Important Exposure Factors 

for Children

An Analysis of Laboratory and 

Observational Field Data Characterizing 

Cumulative Exposure to Pesticides 

R E S E A R C H A N D D E V E L O P M E N T

EPA 600/R-07/013 

March 2007 

Important Exposure Factors 

for Children 

An Analysis of Laboratory and Observational 

Field Data Characterizing Cumulative 

Exposure to Pesticides 

By 

Peter P. Egeghy1

, Linda S. Sheldon1, Roy C. Fortmann1, Daniel M. Stout II1, Nicolle S. Tulve1, Elaine Cohen 

Hubal2

, Lisa J. Melnyk3, Marsha Morgan1, Paul A. Jones1, Donald A. Whitaker1, Carry W. Croghan1, April Coan1

1

US EPA, Office of Research and Development, National Exposure Research Laboratory, Human Exposure and 

Atmospheric Sciences Division, Research Triangle Park, NC 27711 2

US EPA, Office of Research and Development, National Center for Computational Toxicology, Research 

Triangle Park, NC 27711 3

US EPA, Office of Research and Development, National Exposure Research Laboratory, Microbiological and 

Chemical Exposure Assessment Research Division, Cincinnati, OH 45268 

National Exposure Research Laboratory 

Office of Research and Development 

U.S. Environmental Protection Agency 

Research Triangle Park, NC, 27711 
Notice 

The U.S. Environmental Protection Agency, through its Office of Research and Development, funded and 

managed or partially funded and collaborated in the research described in this report. It has been subjected to the 

Agency’s peer and administrative review and has been approved for publication as an EPA document. Mention of 

trade names or commercial products does not constitute endorsement or recommendation for use. 

ii
Abstract 

In an effort to facilitate more realistic risk assessments that take into account unique childhood 

vulnerabilities to environmental toxicants, the U.S. EPA’s National Exposure Research 

Laboratory (NERL) developed a framework for systematically identifying and addressing the 

most important sources, routes, and pathways of children’s exposure to pesticides. Four priority 

research areas were identified as representing critical data gaps in our understanding of 

environmental risks to children. Several targeted studies were conducted under NERL’s 

children’s exposure research program to specifically address these priority research needs. This 

document is a comprehensive summary report of data collected in these studies to address the 

priority research needs and is intended for an audience of exposure scientists, exposure modelers, 

and risk assessors. The parameters measured and the measurement methods are described. Data 

on representative organophosphate and pyrethroid pesticides are compared across studies and 

across compounds with the primary purpose of identifying or evaluating important factors 

influencing exposures along each relevant pathway. Summary statistics, comparative analyses, 

and spatial and temporal patterns are presented to address previously identified data gaps. 

Results are compared across studies in order to identify trends that might provide a better 

understanding of the factors affecting children’s exposures. While highlights of the results of 

individual studies are presented, the focus is on presenting insights gleaned from the analysis of 

the aggregated data from several studies. By examining relationships among application 

patterns, exposures, and biomarkers for multiple compounds from different classes of pesticides, 

this report strives to help produce more reliable approaches for assessing cumulative exposure. 

iii
iv
Executive Summary 

In an effort to facilitate more realistic risk assessments that take into account unique childhood 

vulnerabilities to environmental toxicants, the National Exposure Research Laboratory (NERL) 

in the U.S. Environmental Protection Agency’s (U.S. EPA) Office of Research and Development 

(ORD) developed a framework for systematically identifying and addressing the most important 

sources, routes, and pathways of children’s exposure to pesticides (Cohen Hubal et al., 2000a, 

2000b). Using this framework, a screening-level assessment was performed to identify the 

exposure pathways with the greatest potential exposures. The uncertainty associated with 

assessing exposure along each pathway was then evaluated through an exhaustive review of 

available data. Four priority research areas were identified as representing critical data gaps in 

our understanding of environmental risks to children. The absence of sufficient real-world data 

in all four of these areas produces an excessive reliance on default assumptions when assessing 

exposure. These priority research areas are: 1) pesticide use patterns; 2) spatial and temporal 

distributions of residues in residential dwellings; 3) dermal absorption and indirect (non-dietary) 

ingestion; and 4) dietary ingestion. 

Several targeted studies were conducted or financially supported by NERL under the children’s 

exposure research program to specifically address these priority research needs. These studies 

included: 

• Children’s Total Exposure to Persistent Pesticides and Other Persistent Organic 

Pollutants (“CTEPP”) 

• First National Environmental Health Survey of Child Care Centers (“CCC”) 

• Biological and Environmental Monitoring for Organophosphate and Pyrethroid Pesticide 

Exposures in Children Living in Jacksonville, Florida (“JAX”) 

• Center for the Health Assessment of Mothers and Children of Salinas Quantitative 

Exposure Assessment Study (“CHAMACOS”) 

• Children’s Pesticide Post-Application Exposure Study (“CPPAES”) 

• Distribution of Chlorpyrifos Following a Crack and Crevice Type Application in the US 

EPA Indoor Air Quality Test Research House (“Test House”) 

• Pilot Study Examining Translocation Pathways Following a Granular Application of 

Diazinon to Residential Lawns (“PET”) 

• Dietary Intake of Young Children (“DIYC”) 

• Characterizing Pesticide Residue Transfer Efficiencies (“Transfer”) 

• Food Transfer Studies (“Food”) 

• Feasibility of Macroactivity Approach to Assess Dermal Exposure (“Daycare”) 

Two studies performed prior to the identification of priority research areas also provided useful 

data. These were: 

v
• National Human Exposure Assessment Survey in Arizona (NHEXAS-AZ) 

• Minnesota Children’s Pesticide Exposure Study (“MNCPES”) 

All studies involving children were observational research studies, as defined in 40 CFR Part 

26.402. All study protocols and procedures to obtain the assent of the children and informed 

consent of their parents or guardians were reviewed and approved by an independent institutional 

review board (IRB) and complied with all applicable requirements of the Common Rule 

regarding additional protections for children. Further, all protocols regarding recruitment and 

treatment of participants were reviewed by the EPA Human Subjects Research Review Official 

(HSRRO) to assure compliance with the Federal Policy for the Protection of Human Subjects. 

The studies took place in EPA research laboratories, in the EPA Indoor Air Quality Research 

Test House, in private residences, and in child care centers. The studies have been grouped as 

a) large observational field studies (NHEXAS-AZ, MNCPES, CTEPP, and CCC), b) small pilotscale observational studies (JAX, CPPAES, DIYC, CHAMACOS, and Daycare), and 

c) laboratory studies (Test House, Transfer, and Food). The large observational field studies had 

either a regional (NHEXAS-AZ, MNCPES, CTEPP) or national (CCC) focus. A broad suite of 

chemical contaminants, including organophosphate and pyrethroid pesticides and their metabolites, were typically measured in multiple environmental media and in urine. Some of the small 

pilot-scale studies included measurements of multiple chemicals in multiple media in locations 

either with year-round residential pesticide use (JAX) or in close proximity to agricultural fields 

(CHAMACOS). Other pilot-scale studies focused on a single compound (CPPAES, DIYC, PET, 

Daycare). The laboratory studies (Transfer, Food, Test House) evaluated factors affecting 

transfer from surfaces or investigated post-application spatial and temporal variability. One of 

the primary objectives for all of these studies was to determine and quantify the key factors that 

influence exposure along the pathways relevant to the four priority research areas. 

This document is a comprehensive summary report of data collected under the NERL children's 

exposure research program and is intended for an audience of exposure scientists, exposure 

modelers, and risk assessors. The parameters measured and the measurement methods are 

described. Data on representative organophosphate and pyrethroid pesticides are compared 

across studies and across compounds with the primary purpose of identifying or evaluating 

important factors influencing exposures along each relevant pathway. Summary statistics, 

comparative analyses, and spatial and temporal patterns are presented to address previously 

identified data gaps. Results are compared across studies in order to identify trends that might 

provide a better understanding of the factors affecting children’s exposures. While highlights of 

the results of individual studies are presented, the focus is on presenting insights gleaned from 

the analysis of the aggregated data from several studies. By examining relationships among 

application patterns, exposures, and biomarkers for multiple compounds from different classes of 

pesticides, this report strives to help produce more reliable approaches for assessing cumulative 

exposure. 

With limited data available to EPA researchers on the types, locations, and frequency of 

pesticide usage in residential and other non-occupational environments, pesticide use patterns 

were identified as a priority research area. Accordingly, pesticide use information was collected 

by inventory and questionnaire in each of the field studies. Questionnaire items and inventory 

vi
forms differed, geographic regions represented were limited, and the total number of study 

participants was relatively small. Furthermore, during the period of four years covered (1997 to 

2001), pesticide manufacturers were increasingly replacing organophosphates with pyrethroids in 

their formulations, and restrictions on residential applications of the most commonly used 

organophosphates were approaching. Nevertheless, important usage information was produced 

by the studies. Pyrethrins and their synthetic analogs (pyrethroids), specifically permethrin, 

cypermethrin, and allethrin, are clearly the most frequently used insecticides for indoor applications in homes and child care centers based on inventories and records. Organophosphates 

appear to persist in indoor environments, as chlorpyrifos and diazinon were more frequently 

detected in screening wipes (at frequencies comparable to permethrin) than in inventories. 

Among the carbamates, only propoxur and carbaryl were inventoried or reportedly used. 

“Crack-and-crevice” type applications were used more often than either broadcast or total release 

aerosol (“fogger”) applications. Applications were more likely to be performed by the resident 

than by a professional service in JAX, and also as reported in NHANES. In JAX, the modes of 

application included hand pump sprayer (37%), aerosol can (24%), fogger (3%), and baits (3%), 

but the pertinence of these results to other locations is unknown. Apart from these results, 

information on application type and method was not collected. 

Pesticide products were found in at least 86% of JAX and MNCPES screening households, with 

a mean of three products per household. There is evidence in support of a pattern of higher 

application frequencies in warmer climates, with the percentage of participants reporting use in a 

given time period highest in Florida, lower in North Carolina and Ohio, and lowest in Minnesota. 

The percentage in Jacksonville, FL is substantially higher, and the percentage in Minnesota is 

substantially lower, than the national average reported in NHANES. In childcare centers, 

monthly interior pesticide applications were performed in about a third of the CCC facilities 

nationwide and were anecdotally found to be standard practice among daycares contacted in 

North Carolina. 

There were no statistically significant differences in the total number of products found or 

reportedly used in MNCPES based on either population density (urban vs. non-urban 

households) or other socio-demographic factors including race, ethnicity, home type, income, 

and level of education. Similarly, analysis of CTEPP data found no association between 

application frequency and either population density or income class. 

A second primary research area is spatial and temporal distributions of pesticides in residential 

dwellings. Spatial and temporal heterogeneity may affect exposure estimates along all exposure 

routes. Absorption via the inhalation route relies on the measured airborne concentration. 

Absorption via the dermal and indirect ingestion routes relies on the measured surface loading. 

Even estimates of dietary ingestion for children may depend on surface concentrations due to 

pesticide transfer during food preparation and handling. Examination of distribution patterns of 

airborne and surface residues has yielded important insights. 

The organophosphate insecticides chlorpyrifos and diazinon were most frequently detected in 

both indoor air and outdoor air in these field studies, but the detection frequencies in outdoor air 

were lower and more variable across studies. Chlorpyrifos was frequently detected even after its 

vii
indoor residential use was restricted, perhaps due to emissions from indoor sinks (e.g., carpets) 

and from continued use of existing home inventories. Indoor air concentrations were typically 

an order of magnitude higher than outdoor air concentrations, with notable exceptions of outdoor 

diazinon and permethrin levels which were nearly as high as indoor levels in JAX, and outdoor 

diazinon levels that exceeded indoor levels in the agricultural community monitored in 

CHAMACOS. The low pesticide concentrations routinely measured outdoors (notwithstanding 

the exceptions noted) together with the relatively short time spent outdoors suggests that 

inhalation of outdoor air is not typically an important contributor to aggregate pesticide 

exposure. The similarity across large observational field studies in the variability of the 

observed indoor air chlorpyrifos concentrations, despite sample collection periods ranging from 

1 to 7 days, suggests that air concentrations are reasonably consistent from day-to-day in the 

absence of a recent application. 

The median indoor air concentrations of the organophosphates are higher than that of the 

pyrethroids. While these studies were conducted at a time when organophosphates arguably 

dominated the marketplace, a comparison of the mean levels of various organochlorine, 

organophosphate, and pyrethroid pesticides measured in CTEPP finds that the concentrations 

measured in the absence of recent applications appear to be strongly influenced by vapor 

pressure, with the more volatile pesticides, such as chlorpyrifos, found at the highest levels. 

Consequently, the importance of inhalation as a route of exposure for pesticides is likely to 

decrease as less volatile pesticides, such as the pyrethroids, are introduced into the market. 

Differences in sampling methods, year of the study, and time of year when samples were 

collected make it difficult to distinguish any regional differences in pesticide concentrations. In 

general, median indoor air concentrations were somewhat higher in southern states (NHEXASAZ and CTEPP-NC) than in northern states (MNCPES and CTEPP-OH). However, the 

distributions exhibit considerable overlap across geographical locations. When daycare 

measurements are included, a geographical difference is less obvious, perhaps due to regular, 

calendar-based pesticide treatments at many daycare facilities. 

Irrespective of region, differences in indoor air levels between homes and daycares were not 

found to be statistically significant. Similar mean indoor air levels observed in homes and 

daycares demonstrate the potential for continued exposure as a child spends time in other indoor 

locations. Additional concentration measurements in other locations would be useful to examine 

exposure potential from different settings such as schools, restaurants, and other public and 

private locations where pesticides are also applied. 

Differences in indoor air concentrations associated with population density and income level 

were observed in the field studies. Differences between urban and rural air concentrations were 

observed in both MNCPES and CTEPP. In fact, urban chlorpyrifos levels were about 25% 

higher than rural levels across studies. A reasonable explanation may be that urban areas require 

more intensive use of pesticide products to control a range of pests over a wider seasonal span. 

Concentrations of chlorpyrifos and diazinon were higher in low-income homes than in 

medium/high income homes in CTEPP, but the difference was statistically significant only for 

diazinon, and only in NC. 

viii
Within-home spatial and temporal patterns were investigated following a crack and crevice 

application of chlorpyrifos in the kitchen of the Test House. The pesticide was detected even in 

the farthest bedroom from the application, with a concentration gradient observed from the 

kitchen to the den (proximal area) to the master bedroom (distal area). Temporally, airborne 

concentrations peaked on day 1, then decreased by approximately 80%, but were still 

measurable, at 21 days after application. In contrast, airborne diazinon concentrations among 

homes in the DIYC study were most pronounced 4-5 days after application. Between-home 

spatial variability following a pesticide application was investigated in the CPPAES study. 

Indoor air chlorpyrifos concentrations spanned more than an order of magnitude among the 

homes one day after application. 

Significant progress has also been made in understanding spatial and temporal distributions of 

organophosphate residues on surfaces. In a published analysis of the MNCPES surface wipe 

data, Lioy and colleagues (2000) reported substantial variability in surface chlorpyrifos levels 

among different rooms. Substantial variability among and within rooms is also evident in the 

Daycare data. Furthermore, data from the Test House also show that surface loadings cannot be 

assumed to be homogenous even within a room. These observations suggest that multiple 

locations should be sampled to more accurately represent surface loadings. Exposure modelers 

using probabilistic methods have already begun to account for differences in surface loadings 

based on proximity to application sites in order to reduce possible exposure misclassification in 

their exposure estimates. 

A number of observations suggest that there is substantial translocation of pesticides from 

application surfaces to adjacent surfaces, but levels remain higher at the application location. In 

CPPAES, the post-application chlorpyrifos loadings were higher than the pre-application values 

even on surfaces that did not receive a direct application. In DIYC, the transferable residues on 

the counters were nearly as high as those on the floors immediately after application. In JAX, 

the application area surface residue loadings were generally higher than the play area surface 

residue concentrations. In the CCC, the floor residue loadings were generally higher than the 

desk top loadings. High loadings of diazinon in indoor house dust following the lawn treatment 

in the PET study suggest that transfer into the house may also occur. 

Examination of chlorpyrifos and diazinon loadings following applications indicates that total 

available residue loadings decay at a slower rate than airborne concentrations. Total available 

residue loadings (obtained by methods intended to measure the total amount of contaminant on a 

surface) also appear to decline at a slower rate than transferable residue loadings (intended to 

represent the amount that is transferred as a result of contact with the contaminated surface). In 

fact, using a total available residue method, chlorpyrifos was measured in 62% of the MNCPES 

samples, even in the absence of a recent pesticide application. 

On a regional level, Jacksonville, Florida, an area known for year-round pest control issues and 

identified as having high pesticide usage during the NOPES study (Whitmore et al., 1994), had 

much higher surface concentrations than any of the other studies without recent applications. 

Within a given region, however, there appears to be little relationship between questionnaire 

information and measured surface values. Previously published results from the MNCPES 

indicate that the residential pesticide use questions and overall screening approach used in the 

MNCPES were ineffective for identifying households with higher levels of individual target 

ix
pesticides (Sexton et al., 2003). Results from the CPPAES study suggest that cleaning activities 

and ventilation influence surface concentrations; it appears that the surface chlorpyrifos loadings 

were lower in those homes in which the occupants reported additional cleaning activities and/or 

high ventilation rates. 

While significant progress has been made in understanding spatial distributions of organophosphate and pyrethroid pesticides in the absence of a recent application and in understanding 

spatial and temporal distributions of organophosphate pesticides following an application, no 

data have been produced on the spatial and temporal distributions of pyrethroids following 

applications. The movement of residentially applied insecticides follows a complex and poorly 

understood process of transformation and phase distribution and is influenced by several factors. 

Differences in physicochemical characteristics make it difficult to generalize the spatial and 

temporal distributions of organophosphate pesticides to pyrethroid pesticides, but with 

information on chemical properties and on human activities, distribution patterns can be 

modeled. 

The third primary research area was identified as dermal absorption and indirect ingestion. 

Intake via these exposure routes is often estimated using measurements of pesticide 

concentrations in dust and soil and pesticide loadings on surfaces. Intake estimates also rely on 

numerous default exposure factor assumptions. Pesticides in dust generally had high detection 

frequencies, consistent with dust being considered a repository of contaminants. Detection 

frequencies for soil samples, on the other hand, were generally low (with the exception of 

measurements made immediately following lawn applications). 

Compounds found at relatively higher concentrations in dust tend to be found at relatively lower 

concentrations in air. The less volatile pyrethroid pesticides tend to partition to the dust and may 

degrade more slowly allowing accumulation over time from repeated applications. This 

underscores the importance of dust as a primary residential exposure medium for the less volatile 

pesticides. In addition, the exposure factors that are important for other nonvolatile 

contaminants such as lead may also be important for the less volatile pesticides. 

Pyrethroids generally have low vapor pressures and Henry’s Law constants, thus they are poorly 

volatilized and exist almost entirely in the particulate phase at room temperature. Furthermore, 

high octanol/water (Kow) and water/organic carbon (Koc) partition coefficients cause pyrethroids 

to partition into lipids and into organic matter. With these characteristics, pyrethroids can be 

expected to bind readily to the particulate matter that comprises house dust. Particles 

resuspended by human activity then act as the primary vector for pyrethroid transport and for 

human exposure. Particle-bound movement and transfer of pyrethroids imply a decreased 

importance of the inhalation route and an increased importance of routes that involve dermal 

transfer, such as indirect ingestion and dermal absorption. Exposure of young children, for 

whom indirect ingestion of residues from object- and hand-to-mouth activities is particularly 

important, may be most strongly affected. In fact, algorithm-based estimates of distributions of 

intake of chlorpyrifos and permethrin from the four contributing routes among the CTEPP-OH 

children indicated that the contribution from the indirect route is much more important for 

permethrin than for chlorpyrifos. 

x
Comparisons of pesticide surface loadings (ng/cm2) showed higher levels in the CTEPP daycare 

centers than in the homes. This appears to be the result of higher amounts of dust in the daycare 

centers, as there is not as large of a difference in the pesticide concentrations (ng/g) in the dust. 

Studies with lead have suggested that loading may have a greater impact than concentration on 

actual intake, thus higher amounts of dust may be important even if the concentration within the 

dust is similar. 

Data from our studies show that the collection methods utilized may have sizeable effects on 

estimates of dermal exposure and indirect ingestion. Total residue methods, which use both 

solvent and mechanical action to remove residues that may have penetrated into the surface, 

produce the highest values, followed by dust methods, and then by transferable residue methods. 

These methods are intended to measures different types of transfer, and efficiencies for various 

methods have been previously published. Use of total residue methods allows the assessor to use 

appropriate transfer factors to represent a transfer efficiency applicable to a given scenario. 

Questions remain, however, on exactly how much of what is measured by total residue methods 

is truly available for transfer and how much would otherwise be trapped in the pores and/or body 

material of the surfaces if not for the mechanical and solvent action of the methods. 

Even the amount of solvent used with wipe samples affects the results. The low pesticide 

surface loadings obtained with 2 mL isopropyl alcohol wipes in both the NC and OH CTEPP 

studies (loadings similar to those obtained with the polyurethane foam [PUF] roller) suggest that 

the amount of IPA applied to the wipe may affect the amount of pesticide residue recovered. 

Surface type has also been shown to affect the collection efficiency of wipes. Recently 

published NERL data (Rohrer et al., 2003) found that with respect to pesticide transfer, wiping 

from hard surfaces greatly exceeded carpet, and wiping from tile generally exceeded hardwood. 

Clearly, some standardization of surface sampling methods is needed. 

Although successfully used in laboratory studies, the Modified C18 Surface Press Sampler was 

rarely able to measure pesticide residues in field studies. The original press sampler was 

designed to measure transfer of dust-bound pesticides to the skin from a single hand press onto a 

carpeted surface. The uses for the modified C18 surface press sampler have expanded to include 

hard surfaces and longer contact times, effectively using the press sampler in a manner for which 

it was not intended. Our data suggest that the sensitivity of the modified C18 surface press 

sampler may be too low to measure residential pesticide residues (which may transfer by both 

equilibrium mass transfer and mechanical transfer). 

Laboratory studies using fluorescent tracers (as surrogates for pesticide residues) indicated that 

tracer type, surface type, contact motion, and skin condition were all significant factors. 

Transfer was greater with laminate (over carpet), smudge (over press), and sticky skin (over 

moist or dry). Contact duration and pressure (force) were not found to be important factors. 

The effect of surface type appeared to diminish with repeated contact, while the effect of skin 

condition (moist vs. dry) appeared to increase with repeated contact. Additional studies are still 

needed to gain a better understanding of the key factors that influence the dermal transfer and 

indirect ingestion of pesticides. 

xi
The frequencies of hand- and object-to-mouth contacts were quantified for preschool children in 

the CTEPP and CPPEAS studies using the Virtual Timing Device (VTD) software (Zartarian et 

al.. 1997). The CPPAES results support the use of the commonly assumed median count of 9.5 

hand-to-mouth contacts per hour; however CTEPP data suggest a much higher value for younger 

children. The CTEPP methodology also accounts for combination hand- and object-to-mouth 

contacts during both eating and non-eating events. 

The fourth primary research area was identified as dietary ingestion. Diet can be an important 

pathway of exposure. Foods may contain residues of pesticides and other environmental 

chemicals because of intentional applications or may become contaminated during processing, 

distribution, storage, and consumption. For certain chemicals, diet is potentially the predominant

pathway of exposure. Children’s dietary exposure to pesticides is not limited to the residues in 

or on foods when they are brought into the home. Children’s unique handling of foods prior to 

consumption requires special attention, but it is rarely considered in study designs. 

Based on route-specific intake estimates, dietary ingestion represented the dominant route of 

exposure for chlorpyrifos, diazinon, and permethrin in the CTEPP study. Unfortunately, the 

route that represented the dominant route of exposure was also the route with the lowest 

detection frequencies (approximately 2/3 of the values for permethrin in CTEPP were 

nondetects), which increases the uncertainty in the estimates. Substituting a fraction of the 

detection limit for values below the limit of detection may have a disproportionate impact on 

assessing the importance of the dietary route. 

The most common measure of dietary exposure was by composited duplicate diet analyses. 

However, great care must be taken to ensure that the duplicate diet accurately reflects what is 

actually consumed instead of what is served because significant quantities of food may remain 

uneaten by children. Duplicate diets fail to capture those pesticide residues transferred to foods 

as a result of the child’s handling of food prior to and during consumption. In DIYC, estimates 

of dietary intake that included excess contamination due to handling were as much as double the 

estimates of intake based on duplicate diet alone. These results suggest that dietary estimates 

based on duplicate diet may not be as reliable for young children as they are for adults. 

Progress has been made in many areas and we are beginning to understand the environment that 

children live in, their activities, and the resulting exposures. However, research is still needed to 

adequately characterize the magnitude, routes and pathways of exposure. We still need to 

understand the key factors that influence the dermal transfer and indirect ingestion of pesticides. 

We need to be able to more accurately assess dietary exposure. In order to evaluate exposure 

models, we must be able to quantify the relationships between and among environmental 

concentrations of pesticides in various media, children’s activities, and the results of biomarkers 

of exposures as measured in urine and/or blood. Exposure models outputs that include the 

timing and route of exposure need to be linked to PBPK models in order to develop accurate 

assessment of target tissue dose. Research, especially model development, needs to extend 

beyond single chemical aggregate exposures and dose to include exposures and risks that 

accumulate across chemicals and over time. 

xii
Table of Contents 

Abstract .......................................................................................................................................iii 

Executive Summary................................................................................................................... v 

Tables......................................................................................................................................... xvi 

Figures ........................................................................................................................................ xx 

Acknowledgments ................................................................................................................xxiii 

Abbreviations and Acronyms............................................................................................ xxiv 

1.0 INTRODUCTION................................................................................................................... 1 

1.1 Background........................................................................................................................... 1 

1.2 Purpose of the Report and Intended Audience ..................................................................... 2 

1.3 Structure of the Report.......................................................................................................... 4 

1.4 Data Treatment...................................................................................................................... 5 

1.5 Description of the Studies and Data Collected ..................................................................... 5 

1.6 Pesticides of Interest to this Report ...................................................................................... 7 

1.7 Summary Descriptions of the Studies................................................................................... 9 

1.8 Exposure and Dose Models ................................................................................................ 12 

2.0 PESTICIDE USE PATTERNS............................................................................................ 13 

2.1 Sources of Information ....................................................................................................... 13 

2.2 Application Frequency........................................................................................................ 17 

2.3 Application Locations......................................................................................................... 19 

2.4 Application Types and Methods ......................................................................................... 20 

2.5 Pesticides Identified in Inventories, Records and Wipe Samples....................................... 20 

2.6 Demographic Factors Influencing Applications ................................................................. 21 

3.0 AIR CONCENTRATION MEASUREMENTS................................................................. 25 

3.1 Introduction and Data Availability ..................................................................................... 25 

3.2 Pesticide Presence............................................................................................................... 25 

3.3 Comparisons of Air Concentrations.................................................................................... 30 

3.4 Differences Related to Location ......................................................................................... 37 

3.5 Spatial and Temporal Variability........................................................................................ 41 

3.6 Factors that Influence Air Concentrations .......................................................................... 41 

3.7 Summary: Air Concentrations ............................................................................................ 43 

4.0 SURFACE MEASUREMENTS .......................................................................................... 47 

4.1 Introduction and Data Availability ..................................................................................... 47 

4.2 Dust and Soil Measurements .............................................................................................. 50 

4.3 Total Available Residue Measurements ............................................................................. 59 

4.4 Transferable Residue Measurements .................................................................................. 66 

4.5 Spatial and Temporal Variability........................................................................................ 73 

4.6 Differences Related to Location ......................................................................................... 77 

4.7 Influential Factors ............................................................................................................... 78 

xiii
4.8 Correlations among Soil, Wipes, and Dust......................................................................... 79 

4.9 Particle-Bound Pyrethroid Residues: Implications toward Exposure................................ 80 

5.0 DIETARY EXPOSURE MEASUREMENTS .................................................................... 81 

5.1 Introduction and Data Availability ..................................................................................... 81 

5.2 Pesticide Presence............................................................................................................... 83 

5.3 Relative Importance of the Ingestion Route ....................................................................... 90 

6.0 INDIRECT INGESTION MEASUREMENTS.................................................................. 93 

6.1 Characterizing Hand- and Object-to-Mouth Activities....................................................... 93 

6.2 Residue Loadings on Mouthed Objects and Removal by Mouthing .................................. 94 

6.3 Transfer of Pesticide Residues to Food .............................................................................. 98 

6.4 Indirect Ingestion of Dust and Soil ................................................................................... 103 

6.5 Indirect Ingestion: Summary............................................................................................. 104

7.0 DERMAL EXPOSURE MEASUREMENTS................................................................... 105 

7.1 Laboratory Fluorescent Measurement Studies.................................................................. 106 

7.2 Measurements of Pesticides on Hands by Wipe and Rinse Methods ............................... 112 

7.3 Measurements with Cotton Garments............................................................................... 123 

8.0 URINARY BIOMARKER MEASUREMENTS.............................................................. 129 

8.1 Toxicokinetics of Organophosphate and Pyrethroid Pesticides........................................ 129 

8.2 Measurements of Pesticide Metabolites in Urine ............................................................. 133 

8.3 Temporal Variability in Biomarker Measurements .......................................................... 141 

8.4 Urine and Creatinine Excretion among Children.............................................................. 144 

8.5 Relative Importance of Exposure Routes ......................................................................... 146 

8.6 Model Predictions ............................................................................................................. 152 

9.0 SUMMARY AND CONCLUSIONS ................................................................................. 153 

10.0 REFERENCES.................................................................................................................. 155 

11.0 BIBLIOGRAPHY............................................................................................................ 162 

APPENDIX A: Summary Statistics ....................................................................................... 165 

Air Concentrations.................................................................................................................. 166 

Dust and Soil Concentrations and Loadings........................................................................... 170 

Total Available Surface Residue Loadings............................................................................. 176 

Transferable Surface Residue Loadings ................................................................................. 179 

Solid Food Concentrations and Intakes .................................................................................. 182 

Hand Loadings........................................................................................................................ 186 

Urinary Metabolite Concentrations......................................................................................... 188 

APPENDIX B: Individual Study Details............................................................................... 189 

National Human Exposure Assessment Survey in Arizona (NHEXAS-AZ) ......................... 190 

Minnesota Children’s Pesticide Exposure Study (MNCPES) ................................................ 191 

Children’s Total Exposure to Persistent Pesticides and Other Persistent Organic Pollutants 

Study (CTEPP)........................................................................................................................ 192 

First National Environmental Health Survey of Child Care Centers (CCC).......................... 193 

Biological and Environmental Monitoring for Organophosphate and Pyrethroid Pesticide 

Exposures in Children Living in Jacksonville, Florida (JAX)................................................ 194 

Center for the Health Assessment of Mothers and Children of Salinas Quantitative Exposure 

Assessment Study (CHAMACOS)......................................................................................... 195 

Children’s Pesticide Post-Application Exposure Study (CPPAES) ....................................... 196 

xiv
The Distribution of Chlorpyrifos Following a Crack and Crevice Type Application in the US 

EPA Indoor Air Quality Research Test House (Test House) ................................................. 197 

A Pilot Study Examining Translocation Pathways Following a Granular Application of 

Diazinon to Residential Lawns (PET) .................................................................................... 198 

Dietary Intake of Young Children (DIYC)............................................................................. 199 

Characterizing Pesticide Residue Transfer Efficiencies (Transfer)........................................ 200 

Feasibility of Macroactivity Approach to Assess Dermal Exposure (Daycare)..................... 201 

Food Transfer Studies, also known as Press Evaluation Studies (Food)................................ 202 

xv
Tables 

Table 1.1 Available media, participant characteristics, and activities by study. ............................ 8 

Table 1.2 Pesticides and metabolites measured in the studies........................................................ 8 

Table 2.1 Pesticides use information collection methods............................................................. 16 

Table 2.2 Proportion (unweighted) of participants reporting pesticide use by study. .................. 18 

Table 2.3 The proportion of CTEPP participants reporting use of four types of pesticides......... 18 

Table 2.4 Pesticides inventoried in 36 households in Jacksonville, FL (JAX) in fall 2001. ........ 22 

Table 2.5 Most commonly applied pyrethroids in 1217 households with complete 12 month 

REJV survey data, as reported by Ozkaynak (2005). ................................................................... 22 

Table 2.6 Number of pesticide products applied during one year (2001) in 168 child care centers 

(CCC), as reported by the center directors and/or professional applicators. ................................ 23 

Table 2.7 Pesticides inventoried and used in 308 households in Minnesota (MNCPES) in 

summer 1997 (adapted from Adgate et al., 2000). ....................................................................... 23 

Table 2.8 Detection frequencies of target analytes in soil and wipe samples in the CCC study 

(weighted) and in screening wipe samples collected in JAX (unweighted). ................................ 24 

Table 3.1 Summary of air sample collection methods.................................................................. 27 

Table 3.2 Limits of detection (ng/m3) for air samples by compound and study........................... 28 

Table 3.3 Median and 95th percentile air concentrations (ng/m3, unweighted) for frequently 

detected pesticides. ....................................................................................................................... 31 

Table 3.4 Spearman correlations among personal, indoor, and outdoor concentrations of 

chlorpyrifos and diazinon measured in MNCPES........................................................................ 39 

Table 3.5 Urban and rural differences in airborne concentrations of chlorpyrifos and diazinon 

measured in MNCPES. ................................................................................................................. 39 

Table 3.6 Differences in airborne concentrations measured in CTEPP for urban versus rural, low 

versus medium income, and home versus daycare expressed as ratios of geometric means........ 39 

Table 3.7 Airborne chlorpyrifos residues collected following a crack and crevice type application 

versus a total release aerosol in the EPA Test House. .................................................................. 44 

Table 4.1 Studies and sample collection methods for surface measurements. ............................. 48 

Table 4.2 Limits of detection (ng/g or ng/cm2) for surface measurements by study, method, and 

compound...................................................................................................................................... 49 

Table 4.3 Median and 95th percentile values for soil (ng/g) and dust (ng/cm2 and ng/g) 

measurements by study................................................................................................................. 52 

Table 4.4 Median and 95th percentile values for total available residues (ng/cm2) by study. ...... 63 

Table 4.5 Median and 95th percentile values for transferable residues (ng/cm2) by study. .......... 70 

Table 5.1 Dietary exposure sample collection methods for pesticides......................................... 82 

Table 5.2 Limits of detection (μg/kg) for pesticides measured in duplicate diets........................ 84 

Table 5.3 Median and 95th percentile pesticide concentrations (μg/kg) measured in duplicate diet 

food samples. ................................................................................................................................ 84 

Table 6.1 Collection methods for the transfer of pesticide surface residues to food or objects. .. 95 

xvi
Table 6.2 Videotaped children’s hand- and object-to-mouth activity details............................... 96 

Table 6.3 Videotaped hand-to-mouth and object-to-mouth counts .............................................. 96 

Table 6.4 Objects commonly mouthed by preschoolers in CTEPP.............................................. 96 

Table 6.5 Median and 95th percentile pesticide loadings (ng/cm2) measured on toy surfaces. .... 97 

Table 6.6 The transfer efficiency (percent transfer, mean ± sd) of pesticide residues from treated 

surfaces to foods (relative to transfer to IPA wipes), after a 10-min contact duration (Food 

Transfer Studies)........................................................................................................................... 99 

Table 6.7 The transfer efficiency (percent transfer, mean ± sd) of pesticide residues from a 

treated ceramic tile surface to various foods and to an IPA Wipe (Food Transfer Studies)....... 100 

Table 6.8 The measured and predicted ingestion (ng/day) of diazinon from the DIYC. ........... 101 

Table 6.9 The estimated exposures (ng/day) of NC and OH preschool children in the CTEPP 

study to chlorpyrifos, diazinon, and permethrin through indirect ingestion............................... 103 

Table 7.1 Factors commonly believed to affect dermal transfer. ............................................... 107 

Table 7.2 Study parameters tested in surface-to-skin transfer experiments in the Characterizing 

Pesticide Residue Transfer Efficiencies study............................................................................ 107 

Table 7.3 Skin loadings (mean, standard deviation) measured following surface-to-skin transfer 

experiments (initial experiments). .............................................................................................. 108 

Table 7.4 Statistical analysis results (p-values) from initial surface-to-hand transfer experiments 

(Riboflavin)................................................................................................................................. 109 

Table 7.5 Statistical analysis results (p-values) from refined, follow-up surface-to-hand transfer 

experiments (Riboflavin and Uvitex).......................................................................................... 109 

Table 7.6 Evidence of importance of factors tested across surface-to-skin transfer experiments.

..................................................................................................................................................... 110 

Table 7.7 Limits of detection (ng/cm2) for dermal measurements by compound and study ...... 114 

Table 7.8 Median and 95th percentile values of pesticide hand loadings (ng/cm2

) measured by 

hand rinse (HR) or hand wipe (HW) in the large observational field studies............................. 114 

Table 7.9 Comparison of chlorpyrifos and diazinon loadings (ng/cm2) on children’s hands 

measured with hand rinse (HR) and hand wipe (HW) methods ................................................. 115 

Table 7.10 Pesticide loading (ng/cm2) on cotton garments worn by children in three studies... 125 

Table 7.11 Results of multiple linear regression modeling of measured bodysuit pesticide loading 

(ng/cm2/sec) from data collected in the daycare study. .............................................................. 126 

Table 7.12 Estimates of between- and within-person variability for loading on individual 

bodysuit sections......................................................................................................................... 126 

Table 8.1 Absorption and elimination characteristics for pesticides and urinary biomarkers of 

pesticide exposure....................................................................................................................... 132 

Table 8.2 Summary of the children’s urinary biomarker collection methods. ........................... 135 

Table 8.3 Urinary metabolites of organophosphate and pyrethroid pesticides measured in the 

children’s observational measurement studies............................................................................ 136 

Table 8.4 Limits of detection (ng/mL) for each pesticide metabolite measured in the children’s 

urine samples by study................................................................................................................ 136 

Table 8.5 Median and 95th percentile values (ng/mL) for the pesticide metabolites TCPy, IMP, 

and 3-PBA measured in the children’s urine samples by study.................................................. 136 

Table 8.6 Intraclass correlation coefficients (ICC) for logged CTEPP urinary metabolites. ..... 142 

Table 8.7 Between- and within-person geometric standard deviations (GSDs) for logged urinary 

concentrations from children in the CTEPP study...................................................................... 142 

xvii
Table 8.8 Estimated relative importance of the inhalation, dietary ingestion, and indirect 

ingestion routes of exposure among children in CTEPP NC and OH. ....................................... 147 

Table A.1 Summary statistics for airborne chlorpyrifos concentrations (ng/m3) by study......... 166 

Table A.2 Summary statistics for airborne diazinon concentrations (ng/m3) by study. ............. 167 

Table A.3 Summary statistics for airborne malathion concentrations (ng/m3) by study. ........... 167 

Table A.4 Summary statistics for airborne cis-permethrin concentrations (ng/m3) by study..... 168 

Table A.5 Summary statistics for airborne trans-permethrin concentrations (ng/m3) by study. 168 

Table A.6 Summary statistics for airborne TCPy concentrations (ng/m3) by study................... 169 

Table A.7 Summary statistics for airborne IMP concentrations (ng/m3) by study..................... 169 

Table A.8 Summary statistics for chlorpyrifos concentrations measured in soil (ng/g)............. 170 

Table A.9 Summary statistics for chlorpyrifos measured in dust, presented as both loading 

(ng/cm2) and concentration (ng/g). ............................................................................................. 170 

Table A.10 Summary statistics for diazinon concentrations measured in soil (ng/g). ............... 171 

Table A.11 Summary statistics for diazinon measured in dust, presented as both loading (ng/cm2) 

and concentration (ng/g). ............................................................................................................ 171 

Table A.12 Summary statistics for cis-permethrin concentrations measured in soil (ng/g)....... 172 

Table A.13 Summary statistics for cis-permethrin measured in dust, presented as both loading 

(ng/cm2) and concentration (ng/g). ............................................................................................. 172 

Table A.14 Summary statistics for trans-permethrin concentrations measured in soil (ng/g). .. 173 

Table A.15 Summary statistics for trans-permethrin measured in dust, presented as both loading 

(ng/cm2) and concentration (ng/g). ............................................................................................. 173 

Table A.16 Summary statistics for cyfluthrin concentrations measured in soil (ng/g). ............. 174 

Table A.17 Summary statistics for cyfluthrin measured in dust, presented as both loading 

(ng/cm2) and concentration (ng/g). ............................................................................................. 174 

Table A.18 Summary statistics for TCPy concentrations measured in soil (ng/g)..................... 175 

Table A.19 Summary statistics for IMP concentrations measured in soil (ng/g). ...................... 175 

Table A.20 Summary statistics for chlorpyrifos in Total Available Residue (ng/cm2). ............. 176 

Table A.21 Summary statistics for diazinon in Total Available Residue (ng/cm2).................... 177 

Table A.22 Summary statistics for cis-permethrin in Total Available Residue (ng/cm2). ......... 177 

Table A.23 Summary statistics for trans-permethrin in Total Available Residue (ng/cm2)....... 178 

Table A.24 Summary statistics for cyfluthrin in Total Available Residue (ng/cm2).................. 178 

Table A.25 Summary statistics for chlorpyrifos in Transferable Residue (ng/cm2)................... 179 

Table A.26 Summary statistics for diazinon in Transferable Residue (ng/cm2)......................... 180 

Table A.27 Summary statistics for cis-permethrin in Transferable Residue (ng/cm2). .............. 180 

Table A.28 Summary statistics for trans-permethrin in Transferable Residue (ng/cm2)............ 181 

Table A.29 Summary statistics for cyfluthrin using in Transferable Residue (ng/cm2). ............ 181 

Table A.30 Summary statistics for chlorpyrifos measured in solid food, presented as both intake 

(μg/day) and concentration (μg/kg). ........................................................................................... 182 

Table A.31 Summary statistics for diazinon measured in solid food, presented as both intake 

(μg/day) and concentration (μg/kg). ........................................................................................... 183 

Table A.32 Summary statistics for cis-permethrin measured in solid food, presented as both 

intake (μg/day) and concentration (μg/kg).................................................................................. 184 

Table A.33 Summary statistics for trans-permethrin measured in solid food, presented as both 

intake (μg/day) and concentration (μg/kg).................................................................................. 184 

Table A.34 Summary statistics for TCPy measured in solid food, presented as both intake 

(μg/day) and concentration (μg/kg). ........................................................................................... 185 

xviii
Table A.35 Summary statistics for IMP measured in solid food, presented as both intake (μg/day) 

and concentration (μg/kg). .......................................................................................................... 185 

Table A.36 Summary statistics for chlorpyrifos hand loadings (ng/cm2)................................... 186 

Table A.37 Summary statistics for diazinon hand loadings (ng/cm2

). ....................................... 186 

Table A.38 Summary statistics for cis-permethrin hand loadings (ng/cm2

)............................... 186 

Table A.39 Summary statistics for trans-permethrin hand loadings (ng/cm2). .......................... 187 

Table A.40 Summary statistics for TCPy hand loadings (ng/cm2)............................................. 187 

Table A.41 Summary statistics for IMP hand loadings (ng/cm2). .............................................. 187 

Table A.42 Summary statistics for TCPy measured in urine (ng/mL). ...................................... 188 

Table A.43 Summary statistics for 3-PBA measured in urine (ng/mL). .................................... 188 

Table A.44 Summary statistics for IMP measured in urine (ng/mL). ........................................ 188 

xix
Figures 

Figure 1.1 Modeling framework for children’s pesticide exposure from Cohen Hubal et al.

(2000b)............................................................................................................................................ 3 

Figure 2.1 Weighted percentage of child care centers reporting treatment of various rooms in the 

Child Care Centers (CCC) study................................................................................................... 19 

Figure 3.1 Frequency of detection of pesticides measured in indoor and outdoor air in selected 

studies ........................................................................................................................................... 29 

Figure 3.2 Log probability plots for chlorpyrifos, diazinon, and cis-permethrin measured in large 

observational field studies............................................................................................................. 32 

Figure 3.3 Log probability plots for trans-permethrin, TCPy, and IMP measured in large 

observational field studies............................................................................................................. 33 

Figure 3.4 Indoor and outdoor air concentrations of chlorpyrifos, diazinon, and cis-permethrin 

measured in selected studies. ........................................................................................................ 34 

Figure 3.5 Indoor and outdoor air concentrations of trans-permethrin and TCPy measured in 

selected studies.............................................................................................................................. 35 

Figure 3.6 Log-scale relationships between levels of parent pesticide (ng/m3) and degradate 

(ng/m3) measured in CTEPP. ........................................................................................................ 36 

Figure 3.7 The detection frequencies of select pesticides and their metabolites measured from the 

indoor air (A) and outdoor air (B) of homes and daycares in NC and OH................................... 40 

Figure 3.8 Airborne concentrations (ng/m3) of chlorpyrifos or diazinon measured from indoor air 

over time in the Test House, PET, CPPAES, and DIYC studies.................................................. 45 

Figure 3.9 Association between measured air concentration (ng/m3) and Applied Effective 

Volume (ng/m3/h) on the second day after application of chlorpyrifos in CPPAES homes ........ 46 

Figure 3.10 Pesticide air concentrations as a function of vapor pressure in CTEPP homes (A) and 

daycares (B) .................................................................................................................................. 46 

Figure 4.1 Detection frequencies of pesticides and degradates in soil. ........................................ 53 

Figure 4.2 Detection frequencies of pesticides and degradates in dust. ....................................... 53 

Figure 4.3 Lognormal probability plots of soil concentrations (ng/g) for chlorpyrifos, diazinon, 

cis-permethrin, trans-permethrin, cyfluthrin, and TCPy. ............................................................. 54 

Figure 4.4 Lognormal probability plots of dust concentrations (ng/g) and loadings (ng/cm2) for 

chlorpyrifos, diazinon, and cis-permethrin. .................................................................................. 55 

Figure 4.5 Lognormal probability plots of dust concentrations (ng/g) and loadings (ng/cm2) for 

trans-permethrin, cyfluthrin, and TCPy........................................................................................ 56 

Figure 4.6 Box-and-whisker plots of dust concentrations (ng/g) and loadings (ng/cm2) for 

chlorpyrifos, diazinon, and cis-permethrin. .................................................................................. 57 

Figure 4.7 Box-and-whisker plots of dust concentrations (ng/g) and loadings (ng/cm2) for transpermethrin, cyfluthrin, and TCPy. ................................................................................................ 58 

Figure 4.8 Detection frequencies for pesticides using total available residue collection methods.

....................................................................................................................................................... 62 

xx
Figure 4.9 Lognormal probability plots for the most frequently detected pesticides which include 

chlorpyrifos, diazinon, cis- and trans-permethrin, cyfluthrin, and cypermethrin......................... 64 

Figure 4.10 Box-and-whisker plots of total available residue surface loadings (ng/cm2) for 

chlorpyrifos, diazinon, cis-permethrin, trans-permethrin, cypermethrin, and esfenvalerate........ 65 

Figure 4.11 Detection frequencies for pesticides using transferable residue collection methods. 68 

Figure 4.12 Lognormal probability plots for transferable residue loadings for the most frequently 

detected pesticides which include chlorpyrifos, diazinon, and cis- and trans-permethrin from 

CTEPP........................................................................................................................................... 71 

Figure 4.13 Box-and-whisker plots for transferable residue loadings for the most frequently 

detected pesticides which include chlorpyrifos, diazinon, cis- and trans-permethrin, cyfluthrin, 

and TCPy. ..................................................................................................................................... 72 

Figure 4.14 Total available surface residue loadings measured in multiple rooms over time in the 

Test House, in multiple rooms in ten homes in CPPAES, and on multiple surfaces in three homes 

in DIYC......................................................................................................................................... 75 

Figure 4.15 Transferable residue measurements over time following an application from multiple 

locations in multiple rooms of the Test House and multiple surfaces in three homes in DIYC... 75 

Figure 4.16 Total available residue measurements from the Daycare study ................................ 76 

Figure 4.17 Spatial variability in deposition coupon loadings in the kitchen (application site) and 

den (adjoining room) of Test House following pesticide application........................................... 76 

Figure 5.1 The detection frequency of pesticides measured in duplicate diet food samples........ 85 

Figure 5.2 Lognormal probability plots of solid food concentrations (μg/kg) and intakes (μg/day) 

for chlorpyrifos, diazinon, and cis-permethrin from large observational field studies................. 86 

Figure 5.3 Lognormal probability plots of solid food concentrations (μg/kg) and intakes (μg/day) 

for trans-permethrin, TCPy, and IMP from large observational field studies.............................. 87 

Figure 5.4 Box-and-whisker plots of solid food concentrations (μg/kg) and intakes (μg/day) for 

chlorpyrifos, diazinon, and cis-permethrin across all studies....................................................... 88 

Figure 5.5 Box-and-whisker plots of solid food concentrations (μg/kg) and intakes (μg/day) for 

trans-permethrin, TCPy, and IMP across all studies. ................................................................... 89 

Figure 5.6 Comparison of SHEDS model prediction for dietary intake of cis-permethrin 

(μg/kg/day) and CTEPP measurement data.................................................................................. 90 

Figure 5.7 Estimated mean proportion of aggregate potential exposure for CTEPP-NC children 

by exposure route.......................................................................................................................... 91 

Figure 5.8 Estimated mean proportion of aggregated potential exposure for CTEPP-OH children 

by exposure route.......................................................................................................................... 92 

Figure 6.1 Comparison of the median hand-to-mouth and object-to-mouth contacts per hour 

among CPPAES and MNCPES children ...................................................................................... 97 

Figure 6.2 Comparison of measured and predicted ingestion of diazinon (ng/day) from the 

DIYC........................................................................................................................................... 102 

Figure 7.1 Comparison of transfer efficiencies of fluorescent tracers and pesticides from laminate 

and carpet surfaces to various sampling media........................................................................... 110 

Figure 7.2 Hand loading by contact number, from the refined, follow-up experiments using 

Riboflavin (left panels) or Uvitex (right panels)......................................................................... 111 

Figure 7.3 Log probability plots of hand loadings (MNCPES data are hand rinses, all others are 

hand wipes) ................................................................................................................................. 116 

Figure 7.4 Comparison of hand loadings across studies............................................................. 117 

xxi
Figure 7.5 Ratios of hand wipe loading to floor wipe loading (left panel) and hand wipe loading 

to dust loading (right panel) for pesticides in CTEPP. ............................................................... 118 

Figure 7.6 Relationship between children’s hand loadings measured at CTEPP homes and 

daycares....................................................................................................................................... 119 

Figure 7.7 Relationship between hand loadings among children and adults in CTEPP............. 120 

Figure 7.8 Relationship between hand wipe measurements and floor wipe measurements in 

CTEPP......................................................................................................................................... 121 

Figure 7.9 Relationship between hand wipe measurements and floor dust measurements in 

CTEPP......................................................................................................................................... 122 

Figure 7.10 Bodysuit section loadings (ng/cm2) by monitoring period from the Daycare study 127 

Figure 7.11 Relative standard deviations of esfenvalerate loadings on cotton garment sections 

among infants and preschoolers in the Daycare study................................................................ 128 

Figure 7.12 Handwipe loadings (ng/cm2) above method detection limit among infants and 

preschoolers in the Daycare study. ............................................................................................. 128 

Figure 8.1 Detection frequencies of pesticide metabolites in the children’s urines samples by 

study............................................................................................................................................ 137 

Figure 8.2 Log probability plots of urinary TCPy, 3-PBA, and IMP concentrations across large 

observational field studies. NHANES results are included for comparison.............................. 138 

Figure 8.3 Box-and-whisker plots comparing the urinary TCPy and 3-PBA concentrations across 

studies. ........................................................................................................................................ 139 

Figure 8.4 Urinary TCPy concentrations (ng/mL) over time for the children in the high and low 

application groups in CPPAES. .................................................................................................. 140 

Figure 8.5 Time profiles for chlorpyrifos in environmental media and TCPy concentrations in 

urine for all children in the CPPAES.......................................................................................... 140 

Figure 8.6 Concentration versus time plots for urinary TCPy measurements among CTEPP-NC 

and CTEPP-OH participants reporting a recent pesticide application........................................ 143 

Figure 8.7 Time-concentration profile for urinary IMP measurements among child and adult PET 

study participants following an outdoor granular turf pesticide application .............................. 143 

Figure 8.8 Estimates of age-specific urinary output and creatinine excretion, based on data from 

the MNCPES............................................................................................................................... 145 

Figure 8.9 The median estimated intakes of chlorpyrifos and TCPy in CTEPP-NC compared with 

the excreted median amounts of TCPy in the preschool children’s urine .................................. 147 

Figure 8.10 Intake of environmental TCPy through the dietary route correlated poorly (r2=0.01) 

with the amount of TCPy excreted in the urine of CTEPP-NC preschool children. .................. 148 

Figure 8.11 Estimated distributions of aggregate intake (“AGGR”) of chlorpyrifos and 

permethrin (ng/kg/day) and estimated distributions of the four contributing routes.................. 148 

Figure 8.12 The contributions of inhalation, dermal absorption, diet, and nondietary ingestion to 

aggregate intake of cis-permethrin.............................................................................................. 149 

Figure 8.13 Children’s estimated aggregate intake of chlorpyrifos and permethrin compared to 

their measured urinary metabolites (CTEPP). ............................................................................ 149 

Figure 8.14 Distributions of TCPy in urine across studies (bottom right panel) in comparison to 

distributions of chlorpyrifos in indoor air, outdoor air, dust, and soil across studies................. 150 

Figure 8.15 Distributions of TCPy in urine across studies (bottom right panel) in comparison to 

distributions of chlorpyrifos on surfaces, in solid food, and on hands across studies. ............... 151 

Figure 8.16 Comparison of TCPy in urine between SHEDS model and observed MNCPES data 

when TCPy in the environment is not considered (Source: Xue et al., 2004)............................ 152 

xxii
Acknowledgments 

We would like to acknowledge the many researchers and support staff who contributed to this 

report by their design and implementation of the included studies. The contributors are too 

numerous to acknowledge individually, but the organizations that collaborated on this research 

are listed in the report and Appendix B. This report would not be possible without all of the hard 

work that was put into the individual studies. A number of other researchers in the Human 

Exposure and Atmospheric Sciences Division, including Dr. Jianping (Jim) Xue, Mr. Thomas 

McCurdy, Dr. Rogelio Tornero-Velez, and Mr. M. Scott Clifton, made valuable contributions to 

this report by their analyses of data, reviews, and comments. 

We would like to acknowledge the EPA Program Office scientists, NERL researchers, and 

Science to Achieve Results (STAR) program grantees who gathered at the NERL Workshop on 

the Analysis of Children’s Measurements Data (Tulve et al., 2006) in September 2005 to assess 

the suitability of the data for testing key hypotheses and to suggest additional analyses. 

The authors also gratefully acknowledge the time, effort, and constructive comments offered by 

the peer reviewers, Dr. Laura Geer (Johns Hopkins University), Dr. Miles Okino (EPA), Dr. B.J. 

George (EPA), and Dr. Valerie Zartarian (EPA). The comprehensive review and comments by 

Mr. Kent Thomas (Associate Director for Human Health in the Human Exposure and 

Atmospheric Sciences Division) also contributed significantly to the quality of the final 

document. 

We would especially like to thank all of the study participants who worked so generously with 

the researchers to help make these observational studies a success. 

 

xxiii
Abbreviations and Acronyms 

%Det Percent of samples above detection limit 

2,4-D 2,4-Dichlorophenoxyacetic acid 

3-PBA 3-Phenoxybenzoic acid 

ACH Air exchanges per hour 

AER Air exchange rate 

AEV Application effective volume 

ANOVA Analysis of variance 

ASTM American Society for Testing and Materials 

ATSDR Agency for Toxic Substances and Disease Registry 

AZ National Human Exposure Assessment Survey in Arizona 

C18 Press C18 surface press sampler 

CCC First National Environmental Health Survey of Child Care 

Centers Study 

CDC Centers for Disease Control 

CDIM Children’s Dietary Intake Model 

CHA Center for the Health Assessment of Mothers and Children 

of Salinas Quantitative Exposure Assessment Study 

CHAMACOS Center for the Health Assessment of Mothers and Children 

of Salinas Quantitative Exposure Assessment Study 

cis-P cis-Permethrin 

c-Perm cis-Permethrin 

c-Permethrin cis-Permethrin 

CPPAES Pre CPPAES Study, pre-application days only 

CPPAES Children’s Pesticide Post-Application Exposure Study 

CRE Creatinine 

CTEPP Children’s Total Exposure to Persistent Pesticides and 

Other Persistent Organic Pollutants Study 

CTEPP-NC CTEPP Study, North Carolina homes and daycares 

CTEPP-NC d CTEPP Study, North Carolina daycares only 

CTEPP-NC DAYCARE CTEPP Study, North Carolina daycares only 

CTEPP-NC h CTEPP Study, North Carolina homes only 

CTEPP-NC HOME CTEPP Study, North Carolina homes only 

CTEPP-OH CTEPP Study, Ohio homes and daycares 

CTEPP-OH d CTEPP Study, Ohio daycares only 

CTEPP-OH DAYCARE CTEPP Study, Ohio daycares only 

CTEPP-OH h CTEPP Study, Ohio homes only 

CTEPP-OH HOME CTEPP Study, Ohio homes only 

DAP Dialkylphosphate 

xxiv
Daycare / DAYCARE Feasibility of Macroactivity Approach to Assess Dermal 

Exposure Study 

Dep Coup Deposition coupon 

DC Deposition coupon 

DCHD Duval County Health Department 

DEET N,N-diethyl-meta-toluamide 

DIYC Dietary Intake of Young Children Study 

EOSHI Environmental and Occupational Health Sciences Institute 

Study 

Food Food Transfer Studies 

FQPA Food Quality Protection Act 

GC/ECD Gas Chromatography/Electron Capture Detector 

GC/MS Gas Chromatography/Mass Spectroscopy 

GLM Generalized linear model 

GM Geometric mean 

GSD Standard deviation of the geometric mean 

HUD US Department of Housing and Urban Development 

HVS3 High Volume Small Surface Sampler 

ICC Intraclass Correlation Coefficient 

IMP / IMPy 2-Isopropyl-6-methyl-4-pyrimidinol 

IPA Isopropyl alcohol 

IPA Wipe Isopropyl alcohol wipe 

JAX Biological and Environmental Monitoring for 

Organophosphate and Pyrethroid Pesticide Exposures in 

Children Living in Jacksonville, Florida Study 

JAX-AG JAX Study, Aggregate Exposure Assessment phase 

JAX-AGG JAX Study, Aggregate Exposure Assessment phase 

JAXAGGREGATE JAX Study, Aggregate Exposure Assessment phase 

JAX-SC JAX Study, Screening phase 

 JAX-SCR JAX Study, Screening phase 

JAXSCREENING JAX Study, Screening phase 

LOD Limit of detection 

LWW Lioy-Weisel-Wainman wipe sampler 

Max Maximum 

MCPA (4-chloro-2-methylphenoxy)acetic acid 

MDA Malathion dicarboxylic acid 

MDL Minimum detection limit 

MGK 264 N-octyl bicycloheptene dicarboximide 

Min Minimum 

MNCPES / MN Minnesota Children’s Pesticide Exposure Study 

MPA 2-methyl-3-phenylbenzoic acid 

N Sample size 

NC Daycare CTEPP Study, North Carolina daycares only 

NC DC CTEPP Study, North Carolina daycares only 

NC HM CTEPP Study, North Carolina homes only 

NC Home CTEPP Study, North Carolina homes only 

xxv
NC North Carolina 

NERL National Exposure Research Laboratory 

NHANES National Health and Nutrition Examination Survey Study 

NHEXAS-AZ National Human Exposure Assessment Survey in Arizona 

NOPES Non-Occupational Pesticide Exposure Study 

NRMRL National Risk Management Research Laboratory 

OCHP Office of Children's Health Protection 

OH Daycare CTEPP Study, Ohio daycares only 

OH DC CTEPP Study, Ohio daycares only 

OH HM CTEPP Study, Ohio homes only 

OH Home CTEPP Study, Ohio homes only 

OH CTEPP Study, Ohio 

OP Organophosphate 

OPP Office of Pesticide Programs 

OPPT Office of Pollution Prevention and Toxics 

ORD Office of Research and Development 

P25 25th percentile 

P50 Median / 50th percentile 

P75 75th percentile 

P95 95th percentile 

PBPK Physiologically-Based Pharmacokinetic Model 

PET A Pilot Study Examining Translocation Pathways 

Following a Granular Application of Diazinon to 

Residential Lawns Study 

PUF Polyurethane foam 

PYR Pyrethroid 

REJV Residential Exposure Joint Venture 

RTI Research Triangle Institute 

SD Standard deviation of the arithmetic mean 

SHEDS Stochastic Human Exposure and Dose Simulation Model 

STAR Science to Achieve Results 

TCPY / TCP / TCPy 3,5,6-Trichloro-2-pyridinol 

TE Transfer Efficiency 

TEST / TESTHOUSE / Test House The Distribution of Chlorpyrifos Following a Crack and 

Crevice Type Application in the US EPA Indoor Air 

Quality (IAQ) Research House Study 

TESTHOUSE Pre Test House Study, pre-application day only 

t-Permethrin trans-Permethrin 

t-Perm trans-Permethrin 

trans-P trans-Permethrin 

Transfer Characterizing Pesticide Residue Transfer Efficiencies

US CPSC US Consumer Product Safety Commission 

US EPA U.S. Environmental Protection Agency 

VTD Virtual Timing Device 

xxvi
1.0 INTRODUCTION 

1.1 Background 

The U.S. Environmental Protection Agency (U.S. EPA) has pledged to increase its efforts to 

provide a safe and healthy environment for children by ensuring that all EPA regulations, 

standards, policies, and risk assessments take into account special childhood vulnerabilities to 

environmental toxicants. Children are behaviorally and physiologically different from adults. 

Their interaction with their environment, through activities such as playing on floors, and 

mouthing of hands and objects, and handling of food, may increase contact with contaminated 

surfaces. Proportionately higher breathing rates, relative surface area, and food intake 

requirements may increase exposure. Differences in absorption, metabolism, storage, and 

excretion may result in higher biologically effective doses to target tissues. Immature organ 

systems may be more susceptible to toxicological challenges. Windows of vulnerability, when 

specific toxicants may permanently alter the function of an organ system, are thought to exist at 

various stages of development. 

Children are exposed to a wide variety of chemicals in their homes, schools, daycare centers, and 

other environments that they occupy. The chemicals to which they are exposed may originate 

from outdoor sources, such as ambient air contaminants, indoor sources such as building 

materials and furnishings, and from consumer products used indoors. One category of consumer 

products to which children may be exposed is pesticides that are used to control roaches, rats, 

termites, ants, and other vermin. Despite widespread residential and agricultural use of 

pesticides, only limited measurement data are available for pesticide levels in environments that 

children occupy and little is known about the factors that impact children’s exposures to 

pesticides. The Food Quality Protection Act (FQPA) of 1996 requires EPA to upgrade the risk 

assessment procedures for setting pesticide residue tolerances in food by considering the 

potential susceptibility of infants and children to both aggregate and cumulative exposures to 

pesticides. Aggregate exposures include exposures from all sources, routes, and pathways for 

individual pesticides. Cumulative exposures include aggregate exposures to multiple pesticides 

with the same mode of action for toxicity. FQPA requires risk assessments to be based on 

exposure data that are of high quality and high quantity or on exposure models using factors that 

are based on existing, reliable data. 

EPA’s Office of Research and Development (ORD) is responsible for conducting research to 

provide the scientific foundation for risk assessment and risk management at EPA. In 2000, 

ORD released its Strategy for Research on Environmental Risks to Children addressing research 

needs and priorities associated with children’s exposure to environmental pollutants and 

providing a framework for a core program of research in hazard identification, dose-response 

evaluation, exposure assessment, and risk management. 

The National Exposure Research Laboratory (NERL) in ORD is working to achieve three 

specific objectives of the Strategy through its children’s exposure research program: (1) develop 

improved exposure assessment methods and models for children using existing information; 

(2) design and conduct research on age-related differences in exposure, effects, and doseresponse relationships to facilitate more accurate risk assessments for children; and (3) explore 

1
opportunities for reducing risks to children. After an exhaustive review of the volume and 

quality of the data upon which default assumptions for exposure factors are based (Cohen Hubal 

et al., 2000a), a framework for systematically identifying the important sources, routes, and 

pathways for children’s exposure was developed (Cohen Hubal et al., 2000b). 

This framework (Figure 1.1), based on a conceptual model for aggregate exposure, provides the 

foundation for a protocol for measuring aggregate exposures to pesticides (Berry et al., 2001) 

and for developing sophisticated stochastic models (Zartarian et al., 2000). Using the 

framework, four priority research areas, representing critical data gaps in our understanding of 

environmental risks to children, have been identified: 

(1) Pesticide use patterns; 

(2) Spatial and temporal distribution in residential dwellings; 

(3) Dermal absorption and indirect (non-dietary) ingestion (including micro- and 

macro-activity approaches); and 

(4) Direct ingestion. 

Several targeted studies were designed and conducted to address these research needs. These 

include laboratory studies, small pilot field studies, and large collaborative observational studies. 

These studies aimed to: (1) evaluate methods and protocols for measuring children’s exposure, 

(2) collect data on exposure factors to reduce the uncertainty in exposure estimates and risk 

assessments, and (3) collect data for use in exposure model development and evaluation. 

1.2 Purpose of the Report and Intended Audience 

This document is a comprehensive summary report of data collected under or otherwise related 

to the NERL children's exposure research program. Data are compared across studies and across 

compounds to identify or evaluate important factors influencing exposures along each relevant 

pathway. Summary statistics, comparative analyses, and spatial and temporal patterns are 

presented to address previously identified data gaps. The primary purpose of this document is to 

identify factors that are most important for children's exposures to pesticides. The objectives of 

this document are to: 

• Compare results across studies in order to identify trends or similar observations that 

might provide a better understanding of the factors affecting children’s exposures; 

• Describe recent children’s exposure studies conducted or funded by NERL, including 

descriptions of the parameters measured and the measurement methods; 

• Provide concentration data and summary statistics for comparison of the studies; and 

• Present highlights of the results of the studies. 

The document was completed with input from staff in the EPA Program Offices, NERL 

researchers, and Science to Achieve Results (STAR) program grantees who gathered at the US 

EPA National Exposure Research Laboratory’s Workshop on the Analysis of Children’s 

Measurement Data (Tulve et al., 2006) in September 2005 to discuss data presented in a draft 

summary report, assess the suitability of the data for testing key hypotheses, and propose 

additional analyses.

2
Nondietary 

Ingestion

Dietary Ingestion

Release

 & 

Transfer

Exposure 

Media

Inhalation

R.T. Uptake

G.I. Uptake

Dermal Uptake

Dermal 

Contact

Dermal Body

Exposure 

Rate

Skin 

Surface

Indoor

air

water

house dust

food

surfaces

clothes

Source

indoor 

residential

outdoor 

residential

industrial

agricultural

Outdoor

air

water

soil

plants

surfaces

Contact 

Activities

Mass 

Transfer 

Rates

Mouthing 

Activities Ingestion 

Rate

Uptake 

Rate

Mouthing 

Activities

Ingestion 

Rate

Absorbed 

Dose

Diet

Ingestion 

Rate

G.I. Tract

Ingestion 

Exposure 

Rate

Uptake 

Rate

Respiratory 

Tract

Inhalation 

Exposure 

Rate Uptake 

Rate

Activity 

Patterns

Inhalation 

Rate

Exposure

Figure 1.1 Modeling framework for children’s pesticide exposure from Cohen Hubal et al.

(2000b). 

3
The document is intended for an audience of exposure scientists, exposure modelers, and risk 

assessors. Exposure scientists will find a useful evaluation of available sampling methods for all 

media relevant to children’s exposures. Exposure modelers will be able to use the data to 

develop or improve probabilistic multimedia, multi-pathway human exposure models. Most 

significantly, the report may be used by EPA Program offices such as the Office of Pesticide 

Programs (OPP), the Office of Pollution Prevention and Toxics (OPPT), and the Office of 

Children's Health Protection (OCHP) to enhance the Agency's risk assessment activities by 

replacing default assumptions with high-quality, real-world data. Fewer default assumptions will 

lead to more accurate assessments of exposure and risk and will bolster ensuing risk reducing 

actions. Furthermore, by examining relationships among application patterns, exposures, and 

biomarkers for multiple compounds from different classes of pesticides, this report contributes to 

the development of more reliable approaches for assessing cumulative exposure. Some of the 

analyses and comparisons that are presented in this summary report include the following: 

• Comparison of concentrations 

• Spatial variability 

• Temporal variability 

• Regional comparisons 

• Urban versus rural 

• Home versus daycare 

• Indoor versus outdoor 

• Parent compound versus metabolite 

• Effect of physical and chemical properties 

• Impact of air exchange rate 

• Effect of surface type 

• Effect of surface concentration 

• Effect of sampling method 

Comparisons between studies may involve different numbers of measurements, different 

sampling strategies and methods, and different chemical analysis methods 

1.3 Structure of the Report 

This document presents data from studies to evaluate children’s exposure to pesticides, spanning 

from pesticide use patterns, through concentrations in exposure media, to biological markers of 

exposure. The exposure media are listed in an order that roughly mirrors the complexity of the 

exposure mechanism; that is, beginning with inhalation exposure and ending with dermal 

exposure. At the beginning of each section, available data from the relevant studies are listed. 

Results are presented in tables and graphs to illustrate the available data and to facilitate 

comparisons both across studies and across pesticides. 

Throughout the document, lognormal probability plots (“logplots”) and box-and-whisker plots 

(“box plots”) are used to graphically depict and compare distributions of concentrations or 

surface loadings. The logplots are used to compare results only from large observational field 

studies and the boxplots are used to compare results from the focused studies against each other 

and against the large observational field studies. In the lognormal probability plot, the ordered 

4
values of the measured concentration are plotted on a log-scale vertical axis, and the percentiles 

of the theoretical normal distribution are plotted on the horizontal axis. If the points in the plot 

form a nearly straight line, the data are approximately lognormal. The box-and-whisker plot is 

actually a group of side-by-side box-and-whisker plots along the x-axis, each representing a 

different study. The upper whisker extends to the maximum value, the upper edge of the box 

represents the 75th percentile, the line inside the box represents the median (50th percentile), the 

lower edge of the box represents the 25th percentile, and the lower whisker extends to the 

minimum value. Note that the vertical axis is log-scale. 

1.4 Data Treatment 

Values that are below the method detection limit (MDL) are common in environmental data sets. 

All values above the MDL are statistically different from zero; however, values near the MDL 

are generally less accurate than those much higher than the MDL. Laboratories often report a 

second limit, the Method Quantitation Limit (MQL), as the smallest amount that can be reliably

quantified in a sample. Despite the higher relative uncertainty in values between the MDL and 

the MQL, all values above the MDL are retained for the purposes of this document. Values 

below the MDL are treated using simple substitution, wherein they are replaced with a fraction 

of the detection limit (MDL//2), a common practice originally proposed by Hornung and Reed 

(1990). These substituted values are used in all statistical analyses performed specifically for 

this report and are presented in all data plots, except for lognormal probability plots, in which 

these substituted values were judged by the authors to be misleading. Detection frequencies (that 

is, the percent of measurements above the MDL) are presented for each compound by each 

relevant sampling method at the beginning of each chapter. 

Sampling weights are available for all of the large-scale observational field studies, but, unless 

otherwise noted, only unweighted concentrations are presented in this report. Summary statistics 

based on unweighted observations may not provide as valid an estimate of true study population 

values as those based on weighted observations, but are used nonetheless to maintain consistency 

in comparisons with studies for which weights are not available. In all cases where a statistical 

test was done to assess differences, the name of the test and the resulting p-value are presented.

1.5 Description of the Studies and Data Collected 

Data are included in this report from the following studies. (The acronyms in parentheses are 

used in the Tables and Figures of this report.) 

• National Human Exposure Assessment Survey in Arizona (NHEXAS-AZ) 

• Minnesota Children’s Pesticide Exposure Study (“MNCPES”) 

• Children’s Total Exposure to Persistent Pesticides and Other Persistent Organic 

Pollutants (“CTEPP”) 

• First National Environmental Health Survey of Child Care Centers (“CCC”) 

• Biological and Environmental Monitoring for Organophosphate and Pyrethroid Pesticide 

Exposures in Children Living in Jacksonville, Florida (“JAX”) 

• Center for the Health Assessment of Mothers and Children of Salinas Quantitative 

Exposure Assessment Study (“CHAMACOS”) 

5
• Children’s Pesticide Post-Application Exposure Study (“CPPAES”) 

• Distribution of Chlorpyrifos Following a Crack and Crevice Type Application in the US 

EPA Indoor Air Quality Research Test House (“Test House”) 

• Pilot Study Examining Translocation Pathways Following a Granular Application of 

Diazinon to Residential Lawns (“PET”) 

• Dietary Intake of Young Children (“DIYC”) 

• Characterizing Pesticide Residue Transfer Efficiencies (“Transfer”) 

• Food Transfer Studies (“Food”) 

• Feasibility of Macroactivity Approach to Assess Dermal Exposure (“Daycare”) 

All studies involving children were observational research studies, as defined in 40 CFR Part 

26.402. All study protocols and procedures to obtain the assent of the children and informed 

consent of their parents or guardians were reviewed and approved by independent Institutional 

Review Boards (IRBs) and complied with all applicable requirements of the Common Rule (45 

CFR 46) regarding additional protections for children (Subpart D). Further, all protocols 

regarding recruitment and treatment of participants were reviewed by the EPA Human Subjects 

Research Review Official (HSRRO) to assure compliance with the Federal Policy for the 

Protection of Human Subjects. 

The studies discussed in the report included large observational studies, such as NHEXAS-AZ, 

MNCPES, CTEPP, and CCC, small pilot-scale observational studies (e.g., JAX, CPPAES, 

DIYC, CHAMACOS, and Daycare), and laboratory studies (e.g., Test House, Transfer, and 

Food). 

• MNCPES, NHEXAS-AZ, CTEPP, and CCC were large observational exposure 

measurement studies with survey designs that involved random sampling. The CCC 

study was a nationwide survey and the others had a regional focus. Sampling weights are 

available for all of these studies, but, unless noted otherwise, only unweighted 

concentrations are presented in this report. 

• The small pilot-scale observational studies are small-scale field studies, such as JAX and 

CHAMACOS, which were performed to evaluate methods for conducting aggregate 

exposure assessments for pesticides and to collect preliminary data that could be used to 

assist in the design of larger observational studies. Like the large observational studies, 

some of these smaller studies included measurements of multiple chemicals in multiple 

media. 

• The laboratory studies consisted of experiments under controlled conditions to evaluate 

factors affecting transfer from surfaces (Transfer and Food studies). The Test House 

study investigated the fate and transport of chlorpyrifos following a crack and crevice 

application and provided valuable information on spatial and temporal variability of 

surface concentrations in the absence of human activity. 

6
During these studies, the following types of measurements were collected (not all types of 

samples were collected in all studies): 

• Air (indoor and outdoor) 

• Soil 

• House dust – Floors (carpet and hard surface) 

• Surface wipes (including eating and food preparation surfaces) 

• Transferable residues (e.g., polyurethane foam roller, C18 press) 

• Hand wipes 

• Dermal surrogates (cotton garment and socks) 

• Duplicate diet (solid food, beverages) 

• Handled food 

• Urine 

Information was also typically collected by questionnaire on: 

• Housing characteristics 

• Participant characteristics 

• Children’s activities (timelines and logs) 

• Recent pesticide use 

The types of media sampled and questionnaires administered in each study are listed in Table 

1.1. Other than the pesticide inventory and use questionnaires, questionnaire data are not the 

focus of this document. 

1.6 Pesticides of Interest to this Report 

The studies presented here were performed when a number of organophosphate and pyrethroid 

pesticides were in use; thus numerous pesticides from various chemical classes (including 

insecticides and herbicides) were measured. All measured insecticides (and insecticides 

synergists) are listed in Table 1.2, although not all of the studies collected data for all of the 

insecticides listed. To reduce complexity, this report focuses on the most commonly detected 

organophosphate and pyrethroid insecticides: 

• Chlorpyrifos 

• Diazinon 

• Permethrin 

• Cyfluthrin 

7
Table 1.1 Available media, participant characteristics, and activities by study. NHE

XAS-AZ

MNC

PES 

CTEPP CCC JAX SCREENING JAX AGGREG

A

TE 

CHA

MACOS

CPPAES TEST

HOUSE

PET DIYC DAYCARE 

Air - Indoor 9 9 9 9 9 9 9 9 9

Air - Outdoor 9 9 9 9 9 9

House Dust 9 9 9

Surface Residue Wipes 9 9 9 9 9 9 9 9 9 9 9

LWW Surface Sampler 9 9

Transferable Residues 9 9 9 9 9 9 9 9 9 9

Hand Wipes 9 9 9 9 9 9 9

Cotton Garments/Socks 9 9 9 9 9

Soil 9 9 9 9 9

Duplicate Diet 9 9 9 9 9

Handled Foods 9

Urine 9 9 9 9 9 9 9 9

Housing Characteristics 9 9 9 9 9 9 9 9 9 9

Participant Characteristics 9 9 9 9 9 9 9 9 9 9

Children’s Activities 9 9 9 9 9 9 9 9

Recent Pesticide Use 9 9 9 9 9

Pesticide Inventory 9 9 9

Table 1.2 Pesticides and metabolites measured in the studies. 

Pyrethroid Organophosphorus Other 

Allethrin Acephate Ethyl parathion Fipronil 

Bifenthrin Azinphos-methyl Fonofos Piperonyl butoxide 

Cyfluthrin a Chlorpyrifos

 a Malathion TCPy a b 

Cyhalothrin Chlorpyrifos-oxon Malathion-oxon IMP a c 

Cypermethrin Demeton-S Methamidophos 3-PBA a d

Deltamethrin Diazinon a Methidathion

Esfenvalerate Diazinon-oxon Methyl-parathion

Permethrin a Dichlorvos Mevinphos 

Pyrethrins Dimethoate Naled

Resmethrin Disulfoton Phosmet

Sumithrin Ethion

Tetramethrin 

Tralomethrin 

a Pesticides and metabolites of primary interest in this document

b 3,5,6-Trichloro-2-pyridinol, a selective metabolite of chlorpyrifos c 2-Isopropyl-4-methyl-6-hydroxypyrimidine, a specific metabolite of diazinon

d 3-phenoxybenzoic acid, a metabolite common to many pyrethroids

8
1.7 Summary Descriptions of the Studies 

Individual study details are listed in Appendix B. Journal articles presenting results of these 

studies are listed in the Bibliography. The studies are summarized below. 

The National Human Exposure Assessment Survey in Arizona (NHEXAS-AZ) was performed in 

collaboration with the University of Arizona, the Illinois Institute of Technology, and Battelle 

Memorial Institute. Probability-based samples were collected in each of Arizona’s 15 counties 

from December 1995 to March 1997. Although 176 households participated, this report only 

includes data from 21 households with children ages 6-12 as primary participants. Environmental samples included indoor and outdoor air (3-day integrated samples), personal air (1-day), 

vacuumed surface dust, and window sill wipes. Personal samples included 24-hour duplicate 

diet and hand wipes. Biological samples consisted of urine samples (first morning void). 

Baseline and follow-up questionnaires and time-activity diaries captured activity patterns. Two 

pesticides (and their metabolites) were of primary interest, namely chlorpyrifos (TCPy) and 

diazinon, and two pesticides (and their metabolites) were of secondary interest, namely 

malathion (MDA) and carbaryl (1-naphthol). 

The Minnesota Children’s Pesticide Exposure Study (MNCPES) was an observational measurement study performed in collaboration with Research Triangle Institute (RTI), the Environmental 

and Occupational Health Sciences Institute (EOHSI), the Minnesota Department of Health, and 

the University of Minnesota. A telephone survey and in-home interviews were used to collect 

data on pesticide storage and use patterns from 308 households in both urban centers (Minneapolis/St. Paul) and rural counties (Goodhue and Rice) during the summer of 1997. Probabilitybased sampling weights were developed and intensive environmental and personal monitoring 

were performed for 102 children, ages 3-13. Households reporting more frequent pesticide use 

were oversampled. Environmental samples included personal, indoor, and outdoor air (6-day 

integrated), surface dust (wipe and press), surface soil, and tap water. Personal samples included 

solid food (4-day composite), beverages (4-day composite), hand rinse, and first morning void 

urine (days 3, 5, and 7). In addition to questionnaires and diaries, videotaping was performed in 

a subset of 20 homes. Four primary pesticides (and their metabolites), namely chlorpyrifos 

(TCPy), atrazine (atrazine mercapturate), malathion (malathion dicarboxylic acid), and diazinon, 

and 14 secondary pesticides were measured, along with 13 polycyclic aromatic hydrocarbons 

(PAHs). 

The Children’s Total Exposure to Persistent Pesticides and Other Persistent Organic Pollutants 

(CTEPP) Study (Morgan et al., 2004) was performed in collaboration with Battelle Memorial 

Institute as an observational study of preschool children’s exposure to contaminants in their 

everyday environments (i.e., homes and daycare centers). Monitoring was performed from July 

2000 to March 2001 in North Carolina (spanning summer, fall, and winter) and from April 2001 

to November 2001 in Ohio (spanning spring, summer, and fall). The study population consisted 

of 257 children, ages 18 months to five years, and their primary adult caregivers (130 children, 

130 homes, and 13 daycare centers in North Carolina; 127 children, 127 homes, and 16 daycare 

centers in Ohio). Samples were collected over a 48-hr period at each home and daycare center, 

including indoor air, outdoor air, floor dust, soil, hand wipe, solid food, liquid food, and urine. 

Supplemental information included a recruitment survey, a house/building characteristics survey, 

pre- and post monitoring questionnaires, and activity and food diaries. In addition, 20% of the 

9
OH participants were videotaped at home for about 2 hours. Additional samples (hard floor and 

food preparation surface wipes and transferable residues) were collected if the participant 

reported indoor or outdoor applications of pesticides within 7 days of the monitoring period. 

The First National Environmental Health Survey of Child Care Centers (CCC) was performed in 

collaboration with HUD (US Department of Housing and Urban Development) and CPSC (US 

Consumer Product Safety Commission). Samples were collected from August through October 

(summer and fall) 2001, at 168 randomly-selected child care centers nationwide. Many facilities 

reported recent pesticide application (either by professionals or by employees). Samples 

included soil, surface wipes, and transferable residues (C18 Press). A multi-residue chemical 

analysis method was used to measure a large suite of current-use pesticides. The study aimed to 

collect data on pesticide use practices and to characterize the distributions of pesticide 

concentrations in a nationally-representative sample of child care centers in the U.S. 

The study titled Biological and Environmental Monitoring for Organophosphate and Pyrethroid 

Pesticide Exposures in Children Living in Jacksonville, Florida (JAX) was performed in collaboration with CDC (Centers for Disease Control and Prevention) and DCHD (Duval County 

Health Department) in Jacksonville (Duval County), Florida, from August through October 

(summer and fall) 2001. The CDC performed a biomonitoring study to measure metabolites of 

organophosphate and pyrethroid pesticides in a sample of 200 children who were 4-6 years of 

age. The DCHD conducted a home screening survey in a subset of 42 of the homes. The 

screening phase employed a pesticide screening inventory, surface wipes, and urine collection. 

The EPA conducted an observational study in a subset of nine of the homes to evaluate sampling 

and analysis methods and protocols for conducting aggregate exposure estimates for children. 

The aggregate exposure study included the pesticide screening inventory, surface wipes, indoor 

and outdoor air, cotton garment, duplicate diet, and transferable residue measurements, a time 

activity diary, and a urine sample. 

The Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) 

Quantitative Exposure Assessment Study was a collaboration with the University of California at 

Berkeley. This observational study was performed in homes of agricultural workers living in 

Salinas, California. Twenty households with children ages 5 months to 3 years old (10 female 

and 10 male) were monitored during the period of June to October (summer and fall) 2002. 

Samples were collected over a 24-hour monitoring period and included indoor and outdoor air, 

house dust, transferable residues from floors (surface wipes and press samples), transferable 

residues from toys (surface wipes), urine, and cotton union suits and socks. A time/activity diary 

was also administered. The objective of the study was to evaluate sampling and analysis 

methods and study protocols that might be applied in larger studies such as the National 

Children’s Study. 

The Children’s Pesticide Post-Application Exposure Study (CPPAES) was a collaborative field 

study with EOHSI (Environmental and Occupational Health Sciences Institute) in urban New 

Jersey over a two-year period stretching from April 1999 to March 2001. Ten homes with 

children 2-5 years of age participated. Each of the homes had a professional “crack and 

crevice”-type application of a chlorpyrifos-based formulation at the time of the study, but only 

trace amounts of chlorpyrifos were applied in three of the homes. The monitoring period 

typically lasted for two weeks with pre- and multiple post-application samples. Sampling was 

10
comprehensive with indoor air, deposition coupons, surface samples (LWW, Lioy-WeiselWainman sampler), toys, hand wipes, urine, air exchange rate, and time activity diary data 

collected throughout the study, and additional samples consisting of surface wipes, dermal 

wipes, cotton garments, and videotaped activities collected on the second day of the study. 

A field laboratory study titled the Distribution of Chlorpyrifos Following a Crack and Crevice 

Type Application in the US EPA Indoor Air Quality Research Test House (Test House) was 

performed in collaboration with the National Risk Management Research Laboratory (NRMRL). 

The Test House is an unoccupied three-bedroom house in Cary, NC. The study investigated the 

translocation of chlorpyrifos and the spatial and temporal variability of chlorpyrifos levels in air 

and on surfaces following a professional “crack and crevice”-type application onto the floor and 

cabinetry of a kitchen. Samples included air, polyurethane foam (PUF) roller, carpet sections, 

C18 surface press, and surface wipes from multiple rooms. Samples were collected preapplication and on days 1, 3, 7, 14 and 21 post-application. 

The Pilot Study Examining Translocation Pathways Following a Granular Application of 

Diazinon to Residential Lawns (PET) was performed during spring 2001 in six residential homes 

within a 50-mile radius of Durham, NC. Measurements were performed at homes where a 

homeowner applied a turf application of a granular formulation of diazinon. Sampling included 

indoor air (multiple rooms), PUF roller (outdoor and indoor), soil, doormat, high-volume small 

surface sampler (HVS3), dermal surrogate (cotton gloves), urine (adult and child), dog fur 

clippings, dog paw wipes, dog blood, and videotaping (15-min). Samples were collected preapplication and 1, 2, 4 and 8 days post-application. A feasibility study was also performed in a 

single home. The study focused on pesticide translocation and exposure pathways. 

The Dietary Intake of Young Children (DIYC) study was a small observational field study in 

collaboration with RTI. It included three homes where diazinon had been applied (two homes 

with commercial crack and crevice applications and one home with non-professional application) 

and took place between November 1999 and January 2000 (fall and winter). Collected samples 

included indoor air, outdoor air, surface wipes, hand wipes, surface press, food press, food 

samples, PUF roller, entry wipe, and urine. A primary goal of the study was to evaluate the 

potential for exposure to pesticides due to food preparation and handling in the home. 

The Feasibility of the Macroactivity Approach to Assess Dermal Exposure (Daycare) study was 

another collaboration with RTI (Cohen Hubal et al., 2006). In this field study, nine daycare 

centers were identified that reported routine pesticide applications as part of the center’s pest 

control program. In each daycare, screening sampling was conducted to evaluate the distribution 

of transferable pesticide residues on floor surfaces in the area where children spent the most 

time. One daycare was selected for more intensive monitoring during the summer of 2001, 

following a series of regularly scheduled (monthly) applications. Surface sampling and 

videotaping of activities were conducted simultaneously with dermal surrogate (cotton garment) 

sampling to calculate dermal transfer coefficients. 

The Characterizing Pesticide Residue Transfer Efficiencies (Transfer) studies evaluated 

parameters that are believed to affect residue transfer from surface-to-skin, skin-to-object, skinto-mouth, and object-to-mouth. The collaboration with Battelle was a series of controlled 

laboratory studies using fluorescent tracers as surrogates for pesticide residues. The protocol 

11
involved applying fluorescent tracers to surfaces of interest as a residue at levels typical of 

residential pesticide applications, and then conducting controlled transfer experiments varying 

six parameters in a systematic fashion. Repetitive contacts with contaminated surfaces were 

used to measure the following transfers: hand to clean surface, hand to washing solution, and 

hand to mouth. In the mouthing trials, mouthing was simulated using saliva-moistened PUF 

material to measure mass of tracer transferred. Laboratory evaluations were performed to relate 

transfer of tracer to transfer of pesticides (Ivancic et al., 2004; Cohen Hubal et al., 2005). 

The Food Transfer Studies were controlled laboratory experiments investigating pesticide 

transfer from household surfaces to foods and evaluating factors that have been identified as 

important, including surface type, duration of contact, surface loading, and contact pressure 

(applied force). Organophosphate, pyrethroid, and pyrazole insecticides were applied onto 

various household surfaces using a customized spray chamber. Pesticide transfer efficiencies 

were measured for three different foods, with standardized surface contact areas. Amounts of 

pesticide residue transferred to foods were compared to the amounts removed using surface 

wipes. Transfer efficiency (TE) was defined as the amount of pesticide recovered from the food 

item divided by the pesticide concentration or loading level. 

1.8 Exposure and Dose Models 

It is neither within the scope nor the intention of this report to provide a detailed discussion of 

the exposure and dose models that have been developed using these data or applied to these data. 

However, since human exposure research progresses through an iterative series of models and 

measurements, it is often necessary to refer to these models. Models are constructed using 

current knowledge and are subsequently used to identify areas of greatest uncertainty. Modeled 

results are used to direct the focus of the measurement studies to address those identified 

uncertainties. As newly collected data yields new knowledge, models are refined and the entire 

process repeats. At each iteration, real-world data replace default assumptions to produce more 

accurate assessments of exposure and risk. Throughout this document models are mentioned. 

“Algorithms” are the set of deterministic mathematical expressions developed in the Draft 

Protocol for Measuring Children’s Non-Occupational Exposure to Pesticides by all Relevant 

Pathways (Berry et al., 2001) to assess exposure by each route as a function of concentration and 

various exposure factors. The Stochastic Human Exposure and Dose Simulation (SHEDS) 

model (Zartarian et al., 2000) is a physically-based, probabilistic model that predicts multimedia/ 

multipathway exposures and doses incurred eating contaminated foods, inhaling contaminated 

air, touching contaminated surfaces, and ingesting residues from hand- or object-to-mouth 

activities. It combines information on pesticide usage, human activities, environmental concentrations, and exposure and dose factors using Monte Carlo methods. The Exposure Related Dose 

Estimating Model (ERDEM) (Blancato et al., 2004) is a physiologically-based pharmacokinetic 

(PBPK) model used to make reliable estimates of the chemical dose to organs of animals or 

humans. It solves a system of differential equations that describes the organ system, directly 

addressing the uncertainties of making route-to-route, low-to-high exposure, and species-tospecies extrapolations when there are exposures to one or to multiple chemicals. The Children’s 

Dietary Intake Model (CDIM) (Hu et al., 2004) estimates total dietary exposure of children to 

chemical contaminants by accounting for excess dietary exposures caused by chemical 

contaminant transfer from surfaces and/or hands to foods prior to consumption. 

12
2.0 PESTICIDE USE PATTERNS 

Very limited data are available to EPA researchers on what pesticides are currently being used in 

non-occupational environments, where they are being used, and the frequency of use. The EPA 

has not conducted a large scale survey to collect data on pesticide use patterns in the U.S. since 

1990, but use patterns are believed to have substantially changed since that time. The children’s 

observational studies described in this report collected information on household pesticide use as 

ancillary information that could be used to address this serious data gap. Despite the limited 

coverage of geographic regions, a relatively small number of study participants, and the general 

lack of knowledge about the active ingredients in brand name products on the part of consumers, 

valuable information was obtained. The NERL studies described in this section covered a period 

from 1997 to 2001. The indoor residential use of chlorpyrifos was cancelled while data 

collection was still ongoing in several studies (JAX, CCC, and CTEPP). 

The pesticides available to consumers or professionals for use in residential settings have 

changed over time. By the late 1980s the use of most organochlorine pesticides (e.g., DDT, 

chlordane, dieldrin, and heptachlor) was severely restricted in the U.S. The organophosphate 

(OP) insecticides (e.g., malathion, chlorpyrifos, and diazinon), appealing for their high insect 

toxicity, low costs, and low likelihood of pest resistance, quickly filled the void and became the 

pesticides of choice for both consumers and professional pest control operators (Karalliedde et 

al., 2001). The popularity of pyrethroid insecticides increased throughout the 1990s because of 

the following favorable properties: higher insecticidal toxicity, lower mammalian toxicity, and 

more rapid environmental degradation (Baker et al., 2004). Passage of the Food Quality 

Protection Act of 1996 led the EPA to consider aggregate childhood pesticide exposure. The 

OPs were the first class of pesticides whose tolerances were reassessed, leading to withdrawal of 

the registrations for indoor applications of chlorpyrifos and diazinon in 2001 and 2002, 

respectively, because of concern regarding the risk to children. Consequently, pyrethroids have 

become the leading residential insecticides. While household use of diazinon and chlorpyrifos is 

now restricted, these and other OPs are still widely used in agriculture, and some structural uses 

for chlorpyrifos, including the treatment of house foundations, are still approved. 

2.1 Sources of Information 

Important sources of information on pesticide use patterns in non-occupational environments 

include Market Estimates from EPA’s Office of Pesticide Programs (US EPA, 2004), national 

pesticide usage surveys, the Residential Exposure Joint Venture (REJV), the National Health and 

Nutrition Examination Survey (NHANES), and published scientific literature. 

The Office of Pesticide Programs uses proprietary data sources in producing “Market Estimates” 

of pesticide sales and use in various market sectors. According to their estimates, the annual 

amount of insecticide active ingredients used in the home and garden sector declined from 24 

million pounds in 1982, to less than 13 million pounds in 1988. Although the figure rose to 17 

million pounds between 1998 and 2001, it still represents a significant decline from the early 

1980s. In contrast, the amount of herbicides applied steadily increased over the same period, 

nearly doubling from 37 million pounds in 1982 to 71 million pounds in 2001 (US EPA, 2004) 

13
as lawn coverage increased. In 2001, insecticides comprised nearly 60% and herbicides nearly 

30% of the home and garden sector expenditures (US EPA, 2004). 

The REJV is a program administered by eight pesticide registrants and is designed to provide 

home pesticide usage information critical for risk assessments on individual active ingredients as 

well as aggregate and cumulative risk assessments. Pesticide use by over 100,000 households in 

nine regions of the U.S. is recorded, with a year-long monthly diary of all residential pesticide 

applications in more than 4000 households. EPA expects to use the results of this 

comprehensive pesticide use survey to refine or replace many of its residential exposure default 

assumptions. Access to REJV results is restricted as confidential business information, thus only 

very limited data are publicly available. 

Results from two other national surveys are available: the National Household Pesticide Usage 

Study (US EPA, 1980; Savage et al., 1981) and the National Home and Garden Pesticide Use 

Survey (US EPA 1992). The National Household Pesticide Usage Study (1976-1977) found that 

91% of the more than 8200 households surveyed reported using pesticides in their home, garden, 

or yard. According to the slightly more recent National Home and Garden Pesticide Use Survey 

(1990), 75% of American households reported using insecticides. These surveys, it should be 

noted, are old and the results are not considered relevant to current pesticide use patterns. 

NHANES is an ongoing assessment of the exposure of the U.S. population to environmental 

chemicals. Beginning with the 1999-2000 cycle, the interview included, at the request of EPA, 

questions on pesticide applications performed in the past month. According to the most recent 

survey (2001-2002), 18% of households used insecticides inside the home within the past month, 

nearly 40% of which were professional treatments. Of households with private yards, 20% 

reported pesticide applications in the yard during the month, roughly 36% of which were 

professional treatments. NHANES does not report results by region or by season. 

Studies in the open literature can also help to identify pesticide use patterns. Davis et al. (1992), 

Bass et al. (2001), Curwin et al. (2002), Freeman et al. (2004), and Carlton et al. (2004) address 

pesticide use patterns in various geographic locations within the U.S., including Missouri, 

Arizona, Iowa, Texas, and New York. 

A study conducted in Missouri from June 1989 to March 1990 using telephone interviews (Davis 

et al., 1992) examined pesticide use in the home, garden, and yard. Nearly all 238 families 

(98%) used pesticides at least one time per year, and two-thirds used pesticides more than five 

times per year. Pesticides were most commonly used inside the home (80%), followed by in the 

yard (57%). Flea collars were the most popular pest control product (50%). Diazinon and 

carbaryl were identified as the two most commonly used active ingredients at that time. 

The community-based survey conducted by Bass et al. (2001) in Douglas, Arizona in 1999 

identified pesticides used in the home, use and storage locations, and disposal methods. All 

(100%) of the 107 randomly chosen study participants reported using pesticides in the six 

months prior to the survey, although only 75% reported pest problems. Over 30% used a 

professional exterminator. A total of 148 pesticide products, representing more than 50 unique 

active ingredients, were catalogued (1.4 products per home). The synergist piperonyl butoxide 

14
(34%) was most common, followed by pyrethrins (24%), permethrin (18%), allethrin (17%), 

diazinon (16%), and boric acid (13%). The majority of the pesticides were stored inside the 

house (70%), typically in the kitchen (45%). 

Curwin et al. (2002) investigated the differences in pesticide use for 25 farm homes and 25 nonfarm homes in Iowa. The target pesticides included atrazine, metolachlor, acetochlor, alachlor, 

2,4-D, glyphosate, and chlorpyrifos. Among the non-farm households, 84% used pesticides in 

their homes or on their lawns or gardens. Only 17% of reported residential pesticide use was by 

commercial application. 

Freeman et al. (2004) examined pesticide use patterns during the summer 2000 and winter 2000-

2001 seasons among families with very young children in a Texas border community. Pesticide 

use inside the home showed seasonal variation (82% of homes treated in summer versus 63% in 

winter). The primary room treated was the kitchen, and the primary structures treated were the 

floors, lower walls, and dish cupboards. The pesticides used were typically pyrethroid 

formulations. For nearly all of the pesticides analyzed, no differences were found in pesticide 

levels in house dust based on family reports of pesticide use in the home or yard. 

Carlton et al. (2004) surveyed stores in New York City, NY in mid-2003 to determine whether 

the phase-out of chlorpyrifos and diazinon had been effective and what alternative pesticides 

were available. The authors found the phase-out to be more effective for chlorpyrifos than for 

diazinon. The summer after chlorpyrifos sales were to have ended, chlorpyrifos-containing 

products were found in only 4% of stores that sold pesticides; however, after diazinon sales were 

to have ended, 18% of stores surveyed, including 80% of supermarkets, still stocked diazinoncontaining products. Lower toxicity pesticides, including gels, bait stations, and boric acid, were 

available in only 69% of the stores and were typically more expensive. 

The children’s exposure research program collected pesticide use information from homes and 

daycare centers in the MNCPES, JAX, CTEPP, CCC, and Daycare studies. Information on 

collection methods is available in Table 2.1. In the context of this report, pesticide use patterns 

include application frequency, locations, types, methods and active ingredients, as well as 

pesticides identified in inventories and detected in screenings. The following are highlights of 

the data collected on pesticide use patterns in these studies. A thorough discussion of MNCPES 

storage and use patterns is found in Adgate et al. (2000). 

15
Table 2.1 Pesticides use information collection methods. 

Study Year Setting Inventory Questionnaire 

Screening 

Wipes 

MNCPES 1997 Residence Brand name, type, EPA 

registration number, use in 

past year. 

Baseline usage (past year) by 

participant recollection. Recent 

use (past week and during 

monitoring period). 

No 

CTEPP 2000-

2001 

Residence and 

Daycare 

Center 

None Baseline usage (ever) of 

insecticides, herbicides, 

fungicides, or shampoos. Recent 

use (past week) of any pesticide. 

No 

CCC 2001 Daycare 

Center 

None Usage frequency (categories) 

and locations for specific active 

ingredients. Questionnaire 

administered to Center Director 

or professional applicator. 

Yes 

JAX 2001 Residence Brand name, type, EPA 

registration number. 

Use in past 6 months, use 

frequency, use location, and 

targeted pest noted for each 

product. 

Usage frequency (categories), 

locations, application methods, 

and anticipated future use. 

Yes 

Daycare 2000 Daycare 

Center 

None Specific active ingredient 

verified by professional 

applicator. 

Yes 

16
2.2 Application Frequency 

The frequency of pesticide application, typically over the past month or year, is generally 

gathered through questionnaires. Although there is little supporting empirical evidence, it is 

believed that the frequency of application, along with the form and chemical properties of the 

pesticide, is an important determinant of indoor air and surface concentrations. It is assumed that 

residue levels within a residence will rise with increasing pesticide application frequency. 

Conversely, infrequent pesticide application is assumed to decrease the likelihood of measuring 

pesticide residues. Arguably, the more frequently pesticide applications occur, the more likely 

the occupant is to have contact with pesticide residue. 

• As presented in Table 2.2, about 20% of study participants in Jacksonville, FL (JAX) 

reported using pesticides in the past seven days (August to October 2001) compared to 

14% in CTEPP-NC (July 2000 to March 2001), 13% in CTEPP-OH (April to November 

2001), and only 10% in Minnesota (MNCPES) (May to August 1997). This provides 

some evidence of a pattern of higher application frequencies in warmer climates. The 

North Carolina study was the only one to include winter months; the percentage would 

likely be higher if winter months were excluded. 

• About the same proportion (unweighted) of participants that used pesticides in the past 

month (or planned to use them in the next month) in JAX (51%), used them in the past 

six months in MNCPES (52%). The percentage of JAX participants is substantially 

higher than 18-23% reporting insecticide use in the past month in NHANES (Table 2.2). 

• Differences according to geographical region become more evident in the CTEPP studies 

(Table 2.3) when focusing on insecticides and rodenticides, as 74% of the participants in 

warmer climate North Carolina reported using insecticides or rodenticides compared to 

only 51% in colder climate Ohio. 

• In Minnesota (MNCPES), 88% of the participants used pesticides in the past year, 

slightly more than the 84% reported by Curwin et al. (2002) in Iowa but less than the 

98% reported by Davis et al. (1992) in Missouri and the 100% reported by Bass et al.

(2001) in Arizona. 

• In the CCC study, 74% of the facilities reported application of pesticides in the last year 

(63% reported interior and 42% reported exterior applications), and 7% were unsure if 

any application occurred. Up to 107 pesticide applications per year were reported. 

• About a third of the interior and a quarter of the exterior applications in the nationwide 

CCC study were performed on a monthly basis. In the Daycare study, monthly or more 

frequent pesticide applications were anecdotally found to be standard practice in the 

Raleigh-Durham area of North Carolina. 

17
Table 2.2 Proportion (unweighted) of participants reporting pesticide use by study. NHANES 

participant responses are included for comparison. 

Study 

Use within the past 

seven days 

Use within the past

one month 

Use within the past 

six months 

CTEPP-NC 14% -- a -- 

CTEPP-OH 13% -- -- 

JAX 20% 51% -- 

MNCPES 10% b -- 52% 

NHANES 99-00 -- 23% c -- 

NHANES 01-02 -- 18% c -- 

a

 Information not available 

b

 Recruited households 

c

 Restricted to use inside of home 

Table 2.3 The proportion of CTEPP participants reporting use of four types of pesticides. 

Type of Pesticide North Carolina Ohio 

Herbicides 38% 50% 

Insecticides / Rodenticides 74% 51% 

Fungicides 6% 4% 

Shampoos / Lotions 8% 9% 

18
2.3 Application Locations 

Although applied pesticides are redistributed throughout a home following an application, a 

concentration gradient exists with higher concentrations in the application room and lower 

concentrations in more distant rooms (Stout and Mason, 2003). Since residential applications 

may be performed by someone other than the occupant (e.g., professional pest control service, 

gardener, lawn service, or property management), the occupant may not know which locations 

were treated. 

• In JAX, 58% reported treating all rooms in the home, and 15% reported treating just the 

kitchen. 

• The most commonly treated room in the CCC study was the kitchen (62%), followed by 

the bathroom (52%) (Figure 2.1). All rooms were treated in 23% of the centers. 

• Areas treated by professional crack and crevice applications in CPPAES represented 93% 

of the homes’ living areas. 

0%

10%

20%

30%

40%

50%

60%

70%

Kitchen Bathroom Multipurpose

room

Classroom Other

room

All

sampled

rooms

Room

Weighted % of centers applying 

pesticides in various rooms

Figure 2.1 Weighted percentage of child care centers reporting treatment of various rooms in the 

Child Care Centers (CCC) study. 

19
2.4 Application Types and Methods 

The three common types of pesticide applications in the non-occupational environment are 

broadcast, total release aerosol, and crack-and-crevice. A broadcast application spreads 

insecticide onto broad surfaces, typically large sections of walls, floors, ceilings, or in and 

around trash containers (Rust et al., 1995). Total release aerosols, also known as “foggers” or 

"bug bombs," contain propellants that release their contents at once to fumigate a large area. 

Alternatively, a crack-and-crevice application is the application of small amounts of insecticide 

into areas where pests typically harbor or enter a building. Cracks and crevices are commonly 

found between cabinets and walls, at expansion joints, and between equipment and floors (Rust 

et al., 1995). Crack and crevice type applications, which usually produce lower airborne 

concentrations and surface loadings than broadcast or total release type applications, are favored 

by professional pest control services. 

Method of pesticide application (as differentiated from “type” of application) refers to the 

equipment or product form used, and may include aerosol sprayer, hand pump sprayer, hose end 

sprayer, spritz sprayer, hand trigger sprayer, liquid, fogger, gel, granules/dust/powder/pellets, 

lotion, shampoo, bait station/trap, candle/coil, fly strip, pet collar, and spot-on pet treatment. 

• Only very limited information on application type and method was collected in any of the 

field study questionnaires. 

• In CCC, 36% of the interior applications were reported by the center directors as crack 

and crevice, and only 2% were reported as broadcast. In the Daycare study, all observed 

pesticide applications were crack and crevice. 

• The most common application methods reported in JAX were as follows: 37% hand 

pump sprayer, 24% aerosol can, 3% fogger, and 3% bait. 

• Applications in JAX were more likely to be performed by the respondent or respondent’s 

family member (41%) than by a professional service (35%). These results are similar to 

NHANES 01-02, where 66% of the survey respondents reported non-professional 

treatments compared to professional treatments that were reported by 40% of the 

respondents. These results are also similar to the survey by Bass et al. (2001) in Douglas, 

Arizona, where 30% used professional services. 

2.5 Pesticides Identified in Inventories, Records and Wipe Samples 

• Pesticide products were found in 86% of the 36 homes inventoried in the JAX study 

(Table 2.4), with up to three products per household. Pyrethroids were the most common 

active ingredient (67% of homes), primarily cypermethrin (25%) and allethrin (12%), 

followed by imiprothrin, pyrethrins, and tralomethrin (all 14%). Only one 

organophosphate insecticide (diazinon) and one insect repellent (DEET) were found. 

• The most commonly inventoried pyrethroids in JAX (Table 2.4) corresponded well with 

commonly reported pyrethroids in the Residential Exposure Joint Venture (Table 2.5). 

• Cataloguing of pesticides in the CCC study (Table 2.6) gave results similar to JAX, with 

pyrethroid products most commonly identified (second only to products with unknown 

20
active ingredients). 

• The finding of 145 application events (Table 2.6) with unidentified active ingredients in 

the CCC study suggests that tracking of pesticide use in and around daycare facilities 

may require improved recordkeeping. 

• As reported in Adgate et al. (2000), pesticide products were found in 97% (weighted) of 

the MNCPES households. The weighted mean number of pesticide products used per 

household was 3.1. Participants reported that fewer than 25% of the pesticides 

inventoried in their homes were used during the past year. 

• In MNCPES, DEET-containing products were used in 47% of the homes during the last 

year (Table 2.7). 

• Repellents, pyrethrins and pyrethroids, organophosphates, chlorophenoxy herbicides, and 

carbamates were present in more than 20% of the MNCPES households (Table 2.7). 

• In the Daycare study, professional pest control services applied pyrethroid or pyrethrin 

pesticides in six of the eight facilities (data not presented). Esfenvalerate was applied in 

two facilities while cyhalothrin, pyrethrins, cypermethrin, and tralomethrins were each 

used in one. 

• Cypermethrin, cis-permethrin, and trans-permethrin were detected in over 80% of the 

surface wipe samples collected in 46 homes in JAX (Table 2.8), consistent with the 

pesticide inventories. Chlorpyrifos and diazinon, although not identified in the 

inventories, were present in 89% and 91%, respectively, of the surface wipe samples. 

• Permethrin and cypermethrin were the most frequently detected pyrethroid pesticides in 

both JAX (homes) and CCC (childcare centers) (Table 2.8). Chlorpyrifos and diazinon 

were the most frequently detected OPs, at frequencies comparable to permethrin. 

• As of 2001, the synthetic pyrethroids appeared to be the most frequently used insecticides 

for indoor applications in homes and child care centers. It is anticipated that their use has 

become even more common since the cancellation of indoor use registrations of 

chlorpyrifos (2001) and diazinon (2002). 

2.6 Demographic Factors Influencing Applications 

• As reported by Adgate et al., (2000), there were no statistically significant differences in 

the weighted total number of products found or reportedly used in MNCPES based on 

either population density (urban versus non-urban households) or other sociodemographic factors including race, ethnicity, home type, income, and level of education. 

• Chi square analysis of CTEPP data (not presented) found no association between having 

applied pesticides within the past week and either income class or urban/rural status. 

21
Table 2.4 Pesticides inventoried in 36 households in Jacksonville, FL (JAX) in fall 2001. 

Active Ingredient Pesticide Class 

Number of Homes Where 

Found (% of Homes) 

Cypermethrin Pyrethrins/Pyrethroids 9 (25%) 

Allethrin Pyrethrins/Pyrethroids 8 (22%) 

Pyrethrins Pyrethrins/Pyrethroids 5 (14%) 

Imiprothrin Pyrethrins/Pyrethroids 5 (14%) 

Tralomethrin Pyrethrins/Pyrethroids 5 (14%) 

MGK 264 a Synergist 4 (11%) 

Permethrin Pyrethrins/Pyrethroids 4 (11%) 

Fipronil Phenylpyrazole 4 (11%) 

Piperonyl butoxide Synergist 4 (11%) 

Hydramethylnon Aminohydrazone 3 (8%) 

Tetramethrin Pyrethrins/Pyrethroids 3 (8%) 

Cyfluthrin Pyrethrins/Pyrethroids 2 (6%) 

Esfenvalerate Pyrethrins/Pyrethroids 2 (6%) 

Prallethrin Pyrethrins/Pyrethroids 2 (6%) 

Bifenthrin Pyrethrins/Pyrethroids 1 (6%) 

DEET Repellent 1 (6%) 

Diazinon Organophosphate 1 (6%) a

 N-octyl bicycloheptene dicarboximide 

Table 2.5 Most commonly applied pyrethroids in 1217 households with complete 12 month 

REJV survey data, as reported by Ozkaynak (2005). 

Pyrethroid Pesticide 

Number of Homes Where 

Applied (% of Homes) 

Permethrin 518 (43%) 

Pyrethrins 472 (39%) 

Piperonyl Butoxide 461 (38%) 

Allethrin 437 (36%) 

Tetramethrin 342 (28%) 

Phenothrin 293 (24%) 

Tralomethrin 279 (23%) 

Cypermethrin 163 (13%) 

Resmethrin 106 (9%) 

Bifenthrin 99 (8%) 

Cyfluthrin 46 (4%) 

Fenvalerate 37 (3%) 

Esfenvalerate 25 (2%) 

Deltamethrin 22 (2%) 

Prallethrin 13 (1%) 

Cyhalothrin 4 (<1%) 

22
Table 2.6 Number of pesticide products applied during one year (2001) in 168 child care centers 

(CCC), as reported by the center directors and/or professional applicators. 

Pesticide Class or Type 

Number of Products Applied in Past Year

(Unweighted % of All Products) 

Unknown 145 (39%) 

Pyrethroids 93 (25%) 

Phenyl pyrazole or unclassified insecticide 44 (12%) 

Pesticide mix 22 (6%) 

Fungicide/insecticide 20 (5%) 

Organophosphate 10 (3%) 

Glueboard/Mouse traps 7 (2%) 

Carbamates 6 (2%) 

Juvenile hormone mimic insecticide 6 (2%) 

Coumarin rodenticides 5 (1%) 

Herbicides 3 (1%) 

Insecticides 3 (1%) 

Unclassified acaricide 3 (1%) 

Unclassified insecticide 3 (1%) 

Biopesticides 2 (1%) 

Pheromone 1 (<1%) 

Phosphoramidothioate acaricide 1 (<1%) 

Rodenticides 1 (<1%) 

Table 2.7 Pesticides inventoried and used in 308 households in Minnesota (MNCPES) in 

summer 1997 (adapted from Adgate et al., 2000). 

Active Ingredient Pesticide Class 

Homes Where Found 

(Weighted Percent) 

Homes Where Used 

in the Past Year 

(Weighted Percent) 

DEET Repellent 196 (58%) 162 (47%) 

Piperonyl butoxide Synergist 152 (45%) 91 (25%) 

Pyrethrins Pyrethrins/Pyrethroids 147 (43%) 88 (25%) 

MCPA Chlorphenoxy herbicide 107 (35%) 55 (17%) 

Permethrin Pyrethrins/Pyrethroids 93 (35%) 65 (15%) 

Chlorpyrifos Organophosphate 89 (29%) 55 (17%) 

Propoxur Carbamate 84 (25%) 53 (17%) 

MGK 264 a Synergist 83 (25%) 43 (12%) 

Allethrin Pyrethrins/Pyrethroids 81 (24%) 49 (13%) 

2,4-D Chlorphenoxy herbicide 74 (23%) 37 (11%) 

Diazinon Organophosphate 65 (18%) 37 (11%) 

Glyphosoate Aminophosphate 62 (18%) 37 (12%) 

Tetramethrin Pyrethrins/Pyrethroids 62 (18%) 32 (8.5%) 

Resmethrin Pyrethrins/Pyrethroids 60 (20%) 24 (8.1%) 

Carbaryl Carbamate 50 (14%) 24 (5.4%) 

a

 N-octyl bicycloheptene dicarboximide 

23
Table 2.8 Detection frequencies of target analytes in soil and wipe samples in the CCC study 

(weighted) and in screening wipe samples collected in JAX (unweighted). 

CCC JAX 

Compound 

% Detect in 

Soil Samples 

% Detect in Floor 

Wipes 

% Detect in 

Surface Wipes 

% Detect in 

Surface Wipes 

PYRETHROIDS 

cis-Allethrin 5 2 0 22 

trans-Allethrin 5 2 0 22 

Bifenthrin 14 5 4 20 

Cyfluthrin 7 7 1 20 

lambda-Cyhalothrin 6 7 5 9 

Cypermethrin 8 23 9 80 

Delta/Tralomethrin 5 2 0 15 

Esfenvalerate 9 6 0 30 

cis-Permethrin 12 63 48 89 

trans-Permethrin 15 64 64 87 

Resmethrin 5 3 6 0 

Sumithrin 5 2 1 4 

Tetramethrin 5 2 0 13 

ORGANOPHOSPHATES 

Acephate 50 3 0 7 

Azinphos methyl 15 1 0 2 

Chlorpyrifos 21 67 76 89 

Chlorpyrifos oxon 11 1 1 0 

Demeton S 11 0 0 0 

Diazinon 19 53 43 91 

Diazinon oxon 13 17 8 17 

Dichlorvos 11 0 0 2 

Dimethoate 11 1 0 0 

Disulfoton 11 0 0 0 

Ethion 11 1 0 2 

Ethyl parathion 11 1 0 0 

Fonofos 12 0 0 0 

Malathion 12 18 5 20 

Malathion oxon 11 0 0 0 

Methamidophos 11 2 1 0 

Methidathion 11 1 1 0 

Methyl parathion 11 0 0 0 

cis-Mevinphos 11 21 7 7 

trans-Mevinphos 11 5 0 4 

Naled 11 0 0 0 

Phosmet 11 2 0 4 

OTHER PRODUCTS 

Fipronil 11 8 10 7 

Piperonyl butoxide 12 23 11 50 

24
3.0 AIR CONCENTRATION MEASUREMENTS 

3.1 Introduction and Data Availability 

Children are exposed to residential pesticides via the ingestion, dermal, and inhalation routes. Of 

these routes, inhalation is the best characterized and requires measurements that are simple to 

collect in field studies. Estimating absorption via inhalation relies on measured airborne 

chemical concentrations and on relatively few default exposure factor assumptions, such as the 

inhalation rate and time spent in specific locations. Since indoor pesticide concentrations are 

typically higher than outdoor concentrations, and since young children spend the majority of 

their time indoors, indoor concentrations account for the bulk of their inhalation exposure. 

Absorption via the inhalation pathway involves the uptake of vapors and particle-bound residues 

present in the air. It is generally assumed that inhaled vapors will be readily absorbed across the 

alveolar membrane into the bloodstream (at least for soluble compounds). Particle-bound 

residue may vary in size and composition, both of which may influence thoracic penetration and 

affect absorption. Inhaled particle-bound contaminants trapped in upper airway (nasal and upper 

lung) mucosa may also be subsequently ingested. 

The methods for measuring of airborne pesticide concentrations are well-developed and easily 

implemented indoors and outdoors using stationary or personal samplers. The methods involve 

collecting gases and/or particle-bound residues onto filters and sorbent media (the two are 

combined so that no distinction is made between gases and particle-bound residues). Stationary 

samplers are typically placed adjacent to treated areas and/or in the location where the participant 

spends the most time. Samplers may be placed at several locations throughout the home to 

investigate the spatial distribution of pesticides. Stationary samplers are located at specified 

heights above the floor to represent the assumed breathing area of the study participants. 

Personal samplers are worn by the study participants near the breathing zone. Either type of 

sampler may be modified with a size selective inlet to exclude specific particle size fractions. 

Sampling media vary but often consist of a pre-filter in tandem with a sorbent composed of 

polyurethane foam (PUF) or polymeric resin beads (e.g., XAD). 

The sampling approaches and methods for each study are described in Table 3.1. Since air 

sampling techniques are fairly standardized, the methods are consistent across studies. In the 

large observational field studies, air samples were collected over multiple days for reasons that 

included reducing measurement error due to day-to-day variability, improving detection limits, 

and reducing costs associated with changing and analyzing filters. The smaller, focused studies 

typically employed multiple, consecutive 24-hour sampling periods to capture temporal 

variability. Personal sampling was attempted in only one study, MNCPES, but compliance 

issues were noted. 

3.2 Pesticide Presence 

All pesticides included in this report have been used in residential settings. Because of the 

potentially long persistence of some pesticides in the indoor environment (Gurunathan et al.,

1998), they may be detected even in the absence of a recent application. Detection frequencies 

for indoor and outdoor samples are presented graphically in Figure 3.1. While detection 

25
26

frequency corresponds inversely to the limit of detection (LOD), the LOD for each compound is 

relatively consistent across the large observational field studies. The exception to this is the 

NHEXAS-Arizona study, which employed a collection method with a relatively small sample 

volume, resulting in a higher LOD. The LODs for each pesticide by study are presented in Table 

3.2. 

• Detection limits (Table 3.2) varied by as much as an order of magnitude across studies. 

Within studies, detection limits were similar for organophosphate and pyrethroid 

insecticides. Detection limits are influenced by sample volume (Table 3.1). For 

example, the much lower detection limits for chlorpyrifos and diazinon in MNCPES 

compared to NHEXAS-AZ reflects the much larger volume sampled in MNCPES. 

• The compounds most frequently detected in indoor air (Figure 3.1) were the 

organophosphate (OP) insecticides chlorpyrifos, (typically > 90%) and diazinon 

(typically > 75%), followed by the pyrethroid insecticide permethrin (typically > 50%). 

• The insecticides most frequently detected in outdoor air (Figure 3.1) were also 

chlorpyrifos and diazinon, but the detection frequencies were lower and more variable 

across studies. 

• Chlorpyrifos was detected at a high frequency (Figure 3.1) even in those studies 

conducted after its indoor residential use was restricted (JAX and CHAMACOS). 

• The pesticide degradation products of chlorpyrifos and diazinon, TCPy and IMP, 

respectively, were frequently detected in air samples collected in CTEPP (Figure 3.1); 

none of the other studies included these as target analytes. 
27

Table 3.1 Summary of air sample collection methods. 

Study 

Samples 

Collected 

Cohort 

Size 

Sampling 

Location 

Sampling 

Device Device Details Sample Volume 

Collection 

Frequency 

Collectio

Pesticid

NHEXAS-AZ Indoor 14 Home Pumps w/ 10 :m 

inlet, PUF and Teflon-coated glass filters 

Intermittent sampling (total of 12 h over 3 d) 

Approx 3 m3 (4 L/min for 12 hr) 

Integrated 3-day monitoring period 

No 

MNCPES Personal 

Indoor Outdoor 

70 97 52 

Home Pumps w/ XAD 

cartridge and quartz filter 

Backpack carrying case for personal, sound-proof enclosure 

Approx 10.8 m3 (1.25 L/min for 144 hr) 

Continuous, Days 1-7, integrated 

No 

CTEPP Indoor 

Outdoor 

257 Home and 

Daycare 

Pumps w/ 10 :m 

inlet, quartz fiber filter and XAD-2 cartridge 

Indoor: Styrofoam box w/ cooling fan; Outdoor: plastic dog house. 75 cm height. 

Approx 12 m3 (4 L/min for 48 hr) 

One 48-hr sample No 

JAX 2001 Indoor 

Outdoor 

9 Home Constant-flow 

battery powered pump w/ PUF cartridge 

Breathing-zone height indoor, 1.5 m height outdoor 

Approx 5.5 m3 (3.8 L/min for 24h) 

One 24-hr sample Yes, indo

CHAMACOS Indoor 

Outdoor 

20 Home Sampling pump 

with PUF cartridge

Tamper-resistant box 

Approx. 3.6 m3 (2.5 L/min for 24 hr) 

One 24-hr sample No 

CPPAES Indoor 10 Home Harvard Sampler 

w/ PM10 inlet, 

cotton filter impregnated w/ activated carbon 

Placed in room most frequented by child, approx 1 m high. 

Approx.14 m3 (24h) and 29 m3 (48h) 

Four 24-hr samples on days 0-3; four 48-hr samples days 3-11 

Yes, indo

Test House Indoor 1 Test House Low volume pump 

w/PUF 

Multiple rooms Approx 5 m3 (3.5 

L/min for 24 hr) 

Time series over 21 days 

Yes 

PET Pilot Study Indoor 6 Home Low volume pump 

w/PUF 

Living room and child’s bedroom 

Approx 5 m3 (3.5 L/min for 24 hr) 

24-hr samples: Pre-application and days 1, 2, 4, & 8 post-application 

Yes, lawn applicatio

DIYC Indoor 

Outdoor 

3 Home Pump w/XAD Placed in room 

most frequented by child, 

Approx. 11.5 m3

(8 L/min for 24 hr)

One pre- and six post-application measurements 

Yes, indoprofessioresident) 
Table 3.2 Limits of detection (ng/m3) for air samples by compound and study. 

Compound Chlorpyrifos Diazinon 

cisPermethrin transPermethrin Cyfluthrin TCPy IMP 

NHEXAS-AZ 3.2 2.1 --a -- -- -- -- 

MNCPES 0.10 0.10 0.09 0.09 -- -- -- 

CTEPP NC 0.09 0.09 0.09 0.09 0.87 0.09 0.09 

CTEPP OH 0.09 0.09 0.39 0.33 0.87 0.09 0.09 

JAX 1.0 0.4 1.0 1.0 1.2 -- -- 

CHAMACOS 0.3 0.3 0.6 0.6 7.0 -- -- 

CPPAES 2.0 -- -- -- -- -- -- 

DIYC -- 1.2 -- -- -- -- -- 

PET -- 1.0 -- -- -- -- -- 

a Blank cells (--) indicate that the pesticide or metabolite was not measured in the study. 

28
Detection Frequency in Indoor Air

Chlorpyrifos TCPY Diazinon IMP c-Perm t-Perm Cyfluthrin

0

10

20

30

40

50

60

70

80

90

100

NHEXAS-AZ MNCPES CTEPP-NC CTEPP-OH CHAMACOS

JAX CPPAES Test House PET DIYC

Detection Frequency (%)

Detection Frequency in Outdoor Air

Chlorpyrifos TCPY Diazinon IMP c-Perm t-Perm Cyfluthrin

0

10

20

30

40

50

60

70

80

90

100

NHEXAS-AZ MNCPES CTEPP-NC CTEPP-OH CHAMACOS JAX

Detection Frequency (%)

Figure 3.1 Frequency of detection of pesticides measured in indoor and outdoor air in selected 

studies. 

29
3.3 Comparisons of Air Concentrations 

Previous studies have reported post-application concentrations of semi-volatile pesticides in air 

that may reach levels representing considerable exposure by the inhalation route (Byrne et al.,

1998; Fenske et al., 1990; Lewis et al., 2001). Low measurable airborne levels have also been 

reported even in the absence of a recent application event (Lewis et al., 1994; Whitmore et al.,

1994). Lognormal probability plots and box-and-whisker plots graphically depicting the 

(unweighted) measurements of compounds of interest in our studies are presented in Figures 3.2 

through 3.5. The median and 95th percentile concentrations are presented in Table 3.3 (complete 

summary statistics are presented in Tables A.1 through A.7 in Appendix A). 

• For pesticides measured in indoor and outdoor air, the observed concentrations typically 

approximate lognormal distributions, as demonstrated in the lognormal probability plots 

in Figures 3.2 and 3.3. 

• Despite differences in the lengths of the sample collection periods (1 to 7 days), the indoor chlorpyrifos concentrations observed across the large observational field studies are 

similar in their variability, as demonstrated by similar slopes in the probability plot 

(Figure 3.2). Similar variability over varying collection periods suggests that air 

concentrations are reasonably consistent from day-to-day in the absence of a recent 

application. 

• Comparison of air concentrations across studies in the box-and-whisker plots (Figure 3.4) 

finds that, as expected, pesticide concentrations in smaller studies, where measurements 

immediately followed an application, are much higher than in the larger observational 

field studies; for example, note the high indoor chlorpyrifos levels measured in CPPAES 

and the Test House. 

• Median concentrations are typically an order of magnitude higher indoors than outdoors 

(Table 3.3). Two notable exceptions are JAX and CHAMACOS. In the JAX samples, 

collected in a community with high year-round pesticide usage, outdoor diazinon and cisand trans-permethrin levels are nearly as high as indoor levels. In the CHAMACOS 

samples, collected in an agricultural community, median outdoor diazinon levels exceed 

indoor levels. 

• The low pesticide concentrations routinely measured outdoors (notwithstanding the 

exceptions noted above) together with the relatively short amount of time that young 

children typically spend outdoors suggest that inhalation of outdoor air is not an 

important contributor to their aggregate pesticide exposure. 

• The median indoor concentrations in the large observational field studies are higher for 

the organophosphates (OPs) than for the pyrethroids (Figure 3.4). Not only do OPs tend 

to have higher vapor pressure, but at the time these studies were conducted, OPs still 

dominated the marketplace. Detectable levels of chlorpyrifos and diazinon are likely to 

exist for some time after restriction of their indoor uses due continued use of existing 

home inventories and reemission from indoor surfaces serving as sinks (such as carpet). 

30
• In indoor air measured in CTEPP (Figure 3.6), a relationship is evident between 

chlorpyrifos and its degradation product TCPy. The same is true for diazinon and its 

degradation product IMP. The nearly log-log relationship suggests a power relationship, 

and at the median level the degradate is present at about 25 to 30% of the concentration 

of its parent. Accordingly, the metabolites/degradates measured in urine may reflect 

exposure to both the parent pesticide and the degradate, not just to the parent compound 

as is often assumed. 

• Environmental concentrations of the degradation products were not measured in any of 

the small, pilot-scale studies, thus the degradate-to-parent ratio immediately following 

application is unknown. 

Table 3.3 Median and 95th percentile air concentrations (ng/m3, unweighted) for frequently 

detected pesticides. 

Chlorpyrifos Diazinon cis-Permethrin trans-Permethrin 

Study Location P50 P95 P50 P95 P50 P95 P50 P95 

Indoor 3.37 164.7 5.59 219.6 --a NHEXAS-AZ -- -- -- 

Outdoor NDb ND ND ND -- -- -- -- 

Personal 1.52 16.86 0.28 4.66 0.20 2.07 <0.09 1.72 

Indoor 1.85 30.25 0.27 8.59 0.09 1.26 <0.09 1.26 

MNCPES 

Outdoor <0.10 0.19 <0.10 0.22 <0.09 0.15 <0.09 0.48 

CTEPP-OH Indoor 1.75 21.69 0.97 56.87 0.28 1.63 0.23 1.04 c

Outdoor 0.20 1.13 0.15 1.49 0.28 0.95 0.23 0.66 

CTEPP-NC Indoor 6.07 62.22 2.03 63.66 0.41 7.79 0.27 7.16 c

Outdoor 0.28 3.99 0.09 0.98 0.06 0.47 0.06 0.30 

JAX Indoor 20.37 84.92 4.64 28.04 0.71 92.47 3.06 134.3 

Outdoor 3.77 6.62 3.53 6.76 2.13 2.29 2.50 10.24 

Indoor 1.90 NAd 1.80 NAd 0.50 NAd <0.10 NAd CHAMACOS 

Outdoor 0.90 NAd 2.80 NAd 0.10 NAd <0.10 NAd

CPPAES e Indoor 149.0 815.6 4.55 23.88 -- -- -- -- 

Test House e Indoor 290.0 1000 -- -- -- -- -- -- 

PET Indoor -- -- 45.6 562 -- -- -- -- 

DIYC Indoor -- -- 1800 4900 -- -- -- -- 

a

 Blank cells indicate the pesticide was not measured in the study 

b

 ND = not detected 

c

 CTEPP samples collected at both homes and daycares 

d

 NA = summary statistic not available at time the report was prepared 

e

 Day 1 measurements only, multiple rooms 

31
 

Figure 3.2 Log probability plots for chlorpyrifos, diazinon, and cis-permethrin measured in large 

observational field studies. Only values above the limit of detection are plotted. 

32
Figure 3.3 Log probability plots for trans-permethrin, TCPy, and IMP measured in large 

observational field studies. Only values above the limit of detection are plotted.

33
Figure 3.4 Indoor and outdoor air concentrations of chlorpyrifos, diazinon, and cis-permethrin 

measured in selected studies. Legend: AZ = NHEXAS-AZ, MN = MNCPES, NC HM = 

CTEPP-NC Home, NC DC = CTEPP-NC Daycare, OH HM = CTEPP-OH Home, OH DC = 

CTEPP-OH Daycare, CHA = CHAMACOS, TEST = Test House.

34
Figure 3.5 Indoor and outdoor air concentrations of trans-permethrin and TCPy measured in 

selected studies. Legend: AZ = NHEXAS-AZ, MN = MNCPES, NC HM = CTEPP-NC Home, 

NC DC = CTEPP-NC Daycare, OH HM = CTEPP-OH Home, OH DC = CTEPP-OH Daycare, 

CHA = CHAMACOS, TEST = Test House. 

35
Figure 3.6 Log-scale relationships between levels of parent pesticide (ng/m3) and degradate 

(ng/m3) measured in CTEPP. Left Panel: Chlorpyrifos with TCPy. Right Panel: Diazinon with 

IMP. 

36
3.4 Differences Related to Location 

This section addresses differences in potential for exposure related to geographic region, 

population density (urban vs. rural), and home vs. daycare environment. There is available 

evidence to support all three of these location-related factors as having a discernable impact on 

pesticide exposure. 

The large observational field studies were conducted in several geographical regions. A 

difference in climate impacts the type and density of pests found in the region. Residents of 

areas with mild winter conditions, as exist in the southern United States, may experience 

significant pest control problems throughout the year and may respond with increased pesticide 

usage. The landmark EPA Non-Occupational Pesticide Exposure Study (NOPES) conducted 

during 1986-1988 (Whitmore et al., 1994) reported much higher indoor air concentrations of 

chlorpyrifos and diazinon in Jacksonville, Florida, than in Springfield and Chicopee, 

Massachusetts (purposely selected as high-use and low-use regions, respectively). 

The residents of rural communities may be exposed to pesticides from residential as well as 

agricultural applications. Both spray drift and work-to-home transport are potential pathways of 

exposure to agricultural pesticides, some of which have the same active ingredient as 

formulations used within the home (Curl et al., 2002). Residents of urban areas, on the other 

hand, may experience frequent applications to combat persistent pest control problems arising 

from high population density (Landrigan et al., 1999), may have little control over pesticide 

applications by building management, and may be exposed to pesticides applied in neighboring 

residences. 

Young children spend nearly 20 hours per day indoors (US EPA, 2002). For pre-school age 

children, much of this time is spent in residences or in daycare facilities. According to recent 

estimates, nearly 4 million children under age 6 spend some portion of their day in center-based 

child care, with many children spending a full work day (8-10 hours) in the child care center (US 

CPSC, 1999). Pesticide concentrations in daycare facilities are potentially significant (Wilson et 

al., 2003) and are typically out of the control of the parents. 

• Positive and highly significant associations (p < 0.01) between personal-air exposures 

and indoor air concentrations were observed in MNCPES for both chlorpyrifos and 

diazinon with Spearman correlation coefficients of 0.81 and 0.62, respectively (Table 

3.4). 

• Comparison of the box-and-whisker plots in Figure 3.4 of indoor air concentrations 

measured in homes finds median values were somewhat higher in southern states 

(NHEXAS-AZ and CTEPP-NC) than in northern states (MNCPES and CTEPP-OH). 

However, considerable overlap in the interquartile ranges is evident. Since these studies 

focus on compounds that have been used to control a variety of common insect pests both 

inside and outside of homes (chlorpyrifos was until recently among the most poplar 

residential insecticides for cockroach, flea, ant and termite control), it is not surprising 

that the distributions would overlap across geographical locations. 

37
• When daycare measurements are included, a geographical difference is less obvious 

(results not shown). Despite recent gains in the adoption of integrated pest management 

policies, many daycare facilities still have regular calendar-based pesticide treatments, 

irrespective of actual demonstrated need. This may have the effect of minimizing 

differences in usage in daycares among geographic regions. 

• CTEPP data (Figure 3.7) suggest that, within each state, indoor air levels in daycares are 

similar to those in homes, particularly for diazinon and permethrin. This demonstrates 

the potential for continued exposure as a child transitions from the home to a daycare. To 

reduce the uncertainty of risk assessments for children, their exposures must be 

considered for all indoor and outdoor environments they occupy, including homes, child 

care centers, and other buildings. Additional information may be required to examine 

exposure potential from schools, restaurants, and other public and private locations where 

pesticides are also applied. 

• Differences between urban and rural air concentrations of chlorpyrifos were observed in 

both MNCPES (Table 3.5) and CTEPP-OH (Table 3.6). The differences reached 

statistical significance only in MNCPES, with higher concentrations in the urban areas. 

Likewise, the detection frequencies for both chlorpyrifos and diazinon in indoor and 

personal air were higher in urban locations (Table 3.5). 

• Across compounds in MNCPES, median levels were consistently higher in urban areas 

than in rural areas. A reasonable explanation may be that urban areas require more 

intensive use of pesticide products to control a range of pests over a wider seasonal span. 

In addition the application may be of more mass of active ingredients in a smaller area, as 

is the case with a liquid termiticide application. While it is not entirely clear why the 

pattern of higher urban levels was not evident in CTEPP-NC, it may be due to a less 

stringent definition of “urban” in CTEPP. 

• Air samples collected in low-income homes generally had higher concentrations of 

chlorpyrifos and diazinon than samples collected in medium/high income homes (Table 

3.6), but the difference was only statistically significant for diazinon in NC. 

38
39

Table 3.4 Spearman correlations among personal, indoor, and outdoor concentrations of 

chlorpyrifos and diazinon measured in MNCPESa

. 

 Chlorpyrifos Diazinon 

Type Indoor Outdoor Indoor Outdoor 

Personal 0.81** 0.23 0.62** 0.67** 

Indoor -- -0.01 -- 0.28 

a

 Excerpted from Clayton et al., 2003 

** Statistically significant at the 0.01 level. 

Table 3.5 Urban and rural differences in airborne concentrations of chlorpyrifos and diazinon 

measured in MNCPES. The limit of detection was 0.1 ng/m3. 

Sample 

Type Chemical Location N 

Detection 

Frequency 

Median 

Concentration 

(ng/m3

) 

Urban/Suburban 40 98% 2.2 

Chlorpyrifos* Rural 20 90% 1.2 

Urban/Suburban 30 77% 0.4 

Personal 

Diazinon* 

Rural 18 44% <0.1 

Urban/Suburban 57 96% 2.2 

Chlorpyrifos* Rural 25 80% 0.7 

Urban/Suburban 54 74% 0.4 

Indoor 

Diazinon 

Rural 21 52% 0.1 

* denotes significant (p < 0.05) difference in medians using two-sided Wilcoxon test. 

Table 3.6 Differences in airborne concentrations measured in CTEPP for urban versus rural, low 

versus medium income, and home versus daycare expressed as ratios of geometric means. 

Adapted from Morgan et al., 2004. 

Estimated Ratio of Geometric Means (95% C.I.) 

State Chemical Urban/Rural Low /Mid-High Income Home/Daycare 

Chlorpyrifos 0.94 

(0.50, 1.77) 

1.36 

(0.84, 2.21) 

1.78 

North (0.81, 3.92) 

Carolina 

Diazinon 0.95 

(0.43, 2.11) 

3.59*

(1.95, 6.61) 

0.82 

(0.30, 2.24) 

Chlorpyrifos 1.64 

(0.80, 3.37) 

1.63 

(0.97, 2.74) 

0.76 

(0.38, 1.52) Ohio 

Diazinon 1.04 

(0.44, 2.49) 

1.67 

(0.89, 3.12) 

0.78 

(0.34, 1.80) 

* denotes significance, p < 0.05. 
40

0%

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

100%

Chlorpyrifos 3,5,6-TCPy Diazinon IM P c-Perm ethrin t-Perm ethrin Cyfluthrin

Indoor Detection Frequency (%)

NC HomeOH HomeNC DaycareOH Daycare

0%

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

100%

Chlorpyrifos 3,5,6-TCPy Diazinon IMP c-Perm ethrin t-Perm ethrin Cyfluthrin

Oudoor Detection Frequency (%)

NC HomeOH HomeNC DaycareOH Daycare

Figure 3.7 The detection frequencies of select pesticides and their metabolites measured from the indoor air (A) ahomes and daycares in NC and OH, and the mean concentrations of select pesticides and their degradation produthe indoor air (C) and outdoor air (D) of homes and daycares in NC and OH. 

0.01.02.03.04.05.06.07.0

Chlorpyrifos 3,5,6-TCPy Diazinon IMP 

Indoor Air Geometric Mean (ng/m3)

0.00.10.20.30.40.50.60.7

Chlorpyrifos 3,5,6-TCPy Diazinon IMP 

Oudoor Air Geometric Mean (ng/m3) 

B

A
3.5 Spatial and Temporal Variability 

Few studies have been designed to measure either the spatial variability of airborne pesticide 

concentrations in a home or the temporal variability following crack-and-crevice pesticide applications (Byrne et al., 1998; Lewis et al., 2001). Recently, the Test House, CPPAES, DIYC, 

and PET studies have provided data on both spatial and temporal variability, as shown in Figure 

3.8. 

• Within-home spatial patterns were investigated in the Test House experiments. 

Following a crack and crevice application of chlorpyrifos (Figure 3.8 and Table 3.7), the 

pesticide was detected in the application room (kitchen), adjacent den, and the farthest 

bedroom from the application. Airborne concentrations in the kitchen peaked at 790 

ng/m3, then decreased by approximately 80%, but were still measurable, at 21 days after 

application. A concentration gradient was observed from the kitchen (application area) to 

the den (proximal area) to the master bedroom (distal area). 

• Between-home spatial variability following a pesticide application was investigated in the 

CPPAES and DIYC studies. Indoor air concentrations of chlorpyrifos among the 10 

homes in the CPPAES spanned more than an order of magnitude one day after 

application (Figure 3.8). 

• The highest measured chlorpyrifos indoor air concentrations following crack and crevice 

applications among a subset of 5 CPPAES homes were between days 0 and 2 post application (mean = 315 ng/m3), then decreased throughout the 2-week sampling period (mean 

= 172 ng/m3), but were still greater than the pre application levels (mean = 18 ng/m3). 

The indoor air concentrations for the remaining CPPAES homes were much lower and 

did not follow the same decay pattern (data not presented, see Hore et al., 2005). 

• Air concentrations of diazinon in the homes of the DIYC study were nearly an order of 

magnitude higher than concentrations of chlorpyrifos in CPPAES, and the decay pattern 

differed dramatically among the three DIYC homes. The difference in airborne diazinon 

concentrations among the three homes was most pronounced 4-5 days after application 

(Figure 3.8), perhaps partially attributable to both the application method employed and 

the amount of active ingredient applied in each home. 

• Following outdoor granular application to lawns in the PET study, indoor air 

concentrations of diazinon generally reached maximal levels by days 1 and 2 post 

application and declined over the duration of the study (Figure 3.8). 

3.6 Factors that Influence Air Concentrations 

Multiple factors influence the concentration of pesticides in air and the potential for inhalation 

exposure. The physico-chemical characteristics of the chemicals applied, the formulation type 

and the frequency of application are believed to be some of the most important of these factors. 

Other factors such as seasonal variation, housing type, pets, occupancy, application location, 

type of surface to which the applications are made, and the rooms where the samples are 

collected may also influence the concentrations measured. Some of these factors have been 

41
investigated using the data from NERL’s pesticide exposure measurement program. 

• The impact of air exchange rate (AER) on air concentrations is shown in Figure 3.8 for 

the CPPAES data. Indoor air concentrations of chlorpyrifos (immediately following 

application) among the homes spanned more than an order of magnitude. Homes with 

low air exchange rates had higher initial airborne concentrations and a noticeably slower 

reduction of airborne levels. 

• The amount, or mass, of active ingredient applied also clearly affected the concentrations 

measured in CPPAES, with low airborne concentrations observed in three homes 

receiving applications containing only trace amounts of chlorpyrifos (data not presented, 

please see Hore et al., 2005). 

• An empirically derived Application Effective Volume (AEV, applied mass divided by the 

product of air changes per hour and home volume) was applied to the CPPAES data to 

demonstrate the relationship between measured air concentrations, air exchange rate, and 

mass of active ingredient applied. Measured airborne concentration was more 

consistently correlated with AEV than with any of the constituents of AEV (Pearson 

product-moment correlations, data not presented). The association of AEV with airborne 

concentrations measured on the second day after application (Figure 3.9) suggests that 

AEV may serve as an effective surrogate for air concentrations and that constituent 

measures including air exchange rate are important determinants of air concentrations. 

• The geometric mean concentrations of the organochlorine, organophosphate, and 

pyrethroid pesticides measured in indoor air in the absence of a recent application appear 

to be strongly influenced by vapor pressure. Regressing concentrations measured in the 

CTEPP study upon the logged vapor pressures (Figure 3.10) results in nearly equivalent 

R2 values of 0.69 and 0.70 for homes and daycares, respectively. The importance of 

inhalation as a route of exposure for pesticides is likely to decrease as less volatile 

pesticides are introduced into the market. 

• Results in the US EPA Research Test House comparing total release aerosol to crack and 

crevice applications confirm that the application method is an important factor 

influencing the measured airborne concentration of chlorpyrifos (Table 3.7). The 

application method is also suspected of being a factor responsible for the differences 

observed among homes in the DIYC study. 

• The PET study demonstrates the intrusion of diazinon from an outdoor source. The lawn 

applications resulted in a source of diazinon that contributed to indoor concentrations in 

all homes. Indoor concentrations are likely associated with both the physical 

translocation of particle bound residues and the intrusion of volatilized diazinon from the 

source. The results suggest that lawn applications increase the potential for occupant 

exposure both on the treated lawns and indoors. 

• While some progress has been made in understanding the multitude of factors that 

influence the concentration of pesticides in air and the potential for inhalation exposure, 

additional studies are needed. 

42
3.7 Summary: Air Concentrations 

As shown in the bulleted lists of observations from these studies, there are a number of factors 

that may impact children’s exposure to pesticides in homes and child care centers. They include 

the following: 

• The physical and chemical characteristics of the pesticides used indoors will have a 

significant impact on exposure via the inhalation route. Airborne concentrations will be 

higher for the more volatile pesticides, such as chlorpyrifos and diazinon (no longer 

registered for indoor use). Use of less volatile alternatives, such as the pyrethroids, will 

likely result in lower airborne concentrations of the active ingredients. 

• The type and method of pesticide application (see Section 2.4) are factors affecting 

exposure. As shown in the Test House experiments, the airborne concentrations are 

higher for foggers than for crack and crevice applications. Past studies have focused on 

crack and crevice and other spray applications, although newer types of applications, 

such as use of gels, may further reduce the translocation of pesticides to areas that may be 

contacted by children. 

• The data from these studies highlight the importance of geographic location on airborne 

concentrations. Frequency of application and total amount of pesticide used may be 

associated with geographic location. 

• The data on spatial variability of pesticide residues within a home are limited. But, data 

from the Test House and other studies show that pesticides are distributed to other 

locations within a building from the point of application and are measurable in air 

samples collected in other rooms. 

• The data also clearly show that there are temporal changes in concentrations following an 

application. These changes are related to air infiltration and air exchange rates in the 

home. The changes are also likely related to degradation processes, but there are few 

studies that have addressed the temporal changes in concentration for different pesticides 

as related specifically to the degradation process. 

43
44

Table 3.7 Airborne chlorpyrifos residues collected following a crack and crevice type application 

versus a total release aerosol in the EPA Test House. 

Indoor Air Concentration (ng/m3) Application 

Type Room Pre 3 hr Day 1 a Day 2 Day 3 Day 7 Day 14 Day 21 

Kitchen NC b NC 790 NC 770 320 220 140 

Den 3 NC 250 NC 140 90 60 70 Crack and 

Crevice 

Bedroom NC NC 100 NC 0.07 60 40 30 

Living Room ND c 15 9200 4100 2300 860 450 NC 

Den ND 17 8300 4000 2100 1100 410 NC 

Total 

Release 

Aerosol Bedroom NC 1.4 4700 NC NC 370 320 NC

a

 Air sampling was initiated immediately following the application and monitored continuously for 24-h. 

b

 NC indicates the sample was not collected. 

c

 ND indicates the sample was not detected <0.05 μg/m3 
45

igure 3.8 Airborne concentrations (ng/m3) of chlorpyrifos or diazinon measured from indoor air over time in the 

EPA Test House Rooms - Crack and Crevice

0

100200300400500600700800900

-3 0 3 6 9 12 15

Days after Application

Chlorpyrifos in Air (ng/m3) Kitchen Den Bedroom

CPPAES Low and High AER Homes

0

100200300400500600700800900

-3 0 3 6 9 12 15

Days after Application

Chlorpyrifos in Air (ng/m3) Low AER High AER

PET Study Home

0

100200300400500600700800900

-3 0 3 6 9 

Days after Application

Diazinon in Air (ng/m3)L

B

DIYC Study Homes

0

100020003000400050006000700080009000

-3 0 3 6 9 

Days after Application

Diazinon in Air (ng/m3)

FCPPAES, and DIYC studies. 
Figure 3.9 Association between measured air concentration (ng/m3) and Applied Effective 

Volume (ng/m3/h) on the second day after application of chlorpyrifos in CPPAES homes. 

ure 3.10 Pesticide air concentrations as a function of vapor pressure in CTEPP homes (A) and 

cares (B). 

Fig

day

Pesticide Air Concs. In CTEPP Hom es vs Vapor Pressure 

y = 1.77x + 3.90

R2 = 0.69

-2

0

2

4

6

8

-3 -2 -1 0 1 2

log10VP(mPa)

om. Mean (ng/m3) in 

CTEPP homes

Ge

Pesticide Air Concs. in CTEPP Daycares vs Vapor Pressure

y = 1.83x + 3.57

R2 = 0.70

-2

0

2

4

6

8

10

-3 -2 -1 0 1 2

log10VP(m Pa)

Geom. Mean (ng/m3) in 

CTEPP Daycares

A B

46
47

4.0 SURFACE MEASUREMENTS 

4.1 Introduction and Data Availability 

The objectives of measuring pesticide surface residue concentrations and loadings are to describe 

the extent and distribution of concentrations, identify possible sources of indoor contamination, 

evaluate factors that may impact concentrations, and identify elevated concentrations for the 

purposes of intervention. Surface measurements tell us what pesticide residues are present in an 

environment and at what concentrations. With appropriate transfer coefficients and activity data, 

these measurements can be used to estimate dermal and nondietary ingestion exposure. 

Although exposure potential is highest during the first few days following an application, 

pesticide residues introduced into the indoor residential environment may persist for months or 

even years on surfaces or embedded in carpets, where these are protected from sunlight, rain, 

temperature extremes, and microbial action (Lewis et al., 1994). Surface residues may 

contribute to the exposure of household occupants through multiple routes: dermal absorption, 

inhalation of resuspended particles, nondietary ingestion of residues adhering to mouthed objects 

and skin, and dietary ingestion resulting from children’s unique handling of food (Butte and 

Heinzow, 2002). Oral ingestion and dermal absorption of surface residues may be major routes 

of exposure for infants and toddlers who spend much of their time on the floor, explore their 

world through mouthing, experience frequent hand-to-mouth and object-to-mouth contacts, and 

who may have pica tendencies (Butte and Heinzow, 2002; Cohen Hubal et al., 2000a, b; 

Freeman et al., 2004; Lewis et al., 1994; Tulve et al., 2002). Ingestion of soil is also a special 

oncern for young children, who may ingest up to 10 times more soil than adults on a per 

face 

ress sampler (EL Sampler), Lioy-Weisel-Wainman (LWW) sampler, vacuum, drag bar, 

California-roller, PUF roller, and surface wipes. hese methods are generally classified by the 

and dust (Lewis, 2001). Total available residue ethods attempt to measure the total amount of 

ontaminant on a surface (often with the aid of isopropanol as a solvent), transferable residue 

ethods are intended to represent the amount that is transferred as a result of contact with the 

ontaminated surface, and dust collection methods use a vacuum to collect dust-borne residue on 

rfaces and from carpet. Transferable residues are also referred to as dislodgeable residues. All 

udies discussed in this chapter employed more than one sampling method for surface measureents. Table 4.1 lists the studies that collected surface measurements along with the type of 

easurement taken. Limits of detection for each chemical by study and method are listed in 

able 4.2. 

cteristics, application method, application frequency, sampling locations, 

articipant activities, and analytical capabilities. This chapter examines how these factors may 

have affected the surface residue measurements in the children’s exposure measurement 

program, the implications for interpreting the data, and the consequences for exposure estimates. 

c

kilogram body weight basis (LaGoy, 1987). 

Several surface sampling methods exist including deposition coupons, Octadecyl (C18) sur

p

 T

degree to which they remove residues from surfaces: total available residue, transferable residue, 

 m

c

m

c

su

st

m

m

T

Several variables may influence measured dust concentrations or surface loadings of pesticide 

residues. These variables include the collection method itself, surface type, compound physicochemical chara

p
Table 4.1 Studies and sample collection methods for surface measurements. 

Dust Dust Load Soil Total Surface Load Transferable Residues 

 

Study (ng/g) (ng/cm2

) (ng/g) (ng/cm2) (ng/cm2) 

NHEXAS-AZ 9 9 9 -- Wipes (water) 

MNCPES LWW C18 Press 

CTEPP 9 9 9 -- Wipes (2 mL IPA), 

PUF Roller 

CCC -- -- 9 Wipes (20 mL IPA) C18 Press 

JAX -- -- -- Wipes (20 mL IPA) C18 Press 

CHAMACOS 9 9 9 Wipes (20 mL IPA) C18 Press 

CPPAES -- -- -- Deposition Coupons, 

LWW -- 

Test House -- -- -- Deposition Coupons, 

Wipes (10 mL IPA) 

PUF Roller 

C18 Press 

PET 9 -- 9 PUF Roller 

DIYC -- -- -- Wipes (20 mL IPA) PUF Roller 

Daycare -- -- -- Wipes (20 mL IPA) PUF Roller, 

C18 Press 

--, matrix not sampled 

LWW, Lioy-Weisel-Wainman sampler 

C18, 3M EmporeTM Octadecyl (C18) filters 

PUF, Polyurethane foam 

48
Table 4.2 Limits of detection (ng/g or ng/cm2) for surface measurements by study, method, and 

S M

p inon 

rint

methrin

ermethrin valerat

compound. 

tudy ethod Chloryrifos 

Diaz- c-Pe

methr

-Per- Cyfluthrin Cyp Esfene TCPy IMP

 Soil (ng/g) 

MNCPES Soil 0 10 10 -- -- -- -- 1 10 -- 

CTEPP Soil 0.5 0.5 0.5 0.5 5 -- -- 0.2 0.2 

CCC Soil 5 2 5 5 6 6 -- -- -- 

PET Soil -- 60 -- -- -- -- -- -- -- 

 Dust (ng/cm2 or ng/g) 

NHEXAS-AZ Dust ( 2) 0. 0.002 -- -- -- -- -- -- -- ng/cm 002 

CTEPP Dust (ng/cm2) 0.0003 0.0003 0.0003 0.0003 0.0030 -- -- 0.0003 -- 

NHEXAS-AZ Dust (ng/g) 4 18 -- -- -- -- -- -- -- 

CTEPP Dust (ng/g) 2 2 2 2 10 -- 2 2 -- 

CHAMACOS Dust (ng/g) 1 1 1 1 100 -- -- -- -- 

PET Dust (ng/g) -- 60 -- -- -- -- -- -- -- 

 Total Available Resid /cm2) ue (ng

NHEXAS-AZ IPA W 0. 2.00 -- -- -- -- -- -- -- ipe 070

MNCPES LWW 1.20 3.50 -- -- -- -- -- -- -- 0 

CCC IPA Wipe 0.005 0.002 0.005 0.005 0.006 0.006 -- -- -- 

JAX IPA Wipe 0.005 0.002 0.005 0.005 0.006 0.006 0.008 -- -- 

CHAMACOS IPA Wipe 0.005 0.005 0.005 0. 002 -- -- -- -- -- 

CPPAES IPA Wipe 0.001 -- -- -- -- -- -- -- -- 

CPPAES LWW 0.030 -- -- -- -- -- -- -- -- 

CPPAES Dep Coup 0.010 -- -- -- -- -- -- -- -- 

TESTHOUSE IPA Wipe 0.001 -- -- -- -- -- -- -- -- 

TESTHOUSE Dep Coup 0.010 -- -- -- -- -- -- -- -- 

DIYC IPA Wipe -- 0.300 -- -- -- -- -- -- -- 

DAYCARE IPA Wipe -- -- -- -- -- -- 0.400 -- -- 

 Transferable Residue (ng/cm2) 

MNCPES C18 Press 0.330 0.140 -- -- -- -- -- -- -- 

CTEPP IPA Wipe 0.0007 0.0007 0.0007 0.0007 0.007 -- -- 0.0007 0.0007 

CTEPP PUF 0.0004 0.0004 0.0004 0.0004 0.004 -- -- 0.0004 0.0004 

TESTHOUSE C18 Press 0.030 -- -- -- -- -- -- -- -- 

TESTHOUSE PUF 0.001 -- -- -- -- -- -- -- -- 

PET PUF -- 0.030 -- -- -- -- -- -- -- 

DIYC C18 Press -- 1.200 -- -- -- -- -- -- -- 

--, analyte not measured

49
4.2 Dust and Soil Measurements 

Dust is considered a repository of environmental pollutants that have accumulated indoors from 

both internal and external sources. Dust collected by vacuum v etain a 

particular size fraction for analysis, which ma n l e 

c ersely related to particle size (Lewis et al., 1999). Measurements in dust 

m orted oncentrations ass r ue unit ight 

( idue p it area sampl g/c Th is a k of c sens on w h o se 

m an exposure to pe

that lead loading correlates better with children's b d le level han d s lea once ation

(L ear, 199

P du p m th ACOS and 

PET studies. T H Hig olum S urfac

S 3 NHEXA AZ d a m ified mm ially ailab vacu for 

e mple The HV was velop tly collec arpe

e t e associ d pes ides obert 91; L et al., 19 ). Th

HVS3 is a high-powered vacuum c ner ipped ith a zzle that ca e adj ed to a 

s c static p air flow te. yclon emo par es >5 m from the air strea

fo se of this sampler is limited to floors or other large flat surfaces 

( s, 199 is ., 1994). The ASTM (Ame an S ety f esti

a als) m for the c on rpet bedded dust requir n ap ratus th th

s cations o 3 (AS 9 e easured in the 

s tudies an ave b l n h o c i etwe indo

a p hways e c

P Prese st and Soil 

Detection limits are listed in Ta . D ction quen es ar

s g r dust es. C cen ples at 

th ntile a ed in ble 4 (com ete s mary atistics are listed in 

T .8 thro in Appen A

the n of cyflu in (fo hich analytical difficulties produced a higher 

amples had high detection frequencies (>95%) in CTEPP and 

AMA etectio u wer wer NHE S-A due t ighe

etectio

he hig ction freq t ud

s reposi con inants. 

Detectio quencies for so s , on othe and, ere g rally w (F re 

4.1). The high detection frequency of diazinon in PET study soil was due to direct lawn

 pesticide prior to sample collection. 

• Pesticide concentrations were much lower in soil samples than in dust samples. In 

general, soil levels at the 95th percentile were a factor of 10 to 100 times lower than dust 

levels at the same percentile. This result suggests that in the absence of outdoor turf 

treatments, ingestion of soil may not be an important exposure pathway for these 

 is usu

t imp

ally sie

ications

ed to r

y have importa since pesticid

oncentrations are inv

ay be rep as c (m esid per we of dust, ng/g) or as loadings 

mass res er un ed, n m2). ere

sticides; however, lead 

 lac on us hic f the

etrics is more relevant to hum studies have suggested 

loo ad s t oe d c ntr

anph 5). 

esticides were measured in st sam les fro e NHEXAS-AZ, CTEPP, CHAM

he CTEPP, C AMACOS, and PET studies used the h V e mall S e 

ampler (HVS ), whereas S- use od co erc av le um

ase of sa collection. S3 de ed for the EPA and efficien ts c tmbedded dus retaining th ate

lea

tic

qu

(R

 w

s et al.,

 no

 19 ewis 

n b

94 e 

e

A c

ust

pecifi ressure and ra e r ves ticl μ m 

r collection in a catch bottle. U

Roberts et al., 1991; Nes 4; Lew et al ric oci or T ng 

nd Materi ethod ollecti of ca -em es a pa wi e 

pecifi f the HVS TM, 1 93). P sticide concentrations in soil were m

ame s d results h een inc uded i this c apter t allow ompar sons b en or 

nd outdoor ex osure pat for th same hildren. 

esticide nce in Du

ble 4.2 ete fre ci e presented in Figure 4.1 for soil 

amples and Fi ure 4.2 fo sampl on trations of pesticides in soil and dust sam

e median and 95th perce re list Ta .3 pl um st

ables A ugh A.19 dix ). 

• With exceptio thr r w

detection limit), dust s

CH COS. D n freq encies e lo in XA Z o h r 

d n limits. 

• T h dete uencies of pes icides observed in dust across st ies is consistent 

with du t being a tory of tam

• n fre il amples the r h w ene lo igu

applications of the

50
51

of children exhibiting pica behavior. 

e 

r both chlorpyrifos and diazinon in soil is approximately 10 ng/g, and the 5th

occupants and their pets. 

pounds in dust is the opposite of that found in 

ticides showed the higher concentrations. The less volatile 

lso be important for the less volatile pesticides. 

• ings in surface dust (ng/cm2) were higher in daycare centers 

ested that loading has a greater impact than 

•

 significantly from the timeframe 

•

pesticides, with the possible exception 

Concentrations in Dust and Soil: Summary Findings 

Lognormal probability plots that graphically depict pesticide concentrations in soil from larg

observational field studies are presented in Figure 4.3. Plots that depict pesticide concentrations 

and loadings in dust are given in Figures 4.4 and 4.5. Box-and-whisker plots comparing 

pesticide concentrations and loadings in dust across all studies are given in Figures 4.6 and 4.7. 

• The upper tails of the soil concentration distributions tend to be in the same range as the 

lower tails of the dust concentration distributions (Figures 4.3-4.5). For example, the 95th

percentile fo

percentile for both of these compounds in dust is also near 10 ng/g. 

• Among the pesticides measured in soil, cyfluthrin stands out for its high values at the 

95th percentile (Table 4.3). Due to the low detection frequencies, no additional analysis 

was conducted with the soil data. 

• Comparisons of concentrations in dust across studies (Figures 4.4-4.5) show permethrin 

(a pyrethroid) to be about an order of magnitude higher than chlorpyrifos and diazinon 

(both organophosphates). 

• Overall, diazinon concentrations are lower than all other pesticides reported in dust, as 

illustrated in the box-and-whisker plots (Figures 4.6-4.7). 

• High loadings of diazinon in indoor house dust following the lawn treatment in the PET 

study suggest translocation into the house by the 

• The concentration ranking among the com

air where the more volatile pes

pyrethroid pesticides tend to partition to the dust and may degrade more slowly, allowing 

accumulation over time from repeated applications. These results point to the importance 

of dust as a primary residential exposure medium for the less volatile pesticides. In 

addition, the exposure factors that are important for other nonvolatile contaminants such

as lead (Melnyk et al., 2000) may a

• In general, the lognormal plots (Figures 4.4-4.5) indicate that differences between study 

populations are more apparent with dust loadings than with dust concentrations. 

In CTEPP, pesticide load

(DC) than in homes (HM) (Figures 4.6-4.7). This appears to be a function of the amount 

of surface dust present, as the pesticide concentrations in the dust do not differ by much 

(Figures 4.6-4.7). Studies with lead have sugg

concentration on intake, and the same may or may not be true for pesticides. 

Concentrations of chlorpyrifos in dust (ng/g) are similar across studies (Figure 4.4) 

suggesting that the usage of chlorpyrifos did not change

of the NHEXAS-AZ study (1995-1997) to the CTEPP study (2000-2001). 

As with the other surface measurement methods, cis- and trans-permethrin have similar 

concentration profiles in dust samples. 
Table 4.3 Median and 95

52

th percentile values for soil (ng/g) and dust (ng/cm2 and ng/g) measurements by study. 

Chlorpyrifos Diazinon c-Permethrin t-Permethrin Cyfluthrin TC

Units P50 P95 P50 P95 P50 P95 P50 P95 P50 P95 P50 

SOIL 

MNCPES ng/g <10.0 <10.0 <10.0 <10.0 -- -- -- -- -- -- -- CTEPP-NC ha ng/g <0.5 17.0 <0.5 4.2 <0.5 13.0 <0.5 18.0 <5.0 32.0 0.6 CTEPP-NC d ng/g <0.5 0.8 <0.5 <0.5 <0.5 2.6 <0.5 2.2 <5.0 42.0 <0.2 CTEPP-OH h ng/g <0.5 14.0 <0.5 4.7 <0.5 2.7 <0.5 2.1 <5.0 64.0 0.7 CTEPP-OH d ng/g <0.5 6.2 <0.5 7.1 <0.5 <0.5 <0.5 <0.5 <5.0 42.0 0.6 CCC ng/g <5.0 27.0 <2.0 22.0 <5.0 8.6 <5.0 12 <6.0 8.6 -- PET ng/g -- -- 22000 50000 -- -- -- -- -- -- -- 

DUST (Loadings) 

NHEXAS-AZ ng/cm2 0.007 2.80 0.002 0.18 -- -- -- -- -- -- -- CTEPP-NC h ng/cm2 0.009 0.42 0.002 0.12 0.10 4.90 0.09 4.40 <0.003 0.16 0.008 CTEPP-NC d ng/cm2 0.066 1.30 0.026 9.90 0.69 5.50 0.41 6.30 <0.003 0.60 0.020 CTEPP-OH h ng/cm2 0.006 0.35 0.002 0.31 0.05 3.80 0.03 3.90 0.018 0.25 0.004 CTEPP-OH d ng/cm2 0.046 0.89 0.022 0.39 0.27 4.80 0.31 4.70 0.140 1.10 0.024 PET ng/cm2 -- -- 0.350 68 -- -- -- -- -- -- -- 

DUST (Concentrations) 

NHEXAS-AZ ng/g 140 120000 150 8000 -- -- -- -- -- -- -- CTEPP-NC h ng/g 130 1200 18 390 800 21000 0 63 19000 47 1700 96 CTEPP-NC d ng/g 140 920 47 6900 890 10400 0 76 12000 79 1500 63 CTEPP-OH h ng/g 52 1400 20 1700 470 7600 0 34 9200 200 1300 41 CTEPP-OH d ng/g 180 1100 38 1600 690 3800 0 48 3400 350 890 67 CH CO AMA S ng/g 49 1200 21 820 150 2900 40 15000 <50 30 - 3.6 - PET ng/g -- -- 3100 150000 -- -- -- -- -- -- -- 

a CTE h = = d

ured

PP: 

--, analyte not 

home, d 

meas

aycare 
Detection Frequency: Soil

Chlorpyrifos TCPy

90

80

70

Diazinon IMP c-Perm t-Perm Cyfluthrin Cypermeth

0

10

20

30

40

50

60

100

ES

Detection Frequency

Fig

MNCP CTEPP-NC CTEPP-OH CCC PET

 (%)

ur etectio e 4.1 D n frequencies of pesticides and degradates in soil. 

Detection Frequency: Dust

Chlorpyrifos TCPy Diazinon IMP c-Perm t-Perm Cyfluthrin

0

10

20

30

40

50

60

70

80

90

100

NH

Detection Frequency (%)

Fig

EXAS-AZ CTEPP-NC CTEPP-OH CHAMACOS PET

ure 4.2 Detection frequencies of pesticides and degradates in dust.

53
Figure 4.3 Lognormal probability plots of soil concentrations (ng/g) for chlorpyrifos, diazinon, 

cis-permethrin, trans-permethrin, cyfluthrin, and TCPy. 

54
Figure 4.4 Lognormal probability plots of dust concentrations (ng/g) and loadings (ng/cm2) for 

chlorpyrifos, diazinon, and cis-permethrin. 

55
Figure 4.5 Lognormal probability plots of dust concentrations (ng/g) and loadings (ng/cm2) for 

trans-permethrin, cyfluthrin, and TCPy.

56
Figure 4.6 Box-and-whisker plots of dust concentrations (ng/g) and loadings (ng/cm2) for 

chlorpyrifos, diazinon, and cis-permethrin. 

57
Figure 4.7 Box-and-whisker plots of dust concentrations (ng/g) and loadings (ng/cm2) for trans

permethrin, cyfluthrin, and TCPy. 

-

58
4.3 Total Available Residue Measurements 

Total available residue methods are intended to measure the total amount of contaminant on a 

surface. These methods involve either a solvent-assisted mechanical (wiping) action or the 

stationary capture of descending airborne droplets and particles. Total available residue loadings 

were measured in:

• NHEXAS-AZ using the LWW sampler, 

• MNCPES using the LWW sampler, 

• CCC from the floors and other surfaces (e.g., counters, desktops) using surface wipes, 

• JAX from the floor in the application area using surface wipes, 

• CHAMOCOS using surface wipes, 

• CPPAES using the LWW and deposition coupons, 

• Test House using deposition coupons and surface wipes, 

• DIYC using surface wipes, and 

• Daycare using surface wipes. 

The Lioy-Weisel-Wainman (LWW) sampler (Patent #RWJ-91-28) was developed to 

quantitatively measure dust on smooth surfaces and has been validated in laboratory and field 

tests (Lioy et al., 1993; Freeman et al., 1996). The LWW sampler achieves quantitative wipe 

collection using a movable constant pressure block within a template marking a specific area of 

100 cm2. Octadecyl-bonded (C18) disks that have been immersed in isopropyl alcohol are 

attached to a silicon rubber pad on the block. More details about this sampler can be found in 

Gurunathan et al. (1998) and Hore (2003). 

Surface wipes are typically surgical dressing sponges wetted with isopropyl alcohol (IPA). The 

sponge is wiped multi-directionally through a defined area in an S-shaped configuration. Floor 

locations where young children may spend the most amount of time are usually selected. 

Residue loadings on irregularly shaped objects such as toys that are frequently handled by 

children (for estimating indirect ingestion exposures) are also measured using the wipe method. 

Deposition coupons are used to estimate surface loadings of airborne and dust-bound residues 

that “settle out” of the air following an application (Ness, 1994). These consist of a sorptive 

material (e.g., cotton, sponge, rayon) with a non-sorptive backing (aluminum foil) (Stout and 

Mason, 2003) and are placed in locations where the coupons will not be disturbed. Coupons may 

be repeatedly collected and replaced (interval) or collected only at the end of the sampling event 

(cumulative). Both interval and cumulative types were collected in CPPAES, whereas only 

interval deposition coupons were used in the Test House. 

59
Pesticide Presence in Total Available Residues 

f detection varied widely among studies, but are similar within a study for 

ticides. 

higher for the organophosphate pesticides in two of 

icides were measured. 

 studies than in the survey 

urements with respect to recent applications. 

es 

y 

encies. Box and whisker plots that graphically depict 

e 

• Levels of diazinon and esfenvalerate reported at the 95 percentile were at least an order 

) of chlorpyrifos and cis- and transpermethrin are relatively similar to each other within a specific large observational field 

study. 

• Cypermethrin loadings tend to be the highest and diazinon loadings tend to be the lowest 

(Figure 4.9) of the pesticides of interest in the large observational field studies. 

• The boxplots (Figure 4.10) reveal that chlorpyrifos, diazinon, and esfenvalerate loadings 

are substantially higher in those studies with a known application (CPPAES, Test House, 

DIYC, and Daycare). 

Limits of detection for each chemical by study are given above in Table 4.2. Detection 

frequencies are given in Figure 4.8. 

• The limits o

both organophosphate and pyrethroid pes

Following dust methods, total available residue methods have the lowest limits for 

detection. 

•

• Detection frequencies were slightly 

the three studies where both OP and pyrethroid pest

• Detection frequencies were higher in the smaller, focused

studies due to timing of the meas

Total Available Residues: Summary Findings 

Surface loadings for the median and 95th percentile are listed in Table 4.4 for all of the pesticid

that were detected across studies (complete summary statistics are listed in Tables A.20 through 

A.24 in Appendix A). Lognormal probability plots are presented in Figure 4.9 for the most 

frequently detected pesticides which include chlorpyrifos, diazinon, cis- and trans-permethrin, 

cyfluthrin, and cypermethrin. The MNCPES data are not included because of the comparativel

high detection limit and low detection frequ

the total available residue loading results from all studies are given in Figure 4.10. 

• In wipe samples, permethrin levels reported at the 95th percentile were approximately an 

order of magnitude higher than chlorpyrifos and diazinon levels at the 95th percentil

(Table 4.4). 

th

of magnitude higher in studies with a known application (DIYC, Daycare) than in the 

survey studies (CCC, JAX-Screening). 

• The lognormal probability plots (Figure 4.9) show that loadings of all frequently detected 

pesticides are substantially higher in the JAX screening wipe samples than in the CCC 

and CHAMACOS wipe samples. 

• The total available residue distributions (Figure 4.9

60
• Low cyfluthrin loadings in wipe samples in Figure 4.9 (substantially lower than all other 

pesticide residues) suggest that cyfluthrin may not have been routinely used for pest 

e only studies that employed the LWW. The chlorpyrifos 

s 

. 

, 62% 

ifos 

 residential surfaces for a long period of time. It is unclear, however, how 

r 

WW sampler. 

rs 

responsible may include the following: three CPPAES homes received applications with 

application performed in the Test House may 

 in the CPPAES homes; the Test House may 

urfaces that 

did not receive a direct application. This suggests that semi-volatile pesticides rapidly 

he floor residue loadings were higher. 

treatment. 

• MNCPES and CPPAES are th

loadings measured in CPPAES were significantly higher (ANOVA, p=0.002, test result

not presented) due to known pesticide applications coinciding with the sampling period

• Although the MNCPES measurements did not coincide with a pesticide application

of the LWW samples had detectable levels of chlorpyrifos, suggesting that chlorpyr

remains on

much of this is readily available for transfer and how much is freed from the pores and/o

body material of the surfaces by the mechanical and solvent action of the L

• Mean post-application deposition coupon levels were significantly higher in the Test

House than in CPPAES (ANOVA, p<0.0001, test results not presented). Facto

only trace chlorpyrifos concentrations; the 

have been more thorough than applications

have had a higher application of active ingredient per effective volume of the home (see 

Section 3.6), and some of the CPPAES occupants reported cleaning their homes and/or 

intentionally increasing ventilation after application, thereby reducing the amount of 

chlorpyrifos available for movement and capture on a deposition coupon. 

• In studies (e.g., CPPAES) where surface wipe samples were collected both pre- and postapplication of a semi-volatile pesticide such as chlorpyrifos, the post-application 

pesticide loadings were higher than the pre-application values, including on s

translocate from application surfaces to adjacent surfaces. We do not yet have 

information on the speed or extent of translocation for less volatile pesticides like 

pyrethroids. 

• Two types of locations were sampled in JAX, the application area and a play area. In 

general, the surface residue loadings were higher at the application area than at the play

area. 

• The surface wipe samples collected in the CCC study were collected from two locations 

in each of the randomly selected rooms of the child care centers: a floor and desk 

top/table top surface. In general, t

61
Figure 4.8 Detection frequencies fo

62

r pesticides using total available residue collection methods. 

Detection Frequency: Total Surface Loading

Chlorpyrifos Diazinon c-Perm t-Perm Cyfluthrin Cype rmeth Esfenval

0

10

20

30

40

50

60

70

80

90

100

NHEXAS-AZ IPA MNCPES LWW CCC IPA JAX-SCR IPA

CHAMACOS IPA CPPAES IPA CPPAES LWW CPPAES DC

TESTHOUSE IPA TESTHOUSE DC DIYC IPA DAYCARE IPA

Detection Frequency (%)
63

Table 4.4 Median and 95th 2) by study. 

Chlorpyrifos Diazinon c-Permeth t-Permethrin Cyfluthrin Cyperme

Study Method P50 P95 P50 P95 P50 P50 P95 P50 P95 P50 

 percentile values for total available residues (ng/cm

rin 

P95 

NHEXAS-AZ IPA Wipe <0.07 7.5 <2.000 <2.0 -- -- -- -- -- -- -- MNCPES LWW 1.20 1.5 <3.500 3.5 -- -- -- -- -- -- -- CCC IPA Wipe 0.03 0.9 0.002 0.5 0.009 0.67 0.02 1.1 <0.006 0.08 <0.006 JAX-SCR IPA Wipe 0.53 10.0 0.110 3.3 2.200 32.00 2.90 40.0 <0.006 4.30 2.600 JAX-AGG IPA Wipe 0.10 3.1 <0.002 4.0 0.210 42.00 0.26 67.0 <0.006 10.00 -- CHAMACOS IPA Wipe 0.05 0.2 0.040 0.1 0.100 1.70 0.20 3.6 <0.050 0.40 -- CPPAES Pre LWW 0.17 1.3 -- -- -- -- -- -- -- -- -- CPPAES LWW 0.61 10.0 -- -- -- -- -- -- -- -- -- CPPAES IPA Wipe 0.03 0.2 -- -- -- -- -- -- -- -- -- CPPAES Dep Coup 1.40 9.6 -- -- -- -- -- -- -- -- -- TESTHOUSE Pre IPA Wipe 4.70 9.1 -- -- -- -- -- -- -- -- -- TESTHOUSE IPA Wipe 11.00 36.0 -- -- -- -- -- -- -- -- -- TESTHOUSE Dep Coup 3.20 62.0 -- -- -- -- -- -- -- -- -- DIYC Pre IPA Wipe -- -- 3.8 21.0 -- -- -- -- -- -- -- DIYC IPA Wipe -- -- 5.5 72.0 -- -- -- -- -- -- -- DAYCARE IPA Wipe -- -- -- -- -- -- -- -- -- -- -- --, pesticide not measured
 

Fig

chlo

ure 4. ed pesticides which include 

rpyrifos ermethrin. 

9 Logn

, dia

orm

zin

al 

on,

pro

cis

bab

- an

ility

d tr

 pl

an

ots 

s-pe

for

rm

 the

eth

 mo

rin,

st f

 cyf

req

luth

uen

rin

tly

, an

 de

d c

tect

yp

64
Figure 4.10 Box-and-whisker plots of total available residue surface loadings (ng/cm2) for 

chlorpyrifos, diazinon, cis-permethrin, trans-permethrin, cypermethrin, and esfenvalerate. 

65
4.4 Transferable Residue Measurements 

Transferable residue methods are intended to represent the surface loading that may be 

transferred as a result of contact with the contaminated surface; that is, instead of complete 

removal, they are typically intended to mimic transfer to skin during a single dermal contact with 

a surface, where transfer is aided by only saliva, sweat, or the sebum layer on the skin. 

Transferable residue loadings were measured in: 

• MNCPES using the C18 press sampler on floors and non-floor surfaces, 

• CTEPP using surface wipes with 2 mL 75% IPA on hard-surface floors and counters and 

a PUF roller on carpeted floors, 

• CCC using the C18 press sampler on carpeted floors, 

• JAX using the C18 press sampler on carpeted floors, 

• CHAMACOS using the C18 press sampler on carpeted floors, 

• Test House using the C18 press sampler and a PUF roller skin on carpeted floors, 

• DIYC using the PUF roller on both hard-surface and carpeted floors, and 

• Daycare using the C18 press sampler and the PUF roller on carpeted floors. 

The Modified C18 Surface Press Sampler was based on the original EL Sampler designed by 

Edwards and Lioy to collect pesticides in house dust from carpeted floors (Edwards and Lioy, 

1999; Hore, 2003). EPA modified the press sampler to use two 9-cm diameter sampling discs 

for a total sampling area of 114 cm2

 and eliminated the spring mechanism, henceforth it became 

known as the Modified C18 Surface Press Sampler. Unlike vacuum methods that collect 

household dust from all depths of the carpet pile and base, the surface press sampler is designed 

to only contact and remove residue from the surface. The developers maintain that the sampler 

replicates the collection efficiency of human skin and reflects transfer from single hand press 

(Edwards and Lioy, 1999; Lioy et al., 2000), ignoring the inter- and intra-individual factors that 

may affect transfer. 

The PUF roller transferable residue sampler was developed to simulate the pressure applied to a 

surface by a crawling child weighing 9 kg (7,300 Pa) (Hsu et al., 1990). The PUF roller consists 

of a weighted roller fitted with a thick, moistened polyurethane foam (PUF) cover. 

Modifications include using either a dry PUF roller cover or a thinner PUF skin. More details 

can be found in the literature (Hsu et al., 1990; Lewis et al., 1994; Stout and Mason, 2003). 

Discussion of the CTEPP surface wipe samples is included here rather than in Section 4.3 

because of the small volume (only 2 mL) of isopropyl alcohol used. Also, it should be restated 

that in CTEPP transferable residue samples were only collected in those homes and daycare 

centers that reported recent pesticide use. 

Limits of detection for each method and chemical are given by study above in Table 4.2. 

Detection frequencies are given in Figure 4.11. The C18 Press and PUF roller results from 

Daycare are not included (or further discussed) due to extremely poor detection frequencies, with 

only one C18 and two PUF samples above the limit of detection. 

66
Pesticide Presence in Transferable Residues 

er than 

erable residue 

entified pesticides. 

ies by the modified C18 surface 

lorpyrifos was zero. In 

rfaces were 8 and 5 

y studies 

plied 

• Overall, the detection frequencies for transferable residues were substantially low

those for total available residues. 

• Chlorpyrifos was detected in greater than 75% of transferable residues in all of the 

studies except MNCPES. 

• Cis- and trans-permethrin were detected in greater than 50% of the transf

samples collected in CTEPP. These measurements were made in a subset of homes with 

recent indoor applications of unid

• Transferable residues were rarely detected in field stud

press sampler. In CHAMACOS, the detection frequency for ch

MNCPES, the detection frequencies on the floor and on other su

percent, respectively. The only exception was the DIYC study, where the postapplication detection frequency for diazinon was greater than 50%. 

• The modified C18 press sampler was more successfully used in the laborator

(Test House and Food Transfer studies) where residues were measured on all surface 

types sampled. 

• CTEPP used IPA wipes with only 2 mL isopropanol instead of the 10 to 20 mL often 

applied for total available residue measurements. It is likely that the amount of pesticide 

residue recovered from the sampled surfaces is influenced by the amount of IPA ap

to the wipe. Other variables that should be considered include location sampled within 

the room and last known pesticide application. 

. 

67
Detection Frequency: Transferable Residues

Figure ransferable residue collection methods. 

lts from the C18 Press samplers used in CHAMACOS were below the limits of 

tection. 

4.11 Detection frequencies for pesticides using t

All resu

de

Chlorpyrifos TC

100

90

80

Detection Frequency (%)

70

60

50

40

30

20

10

0

Py Diazinon IMP c-Perm t-Perm Cyfluthrin

CTEPP-NC IPA

CTEPP-OH IPA

CTEPP-NC PUF

CTEPP-OH PUF TESTHOUSE PUF

PET PUF

MNCPES PRESS

TESTHOUSE PRESS DIYC PRESS

68
Transferable Residues: Summary Findings 

Transferable residue loadings at the median and 95th percentile are given in Table 4.5 for all of 

the pesticides that were detected across studies (complete summary statistics are lis

A.25 through A.29 in Appendix A). Transferable residue loadings of chlorpyrifos, diazinon, and 

permethrin are depicted in lognormal probability plots and box-and-whisker plot

and 4.13, respectively. 

• The original C18 press sampler was designed to represent what adheres to the skin from

single hand press onto a carpeted surface. The uses for the modified C18 surface pres

sampler have expanded to include hard surfaces and longer contact times, contrary to its 

intended use. The data in Table 4.5 suggest that the sensitivity of the modified C18 

surface press sampler is not adequate to measure typical residential pesticide residu

levels due to its low collection efficiency (estimated as less than 1%). 

• The mean transferable (2 mL IPA wipe) loadings were significantly different between 

CTEPP NC and OH for cis-permethrin (p<0.01), trans-permethrin (p<0.05), and diazinon 

(p<0.01). The mean loadings were not significantly different for either chlorpyrifos 

(ANOVA, p=0.12) or cyfluthrin (ANOVA, p=0.17). 

• Wipe sampling methods varied in the volume of IPA used as a solvent (Table 4.1). T

2-mL IPA wipes used in CTEPP produced surface loading values that were very sim

to those produced with the PUF roller (Figure 4.13). Since the PUF roller is a 

transferable residue method, it appears that the amount of IPA applied to the wipe 

ted in Tables 

s in Figures 4.12 

 a 

s 

e 

he 

ilar 

determines the type of surface residue collected (i.e., total or transferable residue). 

Interpretation of these results is complicated by other factors including recent application

and sampling location with respect to application. 

69
Table 4.5 Median and 95th percentile values for transferable residues (ng/cm2) by study. 

Chlorpyrifos Diazinon c-Permethrin t-Permethrin Cyfluthrin TCP

Study Method P50 P95 P50 P95 P50 P95 P50 P95 P50 P95 P50 

MNCPES Press <0.330 0.420 <0.140 1.13 -- -- -- -- -- -- -- CTEPP-NC h a IPA Wipe 0.007 0.140 0.001 0.51 0.050 1.500 0.034 1.600 <0.007 <0.007 0.005 CTEPP-OH h a IPA Wipe 0.002 0.760 <0.001 0.05 0.005 0.780 0.005 0.790 <0.007 0.041 0.001 TESTHOUSE PUF 0.005 0.15 -- -- -- -- -- -- -- -- -- TESTHOUSE Press 0.230 6.90 -- -- -- -- -- -- -- -- -- PET PUF -- -- <0.005 -- -- -- -- -- -- -- DIYC Press -- -- 3.80 24.0 -- -- -- -- -- -- -- 

--, pesticide not measured a Homes only (daycares excluded)

70
Fig

dete

CTE

ur l probability plots for transferable residue loadings for the most frequently 

cted pes ich include chlorpyrifos, diazinon, and cis- and trans-permethrin from 

PP. 

e 4.12 Log

ticid

nor

es

ma

 wh

71
Figure 4.13 Box-and-whisker plots for transferable residue loadings for the most frequently 

detected pesticides which include chlorpyrifos, diazinon, cis- and trans-permethrin, cyfluthrin, 

and TCPy. 

72
4.5 Spatial and Temporal Variability 

Spatial and temporal variability were investigated in studies involving recent pesticide 

applications, including: 

• Test House using IPA wipes, deposition coupons, C18 press sampler and PUF roller; 

• CPPAES using IPA wipes, deposition coupons, and the LWW sampler; 

• DIYC using IPA wipes and C18 press; and 

• Daycare study using the IPA wipes. 

In studies with a series of measurements over time, the interval of time between measurements 

ranged from one to three days. In CPPAES, multiple rooms in ten homes were monitored for 

two weeks post application. In DIYC, multiple surfaces in three homes were monitored for one 

week. In the Test House, multiple surfaces in multiple rooms of a single house were monitored 

for 21 days. The Daycare study included multiple applications, each separated by one to three 

months, in a single daycare facility. In addition to sampling main activity areas, some studies 

also sampled less frequently contacted areas. 

Figure 4.14 presents total available surface residue loadings measured in multiple locations in 

multiple rooms over time in the Test House, in multiple rooms in ten homes in CPPAES, and on 

multiple surfaces in three homes in DIYC. Figure 4.15 presents transferable residue 

measurements over time in multiple rooms of the Test House and on multiple surfaces in three 

homes in DIYC. Figure 4.16 presents total available residue measurements from the Daycare 

study, collected immediately following applications on multiple surfaces in two rooms. Figure 

4.17 presents spatial variability in deposition coupon loadings in the kitchen (application site) 

and den (adjoining room) of the Test House following pesticide application. 

Spatial and Temporal Variability: Summary Findings 

• Preliminary examination indicates that total available residue loadings decay at a slower 

rate than airborne concentrations (See Figures 4.14 and 3.8). 

• In the Test House experiment, the transferable residue loadings appeared to decrease at a 

faster rate than the total available residues (Figures 4.14 and 4.15). This may have 

occurred because the pesticide residue became less available for transfer (for example, 

due to an interaction with the surface or because the dried residue was less available for 

transfer). 

• The transferable residues on the counters in DIYC (Figure 4.15) are nearly as high as 

those on the floors immediately after application, suggesting translocation of the pesticide 

from the site of application (assuming counters were not application surfaces).

• Substantial variability within rooms (at times a 100-fold difference in loadings) is evident 

in the Daycare data (Figure 4.16). Exposure estimates using measurements at a single 

location based on an assumption of homogenous surface loadings may result in exposure 

misclassification. The spatial variability points to the need for sampling of multiple 

locations and perhaps for better resolution in the activity data that is gathered.

73
• Data from the Test House (Figure 4.17) show that surface loadings cannot be assumed to 

be homogenous within a room.

le tops. 

rent rooms. 

• In the CCC study, loadings on floors were generally higher than loadings on tab

• In a published analysis of the MNCPES LWW wipe data, Lioy and colleagues (2000) 

reported substantial variability in surface chlorpyrifos levels among diffe

74
EPA Test House - Chlorpyrifos CPPAES - Chlorpyrifos

Figure 4.14 Total available surface residue loadings measured in multiple rooms over time in the 

Test House, in multiple rooms in ten homes in CPPAES, and on multiple surfaces in three homes 

in DIYC. 

Figure 4.15 Transferable residue measurements over time following an application from multiple 

locations in multiple rooms of the Test House and multiple surfaces in three homes in DIYC. 

-3 0 3 6 9 12 15 18 21

0

10

20

30

40

50

60

70

Deposit Coup - Den

Deposit Coup - Kitchen

IPA W ipe - Kitchen

Day

Loading, ng/cm2

-3 0 3 6 9 12 15 18 21

0.0

0.1

Deposition Coupons

IPA W ipes

LWW

8

7

6

1

2

3

4

5

Day

Loading, ng/cm2

DIYC - Diazinon

60

50

40

-3 0 3 6 9 12 15 18 21

0

10

20

30

70

IPA W ipe - Floor

Day

Loading, ng/cm2

IPA W ipe - Playmat

IPA W ipe - Counter

EPA Test House - Chlorpyrifos DIYC - Diazinon

-3 0 3 6 9 12 15 18 21

0

1

2

3

4

5

6

PUF - Kitchen

PUF - Den

Press - Kitchen

Press - Den

Day

Loading, ng/cm2

25

20

15

30

Press - Floor

-3 0 3 6 9 12 15 18 21

0

5

10

Day

Loading, ng/cm2

Press - Counter

Press - Playmat

75
76

en (adjoining room) of Test House following pesticide application. 

Figure 4.16 Total available residue measurements from the Daycare study, collected immediately 

following applications on multiple surfaces in two rooms in a single daycare facility. Solid Line 

represents the preschool room and dashed line represents infant room 

Dotted vertical line represents application. 

0.1

1.0

10.0

100.0

1000.0

6/10 6/25 7/10 7/25 8/9 8/24 9/8 9/23

Sampling Date

Loading (ng/cm2)

ext_door restrooms center table/sink entryway

Figure 4.17 Spatial variability in deposition coupon loadings in the kitchen (application site) and 

d

1

2

3

4 Left

Center 

Right

250

Kitchen Deposition Coupon Loading Den Deposition Coupon Loading

0

50

100

150

200

Loading (ng/cm2)

Location in Row

1

2

3

4 Left 

Center

Right

0

5

10

15

Loading (ng/cm2)

Location in Row

Left Center Right
4.6 Differences Related to Location 

Regional Differences 

tudies dating back to the Non-Occupational Pesticide Exposure Study (NOPES) from 1986 to 

988 (Whitmore et al., 1994) have reported regional differences in environmental pesticide 

oncentrations and loadings. Differences are thought to result from heavier use of insecticides in 

arm weather climates with higher year round insect control problems than in colder regions 

here hard winters help to curb insect populations. 

• Median diazinon surface dust loadings (ng/cm2) in home environments (daycares 

excluded) were very similar (about 0.002 ng/cm2) across three states (NC, OH, and AZ, 

Table 4.3), and the 95th percentiles were also somewhat similar (0.12, 0.31, and 0.18, 

respectively). ANOVA analysis with Bonferroni adjustment for multiple comparisons 

found no significant differences among the three locations. These dust measurements do 

not provide evidence of the geographic variations consistent with geographic differences 

in pest treatment practices reported by Colt (1998). 

-specific pesticide use. 

• For transferable residues obtained with 2-mL IPA surface wipes, the mean chlorpyrifos 

and cyfluthrin loadings were higher for CTEPP-NC compared to CTEPP-OH but not 

statistically different (Figures 4.12, 4.13). However, the mean loadings were 

resent in the house dust of 75% of agricultural area homes but only 7% of metropolitan area 

ing and 

ther rural areas, widespread elevated pesticide residue levels have also been reported in highly 

urbanized minority communities of New York City (Whyatt et al., 2002). 

S

1

c

w

w

• The overlapping distributions of pesticide concentrations in dust (ng/g) in the large 

observational field studies in Arizona, North Carolina, and Ohio (Figure 4.4) suggest that 

concentrations in dust may not be useful for determining region

significantly higher in NC for cis-permethrin (ANOVA; p<0.01) and trans-permethrin 

(ANOVA; p<0.05) and marginally significant for diazinon (ANOVA; p<0.10). 

• Analysis of surface wipe samples from the national, probability-based Child Care Center 

study indicated no differences in the mean pesticide loadings among daycares in the four 

Census regions (data not shown, Tulve et al., 2006). 

• Differences in surface sampling methods, year of the study, and time of year when 

samples were collected make it difficult to examine any regional differences in surface 

pesticide loadings in homes. The transferable residue measurements suggest higher 

levels in NC than in OH, but no systematic differences are evident in dust concentrations 

or total surface residue loadings, although JAX had much higher surface loadings than 

any of the other studies without recent applications. 

Urban vs. Rural 

Lu and colleagues (2004) recently reported that at least one organophosphate pesticide was 

p

homes, suggesting different exposure pathways for children living in agricultural and 

nonagricultural regions. While concerns about pesticides may be more obvious in farm

o

77
• Neither the median nor 95th percentile concentrations of chlorpyrifos measured in 

CHAMACOS dust was substantially higher than the median and 95th percentile in the 

able 4.3). The assumption that children living in agricultural areas 

experience higher exposures than children in nonagricultural regions is not supported by 

est 

4.7 Inf

As disc r 

loading

Collect

t 

• and OH 

• ining typical surface pesticide 

iency 

Surfac

•

iping from hard surfaces greatly 

exceeded carpet, and tile generally exceeded hardwood. As stated by Rohrer, “Highest 

coveries were from tile with diazinon (59%), chlorpyrifos (80%), and 

permethrins (52% cis; 53% trans) being the only pesticides recovered by wiping at 

rface residue loadings 

in JAX. 

other studies (T

these chlorpyrifos in dust measurements. 

• Relatively high pre-application surface loadings in some of the CPPAES homes (data not 

presented) suggest possible contamination from pesticides applied in neighboring 

apartments in close proximity (Hore, 2003). Alternatively, the high loadings may sugg

frequent treatments in those homes. 

luential Factors 

ussed above, the following factors appear to influence measured surface concentration o

 values: 

ion Methods 

• The different types of collection methods are intended to have different collection 

efficiencies to serve different purposes. Efficiencies for various methods have been 

previously published. 

• Total residue methods (which use both solvent and mechanical action to remove residues

that may have penetrated into the surface) produce the highest values, followed by dus

methods, and then by transferable residue methods. 

The low pesticide surface loadings obtained with 2 mL IPA wipes in both the NC

CTEPP studies (comparable to loadings obtained with the PUF roller) suggest that the 

amount of IPA applied to the wipe affects the amount of pesticide residue recovered. 

The C18 Press does not appear to be useful for determ

residue loadings, for which it was never intended, because of its low collection effic

and small size. 

e Types 

Surface type has been shown to affect the collection efficiency of wipes. Recently 

published NERL data (Rohrer et al., 2003) found that w

pesticide re

greater than 50% of the applied concentrations.” 

Sampling Locations 

• Despite evidence of translocation from direct application areas, the application area 

surface residue loadings were generally higher than the play area su

78
• In the CCC study, floor residue loadings were typically higher than table top or des

loadings. 

Experiments in the Test House showed high spatial variability in loadings in the room of 

application (kitchen) and transport of pesticide residues to the adjoining room. 

k top 

•

Occup

• Surface chlorpyrifos loadings were reportedly lower in the CPPAES homes in which the 

ed cleaning activities and/or the homes that had high ventilation rates 

(Hore, 2003). 

es than the same type of application (albeit with less active 

ased) in the occupied CPPAES homes. 

es i

• eargh pesticide usage, were much higher than in any of the 

•

s. Published results from 

4.8 or

• et al., 2006) found little correlation between surface wipe 

and soil concentrations for 16 common organophosphate and pyrethroid 

s 

•

• Results from the Daycare study showed substantial differences in surface loadings (up to 

two orders of magnitude) at different locations in a daycare center. 

ant Activities 

occupants perform

• Crack and crevice applications in the unoccupied Test House produced higher surface 

loadings and longer decay tim

ingredient rele

P tic de Use Patterns 

On a regional level, surface loadings in Jacksonville, Florida, an area likely to have y

round pest control issues and hi

other observational studies. 

Within a given region, however, pesticide use information collected with questionnaires 

or inventories may not correlate with measured surface value

the MNCPES indicate that the residential pesticide use questions and overall screening 

approach used in the MNCPES were ineffective for identifying households with higher

levels of individual target pesticides (Sexton et al., 2003). 

C relations among Soil, Wipes, and Dust 

Analysis of CCC data (Tulve 

loadings 

pesticides. 

• In the CTEPP study, significant Spearman correlations between dust and soil 

concentrations were observed with diazinon (r=0.26, p<0.01) and TCPy (r=0.21, p<0.05)

in NC homes and chlorpyrifos (r=0.28, p<0.01) and TCPy (r=0.20, p<0.05) in OH home

(data not presented). 

Identification of correlations is hindered by the low detection frequencies for many 

pesticides in soil. 

79
4.9 r

The c

com

physica . In 

gen l

mechan ards the particulate 

hase also suggests a decreased relative importance of the inhalation route and an increased 

 the dermal and indirect ingestion routes. 

Pes id

surface

obstructed or otherwise hindered, it is largely the movement of residues from the point of 

app a

resi n

transfo

chemical properties of the active 

nd companion animal activity. 

ve ll

sim

Pyrethr

volatili ly in the particulate phase at room temperature. They have 

hig c

and ver

tend to

bind re

activity for human exposure. 

ticle size dependent (Rodes et al., 2001). 

issel et al. (1996) reported that dermal adherence of dry soil primarily involves particles in the 

<15

size f a but 

also co hest pesticide concentrations. Rodes et al. (2001) reported that the <150 μm 

size fraction com sticide concentrations in house dust increase 

wit e , 1999). 

Becaus

appear 

Par le

inhalation route and an increased

hildren, for whom indirect ingestion of residues from object- and hand-to-mouth activities is 

articularly important, may be most strongly affected. Particle-bound residues may also have a 

reduced potential for dermal absorption, as a consequence of being bound to the particle. 

 Pa ticle-Bound Pyrethroid Residues: Implications toward Exposure 

 re ent shift in commonly applied residential pesticides from organophosphate to pyrethroid 

pounds carries with it important implications for human exposure. The chemical and 

l properties of a pesticide govern its behavior with respect to movement and fate

era , pyrethroids have properties that favor the particulate phase, resulting in transport 

isms preferentially involving dust rather than vapor. A tendency tow

p

relative importance of

tic es applied in homes translocate from the point of application and deposit onto non-target 

s. Because human contact with target surfaces (e.g., cracks and crevices) is typically 

lic tion into the air and onto non-target surfaces that results in exposure. The movement of

de tially applied insecticides follows a complex and poorly understood process of 

rmation and phase distribution and is influenced by several factors, namely: delivery 

system, application surface type, solvent, formulation, physico

insecticide, and human a

O ra , pyrethroids have similar physicochemical properties, and as a result, they display 

ilar behavior in the residential environment (Laskowski, 2002; Oros and Werner, 2005). 

oids generally have low vapor pressures and Henry’s Law constants, thus they resist 

zation and exist almost entire

h o tanol/water partition coefficients (Kow), which suggests they tend to partition into lipids, 

y high water/organic carbon partition coefficients (Koc), which suggests that they also 

 partition into organic matter. With these characteristics, pyrethroids can be expected to 

adily to the particulate matter that comprises house dust. Particles resuspended by human 

 then act as the primary vector for pyrethroid transport and 

Particle-phase contaminant transfer is strongly par

K

0 μm size fraction. Assuming that house dust behaves similarly with respect to transfer, the

r ction that preferentially adheres to skin not only comprises the bulk of house dust, 

ntains the hig

prises about 60% of house dust. Pe

h d creasing particle size, and are highest in the <25 μm size fraction (Lewis et al.

e the surface-to-volume ratio similarly increases with decreasing particle size, pesticides 

to be primarily attached to the surfaces of the particles (rather than trapped within). 

tic -bound movement and transfer of pyrethroids imply a decreased importance of the 

 importance of the indirect ingestion route. Exposure of young 

c

p

80
81

sidues on foods resulting from 

ontact with hands and surfaces during consumption as well as the ingestion of pesticide residues 

mples were collected at both homes and 

aycares. Duplicate diet samples were also collected in three pilot-scale studies, CHAMACOS 

ained 

5.0 DIETARY EXPOSURE MEASUREMENTS 

5.1 Introduction and Data Availability 

Diet can be a significant pathway of exposure to humans. Infants and young children may be 

particularly vulnerable to exposure by dietary ingestion because they eat more than adults do 

relative to their body weights. Foods may contain residues of pesticides because of intentional 

agricultural applications or they may become contaminated during processing, distribution, 

storage, preparation, and even consumption. The ingestion of re

c

while mouthing contaminated hands and objects are considered “indirect ingestion” pathways 

and are the subject of the next chapter (Chapter 6.0). This chapter provides a comparative 

summary of measurements of pesticides in duplicate diet samples and of estimated dietary 

intakes. The sample collection methods for the studies that included duplicate diet 

measurements are summarized in Table 5.1. 

Among the large observational studies, duplicate diet samples were collected in NHEXAS-AZ, 

MNCPES, and CTEPP. In CTEPP, food and beverage sa

d

(20 participants), DIYC (three participants), and JAX (nine participants). 

• The most common measure of dietary exposure was by composited duplicate diet 

analyses (Table 5.1). This approach reduces study costs compared to analyzing 

individual foods, but it increases the complexity of the sample analysis and produces 

higher method detection limits. 

• Duplicate diet samples measure the pesticide residues in the children’s foods after 

processing and preparation by the caregiver. The samples, therefore, may include 

residues from contaminated food handling surfaces in addition to the residues cont

in the food products. However, duplicate diets fail to capture the additional intake of 

pesticides resulting from the child’s activities before and during consumption, as 

discussed in Chapter 6. 

• Duplicate plate samples were used for dietary measurements at the daycares in CTEPP. 

The distinction between a duplicate plate and a duplicate diet (with the latter accounting 

for uneaten foods) is typically more important for children than adults because significant 

quantities of food may be left uneaten. 
82

Table 5.1 Dietary exposure sample collection methods for pesticides. 

Study 

Children 

Ages 

(years) Sampl

Collection 

e Type Sa 

aft

Pes

er Indoor 

ticide Use

Mass 

Recorded

Collection 

Period mple Handling Composite R

NHEXAS-AZ 6 - 12 Duplicate qui d

lle i

ly

nt

 diet No No 24 hr Li

copoco

d and solid foo

cted separately

ethylene 

ainers 

n 

Yes Chlorpyrifo

MNCPES 3 - 12 Duplicate qui d

lle ; 

lid

te

sti

em

diet No Yes 4 d Li

cosopope“r

d and solid foo

cted separately

 food split into 

ntially “high 

cide” foods and

aining” foods 

Yes Chlorpyrifo

permethrin, 

CTEPP 2 - 5 Duplicate

(homes), duplicate (at daycare ce

48 qui d

lle i

as

 diet 

and 

servings 

nters)

No Home 

samples only 

 hr Li

cogl

d and solid foo

cted separately

s jars 

n 

Yes Chlorpyrifo

(Ohio only) 

JAX 4 - 6 Duplicate die 24 lid d 

re ne 

nt

Y 

t Yes Yes hr Sosto

co

 and liquid foo

d in polyethyle

ainers 

es Chlorpyrifo

permethrin, cyfluthrin 

CHAMACOS 0.5 - 2 Duplicate Di 24 qui

ly s 

d 

ly

s

Y 

et No Yes hr Li po

anpoclo

d collected in 

carbonate bottle

solid food in 

ethylene zip 

ure bags 

es Chlorpyrifo

permethrin, cyfluthrin 

DIYC 1 - 3 Duplicate die

each food colindividually 

 24 ch

di

gs 

t, N

lected 

Yes Yes hr Ea

inba

 food stored in 

vidual zip-loc 

o Diazinon 
5.2 Pesticide Presence 

Table 5.2 presents the detection limits for the studies. The frequency of detection for the 

selected pe ides is pre in Figur 1. The n 5th percentile concentrations are 

presented in Table 5.3. Data are presen in logn lity plots (Figures 5.2 and 5.3) 

for the large observational field studies and box-and-whisker plots (Figures 5.4 and 5.5) for all of 

the studies e food measurem ts are available (Table 5.1), both concentration and 

intake (mass of compound ingested) are presented. Intake is defined as μg/day in keeping with 

the dietary exposure algorithm of the D otoc 001 ther than as μg/kgbw/day which uld be consisten the r fD) adigm. 

• Reported method detection limits for chlorpyrifos ranged from 0.04 μg/kg in JAX up to 

1.7 μg/kg in CHAMACOS (Table 5.2). 

• Chlorpyrifos was detected in over 50% of the duplicate diet sam s in MNCPES, 

CTEPP, and JAX (Figure 5.1). The median rpyri concentrations in the MNCPES 

and t sam r ice a a e CTEP ples (Table 5.3). 

• Dia o in an e C, a study in which 

there had been prior indoor applications T t that 

con d t in homes with 

rec

• While detection of diazinon in food samples was typically below 30% (Figure 5.1), 

detection immediately following crack and in DIYC was 100%. 

• The logplots (Figures 5.2 and 5.3) show that in the upper half of the distribution (between 

the th and the 95th percentiles), higher concentrations of cis- and trans-permethrin were 

m ed in solid food in North ina homes than in North Carolina daycares or Ohio 

h daycar

• ulations using DIYC data (results not presented) revealed that pesticides 

rred to food during contact with surfaces and handling by a child may increase 

 intake significantly (over 60% under the modeled scenario). 

• Published results from the MNCPES (Clayton et a 003) show that extant residue 

databases can successfully be used to select samples for analysis, potentially reducing 

costs by avoiding analyses of foods not likely to contain measur vels. Care must be 

tak ever, oid neglect

• Me le level these partic s we arely dete everages in any 

of t udies. ure studies h pes des that a pected to be 

found in drinking water may con ing t costly me

• d child consume fa er typ

e of ce foods) (NR 1993). ber of days of collection may 

be less important for children than for adults. 

• The large potential for enzymatic degradation of pesticides (especially chlorpyrifos) 

during food samp torage and ng homogenation prior to analysis has not been 

directl dresse any studie der thi ogra

stic

. W

sented

 mass 

 more 

e 5.

ted 

en

raft Pr

t with

 media

ormal probabi

ol (Berry

eference

 and 9

et al., 2

 dose (R

her

 wo

) ra

 par

ple

 chlo

s high

y of th

he data 

 surface 

fos

s in th

 studies excep

from DIYC s

contact is im

 JA

zin

tam

ent 

X die

on was n

ination of

application

ples we e at lea

t frequently dete

 food due to han

s (see Section 6

st tw

cted 

.

dling an

). 

P sam

t DIY

ugges

portan

crevice application 

 50

easur

omes

Carol

 or es. 

Model sim

transfe

dietary

l., 2 ed

able le

cted in b

re not ex

asurement. 

en, 

asu

hes

how

rab

e st

to av

s of

 Fut

ing those r

ular pestic

with other 

sider elim

esidues that are transferred during handling. 

ide

suc

inat

re r

tici

his 

Infants

much m

 an

or

ren 

rtain

r few

C,

es of foods than do adults (while consuming 

 Thus, the num

le s

d by

duri

y ad s un s pr m. 

83
Table 5.2 Limits of detection (μg/kg) for pesticides measured in duplicate diets. 

Compounds 

Study Chlorpyrifos Diazinon cis-Permethrin trans-Permethrin Cyfluthrin 

NHEXAS-AZ 1.0 0.7 --a -- -- 

MNCPES 0.26 0.3 0.2 0.2 -- 

CTEPP 0.08 0.08 0.08 0.08 0.83 

JAX 0.04 0.04 0.02 0.02 0.4 

CHAMACOS 1.4 1.2 4.5 2.9 -- 

DIYC -- 0.36 – 1.25 -- -- -- a Bla c

Tab 5

food sa

nk ells (--) indicate that the pesticide was not measured in the study. 

le .3 Median and 95th percentile pesticide concentrations (μg/kg) measured in duplicate diet 

mples. 

Chlorpyrifos Diazinon cis-Permethrin trans-Permethrin Cyfluthrin 

Study P50 P95 P50 P95 P50 P95 P50 P95 P50 P95 

NHEXAS-AZ BDLa 5.7 1.8 1.9 --b -- -- -- -- --

MNCPES 0.53 2.4 BDL 0.38 -- -- -- -- -- -- 

CTEPP-NC Home 0.2 2.1 BDL 0.4 BDL 15.6 BDL 8.7 BDL 0.9 

CTEPP-NC Daycare 0.1 0.9 BDL 0.2 BDL 5.2 BDL 3.0 BDL BDL 

CTEPP-OH Home 0.2 1.6 BDL 0.2 BDL 8.8 BDL 8.0 BDL BDL 

CTEPP-OH Daycare 0.1 0.6 BDL 0.2 BDL 2.2 BDL 1.4 BDL BDL 

JAX 0.38 7.4 BDL 1.0 0.29 13 0.22 22 BDL 3.6 

CHAMACOS BDL 1.4 BDL BDL BDL BDL BDL BDL -- -- 

DIY C -- -- 0.17 0.78 -- -- -- -- -- -- a

 BDL, B

b

 Blank c

elow minimum detection limit 

ells (--) indicate the pesticide was not measured in the study 

84
Detection Frequency: Solid Food

Figure 5.1 T e detection frequency of pesticides h measured in duplicate diet food samples. 

Chlorpyrifos Diazinon c-Perm t-Perm Cyfluthrin TCPy IMP

0

10

20

80

90

30

40

50

60

70

100

MNCPES CTE C H PP-N OME

CTEPP-OH HOME JAX

NHEXAS-AZ

DIYC

CTE D RE PP-NC AYCA

CTEPP AY E -OH D CAR CHA OS MAC

Det on Frequency (%) ecti

85
86

Figure 5.2 Lognormal probability plots of solid food concentrations (μg/kg) and intakes (μg/day) 

for chlorpyrifos, diazinon, and cis-permethrin from large observational field studies. 
Figure 5.3 Lognormal probability plots of solid food concentrations (μg/kg) and intakes (μg/day) 

for trans-permethrin, TCPy, and IMP from large observational field studies. 

87
Figure 5.4 Box-and-whisker plots of solid food concentrations (μg/kg) and intakes (μg/day) for 

chlorpyrifos, diazinon, and cis-permethrin across all studies. 

88
Figure 5.5 Box-and-whisker plots of solid food concentrations (μg/kg) and intakes (μg/day) for 

trans-permethrin, TCPy, and IMP across all studies. 

89
5.3 Relative Importance of the Ingestion Route 

The Stochastic Human Exposure and Dose Simulation (SHEDS) model (Zartarian et al., 2000) 

prediction for dietary intake of cis-permethrin is compared to CTEPP measurements in Figure 

5.6. The estimated proportion of aggregate exposure represented by dietary intake for CTEPPNC and CTEPP-OH children is from the CTEPP Report (Morgan et al., 2004) and is presented in 

Figures 5.6 and 5.7, respectively. 

• An example of use of the SHEDS model to predict dietary intake of cis-permethrin in a 

study population is shown in Figure 5.6. The dietary intake estimates may then be 

compared to SHEDS model estimates of intake by other relevant routes to determine the 

relative importance of the ingestion route. 

• Based on route-specific estimates (Figures 5.7 and 5.8), dietary ingestion represents the 

dominant route of exposure for chlorpyrifos, diazinon, and permethrin in the CTEPP 

study. Indirect ingestion, estimated based on dust and soil measurements, is a far greater 

concern for the permethrin than for chlorpyrifos and diazinon in the CTEPP study. 

• The route that represents the dominant route of exposure (dietary ingestion) is also the 

route with the lowest detection frequencies (approximately 2/3 of the values for 

permethrin in CTEPP are nondetects), which increases the uncertainty in the estimates. 

Substituting a fraction of the detection limit for values below the limit of detection may 

have a disproportionate impact on the outcome. 

0

0.5

1

1.5

45 50 55 60 65 70 75 80 85 90 95 100

Percentile

ug/kg/day

SHEDS model Observed data

Figure 5.6 Comparison of SHEDS model prediction for dietary intake of cis-permethrin 

(μg/kg/day) and CTEPP measurement data. 

90
91

Figure 5.7 Estimated mean proportion of aggregate potential exposure for CTEPP-NC children 

by exposure route. (TCP = 3,5,6-Trichloro-2-pyridinol; cis-P and trans-P = cis- and transPermethrin; 2,4-D = 2,4-Dichlorophenoxyacetic acid.) From Morgan et al., 2004. 
Figure 5.8 Estimated mean proportion of aggregated potential exposure for CTEPP-OH chil

by exposure route. (TCP = 3,5,6-Trichloro-2-pyridinol; cis-P and trans-P = cis- and

dren 

transPermethrin; 2,4-D = 2,4-Dichlorophenoxyacetic acid.) From Morgan et al., 2004. 

92
6.0 INDIRECT INGESTION MEASUREMENTS 

Children’s ingestion of pesticide residues is not limited to residues in food and beverages 

acquired during cultivation, food production, and in-home preparation. Indirect ingestion refers 

to the ingestion of residues from hands or objects that enter the mouth, as well as to the ingestion 

of residues transferred to food items by contact with the floor or other contaminated surfaces 

during consumption. Indirect ingestion is believed to be an important route of exposure for 

children because of their frequent mouthing activities and their unique handling of foods while 

eating. Indirect ingestion may be the result of hand-to-mouth, object-to-mouth, or hand-toobject-to-mouth activity. Indirect ingestion may be estimated using an approach that lumps 

some of the exposure factors and activity patterns associated with indirect ingestion. This 

simplified approach allows for assessment of indirect ingestion exposure based on measurement 

data collected in the field and on factors that characterize the activities that lead to indirect 

ingestion. In this approach, objects (including food) that are commonly handled, mouthed, 

and/or ingested are identified in the field. The residue loadings on these objects are measured 

directly or estimated from surface loading measurements combined with transfer efficiencies 

measured in the laboratory. General information relating to the frequency and nature of these 

mouthing and ingestion activities is also collected. Data on the fraction of residues that may be 

removed from an object during mouthing that has been collected in the laboratory is then 

required to complete the assessment. In addition, the items identified as most often mouthed 

and/or eaten are assumed to represent the most significant sources of indirect ingestion exposure. 

This section presents summary data for studies addressing the indirect ingestion route of 

exposure (Table 6.1). Highlights of the data are presented below. 

6.1 Characterizing Hand- and Object-to-Mouth Activities 

Exposure models are based on two factors: how much pesticide residue is available for human 

uptake and what human activities occur that would result in contact with and uptake of residues. 

Hand-to-mouth and object-to-mouth activities are believed to directly impact ingestion of 

pesticides among children through the indirect ingestion exposure route, but the relative 

importance of these activities has not been established. In fact, the lack of empirical data 

showing that either hand- or object-to-mouth activities appreciably affect exposure makes it a 

hypothesis that has not yet been adequately addressed. The frequency of hand-to-mouth, objectto-mouth, and/or combo-to-mouth contacts were quantified for children in the MNCPES and 

CPPAES studies using a computer software syst (Table 6.2). These studies used Virtual 

s. 

• Assigning contact as either a hand-to-mouth or an object-to-mouth contact can cause the 

hand-to-mouth and/or object-to-mouth contacts per hour to be underestimated. A comboto-mouth category that accounts for both simultaneous types of contacts may provide a 

more accurate estimate of the indirect ingestion route of exposure. 

• An average frequency of 9 hand-to-mouth contacts per hour among 2 to 5 year olds is 

recommended for regulatory risk assessments (US EPA, 2002). The CPPAES results 

suggest that a higher value may be appropriate (Table 6.3). 

em

Timing Device (VTD) software (Zartarian et al.. 1997) to quantify the children’s normal daily 

activities captured on videotape. The following are highlights of the data from these studie

93
94

outh contacts during 

all eating and non-eating events. The highest hand-to-mouth frequency was observed in 

et 

or indirect ingestion estimates, objects that are commonly mouthed are identified in the field 

ts commonly mouthed by 

preschoolers were identified in CTEPP. Pesticid loadings on toy surfaces were measured in the 

s 

Measurements from CPPAES (data not presented) suggest that surface wiping of plush 

• boflavin) as part of 

icantly different from zero in 

only one-half of the replicates). 

• Figure 6.1 presents the average frequency of hand- and object-to-m

CPPAES. 

• Factors affecting hand-to-mouth contact frequencies may include inclusion of eating 

events, amount of time on tape, types of activities, number of children, and age range. 

• An analysis of hand-to-mouth activities in MNCPES has been published by Freeman 

al. (2001). They reported that hand-to-mouth activities were significantly more frequent 

(t test, P<0.05) among girls than among boys. 

• The MNCPES data also showed that hand-to-mouth and object-to-mouth activities were 

more frequent (Mann–Whitney, p<0.05) indoors than outdoors (Freeman et al., 2001). 

• Published studies have quantified the hand- and object-to-mouth activities of young 

children (Zartarian et al., 1998; Reed et al., 1999; Tulve et al., 2002; Freeman et al.,

2005). These studies suggest that young children may exhibit higher hand-to-mouth 

and/or object-to-mouth contacts than older children and adults. 

• Standardized approaches for quantifying the activity patterns of children are needed in 

order to compare results among different studies. 

6.2 Residue Loadings on Mouthed Objects and Removal by Mouthing 

F

and the residue loadings on these objects are measured. Objec

e

CHAMACOS and CPPAES studies. Data on the fraction of residues that may be removed by 

mouthing of fingers was collected in the laboratory-based Transfer studies using non-toxic 

fluorescent surrogates. 

• Objects commonly mouthed by preschoolers were identified in CTEPP. These item

were typically toys and food-related items (Table 6.4). 

• Chlorpyrifos loadings on toy surfaces were much higher following recent applications, as

evidenced by the higher values in CPPAES than in CHAMACOS (Table 6.5). Loading 

on toy surfaces in CPPAES (Table 6.5) were greater than surface loadings as measured 

by deposition coupons (Table 4.4). 

•

toys yields only a small fraction of the total amount of chlorpyrifos absorbed into the toys

(as measured by extraction). Indirect ingestion among children who regularly mouth soft 

toys may thus be underestimated by toy surface wipes. 

In “transfer off” experiments conducted with a fluorescent tracer (ri

the Transfer studies, removal from skin via the mouthing of 4 fingers was measured. 

Eight replicates were performed with each of three participants (data not presented), with 

0 to 26% of the tracer removed per replicate (loss was signif
95

ethods for the transfer of d or objects.

ai le Han

Composit In es 

pesticide surface resi

ls 

Collected After 

Application 

dues t

Samp

o foo

Study Study Type Age Range Sampling Det dling 

e 

Sample 

secticid

Measured 

Fo(SuFo

fo

d 

 extra

i diatelyf ing s ing 

od 

rfaces to 

ods) 

Laboratory n/a 1, 10, &

contact and consurfaces

 60 min 

between 

taminate

od 

Yes-1 hr following applications 

Foods

mme

ollow

ampl

cted No C

DHIsMP

hlorpyrif

iazinon eptachlo

ofenpho

alathion

ermethri

os 

r 

s 

n 

Fo(Ti d 

e 

 extra

i diatelyf ing s ing 

od 

le to Foods) 

Laboratory n/a 10 min 

betweencontamisurface 

contact 

 food an

nated til

Yes-1 hr following applications 

Foods

mme

ollow

ampl

cted No C

CCDFMP

hlorpyrif

yfluthrinypermet

eltameth

ipronil 

alathion

ermethri

os 

hrin 

rin 

n 

DIYC r food

er 

Collected in i dual zi

e bags

Field 1-3 y Handled

untouchfood, fo

 leftover

ed leftov

od press 

, Yes 

ndivi

closur

p 

Yes Diazinon 

CHAM d .5 g ri small 

vid days 

am

d at -20 C

nalysis 

os 

n 

ACOS Fiel 0.5-2 yr Teethin 

ball probefore s

ng or 

ed 1.5

pling 

No Store

until a

No C

DP

hlorpyrif

iazinon 

ermethri

CPPA d y gi to 

han or 11 

No information o os 

ES Fiel <5 yr Plush to

child to days 

ven 

dle f

Yes N Chlorpyrif 

Transfer Laboratory Adult g r al of 

ent r 

Videofluorescence imaging 

o 

n) 

S(

urrogate 

Riboflavi

emov n/a N

 trace

Mouthinfluoresc

Table 6.1 Collection mn/a, Not applicable
Table 6.2 Videotaped children’s hand- and object-to-mouth activity details. 

Study N 

Age Sam

Lo Time Period 

pling 

cation Method of Analysis

A

(years) 

ctivity of 

Interest Availability 

MNCPES 19 3 to 12 

out

H

(in

an

4 consecutive 

ours in norma

aily activities

omes 

side 

d/or 

side) 

h

d

l 

Methods of Reed et 

al., 1999 

Hand-to-mouth 

Object-to-mouth 

Freeman et al., 

2001. 

CPPAES 10 2 to 5 Hom s rs on Day 

llo

Computer software

(Virtual Timing 

Device) 

uantified 4 hours 

of videotape for 

both hands 

e

ide o

side

(ins

out

r 

) 

4 

a

hou

2 fo

cr

c

pp

chlorpyri

win

 an

ice

tion

f

g 

d 

 of 

os 

ack

rev

lica Q

Hand-to-m h out Freeman et al., 

Object-to-mou 2004. th 

le 6.3 V otaped hand- outh and object-to-mouth counts. 

and-to-Mouth Object-to-Mo

Tab ide to-m

H uth 

Study Mean Median Mean Median Eating Events 

CPPAES (2 to 5 yrs) 19.8 16 8.4 6.4 Unspecified 

Tulve a ≤ 24 month old 18 12 45 39 Excluded 

Tulve onth old >24 m 16 9 17 9 Excluded 

MNC o PES (3 t 12 yrs) 5.7 2.5 1.8 0 Unspecified 

MNCPES boys indoor 4.7 NR 1.0 NR Unspecified 

MNCPES girls indoor 8.1 NR 2.6 NR Uns fied peci

NR,

a Tul

Tab

 Not Report

ve d Tu et al., 2002) included for comparison. 

le 6 monl by presch CTEPP. 

C ems 

ed 

lve 

bjects com

 It

ata (

.4 O y mouthed oolers in

ategory

Toys Plastic rings/bracelets, stuffed animals, balls, walkie tal building blocks, 

doll, bubble blower 

kie, 

Food-R tems Ice pop ndy wrapper, water le, utensils, napkins nks elated I s, ca bott , dri

Mis us Plastic bl w-up chair, pens, greeting cards, clothing, CDs, towels, blanket, pet cellaneo o s

96
Table 6.5 Median and 95th percentile pesticide loadings (ng/cm2) measured on toy surfaces. 

Chlorpyrifos Diazinon cis-Permethrin trans-Permethrin cyfluthrin 

Study P5 5 0 P95 P50 P9 P50 P95 P50 P P95 50 P95 

CHAMACOS BDLa 0.15 0.034 0.27 BDL 0.053 BDL 0.072 BDL BDL 

CPPAES 3.0 21 -- - -- -- b -- -- - -- -- 

a

 BDL, Below minimum detec

lls (- d p a

 

tion limit 

b

 Blank ce -) in icate the esticide w s not measured in the study 

0

5

10

Fr

15

quenc

20

y (

25

nts/

30

40

hr)

35 CPPAES 2-5 yr.

Tulve ≤ 2 yr.

Tulve >2 yr.

MNCPES Girls ≤ 13 yr.

M ES Boys NCP ≤ 13 yr.

e eve

Hand-to-Mouth Object-to-Mouth

Figure 6.1 Compariso hour 

among CPPAES and MNCPES children. MNCPES values are means instead of medians. Tulve 

d 00

n of the median hand-to-mouth and object-to-mouth contacts per 

ata (Tulve et al., 2 2) included for comparison. 

97
6.3 Transfer of Pesticide Residues to Food 

• periments reported here (Appendix B, Tr r S s) lo s t

ear to o er th percentil oa in t o ec el

 food occurred from hard, smooth surfaces, such as hardwood 

xample, 33% of chlorpyrifos was 

transferred from wood flooring to an apple, whereas the amount transferred from carpet 

was not enough to be reliably quantified (Table 6.6). 

oist and fatty food, removed a higher percentage of pesticides from a hard 

id fruit leather, a low-fat and low-water content food (Table 6.7). 

• Comparison (Table 6.8, Figure 6.2) of measured dietary intake of diazinon (incorporating 

excess contamination due to handling) with estimates predicted by the Children’s Dietary 

Intake Model (CDIM) suggests that use of fixed values for transfer efficiencies and for 

activity factors in the model may result in inaccurate estimates of daily dietary intake. 

Model-predicted estimates generally under-predicted intake. 

• Diazinon concentrations in untouched leftover food were compared with those in handled 

leftover food in DIYC. Daily dietary intake estimates accounting for contamination due 

to handling by children were often double the intake estimates based on untouched food 

(Total Measured Dietary Intake vs. Duplicate Diet Intake, Table 6.8), indicating that 

duplicate diets may significantly underestimate actual intake in homes that have high 

surface pesticide residue loadings. 

• Food transfer studies have provided evidence that transfer of pesticide residues from 

surfaces to foods is dependent on such factors as pesticide class, food type, contact 

duration, and contact force (data not presented). 

• Applied force produced a considerable increase in transfer efficiency (data not 

presented). Moreover, the effect of applied force was even more dramatic as contact 

duration increased. 

The ex Food ansfe tudie used ading hat 

were n r great than e 95th e for l dings mos f the r ent fi d 

studies (See Table 4.4). 

• Higher pesticide transfer to

flooring; lower transfer occurred from carpet. For e

• Bologna, a m

surface than d

98
Table 6.6 The transfer efficiency (percent transfer, mean ± sd) of pesticide residues from treated 

ipes), after a 10-min contact duration (Food 

ransfer Studies). 

surfaces to foods (relative to transfer to IPA w

T

Treated Surface 

Pesticide Sampling Media N Ceramic Tile Wood Flooring Carpet 

Bologna 2 36 ± 20 15 ± 4 BQL a

Apple 2 18 ± 5 33 ± 8 BQL 

Chlorpyrifos 

(2 38 ng/cm2) 

Cheese 2 7 ± 0 26 ± 1 BQL 

1-

Bologna 2 41 ± 5 29 ± 0 BQL 

Apple 2 35 ± 8 50 ± 5 BQL 

D

0-

QL 

iazinon 

(2 30 ng/cm2) 

Cheese 2 20 ± 7 103 ± 18 B

Bologna 2 60 ± 21 31 ± 1 BQL 

Apple 2 132 ± 74 18 ± 1 212 ± 60 

M

3-

alathion 

(3 45 ng/cm2) 

Cheese 2 94 ± 33 52 ± 37 400 ± 173 

Bologna 2 19 ± 15 70 ± 86 BQL 

Apple 2 26 ± 13 3 ± 1 BQL 

cis-

(40-

Permethrin 

53 ng/cm2) 

Cheese 2 BQL BQL BQL 

Bologna 2 23 ± 20 10 ± 1 BQL 

Apple 2 29 ± 14 5 ± 0 BQL 

trans

(43-

-Permethrin 

55 ng/cm2) 

Cheese 2 BQL BQL BQL 

a BQL = Below Quantitation Limit 

99
Table 6.7 The transfer efficiency (percent transfer, mean ± sd) of pesticide residues from a 

treated ceramic tile surface to various foods and to an IPA Wipe (Food Transfer Studies). 

Pesticide Class Pesticide Sampling Media N % Transfer 

Bologna 3 64.7 ± 15.0 

Apple 3 27.5 ± 8.0 

Chlorpyrifos 

(123 ng/cm2) 

Fruit Leather 3 13.5 ± 2.0 

20-mL pe 3 99.8 ± 10.8 IPA Wi

Bologna 3 74.9 ± 17.7 

Apple 3 29.7 ± 8.4 

Fruit 3 8.7 ± 2.7 Leather

Orga ate 

n 

( 2) 

20-mL pe 3 4.6 ± 10.9 

nophosph

Malathio

193 ng/cm

IPA Wi 10

Bologna 3 47.8 ± 13.4 

Apple 

Cyfluthrin

3 24.0 ± 3.4 

Fruit Leather 3 0.7 ± 0 

(1 2) 

20-mL 3 08.5 ± 12.1 

43 ng/cm

Pyrethroid 

IPA Wipe 1

Bologna 3 45.0 ± 10.7 

Apple 3 21.5 ± 6.9 

Fruit Leather 3 0.6 ± 0 

Cy n 

(1 2) 

20-mL 3 101.5 ± 7.0 

permethri

85 ng/cm

IPA Wipe 

Bologna 3 39.2 ± 6.1 

Apple 3 22.2 ± 5.1 

Fruit Leather 3 2.4 ± 0.2 

D rin 

1 ng/cm2) 

20-mL IPA Wipe 3 83.7 ± 4.3 

eltameth

(21

Bologna 3 44.0 ± 11.5 

Apple 3 19.8 ± 7.1 

Fruit Leather 3 1.3 ± 0.1 

Permethrin 

(147 ng/cm2) 

20-mL IPA Wipe 3 100.8 ± 4.8 

Bologna 3 43.3 ± 1.6 

Apple 3 30.9 ± 14.8 

Fruit Leather 3 2.0 ± 1.7 

Phenylpyrazole Fipronil 

(203 ng/cm2) 

20-mL IPA Wipe 3 103.8 ± 10.4 

100
Table 6.8 The measured and predicted ingestion (ng/day) of diazinon from the DIYC. 

Duplicate Diet 

Intake

Excess Dietary 

Intake a

Total Measured 

ake b

CDIM Predicted 

ietary 

Percent 

rence d Dietary Int D Intake c Diffe

Child Day ng/ ng/d g/d ng/ % 

Sampling 

d n d 

Pre 197 384 581 357 -39 

1 1063 1270 127 2333 1 -46 

4 280 220 500 281 -44 

5 270 501 71 33 7 3 -57 

6 140 322 462 142 -69 

7 563 536 702 -36 1099

1 

8 253 160 413 397 -4 

1 455 156 11 66 6 3 9 

2 233 95 328 402 23 

3 212 373 585 392 -33 

4 260 414 674 612 -9 

2 

5 188 189 77 27 3 8 -26 

3 2 95 90 185 509 175 

8 412 344 756 940 24 

a Measured surface-to-food and hand-to-food transfer d ods, i but uneaten 

portion extrapolated to eaten po

b Duplicate Diet intake plus Exc ke. c Estimated by deterministic mo transfer efficiency and activity values. 

d Percent Difference = 100*[(CDIM Predicted Intake – T ake)/ al Meas )]. 

ue to handling of fo concentrat on in handled 

rtion. 

ess Dietary inta

del using fixed

otal Measured Int (Tot ured Intake

101
0

2500

500 1000 1500 2000 2500

0

500

1000

1500

2000

Me ured Intak d)

Predicted Intake (ng/d

 

red and predicted ingestion of diazinon (ng/day) from the 

al slope of 1. Measured intake generally exceeds 

e. 

as e (ng/

)

Figure 6.2 Comparison of measu

DIYC. Dashed line represents a hypothetic

predicted intake, as indicated by the majority of points lying to the right of the dashed lin

102
6.4 Indirect Ingestion of Dust and Soil 

The potential indirect ingestion exposure (ng/day) can be estimated using indoor floor dust 

(ng/g) and outdoor soil sample concentrations (ng/g) together with the child’s body weight (kg), 

estimated daily dust ingestion rate (g/day), estimated daily soil ingestion rate (g/day), and the 

estimated oral bioavailability. In CTEPP, the daily dust ingestion rates were calculated based on 

questionnaire responses related to specific activities of each child in the month prior to field 

sampling. These activities included pacifier use, teething, mouthing body parts, licking floors, 

and placing toys or other objects into the mouth. The daily soil ingestion rates were estimated 

based on how often a child played with sand/dirt and ate dirt, sand, or snow. Many of these 

parameters have very high uncertainty associated with them. The daily dust and soil ingestion 

rates were each estimated as 0.025, 0.050, or 0.100 g/day. The indirect exposure estimates, 

presented in Table 6.9, showed the following: 

• Indirect ingestion estimates for the permethrin isomers were much higher than for 

chlorpyrifos or diazinon, largely because permethrin was measured at much higher 

concentrations in floor dust (Figures 4.6 and 4.7). 

• The differences between NC and OH in mean permethrin concentrations in dust suggest 

potential regional differences in indirect ingestion. 

Table 6.9 The estimated exposures (ng/day) of NC and OH preschool children in the CTEPP 

study to chlorpyrifos, diazinon, and permethrin through indirect ingestion. 

Pesticide State N Mean SD GM GSD Min P25 P50 P75 P95 Max 

Chlorpyrifos NC 117 15.5 29.0 6.2 1.3 0.3 2.8 5.2 14.8 80.4 233 

OH 116 27.8 164 3.0 1.5 0.2 1.1 2.7 6.2 33.5 1570 

Diazinon NC 118 21.7 81.9 1.6 2.0 <MDL 0.4 1.0 4.3 150 622 

OH 116 49.1 367 1.5 1.9 <MDL 0.4 1.0 3.4 45.3 3800 

cis-Permethrin NC 120 220 670 48.4 1.6 1.7 17.1 48.1 113 718 4540 

OH 116 61.5 139 21.3 1.4 1.9 7.8 17.9 52.7 327 1210 

trans-Permethrin NC 120 222 698 42.7 1.7 1.1 11.9 35.4 119 680 4800 

OH 102 61.2 153 16.6 1.5 1.2 5.3 11.7 45.9 210 1190 

<MDL, less than method detection limit 

103
6.5 Indirect Ingestion: Summary 

As shown in the bulleted lists of observations from these laboratory and observational studie

progress has been achieved in identifying and quantifying a number of factors that are believed 

to potentially impact indirect ingestion among children. 

• Videotape analysis of children’s hand- and object-to-mouth contacts has provided 

evidence that hand-to-mouth activities were more frequent: among infants and toddlers 

than among older children, among girls than among boys, and at indoor locations than a

outdoor locations. 

• Objects most commonly mouthed by preschoolers were identified as typically being toy

and food-related items. 

s, 

t 

s 

• High chlorpyrifos loadings were measured on toy surfaces following routine residential 

•

onal information is still needed on the 

At high surface loadings, pesticide transfer to food was greater from hard, smooth 

surfaces than from carpet. 

In homes with high surface pesticide residue loadings, residue concentrations in foods 

handled by children were often twice as high as concentrations in leftover unhandled 

foods. 

ch 

rce. 

non, y au m in re u g o r s 

r dust.

application. 

Fluorescent tracer experiments found that removal from skin (at very high tracer 

loadings) by mouthing was highly variable. Additi

fraction of residue transferred from the hands to mouth during typical mouthing events at

dermal loading levels observed in field studies. 

•

•

• The transfer of pesticide residues from surfaces to foods appears to be dependent on su

factors as pesticide class, food type, contact duration, and applied fo

• Indirect ingestion estim

diazi

ates for perm

se per

ethrin 

 was

were much higher than for chlorpyrifos or 

largel bec ethr measu d at m ch hi her c ncent ation in 

floo

104
7.0 DERMAL EXPOSURE MEASUREMENTS 

ated surfaces such as floors and 

rniture is potentially significant. Once on the skin, residues and contaminated particles can be 

tran r nt or 

washin

better u

skin an al loading will reduce uncertainty in exposure assessment. Areas of 

unc a

tran r

removal. Laboratory tests were conducted by NERL using nontoxic fluorescent tracers to 

eva t

(Sectio

Me r

studies

differen

betwee , 2003). Furthermore, differences in 

der

pesticid rpreting the results. Results of wipes and rinses in selected 

stud s

An alte

to the approach used for measuring occupational exposures to pesticides, cotton garments, which 

can n

(Sectio

Imp t

Dermal exposure to surface residues is dependent on human activities that result in contact with 

rfaces and the physicochemical and mechanical mechanisms of transfer of residues from the 

rface to the skin. Several factors are commonly believed to affect transfer (Table 7.1). These 

factors can be grouped as characteristics of the surface (including contaminant loading, type of 

surface, and temperature), of the contaminant (including formulation, physical state, particle size, 

vapor pressure, viscosity, water solubility, lipophilicity, and being particle-bound), of the skin 

(including moistness and contact area), of contact (including duration, force, frequency, motion, 

and interval), and of protection measures (including clothing and hand washing). 

Many of these have previously been investigated, though not necessarily specific to pesticides 

and skin. Kissel et al. (1996) reported moisture content and particle sizes of soil to be significant 

factors affecting the process of adherence to skin. Rodes et al. (2001) reported that only about 

1/3 of the palm contacted surfaces during a press and that dust-to-skin transfer increased with 

hand dampness, decreased as surface roughness increased, and decreased with consecutive 

presses (requiring about 100 presses to reach equilibrium). Brouwer et al. (1999) reported that 

The ability to accurately estimate surface-to-skin transfer of contaminants from intermittent 

contacts remains a critical and missing link in pesticide exposure and risk assessments. For 

children’s exposures, transfer of chemicals from contamin

fu

sfe red back to the contaminated surface during subsequent contact, lost by dislodgeme

g, or transferred into the body by percutaneous absorption or hand-to-mouth activity. A 

nderstanding of the relevant factors influencing transfers from contaminated surfaces to 

d the resulting derm

ert inty with respect to dermal transfer are related to the important factors that impact 

sfe , whether or not a steady-state condition is reached, and the conditions that affect 

lua e significant transfer parameters. The results of these tests are described in this section 

n 7.1). 

asu ements of pesticide residues on children’s hands have been performed in a number of 

. Both hand wipe and hand rinse methods have been used. The collection efficiency of 

t wipe and rinse methods can be expected to differ, with an eight-fold difference reported 

n hand rinses and hand wipes in one study (Hore

mal exposure and dose due to free pesticide residue versus particle- (or dust-) bound 

es may be important in inte

ie are summarized in tables and figures presented below (in Section 7.2). 

rnative approach for estimating dermal exposure is the cotton garment surrogate. Similar 

 co sist of a bodysuit and/or socks, have been used in three studies that are reported below 

n 7.3). 

or ant Factors Affecting Transfer 

su

su

105
whereas only 4-16% of the surface area of the palm of the hand is covered with a fluorescent 

acer after one contact with a hard surface, about 40% becomes covered after twelve 

rted 

ts were performed to evaluate transfer efficiencies (TEs) of nontoxic fluorescent 

acers (as surrogates for pesticide residues) from common household surfaces to hands (Cohen 

r 

os, and that the 

transfer of Uvitex is similar to that of the pyrethroids permethrin and esfenvalerate. 

and sticky skin (over moist or dry). Contact duration and pressure (force) were 

• Comparison of “first contact” to “repeated contact” results (Table 7.4) suggests that the 

s appear to 

reach a maximum by the fourth or fifth contact (data not presented), suggesting a 

, 

tr

consecutive contacts. At least three studies have investigated the transfer of pesticides from 

surfaces to hands (measured using IPA wipes of hands.). Briefly, Lu and Fenske (1999) repo

transfer of chlorpyrifos residues to hands to be 0.04 to 0.26% from carpets and 0.69% from

furniture. Camann et al. (1996) examined transfer from nylon carpet to dry or moistened hands 

and reported transfers ranging from 0.7–1.3% for chlorpyrifos, 2.9–4.8% for pyrethrin I, and 

1.5–2.8% for piperonyl butoxide. Clothier (2000) examined transfer of the same residues from 

vinyl sheet flooring and reported transfers of 1.5% to dry and 4.4-5.2% to wet skin for 

chlorpyrifos, 3.6% (dry) and 8.9 – 11.9% (wet) for pyrethrin I, and 1.4% (dry) and 4.1-4.8% 

(wet) for piperonyl butoxide. 

7.1 Laboratory Fluorescent Measurement Studies 

Laboratory tes

tr

Hubal et al., 2005). The laboratory studies evaluated parameters affecting surface-to-hand 

transfer, including surface type, surface loading, contact motion, pressure, duration, and skin 

condition in two sets of experiments (Table 7.2). The data from the laboratory fluorescent 

measurement studies are presented in Tables 7.3 to 7.6 and Figures 7.1 and 7.2. 

• Tests comparing fluorescent tracers with pesticides (Figure 7.1) showed that the transfe

of riboflavin to PUF rollers and C18 disks is similar to that of chlorpyrif

• Laboratory studies using fluorescent tracers riboflavin and Uvitex OB (Tables 7.3 to 7.6) 

indicated that tracer type, surface type, contact motion, and skin condition were all 

significant factors. Transfer was greater with laminate (over carpet), smudge (over 

press), 

not important factors. 

effect of surface type appears to diminish with repeated contact while the effect of skin 

condition (moist vs. dry) appears to increase with repeated contact. 

• Laboratory surface loadings (0.2 and 2.0 μg/cm2) were much higher than the median 

values of 0.032 and 0.0014 μg/cm2 measured by deposition coupons (Table 4.4) after 

crack and crevice application of chlorpyrifos in the Test House and CPPAES studies, 

respectively, 

• In the initial tracer experiments with high surface loadings, dermal loading

saturation effect. In the follow-up experiments with lower surface loadings (Figure 7.2)

dermal loadings appear to increase linearly through the seventh contact, suggesting that at 

lower surface loadings, more contacts may be required to reach steady state. 

• In “transfer off” experiments described earlier (Section 6.2), the amount removed from

fingers by mouthing was significantly different from zero in only half of the replicates. 

106
107

Table 7.1 Factors commonly believed to affect dermal transfer. 

Category Parameter Source 

Surface Level of contamination Goede et al., 2003; This Report 

Type of surface: roughness, carpet vs. hard 

surface 

Brouwer et al., 1999; Rodes et al., 2001 

Formulation Marquart et al., 2005 

Physical state: solid, liquid Marquart et al., 2005 

Particle characteristics: particle size 

distribution, moistness 

Kissel et al., 1996 

Liquid characteristics: viscosity and related Marquart et al., 2005 

properties 

Contaminant 

Physical properties of active ingredient: 

vapor pressure, water solubility, lipophilicity 

This Report 

Moistness Camann et al., 1996; Clothier, 2000; Rodes et 

al., 2001; This Report 

Skin 

Contact area Brouwer et al., 1999 

Frequency: number of contacts or objects Brouwer et al., 1999; Rodes et al., 2001; Th

Report 

is 

Interval between contacts Camann et al., 1996; 

Contact 

Motion: press, smudge, drag Lu and Fenske, 1999; 

Protection Clothing: use, area covered, material Marquart et al., 2005 

Hand washing: frequency This Report 

Cate ri

Table 7.2 Study param

Pesticide Residue Transf

go es and parameters modified from Marquart et al., 2005. 

eters tested in surface-to-skin transfer experiments in the Characterizing 

er Efficiencies study. 

Parameter Initial Experiments Refined Experiments a

Tracer Riboflavin a Riboflavin b or Uvitex c

Skin Condition Dry, Moist, or Sticky Dry or Moist 

Surface Type Carpet or Laminate Carpet or Laminate 

Surface Loading 2 or 10 μg/cm2 0.2 or 2 μg/cm2

Contact Motion Press or Smudge Press or Smudge 

Contact 2 sec or 20 sec --d Duration 

Cont t P ac ressure 7 or 70 kg/cm2 -- 

Contact Number Multiple Multiple 

a Refined

b Relativ

c Relativ

d Bla c

 experiments added Uvitex, reduced the loading levels, and reduced the number of parameters tested 

ely water soluble 

ely water insoluble 

nk ells indicate that parameter was not investigated in the study 
Table 3 n n r ati low surface-t kin tr fer experiments (init

(Source

nditi Surface type 

 7. S

: C

ki

oh

 l

en

oa

 Hu

din

bal

gs (

et 

me

al.,

an, 

 20

sta

05.)

H

da

and

d d

 co

evi on) measured fol ing o-s ans 

Su

on 

Contact Dry Moist cky Carpet Laminate High Sti 

Skin loading, μg/cm2, average (SD) a

1 0.3 (0.6) 0.4 (0.3) 0.7 (0.6) 0.4 (0.5) 0.5 (0.5) 0.6 (0.6) 2 0.4 (0.4) 0.9 (0.6) 1.2 (0.7) 0.8 (0.7) 0.8 (0.6) 1.0 (0.7) 3 0.5 (0.5) 1.0 (0.6) 1.5 (0.7) 1.0 (0.8) 1.0 (0.7) 1.2 (0.8) 4 0.6 (0.5) 1.3 (0.8) 1.6 (0.8) 1.2 (0.9) 1.2 (0.7) 1.4 (0.8) 5 0.5 (0.3) 1.3 (0.7) 1.8 (0.8) 1.3 (1.0) 1.0 (0.6) 1.4 (0.9) 

Skin loading, μg/cm2 (without sticky hand conditio verage (S n), a D) 

1 0.3 (0.6) 0.4 (0.3) 0.4 (0.6) 0.3 (0.2) 0. .6) 5 (0 2 0.4 (0.4) 0.9 (0.6) 0.7 (0.7) 0.6 (0.4) 0. .7) 8 (0 3 0.5 (0.5) 1.1 (0.6) 0.8 (0.8) 0.8 (0.5) 1.0 (0.7) 4 0.6 (0.5) 1.3 (0.8) 1.0 (0.9) 0.9 (0.5) 1.2 (0.8) 5 0.5 (0.3) 1.3 (0.7) 0.9 (0.9) 0.8 (0.4) 1.1 (0.8) 

a Three s t d three indepe ubjec s provide ndent replicates for each e ment xperi

108
109

Analysis Tracer Surface Type Surface Loading Contact Motion Pressure Duration Skin C

 Transfer efficiency (%) p<0.05 b p<0.05 p<0.01 p<0.1 ------------- ------------- p>0.1  Loading (μg/cm2) p<0.01 p=0.1 p<0.001 p<0.001 ------------- ------------- p<0.05 

Loadin ug/cm2) ----- p p<0. 01 p<0. p>0 >0.1 0

Table 7.4 Statistical analysis results (p-values) from initial surface-to-hand transfer experiments (Riboflavin). 

First contact (ANOVA) Tran ficiency (%) --------- p<0 sfer ef ---- .1 p<0.001 p<0. p>0 .1 0

a 05 .1 p>0 p<0.0 

Loading (ug/cm2) ------------- p>0.1 p<0.05 p<0.05 p>0.1 p>0.1 p<0.05 

First c act, sticky ha d (ANOV ont nd exclude A)  Trans efficiency (% ------ p fer ) ------- >0.1 p<0.001 p>0.1 p>0 >0.1 .1 p p< 0.00 Loadi (ug/cm2) ng ------------- p>0.1 p<0.1 p<0.05 p>0 >0.1 .1 p p>0.1 Repeated contact (Mix Model) ed-Effects

g ( -------- >0.1 0 001 .1 p p<0.0 

Repeated contact, sticky hand excluded (Mixed-Effects Model) Loadin ug/cm2) g ( ------------- p>0.1 p<0.001 p<0.01 p>0 <0.1 .1 p p<0.00

a Bold t indicates the is signifiTable Statistical re refined, follow-up surface-to-han perim 

Analysis Tracer Surface Type Surface Loading Contact Motion Pressure a Duration a Skin C

ext parameter cant.

7.5 analysis sults (p-values) from d transfer ex ents (Rib 

First Contact (ANOVA)  Loading (μg/cm2) p=0.1 p<0.05 p=0.001 p<0.001 ------------- ------------- p>0.1 Repeated Contact (Mixed-Effects Model) 

a Pressure and duration not included in the follow-up experiments. b Bold text indicates the parameter is statistically significant at p<0.05. 
Table 7.6 Evidence of importance of factors tested across surface-to-skin transfer experiments. 

Parameter Initial E rim xpe ents Refine rim d Expe ents

Tracer -- z{

Skin Condition z{ z{

Surface Type {{ z{

Surface L ing oad z{ zz

Contact M on oti zz z{

Contact D tion ura {{ -- 

Contact Pressure {{ -- 

Contact N ber um zz zz

-- no

{{

z{

zz

t tes

 not f d to fica

 mixe lts or marginally significant at p<0.10 

 sign nt at p<0.05 in all tests 

ted 

oun be signi nt 

d resu

ifica

Transfer E y (% Tran ) for Pes es a luo t Tracers

0.

0

1

la car laminate c et 

fficienc sfer ticid

pet 

nd F rescen

Diazinon

01

.1

1

10

00

minate carpet laminate

Chlorpyrifos

arp

Transfer

Wi

 to 

p

Aqu

e

eous Transfer to PUF R sfe

Dis

oller Tran r to

k (2

 C18

0 se

 Pr

c)

ess

cis- ethrin Perm

tran methrin s-Per

Esfenvalerate

Riboflavin

U B vitex O

ure 7.1 riso ans eff nci f flu cent tracers and pesticides from laminate 

 car

Fig

and

Com

urf

pa

ace

n o

 va

f tr

riou

fer 

amp

icie

g m

es o

ia. 

ores

pet s s to s s lin ed

110
Figure 7.2 Hand loading by contact number, from the refined, follow-up experiments using 

Riboflavin (left panels) or Uvitex (right panels) with 2 μg/cm2 (high) (top panels) or 0.2 μg/cm2 

ttom panels) surface loadings. In these particular box-and-whisker plots, means and 

th th

(low) (bo

outliers (below 5 or above 95 percentiles) are represented by dots. 

111
7.2 Measurements of Pesticides on Hands by Wipe and Rinse Methods 

Measurements of pesticide residues on children’s hands have been performed in the MNCPES, 

CTEPP, CPPAES, PET, and DIYC studies. Collection efficiencies may vary among studies for a 

number of reasons. The method of wiping the surfaces of the hand may vary when performed by 

different researchers or by study participants themselves. Hand rinses may be more effective 

than hand wipes. Whether the method is a hand wipe or hand rinse, collection efficiency may 

differ for free pesticide residues versus particle-bound residue. Most of the data presented in this 

section were collected with hand wipes, except for MNCPES, in which rinses were collected. 

Both hand wipes and rinses were collected in CPPAES (with mean hand rinse to hand wipe 

ratios ranging from 4.1 to 7.8 by home). The amount of isopropanol used to collect the hand 

wipes/ rinses varied by study. A major issue associated with interpreting results of these 

measurements is the amount of a pesticide on the surface of skin that is never absorbed into the 

bloodstream. Solvents may extract some of pesticide from top layers of skin, though the extent 

of extraction will be a function of many factors including pesticide properties. 

Methods 

In CTEPP, hand wipe samples were collected from 257 preschool children using cotton sponges 

(SOF-WICK gauze pad; 4” x 4” B 3 ply; Johnson & Johnson) that were pre-cleaned and wetted 

with 2 mL of 75% isopropanol. The adult caregiver wiped the front and back of both hands of 

the child. A total of four wipe samples were collected over a 48-hr period (two per day, one 

before lunch and dinner, before washing hands). Samples were composited (combined) before 

analysis. The MNCPES hand rinses were collected at home from 102 children on day 1 of the 7-

day monitoring period. A technician placed each of the child’s hands into a separate zip-closure 

bag containing 150 mL of isopropanol. Each hand’s sample was analyzed separately. The 

feasibility portion of the PET study collected hand wipes on multiple days from two children 

after a granular application of diazinon to the lawn by the homeowner. The cotton sponges 

(SOF-WICK gauze pad; 4” x 4” B 6 ply; Johnson & Johnson) were presoaked with 20 mL of 

isopropanol. Each child wiped the front and back of each hand. A total of five samples were 

collected from each child and each was analyzed separately. The CPPAES hand wipe samples 

were collected from 10 children on multiple days following a professional crack and crevice 

application of chlorpyrifos. Separate swabs that were wetted with an unreported amount of 

isopropanol were used to wipe the front and back of each hand. A small number of hand rinse 

samples were also collected. The DIYC study collected hand wipes on multiple days from three 

d crevice application of diazinon. Each of two gauze pads, pre-wetted 

Table 7.7 summarizes the detection limits for the studies. The median and 95th percentile 

concentrations are presented in Table 7.8. Individual hand loading measurements are presented 

in Tables 7.9. Relationships among populations and locations are illustrated in Figures 7.3 to 7.9 

and highlighted below. 

children after a crack an

with 10 mL of isopropanol, was used to wipe both hands. The two wipes were extracted and 

analyzed as one sample. In all studies, the surface area of the children’s hands was measured. 

Results 

112
113

chlorpyrifos on children’s hands measured with rinses in MNCPES were higher than the 

dues (Table 7.9). 

ay be more efficient than hand wipes at removing chlorpyrifos from the 

ation is available on which method better reflects the amount of 

 at 

wipe measurements for chlorpyrifos, diazinon, and permethrin (Figures 7.8 and 7.9), 

 hand wipe and floor dust measurements 

(Figure 7.9) than between hand wipe and floor wipe measurements (Figure 7.8). 

• In the large observational field studies (Figure 7.3, Table 7.8), the loadings of 

loadings measured with wipes in the other studies. 

• For all compounds, the hand loadings measured with hand wipes in the large 

observational field studies did not differ substantially (Figure 7.3, Table 7.8). 

• Median chlorpyrifos loadings on children’s hands (Figure 7.4) were much higher in 

CPPAES, where homes had recent crack and crevice applications, than in the large 

observational CTEPP and MNCPES studies. 

• Median diazinon loadings on children’s hands in the small, pilot-scale PET (lawn 

application) and DIYC (crack and crevice application) studies were much higher than in 

the large observational field study CTEPP (Figure 7.4). 

• Comparison of hand rinse and hand wipe samples collected from the same participants in

CPPAES suggests that hand rinses were more effective at removing resi

• Hand rinses m

skin, but no inform

pesticide that is either absorbed (dermal absorption) or potentially transferred to the 

mouth (indirect ingestion). 

• In the CTEPP study, the median chlorpyrifos hand loadings were higher in NC than OH 

(at both homes and daycares), suggesting greater chlorpyrifos usage in NC than in OH. 

Permethrin levels were only slightly higher in NC than in OH (Figure 7.4). 

• At residential levels observed in CTEPP, median hand wipe-to-surface loading ratios 

reach or exceed 1 for the pesticides of interest (Figure 7.5). Please note that floor wipe 

loadings were measured using an IPA wipe method that was not as efficient as typical 

wipe methods (Section 4.4). 

• A strong relationship is evident in Figure 7.6 between CTEPP hand loadings measured

homes and those measured at daycares for chlorpyrifos (R2=0.47), diazinon (R2=0.44), 

and permethrin (R2=0.41). The relationship is weak for the degradation product TCPy 

(R2=0.03). 

• There was a strong relationship between children’s hand wipe loadings and adult hand 

wipe loadings for chlorpyrifos (R2=0.64; β=0.77), diazinon (R2=0.77; β=0.81), and 

permethrin (R2=0.49; β=0.65) measured in CTEPP (Figure 7.7), despite largely different 

activity patterns between children and adults. 

• Based on regressions of CTEPP hand wipe measurements on either floor dust or floor 

better relationships were observed between
Table 7.7 Limits of detection (ng/cm2) for dermal measurements by compound and study. 

Study Sample type Chlorpyrifos Diazinon c-Permethrin t-Permethrin 

--

 a NHEXAS-AZ Hand wipe 0.004 0.016 -- 

MNCPES Hand rinse 0.06 0.08 -- -- CTEPP Hand wipe 0.003 0.003 0.003 0.003 CPPAES NA b Hand wipe -- -- -- CPPAES NA b Hand rinse -- -- -- DIYC Hand wipe -- 0.02 -- -- PET Hand wipe -- 0.01 -- -- 

a Blank cells indicat asub Detection limit infTable 7.8 Media es e h 2) the large observ

rpy Di c- eth CP

e that the pestic

ormation unava

n and 95th pe

ational field s

Chlo

ide was not me

ilable. 

rcentile valu

tudies. 

rifos 

red in the stu

of pesticid

azinon 

dy. 

and loadin

Permethrin 

gs (ng/cm

t-Perm

measured 

rin C

by han

yfluthrin

d rinse (H

T

R) or 

Y

Study Type P50 P95 P50 P P95 50 P95 P50 P95 P50 P95 P50 P

--

 a NHEXAS-AZ HW 0.01 0.1 0.015 0.1 -- -- -- -- -- -- 

MNCPES HR 0.07 0.3 0.07 0.1 -- -- -- -- -- -- -- CTEPP-NC h b HW 0.02 0.3 0.003 0.1 0.1 1.5 0.1 1.3 0.03 0.4 0.02 CTEPP-NC d HW 0.02 0.1 0.01 0 0.1 .1 0.3 0.04 0.3 0.03 0.3 0.01 0CTEPP-OH h HW 0.01 0.2 0.003 0.1 0.03 0.8 0.03 0.8 0.03 0.1 0.01 0CTEPP-OH d HW 0.01 0.1 0.003 0.04 0.04 0.6 0.03 0.8 -- -- 0.01 0a Blank cells indicat ide asu dyb CTEPP: h = home

e that the pestic

, d = daycare 

 was not me red in the stu . 

114
115

measured with hand ri

e-Appl a D Da Day 7 D

Table 7.9 Comparison of chlorpyrifos and diazinon loadings (ng/cm2) on children’s hands wipe (HW) methods. 

Pr Day 1 ay 3 y 5 Day 9

Study Participant HR HW HW HR HR HW HR HW HR HW HR 

HR HW 

Child 1 (4 b yr) -- -- -- -- -- -- 0.7 -- -- -- 

-- -- -- 

Child 2 (4 3 -- yr) 0.5 5.2 -- 18 1.6 -- 3.8 -- -- 2.3 -- 2.3 Child 3 (4 -- yr) -- 11 -- 2.3 -- -- 3.8 -- 2 -- 2.6 

-- .6 

Child 4 (2 7 -- 0.79 -- -- 0.81 1.3 -- yr) 0.5 -- 0.34 -- -- -- Child 5 (4 9 -- 0.3 -- yr) 0.0 -- 1.4 -- 0.28 -- 0.37 1 -- -- 

.3 

Child 6 (3 yr) -- 0.57 0.36 -- -- 0.67 -- 0.35 -- 0.68 2.3 -- -- Child 7 (3 yr) 2.3 -- -- 0.17 -- 0.25 -- 0.22 -- 0.51 -- -- -- Child 8 (3 yr) 0.21 -- -- 0.1 -- 0.01 -- 0.02 -- 0.02 0.26 -- -- Child 9 (4 yr) -- 0.07 -- 0.08 -- -- -- 0.09 -- -- 0.74 -- -- 

CPPAES (chlorpyrifos) 

Child 10 (4 yr) -- 0.43 -- 0.43 -- 0.68 -- 0.5 -- 0.36 1.8 -- -- 

Child 1 (6 yr) -- 0.01 -- 0.6 c PET -- 0.9 -- -- -- 0.2 -- 

(diazinon) Child 2 (10 yr) -- 0.7 -- 0.7 c -- 0.6 -- -- -- 0.1 -- 

Child 1 (2 y 06 d -- -- -- -- 0.19 0. r) -- 0. -- -- -- 

0.14 d e 0.08 e f 0.13 g 21f g -- 0. h h 20 

Ch 3 yr -- -- ild 2 ( ) -- -- - 0.03 -- MDL - < -- 

f -- -- -- -- 

DIYC (diazinon) 

Chi 1 y -- -- - 0.10 0.10 ld 3 ( r) -- -- - b -- 0.11 -- 3 0.1 -- -- -- 

a Pre-Appl, Pre-application; b (--) indicate no m Day 0 Collected from only the ri and e ch Day 

ollec th on re b st a e oth e be supp bedt g Da Day <MD s th 

Blank cells easurement; c ; d ght h of th ild; e 

samples were c ted on at day: e befo reakfa nd th er on fore er or ime; y 6; h 8; f L, les a
Figure

hand w

 7.3 Log probability plots of hand loadings (M PES are 

ipes)

NC data hand rinses, all others are 

. 

116
b

Figure 7.4 Comparison of hand loadings across studies. MNCPES data are hand rinses, 

CPPAES includes both hand rinses (HR) and hand wipes (HW), all others are hand wipes.

117
Figure 7.5 Ratios of hand wipe loading to floor wipe loading (left panel) and hand wipe loading 

to dust loading (right panel) for pesticides in CTEPP. 

118
Figure 7.6 Relationship between children’s hand loadings measured at CTEPP homes and 

daycares. Coefficients of determination (R2) and slopes (β) for log (base 10) values: chlorpyrifos 

(R2=0.47; β=0.91), diazinon (R2=0.44; β=0.81), permethrin (R2=0.41; β=0.72), cyfluthrin 

(R2=0.02; β=0.19), TCPy (R2=0.03; β=0.54), and IMP (R2=0.31; β=0.54). 

119
120

Figure 7.7 Relationship between hand loadings among children and adults in CTEPP. 

Coefficients of determination (R2) and slopes (β) for log (base 10) values: chlorpyrifos (R2=0.64; 

β=0.77), diazinon (R2=0.77; β=0.81), permethrin (R2=0.49; β=0.65), cyfluthrin (R2=0.20; 

β=0.61), TCPy (R2=0.30; β=0.47), and IMP (R2=0.28; β=0.63). 
Figure 7.8 Relationship between hand wipe measurements and floor wipe measurements in 

CTEPP. Coefficients of determination (R2) and slopes (β) for log (base 10) handwipe loadings 

regressed on log (base 10) floor wipe loadings are as follows: chlorpyrifos (R2=0.38; β=0.64), 

diazinon (R2=0.46; β=0.64), cis-permethrin (R2=0.54; β=0.78), and trans-permethrin (R2=0.60; 

β=0.82).

121
Figure 7.9 Relationship between hand wipe measurements and floor dust measurements in 

CTEPP. Coefficients of determination (R2) and slopes (β) for log (base 10) handwipe loadings 

regressed on log (base 10) floor dust loadings are as follows: chlorpyrifos (R2=0.71; β=0.78), 

diazinon (R2=0.69; β=0.61), cis-permethrin (R2=0.72; β=0.86), and trans-permethrin (R2=0.76; 

β=0.88).

122
7.3 Measurements with Cotton Garments 

The US EPA Office of Pesticide Programs uses a transfer coefficient approach to assess 

children’s residential exposures to pesticides. The transfer coefficient approach was developed 

to assess occupational exposure in an agricultural setting, using empirically-derived dermal 

transfer coefficients to aggregate the mass transfer associated with a series of contacts with a 

contaminated medium. Dermal exposure sampling using a surrogate-skin technique such as a 

patch sampler or a whole-body garment sampler is conducted simultaneously with surface 

sampling for a specific activity, and a dermal transfer coefficient is then calculated. This 

transfer coefficient can then be used to estimate exposure for a similar activity by collecting only 

surface samples (Fenske, 1993), assuming that transfer is unidirectional (from surface to skin) 

and linear with time. Only limited research has been conducted to develop transfer coefficients 

for children in residential and daycare settings. Data were collected in the Daycare study (Cohen 

Hubal et al., 2006), JAX, and CPPAES with cotton garments. The data are presented in Tables 

7.10 to 7.12 and Figures 7.10 to 7.12. 

• Comparison of mean chlorpyrifos loadings on socks in JAX and CPPAES (Table 7.10) 

with surface loadings (Table 4.4) suggests that higher surface loadings do not necessarily 

correspond to higher sock loadings across studies. It also suggests that perhaps activity 

levels influence transfer. 

• The median chlorpyrifos loading on socks after a three-hour period in CPPAES was only 

about twice as high as the median loading after a one-hour period in the same 

environment (Table 7.10). This suggests that transfer to socks may not be linear with 

time, and again points towards the importance of activity levels. 

• Bodysuit esfenvalerate loadings in the Daycare study were typically higher in the 

mornings, corresponding to higher group activity levels at that time (Figure 7.10). 

Depletion of surface loadings by morning activities is unlikely but was not tested. 

• Multiple regression analysis of Daycare data suggests that body section (arms, legs, lower 

torso, and upper torso), relative activity level, and age group are all important predictors 

of bodysuit loadings (Table 7.11). 

• The statistical significance of activity (Table 7.11), even when controlling for age group, 

. 

-person variability (compared to between-person variability) in cotton 

garment loadings (Table 7.12) suggests that factors related to changing environmental 

conditions and to differences in structured activities may be more important than childspecific characteristics. 

• The relative standard deviations (%) of esfenvalerate loadings on cotton garment sections 

(Figure 7.11) were typically higher among infants during the morning sessions and 

among preschoolers during the afternoon sessions. This suggests that the structured 

suggests that activity level within age groups may be as important as age-related 

differences. 

• The between- and within-person variability (GSD) in dermal exposures in the daycare 

setting (Table 7.12) is similar to what has been reported in agricultural/industrial settings

• High within

123
activities may have had a stronger influence on the observed variability than surface 

loadings in the respective rooms. 

e 

 not 

• Infants had 1.5 times as many hand wipe values (36%) above the MDL as preschool 

children (24%), consistent with the higher bodysuit loadings, perhaps reflecting greater 

contact with the floor surface. Figure 7.12 illustrates that among the hand wipes above

the MDL, infants typically had higher loadings, with greater variability. 

• The association between hand wipe samples above the limit of detection and averag

body suit loadings was statistically significant (Spearman rho = 0.54, p < 0.05, data

presented). 

124
Table 7

95 

.10 Pesticide loading (ng/cm2) on cotton garments worn by children in three studies. 

Study Compound 

Garment 

Type/Section Age N % Det MDL Mean SD P50 P

Arms 9-13 mo 26 92 0.01 0.12 0.18 0.06 0.42 

24-38 mo 28 100 0.01 0.1 0.09 0.07 0.23 

Legs 9-13 mo 26 100 0.01 0.27 0.21 0.22 0.75 

24-38 mo 28 93 0.01 0.2 0.41 0.1 0.46 

Lower Torso 9-13 mo 26 100 0.01 0.28 0.23 0.18 0.73 

24-38 mo 28 100 0.01 0.2 0.18 0.12 0.52 

9-13 mo 26 96 0.01 0.05 0.05 0.03 0.12 

Daycare

Upper Torso

24-38 mo 28 100 0.01 0.09 0.13 0.05 0.16 

 Esfenvalerate 

Bottom 2-5 yr 7 100 0.01 0.58 0.37 0.7 1.0 

Knee 2-5 yr 14 100 0.01 0.62 0.4 0.7 1.2 

Leg 2-5 yr 14 100 0.01 0.38 0.27 0.45 0.8 

Sock (1 hr) 2-5 yr 14 100 0.01 8.6 14 3.5 53 

CPPAES Chlorpyrifos 

Sock (3 hr) 2-5 yr 14 100 0.01 10.8 13 7.6 30 

Chlorpyrifos Sock 4-6 yr 9 100 0.4 2.3 1.3 2.2 5.1 

Diazinon Sock 4-6 yr 9 33 0.08 NC NC <0.08 1.8 

Esfenvalerate Sock 4-6 yr 9 22 0.28 NC NC <0.28 2.6 

Cyfluthrin Sock 4-6 yr 9 0 0.24 NC NC <0.24 <0.24 

cis-Permethrin Sock 4-6 yr 9 44 0.8 NC NC <0.8 128 

JAX 

trans-Permethrin Sock 4-6 yr 9 100 0.2 23.6 59 1.44 180 

Union Suit 6-10 mo 10 100 0.001 0.026 0.025 0.019 0.095 

21-27 mo 10 100 0.001 0.016 0.008 0.015 0.025 

6-10 mo 9 89 0.05 0.18 0.10 0.17 0.37 

Chlorpyrifos 

Sock 

21-27 mo 10 90 0.05 0.28 0.18 0.24 0.64 

Union Suit 6-10 mo 10 100 0.001 0.017 0.012 0.014 0.043 

21-27 mo 10 100 0.001 0.052 0.13 0.009 0.42 

6-10 mo 9 78 0.02 0.099 0.094 0.070 0.29 

Diazinon 

Sock 

21-27 mo 10 90 0.02 0.50 1.1 0.13 3.5 

Union Suit 6-10 mo 10 10 0.02 NC NC <0.02 0.038 

21-27 mo 10 10 0.01 NC NC <0.01 0.047 

6-10 mo 9 11 0.25 NC NC <0.25 1.9 

Esfenvalerate 

Sock 

21-27 mo 10 10 0.25 NC NC <0.25 2.3 

Union Suit 6-10 mo 10 10 0.07 NC NC <0.07 1.1 

21-27 mo 10 0 0.04 NC NC <0.04 <0.04 

6-10 mo 9 0 2.5 NC NC <2.5 <2.5 

Cyfluthrin 

Sock 

21-27 mo 10 10 2.5 NC NC <2.5 14 

Union Suit 6-10 mo 10 100 0.001 0.19 0.11 0.18 0.41 

21-27 mo 10 100 0.001 0.96 2.4 0.16 7.9 

6-10 mo 9 100 0.02 2.0 2.8 1.1 8.7 

cis-Permethrin 

Sock 

21-27 mo 10 100 0.02 6.2 13 1.8 43 

Union Suit 6-10 mo 10 100 0.001 0.18 0.35 0.088 1.2 

21-27 mo 10 100 0.001 0.96 2.6 0.059 8.4 

6-10 mo 9 100 0.02 2.6 2.4 1.9 7.7 

CHAMACOS 

trans-Permethrin 

Sock 

21-27 mo 10 100 0.02 10 22 2.0 71 

NC, Not calculated 

125
Table 7.11 Results of multiple linear regression modeling of measured bodysuit pesticide loading 

ng/cm2/sec) from data collected in the daycare study. 

ffect L Es u

(

E evel timate p-Val e 

Intercept intercept -1.43 <0.0001

arms 0.46 

legs 1.05 

lower torso 1.35 

Bodysuit Section 

upper t

001

orso 0 

<0.0

first 0.87 

second 0.31 

Visit 

ird 

06

th 0 

0.00

Session am 0.44 

pm 

06

0 

0.00

high 1.36 

middle 0.65 

Activity Level 

w 

001

lo 0 

<0.0

Classroom infant 0.38 

h

86

presc ool 0 

0.03

Table 7.12 Estimates of between- and within-person variabilit o o v

bodysuit sections. 

A pe w

y for l ading n indi idual 

Statistic rms Up r Legs Lo er 

Between-person variance (logged) 0.26 0.04 0.67 0.37 

Within-person variance (logged) 0.76 0.76 1.02 0.59 

Intraclass Correlation Coefficient 0.25 0.05 0.40 0.39

GSD, between 1.7 1.2 2.3 1.8

GSD, within 2.4 2.4 2.7 2.2

126
Figure 7.10 Bodysuit section loadings ( 2) ng/cm by toring d from Daycare study. moni perio the 

127
0

30

60

90

120

150

Legs

Lower TorsoUpper Torso

Arms

Legs

Lower TorsoUpper Torso

Arms

Legs

Lower TorsoUpper Torso

Arms

Legs

Lower TorsoUpper Torso

Arms

Legs

Lower TorsoUpper Torso

Arms

Legs

Lower TorsoUpper Torso

Arms

am pm am pm am pm

Visit No. 1 Visit No. 2 Visit No. 3

Relative Standard Deviation (%)

Infants

Preschoolers

Figure 7.11 Relative standard deviations of esfenvalerate loadings on cotton garment sections 

among infants and preschoolers in the Daycare study. 

0.00

0.02

0.04

0.06

0.08

0.10

0.12

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Rank (Highest=1)

Handwipe (ng/cm2)

Infants

Preschoolers

Figure 7.12 Handwipe loadings (ng/cm2) above method detection limit among infants and 

preschoolers in the Daycare study. Values are sorted in descending order, illustrating that the 

highest loadings were typically from infants and the lowest typically from preschoolers. 

128
8.0 URINARY BIOMARKER MEASUREMENTS 

Biological markers are indicators of the actual body burden of a chemical. As such, they reflect 

all routes of exposure, as well as inter-individual differences in absorption and metabolism. 

Moreover, they are often more directly related to potential adverse health effects than the 

external concentrations (Lowry, 1986: Hulka and Margolin, 1992). In human observational 

measurement studies involving young children, urine is the primary vehicle for biomonitoring. 

Urine is advantageous over blood because of its noninvasiveness, ease of collection, and large 

available quantity. Urinary biomarkers, however, also have disadvantages related to 

uncertainties in the fraction of the absorbed compound that is eliminated and in the precision of 

the measurements. 

The relationship between a biological marker and external exposure is influenced by factors 

related both to the environment and to human physiology. Factors related to the environment 

include spatial and temporal variability in exposure concentrations (as discussed in earlier 

chapters of this report) and effects of the presence of other chemicals (Coble et al, 2005). 

Factors related to human physiology include differences, both over time and across individuals, 

in the rates of absorption, distribution, metabolism, and excretion (Droz, 1989). When biological 

monitoring and exposure monitoring are used together, the relationship between the two may be 

evaluated to investigate the relative contribution of the various exposure routes. 

 Issues related to route-specific 

xposure estimates have been discussed earlier. Dependable information on the toxicokinetics 

absorption, distribution, metabolism, and excretion) of a compound are necessary for reliable 

stimates of aggregate intake, whether those estimates are derived from the sum of route-specific 

absorption estimates or from excreted biomarker levels. To accurately estimate aggregate intake 

from excreted biomarker levels, urinary biomarker output rates must be calculated from the 

biomarker levels. Such calculations require information on the entire urine volume and elapsed 

time since previous void - information that has rarely been collected in field studies. 

8.1 Toxicokinetics of Organophosphate and Pyrethroid Pesticides 

Some understanding of organophosphate and pyrethroid pesticide toxicokinetics is necessary to 

meaningfully compare the environmental and dietary concentrations presented in the previous 

chapters with the urinary biomarker concentrations presented in this chapter. Despite extensive 

usage, remarkably little is available from the scientific literature on kinetic parameters in 

humans. Parameters reported for absorption of parent compounds and elimination of urinary 

metabolites following pesticide exposure are summarized in Table 8.1. 

Absorption 

Inhalation studies with a variety of gases have shown that even the most efficiently absorbed low 

molecular weight, highly water soluble compounds rarely exceed 70% uptake. No studies 

d, but 

Evaluating the relative contribution of exposure routes to aggregate intake is subject to error 

related to estimates of exposure and of aggregate intake.

e

(

e

reporting the fraction of organophosphate pesticides absorbed through inhalation were foun

129
Leng et al. (1997) reported that only about 16% of the pyrethroid cyfluthrin was absorbed 

rough inhalation. 

gested 

 As for 

gues (1983; 1988) estimated 45-49% and 72-78% for the cis and trans

omers, respectively. 

ated, 

2-20 

 that is 

bsorbed increases as the applied dose (per cm2) decreases. Large differences have been 

lied 

n required. 

or small children (ages 1-6) the following route-specific absorption is often assumed: 50-100% 

aily intake of 100 mg of 

ouse dust is assumed for indirect ingestion. These absorption assumptions are a source of 

loodstream, organophosphate or pyrethroid pesticides are rapidly distributed and 

etabolized. A typical organophosphate (OP) pesticide is composed of a dialkyl (either 

al.,

metabolites and diethyl OPs (including chlorpyrifos and diazinon) produce diethyl metabolites 

th

The importance of the dietary contribution to aggregate exposure among infants and young 

children is well known (NRC, 1993), but few studies have investigated what fraction of in

pesticide residue is absorbed. For organophosphates, Nolan et al. (1984) estimated 70% 

absorption of chlorpyrifos based on urinary 3,5,6-trichloro-2-pyridinol (TCPy), whereas others 

estimated 60% to 93% absorption based on dialkylphosphate (DAP) metabolites (Garfitt et al., 

2002; Griffin et al., 1999). Diet reportedly affects absorption (Timchalk et al., 2002).

pyrethroids, Woollen et al. (1992) estimated that 27-57% of cypermethrin was absorbed, while 

Eadsforth and collea

is

Dermal absorption is typically low due to loss by washing, evaporation, or exfoliation (Feldmann 

and Maibach, 1974). For organophosphate pesticides, absorption of chlorpyrifos was estim

based on its primary metabolite TCPy, to be 1.28% of an applied dose of 4 mg/cm2 (over 1

hr) (Nolan et al., 1984), and 1.2% and 4.3% of applied doses of 0.15 and 0.05 mg/cm2 (over 4 

hr), respectively (Meuling et al., 2005). Absorption of both chlorpyrifos and diazinon was 

estimated to be about 1% of applied doses of about 0.4 and 1.3 mg/cm2 (over 8 hr), respectively, 

based on DAP metabolites (Griffin et al., 1999; Garfitt et al., 2002). The percent

a

reported by anatomical area (Maibach et al., 1971) and among individuals (Feldmann and 

Maibach, 1974). For pyrethroids, Bartelt and Hubbell (1987) found only about 2% of app

permethrin to be absorbed within 24 h. Wester et al. (1994) observed that approximately 2% 

(forearm) and 7.5% (scalp) of radiolabeled pyrethrin was absorbed. The ATSDR (2001) has 

concluded that for pyrethroids in general, < 2% of the applied dermal dose is absorbed, at a rate 

much slower than that by the oral or inhaled routes. 

Due to the paucity of available information on absorption from human studies, simple default 

values based on human studies, animal studies, and conservative assumptions are ofte

F

for inhalation, 50% for ingestion, and 1-3% for dermal. In addition, a d

h

substantial uncertainty in route-specific intake estimates. In fact, since dermal absorption 

increases with decreasing dermal loadings (as demonstrated above with organophosphates), 

default assumptions of less than 3% for dermal absorption may underestimate absorption at the 

very low levels measured in field studies 

Distribution and Metabolism 

Once in the b

m

dimethyl or diethyl) phosphate moiety and an organic group. Hydrolytic cleavage of the ester 

bond yields one dialkylphosphate (DAP) metabolite and one organic group moiety (Barr et 

2004). Dimethyl OPs (including malathion, phosmet, and azinphos-methyl) produce dimethyl 

130
131

for diazinon and 3,5,6-trichloro-2-pyridinol (TCPy) for chlorpyrifos, are 

onsidered to be semi-specific. 

% of 

d by Woollen et al. (1992) to undergo further oxidation to 3-(4'-

ydroxyphenoxy) benzoic acid (4OH3PBA). The chrysanthemic acid derivative cis-2,2-

ollow 

inary OP pesticide metabolites have been 

ported (Griffin et al., 1999; Garfitt et al., 2002; Meuling et al., 2005). Peak excretion is 

centrations. In the future, all studies should include 

formation on void volumes and times to allow excreted mass to be calculated. Relevant 

et al. (2001) and are currently incorporated in the SHEDS 

odel. 

(Aprea et al., 2002). The organic group metabolites, including 2-isopropyl-6-methyl-4-

pyrimidinol (IMPy) 

c

Pyrethroids are esters of chrysanthemic acid and benzyl alcohols. Hydrolytic cleavage of the 

ester bond yields a benzoic acid and a chrysanthemic acid derivative. The 3-phenoxybenzoic 

acid (3-PBA) metabolite is common to 10 of the 18 pyrethroids registered in the United States 

including permethrin, cypermethrin, deltamethrin, esfenvalerate (Baker et al., 2004). Other 

benzoic acid metabolites analogous to 3-PBA are more specific and include 4-fluoro-3-

phenoxybenzoic acid (4F3PBA) from cyfluthrin and 2-methyl-3-phenylbenzoic acid (MPA) 

from bifenthrin. These are not necessarily terminal metabolites; for example, as much as 38

3-PBA has been reporte

h

dibromovinyl-2,2-dimethyl-cyclopropane-1-carboxylic acid (DBCA) is specific to deltamethrin 

while the cis- and trans- isomers of 2,2-dichlorovinyl-2,2-dimethyl- cyclopropane-1-carboxylic 

acid (DCCA) are common to permethrin, cypermethrin, and cyfluthrin. 

Excretion 

Both the OPs and the pyrethroids are rapidly eliminated in urine. Elimination appears to f

first-order kinetics, with elimination half-times in humans ranging from 2 to 41 hours for OPs 

and from 6.4 to 16.5 hours for pyrethroids, depending on both the compound and the route of 

exposure (ATSDR, 2001; Garfitt et al., 2002; Meuling et al., 2005). The elimination half-life of 

about 8 hours reported for 3-PBA among workers exposed to cypermethrin (Kuhn et al., 1999) 

suggests that 88% of the metabolite is excreted within the first 24 hours following exposure. 

Route-specific differences in the peak excretion of ur

re

observed to occur 6 to 24 hours later when absorption is by the dermal route compared to when

absorption is by the oral route, largely because of route-specific differences in absorption. Peak 

excretion may occur as late as 48 hours following dermal exposure, as observed among 

volunteers performing scripted “Jazzercise” activities (Krieger et al., 2000). Extended peak 

excretion times suggest that chlorpyrifos may be retained by the skin and may remain 

systemically available for prolonged periods (Meuling et al., 2005) 

While the above toxicokinetic studies evaluate excreted mass or mass rates, our past field studies

have largely evaluated only biomarker con

in

transformations can be found in Rigas 

m
132

able 8.1 Absorptio

S ND 

n and eliminati

 AB

on characteristics for pest

ORPTION OF PARENT COMPOU

icides and urinary biomarkers of pesticide exposure

ELIMINATION OF METAB

COMPOUND ORAL DERMAL INHALATION ORAL DERMAL 

Chlorpyrifos Volunt or

dose exTCPy (93% of inurine a s (GriffiAbsorp d 0.90 (A

N nteer study

an et al., 19

nteer study

h oral (Grif

). 

eer studies: 70% of 

creted in urine as 

Nolan et al., 1984),

 oral dose excreted 

s dialkyl-phosphate

n et al., 1999). 

tion factor estimate

TSDR). 

al 

at 

Volunteer studies: 1.3% of dermal dose excreted in urine as TCPy (Nolan et al., 1984). 

1% of dermal dose excreted as dialkyl-phosphates (Griffin et al., 1999), 1.2 – 4.3% of dermal dose excreted as TCPy (Meuling et al., 2005). 

o Information. Volu

(NolVolu15.5 1999

, 27 h oral 

84). 

, approx 

fin et al.,

Volunteer study, 27 h dermal (Nolan et al.,1984). Volunteer study, approx 30 h dermal (Griffin et al., 1999). Volunteer study, approx h dermal (Meuling et al2005). 

Diazinon Human

approx2002). iofactor o

N an study, 2 

itt et al., 20

oral absorption 

. 60% (Garfitt et al.,

Default oral absorpt

f 0.85 (ATSDR). 

n 

Human dermal absorption rate: 456 ng/cm2/h (Garfitt et al.,2002). 

o Information. Hum

(Garf

h oral 

02). 

Human study, 9 h derma(Garfitt et al., 2002). 

Pyrethroids (as a group) 

Absorpminimu %but firs mundere(ATSD

Rahuinestiab(A

nation app 

ns ranging 

ure route s

tion is incomplete, 

m estimate 40 - 60

t- pass metabolism 

stimate absorption 

R, 2001). 

, 

ay 

<2% of the applied dermal dose is absorbed, rate of absorption much slower than by the oral or inhaled routes; may be stored in skin and then slowly released into the systemic circulation (ATSDR, 2001). 

pidly absorbed in 

mans following 

halation, but no 

mates of fraction 

sorbed are available 

TSDR, 2001). 

Elimihumaexpos

ears to follow first-order kinetics, wi

 from 6.4 to 16.5 hours, depending up

tudied (ATSDR, 2001). 

Permethrin Oral ab .7

sugges

sorption factor of 0 N formation. 

ted (NRC). 

0 Poor dermal absorption: ~2% 

of applied dose absorbed/24 h (Bartelt and Hubbell, 1987); 7.5% (scalp) and 1.9% (forearm) of applied dose (Wester et al., 1994). 

o Information. No In No Information. 

Cyfluthrin No Inf Hu

~1(L

an oral dosi

ced t-1⁄2 of

 et al, 1997b)

ormation. No Information. man data suggest 

5% absorption 

eng et al, 1997). 

Humprodu(Leng

ng 

 6.4 h 

. 

No Information. 

Cypermethrin Human -

57% (mcyperm(Wooll

N an oral dosing, 

ry metabolites h

 1⁄2-life of 16.5 

llen et al., 1992

ave 

h 

). 

Human dermal dosing, excretion rates peaked a12-36 h, mean 1⁄2-life wa13 h (Woollen et al.,1992). 

o Information. Hum 

urinamean(Woo

 volunteer study 27 No Information. 

ean 36%) 

ethrin absorbed 

en et al., 1992). 

T
8.2 Measurements of Pesticide Metabolites in Urine 

Urinary biomarkers were measured in several large-scale and pilot-sc dren’s observational 

measurem dies describe Table These inclu the MNC TE , NHEXASAZ, CPPA X, CHAMA S, PE d DIYC studies. All urine es re collected 

exclus ly a e children’s h es except for the CTEPP study, in which urine samples were 

also collected at daycare centers. Urine collection follow outdoor t ns in the PET 

y routine profe al oor ap tions in the DIYC and CPPAES studies. 

t u e fir rning voids, were collected using -appro ethods 

ud on (CT ET), colle n cup (NH AS-A PES), 

er o air” ES). Tab .3 presents selected organophosphate 

) a pyr t we sured in the children’s e sam ltiple 

ie he pesticide metabolites are 3,5,6-trichloro-2-pyridinol (TCPy), 2-isopropyl-6-methylyri ino nd 3-phenoxybenzoic acid (3-PBA). 

ple co perform y th en’s caregivers following protocols provided by 

invest t mical an s of metaboli in nearly 

ormed by the National Center for Environmental He of the Ce r ontrol 

 Preventio ta, GA g va tandem mass spectroscopy techniques (Baker et 

aker et al., 2004; Beeson et al., 199 ill et al., 1995). Chemical analysis for the 

PP st was performed by Battell using validated gas tography/mass 

trosco hniques. 

its of e m give y study in 8. Detection 

ue es a rovided in Fi e 8.1. edian and 95th rcentiles for 

 u ary m a pr nted by stu e igure 8.2 shows the log probability 

s o rina -P once o hi s large observational field 

ie -an th ly depict the urinary TCPy 

 3- o the p l n’s ob vational 

su

 N nal am udes a ngoing 

ss t of S. p icals through the 

su ent b . Sp easu nts of urinary pesticide biomarkers among children 

 12 ars o the e 2001- 2 cycles are includ f mparison 

 resul . o HANES does not report results by region or by 

on. 

• The c b ected in over 90% of the children’s urine 

sampl u d metabolite 3-PBA was detected in over 60% 

of the CTEPP-OH samples and over 90% of the JAX samples (Figure 8.1). 

• The urinary TCPy concentrations were at least an order of magnitude higher than the 

urinary 3-PBA concentrations across studies (Figure 8.2). 

ale chil

PES, C

 sampl

urf applic

ent

ES

 stu

, JA

t th

d in

CO

om

 8.2.

T, an

plica

EPP, P

 (CPPA

re mea

e childr

 urinary

lidated

de

ed

PP

 we

atio

ive

and

rin

ing

 ins

nd 

s. T

mid

stud

Spo

incl

diap

(OP

stud

4-p

Sam

the 

perf

and

al., 2000; B

CTE

spec

Lim

freq

each

plot

stud

and

mea

The

asse

mea

6 to

with

seas

ssion

mples, mainly 

er-toilet seat b

(DIYC), and “p

ethroid metabolit

ind

st mo

nets 

tty ch

es tha

 sa

 und

ert

age

EX

 urin

priate m

Z, MNC

ples in mu

ctio

le 8

l (IMP), a

ction was

ors. Che

n in Atlan

lle

iga

ed b

alysi

, usin

tes 

alth

all included studies was 

nters fo Disease C

9; H

e Institute 

etabolite are

 Concentrations for the m

udy

py

detection for each pesticid

 chroma

 Table

 tec

re p

n b 4. 

nci pe

rin

f u

s. F

PB

rem

atio

men

rem

 ye

gur

etabolite re 

ry TCPy and 3

re 8.3 presents th

ncentrations for

 studies. 

 Health and Nutr

e exposure of

ese

BA c

e box

 both 

ition Ex

the U.

dy in Tabl

ntrations f r c

d-whisker plots

large-scale and

ination Survey 

opu tion to environm

8.5. F

ldren acros

at graphical

ilot-scale chi

(NHANES) i

ental chem

igu

A c

ent

dre

ncl

ser

n o

 th

 of iomarkers

old from b th 

rom our studies

hlorpyrifos meta

es in all listed st

la

reme

00 and th

te that N

Py was det

e pyrethroi

ot m

 1999-20

 Please n

olite TC

dies. Th

200 ed or co

ts f

133
• There is virtually no difference in urinary TCPy concentrations measured in CTEPP NC 

and OH, but the concentrations from Minnesota and Arizona are substantially higher 

e 

at 

• Levels of IMP were about an order of magnitude higher in DIYC compared to PET or 

tions five orders of magnitude higher than those from “low” 

applications. Figure 8.4 shows that the urinary TCPy concentrations over time were not 

t 

n-time profiles for urinary TCPy levels in CPPAES did not mirror the 

environmental concentration time profiles (Figure 8.5). 

(Figure 8.2, all unweighted). Higher levels in MNCPES and NHEXAS-AZ may reflect 

intentional oversampling of pesticide-using households in MNCPES, and greater use of 

chlorpyrifos at the time that MNCPES and NHEXAS-AZ were conducted. 

• Compared to values for children under 12 years old collected in the 1999-2002 NHANES 

(Figure 8.2), the median TCPy values were higher in all of our studies, but the 95th

percentile values were only higher for MNCPES. 

• The children in JAX had levels of 3-PBA that were at least seven times higher than thos

of children in CTEPP-OH (Figure 8.3). All urine data from JAX participants suggest th

JAX is a high pesticide usage area. 

• The median 3-PBA value in CTEPP (0.3 ng/mL) was similar to NHANES (0.3 ng/mL), 

but the median JAX value (2.2 ng/mL) was much higher (Figure 8.3). 

NHANES (Figure 8.3). 

• The median urinary TCPy concentration was the highest for the NHEXAS-AZ and JAX 

studies and the lowest for the CTEPP-NC and CTEPP-OH studies (Table 8.5). 

• In the CPPAES study, the intensity of the crack and crevice applications of chlorpyrifos

was described as either high (n = 7) or low (n = 3), with mean air concentrations resulting 

from “high” applica

much different for the children in the high versus low application groups. 

• For children in the “high” application group in CPPAES, the median urinary TCPy 

concentration one day before application of chlorpyrifos was higher than on the first two 

days following application (Figure 8.4). Crack and crevice applications of chlorpyrifos a

these homes did not substantially increase the children’s urinary TCPy concentrations. 

• The concentratio

134
Table 8.2 Summary of the arker collection methods. 

Study N 

Age 

Range Sampli

Co n 

children’s urinary biom

ng Device 

Collecti

Strateg

on 

y 

llectio

After Pestic

Use 

ide 

Collection Frequency Analyte

NHEXAS-AZ (subset) 

21 5 to12 yr Urine c

cup 

ollection Morning voi Onc

mon

e (in 3-da

itoring p

y 

eriod) 

d No TCPy 

MNCPES 102 3 to 13 yr Urine c

cup 

ollection Morning voi Day

sam

s 3, 5, an

pling per

d 7 of 

iod 

d No TCPy 

CTEPP 257 2 to 5 yr Bonnet

childrencollectiadults 

 for 

, urine 

on cup for 

Morning voiafter lunch, dinner/ befobedtime 

d, 

after 

re 

Only for sohomes (~15

me 

%) 

Ove TCPy, 3

(Ohio, o

-PB

nly

r a 48-hr period 

TCPy, I3-PBA 

JAX 9 4 to 6 yr Plastic cup Morning void Yes, indoor 1 day MPCHAMACOS 20 6 to 24 mo Cotton 

Infant ucollecticommocontain

diaper a e 

rine 

on bag o

de 

er 

nd 

r 

One overnigand one sposample 

ht 

t 

No Dialkyl 

Phosphametabol

Onc

te 

ites 

CPPAES 10 2 to 4 yr Toys R

child’s plastic cup 

and 5, 

 an

icat

’ Us 

potty, 

Pre7, 9,appl

 days

d 11 

ion 

 1, 2, 3,

postMorning void Yes, indoor TCPy 

PET Pilot 6 5 to 12 yr Urine co

bottle or urbonnet 

and

8 p

llection 

ine 

r Preand days ost-ap 1, 2, 4, plication Morning void Yes, outdoo IMP 

DIYC 3 1 to 3 yr Diaper inse

collection c

s 3, 

icat

rt or 

ups 

Morning voiother spot samples 

d and Yes, indoor Day

appl

5, an

ion 

d 7 post- IMP 

a Analytes relevant to interstudy comparison. Most studies included additional metabolites. 

135
Table 8.3 Urinary metabolites of organophosphate and pyrethroid pesticides measured in the 

children’s observational measurement studies. 

Meta e P t bolit aren Com pound

3,5,6- o- ridino P rpyrifos a Trichlor 2-py l (TC y) Chlo

2-Isopropyl-6-m l-4-py idinol P) ethy rim (IM Diazinon 

3-Phenoxyb c acid (3-PBA) Permethrin b enzoi a TCPy is al metabolite of chl s-me ich m ur in children’s diet. 

b Several oth yrethroids are me n PBA i ypermethrin, deltamethrin, fenvalerate, 

fluvalinate, permethrin, su rin

Table 8.4 Limits of detection (ng/mL) for each pesticide me olite m re the children’s 

urine sam ud

Study TCPy IMP 

so a 

er p

orpyrifo

tabolized i

. 

thyl, wh

to 3-

ay occ

ncluding c

mith

tab

3-PBA 

easu d in

ples by st y. 

NHEXAS-AZ 1.0 NA NA 

MNCPES 1.4 NA NA 

CTEPP-NC 1.0 NA NA 

CTEPP-OH 1.0 NA 0.2 

JAX 0.4 2.0 0.5 

CPPAES 1.0 NA NA 

PET NA 0.3 NA 

DIYC NA 1.0 NA 

NA,

Tab

and

 Not 

le 8.5 and per values (n r the p id b C , IMP, 

 3-PBA ured e ’s e sa

Applicable.

Me

 m

dian

eas

 95th

in th

centile

 children

TCPy 

g/mL) fo

mples by stud

IMP 

estic

y. 

e meta olites T

3-PBA

Py

 urin

Stu

P50 P95 P50 P95 P50 P95 dy 

NHEXAS-AZ 12.0 26.0 NA NA NA NA

MNCPES 7.2 23.0 NA NA NA NA

CTEPP-NC 5.3 15.5 NA NA NA NA

CTEPP-OH 5.1 12.3 NA NA 0.3 1.8 

JAX 9.8 21.2 <MDL <MDL 2.2 98.7 

CPPAES 7.7 18.0 NA NA NA NA 

PET NA NA 6.58 0.71 NA NA 

DIYC A N NA 1 NA 7. 27.0 NA 

NA, Not Applicable. 

136
Detection Frequency in Urine

Figure 8.1 Detection frequencies of pesticide metabolites in the children’s urines samples by 

study. 

90

100

)

80

TCPy IMP 3-PBA

0

10

20

30

40

50

60

70

NHEXAS-AZ MNCPES CTEPP-OH CTEPP-NC

JAX CPPAES PET DIYC

Detecti uency (% on Freq

137
138

Figure 8.2 Log probability plots of urinary TCPy, 3-PBA, and IMP concentrations across large 

observational field studies. NHANES results are included for comparison. 
Figure 8.3 Box-and-whisker plots comparing the urinary TCPy and 3-PBA concentrations acros

studies. 

s 

139
Figure 8.4 Urinary TCPy concentrations (ng/mL) over time for the children in the high and low 

application groups in CPPAES. 

CPPAES - Chlorpyrifos in Air

-1 1 3 5 7 9 11 0

50

100

150

200

250

300

Air

Day

Concentration (ng/m3)

CPPAES - Chlorpyrifos on Surfaces

-1 1 3 5 7 9 11 0

1

2

3

4

5

6

7

8

LWW

Day

Loading (ng/cm2)

CPPAES - TCPy in Urine

-1 1 3 5 7 9 11 0

3

6

9

12

15

TCPy

Day

Concentration (ng/mL)

5 Time profiles for chlorpyrifos in environmental media and TCPy concentrations in 

urine for all children in the CPPAES. 

Figure 8.

140
8.3 Temporal Variability in Biomarker Measurements 

In the CTEPP study, the children’s spot urine samples (up to six per child) were analyzed 

separately for pesticide metabolites if the participants reported that a pesticide had been used in 

their homes within seven days of field monitoring. Figure 8.6 shows the variability of urinary 

TCPy concentrations in the children’s urine samples over a 48-h period. 

Intraclass correlation coefficients (ICCs) for urinary TCPy and 3-PBA concentrations in NC and 

OH children in the CTEPP study are provided in Table 8.6. The between and within-person 

geometric standard deviations (GSDs) for logged urinary concentrations of TCPy and 3-PBA for 

the NC and OH children in the CTEPP study are given in Table 8.7. Concentration-time profiles 

for TCPy and 3-PBA among CTEPP children are provided in Figure 8.6 and for IMP among 

PET study children in Figure 8.7. 

• Relatively low ICCs (Table 8.6) indicate that a single measurement may not adequately 

ncy of urinary metabolite concentrations over even short 

periods of time appears to be dependent on both the metabolite and the study population. 

• Within-person GSDs are equal to or nearly equal to between-person GSDs for both TCPy 

and 3-PBA in urine measured in CTEPP (Table 8.7). This indicates that a single spot 

urine measurement is not sufficient to differentiate among children over a 48-hr time 

frame. 

• Spot urine measurements over 48 hours among CTEPP participants reporting recent 

pesticide applications show large sample-to-sample variability and large differences 

among individuals (Figure 8.6). 

• Adjustment of urinary metabolite values by specific gravity did not meaningfully reduce 

within-person variability of TCPy (Figure 8.6). 

• While no statistically significant difference was observed between pre- and postapplication urinary IMP concentrations in the PET study, the time-concentration profile 

clearly shows an observable decay in children’s urinary biomarker concentrations in the

eight days following the outdoor lawn application (Figure 8.7). The pattern among adults 

 (FMV) to other spot samples collected among a 

subsample of CTEPP children (data not presented), the median concentration in FMV is 

substantially (43%) higher than the median of the non-FMV samples for TCPy, and 

slightly (35%) higher for 3-PBA, due to longer urine accumulation time in the bladder. 

• In CHAMACOS, concentrations in overnight diapers were compared to concentrations in 

spot samples (Bradman et al., 2006; data not presented). In all cases, diethyl phosphates 

were lower in overnight diaper samples than in spot samples, while for toddlers dimethyl 

phosphates were higher in overnight diaper samples. Median total DAP concentrations 

for all children were higher in the overnight samples compared to the spot samples (140 

vs. 100 nmol/l), but the differences were not statistically significant (Wilcoxon test). 

represent the mean of the 48-hr sampling period for 3-PBA among adults and TCPy 

among children. Consiste

is not consistent with that among children. 

• Comparing first morning voids

141
• Spearman correlations were calculated for CHAMACOS spot and overnight samples by 

age (Bradman et al., 2006). Spot and overnight urine concentrations were significantly 

correlated in CHAMACOS (Bradman et al., 2006): dimethyl phosphate (Spearman 

rho=0.53; p=0.02), diethyl phosphate (Spearman rho=0.48; p=0.03), and total DAP 

metabolites (Spearman rho=0.57; p=0.009). 

Table 8.6 Intraclass correlation coefficients (ICC) for logged CTEPP urinary metabolites. a

Metabolite NC Children OH Children 

3-PBA -- b 0.70 

TCPy 0.65 0.48 

a An C

b

 -- = no

Table 8 ry 

concen

IC of 0.80 indicates that a single measurement reliably represents the average of a set of measurements. 

 data. 

.7 Between- and within-person geometric standard deviations (GSDs) for logged urina

trations from children in the CTEPP study. 

Metabolite Measure NC Children OH Children 

Between-person GSD -- a 3-PBA 1.5 

Within-person GSD -- 1.2 

TCPy Between-person GSD 1.5 1.5 

Within-person GSD 1.3 1.5 

a

 -- = o n data. 

142
A B 

C D

Figure 8.6 Concentration versus tim r urinary TCPy me ments among CTEPP-NC 

and CTEPP-OH partic recent p lication. Urines in panels A and B 

thout adjustment. Urines in panels C and re adjusted b ecific gravity. Note that not 

all voids within the 48 collect

Figure 8.7 Time-concentration profile for urinary IMP measurements among child and adult PET 

study participants following an outdoor granular turf pesticide application. 

e plots fo

ipants reporting a

asure

esticide app

are wi D a y sp

 hour period were ed. 

Children's IMP (mean +/- std err) Adults' IMP (mean +/- std err)

-2 0 2 4 6 8

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Day

IMP (ng/ml)

-2

5

4

3

2

1

0

0 2 4

6

Day

IMP (ng/ml)

6 8

143
144

.4 Urine and Creatinine Excretion among Children 

ity, and osmolality (Wessels et al.,

tabolites in spot urine samples may vary, even if 

the in ecting 24-h urine samples from children is often 

im mmonly collected and normalized using creatinine (CRE) 

own to be variable among children (Freeman et 

al. ecause CRE excretion is dependent upon 

E than adults. This makes comparisons 

arker concentrations subject to error due 

Age-dependent differences in daily creatinine 

aring young children and older ones (Krieger et 

al., for 1-year olds (0.08 g 

Alterna dilution are based on urinary specific gravity and 

counts for all dissolved solids, with a specific 

gravity of 1.024 considered normal for adults. Both specific gravity and creatinine were 

measured in CTEPP urine samples. 

Urinary output among young children is often estimated with equations from the Exposure 

Factors Handbook. Zartarian et al (2000) estimated daily urinary output volumes of 500 and 800 

mL for the children 0–4 and 5–9 years of age, respectively, based on Geigy Scientific Tables. 

Estimated daily urinary output and creatinine excretion for children 3-12 years of age based on 

orning void measurements and recorded ancillary information from the MNCPES are 

t urine (t-test, p < 0.001). 

• In the MNCPES study, the daily urine output rates (mean ± SD) increased from 13 ± 6 

8

Urine output varies with water intake, urea, salt, specific grav

2003). Consequently, the concentration of me

ternal dose remains constant. Since coll

practical, spot urine samples are co

concentration. However, CRE yield has been sh

, 1995; O’Rourke et al., 2000). Furthermore, b

muscle mass, children inherently excrete less CR

between CRE-adjusted adult and children urinary biom

to “over-correction” of children’s samples. 

clearance must also be considered when comp

 2001; Wessels et al, 2003), as differences are great even

creatinine/day) relative to 5-year olds (0.4 g creatinine/day). 

tive approaches for adjusting for urine 

on urinary output. Specific gravity adjustment ac

first m

presented in Figure 8.8. 

• In unpooled samples from CTEPP, specific gravity of children’s urine averaged 1.020, 

significantly different than the 1.024 of adul

mL/hr for 3-4 year olds to 19 ± 7 mL/hr for 11-12 year olds (Figure 8.8) based on first 

morning void samples with known volumes and void times. 

• In the MNCPES study, creatinine excretion rates (mean ± SD) increased from 10 ± 4 

mg/hr for 3-4 year olds up to 24 ± 12 mg/hr for 11-12 year olds (Figure 8.8). 

• There was neither a substantial nor consistent difference between sexes for either daily 

urine output or daily creatinine excretion rate, suggesting that sex is not an important 

predictor of creatinine excretion for pre-pubescent children (Figure 8.8). 

• Failure to appropriately account for creatinine excretion results in “over-correction” of 

children’s samples when making comparisons between CRE-adjusted adult and children 

urinary metabolite concentrations, making child levels appear higher by comparison. 

• An alternate approach for avoiding issues with variable urine volumes is to calculate 

biomarker excretion rates. This requires collection of complete voids, void volume 

measurements, and recording previous and final void times. 

144
Creatinine Concentration (mL)

0

50

100

150

200

3-4 5-6 7-8 9-10 11-12

Age (years)

Creatinine Concentration (mL)

Male

Female

Creatinine Excretion Rate (mg/hr)

40

 Excretio

0

10

3-4 5-6 7-8 9-10 11-12

Age (years)

Creatinine 20

30

n Rate (mg/hr)

Male

Female

Estimated 24-hr Creatinine Excretion (mg)

11-12

h io

0

3-4 5-6 7-8 9-10

Age (years)

24-

250

500

r Creatinine Excret

750

1000

n (mg)

Male

Female

Overnight Urine Output (mL)

0

50

100

150

200

250

3-4 5-6 7-8 9-10 11-12

Age (years)

Overnight Urine Output (mL)

Male

Female

Overnight Urine Output Rate (mL/hr)

10

30

Ou 15

20

25

tput Rate (mL/hr)

Male

Female

0

5

3-4 5-6 7-8 9-10 11-12

Age (years)

Urine 

Estimated 24-hr Urine Output (mL)

100

200

400

24-hr Urine Output (mL) 500

600

Male

Female 300

0

3-4 5-6 7-8 9-10 11-12

Age (years)

Figure m 

the MN

8.8 Estimates of age-specific urinary output and creatinine excretion, based on data fro

CPES. 

145
8.5 Relative Importance of Exposure Routes 

The relative importance of the dietary ingestion, indirect ingestion, dermal, and inhalation routes 

of exposure with respect to aggregate intake has been investigated with data from both the 

MNCPES and CTEPP studies. Daily inhalation and dietary intake estimates (ng/kg/day) for 

chlorpyrifos among children in MNCPES are available in Clayton et al. (2003). Estimated 

relative importance of the inhalation, dietary ingestion, and indirect ingestion routes of exposure 

to OPs and pyrethroids among children in CTEPP are presented in Morgan et al. (2004). 

• MNCPES chlorpyrifos data showed that ingestion was a more dominant route of intake 

than inhalation. Urinary metabolite levels, however, showed a stronger association with 

air (r=0.42, p<0.01) than with dietary (r=0.22, p<0.05) measurements. 

• Using MNCPES data as an input, the SHEDS model suggested (data not presented) that 

the dominant pathway for highly exposed chlorpyrifos users was non-dietary ingestion, 

followed by dietary ingestion. The model also suggested that the relative contribution of 

exposure pathways may differ by pesticide. 

• TCPy was found in several environmental media in CTEPP, particularly in solid food 

samples. Estimated intake of TCPy (Figure 8.9) was about 12 times higher than intake of 

chlorpyrifos for CTEPP children. Even when environmental TCPy is considered, nearly 

60% of the TCPy excreted in urine remained unaccounted for. This suggests that either a 

major pathway of children’s exposure to chlorpyrifos and TCPy remains unaccounted for 

in our algorithms or that some underlying assumptions are incorrect. 

• Despite indications that intake of TCPy from solid food may be responsible for the bulk 

of TCPy intake, intake from solid food and excretion are poorly correlated (r2=0.01, 

Figure 8.10). The absorption rate for TCPy remains unknown, as does whether or not it 

is metabolized to other products in the body. 

• Based on exposure algorithms (with absorption assumed to be 50% by each route), the 

primary route of exposure and intake for chlorpyrifos and permethrin among CTEPP 

children was dietary ingestion (Table 8.8 and Figure 8.11). Inhalation was the secondary 

route for chlorpyrifos and diazinon (organophosphates); while indirect ingestion was the 

secondary route for permethrin (pyrethroid). 

• Based on algorithms, the contribution of diet to aggregate intake generally decreases as 

intake increases (Figure 8.12). Conversely, nondietary ingestion becomes increasingly 

important with increasing aggregate intake. 

ay have also been exposed to other pyrethroids that are metabolized 

into 3-PBA and could have contributed to the excreted amounts measured. 

• Our studies consistently report a low correlation between concentrations of urinary 

biomarkers of pesticide exposure and environmental concentrations. Algorithm-based 

estimates of aggregate intake do little to improve the correlation. A better understanding 

of how differences in activities between children affects intake may be needed. 

• Figures 8.14 and 8.15 present environmental and dietary levels of chlorpyrifos and 

• Unlike with TCPy, the estimated aggregate intake of cis- and trans-permethrin among 

CTEPP-OH children was close to the excreted amount of 3-PBA (Figure 8.12). 

However, children m

146
urinary concentrations of TCPy by study. There is little evidence that differences in 

environmental media concentrations translate into differences in urinary concentrations. 

The pattern is most similar between food and urine concentrations (Figure 8.15). 

Table 8.8 Estimated relative importance of the inhalation, dietary ingestion, and indirect 

ingestion routes of exposure among children in CTEPP NC and OH. 

Class Pollutants Apportionment of Aggregated Exposure/Dose 

OP Insecticide Chlorpyrifos and Diazinon NC: dietary ingestion ≈ inhalation > indirect ingestion 

OH: dietary ingestion > inhalation > indirect ingestion 

oid Insecticide cis- and trans-Permethrin NC: dietary ingestion ≈ indirect ingestion > inhalation 

OH: dietary ingestion > indirect ingestion > inhalation 

Pyrethr

Fig ith 

the exc

100

120

60

80

20

40

0

 Intake of Intake of Excreted amount 

chlorpyrifos TCP of TCP in urine

ng/kg/day 

ure 8.9 The median estimated intakes of chlorpyrifos and TCPy in CTEPP-NC compared w

reted median amounts of TCPy in the preschool children’s urine (Morgan et al., 2005). 

147
Figure 8.10 Intake of environmental TCPy through the dietary route correlated poorly (r2

with the amount of TCPy excreted in the urine of CTEPP-NC preschool children. (ng/kg/day) TCPy excreted edEstimat

Dietary intake of TCPy (ng/kg/day) 

=0.01) 

igure 8.11 Estimated distributions of aggregate intake (“AGGR”) of chlorpyrifos and 

permethrin (ng/kg/day) and estimated distributions of the four contributing routes (diet, 

inhalation, indirect ingestion, and dermal) among CTEPP-OH children. 

F

148
149

Dose (cis-Permethrin)

100%

90%

e

80%

o Dost

70%

tion 

60%

buri Cont

50%

ent of Total

40%

30%

rcPe

20%

10%

0%

1

4

7

0

3

6

9

2

25

8

1

4

7

0

3

6

9

2

5

8

1

4

7

0

3

6

9

2

5

1

1

1

1

2

2

3

3

3

4

4

4

4

5

5

5

6

6

6

7

7

7

7

8

8

Lowest to Highest Aggregate Dose

inhal

derm

nondiet

diet

Figure 8.12 The contributions of inhalation, dermal absorption, diet, and nondietary ingestion to 

aggregate intake of cis-permethrin. 

TCPy

Intak e (NC) Excre tion (NC) Intak e (OH) Excre tion (OH)

0.1

1

10

100

1000

ydag/k/ng

3-PBA

Intak e (OH) Excre tion (OH)

0.1

1

10

100

1000

yadg/kng/

Figure 8.13 Children’s estimated aggregate intake of chlorpyrifos and permethrin compared to 

their measured urinary metabolites (CTEPP). 
150

Figure 8.14 Distributions of TCPy in urine across studies (bottom right panel) in comparison to 

distributions of chlorpyrifos in indoor air, outdoor air, dust, and soil across studies. 
Figure 8.15 Distributions of TCPy in urine across studies (bottom right panel) in comparison to 

distributions of chlorpyrifos on surfaces, in solid food, and on hands across studies. 

151
 8.6 Model Predictions 

The Stochastic Human Exposure and Dose Simulation (SHEDS) model (Zartarian et al., 2000) 

provides route-specific estimates of aggregate exposures, relying on input data from assorted 

data sets, including those described in this report. The Safe Foods Project is currently 

developing an exposure-dose-response model to address cumulative risks associated with 

exposures to multiple pyrethroids. The Project intends to use the Exposure Related Dose 

Estimating Model (ERDEM) (Blancato et al., 2004) to predict internal dose based on cumulative 

exposure estimates from SHEDS. The model will be used to identify critical pathways of human 

exposure and dose. A meaningful discussion of SHEDS and ERDEM is beyond the scope of this 

report, but an example of an important application of SHEDS is described below. 

• Use of the SHEDS model with MNCPES data (Figure 8.16) helped reveal the importance 

of accounting for exposures to the metabolite/degradate TCPy in environmental media. 

Without such accounting, the model under-predicted urinary TCPy concentrations. 

• SHEDS found that urinary biomarker concentrations depend mainly on dietary intake. 

An uncertainty analysis (independent of dietary) found other important factors to be: 

applied pesticide mass; surface area of treated rooms; time in treated rooms; air and 

residue decay rates; surface-to-skin transfer efficiency; dermal transfer coefficient; saliva 

removal efficiency; fraction hands mouthed; daily hand wash events; removal efficiency; 

maximum dermal loading; dermal absorption rate; and frequency of hand-mouth activity. 

• By identifying critical pathways of human exposure and dose (and their associated 

uncertainties), models such as SHEDS and ERDEM guide the planning for future 

measurement studies so that newly identified data gaps may be filled with real-world 

measurement data. 

• Applying SHEDS to different pesticide classes will provide information on degree to 

which factors that affect exposure differ across pesticide classes (e.g., pyrethroids vs.

organophosphates). 

100

L)

10

 (ug/noit

1

artnecno0.1

C 0.01

0 10 20 30 40 50 60 70 80 90 100

Percentile

Modeled Observed

Figure 8.16 Comparison of TCPy in urine between SHEDS model and observed MNCPES data 

when TCPy in the environment is not considered (Source: Xue et al., 2004). 

152
9.0 SUMMARY AND CONCLUSIONS 

ORD) 

g of 

s; 

ith children’s 

xposure and aimed to produce sufficient real-world data to eliminate excessive reliance on 

def t

four pr

from ch

In th a

to be fo

typicall

The ap

“cracktypes. 

bas o ace, 

ethnicit

questio

with re More effort is still needed to improve questionnaires and to ensure 

uni m e 

cho n 

studied to capture divergent us

included to docum

In an effort to facilitate risk assessments that take into account unique childhood vulnerabilities 

to environmental toxicants, the National Exposure Research Laboratory (NERL) in the U.S. 

Environmental Protection Agency’s (U.S. EPA) Office of Research and Development (

identified four priority research areas as representing critical data gaps in our understandin

environmental risks to children. These priority research areas are: 1) pesticide use pattern

2) spatial and temporal distributions of residues in residential dwellings; 3) dermal absorption 

and indirect (non-dietary) ingestion; and 4) dietary ingestion. Several targeted studies were 

conducted or financially supported by NERL to specifically address these priority research 

needs. The studies were designed to address the largest uncertainties associated w

e

aul assumptions when assessing exposure. Significant progress has been made in each of the 

iority areas leading to a more comprehensive understanding of the exposures resulting 

ildren’s interactions with their environment. 

e rea of pesticide use patterns, our studies have taught us that pesticide products are likely

und in nearly 9 out of every 10 homes. The most frequently applied of these products 

y contain pyrethrins and pyrethroids (namely, permethrin, cypermethrin, and allethrin). 

plications are more likely to be performed by an occupant than by a professional, with 

and-crevice” type applications favored over either the broadcast or total release aerosol 

The application frequencies appear to be higher in warmer climates, but no differences 

ed n population density (urban vs. rural) or other socio-demographic factors including r

y, home type, income, and level of education are evident. Despite much effort in 

nnaire development, we have had little success in correlating questionnaire responses 

sidue measurements.

for ity in inventory forms in future studies. Target populations for future studies should b

sen from areas that extend outside the limited geographic regions that have previously bee

e patterns, but previously studied populations should also be 

ent trends. 

We have learned a great deal about spatial and temporal distributions of pesticide residues. 

Indoor air concentrations are typically ten-fold higher than outdoor concentrations, but 

surprisingly high outdoor air concentrations have also been measured. In the absence of any 

recent application, concentrations in indoor air are strongly influenced by vapor pressure. 

Immediately following an application, airborne concentrations peak within 24 hours and produce 

a concentration gradient with levels decreasing with distance from the application site. Southern 

states do have higher airborne concentrations than Northern states, but there is considerable 

overlap. Population density (urban vs. rural) and income level differences are evident. With 

surface residues, considerable variability exists not only among rooms but also in different 

locations within a room. Substantial translocation of pesticides from application surfaces to 

adjacent surfaces, and from outdoor surfaces to indoor surfaces has been observed. Cleaning 

activities and ventilation have been found to be important for both air and surface concentrations. 

Much, though not all, of what we have learned about spatial and temporal variability has come 

from organophosphate pesticides, and more studies with pyrethroids are needed. 

153
These studies have added merit to earlier hypotheses that dermal transfer and indirect ingestion 

are important routes of children’s exposure to pesticides. In fact, the shift to less volatile, more 

s 

ce 

 are 

he 

ion routes). Low detection frequencies in 

od measurements, however, increase uncertainty, as does the questionable reliability of 

n urine. 

ent and management activities. Although much of this highuality, real-world data has already been made available to the Program Offices piecemeal and 

y to 

 inherent 

organophilic pyrethroid pesticides magnifies the importance of particle-bound transfer and 

implies an increased significance of indirect ingestion. Substantial challenges still exist in thi

area. One challenge is to incorporate into estimates of dermal exposure what we have learned 

through laboratory studies of the importance of skin condition, contact motion, and number of 

contacts. Another challenge is to standardize the collection methods used to measure the surfa

residues that are a key part of dermal exposure estimates. A third challenge is to improve our 

indirect ingestion exposure algorithms to ensure that we are not missing major transfer 

mechanisms that may bridge the gap between what we are estimating as intake and what we

measuring as excreted. 

Analysis of the dietary ingestion components of our studies produce intake estimates that suggest 

dietary ingestion may often be the dominant route of exposure (even with pyrethroids despite t

increased importance of the dermal and indirect ingest

fo

duplicate diet estimates for young children. Improvements are still essential in both the sample 

collection and the chemical analysis methods. Large differences in dietary exposure estimates 

among children in the same studies point to a need for a better understanding of the variability in

dietary exposure. 

Clearly, more information is needed to assess the relative importance of the exposure routes 

under different conditions and with pesticides from diverse compound classes. More work is 

necessary to reconcile aggregate exposure estimates with levels of biomarkers measured i

Moreover, more work is needed to better understand how exposures and important exposure 

factors differ across age groups, as children move through different developmental stages. 

We anticipate that the analyses presented in this report will be useful to the EPA Program 

Offices, including the Office of Pesticide Programs and the Office of Children's Health 

Protection, in their risk assessm

q

by publication in the peer reviewed literature, we expect consideration of the data collectivel

provide added value to the results of individual studies. Admittedly there are limitations

in the comparisons: studies were performed in different seasons, in different years, using 

different methods, and with different sample sizes. We are confident, however, that these 

analyses will facilitate more accurate exposure and risk assessments, thereby strengthening 

regulatory actions aimed at reducing risk, and helping to ensure that pesticides are appropriately 

regulated. 

154
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164
165

APPENDIX A: Summary Statistics 
Air Concentrations 

Table A.1 Summary statistics for airborne chlorpyrifos concentrations (ng/m3) by study. 

Study Location N %Det Mean SD GM GSD Min 25th 50th 75th 95t

NHEXAS-AZ Indoor 14 50 25.9 44.6 8.13 4.7 <3.2 <3.2 3.37 31.6 16

Outdoor 3 0 NC NC NC NC NC NC NC NC NC 

MNCPES Personal 61 95 6.05 17.6 1.91 4.2 <0.10 0.93 1.52 4.61 16.

Indoor 80 93 5.61 10.1 1.71 5.1 <0.10 0.50 1.85 4.40 30.

Outdoor 52 6 0.09 NC NC NC <0.10 <0.10 <0.10 <0.10 0.1

CTEPP-NC Indoor 148 100 17.5 39.3 6.45 4.0 0.31 2.26 6.07 17.3 62.

Outdoor 140 83 1.00 4.02 0.30 3.6 <0.10 0.11 0.28 0.64 3.9

CTEPP-OH Indoor 147 98 6.24 13.8 2.26 3.7 <0.10 0.93 1.75 5.82 21.

Outdoor 126 75 0.39 0.75 0.21 2.7 <0.10 0.07 0.20 0.39 1.1

JAX Indoor 9 100 30.0 23.3 24.3 1.9 9.81 18.3 20.4 32.4 84.

Outdoor 9 56 3.05 2.35 2.06 2.8 <1.0 <1.0 3.77 4.94 6.6

CHAMACOS Indoor 20 100 2.0 1.1 1.8 1.6 0.6 1.5 1.9 2.3 4.

Outdoor 19 84 1.2 1.1 0.8 2.3 <0.3 0.5 0.90 1.5 5.

CPPAES (Day 1) Indoor 10 100 204 247 86.3 5.1 4.55 23.9 150 312 81

Test House (Day 1) Indoor 6 100 431 376 301 2.6 100 115 290 790 100

NC, not calculated due to low detection frequency

166
Table A.2 Summary statistics for airborne diazinon concentrations (ng/m3) by study. 

Study Location N %Det Mean SD GM GSD Min 25th 50th 75th 95t

NHEXAS –AZ Indoor 14 64 30.9 61.4 7.22 5.4 <2.0 <2.0 5.59 12.0 22

Outdoor 3 0 NC NC NC NC NC NC NC NC NC 

MNCPES Personal 48 65 1.88 7.86 0.34 4.5 <0.10 <0.10 0.28 0.82 4.6

Indoor 73 66 1.68 5.76 0.35 4.7 <0.10 <0.10 0.27 0.81 8.5

Outdoor 52 12 0.29 NC NC NC <0.10 <0.10 <0.10 <0.10 0.2

CTEPP-NC Indoor 148 100 36.4 202 2.42 6.0 0.14 0.66 2.03 5.09 63.

Outdoor 140 52 0.59 3.70 0.13 3.0 <0.10 <0.10 0.09 0.22 0.9

CTEPP-OH Indoor 147 98 11.8 48.0 1.41 5.3 <0.10 0.51 0.97 2.41 56.

Outdoor 143 74 1.09 6.91 0.19 3.3 <0.10 <0.10 0.15 0.33 1.4

JAX Indoor 9 78 7.18 8.45 3.43 4.7 <0.40 3.43 4.64 8.05 28.

Outdoor 9 67 3.45 2.63 1.89 4.2 <0.40 <0.40 3.53 5.78 6.7

CHAMACOS Indoor 20 100 5.2 9.8 2.5 2.8 1.0 1.3 1.8 2.8 2

Outdoor 19 100 5.3 6.1 3.3 2.6 1.0 1.4 2.8 5.3 2

DIYC Indoor 16 100 2280 1790 1470 3.0 245 541 1840 4060 490

PET Indoor 60 77 127 196 25.8 10.7 <0.85 7.60 45.6 163 56

NC, not calculated due to low detection frequency

Study Location N %Det Mean SD GM GSD Min 25th 50th 75th 95t

NHEXAS-AZ Indoor 14 14 NC NC NC NC <3.0 <3.0 <3.0 <3.0 5.6

Outdoor 3 33 NC NC NC NC <3.0 <3.0 <3.0 6.85 6.8

MNCPES Indoor 88 67 1.53 1.87 0.59 5.3 <0.10 <0.10 1.18 2.11 4.8

Outdoor 51 12 NC NC NC NC <0.10 <0.10 <0.10 <0.10 0.7

JAX Indoor 9 0 NC NC NC NC NC NC NC NC NC 

Outdoor 9 11 NC NC NC <1.4 <1.4 <1.4 <1.4 <1.4 6.5

CHAMACOS Indoor 20 15 NC NC NC NC <0.5 <0.5 <0.5 <0.5 5.

Outdoor 19 37 NC NC NC NC <0.5 <0.5 <0.5 2.6 1

NC, not calculated due to low detection frequency

167

Table A.3 Summary statistics for airborne malathion concentrations (ng/m3) by study. 
Table A.4 Summary statistics for airborne cis-permethrin concentrations (ng/m3) by study. 

Study Location N %Det Mean SD GM GSD Min 25th 50th 75th 95t

MNCPES Personal 64 86 0.78 2.21 0.23 4.1 <0.09 0.09 0.20 0.61 2.0

Indoor 89 69 0.53 2.34 0.11 3.8 <0.09 <0.09 0.09 0.18 1.2

Outdoor 51 43 NC NC NC NC <0.04 <0.04 <0.04 0.06 0.1

CTEPP-NC Indoor 148 65 1.91 4.83 0.42 5.5 <0.10 <0.10 0.41 1.43 7.7

Outdoor 140 19 NC NC NC NC <0.10 <0.10 <0.10 <0.10 0.4

CTEPP-OH Indoor 147 22 NC NC NC NC <0.40 <0.40 <0.40 <0.40 1.6

Outdoor 143 21 NC NC NC NC <0.40 <0.40 <0.40 <0.40 0.9

JAX Indoor 9 44 NC NC NC NC <1.0 <1.0 <1.0 2.21 92.

Outdoor 9 56 1.55 0.80 1.34 1.8 <1.0 <1.0 2.13 2.22 2.2

CHAMACOS Indoor 20 40 NC NC NC NC <0.6 <0.6 <0.6 0.77 1.

Outdoor 20 32 NC NC NC NC <0.6 <0.6 <0.6 1.1 1.

NC, not calculated due to low detection frequencyTable A.5 Summary statistics for airborne trans-permethrin concentrations (ng/m3) by study. 

Study Location N %Det Mean SD GM GSD Min 25th 50th 75th 95t

MNCPES Personal 68 63 0.61 1.95 0.11 5.3 <0.09 <0.09 <0.09 0.38 1.7

Indoor 96 42 NC NC NC NC <0.09 <0.09 <0.09 0.09 1.2

Outdoor 51 14 NC NC NC NC <0.09 <0.09 <0.09 <0.09 0.4

CTEPP-NC Indoor 148 63 1.72 4.89 0.35 5.3 <0.10 <0.10 0.27 1.16 7.1

Outdoor 140 19 NC NC NC NC <0.10 <0.10 <0.10 <0.10 0.3

CTEPP-OH Indoor 147 19 NC NC NC NC <0.40 <0.40 <0.40 <0.40 1.0

Outdoor 143 17 NC NC NC NC <0.40 <0.40 <0.40 <0.40 0.6

JAX Indoor 9 67 17.8 43.7 3.49 5.3 <1.0 <1.0 3.06 6.38 13

Outdoor 9 78 3.51 3.01 2.54 2.4 <1.0 2.08 2.50 4.55 10.

CHAMACOS Indoor 19 16 NC NC NC NC <0.6 <0.6 <0.6 <0.6 1.

Outdoor 18 0 NC NC NC NC <0.6 <0.6 <0.6 <0.6 <0.

NC, not calculated due to low detection frequency

168
Table A.6 Summary statistics for airborne TCPy concentrations (ng/m3) by study. 

Study Location N %Det

Mean SD GM GS

D

Min 25th 50th 75th 95t

CTEPP-NC In

door 148 99 4.68 12.47 1.78 3.8 <0.09 0.81 1.77 3.99 14.

Outdoor 140 88 0.44 0.91 0.24 2.6 <0.09 0.13 0.22 0.40 1.5

CTEPP-OH In

door 144 100 1.97 4.62 0.84 3.1 0.09 0.43 0.65 1.74 8.6

Outdoor 133 88 0.32 0.48 0.22 2.2 <0.09 0.13 0.21 0.36 0.8

Study

Location N 

%Det

Mean SD GM GS

D

Min 25th 50th 75th 95t

CTEPP-OH In

door 147 95 1.52 3.62 0.64 3.1 <0.09 0.35 0.53 1.04 5.6

Outdoor 141 86 1.48 5.93 0.36 3.7 <0.09 0.14 0.33 0.77 2.4

Table A.7 Summary statistics for airborne IMP concentrations (ng/m3) by study. 

169
 Dust and Soil Concentrations and Loadings 

Table A.8 Summary statistics for chlorpyrifos concentrations measured in soil (ng/g). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

MNCPES Soil Home 102 3 NC NC NC NC <10 <10 <10 

CTEPP (NC) Soil Home 128 19 NC NC NC NC <0.5 <0.5 <0.5 

Daycare 13 8 NC NC NC NC <0.5 <0.5 <0.5 

CTEPP (OH) Soil Home 127 39 NC NC NC NC <0.5 <0.5 <0.5 

Daycare 16 38 NC NC NC NC <0.5 <0.5 <0.5 

CCC Soil Daycare 117 23 NC NC NC NC <5 <5 <5 

NC, Not calculated 

 Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

Loading 

(ng/cm2) 

NHEXAS-AZ Vacuum Children ≤ 12 13 77 0.34 0.80 0.012 23 <0.002 0.002 0.007 

CTEPP (NC) Floor Dust Home 121 100 0.14 0.63 0.140 7.3 0.0001 0.0034 0.0094 

Daycare 19 100 0.21 0.37 0.055 6.4 0.0009 0.014 0.057 

CTEPP (OH) Floor Dust Home 120 100 0.106 0.54 0.008 6.9 0.0001 0.002 0.006 

Daycare 23 100 0.19 0.33 0.044 6.8 0.003 0.008 0.045 

CHAMACOS House Dust All 20 95 0.014 0.030 0.005 4.2 <0.001 0.004 0.005 

Concentration 

(ng/g)

CTEPP (NC) Floor Dust Home 121 100 413 1430 137 3.7 11.5 47.5 135 

Daycare 19 100 237 256 132 3.5 12.4 94.2 142 

CTEPP (OH) Floor Dust Home 120 100 871 5030 70.4 5.1 3.62 23.1 52.0 

Daycare 23 100 272 285 168 2.7 40.6 67.0 174 

CHAMACOS House Dust All 20 95 370 684 128 4.7 <4 78.5 120 

Table A.9 Summary statistics for chlorpyrifos measured in dust, presented as both loading (ng/cm2) and concentr

170
Table A.10 Summary statistics for diazinon concentrations measured in soil (ng/g). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

MNCPES Soil Home 102 4 NC NC NC NC <10 <10 <10 

CTEPP (NC) Soil Home 129 18 NC NC NC NC <0.5 <0.5 <0.5 

Daycare 13 0 NC NC NC NC <0.5 <0.5 <0.5 

CTEPP (OH) Soil Home 127 34 NC NC NC NC <0.5 <0.5 <0.5 

Daycare 16 19 NC NC NC NC <0.5 <0.5 <0.5 

CCC Soil Daycare 117 20 NC NC NC NC <2 <2 <2 

PET Soil Home 4 100 16900 6140 16000 1.45 10100 12600 16200 

NC, Not calculated 

able A.11 Summary statistics for diazinon measured in dust, presented as both loading (ng/cm2) and concentrat

T

 Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

NH AZ EXAS- Vacuum Children ≤ 12 13 0. 0.06 0.0 54 035 2 07 7.1 <0.0 <0. 0. 

02 002 002 

CTEPP (NC) Floor Dust Home 121 .0 0.6 . 96 0 964 38 0 0025 8.8 <0. 0. 0. 

0003 0006 0016 

Daycare 1 10 0.5 2. 0. 11 0. 0. 9 0 71 25 0235 0002 0032 0.0177 

CTEPP (OH) Floor Dust Home 912 9 0.0 0 0 7. 0. 0 6 94 .59 .004 5 < 0003 0.001 0.002 

Daycare 2 10 3 0 0.1 0.27 0.02 5.9 0.001 0.004 0.022 

CHAMACOS House Dust All 20 10 .0 0.0 . 3. . 0. 0. 

0 0 065 18 0 0022 2 0 0004 0010 0021 

Loading 

(ng/cm2) 

PET Floor Dust All 17 100 5.72 16.5 0.44 2.4 0.005 0.092 0.35 

CTEPP (NC) Floor Dust Home 12 9 2 1 2 5. 1 6 82 380 4.4 1 <2 7 1 

.90 7.5 

Daycare 1 10 4 15 5 5. 3 2 6 9 0 39 60 8.6 6 .06 6.0 5.2 

CTEPP (OH) Floor Dust Home 12 9 13 8 3 7. 0 6 60 470 4.3 2 <2 9.72 19.8 

Daycare 2 10 2 4 7 4. 5 2 4 3 0 60 72 3.7 8 .08 8.4 0.0 

CHAMACOS House Dust All 20 10 2 5 5 3. 7 2 5 

0 02 62 3.9 9 .75 1.3 8.8 

Co

(n

st ll 17 100 2920 5300 4 2.1 256 6 3 

ncentration 

g/g) 

PET Floor Du A 0 0 990 54 12 

NC, Not calculated

171
Table A.12 Summary statistics for cis-permethrin concentrations measured in soil (ng/g). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

MNCPES Soil Home 102 3 NC NC NC NC <10 <10 <10 

CTEPP (NC) Soil Home 128 19 NC NC NC NC <0.5 <0.5 <0.5 

Daycare 13 8 NC NC NC NC <0.5 <0.5 <0.5 

CTEPP (OH) Soil Home 127 39 NC NC NC NC <0.5 <0.5 <0.5 

Daycare 16 0 NC NC NC NC <0.5 <0.5 <0.5 

CCC Soil Daycare 117 23 NC NC NC NC <5 <5 <5 

NC, Not calculated 

 Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

Loading 

(ng/cm2) 

CTEPP (NC) Floor Dust Home 121 100 0.975 3.02 0.104 8.8 0.0012 0.026 0.103 

Daycare 20 100 5.44 19.6 0.507 8.3 0.005 0.181 0.694 

CTEPP (OH) Floor Dust Home 120 100 0.83 4.32 0.063 7.5 0.002 0.015 0.045 

Daycare 23 100 0.78 1.36 0.26 5.0 0.01 0.07 0.27 

CHAMACOS House Dust All 20 100 0.030 0.063 0.013 3.4 0.0013 0.0057 0.015 

Concentration 

(ng/g)

CTEPP (NC) Floor Dust Home 121 100 6080 29400 995 4.6 67.1 347 804 

Daycare 20 100 3500 6760 1140 4.3 113 455 806 

CTEPP (OH) Floor Dust Home 120 100 2320 8050 572 4.3 16.6 197 470 

Daycare 23 100 1460 1300 968 2.6 127 418 1010 

CHAMACOS House Dust All 20 100 923 2010 317 4.2 25.6 113 345 

Table A.13 Summary statistics for cis-permethrin measured in dust, presented as both loading (ng/cm2) and conc

172
Table A.14 Summary statistics for trans-permethrin concentrations measured in soil (ng/g). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

CTEPP (NC) Soil Home 129 22 NC NC NC NC <0.5 <0.5 <0.5 

Daycare 13 8 NC NC NC NC <0.5 <0.5 <0.5 

CTEPP (OH) Soil Home 124 6 NC NC NC NC <0.5 <0.5 <0.5 

Daycare 14 0 NC NC NC NC <0.5 <0.5 <0.5 

CCC Soil Daycare 117 16 NC NC NC NC <5 <5 <5 

NC, Not calculated 

 Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

Loading 

(ng/cm2) 

CTEPP (NC) Floor Dust Home 121 100 0.94 2.99 0.09 10 0.0006 0.015 0.09 

Daycare 20 100 5.59 20.2 0.49 8.2 0.005 0.137 0.41 

CTEPP (OH) Floor Dust Home 118 100 0.76 4.26 0.05 8.2 0.002 0.010 0.03 

Daycare 22 100 0.73 1.40 0.20 6.0 0.007 0.047 0.26 

CHAMACOS House Dust All 20 100 0.06 0.13 0.03 3.4 0.002 0.014 0.02 

Concentration 

(ng/g

)

CTEPP (NC) Floor Dust Home 121 100 6120 30400 835 5.0 51.3 267 629 

Daycare 20 100 3600 7120 1110 4.5 125 542 856 

CTEPP (OH) Floor Dust Home 118 100 2340 8320 453 5.0 16.5 132 344 

Daycare 22 100 1260 1220 784 2.7 126 362 554 

CHAMACOS House Dust All 20 100 1860 4030 655 4.0 43.2 310 608 

Table A.15 Summary statistics for trans-permethrin measured in dust, presented as both loading (ng/cm2) and co

173
Table A.16 Summary statistics for cyfluthrin concentrations measured in soil (ng/g). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

CTEPP (NC) Soil Home 129 12 NC NC NC NC <5 <5 <5 

Daycare 13 8 NC NC NC NC <5 <5 <5 

CTEPP (OH) Soil Home 127 17 NC NC NC NC <5 <5 <5 

Daycare 16 25 NC NC NC NC <5 <5 <5 

CCC Soil Daycare 117 10 NC NC NC NC <6 <6 <6 

NC, Not calculated Table A.17 Summary statistics for cyfluthrin measured in dust, presented as both loading (ng/cm2) and concentra

Study t Method Group n %De Mean SD GM GSD M 2 in 5th 50th 

CTEPP (NC) Home 121 48 NC NC NC NC <0 <0. <0.0 .0003 0003 003 

e N 0. <0. <0.0

Floor Dust

Daycar 19 42 NC NC NC C < 0003 0003 003 

CTEPP (OH) Home 119 74 0.056 0.10 0.0 5. 0.0 <0. 0. 16 6 < 003 0003 018 

e 0.0 0 <0.

Floor Dust

Loading 

(ng/cm2) Daycar 23 74 0.37 0.5 59 14 <0. 003 0003 0.14 

CHAMACOS t House Dus All 20 10 NC NC NC N <0. <0. <0. 

C 005 005 005 

CTEPP (NC) Home 121 48 NC NC N N < < C C 10 10 <10 

e N < <

Floor Dust

Daycar 19 42 NC NC NC C 10 10 <10 

CTEPP (OH) Home 119 74 329 482 148 3. < < 9 10 10 195 

e 2 3. < <

Floor Dust

Daycar 23 74 389 323 21 7 10 10 336 

Concentration 

(ng/g) 

CHAMACOS t House Dus All 20 10 NC NC N N <1 <1 < C C 00 00 100 

NC, Not calculated 

174
Table A.18 Summary statistics for TCPy concentrations measured in soil (ng/g). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

CTEPP (NC) Soil Home 129 71 3.61 14.9 0.62 4.22 <0.2 <0.2 0.57 

Daycare 13 46 NC NC NC NC <0.2 <0.2 <0.2 

CTEPP (OH) Soil Home 127 80 3.99 15.3 0.82 4.35 <0.2 0.23 0.70 

Daycare 16 81 1.15 1.57 0.60 3.17 <0.2 0.22 0.63 

NC, Not calculated 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

CTEPP (OH) Soil Home 125 41 NC NC NC NC <0.2 <0.2 <0.2 

Daycare 16 38 NC NC NC NC <0.2 <0.2 <0.2 

NC, Not calculated Table A.19 Summary statistics for IMP concentrations measured in soil (ng/g). 

175
Total Available Surface Residue Loadings 

Table A.20 Summary statistics for chlorpyrifos in Total Available Residue (ng/cm2). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

NHEXAS-AZ Surface Wipe Window Sill 6 17 NC NC NC NC <0.07 <0.07 <0.07 

MNCPES LWW Floor 99 62 1.04 0.41 0.83 1.4 <1.15 <1.15 <1.15 

CCC Surface Wipe Floor 168 64 0.38 2.28 0.027 7.7 <MDL <MDL 0.02 

Desk/Table 80 73 0.18 0.53 0.036 6.4 <MDL 0.004 0.04 

JAX Surface Wipe Floor (Screening) 46 87 4.87 20.32 0.44 12.5 <MDL 0.16 0.50 

Floor 9 78 0.85 1.11 0.21 12.0 <MDL 0.16 0.39 

Play Area 9 67 0.32 0.77 0.014 17.0 <MDL <MDL 0.006 

CHAMACOS Surface Wipe All 20 95 0.060 0.057 0.037 2.96 <MDL 0.017 0.046 

CPPAES LWW Living Area/Kitchen

(Pre-application) 20 60 0.29 0.38 0.1 4.91 0.02 0.02 0.099 

Living Area/Kitchen 97 100 2.39 4.30 0.95 3.68 0.07 0.43 0.82 

Bedroom

(Pre-application) 20 65 0.41 0.48 0.16 5.24 0.02 0.02 0.26 

Bedroom 64 100 1.97 4.84 0.52 4.40 0.031 0.18 0.35 

Deposition Cumulative 39 100 2.12 2.66 0.99 4.17 0.03 0.34 1.4 

Coupons Interval 40 100 1.24 1.59 0.62 3.96 0.025 0.30 0.89 

Test House Deposition Bedroom 5 100 1.89 2.12 1.07 3.81 0.14 0.83 1.26 

Coupons Den 28 100 2.23 2.57 1.64 2.07 0.63 0.79 1.68 

Kitchen 24 100 31.6 56.4 11.5 4.16 1.0 5.00 9.12 

All 57 100 14.6 39.0 3.58 4.46 0.14 1.26 2.82 

Surface Wipe Kitchen 9 100 1548 2793 627 3.71 120 270 470 

NC, Not calculated LWW, Lioy-Weisel-Wainman sampler 

176
Table A.21 Summary statistics for diazinon in Total Available Residue (ng/cm2). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

NHEXAS-AZ Surface Wipe Window Sill 6 0 NC NC NC NC <2.0 <2.0 <2.0 

MNCPES LWW Floor 99 7 NC NC NC NC <3.5 <3.5 <3.5 

CCC Surface Wipe Floor 168 54 0.21 1.44 0.011 9.1 0.001 0.002 0.004 

Desk/Table 80 41 NC NC NC NC 0.001 0.002 0.002 

JAX Surface Wipe Floor (Screening) 46 89 1.35 5.07 0.11 10.5 <0.002 0.03 0.11 

Floor 9 44 NC NC NC NC <0.002 <0.002 <0.002 

Play Area 9 33 NC NC NC NC <0.002 <0.002 <0.002 

CHAMACOS Surface Wipe All 20 95 0.041 0.033 0.024 3.73 <0.005 0.011 0.038 

DIYC Surface Wipe Floor 

(Pre-application) 7 86 7.06 6.87 4.71 2.7 <0.3 2.61 3.85 

Floor 35 100 12.7 20.4 6.35 2.9 0.71 3.93 5.54 

NC, Not calculated 

LWW, Lioy-Weisel-Wainman sampler 

Table A.22 Summary statistics for cis-permethrin in Total Available Residue (ng/cm2). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

CCC Surface Wipes Floor 168 60 0.14 0.36 0.022 6.3 0.002 0.004 0.02 

Surfaces 80 44 1.55 10.5 0.015 8.4 <0.005 <0.005 <0.005 

JAX Surface Wipes Floor (Screening) 46 87 8.46 15.5 0.93 19.9 <0.005 0.19 2.22 

Floor 9 78 8.56 16.4 0.35 28.3 <0.005 0.13 0.24 

Play Area 9 67 1.57 3.2 0.09 23.3 <0.005 <0.005 0.04 

CHAMACOS Surface Wipe All 20 85 0.21 0.36 0.1 6.8 <0.005 0.053 0.10 

177
Table A.23 Summary statistics for trans-permethrin in Total Available Residue (ng/cm2). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

CCC Surface Wipe Floor 168 62 0.25 0.71 0.031 8.1 <0.005 <0.005 0.03 

Desk/Table 80 60 3.23 24.7 0.027 9.0 <0.005 <0.005 0.02 

JAX Surface Wipe Floor (Screening) 46 89 10.2 19.4 1.18 19.3 <0.005 0.26 2.93 

Floor 9 78 12.9 24.9 0.44 34.1 <0.005 0.12 0.34 

Play Area 9 89 2.06 4.41 0.14 19.8 <0.005 0.02 0.05 

CHAMACOS Surface Wipe All 20 95 0.43 0.77 0.18 5.1 <0.002 0.14 0.23 

Table A.24 Summary statistics for cyfluthrin in Total Available Residue (ng/cm2). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

CCC Surface Wipe Floor 168 7 NC NC NC NC <0.006 <0.006 <0.006 

Desk/Table 80 1 NC NC NC NC <0.006 <0.006 <0.006 

JAX Surface Wipe Floor (Screening) 46 20 NC NC NC NC <0.006 <0.006 <0.006 

Floor 9 33 NC NC NC NC <0.006 <0.006 <0.006 

Play Area 9 11 NC NC NC NC <0.006 <0.006 <0.006 

CHAMACOS Surface Wipe All 20 5 NC NC NC NC <0.05 <0.05 <0.05 

NC, Not calculated

178
Transferable Surface Residue Loadings 

Table A.25 Summary statistics for chlorpyrifos in Transferable Residue (ng/cm2). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

MNCPES C18 Press Floor 102 8 NC NC NC NC <0.33 <0.33 <0.33 

Surface 102 5 NC NC NC NC <0.33 <0.33 <0.33 

CTEPP (NC) Surface Wipe Home Floor 28 89 0.02 0.05 0.0063 4.6 <0.0007 0.0031 0.0066 

Kitchen Counter 18 89 0.03 0.04 0.008 5.8 <0.0007 0.003 0.007 

PUF Roller Home 18 94 0.01 0.023 0.005 4.5 <0.0004 0.0015 0.0035 

CTEPP (OH) Surface Wipe Home Floor 21 86 0.19 0.84 0.0043 8.8 <0.0007 0.001 0.003 

Kitchen Counter 13 62 0.068 0.21 0.0025 10 <0.0007 <0.0007 0.001 

PUF Roller Home 13 85 0.25 0.89 0.0026 11 <0.0004 0.001 0.002 

CHAMACOS C18 Press All 20 0 NC NC NC NC <0.09 <0.09 <0.09 

CPPAES Surface Wipe Floor 41 100 0.052 0.054 0.026 4.02 0.002 0.014 0.031 

Test House C18 Press Den/Kitchen 16 94 1.02 2.06 0.26 5.13 <0.03 0.11 0.23 

PUF Roller Den/Kitchen 6 100 0.030 0.059 0.007 5.97 0.001 0.002 0.0045 

NC, Not calculated

179
Table A.26 Summary statistics for diazinon in Transferable Residue (ng/cm2). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

MNCPES C18 Press Floor 102 8 NC NC NC NC <0.14 <0.14 <0.14 

Surface 102 8 NC NC NC NC <0.14 <0.14 <0.14 

CTEPP (NC) Surface Wipe Home Floor 28 68 0.056 0.19 0.002 8.4 <0.0007 <0.0007 0.001 

Kitchen Counter 18 61 0.063 0.21 0.003 8.8 <0.0007 <0.0007 0.002 

PUF Roller Home 18 67 0.075 0.22 0.004 13 <0.0004 <0.0004 0.003 

CTEPP (OH) Surface Wipe Home Floor 21 38 NC NC NC NC <0.0007 <0.0007 <0.0007 

Kitchen Counter 13 31 NC NC NC NC <0.0007 <0.0007 <0.0007 

PUF Roller Home 13 54 0.01 0.03 0.001 1.71 <0.0004 <0.0004 0.001 

CHAMACOS C18 Press All 20 0 NC NC NC NC <0.02 <0.02 <0.02 

DIYC C18 Press Floor 9 89 10.9 9.11 6.5 3.5 <1.2 1.24 3.78 

Counter 3 67 NC NC NC NC <1.2 NC 3.18 

Play Area 3 33 NC NC NC NC <1.2 NC <1.2 

NC, Not calculated 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

CTEPP (NC) Surface Wipe Home Floor 28 93 0.161 0.263 0.034 8.6 <0.0007 0.0071 0.0443 

Kitchen Counter 18 83 3.05 11.7 0.044 24 <0.0007 0.0062 0.0596 

PUF Roller Home 18 83 0.164 0.319 0.020 13 <0.0004 0.0038 0.0229 

CTEPP (OH) Surface Wipe Home Floor 21 71 0.28 1.13 0.011 12 <0.0007 <0.0007 0.009 

Kitchen Counter 13 39 NC NC NC NC <0.0007 <0.0007 <0.0007 

PUF Roller Home 13 69 0.035 0.08 0.004 9.3 <0.0004 <0.0004 0.004 

CHAMACOS C18 Press All 20 0 NC NC NC NC <0.2 <0.2 <0.2 

NC, Not calculated Table A.27 Summary statistics for cis-permethrin in Transferable Residue (ng/cm2). 

180
Table A.28 Summary statistics for trans-permethrin in Transferable Residue (ng/cm2). 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

CTEPP (NC) Surface Wipe Home Floor 28 93 0.157 0.268 0.027 9.8 <0.0007 0.005 0.04 

Kitchen Counter 18 83 3.48 13.5 0.041 26 <0.0007 0.006 0.026 

PUF Roller Home 18 83 0.18 0.34 0.018 14 <0.0004 0.003 0.02 

CTEPP (OH) Surface Wipe Home Floor 21 71 0.28 1.12 0.011 13 <0.0007 <0.0007 0.01 

Kitchen Counter 13 39 NC NC NC NC <0.0007 <0.0007 <0.0007 

PUF Roller Home 13 69 0.03 0.08 0.003 8.2 <0.0004 <0.0004 0.003 

CHAMACOS C18 Press All 20 0 NC NC NC NC <0.2 <0.2 <0.2 

NC, Not calculated 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

CTEPP (NC) Surface Wipe Home Floor 28 7 NC NC NC NC <0.0007 <0.0007 <0.0007 <0

Kitchen Counter 18 0 NC NC NC NC <0.0007 <0.0007 <0.0007 <0

PUF Roller Home 18 78 0.11 0.10 0.05 5.4 <0.0004 0.02 0.10 

CTEPP (OH) Surface Wipe Home Floor 21 10 NC NC NC NC <0.0007 <0.0007 <0.0007 <0

Kitchen Counter 13 0 NC NC NC NC <0.0007 <0.0007 <0.0007 <0

PUF Roller Home 13 0 NC NC NC NC <0.0004 <0.0004 <0.0004 <0

CHAMACOS C18 Press All 20 0 NC NC NC NC <0.2 <0.2 <0.2 

NC, Not calculated Table A.29 Summary statistics for cyfluthrin using in Transferable Residue (ng/cm2). 

181
Solid Food Concentrations and Intakes 

Table A.30 Summary statistics for chlorpyrifos measured in solid food, presented as both intake (μg/day) and con

 Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

Intake μg/day) 

(

MNCPES Dup Diet All 96 91 0.42 0.64 0.24 2.9 <0.12 0.14 0.26 

CTEPP-NC Dup Diet/ Dup Plate All 129 75 0.20 0.66 0.079 3.3 <0.024 0.029 0.093 

CTEPP-OH Dup Diet/ Dup Plate All 125 78 0.13 0.18 0.073 2.7 <0.024 0.035 0.071 

JAX Dup Diet All 9 100 1.3 1.6 0.76 3.0 0.12 0.48 1.1 

Concentration

(μg/kg) 

NHEXAS-AZ Dup Diet ≤12 years 20 15 NC NC NC NC <1.0 <1.0 <1.0 

MNCPES Dup Diet All 96 88 0.79 1.2 0.51 2.3 <0.26 0.29 0.53 

CTEPP (NC) Dup Diet/ Dup Plate Home 129 65 0.57 1.8 0.20 3.4 <0.08 <0.08 0.19 

Daycare 24 54 0.23 0.25 0.14 2.7 <0.08 <0.08 0.10 

CTEPP (OH) Dup Diet/ Dup Plate Home 125 66 0.38 0.61 0.19 3.0 <0.08 <0.08 0.19 

Daycare 29 69 0.20 0.19 0.15 2.3 <0.08 <0.08 0.14 

JAX Dup Diet All 9 100 1.3 2.3 0.51 4.2 0.050 0.25 0.38 

CHAMACOS Dup Diet All 17 6 NC NC NC NC <1.0 <1.0 <1.0 

Dup Diet, Duplicate Diet; Dup Plate, Duplicate Plate NC, Not calculated 

182
Table A.31 Summary statistics for diazinon measured in solid food, presented as both intake (μg/day) and concen

 Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

Intake 

y) 

(μg/da

MNCPES Dup Diet All 101 20 NC NC NC NC <0.019 <0.019 <0.019 

CTEPP-NC Dup Diet/ Dup Plate All 128 32 NC NC NC NC <0.024 <0.024 <0.024 

CTEPP-OH Dup Diet/ Dup Plate All 125 23 NC NC NC NC <0.024 <0.024 <0.024 

DIYC Dup Diet All 16 100 0.42 0.29 0.34 2.0 0.095 0.23 0.30 

JAX Dup Diet All 9 11 NC NC NC NC <0.35 <0.35 <0.35 

Concentration

(μg/kg) 

NHEXAS-AZ Dup Diet ≤12 years 20 10 NC NC NC NC <0.7 <0.7 <0.7 

MNCPES Dup Diet All 101 6 NC NC NC NC <0.2 <0.2 <0.2 

CTEPP (NC) Dup Diet/ Dup Plate Home 128 22 NC NC NC NC <0.08 <0.08 <0.08 

Daycare 24 25 NC NC NC NC <0.08 <0.08 <0.08 

CTEPP (OH) Dup Diet/ Dup Plate Home 125 15 NC NC NC NC <0.08 <0.08 <0.08 

Daycare 29 24 NC NC NC NC <0.08 <0.08 <0.08 

DIYC Dup Diet All 16 100 0.29 0.25 0.23 1.9 0.12 0.15 0.17 

JAX Dup Diet All 9 44 NC NC NC NC <0.04 <0.04 <0.04 

CHAMACOS Dup Diet All 17 12 NC NC NC NC <1 <1 <1 

Dup Diet, Duplicate Diet; Dup Plate, Duplicate Plate NC, Not calculated 

183
Table A.32 Summary statistics for cis-permethrin measured in solid food, presented as both intake (μg/day) and 

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

Intake 

y) 

(μg/da

MNCPES Dup Diet All 100 30 NC NC NC NC <0.019 <0.019 <0.019 

CTEPP-NC Dup Diet All 129 50 2.7 14 0.10 7.3 <0.024 <0.024 0.060 

CTEPP-OH Dup Diet All 125 38 NC NC NC NC <0.024 <0.024 <0.024 

Concentration

(μg/kg) 

MNCPES Dup Diet All 100 20 NC NC NC NC <0.024 <0.024 <0.024 

CTEPP (NC) Dup Diet/ Dup Plate Home 129 46 NC NC NC NC <0.08 <0.08 <0.08 

Daycare 24 25 NC NC NC NC <0.08 <0.08 <0.08 

CTEPP (OH) Dup Diet/ Dup Plate Home 125 31 NC NC NC NC <0.08 <0.08 <0.08 

Daycare 29 24 NC NC NC NC <0.08 <0.08 <0.08 

JAX Dup Diet All 9 78 1.6 4.2 0.19 7.9 <0.02 0.080 0.29 

Dup Diet, Duplicate Diet; Dup Plate, Duplicate Plate NC, Not calculated Table A.33 Summary statistics for trans-permethrin measured in solid food, presented as both intake (μg/day) an

(μg/kg). 

 Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

Intake 

(μg/day) 

MNCPES Dup Diet All 101 13 NC NC NC NC <0.01 <0.01 <0.01 

CTEPP-NC Dup Diet/ Dup Plate All 128 50 1.5 8.0 0.087 6.1 <0.024 <0.024 0.051 

CTEPP-OH Dup Diet/ Dup Plate All 125 38 NC NC NC NC <0.024 <0.024 <0.024 

Concentration

(μg/kg) 

MNCPES Dup Diet All 101 7 NC NC NC NC <0.08 <0.08 <0.08 

CTEPP (NC) Dup Diet/ Dup Plate Home 128 46 NC NC NC NC <0.08 <0.08 <0.08 

Daycare 24 25 NC NC NC NC <0.08 <0.08 <0.08 

CTEPP (OH) Dup Diet/ Dup Plate Home 125 31 NC NC NC NC <0.08 <0.08 <0.08 

Daycare 29 24 NC NC NC NC <0.08 <0.08 <0.08 

JAX Dup Diet All 9 78 2.8 7.3 0.27 9.8 <0.02 0.17 0.22 

Dup Diet, Duplicate Diet; Dup Plate, Duplicate Plate NC, Not calculated 

184
Table A.34 Summary statistics for TCPy measured in solid food, presented as both intake (μg/day) and concentra

Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

Intake 

(μg/day) CTEPP-NC Dup Diet/ Dup Plate All 128 99 1.4 0.97 0.99 2.6 <0.038 0.71 1.2 

CTEPP-OH Dup Diet/ Dup Plate All 127 100 1.0 0.90 0.70 2.5 0.038 0.41 0.77 

Concentration

) 

(μg/kg

CTEPP (NC) Dup Diet/ Dup Plate Home 128 98 3.1 2.8 2.1 2.6 <0.12 1.5 2.3 

Daycare 24 100 3.8 3.3 2.8 2.3 0.25 2.3 2.9 

CTEPP (OH) Dup Diet/ Dup Plate Home 127 99 2.6 2.6 1.7 2.7 <0.13 1.0 1.9 

Daycare 29 100 2.8 5.0 1.7 2.4 0.38 0.98 1.5 

JAX Dup Diet All 9 100 5.0 3.7 4.0 1.9 2.0 2.4 3.2 

Dup Diet, Duplicate Diet; Dup Plate, Duplicate Plate NC, Not calculated 

 Study Method Group n %Det Mean SD GM GSD Min 25th 50th 

Intake 

g/day) 

(μ

CTEPP-OH Dup Diet/ Dup Plate All 32 97 0.19 0.17 0.14 2.2 <0.024 0.093 0.12 

Home 40 88 0.52 0.54 0.36 2.4 <0.12 0.26 0.33 

Concentration

(μg/kg) CTEPP (OH) Dup Diet/ Dup Plate

Daycare 29 83 0.40 0.29 0.30 2.3 <0.13 0.14 0.35 

Dup Diet, Duplicate Diet; Dup Plate, Duplicate Plate NC, Not calculated Table A.35 Summary statistics for IMP measured in solid food, presented as both intake (μg/day) and concentrat

185
Hand Loadings 

Table A.36 Summary statistics for chlorpyrifos hand loadings (ng/cm2). 

Study Group n %Det Mean SD GM GSD Min 25th 50th 75

MNCPES Rinse 97 39 NC NC NC NC <0.07 <0.07 <0.07 0.09

CTEPP (NC) Home 96 78 0.053 0.11 0.020 3.9 <0.007 0.0082 0.020 0.04

Daycare 31 68 0.023 0.022 0.013 3.4 <0.007 <0.007 0.017 0.03

CTEPP (OH) Home 97 55 0.18 1.5 0.011 4.8 <0.007 <0.007 0.011 0.02

Daycare 29 55 0.036 0.11 0.010 4.0 <0.007 <0.007 0.010 0.02

CPPAES Rinse 38 100 2.8 3.1 1.6 3.2 0.09 0.74 1.9 3

Wipe 44 100 0.32 0.29 0.19 3.3 0.016 0.87 0.30 0.4

NC, Not calculated

Study Group n %Det Mean SD GM GSD Min 25th 50th 75

CTEPP (NC) Home 96 36 NC NC NC NC <0.005 <0.005 <0.005 0.0

Daycare 31 55 0.015 0.032 0.0069 3.0 <0.005 <0.005 0.0065 0.0

CTEPP (OH) Home 97 31 NC NC NC NC <0.005 <0.005 <0.005 0.00

Daycare 29 31 NC NC NC NC <0.005 <0.005 <0.005 0.00

PET Feasibility 15 100 0.32 0.29 0.19 3.6 <0.005 <0.005 <0.005 <0.0

DIYC All 13 100 0.12 0.063 0.092 2.3 <0.005 <0.005 <0.005 <0.0

NC, Not calculatedTable A.37 Summary statistics for diazinon hand loadings (ng/cm2). Table A.38 Summary statistics for cis-permethrin hand loadings (ng/cm2). 

Study Group n %Det Mean SD GM GSD Min 25th 50th 75

CTEPP (NC) Home 96 86 0.92 6.5 0.071 6.7 <0.005 0.026 0.062 0.2

Daycare 31 94 0.17 0.38 0.067 3.9 <0.005 0.035 0.073 0.1

CTEPP (OH) Home 97 88 0.14 0.30 0.039 4.9 <0.005 0.017 0.033 0.09

Daycare 29 79 0.15 0.29 0.034 6.5 <0.005 0.010 0.035 0.1

NC, Not calculated

186
Table A.39 Summary statistics for trans-permethrin hand loadings (ng/cm2). 

Study Group n %Det Mean SD GM GSD Min 25th 50th 75

CTEPP (NC) Home 96 86 0.93 6.8 0.055 6.9 <0.005 0.015 0.049 0.1

Daycare 31 94 0.14 0.38 0.046 4.0 <0.005 0.020 0.036 0.1

CTEPP (OH) Home 97 88 0.13 0.34 0.032 4.9 <0.005 0.013 0.027 0.07

Daycare 29 79 0.15 0.33 0.030 6.5 <0.005 0.011 0.028 0.08

NC, Not calculatedTable A.40 Summary statistics for TCPy hand loadings (ng/cm2). 

Study Group n %Det Mean SD GM GSD Min 25th 50th 75

CTEPP (NC) Home 99 100 0.023 0.022 0.018 1.9 0.0041 0.012 0.019 0.02

Daycare 32 94 0.012 0.0076 0.010 2.0 <0.003 0.0066 0.010 0.01

CTEPP (OH) Home 98 98 0.015 0.012 0.012 2.0 <0.003 0.0079 0.012 0.01

Daycare 29 90 0.012 0.0075 0.010 1.9 <0.003 0.0062 0.011 0.01

NC, Not calculatedTable A.41 Summary statistics for IMP hand loadings (ng/cm2). 

Study Group n %Det Mean SD GM GSD Min 25th 50th 75

CTEPP (OH) Home 98 49 NC NC NC NC <0.003 <0.003 <0.003 0.004

Daycare 29 31 NC NC NC NC <0.003 <0.003 <0.003 0.003

NC, Not calculated

187
188

rinary Metabolite Concentrations 

p n n 

All 9 100 19.6 33 3.9 7.5 0.39 0.76 2.2 2

Table A.42 Summary statistics for TCPy measured in urine (ng/mL). 

Study Grou %Det Mea SD GM GSD Min 25th 50th 75

NHEXAS-AZ ≤12 years 21 0 2 10 1 7.6 9.3 2.2 2.0 5.7 12 

MNCPES All 263 2 2 9 9. 7.7 6.6 2.3 <1.4 4.0 7.2 

CTEPP-NC All 12

CPPAES All 81 93 8.0 4.7 6.4 2.1 <1.0 4.5 7.7 

PET All 30 77 1.3 1.6 0.75 2.8 <0.22 0.39 0.62 1

9 8 5 9 7. 10 5.5 2.1 <1.0 3.8 5.3 8

CTEPP-OH All 123 0 9 5 9 10 5. 3. 4. 1.9 1.2 3.1 2 

5. 7

JAX All 9 100 11 6.4 9.1 2.1 2.9 7.5 9.8 

NHANES ≤12 years 1245 90 4.7 6.1 2.6 3.2 <0.4 1.3 2.8 6

DIYC All 41 100 9.0 6.9 7.1 2.0 1.7 4.4 7.1 

Su statist for 3 ed e ( ). 

n n 

Table A.43 mmary ics -PBA measur in urin ng/mL

Study Group %Det Mea SD GM GSD Min 25th 50th 75

CTEPP-OH All 126 68 81 0 38 0. 3. 0. 2.6 <0.20 20 0.32 0.

<0. 

NHANES ≤12 years 679 79 1.4 10 0.36 3.7 <0.10 0.13 0.34 0.7

JAX 

Tab 44 Su statist for measured in urine (ng/m

p n ean SD D 

NHANES ≤12 years 1220 15 NC NC NC NC <0.7 <0.7 <0.7 <0

le A. mmary ics IMP L). 

Study Grou %Det M GM GS Min 25th 50th 75

NC, Not calculatedU
APPENDIX B: Individual Study Details 

189
National Human Exposur S-AZ) 

ollaborators: University of Arizona, Battelle Memorial Institute, and the Illinois Institute of 

Technology 

Study Design: 

• Type: Observational exposure measurement study with probability-based sample 

• Location: Each of the 15 counties in Arizona 

• Monitoring period: December 1995 to March 1997 

• Study population: 176 households (this report only includes data from 21 households in 

which the primary participants were children, ages 6-12) 

• Pesticide Use: Participants did not report use prior to the study 

Monitoring Protocol: 

• Indoor and Outdoor air: 3-day integrated samples; Personal air: 1-day sample 

• Surface Dust Loading: Modified Hoover “Port-a-Power” vacuum, center and corner of 

living room and bedroom; Window sill wipes 

• Soil: Yard surface soil composite sample 

• Beverages and solid food: 24-hour duplicate diet 

• Hand wipes: 4-mL IPA wipes of both hands 

• Urine: First morning void samples 

• Activities: Baseline and follow-up questionnaires, time-activity diary 

• Analytes (Pesticides): 

o Two pesticides of primary interest (and metabolites), namely chlorpyrifos (TCPy) 

and diazinon, and 14 secondary pesticides, including malathion (MDA) and 

carbaryl (1-naphthol) 

Key Outputs:

• Occurrence, distributions, and determinants of total exposure to the general population 

• Geographic trends in multimedia exposure 

• Total exposures in minority and disadvantaged subsets of the population 

e Assessment Survey in Arizona (NHEXA

C

190
Minnesota Children’s Pesticide Exposure Study (MNCPES) 

Collaborators: RTI, EOHSI, University of Minnesota, and Minnesota Department of Health 

Study Design: 

bservational exposure measurement study with probability-based sample 

Mo o

amples: 

r air for 

 indoor locations (main play area and 

iet, 4-d composite, days 3-6 

% urban homes), day 4 

• Act t

o

es) 

c acid), and 

o PAHs: 13 PAHs including fluoranthene, phenanthrene, and pyrene 

Key Outputs:

• An "inverse" PK model to predict chlorpyrifos dose resulting both from specific pesticide 

applications and from average low-level exposures 

• Distributions and correlations in environmental and biological media (Adgate et al.,

2001; Clayton et al., 2003) 

• Evaluation of pathways of exposure 

• Type: O

• Location: Minneapolis/St. Paul (urban) and Goodhue and Rice counties (rural) 

• Monitoring period: Summer 1997 

• Study population: 102 children, ages 3-13 

• Pesticide Use: Households reporting a history of more frequent pesticide use were 

oversampled 

nit ring Protocol: 

• Environmental s

o Personal, indoor, and outdoor air: Integrated samples, days 1-7 (outdoo

only 10% of urban homes) 

o Surface dust loading: Wipe and press, 2

family room), day 4 

o Soil: Surface soil grab sample, day 4 

o Beverages and solid food: Duplicate d

o Tap water: Grab sample (10

• Biological/Personal samples: 

o Hand rinse, day 3 

o Urine: First morning void samples (88%) 3 samples per child, days 3, 5, and 7 

ivi ies: 

Baseline and follow-up questionnaires, time-activity diary 

o Videotape (4-h, about 20 hom

• Analytes (Pesticides and PAHs): 

o Pesticides: 4 Primary pesticides and metabolites, namely chlorpyrifos (TCPy), 

atrazine (atrazine mercapturate), malathion (malathion dicarboxyli

diazinon, and 14 secondary pesticides 

191
Children’s Total Exposure to Persistent Pesticides and Other Persistent Organic Pollutants 

tudy (CTEPP) 

ollaborators: Battelle 

Stu 

 in 

H) 

001) 

• ion: 257 children, ages 18 months to five years, and their primary adult 

 130 children, 130 homes, 13 daycare centers; OH = 127 children; 127 

s) 

• Pes d

fam ie

Monitorin r

• Sam li llected over a 48-hr period at a home and/or daycare center: 

• Sam e oor air, indoor floor dust, hand wipe, liquid 

foo o

• Sup

uilding characteristics survey, pre- and post monitoring 

e and food diaries 

o r 

o y the participant as 

rs at a home or daycare center within 7 days of 

pling or during the 48-hr monitoring period (hard floor 

• Ana te

Key Outputs: 

• Pes d

 of pesticides from microenvironmental media to child and factors that affect 

•

S

C

dy Design: 

• Type: Observational exposure measurement study with probability-based sample

homes and child care centers 

• Location: North Carolina (NC) and Ohio (O

• Monitoring period: NC (July 2000 to March 2001); OH (April 2001 to November 2

Study populat

caregivers (NC =

homes, 16 daycare center

tici e use: Use during previous seven days were reported by a subset (n=38) of 

il s in their homes 

g P otocol: 

p ng times: Samples co

pl s/data collected: Soil, outdoor air, ind

d, s lid food, urine 

plemental information: 

o Recruitment survey, house/b

qu stionnaires, activity

In addition, 20% of the participants from OH were videotaped about 2 hours at thei

homes 

Additional samples were collected if a pesticide was reported b

having been applied indoors or outdoo

previously scheduled field sam

surface wipe, food preparation surface wipe, and transferable residue) 

ly s of interest: Chlorpyrifos, diazinon, and cis-/trans-permethrin 

tici e distributions in microenvironments where children spend time 

• Transfer

transfer 

Evaluation of pathways of exposure 

• Evaluation of important factors the affect exposure 

192
First National Environmental Health Survey of Child Care Centers (CCC) 

Collaborators: HUD, CPSC (US Department of Housing and Urban Development, US 

 Commission) 

rs 

•

1 

Monito

• , surface wipes, transferable residues (surface press) 

-use pesticides – organophosphates and pyrethroids 

Key

• ial distribution and magnitude of pesticide concentrations on 

child care centers 

Consumer Product Safety

Study Design:

• Type: Observational study with probability-based sample of licensed child care cente

Location: Nationwide 

• Monitoring period: August 2001 to October 200

• Study population: 168 child care centers; no children or adults participated in the study 

• Pesticide use: Child care center directors reported on the professional or center staff 

applications during the previous 12 months 

ring Protocol: 

• One time visit by field technicians to each child care center 

Samples collected: Soil

• Analytes: Current

 Outputs:

• Data relating to pesticide use practices in child care centers across the US 

Characterization of spat

surfaces in a sample of U.S. 

193
Biological and Environmental Monitoring for Organophosphate and Pyrethroid Pesticide 

xposures in Children Living in Jacksonville, Florida (JAX) 

se Control and Prevention), DCHD (Duval County 

ealth Department) 

Stu 

ilot exposure measurement study 

• cide use in the residences 

r samples 

o Urine 

• Questionnaires: 

o Pesticide screening inventory 

o Time activity diary 

• Analytes: OP, pyrethroid pesticides, metabolites in urine 

Key Outputs:

• The CDC component of the study determined the distribution of urinary metabolite levels 

of organophosphate and pyrethroid pesticides in a group of 4-6 year old children living in 

the greater Jacksonville, Florida area 

• The DCHD component of the study evaluated the use of screening wipes and pesticide 

inventories to identify homes with potentially elevated pesticide levels and to identify 

potential household sources for pesticides 

• The EPA nine-home study was performed to evaluate methods for aggregate exposure 

measurements, to determine whether environmental measures of pesticide exposure are 

correlated with biological samples for a sub-sample of homes using pesticide inventories 

and screening measurements, to evaluate if information collected from pesticide 

screening inventories about pesticides used in the home correlates with environmental 

measures found in the same homes, and to evaluate pathways of exposure and the 

important factors that affect exposure 

E

Collaborators: CDC (Centers for Disea

H

dy Design:

• Type: Observational p

• Location: Jacksonville, Florida (Duval County) 

• Monitoring period: August to October 2001 

• Study population: Nine children 4-6 years of age 

Pesticide use: Participants report recent pesti

Monitoring Protocol: 

• Sampling times: One-time sample collection with 24-hour ai

• Samples collected: 

o Surface wipe 

o Indoor/outdoor air 

o Duplicate diet 

o Transferable residues 

o Cotton garments 

194
Center for the Health Assessment of Mothers and Children of Salinas Quantitative 

Exposure Assessment Study (CHAMACOS) 

ity of California at Berkeley 

Stu 

ment study 

: Twenty children ages 5 to 35 months old, 10 female, 10 male 

Mo o

• Sam i ur monitoring 

• Sam e

oor air 

ues from floors (surface wipes and press samples) 

rable residues from toys (surface wipes) 

ion suits and socks 

• Act t

e-activity diary 

eltamethrin (I, II), diazinon, dimethoate, 

Key O

$

$

$

$

Collaborator: Univers

dy Design: 

• Type: Observational pilot exposure measure

• Location: Salinas, California 

• Monitoring period: June 2002 to October 2002 

• Study population

• Pesticide use: Incidental for farmworker children 

nit ring Protocol: 

pl ng times: 24-ho

pl s collected: 

o Indoor and outd

o House dust 

o Transferable resid

o Transfe

o Cotton un

o Urine 

ivi ies 

o Videotaping 

o Tim

• Analytes: acephate, azinphos methyl, bifenthrin, chlorpyrifos, chlorpyrifos oxon, cisallethrin, trans-allethrin, cis-permethrin, trans-permethrin, cyfluthrin (I, II, III, IV), 

cypermethrin ( I, II, II, IV), dacthal, d

esfenvalerate, fonofos, iprodione, lambda-cyhalothrin, malathion, methidathion, naled, 

p,p’-DDE, p,p’-DDT, phosmet, resmethrin, sumithrin, tetramethrin (I, II), vincloziline 

utputs: 

Evaluation of methods for aggregate exposure measurements 

Pesticide distributions in microenvironments where children spend time 

Transfer of pesticides from microenvironmental media to child and factors that affect 

transfer 

Evaluation of pathways of exposure and important factors that affect exposure 

195
Children’s Pesticide Post-Application Exposure Study (CPPAES) 

ollaborator: EOHSI (Environmental and Occupational Health Sciences Institute) 

• Type: Observational pilot exposure measurement study 

• Monitoring period: April 1999 to March 2001 

pulation: 10 homes; children 2-5 years of age 

os was applied by a professional 

Mo o

ation 

ling days: indoor air, deposition coupons, surface samples (LWW), toys, 

e rate, time activity diary 

y 2 samples - surface wipes, hand wipes, dermal wipes, cotton 

• Analyte: Chlorpyrifos, TCPy in urine 

Key Outpu

• Pes d ldren spend time 

• Tra e onmental media to child and factors that affect 

tran r

 of pathways of exposure 

• Eva tors that affect exposure 

C

Study Design: 

• Location: Urban New Jersey 

• Study po

• Pesticide use: Crack and crevice application of chlorpyrif

applicator in these homes 

nit ring Protocol: 

• Sampling times: 1 day prior to application, 1, 2, 3, 5, 7, 9, and 11 days after applic

• Samples collected: 

o All samp

hand wipes, urine, air exchang

o Additional da

garments, videotaping 

t: 

tici es distributions in microenvironments where chi

nsf r of pesticide from microenvir

sfe 

• Evaluation

luation of important fac

196
The Distribution of Chlorpyrifos Following a Crack and Crevice Type Application in the 

S EPA Indoor Air Quality Research Test House (Test House) 

ollaborator: National Risk Management Research Laboratory 

Stu 

r Air Quality Research Test House) 

• , EC formulation, crack and crevice application in kitchen area 

try) 

Mo o

re, 1, 3, 7, 14 and 21 days post application 

• Sam e

o

o d kitchen) 

r bedroom) 

10-min C18 surface press (den carpet and kitchen vinyl floor), wipes (kitchen 

Key O

• Temporal and spatial variability over sampling period 

U

C

dy Design:

• Type: Field laboratory (Indoo

• Location: Cary, NC 

• Monitoring period: 3 weeks during November 2000 

• Study population: Single residential house; no occupants in the test house 

Pesticide use: Chlorpyrifos

(floor and cabine

nit ring Protocol: 

• Sampling intervals: P

pl types: 

Application formulation concentration 

o Air (kitchen, den and master bedroom) 

PUF-skin roller (den an

o Carpet sections (den and maste

o

floor and counter) 

• Analyte: Chlorpyrifos 

utputs:

• Translocation and exposure pathways

• Inputs to algorithms and SHEDS 

197
A Pilot Study Examining Translocation Pathways Following a Granular Application of 

Diazinon to Residential Lawns (PET) 

Collaborators: None 

Study Design: 

pilot exposure measurement study residential homes 

• wner applied diazinon, granular formulation, residential lawns (turf) 

o

echnician and child) 

lt and child) 

o Videography (15-min) 

Key Outputs:

• Methods evaluation 

• Translocation and exposure pathways 

• Decay rates over sampling period 

• Inputs to algorithms and SHEDS 

• Preceded by a 1-home feasibility study 

• Type: Observational 

• Location: 50 mile radius of Durham, NC 

• Monitoring period: Ten days in Spring 2001 

• Study population: 6 homes, 1 child and care giver (typically mother) 

Pesticide use: Homeo

Monitoring Protocol: 

• Sampling intervals: Pre, 1, 2, 4 and 8 days post application 

• Sample types: 

o Application formulation concentration 

o Air (living room and child’s bedroom) 

o PUF roller (lawn and indoor floor) 

o Soil 

o Entryway doormat 

HVS3 

o Cotton gloves (t

o Urine (adu

o Dog fur clippings 

o Dog paw wipes 

o Dog blood 

198
Dietary Intake of Young Children (DIYC) 

Collaborator: RTI 

tudy Design: 

servational pilot exposure measurement study 

ears old 

by homeowner - commercial crack and 

Mo o

 Pre-application to 8 days post-application (7 visits total) 

nd outdoor air 

ce press 

ess 

• Ana e

Key Outpu

• Eva ds to measure excess dietary exposures that occur from activities by 

you 

’s dietary intake model accurately represents total dietary exposures of children 

e closest to measured results with the highest measured 

ty parameters within model are needed 

es for highly exposed vs. less exposed are needed 

S

• Type: Ob

• Location: Raleigh, NC area 

• Monitoring period: November 1999 to January 2000 

• Study population: 3 homes; children 1-3 y

• Pesticide use: Diazinon applications reported 

crevice (2 homes) or applied by resident (1 home) 

nit ring Protocol: 

• Sampling times:

• Samples collected: 

o Indoor a

o Surface wipes (isopropanol) 

o Entry wipe 

o PUF roller 

o Surfa

o Hand wipes 

o Food pr

o Food samples 

o Urine 

lyt : Diazinon 

ts: 

luation of metho

ng children during eating 

• Children

• Model predictions ar

environmental diazinon concentrations

• Refinements for transfer and activi

• Categories of transfers and activiti

199
Characterizing Pesticide Residue Transfer Efficiencies (Transfer) 

lle 

rs that affect residue transfer from surface-to-skin, skin-to-

$

de residues 

$ Con c nts varying parameters in a systematic fashion 

• Hand Contact Trials 

lly varied six parameters 

tacts with contaminated surface 

• Tra e

n surface 

g solution 

eters 

Key

Collaborator: Batte

Study Design:

$ Type: Controlled laboratory study 

$ Objective: Evaluate paramete

other objects, skin-to-mouth, and object-to-mouth 

$ Monitoring period: not applicable 

$ Study population: not applicable 

 Pesticide use: Nontoxic fluorescent tracers used as surrogates for pesticides 

Monitoring Protocol: 

$ Conduct study using nontoxic fluorescent tracers as a surrogate for pestici

$ Apply fluorescent tracer as a residue at levels typical of residential pesticide applications 

to s a urf ces of interest 

du t controlled transfer experime

o Systematica

o Repetitive con

nsf r off skin 

o Hand to clea

o Hand to washin

o Hand to mouth 

• Mouthing Trials 

o Varied 5 param

o Simulated mouthing using saliva moistened PUF 

o Measured mass of tracer transferred and estimated contact surface area using 

video imaging techniques 

$ Conduct laboratory evaluations to relate transfer of tracer to transfer of pesticides 

 Outputs: 

• Transfer efficiency data 

• Information on type of microactivity data needed to estimate dermal exposure 

• Inputs for multipathway exposure models

200
Feasibility of Macroactivity Approach to Assess Dermal Exposure (Daycare) 

 measurement study 

$ sion 

ers at daycare centers 

and crevice applications as contracted by the daycare 

hly 

• ct screening sampling to evaluate the distribution of transferable 

r intensive measurements 

• Chi e d to wear full-body cotton bodysuits for 

sho i

ampling and videotaping of activities simultaneously with dermal 

load g

• Cal a nts 

Key Outpu

tions in nine daycare centers 

$ Ver ng aggregate surface measurement 

$ Ver

$ Der l

used in

Collaborator: RTI 

Study Design: 

$ Type: Observational pilot exposure

$ Location: North Carolina 

Monitoring period: Three occasions, twice per occa

$ Study population: Infants and toddl

$ Pesticide use: Professional crack 

center 

Monitoring Protocol: 

• Identify up to 9 daycare centers with previously established contracts for routine mont

pesticide applications 

In each daycare, condu

pesticide residue on floor surfaces in the area where children spend the most time 

• Select one daycare fo

ldr n from different age groups volunteere

rt t me periods 

• Conduct surface s

in sampling 

cul te dermal transfer coefficie

ts:

$ Pesticide distribu

ified protocol for collecti

ified protocol for collecting transfer coefficients 

ma transfer coefficients developed with children (to evaluate default assumptions

 OPP’s SOPs) 

201
202

ti 

ces 

glove 

 constant temperature and humidity 

ing surface wipes (isopropanol moistened gauze pads), which were 

•

) content measured with a Denver Instrument IRoisture meter 

d from each food's Nutrition Facts label; 

 measured for three different 

ot Colors® (Betty Crocker®), thinly sliced bologna (made with 

chicken & pork), and Red Delicious apple slices 

• Transfer Efficiency (TE): TE is defined as the amount of pesticide recovered from the 

food item divided by the pesticide concentration or loading level 

• Analytes: Malathion, Chlorpyrifos, Fipronil, Permethrin, Cyfluthrin, Cypermethrin, 

Deltamethrin 

Key Outputs: 

• Determine the extent of pesticide transfer from household surfaces to foods 

• Evaluate factors that have been identified as important, including surface type, duration 

of contact, surface loading, and contact pressure (applied force or weight per area) 

• Compared surface wipes using cotton gauze pads with the pesticide transfer to the foods 

Food Transfer Studies, also known as Press Evaluation Studies (Food) 

Collaborator: RTI 

Study Design: 

• Type: Controlled laboratory study 

• Location: NERL Cincinna

• Study period: Not applicable 

• Study population: Not applicable 

• Pesticide use: Organophosphate, pyrethroid, and pyrazole insecticides on various 

household surfa

Monitoring Protocol: 

• Surfaces: 

o Surface Treatment: A customized spray chamber was used to spray Pesticide 

Spray Solution (PSS) onto the ceramic tiles 

o Surface Drying: Following spraying, each ceramic tile was transferred to a 

box where it was air dried for an hour at

o Surface Wipes: Pesticide transfer to foods were compared to the pesticides 

removed us

wiped across the ceramic tile in both the horizontal and vertical direction 

Food Items: 

o Moisture Content: Moisture (%

30 m

o Fat Content: Fate (%) content determine

% fat = [total fat (g) / food serving size (g)] *100 

o Food Items: Pesticide transfer efficiencies were

foods, with standardized surface contact area; the foods were Fruit Roll-Ups 

Blastin' Berry H
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