2 and were 

greater than 10 for children 3-5. 

iii. Summing food exposures over 24 hours 

Another key principle in cumulative risk assessment is the proper 

matching of duration of the toxic effect (What is the time to peak effect? What 

is the time to recovery?) and the duration of exposure (When do exposures 

occur? How long or how often do exposures last? Do exposures overlap?). As 

described in Chapter I.B, the nature of NMC toxicity is rapid onset (typically 30 

min to 1 hour) followed by rapid recovery (one-half life to recovery is typically 

approx. 2 hours). Conceptually, a robust multi-chemical, multi-pathway PBPK 

or PBPK/PD model would be ideal to account for the timing of environmental 

exposure(s) and the timing for AChE inhibition and recovery. However, at this 

time, such a model is not available. In lieu of such a model, EPA has used the 

RPF method to quantify chemical potency. In this assessment, each NMC was 

converted into units of the index chemical, oxamyl. The probabilistic exposure 

models (DEEM-Calendex, Lifeline, SHEDS) used in this assessment sum 

Section I.G - Page 193 of 277 
exposures to oxamyl equivalents over 24 hour periods. These models 

do not allow the typical user to separate exposures into time steps smaller than 

24 hours or to separate exposures by exposure events (i.e., breakfast, lunch). 

Due to the rapid recovery associated with NMC toxicity, 24 hour exposure 

periods may or may not, a priori, be appropriate. More specifically, to the extent 

that a day’s eating occasions leading to high total daily exposure are close 

together in time or occur from a single eating event, the approach used in this 

revised assessment which sums eating events over a 24 hour period provides 

reasonable estimates of risk from food. Under this assumption, minimal AChE 

recovery would occur between eating occasions (i.e., exposure events) since 

exposure events are assumed to occur close together. Conversely, if eating 

occasions leading to high total daily exposures are widely separated in time 

(within one day), then substantial AChE recovery would occur between eating 

occasions and the estimated risks in the cumulative risk assessment could be 

overstated. 

In the absence of a fully developed PBPK model and in the absence of 

probabilistic exposure models that can evaluate exposure durations shorter 

than 24 hours, OPP began an examination of the exposure patterns for food 

records from the high end of exposure distribution with the case study 

presented to the SAP in February, 2005 and followed this work in a 

presentation of the preliminary NMC CRA to the SAP in August 2005. OPP 

acknowledged this aspect of the limitations in the currently available 

probabilistic food exposure models and these early exercises were an attempt 

at determining the degree to which high-end food exposures in the NMC CRA 

could be attributed to specific eating occasions (within a day) that may (i) occur 

closely spaced in time, (ii) occur widely separated by time, or (iii) come from 

single eating events. This was done by looking at actual individual eating 

occasions as recorded in the USDA’s CSFII. The records in the CSFII capture 

detailed information not only about the identity and amount of foods consumed, 

but also about the timing of each eating occasion within a 24-hour period; it was 

these consumption diary records that were examined for those survey 

respondents at the upper end (99.8th to 100th percentile) of the exposure 

distribution. To the extent that a day’s eating occasions leading to high total 

daily exposure might be found close together in time or to occur from a single 

eating event such that minimal AChE recovery occurs between eating 

occasions (i.e., exposure events), the “24 hour sum” approach, which sums 

eating events over a 24-hour period, would provide reasonable estimates of risk 

from food. To the extent that eating occasions leading to high total daily 

exposures are widely separated in time such that substantial AChE recovery 

occurs between eating occasions, the estimated risks under any 24 hour sum 

approach may be overstated and a more sophisticated approach – one that 

accounts for intra-day eating patterns and the recovery of AChE between 

exposure events -- may be more appropriate. 

The updated analyses described here as part of this revised NMC 

confirms EPA’s prior analysis that daily exposures to NMC pesticides in the 

upper extremes of the distribution (99.8+ percentile) for exposures from food 

Section I.G - Page 194 of 277 
mainly involve single eating events. Specifically, OPP found that a large 

fraction (~80%) of daily records for children 1-2 and children 3-5 years old 

contributing to the upper tail of the food exposure distribution represent single 

eating occasions. Less than about 3% of these upper-end diary records result 

from exposures that are divided among three or more eating occasions. 

(Figures I.G-1& I.G-2). 

Person-Days Categorized by Number of Eating Events 4352 Records for Children 1-2 at the 99.8th Percentile of Exposure and Above 

<1% 2% 

17% 

Number of 

Eating Events 

1 

2 

3 

4 

81% 

Figure I.G-1. Number of Eating Events Contributing to Exposures at 99.8+ Percentile 

for Children 1-2 

Person-Days Categorized by Number of Eating Events

9333 Records for Children 3-5 at the 99.8th Percentile of Exposure and Above 

1% 2% 

16% 

Number of 

Eating Events 

1 

2 

3 

4 

81% 

Figure I.G-2. Number of Eating Events Contributing to Exposures at 99.8+ Percentile 

for Children 3-5 

These pie charts represent exposures from the 99.8th to 100th percentile of 

exposure distribution, use PDP data through 2006, and exclude eating events 

that contribute small amounts (<10%) of total daily exposure. Similar pie charts 

Section I.G - Page 195 of 277 
representing PDP data through 2004 were presented to the SAP in 

February 2005 as part of the NMC Case Study and August 2005 as part of the 

preliminary NMC CRA. At these SAP meetings, EPA concluded and the SAP 

agreed that since most food exposure to NMCs occurred in a single eating 

event, a more sophisticated, temporal-based approach which evaluated food 

exposure patterns throughout the day was not warranted. 

As part of the risk characterization phase of this revised NMC CRA, the 

Agency has further refined its assessment of within-day consumption of food 

and used a second approach to characterizing the effect of eating occasions 

with respect to the timing of exposure events. In this second approach, OPP 

worked collaboratively with ORD’s National Exposure Research Laboratory 

(NERL) to use the SHEDS (Stochasistic Human Exposure Dose Simulation) 

model to evaluate the impact of rapid AChE recovery on estimates of food 

exposure. Specifically, the ORD SHEDS model was used to bound the 

maximum extent to which accounting for NMC reversibility could potentially 

reduce estimates of exposure. The SHEDS model provides the user with 

greater ability to perform “what if” analysis, particularly with respect to dietary 

consumption data which is hard-coded in DEEM and the other dietary exposure 

models. This greater ability to specify the use of specific dietary records affords 

the risk assessor the ability to select specific eating occasions to include in the 

assessment. With respect to investigating the effect of NMC half-lives on 

exposure estimates, this capability permitted the Agency to exclude -- from 

each individual CSFII food consumption record -- all eating events resulting in 

NMC exposures except the eating event resulting in the largest exposure to 

each individual. Here, all other eating events were assumed to result in zero 

exposure and only the eating event associated with each individual’s maximum 

exposure was retained. This is equivalent to assuming an infinitesimal half-life 

for all NMCs (i.e., complete and instantaneous recovery) and provides a 

bounding estimate that demonstrates the maximum theoretical effect that 

quantitative incorporation of half-lives could have on exposure estimates. The 

results of this bounding exercise are shown below in Table I.G-3. 

Section I.G - Page 196 of 277 
Table I.G-3. Sensitivity Analyses NMC Cumulative Food Assessment: 24 Hour 

Food Summation 

Age Group 

Estimated 

Exposure at the 

99.9th Percentile 

(mg/kg oxamyl 

equivalents) 

MOE at the 99.9th 

Percentile 

Percentile at which 

Target of 10 is 

Reached 

Children 1-2 0.0229 7.9 99.848th 

Baseline CRA 

Children 3-5 0.0209 8.6 99.870th 

Children 1-2 

 Children 3-5 

80% of individuals at the 99.8th percentile of exposure and above 

were due to exposures from one eating event 

Children 1-2 0.0220 8.2 99.86th a 

Summing 

Exposure over 

24 Hours 

Children 3-5 0.0196 9.2 99.88th a 

a These percentiles are reported to only four significant digits: these are produced by the ORD SHEDS model and only reported to 

two decimal places 

 This bounding exercise reduces exposure at the 99.9th percentile by no 

more than about 3-9% depending on age group. For 1-2 and 3-5 year old 

children, exposure estimates are reduced by 6% and 7%, respectively. MOEs 

would be expected to change in a similar (proportionate) manner. 

As described above, two approaches have been used to evaluate the 

extent to which the Agency’s 24-hour approach to food risk assessment 

overestimates risk from the NMCs. The results of both approaches indicate that 

the cumulative risk to NMCs is indeed not substantively overestimated using the 

current exposure models and the 24-hour approach. This is due to the fact that 

exposure to NMCs occurs predominantly through single eating events and not 

from multiple events that occur throughout the day. Based on these analyses, 

the Agency concludes that the current exposure assessment methods used in 

the revised NMC CRA provide realistic and high confidence estimates of risk to 

the NMCs through food. 

iv. Consideration of Chemical Specific Adjustment Factor 

Approach for the Inter-species Uncertainty Factor 

The Agency has applied a 10X factor for inter-species extrapolation in the 

NMC cumulative risk assessment for those NMCs without human studies. This 

10X factor is consistent with typical Agency practice for most single chemical 

and cumulative risk assessments. The following text describes a sensitivity 

analysis employing an alternative approach used by the WHO for performing 

inter-species extrapolation. 

In 2005, the WHO published its guidance for deriving chemical specific 

adjustment factors (CSAFs) (WHO, 2005). This CSAF guidance describes 

approaches for use of kinetic and mechanistic data to refine inter-species and 

Section I.G - Page 197 of 277 
intra-species extrapolation factors. The International Programme on 

Chemical Safety (IPSC) guidance is based in large part on analyses by 

Renwick (1993) and Renwick and Lazarus (1998) which describe the use of 

toxicokinetic and toxicodynamic data as a means of replacing the traditional 10­

fold safety factors for human sensitivity and animal-to-human extrapolation. 

Although EPA does not yet have guidance for developing CSAFs, the Agency 

has used these concepts in a few risk assessments. One such example 

includes the recent risk assessment for dimethyl arsenic acid (DMA) where the 

available in vivo and in vitro mode of action and metabolism data supported 

toxicodynamic equivalence between rats and humans and thus the interspecies factor was reduced to 3X for DMA. 

Understanding mode of action is an important component of deriving 

CSAFs in that it provides the foundation for understanding what toxicokinetic 

and/or toxicodynamic characteristics are critical for evaluating inter- or intraspecies extrapolation. In the case of NMCs, the mode of action is well 

understood in both animals and humans. Specifically, in rodents and humans, 

NMCs cause neurotoxicity via the inhibition of AChE by carbamylation of the 

serine hydroxyl group located in the active site of the enzyme leading to 

accumulation of acetylcholine and ultimately clinical signs. As part of the risk 

characterization for the revised NMC CRA, the Agency has considered the 

extent to which available data support a CSAF-type approach for those NMCs 

without human toxicity studies. Regarding toxicokinetics, unlike many OPs, 

NMCs do not require activation; the parent compound is an active AChE 

inhibitor. Although some metabolites of NMCs have been shown to be active 

AChE inhibitiors, none have been shown to be more potent than the parent 

active ingredient. Thus, metabolism is considered to be a detoxification 

process. As such, species differences in tissue dosimetry are likely correlated 

with differences in body weight to the 3⁄4 power and are also consistent with a 

3X factor to account for inter-species differences in toxicokinetics (USEPA, 

2006). 

Regarding toxicodynamic characteristics, as noted above, the mode of 

action of NMCs is applicable to animals and humans such that inhibition of 

AChE leads to clinical signs of neurotoxicity. The AChE enzyme in humans and 

rats has similar function and structure. (See reviews by Radic and Taylor, 2006 

and Sultatos, 2006.) The half-life to recovery values for rats and humans 

provided in Table I.B-9 range from approximately 1 to 2 hours and demonstrate 

the similarity of the half-lives of the two species. Based on this information, 

given a similar dose or concentration at the target site, it is likely that human 

and rat AChE would respond similarly. It may be possible to use in vitro studies 

using human and rat tissues and human and rat AChE to test this hypothesis. 

In other words, it may be possible to use in vitro studies to demonstrate 

toxicodynamic equivalence between rats and humans. If these data were 

available and they showed toxicodynamic equivalence, the Agency could 

reduce the inter-species factor for those NMCs without human toxicity studies to 

3X. Because of the lack of these in vitro studies, the Agency does not believe it 

appropriate at this time to further refine the standard 10X factor for inter-species 

Section I.G - Page 198 of 277 
extrapolation. Instead, the Agency has used the CSAF approach as a 

sensitivity analysis in its risk characterization. 

The Agency also notes that in vivo studies with human subjects are 

available for three NMCs (aldicarb, oxamyl, methomyl). These studies were 

determined by EPA, after considering the advice of the Human Studies Review 

Board, to be ethically and scientifically acceptable for use in this risk 

assessment. The Agency has developed BMD estimates in rats and humans 

for RBC AChE inhibition. This analysis has shown that the ratio of the BMDs 

for rat/human ranges from 2 to 5 for these NMCs. This range would tend to 

support the CSAF approach described here to reduce the standard 10X interspecies factor to 3X as part of the sensitivity analysis in the risk characterization 

for those NMCs without human data and which make meaningful contributions 

to the cumulative risk. 

In this sensitivity analysis, the 10X inter-species factor was reduced to 3X 

based on the assumption of toxicodynamic equivalence for carbaryl, 

carbofuran, and formetanate HCl. These three NMCs were selected as they 

contribute to the overall cumulative MOEs. The results of this sensitivity 

analysis are shown below in Table I.G-4. 

Table I.G-4. Sensitivity Analyses NMC Cumulative Food Assessment: CSAF Approach 

for Inter-species UF 

Age Group 

Estimated Exposure 

at the 99.9th 

Percentile 

(mg/kg oxamyl 

equivalents) 

Percentile at which 

Target of 10 is 

Reached 

MOE at the 99.9th 

Percentile 

Baseline CRA Children 1-2 0.0229 7.9 99.848th 

Children 3-5 0.0209 8.6 99.870th 

CSAF Approach for 

Inter-species UF 

Children 1-2 0.0183 9.8 99.896th 

Children 3-5 0.0171 10.5 N/A 

Using the standard 10X inter-species factor for all NMCs without human 

data, the (baseline) MOEs at the 99.9th percentile of exposure reach the target 

of 10 at the 99.848th and 99.870th percentiles of exposures for children 1-2 and 

3-5 years, respectively as shown in Table I.G-4. However, when considering an 

alternative approach to the inter-species factor which assumes a 3X interspecies factor for carbaryl, carbofuran, and formetanate HCl, the MOEs at 

99.9th percentile of exposure increase to 9.8 and 10.5 for children 1-2 and 3-5 

years, respectively, with the exposure for the younger age group reaching the 

target MOE of 10 at the 99.896th percentile of exposures. [Note: because of 

the lack of key in vitro studies to confirm the assumption of toxicodynamic 

equivalence, the Agency did not believe it appropriate at this time to use a 3X 

factor for inter-species extrapolation in the baseline assessment. Instead, the 

Section I.G - Page 199 of 277 
Agency has used the CSAF approach as a sensitivity analysis in its risk 

characterization.] 

g. Model Outputs & Discussion 

The food component of the NMC cumulative risk assessment was 

conducted using the DEEM software. This software program evaluates the full 

range of dietary exposures and permits a detailed evaluation of the source of 

exposures with regard to which foods and pesticides are the predominant 

sources of the exposure. The results of the food portion of the revised NMC 

cumulative risk assessment using baseline assumptions as wel as the various 

sensitivity analyses are summarized in Tables I.G-1 through 4 with detailed 

discussion of methods and approaches presented in Chapters I.C and I.G. 

Table I.G-5 below presents a summary of the NMC Cumulative food 

assessment baseline MOE estimates and the percentiles at which the target 

MOE of 10 is reached. 

Table I.G-5. Summary of NMC Cumulative Food Assessment: Baseline Estimates 

Age Group Percentiles of Exposure MOE at the Selected 

Percentiles 

Percentile at which 

Target of 10 is 

Reached 

Baseline cumulative risk assessment 

95 141 

Children 1-2 99 35

99.9 7.9 

99.848th 

95 185 

Children 3-5 99 40

99.9 8.6 

99.870th 

95 1278 

Adults 20-49 99 236

99.9 42 

N/A 

95 1035 

Adults 50+ 99 193

99.9 40 

N/A 

 The results are presented in the form of MOEs for children 1-2 and 3-5 

years of age and for adults 20-49 and 50+ years of age. MOEs at the 95th, 99th , 

99.5th , and 99.9th percentiles of exposure are presented for each age group. 

Children 1-2 and 3-5 years old are consistently the most highly exposed 

subgroups in the analysis. 

Due to the complex nature of cumulative risk assessments, it is important 

not to use any single point or any MOE estimate alone or in isolation. Each 

estimated MOE is derived from a combination of data from multiple sources that 

describe multiple areas of exposure or hazard. Each dataset and assumption 

used to derive the MOEs includes its own variability and uncertainty. Moreover, 

Section I.G - Page 200 of 277 
some datasets contain more or less precision than others. As such, 

MOEs and the percentile of regulation are not “bright lines.” The Agency has 

focused its sensitivity analyses on MOEs of 10 and the 99.9th percentiles of 

exposure as points of reference, not as required thresholds, values, or cutpoints. 

When developing any risk assessment, assumptions must be made in 

areas where data are not available; this is the also case for the NMC CRA. In 

the NMC CRA, the Agency has made health protective assumptions in its 

baseline analysis, particularly regarding which years of PDP data are most 

appropriate for use in the CRA and the inter-species extrapolation factors for 

those NMCs without human data. The sensitivity analyses shown and 

discussed here are designed to evaluate the degree to which key areas of the 

risk assessment under- or over-estimate the cumulative risk in an effort to 

characterize and understand the MOEs presented in this assessment. As 

described in detail above, the Agency has conducted four sensitivity analyses 

on the food assessment. The results of these sensitivity analyses were 

discussed earlier in this chapter and are summarized in Table I.G-6. 

Table I.G-6. Summary of NMC Cumulative Food Assessment: Sensitivity Analyses. 

Sensitivity Analysis 

1. Baseline CRA 

Age 

Group 

Children 

1-2 

Estimated Exposure at 

the 99.9th Percentile 

(mg/kg oxamyl 

equivalents) 

0.0229 

MOE at the 99.9th Percentile at which 

Target of 10 is Reached 

99.848th 

Percentile 

7.9 

Children 

3-5 

0.0209 8.6 99.870th 

2. LOD of PDP: Replace 

0s with one-half LOD 

Children 

1-2 

0.0238 7.6 99.833th 

Children 

3-5 

0.0217 8.3 99.859th 

3. Recent PDP Data Only 

(2002-2006) 

Children 

1-2 

0.0185 9.8 99.895th 

Children 

3-5 

0.0170 10.6 N/A 

4. Summing Exposure 

over 24 Hours 

Children 

1-2 80% of individuals at the 99.8th percentile of exposure and above 

were due to exposures from one eating event Children 

3-5 

Children 

1-2 

0.0220 8.2 99.86th a 

Children 

3-5 

0.0196 9.2 99.88th a 

5. CSAF Approach for Children 0.0183 98 99.896th 

Section I.G - Page 201 of 277 
1-2 

Inter-species UF Children 

3-5 

0.0171 10.5 N/A 

Children 

1-2 

0.0160 11.3 N/A Recent PDP Data only & 

CSAF Approach for Interspecies UF Children 

3-5 

0.0147 12.3 N/A 

a These percentiles are reported to only four significant digits since they are produced by the ORD SHEDS 

model and only reported to two decimal places 

As can be seen, these four sensitivity analyses result in only minimal 

changes to the estimated cumulative exposure to the NMCs through the food 

pathway and did not result in meaningful changes in the associated MOEs. 

These results support the Agency’s assumptions and findings that: 

 residues below the LOD can be assumed to be “zero” for the cumulative risk 

assessment without underestimating to any substantial degree the cumulative 

risk to these pesticides. For children 1-2 and 3-5 years, MOEs reach the 

target of 10 at the 99.833th and 99.859th percentiles of exposure when the 

one-half LOD assumption is applied. These percentiles at which MOEs of 10 

are reached are not meaningfully different from those under the Agency’s 

baseline assumption. 

 using only the most recent PDP data (as opposed to all relevant PDP data 

from 1994-200620) does not result in substantive changes in exposure 

estimates or associated MOEs. For children 1-2 and 3-5 years, MOEs reach 

the target of 10 at the 99.895th and >99.9th percentiles of exposure 

respectively, when only the most recent PDP data is used. These percentiles 

at which MOEs of 10 are reached are not meaningfully different from those 

under the Agency’s baseline assumption. 

 the cumulative estimates of food exposure provided by summing exposure 

over 24 hours do not substantively overestimate cumulative exposure to food. 

Food exposure to NMCs most often occurs at one eating event such that 

incorporating recovery between eating events is not necessary. 

 using the CSAF approach for the inter-species UF does not result in 

substantive changes in exposure estimates or associated MOEs. For 

children 1-2 and 3-5 years, MOEs reach the target of 10 at the 99.896th and 

>99.9th percentiles of exposure, respectively, when using the CSAF approach 

to adjust the inter-species UF from 10x to 3x for carbaryl, carbofuran, and 

formetanate. These percentiles at which a MOE of 10 is reached are not 

meaningfully different from those under the Agency’s baseline assumption. 

20 The Agency has used all years of PDP except in cases where use patterns have been 

changed in the baseline analysis. Specifically, use patterns have changed for carbaryl, 

methomyl, formetante HCl, and carbofuran. 

Section I.G - Page 202 of 277 
In addition, Table I.G-6 shows the combined impact of using only the 

recent PDP data and the CSAF approach for the inter-species factors on the 

cumulative food estimates. When evaluating these two aspects simultaneously, 

MOEs for all age groups, including children 1-2 and 3-5 years increase to 11 or 

greater. 

The food risk assessment is considered highly refined and is designed to 

provide realistic estimates of exposure to NMCs. Some assumptions used in 

single chemical risk assessments have been removed in the CRA to prevent 

compounding conservative assumptions when assessing the combined risk to 

the 10 NMC pesticides comprising the cumulative assessment group. Even 

with the highly refined nature of this cumulative risk assessment, there are still 

conservative assumptions used in the baseline estimates of cumulative risk. 

The Agency has evaluated the effect of a number of these assumptions in its 

sensitivity analyses conducted for the food assessment and found that they 

result in only minimal changes to the estimated cumulative exposure to the 

NMCs through the food pathway and did not result in meaningful changes in the 

associated MOEs. Further, the Agency has a high level of confidence that the 

cumulative risks are not under- or over-estimated based on these results. 

4. Residential Assessment 

The residential component of the revised NMC cumulative risk 

assessment is a probabilistic assessment, which applies distributional analysis 

to residential exposure assessments. In addition to incorporating distributional 

analysis, the assessment also factors in the seasonal and regional aspects of 

pesticide use. Three types of data are used in the residential assessment: 

• Pesticide use, 

• Pesticide residue dissipation, and 

• Exposure contact/human exposure factors. 

Pesticide use data are used to determine the percent of households using 

a pesticide, the timing of the pesticide treatments, and frequency and duration 

of exposure. In the revised NMC CRA, all pesticide use data were based on 

pest pressures in the Southeast region of the U.S. While insect growth may 

slow during the winter months in the South, unlike other regions in the country, 

there is no period of dormancy. Residential exposure to pesticides is greatest 

in this region due to the longer periods of pest pressure. Consequently, this 

assessment as a whole is assumed to provide a worst case estimate of 

exposure. 

Section I.G - Page 203 of 277 
Pesticide residue dissipation data address the fate of the pesticides 

once applied to an environment (e.g., lawns). Exposure contact data are 

exposure-specific metrics that relate human exposure to pesticide residues. 

Humans come in contact with the residues by contacting the product directly or 

by contacting the residues left after the pesticide applications are made. 

Distributions of human exposure factors, such as the body weight assumption 

used in this assessment, come from the Agency’s Exposure Factors Handbook 

(USEPA, 1997a). The exposure factors taken from the Agency’s Exposure 

Factors Handbook have been previously characterized and are used throughout 

the Agency. 

a. Pesticide Use Data 

Accurate pesticide use data, including information on regional site/pest 

markets, timing of application and the percent of households using NMC 

products, are key to the residential risk assessment. In the absence of that 

specific pesticide use information, OPP developed residential exposure 

scenarios based on timing aspects found in survey data from the Residential 

Exposure Joint Venture (REJV), regional Cooperative Extension Service 

publications, and Doane's GolfTrak. While the REJV data contains a complete 

12-month pesticide use diary for 1,217 household-users, use of these NMCs by 

homeowners is a relatively infrequent event, leading to relatively high 

uncertainty around the various pesticide use estimates. Additionally, the REJV 

did not collect information on the purpose of use (pest treated), areas treated, 

or application rates. Therefore, REJV data was used in combination with 

professional judgement, and product label and pest pressure information from 

the Cooperative State Extension Services to estimate application frequency and 

timing. Doane's GolfTrak was used to identify the percent of golf courses 

treated with pesticides. OPP believes this is a robust data source. 

b. Pesticide Residue and Exposure Contact Data 

i. Dermal Exposure 

Applicator Exposure 

Dermal exposure to pesticides may occur during application 

and post-application activities. Examples of application activities 

that might result in pesticide exposure include, but are not limited 

to, spraying liquid pesticide formulations on ornamental plants, or 

applying granular formulations to residential turfgrass. 

The application of pesticides is one of the more straightforward activity patterns to measure because it represents easily 

defined activities. As a result, dermal exposure contact data used 

to assess exposures during application of consumer-oriented 

pesticides are the most robust information used in the residential 

Section I.G - Page 204 of 277 
portion of this assessment. Recent data generated by 

ORETF have been used to assess the use of hose-end sprayers 

(lawn care products), rotary granular spreaders (lawn care 

products), and hand-pump sprayers (home gardens and orchards) 

and hand-held dusters (home vegetable gardens). Another study, 

submitted by a registrant, was also used to assess residential 

applicator exposure using granular shaker cans. All studies meet 

or exceed current Agency guideline requirements (in particular 

regarding the number of monitoring units) and can be extrapolated 

to include clothing scenarios ranging from short-sleeved shirts and 

short pants to long-sleeved shirts and long pants. OPP has high 

confidence in these data. 

Post-Application Exposure 

Examples of post-application activities that might result in 

pesticide exposure include, but are not limited to, weeding and 

harvesting home gardens, mowing and playing on lawns, and 

playing golf. There are several post-application dermal exposure 

scenarios addressed in this assessment. These are: postapplication dermal exposure resulting from lawn care products, 

garden and home orchard products, pet collar products, and 

contact with treated golf courses. 

Like the applicator scenarios, the post-application garden 

and home orchard exposure scenarios are easily defined. For 

harvesting vegetables or weeding, there is a substantial amount of 

data on farm worker exposures. These contact values have the 

potential to overestimate residential exposure, since they are based 

on activity patterns of individuals whose pay is based largely on 

their productivity. Professional harvesters are likely to be more 

efficient than most home gardeners, and therefore exposed to a 

greater amount of treated surface. Because home gardens consist 

of a wide variety of plants, the use of a uniform distribution of 

values represents activities as diverse as hoeing and harvesting. 

These values may overestimate early season activities that consist 

predominantly of potential exposure to small plants. 

There are a variety of dislodgeable foliar residue data 

available for carbaryl. Dislodgeable residue data for sunflowers 

were used to assess the vegetable and ornamental garden 

scenarios, while olive tree dislodgeable data were used to assess 

the fruit tree scenario. These dislodgeable data were scaled in 

accordance with the label application rates for the carbaryl home 

garden and orchard products. Chemical-specific residue data for 

crops with foliage similar to those typically found in home gardens 

and orchards are expected to adequately represent residues found 

on home-grown ornamentals, fruit, and vegetables. 

Section I.G - Page 205 of 277 
Dermal exposure from post-application contact with lawn 

chemicals is varied. Contact data, representative of the range of 

human activities on lawns has been difficult to model.21 Dermal 

contact exposure values were identified for adults who performed 

scripted activities (Vaccaro, 1996). Rates of transfer in the studies 

with surrogate compounds were similar to those observed in the 

chemical specific dissipation data available to OPP. 

Granular turf transferable residue (TTR) data are available 

for carbaryl, the only chemical registered for residential lawn use 

considered in this assessment. These residue data were used to 

calculate post-application dermal exposure for the broadcast use of 

carbaryl on residential lawns. Because the current mitigation for 

carbaryl lawn products limits broadcast applications to granular 

formulations only, these data are expected to adequately estimate 

dermal exposures resulting from broadcast applications to the lawn. 

The current assessment also addresses dermal postapplication exposure for adults and teens playing rounds of golf on 

treated courses. Carbaryl liquid TTR data were used to assess risk 

for this scenario. Because golf course turf is intensively maintained 

(generally watered and mowed every day), these residue data are 

assumed to overestimate residues on treated golf course turf. The 

exposure contact factors used to estimate post-application dermal 

exposure are based on a few measurements from two studies that 

assessed golfer exposure. The exposure duration for individuals 

playing golf was assumed to be two to four hours per day based on 

information obtained from a 1992 survey conducted by the Center 

for Golf Course Management. These assumptions are expected to 

adequately estimate potential exposure for golfers. 

The revised NMC CRA also considered exposures through 

the use of flea collar products for carbaryl and propoxur. Estimates 

of exposure for these scenarios were developed using an approach 

similar to the one taken with the turf care products. The dermal 

21 The August 2005 SAP recommended performing a sensitivity analysis to compare exposure 

estimates that result when distributions are entered both with and (then) without truncation of 

distributions that extend (at least theoretically) to infinity. More specifically, the preliminary NMC 

CRA that was presented to the SAP in September 2005 truncated any lognormally distributed 

input parameter at a high end percentile (99th) since values associated with higher percentiles 

were considered to be unrealistic. As part of this revised NMC CRA, OPP performed a 

sensitivity analysis to evaluate the impact of truncation on the residential scenario that was 

found to have the greatest influence on the NMC CRA results. Specifically, OPP utilized the full 

(untruncated) lognormal distribution for the transfer coefficient parameter to estimate dermal 

exposure to treated lawns. This full (untrucated) distribution extends to infinity implying no limit 

to how high the transfer coefficient can be. The results of this sensitivity analysis (not presented 

here) indicate that truncation at the 99th percentile in our baseline assessment had no significant 

effect on the results of the NMC CRA. 

Section I.G - Page 206 of 277 
contact factor(s) for post-application exposure is based on a 

shampoo and groomer exposure study for carbaryl in which each 

groomer shampooed the dogs, picked them up wet, and placed 

them into crates. The dogs were then dried and groomed. These 

activities are likely to result in higher contact factors than 

intermittent contact with a pet wearing a collar and thus provide a 

conservative estimate of exposure. 

ii. Non-dietary ingestion 

Toddler ingestion via hand-to-mouth activity was the only 

oral route of exposure considered in the residential portion of this 

assessment. Specifically, oral hand-to-mouth ingestion was 

considered only for children 1-2 and 3-5 years old for the lawn care 

and pet collar scenarios. 

In the preliminary NMC CRA, the non-dietary oral exposure 

pathway produced the lowest Margins of Exposure (MOEs), and 

would therefore be of greatest concern to the Agency. These low 

MOEs were mainly due to the incorporation of micro-activity data 

into our macro activity models which are based on daily average 

activities (and thus use a daily time step). The non-dietary 

ingestion pathway was the least refined of the residential exposure 

pathways modeled in the preliminary NMC CRA. In the revised 

NMC CRA, OPP has modified the methodology used to assess this 

pathway. This refined methodology is based on comments and 

input from the FIFRA Scientific Advisory Panel, and the SHEDS 

and CARES developers. 

The Calendex model used in the preliminary and the revised 

NMC CRA is a macro activity model. Specifically, this model 

simulates exposures by randomly drawing values for each of the 

various exposure factors (e.g., exposure duration, frequency of 

hand to mouth events, surface area of hand mouthed per event) 

then multiplying these values together per the OPP Residential 

Standard Operating Procedures algorithm (USEPA, 1997b). The 

distributions for many of these exposure factors were obtained from 

micro-activity data. For example, the distribution for frequency of 

hand-to-mouth events was based on data from observational 

studies in which all hand contacts were recorded as hand-to-mouth 

events, regardless of the fraction of hand mouthed. For the fraction 

of hand mouthed, no adjustment was made for the duration of time 

the hand remained in the mouth. Utilizing such micro-activity data 

with macro activity models poses many challenges. For example, if 

two variables are negatively correlated (e.g., more frequent 

mouthing is associated with smaller areas of hand mouthed), then 

“modeling the product of two jointly distributed variables as 

independent draws will overestimate the variances...or 

Section I.G - Page 207 of 277 
overestimate exposure at the high end.” Similarly, “fixing the 

residue on a child’s hands (and/or other exposure factors) for a two 

hour play period...will yield ‘greater variability in the modeled 

distribution of exposures than a run that updates the residue 

concentration hourly during the exposure.” (FIFRA SAP, 2005b). 

The new algorithm establishes a maximum amount of residue 

that can be on the hand, or a maximum dermal loading. The 

amount of non-dietary oral ingestion increases with the exposure 

duration, the frequency of hand-to-mouth events per hour, and the 

surface area mouthed per event, while the hand loading serves as 

an upper constraint on oral ingestion between replenishment 

events. This approach is a refinement of the approach used in the 

preliminary NMC CRA and is better suited for assessing children’s 

hand-to-mouth exposure in a probabilistic model. 

The MOEs for all residential scenarios assessed in the NMC 

CRA were derived from a combination of data from multiple 

sources. The data sources used in the NMC residential 

assessment rely upon the best available data. However, each data 

set introduces possible uncertainties in the outcome of the 

exposure assessment. Post-application exposures from the lawn 

and pet uses are considered to be the most significant source of 

uncertainty in the residential risk assessment. A summary of these 

uncertainties and their direction and magnitude, is presented in 

Table I.H.1. The assumptions made in this assessment provide a 

reasonable, high-end estimate of cumulative exposure to NMC 

residential products. OPP is confident that the residential 

assessment is sufficiently conservative and will not underestimate 

exposure or risk. 

Section I.G - Page 208 of 277 
Table I.G-7. Input Parameters Used in the Exposure Models: Bias, Assumptions, Uncertainties

Model Input Parameter Exposure Bias Assumptions, Uncertainties, or Strengths and Other Comments Exposure Model for Residential Pathway Human Activity Pattern 

+ = upward 

~ = neutral 

- = downward 

Lawn Exposure 

Unit Exposure: push-type rotary spreader (mg exposure per amount of active ingredient applied) 

+ 

Assumptions/Uncertainties This unit exposure value is based on 30 replicindividuals using a push-type rotary spreaderscenarios are possible to be generated from tassessment short-sleeved shirt and short panThis may overestimate exposure as large por

the lower legs. Although a surrogate compounis believed to be more influenced by the type rather being chemical specific. OPP has high data. A lognormal distribution was used for the Unit Assumed gloves are not worn. Survey data dresidential handlers use gloves and thus this exposure for these residential handlers. Howconsumers are unlikely to use, remove and camanner of professionals, it is unclear what imactual use. The surrogate compound (dacthal) used in thbe dustier than the granular formulations of thassessed. This factor increases confidence thunderestimate exposure. 

Area treated (square feet) - to ~ 

Assumptions/Uncertainties A difficult variable to estimate. However, the reasonable given the application equipment uunderestimate areas that have larger lawns (Mexposure are large. 

Section I.G - Page 209 of 277 
Model Input Parameter Exposure Bias Assumptions, Uncertainties, or Strengths and Other Comments 

Exposure Model for Residential Pathway Human Activity Pattern 

+ = upward 

~ = neutral 

- = downward 

Dermal Contact Transfer ~ to + 

Adults: activities performed with tank tops and distributions may be reflective of study design activities (choreographed) Children: Based above scripted activities studfactors for differenced in body weight and suradults and children. Assumes all adults and children living in houswith lawn care products are exposed (enter tr

Turf Residues: dermal and hand-to-mouth ~ 

Chemical specific data for granular formulatio

Frequency of hand-to-mouth events and surface area of hand mouthed 

~ 

Based on analysis of the best available obser2007). 

Duration on lawn + 

For children, the value used actually measureand not just time spent on lawns. Does not aresponses of individuals that did not play on l

Home Garden, Fruit Trees, and Ornamental Plants 

Applicator: Hose-End Sprayer, Dust Shaker Can, Trigger Pump Sprayer, Handwand 

~ to + 

All UE data for these scenarios are chemical-assessment short-sleeved shirt and short panmay overestimate exposure as large portion olegs and upper arms. Although a surrogate coexposure is believed to be more influenced by used rather being chemical specific. OPP hadata. A lognormal distribution was used. 

Assumed gloves are not worn. Survey data d

Section I.G - Page 210 of 277 
Model Input Parameter Exposure Bias Assumptions, Uncertainties, or Strengths and Other Comments 

Exposure Model for Residential Pathway Human Activity Pattern 

+ = upward 

~ = neutral 

- = downward 

Area treated: ornamentals ~ to + 

Assumes all plants are treated around the pesized house. 

Area treated: vegetables ~ A lognormal distribution of a well studied variaArea treated: fruit trees + Assumes all fruit trees are treated with the ma

rate. Little data to determine actual area occu

Postapplication: vegetables/fruits ~ to + 

Contact values represent a wide range of actiassumed to be treated. 

Postapplication: fruit trees ~ to + Based on olive dfr study data. Plant residues ~ Based on chemical specific DFR data. 

Ornamental Snail/Slug Bait Applicator: Granular ~ to + 

This unit exposure is based on 15 replicates. exposure while treating shrubs which had higflowers. A lognormal distribution was used. 

Pet Collars 

Postapplication ~ to + 

Dermal contact value from studies in which thcontact. Assumptions for pet fur residues are based oResidential Exposure Assessment. Based on analysis the best available observa2007). 

Duration ~ Based on data from the Freeman et al, 2001 

Golf Post-application: Dermal Contact Transfer ~ 

The surrogate data used to derive transfer cotwo measurements of four individuals playing treated with chlorothalonil (Ballee, 1990), and (four volunteers) to flurprimidol (Moran et al., 

Section I.G - Page 211 of 277 
Model Input Parameter Exposure Bias Assumptions, Uncertainties, or Strengths and Other Comments 

Exposure Model for Residential Pathway Human Activity Pattern 

+ = upward 

~ = neutral 

- = downward

 Duration ~ Estimate based on 1992 Golf Course Manage

amount of time spent golfing. 

Turf Residues: dermal ~ Chemical specific data for liquid formulation o

Section I.G - Page 212 of 277 
5. Drinking Water Assessment 

The regional drinking water exposure assessments are intended to 

represent exposures from vulnerable drinking water sources resulting 

from typical NMC pesticide usage. Each regional assessment focuses 

on areas where combined NMC exposure is likely to be among the 

highest within the region as a result of total NMC usage, adjusted for 

relative potencies, and vulnerability of the drinking water sources. The 

estimated drinking water concentrations for each scenario are not 

national numbers but are reasonable for people living in those vulnerable 

areas. For ground water, shallow private wells in highly permeable soil 

and vadose zone materials with acidic (pH < 7) soil and ground water are 

expected to be most vulnerable. For surface water, drinking water 

reservoirs in small, predominantly agricultural watersheds are likely to be 

most vulnerable. 

Because the selection process took into account the relative 

potencies of the NMC pesticides, the sites used for the initial drinking 

water exposure estimates are biased toward the areas in which the more 

toxic NMC pesticides are used. Since the purpose of the assessment is 

to identify the impact from multiple NMCs occurring in water in the same 

area, the area(s) selected for the assessment do not necessarily 

represent the highest exposure of a single chemical, but rather the 

highest multiple NMC exposure within the region. Since pesticide use 

may vary from year to year and cropping and usage patterns may 

change, some areas in other parts of the region may have greater water 

exposure in a given year. 

a. Ground Water Exposure 

Based on monitoring studies, pesticide fate and transport 

properties, and model projections, the Agency believes that the highest 

overall cumulative NMC concentrations in drinking water sources will be 

associated with: 

• Shallow wells: Concentrations will vary with varying depths to ground 

water and well depths. Higher concentrations would be expected in 

more shallow wells while lower concentrations would be likely in 

deeper wells. 

• High leaching potential soils and vadose zone: Such soils are welldrained, highly permeable, and have low organic matter content. 

Section I.G – Page 213 of 277 
• Acidic soil and ground water: Which favor the persistence of the 

NMC chemicals, which degrade more rapidly in neutral to alkaline pH 

conditions. 

These conditions have been identified in some areas of the 

Delmarva Peninsula, the southeastern coastal plain, and Florida 

(primarily along the central ridge). Estimated NMC exposures in other 

NMC use areas underlain by less permeable soils or with neutral to 

alkaline soil and ground water are expected to be considerably lower. 

While areas of potential concern are illustrated in Figure I.E.7, it does not 

take into account localized conditions such as type and depth of well, 

local variations in soil/vadose zone permeability, or acidity/alkalinity of 

the ground water. It also can not account for the locations of private 

wells or the population that may be drawing their drinking water from 

such vulnerable wells. 

The estimated NMC concentrations for these vulnerable wells are 

comparable to available monitoring data under similar conditions, 

particularly for aldicarb and carbofuran, which are the dominant NMC 

pesticides in ground water. High concentrations of these pesticides 

(including both the parent pesticide and degradation products) have 

been found in wells across the country where the pesticide use coincided 

with highly permeable soils, shallow ground water, and acidic conditions 

(summarized in Chapter I.E and Appendices II.E.2 and II.E.7). These 

detections led to voluntary label changes that restricted the use of those 

pesticides in some regions or placed conditions under which the 

pesticides could be used in some soils (for example, the well setback 

distances added to the aldicarb labels for certain soil and groundwater 

conditions). 

Actual NMC concentrations in private wells may vary from the 

estimated concentrations as a result of a number of factors. Important 

conditions that may affect NMC residue levels in drinking water from 

private wells including depth to ground water, distance between the well 

and the field of application (setback distance), amount of NMC pesticide 

applied over time, and soil/vadose zone properties that affect the 

downward movement of water and pesticides. 

i. Depth to ground water 

EPA set the water table at 30 feet to represent a shallow private 

well, based on a number of sources (Berndt et al, 1998; McPherson et al, 

2000; USGS, 1990; FL water management districts; monitoring study by 

Bayer CropScience reviewed by USEPA, 2007a). In the Bayer 

CropScience study, which surveyed wells in selected aldicarb use areas, 

37% of the 800 wells sampled in the southeast (exclusive of Florida) had 

Section I.G – Page 214 of 277 
reported groundwater depths <50 feet below the surface, with a total of 

21% of the wells with reported depths <25 feet below the surface 

(however, the depth to groundwater was unknown for 45% of the 

sampled wells). Other factors, such as type of well construction, 

presence of casing, and depth to well screen will also influence the 

concentration of NMC residues found in the water. With deeper wells, 

travel time between the soil surface and ground water will increase, 

allowing more time for degradation in transit and lower concentrations. 

EPA evaluated the potential impact of varying well depth on 

estimated NMC concentrations in groundwater in Appendix II.E.7. In the 

central ridge of Florida, estimated concentrations of total aldicarb 

residues and oxamyl ranged from an order of magnitude greater for wells 

at 15 feet to a factor of 2-to-4 times lower for wells at 50 feet. A similar 

range in concentrations was found for total aldicarb concentrations in the 

southern coastal plain (GA) scenario. 

ii. Setback distances between the well and the treated field 

For aldicarb, EPA simulated a setback distance between the well 

and treated field, based on the label specifications: 1000 feet for citrus in 

Florida; 300-500 feet for other uses in the other regional scenarios. The 

Agency evaluated the impacts of the assumed label setbacks in 

Appendix II.E.7. The conceptual model accounted for setback distances 

by increasing the travel time between the treated field and the well. The 

effect of the setback is based on the assumption of first-order 

degradation of aldicarb by hydrolysis during the extra travel time from the 

field of application to the well. 

For aldicarb, a 300-foot setback distance reduced estimated 

concentrations by a factor of 2 while a 1000-foot setback distance 

reduced estimated concentrations by a factor of 20. Actual reductions 

will vary, depending on the direction and velocity of lateral groundwater 

flow in the field. The Agency does not have any monitoring data in 

similarly vulnerable areas with which to judge estimated concentrations. 

While the Bayer CropScience monitoring study showed some differences 

in frequencies of detection based on soil leaching potential, the study 

only identified distance between the well and the field, not the area of 

application. 

The well setbacks only apply for certain high-leaching soils where 

groundwater is within 25 feet of the surface and the well is not cased. 

For other soils, no setback is specified. 

Section I.G – Page 215 of 277 
iii. Hydraulic conductivity of the soil/vadose zone 

The soils in the central ridge of Florida have very high saturated 

hydraulic conductivities. Less permeable soils and soils without 

substantial macropore flow are likely to result in lower than predicted 

concentrations because of the longer transport time. 

iv. Soil/vadose zone and ground water pH 

All of the NMC pesticides, except for the parent aldicarb, are 

susceptible to pH-dependent hydrolysis. Under acidic conditions (low 

pH), these chemicals persist; under alkaline conditions (high pH), they 

degrade rapidly. The estimated concentrations reflect acidic conditions. 

Where soils and water are neutral to alkaline, the concentrations are 

expected to be lower than those estimated for the preliminary 

assessment. In general, the soils and ground water in the ground water 

scenario locations in the NMC CRA – the Central Ridge of Florida, the 

southeastern Coastal Plain, and the Delmarva Peninsula – are expected 

to be acidic. 

v. Other factors 

Label changes for aldicarb, a major contributor to the NMC residue 

levels in ground water, made in the mid- to late-1990’s were intended to 

reduce the amount of total aldicarb residues reaching ground water in 

vulnerable areas. These included well setbacks and some water 

management changes. While the Agency addressed well setbacks in 

the conceptual model, it did not explicitly account for recommended 

water management changes on the label. As noted in Chapter I.E, while 

the private well monitoring data from FL DEP, which analyzed water from 

the tap rather than from the well, indicate a reduction in total aldicarb 

residues detected in later years, interpretation of these results has been 

confounded because the state of Florida has also been placing carbon 

filters on the taps of those homes with aldicarb detections in well water. 

The ground water exposure represents private drinking water wells. 

The Agency assumed in this assessment that, in general, public water 

supplies supplied by ground water will typically draw from deeper 

aquifers and/or aquifers that have a relatively impermeable layer 

between the surface and the water supply. Such supplies are expected 

to be much less vulnerable to pesticide contamination. Public water 

supplies have a higher probability of being treated, although conventional 

treatments processes are likely to result in little or no reduction of NMC 

residues in water. However, where lime softening, which will accelerate 

pH-dependent hydrolysis for all but parent aldicarb, or activated carbon 

Section I.G – Page 216 of 277 
filtration is used, some reduction in NMC residues between untreated 

and treated water may occur (Appendix II.E.3). 

b. Surface Water Exposure 

The Agency does not expect cumulative NMC residues in surface 

water sources of drinking water to reach levels that will contribute 

substantially to the cumulative exposure. Estimated NMC levels in 

drinking water surface water sources from the coastal plain of North 

Carolina were greater than predicted for any of the other regional surface 

water exposure sites. When the drinking water component was 

combined with the food and residential exposure routes in the cumulative 

assessment, the highest seasonal exposures from surface water sources 

of drinking water were approximately an order of magnitude less than 

those estimated for food or for the total NMC exposure from all routes. 

For most of the year, predicted exposures from drinking water were 

much lower. 

For the surface water sources of drinking water, OPP used 

PRZM/EXAMS to predict pesticide concentrations in a small reservoir. 

This modeling approach makes certain assumptions regarding the nature 

of the drinking water source, the watershed, and year-to-year variability. 

The reservoir used for the exposure assessment is based on the 

specific geometry (watershed and reservoir size) of an actual reservoir 

(Shipman City) in the Midwestern US. As such, it is more representative 

of potential transport to similar drinking water sources in high rainfall 

areas such as the Midwest and Eastern U.S. than in the west. 

PRZM is not a basin-scale model, but a field-scale model which 

estimates edge-of-field pesticide loads in runoff. It does not explicitly 

account for the relative contributions of each field to the reservoir. OPP 

used a cumulative adjustment factor (a combination of the regional 

percentage of the total watershed area in crops with carbamate uses and 

the percentage of acres treated by each carbamate on each crop) to 

adjust the resulting reservoir concentrations calculated by EXAMS (see 

USEPA, 2000b, for assumptions involved in applying percent crop area 

factors for drinking water assessments). 

PRZM does not account for location in the watershed: all fields are 

assumed to be uniformly distributed within the watershed, with runoff 

going directly into the reservoir. Each crop use simulated in PRZM 

assumes that the entire area of the watershed planted in the crop 

consists of a single soil. In each of the regions, OPP used data from 

local soils on which the crops are grown. When possible, the soil 

selected for each scenario was a benchmark soil that was prone to runoff 

Section I.G – Page 217 of 277 
(classified as hydrologic group "C" or "D" soils). While an assessment 

using a single soil assumes that each part of the watershed will be 

equally vulnerable to runoff, areas of higher and lower runoff vulnerability 

will exist in an actual watershed. 

Because the application rates, frequencies, and timing are held 

constant, the PRZM/ EXAMS simulations over multiple years evaluate 

the impact of the variability in precipitation on the amount of pesticide 

that reaches surface water. Because weather data spanning 30 years is 

available for many locations across the country, PRZM/ EXAMS can 

account for pesticide runoff from a wide range of weather patterns not 

otherwise possible with monitoring studies that span relatively few years. 

The age of the weather data (1961 to 1990) limits OPP's ability to 

compare of the modeling output to more recent monitoring data. 

Weather data files for PRZM are available for weather stations 

across the country. The weather station nearest to the county or 

counties used for the simulations was chosen for the cumulative 

assessment. To the extent that precipitation in these counties over the 

period of record might have been greater or less than that recorded at 

the nearest weather station, runoff for that area may have been over- or 

underestimated by PRZM. 

c. Usage Information 

Typical application rates and frequencies for each NMC pesticide 

on each crop were generated by taking the average (spanning multiple 

years) of agricultural chemical usage surveys. This assumes that all 

applications were made at this typical or average rate and that 

frequencies of applications were constant year to year. Using these 

typical application rates and frequencies may underestimate water 

concentrations in years when pest pressure is higher than in our reported 

years and may overestimate in years when lower amounts of pesticide 

are used. The usage data were generally not sufficient to conduct a 

probabilistic assessment over a distribution of actual application rates. 

The Agency used typical application rates and acres treated for the 

NMC assessment because of a low likelihood that all of the NMC 

pesticides will be used at maximum rates on all of the crop acreage at 

the same time. In the case of citrus, which resulted in the highest 

estimated NMC residues in drinking water for this assessment (for 

private wells along the central ridge), the maximum label rate for 

aldicarb, the major contributor to total NMC residues, is 4.95 lb ai/A, 

while the typical rate used was 3.9 lb ai/A. Given that estimated ground 

water residues are expected to be proportional to the application rate, 

the total NMC residues for private wells in the central ridge of FL would 

Section I.G – Page 218 of 277 
be no more than 20 percent greater than that used in the exposure 

assessment. In the earlier OP cumulative risk assessment, the Agency 

compared cumulative OP concentrations in surface water estimated 

using the average application rates with those estimated using maximum 

label rates. Estimated peak exposures assuming maximum application 

rates for all pesticides ranged from no difference for the Florida region to 

2 to 4 times greater in the Southeast and Mid-south Regions (USEPA, 

2002b). 

The typical application rates and percent acres treated are derived 

from state-level data and assume uniform use practices across the state. 

In actuality, an uneven distribution of application rates and percent acres 

treated is expected in response to differing pest pressures. Thus, this 

assumption will underestimate areas where pest pressures may dictate a 

higher percentage of acres treated in a given year; similarly, it will 

overestimate areas where low pest pressures will require fewer acre 

treatments. 

d. Timing of Exposure 

OPP used crop profiles and other relative crop production 

publications to establish a window for the application date of the 

pesticide on a particular crop. This window doesn’t necessarily reflect 

the range over which a pesticide will be applied in a particular year, but 

captures the year-to-year variation in the application dates over time. 

Thus, in any given year, the timing of application may be clustered within 

a shorter time-frame than suggested by the application window. 

However, because of weather and other environmental factors, the 

timing of intensive pest pressure and/or pesticide application may vary 

across the window. Thus, while the time series estimated in the drinking 

water exposures show a definite time period of peak exposures for 

surface water sources, the actual time of that peak may vary by several 

weeks, depending on the size of the window of application. Because of 

the interaction of processes in subsurface transport, there is a damping 

effect in the concentrations observed in shallow groundwater. A slight 

seasonal pattern in ground water residue levels is evident in the ground 

water estimates, but the seasonal patterns in concentrations in ground 

water are less affected by timing of application. 

The date of application can have an effect on the predicted 

concentrations generated by PRZM/EXAMS for surface water exposure, 

depending on how near in time the pesticide application coincides with 

rainfall events in any given year. OPP evaluated the impact of varying 

the dates of application across the application window on the OP 

cumulative distribution (USEPA, 2002b). The impact of varying dates of 

application was most evident at the extremes in the distributions. The 

ratio in maximum concentrations between the lowest and highest 

Section I.G – Page 219 of 277 
estimates was a factor of 5 to 6. For 99th and lower percentiles, the 

differences were not as dramatic, with the ratio between lowest and 

highest values generally two or less. This analysis only looked at the 

cumulative OP distribution and did not evaluate variations in individual 

chemical distributions. This analysis has not been conducted for the 

NMC cumulative. 

In the absence of data to show otherwise, OPP assumed that all of 

the pesticide applied on a particular crop is done on the same date. 

While this may be an unreasonable assumption for a large watershed, it 

is not unrealistic for the size of the watershed or fields overlying shallow 

aquifers supplying private wells used in this assessment. This 

assumption may result in higher peaks for surface water, but similar 

overall average concentrations than if applications are spread out over 

time. The resulting estimate of exposure may result in a small 

overestimation bias in the results that will be greater in large than in 

small watersheds. Little change is expected for ground water. 

6. FQPA 10X Factor for the Protection of Infants and Children 

The FQPA (1996) instructs EPA, in making its “reasonable certainty 

of no harm” finding, that in “the case of threshold effects, an additional 

tenfold margin of safety for the pesticide chemical residue and other 

sources of exposure shall be applied for infants and children to take into 

account potential pre- and post-natal toxicity and completeness of 

data with respect to exposure and toxicity to infants and children.” 

Section 408 (b)(2)(C) further states that “the Administrator may use a 

different margin of safety for the pesticide chemical residue only if, on the 

basis of reliable data, such margin will be safe for infants and children.” 

The following discussion synthesizes information discussed in previous 

sections of this characterization and information from the hazard, food, 

water, and residential chapters of the NMC CRA to inform FQPA 10X 

factor for infants and children. Overall, the Agency believes that there 

are quality data and scientifically supportable methods to account for 

specific exposure and behavioral patterns of children. Because 

characteristics of children are directly accounted for in the exposure 

assessment and the Agency’s methods are not expected to 

underestimate exposure to NMCs, evaluating the potential for increased 

toxicity to juveniles is the key component in determining the magnitude of 

the FQPA factors in the CRA. 

The previous sections of this risk characterization describe the data 

sources and models used to generate the food, drinking water, and 

residential exposure assessments. Overall, there is a high degree of 

confidence in the exposure data and methodologies used when 

assessing cumulative risk to children from food, drinking water and 

Section I.G – Page 220 of 277 
residential exposure. The cumulative exposure assessments are 

considered to be protective of children and do not understate risk. As 

such, the Agency has focused its evaluation of the FQPA 10X safety 

factor on post-natal exposure to juvenile rats. 

Comparative cholinesterase studies with post-natal exposures have 

been shown to provide more sensitive results than DNT studies or from 

studies using in utero only exposures. Thus, comparative cholinesterase 

studies have been identified for use in the cumulative risk assessment as 

the most appropriate studies for developing the chemical-specific factor 

to address the potential susceptibility of infants and children to the 

effects of NMC exposure. Data from comparative cholinesterase studies 

have been used to refine the FQPA safety factor for aldicarb, carbaryl, 

carbofuran, formetanate, methomyl, and oxamyl. For those NMCs 

(methiocarb, pirimicarb, propoxur, thiodicarb) without such data, the 

FQPA 10X safety factor is retained. The Agency believes that the 

refined FQPA factors are protective of infants and children in that high 

quality data from sensitive populations were used. Moreover, the 

methods used to perform dose-response have been peer-reviewed 

multiple times. These methods provide a quality statistical fit to the 

toxicity data in juvenile and adults. 

7. Physiologically-Based Pharmacokinetic Models 

PBPK models, which describe the time course disposition of 

chemicals and their metabolites, could help assess cumulative risk and 

to evaluate the relationship between variable environmental exposures 

and dynamic biological processes. Appropriate PBPK models could 

quantify the cumulative toxicity that can result from multiple exposures 

(multiple chemicals and multiple pathways) and from exposure to 

multiple chemicals with a common mechanism or mode of action. While 

these models are excellent tools, numerous input parameters are 

necessary for each chemical. Organ-specific thermodynamic 

parameters (such as tissue to blood equilibrium partition coefficients) are 

required for each pesticide entering the body and for each of its 

metabolites. Additionally, values for all of the metabolic rates governing 

all the biotransformation steps for each pesticide would be necessary as 

would information on cholinesterase inhibition and potential mixture 

effects. 

Exploratory PBPK models have been developed for some NMCs. 

Appendix II.B.6 includes a description and results from EPA’s work on 

such a model for carbaryl. Because PBPK modeling techniques offer 

good promise, continued development and testing of the models is 

necessary and should be pursued despite the current limitations with 

respect to the amount of input information required. Pharmacokinetic 

Section I.G – Page 221 of 277 
studies (in vivo and in vitro experiments to determine key values for 

pharmacokinetic parameters and the time course disposition of the 

compounds in the body) need to be performed with many compounds to 

determine the key parameters of use in PBPK modeling. It is anticipated 

that data and methods will continue to improve and evolve as more 

experience is gained in this area. Although a biological or 

pharmacokinetic modeling approach would provide another means to 

determine the cumulative risk for these NMCs, the input parameters for 

such an approach are not available. Therefore, OPP has applied simple 

dose addition and used an empirical curve fitting model (i.e., the 

exponential model) to determine RPFs and PoDs. 

8. Conclusions 

With the passage of the FQPA (1996), the Agency is required to 

consider the cumulative risk of pesticides that share a common 

mechanism of action. The Agency designated the NMCs as a common 

mechanism group in 2001 and published its preliminary CRA in 2005. 

Since that time, the Agency has incorporated new hazard and exposure 

data, assigned uncertainty and safety factors, evaluated comments from 

the public, addressed comments by the SAP, and made appropriate 

adjustments due to risk mitigation actions. The NMC CRA is a highly 

complex, highly refined risk assessment that uses data from multiple 

sources and multiple models. Because of this complexity, no single 

value in the assessment should be used to independently arrive at the 

interpretation of the results. Instead, it is necessary to consider the 

results as a whole in order to appropriately interpret the results and 

arrive at conclusions. 

This NMC CRA assessment reflects the completed risk mitigation 

measures that have been proposed or completed as a result of the single 

chemical assessments as of September, 2007. Since the publication of 

the preliminary CRA in 2005, many uses of NMCs have been voluntarily 

cancelled, have had voluntary cancellation requests submitted or have 

been determined to be ineligible for re-registration. Specifically, the 

registrations of methomyl on strawberries is undergoing voluntary 

cancellation, and the registrant has requested that methomyl use on 

grapes be cancelled. In addition, carbofuran was determined to be 

ineligible for reregistration and EPA has initiated the process to cancel all 

domestic uses and to revoke most tolerances; this cancellation impacts 

risk to the food and drinking water pathway. Residential indoor spray 

uses of propoxur that may result in non-occupational exposure for 

children have been voluntarily cancelled. The registrant of aldicarb has 

agreed to an increase in the well setback distance from 300 feet to 500 

feet for aldicarb use on peanuts in the southern portion of the Coastal 

Plain. Each of these risk mitigation measures provides substantive 

Section I.G – Page 222 of 277 
reductions in the exposure to NMCs and improvements to the cumulative 

risk estimates. 

Consistent with the mode of action of NMCs, the revised NMC CRA 

focuses on acute, single day exposures. It presents the estimates of 

cumulative risks associated with exposures to NMCs in food, drinking 

water and from residential uses. Contributions from various pathways 

and routes of exposure are arrayed separately in a set of temporal or 

time-series plots of MOEs over a period of 365 days so that the reader 

can assess and evaluate -- on a pathway and/or route- specific basis -- 

the significant contributors to risk. This practice permits expression of 

the full range of values for each parameter and facilitates interpretation 

of the complete risk picture. OPP is confident that the results reasonably 

represent exposures and risks from food, water, and residential use to 

the U.S. population. 

The food component of the NMC cumulative risk assessment is 

based primarily upon two extensive, reliable data sets: 1) USDA's CSFII 

1994-96/98 and 2) USDA's PDP. The CSFII provides a detailed 

representation of the food consumption patterns of the U.S. public across 

all age groups, during all times of the year, and across the US. The PDP 

data provide a consistent and reliable sample of pesticide residues in the 

major children's foods, including fruits, vegetables, dairy products, 

meats, and grains. The data from PDP are collected so as to closely 

reflect residues in foods, as consumed and are statistically 

representative of the U.S. food supply. The PDP program utilizes multiresidue analytical methods such that co-occurrence of pesticides in 

individual samples is captured. These two sources of data provide a firm 

foundation upon which to assemble other data to develop the NMC 

cumulative risk assessment. Oxamyl serves as the index chemical and 

the residue values for the other NMC pesticides were converted to 

oxamyl equivalents using the RPF approach. After adjustment for 

processing, these index equivalent residues were then compiled as 

distributions of cumulative residues by summing them on a sample-bysample basis. These cumulative residue distributions were combined 

with distributions of daily food consumption values via a probabilistic 

procedure to produce a distribution of potential exposures for the general 

U.S. population and sub-populations using the DEEM-FCID software. 

The primary advantage of using distributions of pesticide concentrations 

and consumption values to assess cumulative exposure is that 

distributions of exposure values are obtained that represent a distribution 

of realistic scenarios of exposure that describe both probabilities and 

magnitudes of multi-chemical cumulative exposure through the food 

pathway. 

Section I.G – Page 223 of 277 
The drinking water assessment focuses on areas where combined 

NMC exposure is likely to be among the highest within each region as a 

result of total NMC usage and vulnerability of drinking water sources. 

This analysis is based on a probabilistic modeling approach that 

considers the full range of data and not a single high-end estimate. EPA 

estimated NMC exposures in drinking water to individuals in the CRA for 

both ground water and surface water sources of drinking water by region. 

The regional drinking water exposure assessments represent exposures 

from vulnerable drinking water sources resulting from typical NMC usage 

and reflect seasonal variations as well as regional variations in cropping 

and NMC use. For the majority of the U.S., NMC residues in drinking 

water sources are at levels that are not likely to contribute substantially 

to the multi-pathway cumulative exposure. Estimated NMC exposures 

from surface water sources of drinking water resulted in MOEs well in 

excess of 10. For most ground water sources of drinking water, NMC 

exposures are expected to be similarly low. Private wells extending 

through highly permeable soils and drawing from shallow depths in 

acidic, unconfined aquifers (also known as water table aquifers) 

represent what the Agency believes to be the most vulnerable drinking 

water sources for the NMCs based on available monitoring, current use 

patterns, and known soil and hydrologic conditions. Those instances 

where NMC concentrations resulted in MOEs of less than 10 are being 

addressed with mitigation measures in the single chemical assessments 

– an increase in the well setback distance from 300 feet to 500 feet for 

aldicarb use on peanuts in the southern portion of the Coastal Plain and 

notice of intent to cancel all domestic carbofuran uses. With these 

mitigation measures, NMC exposures from drinking water result in MOEs 

that are greater than 10. 

There are three NMC chemicals with currently registered residential 

uses considered as part of the revised NMC CRA in the residential/nonoccupational exposure pathway assessment. The residential uses 

considered in this assessment include the carbaryl lawn and golf course 

uses, the carbaryl vegetable and ornamental garden use, the methiocarb 

snail bait use, the carbaryl fruit tree use, and the carbaryl and propoxur 

pet collar uses. Several reliable data sources were used to define how 

pesticides are used, how quickly the residues dissipate, how people may 

come into contact with pesticides (e.g., via dermal or inhalation 

exposure), and the length of time people might be exposed based on 

certain activities (e.g., playing on a treated lawn). As with the drinking 

water assessment, the residential exposure assessment considers 

seasonal applications and timing as well as regional differences. In the 

case of regional differences, the revised NMC CRA focused on the 

Southeast Region of the United States for two reasons; 1) the growing 

season is longer in the South and the associated pest pressures are 

therefore greater, and 2) drinking water concentrations are highest in this 

Section I.G – Page 224 of 277 
region of the country. The residential and groundwater assessments are 

based on the most highly exposed localized areas within the 

southeastern region of the United States. Specifically, the drinking water 

exposure for Georgia was combined with residential exposure in Florida. 

Pest pressure data for Florida are assumed to address pest pressure for 

other areas of the country where estimated NMC water concentrations 

are the highest (such as Georgia and North Carolina). Due to longer 

periods of pesticide use coupled with higher concentrations of NMCs in 

ground water, this assessment provides a reasonable worst case 

estimate of exposure. The results of the residential risk assessment 

indicate that remaining uses of NMCs in a residential setting– as borne 

out by the analyses here -- are below OPP’s level of concern for all 

subpopulations. 

EPA also evaluated total (combined) MOEs for all three pathways 

(e.g., multi-pathway, which is the sum of food + water + residential) 

simultaneously. The multi-pathway MOEs at the 99.9th percentile are 

approximately 8 and 9 for children 1-2 and children 3-5 years of age, 

respectively, for the single day results from Calendex. At the 99.9th 

percentile of exposure, the food pathway is the most significant 

contributor. These multi-pathway results are consistent with – and 

essentially dominated by -- the food results found in Table I.G-5. 

Because the exposure through food is the dominant exposure pathway 

for the revised NMC CRA, the total MOEs derived from the multipathway assessment are virtually identical to the MOEs from exposure 

through the food pathway. 

The sensitivity analyses shown and discussed here are designed to 

evaluate the degree to which key areas of the risk assessment may or 

may not under- or over-estimate the cumulative risk in an effort to 

characterize and understand the MOEs estimated in this assessment. 

When developing any risk assessment, assumptions must be made in 

areas where data are not available; this is the also case for the NMCs. 

In the revised NMC CRA, the Agency has made health protective 

assumptions in its baseline analysis, particularly with regard to the years 

of PDP data which are used (for which it used all years of PDP data 

except in cases where use patterns have been proposed or changed) 

and the use of inter-species extrapolation factors for those NMCs without 

human data. The sensitivity analyses shown here demonstrate that the 

Agency has not under-estimated exposures and associated risks since 

many of the modified scenarios result in only small changes in the 

percentile at which an MOE of 10 is reached.22 

22 More specifically, the complex nature of this CRA has been stressed, and the many, varied 

data sources used to develop quantitative estimates of exposure have been described. Although 

there is a high level of confidence in this assessment, it is important to recognize the limits on the 

precision of the estimates generated by the assessment. For example, although the percentiles 

Section I.G – Page 225 of 277 
The Agency has developed a highly refined and complex 

cumulative risk assessment for the NMCs that represents the state of the 

science regarding existing hazard and exposure data and the models 

and approaches used. The Agency notes that the risk mitigation efforts 

of the past several years have significantly reduced risk from NMCs in 

the food, drinking water and from residential use in the US. Taking into 

account these reductions and acknowledging that several key 

assumptions are designed to minimize the potential to underestimate 

exposure and risk, the Agency concludes that, based on the results of 

the revised NMC CRA, there is a reasonable certainty that no harm will 

result from exposure to the NMC pesticides covered by this assessment, 

taking into account the cumulative effects of such residues. Accordingly, 

the pesticide tolerances for the NMCs covered by this risk assessment 

are considered to be “safe” as defined in FFDCA section 408(b)(2)(A), 

and to be reassessed for purposes of FFDCA section 408(g). 

have been reported out to 5 significant figures (e.g., 99.854), the Agency does not believe that the 

assessment has the power to discriminate between different tenths or hundredths of percentiles of 

exposure. Put another way, there is no meaningful difference between the exposure received by 

the 99.9th and the 99.8th percentile of a subgroup, much less between the 99.85th and 99.86th 

percentiles. The magnitude of actual exposure experienced by a particular percentage of the 

population is likely to be close to, but somewhat below, EPA's estimate for that percentile. Actual 

exposure for, say, the 99.9th percentile may fall within the values estimated for the 99.85th and 

the 99.95th percentiles. But EPA does not believe that the assessment reliably predicts the 

precise difference in exposure levels for people falling at different points on the distribution when 

the points are separated by no more than 0.1% difference. Therefore, for risk management 

purposes, it is also appropriate to considere the percentile at which the estimated MOE for a 

subgroup reaches 10. If that percentile is not meaningfully different from the 99.9th percentile, as 

is the case here, it can be regarded as an additional consideration to support the conclusion that 

there is reasonable certainty no harm will result from cumulative exposure to NMCs. 

Section I.G – Page 226 of 277 
H. References 

“1992 Golf Course Operations: Cost of Doing Business/Profitability.” The Center 

for Golf Course Management. Library of Congress GV975. G56 1992. 

Anderson, S. 2002. The Toxicokinetics of Peripheral Cholinesterase Inhibition 

from Orally Administered Carbofuran in Adult Male and Female CD Rats: Final 

Report: Lab Project Number: 65C-08124: A2001-5379: ATM-0405. Unpublished 

study prepared by Toxicokinetics Laboratory, Center for Life Sciences and 

Toxicology, RTI. 192 p. MRID 45675701. 

Austin, E. 2002. 4 week repeated-dose dermal toxicity study with carbaryl 

technical in rats: Final report: Lab project number: COVANCE 6224-268. 

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Section I.H – Page 247 of 277 
II. Appendices 

A. Summary of Risk Mitigation for Individual N-Methyl Carbamates23 

Decision Document Use Site Mitigation Residential U

ALDICARB 

Alfalfa grown for seed Cancelled Coffee Cancelled Ornamentals Cancelled Pecans Cancelled Sorghum Cancelled Sugarcane Cancelled Tobacco Cancelled Cotton Soybean Rate Reductions Dry Beans Soybean Sugar Beet Sweet Potato Geographic Use Restrictions 

09/2007 RED 

Peanuts 

500 foot well setback and 

application restrictions 

23 This summary only captures those mitigation measures likely to impact the cumulative risk assessment. 

specific mitigation measures intended to protect workers (e.g., REIs, PPE) or to address ecological risks (e.g., spbuffer zones for non-target plants). 

Section II.A.1 - Page 248 of 277 
Decision Document Use Site Mitigation Residential U

CARBARYL 

06/2003 IRED 

Wheat Cancelled - tolerance retained 

Liquid lawn uspot treatmepackaged in use (RTU) hoFor garden/oproducts usevegetables/oend-use prodpackaged in containers wai/container. Granular profor lawncare spreader); fogranular prodRTU contain

Broadcast applications of liquid formulations to turf EXCEPT sod farms, golf courses, commercial landscape areas and cemeteries 

Cancelled 

Applications by hand, spoon, and belly grinder Cancelled Pet uses EXCEPT pet collars Cancelled Corn 

Granular and Bait Formulations 

Prohibited 

Grain sorghum Alfalfa Rice Sunflowers Asparagus 

Rate Reductions Citrus Field Corn 

Stone Fruit 

Section II.A.1 - Page 249 of 277 
Decision Document Use Site Mitigation Residential U

CARBOFURAN 

08/2006 IRED 

Alfalfa 

Not eligible for reregistration - 

Import tolerances retained for 

banana, coffee, sugarcane and rice 

Artichoke Banana Barley Coffee Corn Cotton Curcubits Grapes Oats Pepper Plantain Potato Sorghum Soybean Sugar Beet Sugarcane Sunflower Wheat Spinach for seed 

Cancelled with a 4 year phase out 

Chili Peppers Sunflowers Artichoke 

Cucurbits- granular formulation 

Section II.A.1 - Page 250 of 277 
Decision Document Use Site Mitigation Residentia

FORMETANATE HYDROCHLORIDE 

03/2006 IRED 

Plums Cancelled Prunes Cancelled Pome Fruit Stone Fruit Application Restrictions Citrus 

Orchard crops- aerial application Prohibited 

METHIOCARB 

03/1994 RED 

All food uses Cancelled Ornamental 

vines, hou

Granular formula outdo

Package size restrictions 

METHOMYL 

12/1998 RED 

Grapes* Cancelled in 2007 Strawberries** Broccoli 

Reduction in Max. Seasonal Rates 

Cabbage Cauliflower Celery Chinese Cabbage Corn, Sweet Lettuce, Head Tomato Peaches Reduced Max. Single Application 

Commercial sod farms Rate

OXAMYL 

12/2000 IRED 

Seed piece dip (yams) 

Cancelled 

Soybean Soil broadcast treatment for cotton 

All Crops Rate Reductions 

PIRIMICARB- No Mitigation Necessary 

PROPOXUR 

Section II.A.1 - Page 251 of 277 
Decision Document Use Site Mitigation Residentia

09/1997 RED 

Indoor Residential Uses for Crack and Crevice Treatments*** 

Cancelled in 2007 

Indo

tape/strip/p

sh

Outdoor u

perimeter a

treatments 

ant hill, ins

boat m

THIODICARB 

12/1998 RED Cole crops Reduced Single and Seasonal Application Rates 

* Voluntary cancellation request received September 14, 2007. ** FR Notice announcing receipt of voluntary cancellation published on April 25, 2007 with a 180 day comment period whi*** Use deletion finalized on September 10, 2007. 

Section II.A.1 - Page 252 of 277 
Section II.A.1 - Page 253 of 277 
B. Hazard 

1. Data Spreadsheets of the NMC Pesticides 

A CD contatining the data in this appendix may be obtained by contacting the 

Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

One Potomac Yard 

12777 S. Crystal Drive 

Room S-4400 

Arlington, Virginia. 22202 

703-305-5805 

Monday through Friday, 8:30 am – 4:00 pm 

II.B.1 - Page 254 of 277 
2. Dose-Response modeling of the NMC pesticides 

A CD contatining the data in this appendix may be obtained by contacting the 

Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

One Potomac Yard 

12777 S. Crystal Drive 

Room S-4400 

Arlington, Virginia. 22202 

703-305-5805 

Monday through Friday, 8:30 am – 4:00 pm 

II.B.2 - Page 255 of 277 
3. N-M-Carbamate Dose Response 

A CD contatining the data in this appendix may be obtained by contacting the 

Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

One Potomac Yard 

12777 S. Crystal Drive 

Room S-4400 

Arlington, Virginia. 22202 

703-305-5805 

Monday through Friday, 8:30 am – 4:00 pm 

II.B.3 - Page 256 of 277 
4. R-packages with file names 

A CD contatining the data in this appendix may be obtained by contacting the 

Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

One Potomac Yard 

12777 S. Crystal Drive 

Room S-4400 

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Monday through Friday, 8:30 am – 4:00 pm 

II.B.4 - Page 257 of 277 
5. Summary AChE protocol evaluations, mixture 

experiments, motor activity measurements 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

One Potomac Yard 

12777 S. Crystal Drive 

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Monday through Friday, 8:30 am – 4:00 pm 

Section II.B.5 - Page 258 of 277 
6. Physiologically-Based Pharmacokinetic Modeling for the 

NMC CRA 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

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Room S-4400 

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Monday through Friday, 8:30 am – 4:00 pm 

Section II.B.6 - Page 259 of 277 
C. Food 

1. The Sources of Residue Inputs for the Assessment of the 

Cumulative Dietary Exposure to N-Methyl Carbmate 

Pesticides on Foods 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

One Potomac Yard 

12777 S. Crystal Drive 

Room S-4400 

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Monday through Friday, 8:30 am – 4:00 pm 

Section II.C.1 - Page 260 of 277 
2. Summary of PDP Residue Analyses of N-Methyl Carbamate 

Pesticides on Food Commodities Included in Revised NMC 

CRA 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

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Monday through Friday, 8:30 am – 4:00 pm 

Section II.C.2 - Page 261 of 277 
3. Processing Factors Used to Estimate Residues of N-Methyl 

Carbamate Pesticides in Food Forms* 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

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Monday through Friday, 8:30 am – 4:00 pm 

Section II.C.3 - Page 262 of 277 
4. Translation of Residue Source Data to FCID Food Forms 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

One Potomac Yard 

12777 S. Crystal Drive 

Room S-4400 

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Monday through Friday, 8:30 am – 4:00 pm 

Section II.C.4 - Page 263 of 277 
5. Summary of Residue Distribution Inputs to DEEM-FCID for 

the Revised NMC CRA 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

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Monday through Friday, 8:30 am – 4:00 pm 

Section II.C.5 - Page 264 of 277 
6. Analysis of Chemicals and Foods in the Upper Portion of 

the Revised NMC CRA. Exposure Distribution for Children 

1-2 Years Old 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

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Monday through Friday, 8:30 am – 4:00 pm 

Section II.C.6 - Page 265 of 277 
7. Co-Occurrence of N-Methyl Carbamate Pesticides on PDP 

Samples, 1994-2006 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

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Monday through Friday, 8:30 am – 4:00 pm 

Section II.C.7 - Page 266 of 277 
8. Comparison of DEEM-FCID version 2.03 and Lifeline version 

4.30 Exposure and Risk Estimates through the Food 

Pathway Only

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

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12777 S. Crystal Drive 

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Monday through Friday, 8:30 am – 4:00 pm 

Section II.C.8 - Page 267 of 277 
D. Residential 

1. Residential Pesticide Use Inputs from REJV Survey Data 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

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Monday through Friday, 8:30 am – 4:00 pm

Section II.D.1 - Page 268 of 277 
2. Residential Exposure Scenarios Appendix 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

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Section II.D.2 - Page 269 of 277 
E. Drinking Water 

1. Summary of Surface Water Monitoring Data for NMC 

Pesticides 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

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703-305-5805 

Monday through Friday, 8:30 am – 4:00 pm 

Section II.E.1 - Page 270 of 277 
E-2 Summary of Ground Water Monitoring Data for NMC 

Pesticides 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

One Potomac Yard 

12777 S. Crystal Drive 

Room S-4400 

Arlington, Virginia. 22202 

703-305-5805 

Monday through Friday, 8:30 am – 4:00 pm 

Section II.E.2 - Page 271 of 277 
E-3 Drinking Water Treatment Effects on N-methyl 

Carbamate Pesticides 

A CD contatining the data in this appendix may be obtained by contacting the 

Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

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Monday through Friday, 8:30 am – 4:00 pm 

II.E.3 - Page 272 of 277 
E-4 N-methyl Carbamate Usage Estimates 

T 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

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II.E.4 - Page 273 of 277 
E-5 Chemical-Specific Fate and Transport Properties 

Used For the Water Exposure Models 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

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Page 274 of 277 
E-6 NMC Surface Water Exposure Assessment 

Methods 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

One Potomac Yard 

12777 S. Crystal Drive 

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Monday through Friday, 8:30 am – 4:00 pm 

II.E.6 - Page 275 of 277 
E-7 NMC Ground Water Exposure Assessment Methods 

A CD contatining the data in this appendix may be obtained by contacting 

the Office of Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

One Potomac Yard 

12777 S. Crystal Drive 

Room S-4400 

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703-305-5805 

Monday through Friday, 8:30 am – 4:00 pm 

II.E.7 - Page 276 of 277 
III.Multi-Pathway Graphs 

A CD contatining the data in this section may be obtained by contacting the Office of 

Pesticide Programs Public Docket 

Docket # EPA-HQ-OPP-2007-0935 

One Potomac Yard 

12777 S. Crystal Drive 

Room S-4400 

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703-305-5805 

Monday through Friday, 8:30 am – 4:00 pm 

III - Page 277 of 277