UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

WASHINGTON, D.C. 20460 

 OFFICE OF CHEMICAL SAFETY 

 AND POLLUTION PREVENTION 

 

 

Date: October 4, 2010

MEMORANDUM

SUBJECT: Science Review of the AEATF II Mop Human Exposure Monitoring Study. 

MRID Numbers 48210201, 48231201, and 48231901 

 

FROM: Tim Leighton, Environmental Scientist 

 Antimicrobials Division 

TO: Nader Elkassabany, PhD, Chief 

 Risk Assessment and Science Support Branch 

 Antimicrobials Division 

This memorandum presents the EPA/OPP Antimicrobials Division (AD) science review of the 

human exposure mop study submitted by the Antimicrobial Exposure Assessment Task Force II 

(AEATF II). The dermal and inhalation exposure data as represented in this review are 

acceptable and, subject to the considerations described below, are recommended for use for 

pesticide handler exposure assessments. 

Page 1 of 25 
EXECUTIVE SUMMARY

This document represents the USEPA, Office of Pesticides Program, Antimicrobials Division 

(AD) review of the Antimicrobial Exposure Assessment Task Force II (AEATF II) mop study. 

The mop study investigators monitored inhalation and dermal exposures to 18 workers mopping 

floors using a mop and bucket. EPA confirms that the data meet the study design objective 

outlined in the AEATF II Governing Document and are considered the most reliable data for 

assessing exposures from mopping floors. The reader is referred to Section 3.0 for a discussion 

on the data limitations and generalizability. 

EPA intends to use this AEATF II mop dataset instead of the Chemical Manufacturers 

Association (CMA) dataset to assess exposure for persons using an antimicrobial product while 

mopping floors. The exposure data in the AEATF II mop scenario represent mopping only. The 

scenario does not cover the pouring of the concentrate into the mop bucket; open pouring of the 

concentrate will be measured in a future study. If pesticide products are used with open pouring 

of concentrates (rather than as ready-to-use mops or with automatic dispensers), estimates of 

dermal and inhalation exposures from the future pour study will be combined with mop 

exposures from this study when assessing exposures and risks from pesticide products applied by 

mopping. 

Select summary statistics for the “unit exposures” normalized to pounds active ingredient 

handled are presented in Table 1 for inhalation exposure as well as for 3 clothing configurations. 

Each worker wore both inner and outer whole body dosimeters (WBD) that were sectioned and 

analyzed separately for each body part (e.g., lower leg, upper leg, lower arm, upper arm, etc). 

Therefore, the analyses of residues on the dosimeters worn by each individual worker allow for 

the estimation of exposure for the following 3 clothing configurations: 

 

(1) long pants, long-sleeved shirt, shoes/socks, and no gloves; 

(2) long pants, short-sleeved shirt, shoes/socks, and no gloves; and 

(3) short pants, short-sleeved shirt, shoes/socks, and no gloves. 

For comparison, results from the earlier CMA study for mopping are also presented. The 

summary statistics reported in Table 1 for the AEATF II data are estimated using the lognormal 

mixed model while the CMA results are empirical estimates. 

Page 2 of 25 
Table 1. Unit Exposures: Mopping Scenario 

CMAa AEATF IIb, c Exposure (n=18) 

Route Clothing Arithmetic Mean Arithmetic Meand 95th Percentilee

Long pants/long-sleeves, 

shoes/socks, no gloves 

23.2 

(17.4, 31.4) 

50.8 

(33.3, 77.3) 

Long pants/short-sleeves, 

shoes/socks, no gloves 

71.6 ± 129 

(n=6) 

(workers short-sleeves 

and long-sleeves) 

26.3 

(20.3, 34.6) 

54.7 

(37.2, 80.3) 

Dermal 

(mg/lb ai) 

Short pants/short-sleeves, 

shoes/socks, no gloves Not available 82.1 (55.1, 125.5) 

215 

(124, 373) 

Inhalation 

(μg/m3/lb ai) 

Breathing 

zone 

75.6 ± 87.4 

(n=8) 

(all non-detects) 

52.4 

(27.0, 105.7) 

130 

(54.8, 318) 

a

 CMA data: Mean ± std. Inhalation LOQ varied among samples. Task of mixing of product, mopping, and 

dumping mop bucket; janitors as subjects; observations of incidental contact (splash & contact with mop); and sites 

included hospital, university building, and office building. 

b

Dermal unit exposures reflect method removal efficiencies of 90.3% for hands and 58.8% for face/neck 

measurements. The percent of dermal exposure representing the hands is 93% for the long pants scenario and 38% 

for the short pants scenario. 

c

 Lower and upper 95% confidence intervals reported in “( )”; statistics are estimated using a variance component 

model accounting for correlation between measurements conducted within the same field study (i.e., measurements 

collected during the same time and at the same location). Additional model estimates (e.g., empirical and simple 

random sample assumptions) are described in Appendix A. 

d

 Arithmetic Mean (AM) = GM * exp{0.5*(lnGSD)2} e

 95th percentile = GM * GSD1.645

The following important points with respect to these data are noted: 

• The AEATF II data and associated unit exposures are considered superior to the existing 

mop dataset (i.e., CMA data). AEATF II efforts represented a well-designed, concerted 

process to collect reliable exposure data in a way that takes advantage of and incorporates 

a more robust statistical design, better analytical methods, and improved data handling 

techniques. 

• The report containing dermal and inhalation exposure results is considered scientifically 

complete. No additional monitoring data are required at this time. 

• The data are applicable for assessment of exposure to non-volatile pesticides. The cutoff 

for volatility is reviewed on a case-by-case basis (generally <1E-4 mmHg @ 20° C is 

considered non-volatile). 

• Statistical analysis provides support for proportionality between dermal exposure and 

pounds of active ingredient (ai) handled as described in Section 2.4 below. However, the 

statistical analysis suggests that the inhalation exposure is independent of the amount of 

pesticide usage. 

To assess the risks resulting from mopping exposures, EPA will combine appropriate unit 

exposure (UE) values with chemical-specific inputs (maximum labeled application rates, dermal 

absorption rates, and toxicological endpoints of concern) and default inputs (high end area 

treated or volume applied) in the standard pesticide handler exposure algorithm (i.e., potential 

Page 3 of 25 
exposure = UE (mg/lb ai or μg/m3

/lb ai) x absorption (%) if applicable x maximum label rate (lb 

ai/gallon) x volume (gallons)). 

1.0 Background 

The AEATF II is developing a database representing inhalation and dermal exposure during a 

number of antimicrobial handler scenarios. A scenario is defined as a pesticide handling task 

based on activity (e.g., application) and equipment type (e.g., mop & bucket, ready-to-use wipes, 

pressure treatment of wood facilities, painting). The AEATF II is monitoring both inner and 

outer dosimeters which will allow the EPA to estimate exposures to various clothing 

configurations (e.g., long pants, long-sleeved shirt or long pants, short-sleeved shirt or short 

pants, short-sleeved shirts, plus shoes, socks, and no gloves). 

1.1 Mop Scenario Defined 

The “scenario” in this study is defined as mopping floors and emptying each mop bucket while 

wearing long-sleeved shirts, long pants, shoes, socks, and no gloves. The conditions under 

which the study participants handle the pesticide as they are monitored are referred to as the 

scenario. Both inner and outer dosimeters were worn by the monitored study participants, and 

both inner and outer dosimeters were analyzed for residues. This scenario is defined to exclude 

pouring the antimicrobial product into the mop bucket. Antimicrobial products may be added to 

mop buckets in various ways, including open pouring from no-glug containers, open pouring 

from typical glug containers, or automated dispensers; some mop systems are ready-to-use and 

require no pouring of the concentrated product. Open pouring a pesticide concentrate will be 

monitored in a future AEATF II study.

1.2 Study Objective 

The study objective is to monitor inhalation and dermal exposures to be used as inputs in 

exposure algorithms to predict future exposures to persons mopping floors. Dermal and 

inhalation exposure monitoring was conducted while study participants mopped floors and 

emptied the mop buckets; results are expressed, for use in exposure assessments, as “unit 

exposures”. 

“Unit exposure” (UE) is defined as the expected external chemical exposure an individual may 

receive (i.e., "to-the-skin" or “in the breathing zone”) per weight-unit of chemical handled and is 

the default data format used in pesticide handler exposure assessments. Mathematically, unit 

exposures are expressed as "handler" exposure normalized by the amount active ingredient 

handled by participants in scenario-specific exposure studies (e.g., mg exposure/lb ai handled). 

EPA uses these UEs generically to estimate exposure for other chemicals having the same or 

different application rates. 

Criteria for determining when a scenario is considered complete and operative have been 

developed (Myrta 2007). Outlined in the AEATF II Governing Document, the criteria can be 

briefly summarized as follows: 

Page 4 of 25 
• The primary objective of the study design is to be 95% confident that key statistics of 

normalized dermal exposure are accurate within 3-fold. Specifically, the upper and lower 

95% confidence limits should be no more than 3-fold (K=3) higher or lower than the 

estimates for each the geometric mean, arithmetic mean, and 95th percentile dermal unit 

exposures. To meet this primary objective AEATF II proposed an experimental design 

with a 3 cluster by 6 monitoring events (MEs). 

• A secondary objective is to evaluate the presumption of proportionality between exposure 

and amount of active ingredient handled. To meet this secondary objective, AD used the 

same statistical tests as that being proposed by the AHETF and HED. They proposed a 

log-log regression test to distinguish complete proportionality (slope = 1) from complete 

independence (slope = 0), with 80% statistical power, achieved when the width of the 

95th confidence interval of the regression slope is 1.4 or less (Sarkar 2010). 

1.3 Protocol Modifications, Amendments, and Deviations 

1.3.1 Protocol Modifications Subsequent to EPA/HSRB Review 

EPA required two science-based modifications to the protocol (EPA 2008). EPA indicated that 

the scope of the monitoring event (ME) needed to be revised to include the monitoring of the 

workers disposing of the spent mop bucket solution. The AEATF II responded by including the 

typical disposal events as part of the ME (i.e., pouring the spent solution from the bucket into a 

sink as the worker would normally do). EPA also required a residue removal efficiency study to 

address the efficiency of the hand wash and face/neck wipes. The AEATF II responded by 

purchasing an existing study conducted to assess the removal efficiency (Boatwright 2007, 

MRID 47214801). 

The HSRB provided written discussion on a number of concerns including: 

• Sampling size and replication of ME – The HSRB questioned whether or not the 

sampling size of 3 clusters by 6 MEs per cluster would provide an accuracy goal of k=3. 

Based on EPA’s statistical review provided in Section 2.4 below, the sampling size as 

designed is sufficient to meet the accuracy goal. The HSRB also discussed the need for 

repeat measurements or in lieu of repeat measurements the need for a discussion on the 

limitations of the study design. EPA acknowledges that ideally, the sample design would 

benefit from a large sample size that includes multiple replicates from each worker. 

However, EPA also recognizes that the repeat measures is as a trade-off for overall 

sample size (resource issue). Sampling the same worker twice (or 3X, 4X....) would have 

provided information on the within-worker variability (e.g., do some workers consistently 

experience high or low exposures day-after-day while others are highly variable?). Such 

information would be useful, especially because worker assessments generally represent 

longitudinal (multi-day) exposures. But any gain in characterization of within-worker 

variability information would result in a loss in characterization of between-worker 

variability and, given a fixed sample size, in accuracy (the fold relative accuracy or "K" 

factor as discussed in the AEATF II Governing Document). With respect to the K-factor, 

because of the inherent correlation, sampling workers multiple times reduces "effective" 

Page 5 of 25 
sample size - which, due to the relationship between sample size, variability, and 

accuracy -- would have made the K-factor unacceptably larger. Thus, if EPA wanted 

both within-worker variability information and a K=3, the AEATF II would need to 

increase the total number of workers monitored not only in this study but for the other 

planned scenarios as well. Thus, the trade-off becomes the number of pesticide exposure 

scenarios that could be monitored by the AEATF II. 

Alternatively, EPA could have accepted a larger K-factor if within-worker variability was 

more desirable. Instead, because assumptions can be made for within-worker variability 

in order to model longitudinal exposures from the collected 1-day exposures, EPA elects 

to continue to utilize the 3-fold K factor as its accuracy benchmark In summary, given 

the fixed sample size, EPA has chosen the larger "effective" sample size/smaller K-factor 

and between-worker variability, while sacrificing more concrete information on withinworker variability. 

• ME duration – The HSRB noted that the durations of the MEs should be longer. The 

AEATF II responded with the following, which was discussed and accepted by the JRC: 

“...information from the following sources: 1) the American Hospital Association 

(http://www.aha.org/aha_app/index.jsp), the American Society for Health Care 

Environmental Services (http://www.ashes.org/ashes_app/index.jsp), and the U.S. EPA’s 

Environmental Best Practices for Health Care Facilities (JCAHO Environment of Care 

Standards 1.3,2.3,4.0, November 2005) indicates that a single individual at a hospital 

would typically clean from 15 to 20 hospital patient rooms per day during a standard 6.5 

hour shift. In addition to hospitals, application of antimicrobials by mopping is also 

likely at medical and dental offices and specialty lodging facilities. In these settings 

JohnsonDiversey Inc. feels that the lower typical range could be less than 15 rooms per 

day. Consequently, depending on the degree of conservatism desired, 20-25 rooms/day 

would appear to be a reasonable upper bound for these professional applicators. Thus, 

using the above estimate of 3.3 minutes/room, the total amount of mopping time required 

for these 20-25 rooms would be about 66-83 minutes per workday. This result is also 

consistent with the maximum duration of 66 minutes found by Popendorf et al. (1992). 

Rounding the upper value of 83 minutes to the nearest half-hour suggests that about 90 

minutes of mopping per workday is a reasonable maximum duration to use in the AEATF 

II mopping study.” 

 

• Amount active ingredient handled (AaiH) – The HSRB noted that the AaiH instead of 

exposure duration should be used to differentiate among MEs. Other protocols (e.g., 

aerosol can spraying) have been modified to use the amount handled instead of exposure 

duration to differentiate among MEs. However, for the mop study, the information above 

on mopping duration was determined by the JRC to be the best information available on 

the task of mopping. Individual workers were given the ability to choose to use the 

appropriate amount of mop diluted treatment solution and mop as they would normally 

do. 

• Proportionality between exposure and AaiH – The HSRB indicated in their written 

protocol review comments that they wanted to see a discussion of proportionality and 

Page 6 of 25 
regressions with the completed data. EPA reviewed the data and presents the analysis of 

proportionality in Section 2.4 below and Appendix A. In brief, the statistical analysis 

compared pounds of active ingredient as the normalization variable. [Note: To be 

thorough, alternative analyses were also performed using other normalization variables 

of exposure duration and number of mop buckets used and these results are also 

presented in Appendix A but are not summarized within this review.] Results indicate 

that the preferred normalization method is by pounds active ingredient for the dermal 

exposure and that these exposures can be assumed to be proportional to pounds active 

ingredient. Inhalation exposure cannot be assumed to be proportional to the pounds active 

ingredient. 

• Monitoring equipment – The HSRB indicated that they wanted to see better descriptions 

of the equipment used to measure light levels, air temperature, and relative humidity. 

Better descriptions of these monitoring devices within the protocol are not apparent. 

However, the environmental conditions (e.g., temperature & humidity) do not appear to 

have been a factor that would have hampered the workers in their performance of their 

mopping activities. 

1.3.2 Protocol Amendments 

The study report (page 92) lists 7 protocol amendments. The amendments range from changing 

the building selection criteria to improving efficiency of the conduct of the study. The building 

selection criteria were updated based on EPA requirement of including the dumping of spent 

mop solution. A criterion was added to include that the building must have “...janitorial sinks 

or floor drains suitable for disposing of used mopping solutions...” (page 378 of study report). 

1.3.3 Protocol Deviations 

The majority of the deviations were due to the air sampling. For a detailed description of the 

protocol deviations the reader is referred to pages 92 to 94 in the study report. These deviations 

did not adversely affect the outcome of the study. 

1.4 Material & Methods 

The following is a summary of the field aspects of the study: 

• Study Location: The mop study was conducted in Fresno County, CA. Pictures and 

floor plans of clusters 1, 2, and 3 are provided in Appendix H, I, and J on study report 

pages 257, 260, and 263, respectively. Each cluster is a different building. The 

buildings are an office building, a Rite Aid, and a retired teacher’s memorial building. 

• Pesticide Tested: The test substance monitored was didecyl dimethyl ammonium 

chloride (DDAC), CAS number 7173-51-5. DDAC was formulated in a product known 

as Buckeye Sanicare Lemon Quat (EPA Reg No. 47371-131-559). This product also 

contained another Quat, ADBAC. DDAC and ADBAC are in Lemon Quat at 2.54% and 

1.69%, respectively. 

Page 7 of 25 
• Test System: The mop and bucket configuration used in the study and presented in 

Figure 1 is a string mop and open bucket with a wringer to wring the mop. The mop 

bucket is a 35 Quart Splash Guard Down-Press Combo Pack (product No. 335-37YW) 

manufactured by Continental Manufacturing Company and the mop head is a Bulldog 

Blend Loop, Narrow Band, Large string mop (product Nos. A05013 by Wilen and 

151032 by Buckeye). 

Figure 1: Mop and Bucket Equipment Used in Study. 

• Sequence of Events: A table listing the chronological order of key events for the study 

(e.g., test site selection, IIRB approval, subject recruitment, start of each monitoring 

events, etc) is reported on page 100 of the study report. A second listing of the sequence 

of events is provided on pages 161 - 162 of the supplemental #1 report. Each list reports 

different set of details such that both need to be reviewed for a full accounting of the 

sequence. 

• Sample Size: The study consisted of 3 clusters and 6 MEs per cluster for a total of 18 

MEs. 

Page 8 of 25 
• Tank Mix Solution: The diluted treatment solution of Lemon Quat was prepared by the 

researchers in a 50 gallon tank. The preparation of the treatment solution was not part of 

the monitoring events. The 2.54% DDAC in concentrated solution was diluted 1:64 

(0.0397% DDAC) in cluster 1 and 1:63 (0.0403% DDAC) in clusters 2 and 3. 

• Duration & AaiH: For each of the 3 clusters, the MEs were randomly assigned to 1 of 

the 6 purposively selected mopping times. The pre-determined mopping times were: 

o 30 to <40 minutes 

o 40 to <50 minutes 

o 50 to <60 minutes 

o 60 to <70 minutes 

o 70 to <80 minutes 

o 80 to <90 minutes 

Actual mopping duration for each ME is reported in Table 2 below. The amount of 

DDAC handled by the 18 MEs ranged from 0.00308 to 0.0183 lbs ai with a mean of 

0.00634 ± 0.00328 lb ai. The 18 MEs used varying numbers of mop bucket refills/dumps 

ranging from 2 to 6 buckets per ME. The amount ai per ME is the amount actually 

mopped onto the floor, determined by weighing the bucket before and after mopping. 

These data are also reported in Table 2 below. Because the workers were instructed to 

work as they normally would do, the number of buckets and amount of active ingredient 

handled did not correlate to the monitoring duration. Some workers used more buckets 

of mop solution than others. For example, in cluster 1 subject number ID M6 mopped for 

45 minutes and used 6 buckets (0.00669 lb ai) while M27 worked for 85 minutes yet only 

used 2 buckets (0.00419 lb ai). 

• Mopping procedures: Appendix K on page 266 of the study report records the 

observation notes taken during each ME. The workers were instructed to mop “as they 

would normally do”. Typical mopping procedures/observations were that the workers 

mopped either in a side-to-side motion or figure 8 and walked backwards as they 

mopped. Mop heads were wrung at varying times as the study participant would 

normally do. 

• Environmental Conditions: Environmental conditions (humidity and temperature) are 

reported for the MEs on pages 105 to 107 of the study report (note: humidity readings 

not available for 5 MEs in cluster 3). The humidity averaged in the 40% range. 

Temperatures averaged in the low 70o F range. The heating ventilation air conditioning 

(HVAC) system descriptions for clusters 1 and 3 are reported on page 108 of study report 

(not available for cluster 2). Cluster 1 reports the only air changes per hour (ACH), 

which is 8.1 ACH. It is unclear how the ACH was measured and if it represented ACH 

of outside make-up air or re-circulating air. However, based on the low vapor pressure of 

DDAC and expected minimal aerosol generation, the ACH is not a significant factor for 

this scenario (all air samples measured residues above the limit of quantification (LOQ)). 

Lighting levels were not measured. 

Page 9 of 25 
2.0 Results 

2.1 QA/QC Recovery Results 

Controls: The non-fortified field and laboratory control samples were all less than the limit of 

quantification (LOQ). The LOQs for the various matrices are air sampling tubes 10 ng/sample, 

neck/face wipe 50 ng/sample, WBD sections 3 μg/sample, socks 1 μg/sample, and hand wash 1 

μg/sample. 

Laboratory Recoveries: Most of the individual laboratory fortified recovery values range within 

70 to 120 percent. Exceptions include a few outside of the 120 percent upper bound, none below 

70 percent. A summary of the overall concurrent laboratory recovery samples for each 

monitoring matrix by cluster is reported on page 94 of the study report. The mean recoveries in 

cluster 1 for all matrices range from 101 ± 4 to 113 ± 3; cluster 2 ranged from 100 ± 5 to 110 ± 9; 

and cluster 3 ranged from 95 ± 4 to 107 ± 7. 

Field Recoveries: Most of the individual field fortified recovery values range within 70 to 120 

percent. Exceptions include a few outside of the 120 percent upper bound, none below 70 

percent. A summary of the overall field fortified recovery samples for each monitoring matrix 

by cluster is reported on page 95 of the study report. The mean recoveries in cluster 1 for all 

matrices range from 91 ± 8 to 108 ± 22; cluster 2 ranged from 91 ± 7 to 109 ± 8; and cluster 3 

ranged from 92 ± 11 to 102 ± 8. All exposure/field matrices were corrected for the field fortified 

recovery results. 

2.2 Calculating Unit Exposures 

Dermal Unit Exposure: Dermal exposure is measured using 100% cotton inner and outer 

“whole body dosimeters” (WBD). The inner WBDs were worn underneath normal work 

clothing (i.e., long-sleeved shirt, long pants, socks and shoes). The normal work clothing worn 

over the inner WBDs were also analyzed and reported as “outer” dosimeters. In addition, dermal 

exposures also included hand washes (collected at the end of the day and during breaks), 

face/neck wipes (also collected during the ME to wipe off sweat; see study report page 40), and 

inner and outer socks worn underneath shoes. The inner and outer WBDs are sectioned and 

analyzed by body part (i.e. upper and lower arms, front and rear torso, and upper and lower legs). 

The inner WBD sections were only analyzed if the corresponding outer dosimeter section tested 

above the LOQ. One-half the LOQ was substituted for all non detected samples. If the outer 

dosimeter was ND then the inner dosimeter for the same body section was also considered to be 

ND and 1⁄2 LOQ was substituted for those WBD sections as well. The study report for total 

dermal exposure substituted a single 1⁄2 LOQ value for multiple ND samples. EPA has 

recalculated the total dermal exposure substituting 1⁄2 LOQ for each of the ND WBD sections 

(resulting in a minimal impact on the results). All samples are adjusted as appropriate according 

to recovery results from field fortification samples. 

Dermal exposures to the hands and face/neck are also corrected for sampling efficiency (see 

study report pages 59 and 60). A removal efficiency study for hand washes and wipes was 

performed using the test substance, DDAC, in a previous study (Boatwright 2007, MRID 

Page 10 of 25 
47214801). The hand wash removal efficiency for DDAC is 90.3%. The same study also 

performed wipes. The wipe removal efficiency is calculated as 58.8% and is used to correct the 

face/neck samples. 

Total dermal exposure is calculated by summing exposure across all body parts for each 

individual monitored. The following WBD sections are summed to calculate the clothing 

configuration of long pants, long-sleeved shirts (plus inner socks, face/neck wash, and hand 

wash): 

• inner lower and inner upper arms, 

• inner front and inner rear torso, and 

• inner lower and inner upper legs. 

The following WBD sections are summed to calculate the clothing configuration of long pants, 

short-sleeved shirts (plus inner socks, face/neck wash, and hand wash): 

• outer and inner lower arm, 

• inner upper arm, 

• inner front and inner rear torso, and 

• inner lower and inner upper leg. 

The following WBD sections are summed to calculate the clothing configuration of short pants, 

short-sleeved shirts (plus inner socks, face/neck wash, and hand wash): 

• outer and inner lower arm, 

• inner upper arm, 

• inner front and inner rear torso, 

• inner upper leg, and 

• inner and outer lower leg. 

Dermal unit exposures (i.e., mg/lb ai handled) are calculated by dividing the summed total 

exposure by the amount of active ingredient handled. The AEATF II’s study report normalized 

the dermal exposures by milligrams (mg) of active ingredient applied. EPA recalculated the 

exposures and expressed the results as mg/lb ai applied. EPA prefers the normalization by 

pounds to coincide with the English units reported on pesticide labels (e.g., pounds, ounces). 

Inhalation Exposure: Inhalation exposure is measured using a personal air sampling pump and 

an OSHA Versatile Sampler (OVS) tubes. The tube is attached to the worker’s collar to 

continuously sample air from the breathing zone. The sampling pumps were run continuously, 

even during break. Collected residue, per standard practice, is adjusted for recovery from field 

fortification samples. 

Inhalation unit exposures (i.e., μg/m3

/lb ai handled) are calculated by dividing the air 

concentrations by the amount of ai handled. 

Page 11 of 25 
2.3 Dermal and Inhalation Exposure Results 

Results -- A summary of the 18 MEs and their dermal and inhalation UEs for the mop scenario 

are presented in Table 2 (long pants, long sleeved-shirts), Table 3 (long pants, short-sleeved 

shirts), and Table 4 (short pants, short-sleeved shirts). These tables report the results for each 

individual worker along with empirical statistical summaries of each cluster and overall 

exposures. The inhalation UEs are the same for each of the clothing configurations (i.e., the 

three clothing scenarios are from the same worker). Therefore, the inhalation exposures are only 

reported once (in Table 2). 

Appendix A provides alternative statistical models to estimate the exposure summary statistics, 

including: 

• Empirical simple random sampling model (see Appendix A Table 1); 

• Lognormal simple random sampling model (see Appendix A Tables 3 through 6); and 

• Lognormal mixed model (see Appendix A Table 2). 

The results of the lognormal mixed model have been selected to best represent the summary 

statistics for the unit exposures (as reported in Table 1 above). For a detailed discussion of the 

lognormal mixed model calculations and results the reader is referred to Appendix A. 

Observations -- This mop study includes the recording of individual participant activities by 

observers. Observations recorded during each ME are reported starting on page 266 of the study 

report and record the “real world” events during mopping as a worker would normally do. There 

is one aberrant dermal exposure recorded for subject number ID M6 in cluster 1. For M6, the 

outer dosimeter on the lower leg has a residue value of 3607 μg. The observer noted that for this 

worker the mop brushed the lower leg when exiting through a door and mop solution also 

splashed on knee when pushing the bucket over door threshold. This one value on M6’s outer 

lower leg impacts the summary statistics for the short pants clothing scenario. The empirical 

results with and without (outer lower leg set to 0) the lower legs are as follows for the short pants 

scenario: 

• Mean dermal exposure with the high lower leg residue value is 89.0 ± 120 versus 59.0 ± 

33.7 mg/lb ai without the high lower leg residue value for subject number ID M6. 

• 95th%tile dermal exposure with the high lower leg residue value is 189 versus 108 mg/lb 

ai without the high lower leg residue value for subject number ID M6. 

The JRC views incidental contact of the mop brushing against the leg within the norm of what 

may occur during mopping of floors. Therefore, the lower leg value is not treated as a statistical 

outlier and the JRC recommends using the dermal UE based on a data set which includes the 

lower leg value for subject number ID M6. 

Impact of Non-detects -- Minimal exposure inside of the clothing was expected for many of the 

body parts sampled for the mop pesticide application pesticide technique. Even with sensitive 

analytical methods for the surrogate compound, DDAC, many samples were non-detect (ND). 

Samples with results less than the limit of quantification (LOQ) are included in the calculation of 

Page 12 of 25 
Page 13 of 25 

total exposure as 1⁄2 LOQ. All of the hand and air samples were greater than the LOQ. For the 

face/neck wipe samples 2 of 18 samples were less than the LOQ. For the inner WBD 66 of 72 

sectioned body parts are less than the LOQ and 15 of the 18 inner socks were less than the LOQ. 

The impact of the ND samples for the short pants, short-sleeved shirt, shoes, socks, and no glove 

clothing configuration for the dermal UE is minimal. The following data presentation (empirical 

estimates) illustrate the change in the dermal UE values when NDs were substituted with 0, 1⁄2 

LOQ, and the full LOQ. 

Comparison of Dermal UE (mg/lb ai) for Non-detects Equal to 0, 1⁄2 LOQ, Full LOQ 

Statistic NDs = 0 NDs = 1⁄2 LOQ NDs = Full LOQ 

Mean 87 89 91 

95th%tile 188 189 191 

A similar analysis was not performed for the long pants, long-sleeved shirt or the long pants, 

short-sleeved shirt (plus shoes, socks, and no gloves) clothing configurations but the impact of 

the non-detects on these clothing configurations is expected to be minimal too. This expectation 

is based on the higher contribution of the hand exposure to total dermal exposure for the long 

pants, long-sleeved shirt clothing configuration. For the long pants, long-sleeved shirt 

configuration, 93 percent of the total dermal exposure is attributed to the hand exposure. In 

comparison, 38 percent of the total dermal exposure for the short pants, short-sleeved shirt 

scenario is attributed to the hands. 
Table 2. Summary (Empirical) of Dermal and Inhalation Results for Mop -- Long Pants, Long-sleeved Shirt, Shoes/socks, a

U

Cluster Subject 

Order 

Subject 

Number 

ID 

Task 

Duration 

(minutes) 

Surface 

Area 

(sq ft) 

Number Buckets 

Pounds ai 

Handled 

Dermal 

Exposure 

(μg) 

Inhalation

Exposure 

(μg/m3) 

Dermal 

(mg/lb ai

MW-01 M13 31 3324 3 0.00308 40.7 0.413 13.2 MW-02 M6 45 4996 6 0.00669 42.8 0.334 6.4 MW-03 M12 59 5050 3 0.00584 136.3 0.333 23.3 MW-04 M28 67 4189 4 0.00538 289.4 0.209 53.7 MW-05 M15 53 1884 5 0.00556 191.8 0.437 34.5 MW-06 M27 85 5155 2 0.00419 75.7 0.292 18.1 

Mean 57 4100 4 0.00513 129 0.336 24.9 

1 

Std 19 1291 1 0.00129 98 0.083 17.0 

MW-07 M8 38 5884 6 0.00556226 66.9 0.123 12.0 MW-08 M24 51 4390 5 0.01833364 154.3 0.107 8.4 MW-09 M2 63 8295 5 0.00406091 66.9 0.108 16.5 MW-10 M4 69 4952 4 0.0061509 162.7 0.242 26.5 MW-11 M10 79 14191 4 0.00546085 112.3 0.216 20.6 MW-12 M21 90 6688 3 0.00482371 134.3 0.128 27.8 

Mean 65 7400 5 0.00740 116 0.154 18.6 

2 

Std 19 3599 1 0.00540 42 0.0592 7.8 

MW-13 M7 38 4008 6 0.00838418 288.3 0.273 34.4 MW-14 M18 49 4989 6 0.00703495 116.5 0.391 16.6 MW-15 M26 59 5425 5 0.00740312 365.2 0.431 49.3 MW-16 M14 69 4339 4 0.00699086 70.3 0.257 10.1 MW-17 M20 79 5362 4 0.00528448 79.2 0.249 15.0 MW-18 M1 89 6161 3 0.00392864 95.9 0.195 24.4 

Mean 64 5047 5 0.00650 169 0.299 25.0 

3 

Std 19 783 1 0.00161 125 0.091 14.7 

Mean 62 5516 4 0.00634 138 0.263 22.8 

Std 18 2553 1 0.00328 92 0.110 13.3 

Median 61 5023 4 0.00556 114 0.253 19.3 

Geo 

Mean 59 5094 4 0.00585 114 0.239 19.5 

Overall 

95th%tile 89 9179 6 0.00988 301 0.432 50.0 

Page 14 of 25 
Table 3. Summary (Empirical) of Dermal Results for Mop -- Long Pants, Short-sleeved shirt, Shoes/socks, and N

Cluster Subject 

Order 

Subject 

Number ID 

Task Duration 

(minutes) 

Surface Area 

(sq ft) 

Number 

Buckets Pounds ai Handled 

MW-01 M13 31 3324 3 0.00308 MW-02 M6 45 4996 6 0.00669 MW-03 M12 59 5050 3 0.00584 MW-04 M28 67 4189 4 0.00538 MW-05 M15 53 1884 5 0.00556 MW-06 M27 85 5155 2 0.00419 

Mean 57 4100 4 0.00513 

1 

Std 19 1291 1 0.00129 

MW-07 M8 38 5884 6 0.00556 MW-08 M24 51 4390 5 0.01833 MW-09 M2 63 8295 5 0.00406 MW-10 M4 69 4952 4 0.00615 MW-11 M10 79 14191 4 0.00546 MW-12 M21 90 6688 3 0.00482 

Mean 65 7400 5 0.00740 

2 

Std 19 3599 1 0.00540 

MW-13 M7 38 4008 6 0.00838 MW-14 M18 49 4989 6 0.00703 MW-15 M26 59 5425 5 0.00740 MW-16 M14 69 4339 4 0.00699 MW-17 M20 79 5362 4 0.00528 MW-18 M1 89 6161 3 0.00393 

Mean 64 5047 5 0.00650 

3 

Std 19 783 1 0.00161 

Mean 62 5516 4 0.00634 

Std 18 2553 1 0.00328 

Median 61 5023 4 0.00556 

Geo Mean 59 5094 4 0.00585 

Overall 

95th%tile 89 9179 6 0.00988 

Page 15 of 25 
Page 16 of 25 

Table 4. Summary (Empirical) of Dermal Results for Mop -- Short Pants, Short-sleeved shirt, Shoes/socks, and 

Cluster Subject 

Order 

Subject 

Number 

ID 

Task 

Duration 

(minutes) 

Surface 

Area 

(sq ft) 

Number 

Buckets Pounds ai Handled 

Dermal 

Exposure 

(μg) 

MW-01 M13 31 3324 3 0.00308 82 MW-02 M6 45 4996 6 0.00669 3690 MW-03 M12 59 5050 3 0.00584 569 MW-04 M28 67 4189 4 0.00538 565 MW-05 M15 53 1884 5 0.00556 253 MW-06 M27 85 5155 2 0.00419 103 

Mean 57 4100 4 0.00513 877 

1 

Std 19 1291 1 0.00129 1395 

MW-07 M8 38 5884 6 0.00556 698 MW-08 M24 51 4390 5 0.01833 493 MW-09 M2 63 8295 5 0.00406 227 MW-10 M4 69 4952 4 0.00615 232 MW-11 M10 79 14191 4 0.00546 400 MW-12 M21 90 6688 3 0.00482 198 

Mean 65 7400 5 0.00740 375 

2 

Std 19 3599 1 0.00540 196 

MW-13 M7 38 4008 6 0.00838 789 MW-14 M18 49 4989 6 0.00703 440 MW-15 M26 59 5425 5 0.00740 505 MW-16 M14 69 4339 4 0.00699 245 MW-17 M20 79 5362 4 0.00528 152 MW-18 M1 89 6161 3 0.00393 403 

Mean 64 5047 5 0.00650 422 

3 

Std 19 783 1 0.00161 222 

Mean 62 5516 4 0.00634 558 

Std 18 2553 1 0.00328 807 

Median 61 5023 4 0.00556 401 

Geo 

Mean 59 5094 4 0.00585 358 

Overall 

95th%tile 89 9179 6 0.00988 1224 
2.4 Evaluation of Scenario Benchmark Objectives 

Primary Benchmark Objective -- The data from the mop study have been analyzed to see if this 

mop scenario meets the primary AEATF II objective of a relative 3-fold accuracy (i.e., K=3). 

Using the SAS code developed by the Agricultural Handler Exposure Task Force (AHETF) and 

independently confirmed by the Health Effects Division (HED) (and now modified by AD), EPA 

has determined and presents the analysis that the mop study results meet the 3-fold relative 

accuracy objective (Sarkar 2010). Appendix A provides the detail benchmark analysis which is 

summarized as follows: 

Primary Benchmark Objective: fold Relative Accuracy (fRA) 

The primary benchmark objective for AEATF II scenarios is for select statistics – the geometric 

mean (GM), the arithmetic mean (AM), and the 95th percentile (P95) – to be accurate within 3-

fold with 95% confidence (i.e., “fold relative accuracy”). EPA has analyzed the data using 

various statistical techniques to evaluate this benchmark. First, to characterize the unit exposures 

(also referred to as “normalized exposure”), lognormal probability plots of dermal and inhalation 

UEs (adjusted for residue method collection efficiencies) are provided in Figures 2 to 5 for the 3 

clothing configurations as well as inhalation exposure. log (Normalized Long Dermal Exposure) 

4.0

3.5

3.0

2.5

2.0

1.5

-2 -1 0 1 2

Figure 2: Quantile plot normalized long dermal exposure data with a lognormal distribution 

normalized by pounds of Active Ingredient handled.

Normal Quantiles 

Page 17 of 25 
lnnrmdermls 

4.5

4.0

3.5

3.0

2.5

2.0

-2 -1 0

Figure 3: Quantile plot normalized long short dermal exposure data with a lognormal 

distribution normalized by pounds of Active Ingredient handled.

Normal Quantiles

log (Normalized Short Dermal Exposure) 

6.5

6.0

5.5

5.0

4.5

4.0

3.5

3.0

-2 -1 0 1 2

Figure 4: Quantile plot normalized short dermal exposure data with a lognormal 

distribution normalized by pounds of Active Ingredient handled. 

Normal Quantiles 

log (Normalized Inhalation Exposure) 

5.0

4.5

4.0

3.5

3.0

2.5

2.0

1.5 -2 -1 0 1 2

Figure 5: Quantile plot normalized inhalation exposure data with a lognormal distribution 

normalized by pounds of Active Ingredient handled.

Normal Quantiles 

1 2

Page 18 of 25 
Next, EPA calculated estimates of the GM, AM and P95 based on three different calculation 

methods: 

• Empirical estimates; 

• Assuming a lognormal distribution and a simple random sample (SRS); and, 

• Hierarchical variance component modeling to account for potential ME correlations. 

The 95% confidence limits for each of these estimates were obtained by generating 10,000 

parametric bootstrap samples. Then, the fRA for each was determined as the maximum of the 

two ratios of the statistical point estimates with their respective upper and lower 95% confidence 

limits. Table 5 below presents the results for the long pants, short-sleeved shirt and the 

inhalation exposures. The results of the benchmark analysis for the other clothing configurations 

are reported in Appendix A, Table 3 (long pants, long-sleeved shirt) and Appendix A, Table 4 

(short pants, short-sleeved shirt). 

Table 5. Results of Primary Benchmark Analysis for Long Pants, Short-sleeved Shirt and Inhalation. 

Dermal Exposure Inhalation Exposure 

Statistic Unit Exposure Estimate 

(mg/lb ai) 95% CI fRA Unit Exposure Estimate (ug/m3/lb ai) 95% CI fRA 

GMS 22.8 17.9 - 29.3 1.3 40.9 22.2 – 75.3 1.8 

GSDS 1.7 1.4 – 2.0 1.2 1.9 1.5 – 2.7 1.4 

GMM 22.8 17.9 – 29.3 1.3 40.9 22.2 – 75.3 1.8 

GSDM 1.7 1.4 – 2.0 1.2 2.0 1.5 – 3.1 1.5 

ICC 0 0 – 0.4 -- 0.5 0 – 0.8 -- 

GMS = geometric mean assuming SRS = “exp(average of 18 ln(UE)) values” 

GSDS = geometric standard deviation assuming SRS = “exp(standard deviation of 18 ln(UE)) values” 

GMM = variance component model-based geometric mean 

GSDM = variance component model-based geometric standard deviation 

ICC = intra-cluster correlation 

AMS 26.1 20.1 – 34.0 1.3 48.2 26.0 – 95.9 2.0 

AMU 26.3 20.2 – 34.5 1.3 50.5 26.4 – 97.7 1.9 

AMM 26.3 20.3 – 34.6 1.3 52.4 27.0 – 105.7 2.0 

AMS = average of 18 unit exposures 

AMU = arithmetic mean based on GMS = GMS*exp{0.5*(ln(GSDS)

2

} 

AMM = variance component model-based arithmetic mean = GMM* exp{0.5*(ln(GSDM)

2

} 

P95S 62.4 37.1 – 110.5 1.8 133.9 53.9 – 327.0 2.5 

P95U 54.7 37.0 – 79.3 1.5 119.0 53.4 – 263.5 2.2 

P95M 54.7 37.2 – 80.3 1.5 130.0 54.8 – 317.5 2.4 

P95S = 95th percentile (i.e., estimated as the maximum unit exposure from the 18 unit exposures) 

P95U = 95th percentile based on GMS = GMS * GSDS 

1.645

P95M = variance component model-based 95th percentile = GMM* GSDM 1.645

The benchmark of 3-fold accuracy for dermal and inhalation unit exposures has been met for the 

mop scenario for all 3 clothing scenarios and inhalation exposures for all 3 statistical models, 

except for the empirical 95th percentile for the short pants, short-sleeved shirt configuration 

where the fold relative accuracy is 4.5 (see Appendix A, Table 4). 

Page 19 of 25 
Secondary Benchmark Objective -- A secondary objective of the study was to evaluate the 

presumption of proportionality between exposure and amount of active ingredient handled 

(AaiH). EPA’s secondary statistical benchmark is to be able to distinguish, with 80% statistical 

power, complete proportionality from complete independence between exposure and amount of 

active ingredient handled. 

To evaluate the relationship for this scenario EPA performed regression analysis of ln(exposure) 

and ln(AaiH) to determine if the slope is not significantly different than 1 – providing support for 

a proportional relationship – or if the slope is not significantly different than 0 – providing 

support for an independent relationship. 

A simple linear regression, a mixed-effect regression, and a more complex “repeated measure” 

model (see Appendix A pages 32 and 33 for more details) were used to analyze the data to take 

into account the clustered nature of the data and were used to evaluate the relationship between 

exposure and AaiH. Appendix A also provides an analysis of the proportionality for each of the 

3 clothing configurations. The results of the proportionality analysis for the 3 clothing 

configurations are inconsistent; either all or none of the clothing configurations should show 

proportionality to AaiH. To investigate the proportionality issues further, an alternative model 

(“repeated measure”) was developed to fit the data from all of the clothing configurations. The 

reader is referred to the SAS code for specific details on this repeated measure model. 

The resulting regression slope and confidence intervals are summarized in Table 6 and in Figure 

6 (inhalation only) below. Note that a confidence interval width of 1.4 (or less) indicates at least 

80% statistical power, which was achieved for dermal and inhalation exposures. The results of 

the dermal model indicate that exposure is proportional to AaiH (i.e., confidence interval 

includes 1 but not 0 and the estimated slope is 0.78). However, for inhalation exposure the 

simple linear and mixed-effects models are different and neither model shows proportionality of 

inhalation exposure and AaiH. For more details the reader is referred to Appendix A, Table 7. 

Table 6. Summary Results of log-log Regression Slopes for Dermal and Inhalation Exposure 

Dermal Exposure Inhalation Exposure Regression 

Model Estimate 95% CI CI Width Regression 

Model

Estimate 95% CI Width 

“Repeated Simple Linear -0.20 -0.84 to 0.44 1.29 

Measures” 0.78 0.09 to 1.46 1.37 Mixed-Effects -0.03 -0.49 to 0.44 0.93 

Page 20 of 25 
Figure 6: Inhalation Exposure Regression 

3.0 Discussion of Data Generalizations and Limitations 

The regulatory need for a generic data base of pesticide handlers for antimicrobial pesticide 

products has been discussed previously (Myrta 2007). This mop study represents one study in 

the overall design of an AEATF II generic handler data base. This mop study was designed to 

represent the high end of potential exposure for mopping activities (e.g., selection of string mop 

& bucket, duration of sampling). The study design also incorporated random diversity selection 

where feasible. Such a study design requires a discussion of how the data can be generalized and 

the limitations of the results. The following items are provided to characterize the results of this 

sampling effort: 

(1) The study purposively selected Fresno, CA, as the study location. This selection criterion, 

rather than a random selection of sites across the country, limits to some degree the 

statistical generalizations of the data. Thus we cannot determine whether these results 

provide unbiased estimates of exposure distributions from mopping activities in locations 

other than Fresno, CA, and it is not possible to use these data to estimate the potential bias 

or the geographic variability. To generalize these results to the whole country requires an 

assumption that the exposure distribution for these scenarios is independent of the 

geographic location. The statistical limitations of the purposive site selection are deemed 

acceptable by the JRC. It is reasonable to assume that the mechanics of mopping floors 

inside buildings in Fresno are not substantially different than mopping of floors inside other 

buildings throughout the country. Given a limited set of resources for the overall AEATF II 

monitoring program, the assumption that indoor mopping of floors does not vary 

geographically was sufficiently reasonable to forgo the random site selection in favor of 

Page 21 of 25 
spending the limited resources to monitor additional distinctly different scenarios (e.g., 

wiping, aerosol cans, painting, metal working fluids, pressure treatment of wood, etc). 

(2) The data generated in this study are acceptable to use as surrogate for assessing other 

chemicals considered to have low volatility (i.e., vapor pressures less than ~1E-4 mmHg @ 

20C). This “rule-of–thumb” for the vapor pressure threshold is reviewed by EPA on a caseby-case basis, particularly for those antimicrobial pesticides with vapor pressures that are 

near to this threshold. For example, for those chemicals with vapor pressures of ~1E-4 

mmHg, EPA reviews the pesticide application method for the potential for aerosol 

generation and the available inhalation toxicity data to see if the toxicity studies were 

performed as a gas or with an aerosol. 

(3) The data generated in this study are acceptable to use as surrogate to assess pesticide labeled 

uses of mopping floors. A pesticide product that indicates a product can be applied by mop 

generally does not require or limit the specific type of mop to be used (e.g., string mop or 

sponge mop). The JRC reviewed the use of the string mop application equipment during the 

protocol development stage and decided that the exposures resulting from the use of a string 

mop would be a reasonable surrogate for other type of mops (e.g., sponge mop) that would 

not underestimate the exposure. 

(4) The dermal mop exposure data generated in this study are acceptable to use for clothing 

configurations of long pants, long-sleeved shirts (plus shoes/socks and no gloves), long 

pants, short-sleeved shirts (plus shoes/socks and no gloves), as well as short pants, short 

sleeved-shirts (plus shoes/socks and no gloves). 

(5) The small sample size by itself does not cause statistical limitations other than the high level 

of uncertainty shown by wide confidence intervals for some of the summary statistics. 

More important is the fact that the original sets of subject participants, locations, and dates 

from which the subjects, clusters, and sampling dates were chosen were limited and hence 

might not be representative of all Fresno moppers (e.g., moppers that did not volunteer), 

buildings (e.g. only empty buildings were eligible for this study), and time periods (e.g., 

winter vs summer, night vs day, etc.). In other words, the most significant limitation is that 

these data were not derived from a stratified random sample of MEs even though the 

statistical analyses made that assumption. At a minimum this increases the uncertainty of 

the estimates (so the calculated confidence intervals are too narrow) and there may also be 

some bias (e.g., study participants not in the volunteer pool might be more or less prone to 

exposure than the selected group). 

(6) EPA will continue using exposures normalized by AaiH as a default condition. The results 

of the dermal exposure for this mop study support use of this assumption. Data will 

continue to be collected by the AEATF II to add to the knowledge base of normalized 

exposures. 

Page 22 of 25 
4.0 Conclusion 

EPA has reviewed the AEATF II mop study and concludes that the AEATF II made the 

appropriate changes to the protocol proposed by the EPA and HSRB and has executed the study 

successfully. The protocol deviations that occurred and were reported on have not adversely 

impacted the reliability of these data. The EPA recommends that the inhalation and dermal UE 

generated in this mop study be used provided the data are used within the boundaries set forth in 

this review. 

The following is a summary of our conclusions. 

• The AEATF II data for inhalation and dermal exposures represent reliable data for 

assessing mopping of floors with antimicrobial products. Alternative data sources or 

special circumstances will be considered on a case by case basis. 

• Estimates of the GM, AM, and P95 were shown to be accurate within 3-fold with 95% 

confidence for all of the analyses, except for the empirical (empirical results reported in 

Appendix A) 95th percentile for the short pants, short-sleeved shirt configuration where 

the fold relative accuracy is 4.5. Although the estimated UEs were not based on the 

empirical results, the fold relative accuracy of 4.5 may have been the result of the 

incidental contact for subject M6 in cluster 1. 

• The data provided 80% statistical power to distinguish complete proportionality or 

independence between exposure and AaiH for both dermal and inhalation routes of 

exposure. Proportionality between dermal exposure and AaiH was established but not for 

inhalation exposure. 

5.0 References 

Boatwright, M. (2007) Determination of Removal Efficiency of Didecyl Dimethyl Ammonium 

Chloride (DDAC) from Hand Surfaces Using Isopropyl Alcohol/Water Wash. Unpublished 

study prepared by Golden Pacific Laboratories under Study No. 050211. 341 p. MRID 

47214801. 

EPA, 2008. Science and Ethics Review of AEATF Mop Scenario Design and Protocol for 

Exposure Monitoring. Memorandum dated March 10, 2008 from John Carley, Timothy 

Leighton, and Cassi Walls, PhD. To Norm Cook. 

Hackathorn, D.R. and D.C. Eberhart. 1985. Data Base Proposal for Use in Predicting Mixer-loaderapplicator Exposure. American Chemical Society Symposium Series 273, pp. 341-355.

Myrta C. 2007. Memorandum: Transmittal of Meeting Minutes of the FIFRA Scientific 

Advisory Panel Meeting Held January 9 – 12, 2007 on the Review of Worker Exposure 

Assessment Methods. U.S. Environmental Protection Agency. 

Page 23 of 25 
Popendorf W, Selim M, and Kross, B. 1990. Chemical Manufacturers Association Antimicrobial 

Exposure Assessment Study. MRID No. 41412201. 

Sarkar B. 2010. Memorandum: Review of Statistical Analyses in Agricultural Handler 

Exposure Task Force (AHETF) Monographs. U.S. Environmental Protection Agency. June 25, 

2010. D000000. 

Selim, S., and Taylor, M. (2010) A Study for Measurement of Potential Dermal and Inhalation 

Exposure During Application of a Liquid Antimicrobial Pesticide Product Using Bucket and 

Mop Equipment for Cleaning Indoor Surfaces. Unpublished study prepared by Golden Pacific 

Laboratories, LLC, under Project No. AEA03, Report No. 070265. 2116 p. (MRID 48210201) 

Selim, S., and Taylor, M. (2010) A Study for Measurement of Potential Dermal and Inhalation 

Exposure During Application of a Liquid Antimicrobial Pesticide Product Using Bucket and 

Mop Equipment for Cleaning Indoor Surfaces: Supplement 1 to MRID 48210201. Unpublished 

study prepared by Golden Pacific Laboratories, LLC, under Project No. AEA03, Report No. 

070265. 1146 p. (MRID 48231201) 

Selim, S., and Taylor, M. (2010) A Study for Measurement of Potential Dermal and Inhalation 

Exposure During Application of a Liquid Antimicrobial Pesticide Product Using Bucket and 

Mop Equipment for Cleaning Indoor Surfaces: Supplement 2 to MRID 48210201. Unpublished 

study prepared by Golden Pacific Laboratories, LLC, under Project No. AEA03, Report No. 

070265. 35 p. (MRID 48231901) 

Selim, S. (2008) A Study For Measurement of Potential Dermal and Inhalation Exposure During 

Application of a Liquid Antimicrobial Pesticide Product Using Bucket and Mop Equipment for 

Cleaning Indoor Surfaces. Unpublished protocol dated January 16, 2008, prepared by Golden 

Pacific Laboratories for the Antimicrobial Exposure Assessment Task Force II under Sponsor ID 

AEA03 and GPL Study No. 070265. 134 p., plus 335 p. supplement containing IRB 

correspondence. 

Page 24 of 25 
Appendix A 

Statistical Review of the AEATF II Mop Study 

(See separate electronic .pdf file) 

Cohen, J. (2010) AEATF Mop Study Statistical Review for HSRB. Unpublished memorandum 

dated 28 Sept 2010 from J. Cohen to T. Leighton of EPA, prepared by ICF International 

under Contract No.: EP-W-06-091; Work Assignment 3-02. 73 p. 

Page 25 of 25