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UNITED STATES ENVIRONMENTAL PROTECTION AGENCY 

WASHINGTON, DC 20460 

 OFFICE OF CHEMICAL SAFETY AND POLLUTION PREVENTION

 

MEMORANDUM

DATE: March 17, 2011 

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

(Trigger Spray & Wipe and Ready-to-Use Wipes Scenarios). 

PC Code(s): Not Applicable (NA) DP Barcode(s)/No(s): NA 

Decision No.: NA Registration No(s).: NA 

Petition No(s).: NA Regulatory Action: Human Health 

Risk Assess Type: Surrogate Handler 

Exposure Data 

Case No(s).: NA 

TXR No.: NA CAS No(s): NA 

MRID No(s).: 483756-01 40 CFR: None 

 

FROM: Tim Leighton, Environmental Scientist 

Risk Assessment and Science Support Branch (RASSB) 

OPP/Antimicrobials Division (7510P) 

TO: Nader Elkassabany, PhD, Branch Chief 

Risk Assessment and Science Support Branch (RASSB) 

OPP/Antimicrobials Division (7510P) 

 

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

the human exposure wipe study submitted by the Antimicrobial Exposure Assessment Task 

Force II (AEATF II). One wipe study was submitted that contains two exposure scenarios: 

Ready-to-Use (RTU) Wipes and Trigger Spray & Wipe. 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. 
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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) 

wipe study. The wipe study investigators monitored inhalation and dermal exposures to 18 

workers wiping surfaces using ready-to-use (RTU) wipes and 18 workers using trigger sprayers 

& wipes. 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 

wiping surfaces. The reader is referred to Section 3.0 for a discussion on the data limitations and 

use of the data as surrogate. 

EPA intends to use these AEATF II wipe datasets instead of the Chemical Manufacturers 

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

wiping surfaces. The exposure data in the AEATF II wipe scenarios represent RTU wipes and 

the application of a trigger spray and subsequent wipe only. The scenarios do not cover the 

pouring of the concentrate to prepare the RTU wipes (hence the wipes are defined as “ready-touse”) or pouring the concentrate to prepare a diluted solution to add to the trigger pump sprayer; 

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 wipes or with automatic 

dispensers to fill spray bottles), estimates of dermal and inhalation exposures from the future 

pour study will be combined with wipe exposures from this study when assessing exposures and 

risks from pesticide products applied by wiping. 

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, and no gloves; 

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

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

For comparison, results from the earlier CMA study for wiping 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. 
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Table 1. Unit Exposures: Wiping Scenarios 

Exposure 

Route Clothing CMAa

 AEATF IIb, c (n=18) 

Arithmetic Mean Arithmetic Meand 95th Percentilee

Ready-to-use (RTU) Wipes 

Dermal 

(mg/lb ai) 

Long pants/long-sleeves, 

shoes/socks, no gloves 

Not Available 

2380 

(1150, 5160) 

5990 

(2280, 16200) 

Long pants/short-sleeves, 

shoes/socks, no gloves 

2580 

(1400, 4920) 

6190 

(2780, 14100) 

Short pants/short-sleeves, 

shoes/socks, no gloves 

2740 

(1580, 4870) 

6500 

(3170, 13500) 

Inhalation 

Breathing Zone 

(mg/m3/lb ai) 

0.31 

(0.13, 0.81) 

1.13 

(0.41, 3.09) 

Breathing Zone 

 (mg/lb ai) f

0.48 

(0.24, 1.06) 

1.67 

(0.70, 3.97) 

Trigger Spray & Wipe 

Dermal 

(mg/lb ai) 

Long pants/long-sleeves, 

shoes/socks, no gloves 

2870 ± 4220 

(n=6) 

(some workers shortsleeves and some longsleeves) 

Not available 

1050 

(749, 1490) 

2420 

(1500.5, 3892.5) 

Long pants/short-sleeves, 

shoes/socks, no gloves 

1530 

(1160, 2050) 

3220 

(2148.2, 4835.4) 

Short pants/short-sleeves, 

shoes/socks, no gloves Not Available 1740 

(1220, 2500) 

3640 

(2270, 5840) 

Inhalation 

Breathing Zone 

(mg/m3/lb ai) 

12.2 ± 22.4 

(n=8) 

(7 non-detects) 

11.6 

(4.8, 29.9) 

37.5 

(13.0, 110) 

Breathing Zone 

(mg/lb ai) f 67.3 ± 71.6 

(n=6) 

18.5 

(8.53, 42.3) 

53.8 

(20.5, 144) 

a

 CMA data: Mean ± std. Inhalation LOQ varied among samples. Task of using trigger pump spray and wiping 

restroom and dental fixtures. 

b

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

measurements. The percent of average dermal exposure representing the hands for the long pants, long sleeved 

scenario for the RTU and Trigger Spray & Wipe are 98% and 92%, respectively. 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 Appendices A and B. 

d

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

 95th percentile = GM * GSD1.645 

f

 Inhalation (mg/lb ai) = (air conc (mg/m3) / lb ai) * breathing rate (1 m3/hour) * wipe duration (hours/day) 

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 

wipe 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. 
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• The AEATF II study report containing dermal and inhalation exposure results are 

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 (rule of thumb is that <E-4 mmHg @ 

20° C is considered non-volatile). 

• Ready to use wipes. Although the statistical analysis does not provide evidence of direct 

proportionality (1:1) between dermal exposure and pounds of active ingredient (ai) 

handled (i.e., slope ≠ 1 in Table 10 below), the analysis does show that dermal exposure 

tends to increase with pounds of ai handled (AaiH) as described in Section 2.4 below. 

Inhalation exposure, however, is not proportional to AaiH (slope is negative). 

• Trigger spray and wipe. Although the statistical analysis does not provide evidence of 

direct proportionality (1:1) between dermal exposure and AaiH (i.e., slope ≠ 1 in Table 

11 below), the analysis does show that dermal exposure tends to increase with AaiH as 

described in Section 2.4 below. Inhalation exposure also slightly tends to increase with 

AaiH (i.e., slope = 0.25). 

To assess the risks resulting from wiping 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: Potential 

exposure = UE (mg/lb ai or mg/m3

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

ai/gallon) x volume (gallons) 

 
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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., ready-to-use wipes, mop & bucket, 

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 Wipe Scenarios Defined 

Ready-to-Use (RTU) Wipes. The RTU wipe scenario in this study is defined as wiping 

various horizontal and vertical surfaces such as tile walls, counter tops, sinks, faucets, elevator 

doors, railings, shelves, etc. Wiping motions included up & down, side-to-side, and circular 

motions as the workers worked as they would normally do. The RTU wipes are pre-treated (pretreatment of wipes not monitored for exposure). Subjects wore whole body dosimeters (WBD) 

underneath long-sleeved shirts, long pants, 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. 

Trigger Spray and Rag Wipe. The trigger spray and wipe scenario in this study is 

defined as using a 32 ounce trigger spray bottle to spray surfaces and subsequently wipe them. 

Workers cleaned various horizontal and vertical surfaces such as walls, toilets & stall walls, hand 

railings, shelves including underneath shelves, counter tops, etc using up & down, side-to-side, 

and circular motions as the workers worked as they would normally do. Subjects wore WBD 

underneath long-sleeved shirts, long pants, 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 spray bottles. Antimicrobial products may be added to spray 

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

typical glug containers, packaged as ready-to-use, or automated dispensers. Open pouring a 

pesticide concentrate will be monitored in a future AEATF II study. 

1.2 Study Objective 

The AEATF II’s study objective is to monitor inhalation and dermal exposures to be used 

as inputs in exposure algorithms to predict future exposures to persons wiping surfaces with 

either RTU wipes or trigger spray & wipe/rag. Dermal and inhalation exposure monitoring was 

conducted while study participants wiped various surfaces (walls, bathrooms, etc) 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 
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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 (Christian 2007). Outlined in the AEATF II Governing Document, the criteria can be 

briefly summarized as follows: 

• The AEATF II’s objective for this 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 objective AEATF II proposed an experimental design with 

a 3 cluster by 6 monitoring events (MEs). 

• EPA also plans to use the data to evaluate the presumption of proportionality between 

exposure and amount of active ingredient handled. EPA used 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. 

 

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). The EPA 

review of the protocol noted that the type of wipe to be used in the Trigger Spray & Wipe 

scenario was not specified. The protocol was modified to identify the wipe as cotton rags. 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 
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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" 

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 by increasing the proposed 30 to 120 minute range of monitoring to 

30 to 210 minutes of wiping activities. The justification of the wipe sampling time is 

cited in the AEATF II’s Supplement 2 report submitted previously for the mop study 

(MRID 482102-01). MRID 482102-01 provides wiping durations from time and motionbased estimates for wiping on a per room basis from the International Sanitary Supply 

Association (ISSA) as 8.51 minutes/room. The theoretical maximum of 25 rooms/day 

cleaned was also provided in MRID 482102-01 and cited below: : “...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. ....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.” The maximum wiping duration was thus increased to 210 minutes (i.e., 

8.51 minutes/room x 25 rooms = 212.75 minutes, rounded to 210 minutes). This change 

to the protocol was discussed and accepted by the Joint Regulatory Committee (JRC). 

 

• 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 spray) have been modified to use the amount handled instead of exposure 

duration to differentiate among MEs. However, for the wipe study, the information 
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above on wiping duration was determined by the JRC to be the best information available 

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

appropriate amount of RTU wipes or diluted treatment solution in the Trigger Spray & 

Wipe as they would normally do. This approach was judged by EPA to lead to the most 

relevant information on how much active ingredient would be used by workers working 

as they normally would 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 

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

proportionality in Section 2.4 below and Appendices A and B. In brief, the statistical 

analysis compared pounds of active ingredient to wiping duration and other relevant 

variables as the possible normalization variables. 

o RTU Wipes: Although the statistical analysis does not provide evidence of direct 

proportionality (1:1) between dermal exposure and pounds of active ingredient 

(ai) handled (i.e., slope ≠ 1 in Table 10 below), the analysis does show that 

dermal exposure tends to increase with pounds of ai handled (AaiH) as described 

in Section 2.4 below. Inhalation exposure, however, is not proportional to AaiH 

(estimated slope is negative). The statistical analysis also suggests that the dermal 

exposure is proportional to the wiping duration (see Appendix A). The statistical 

analysis does not distinguish whether inhalation exposure is proportional to or 

independent of the wiping duration. 

o Trigger spray and wipe. Although the statistical analysis does not provide 

evidence of direct proportionality (1:1) between dermal exposure and AaiH (i.e., 

slope ≠ 1 in Table 11 below), the analysis does show that dermal exposure tends 

to increase with AaiH as described in Section 2.4 below. Inhalation exposure also 

slightly tends to increase with AaiH (i.e., estimated slope = 0.25). The statistical 

analysis shows even less support for proportionality between dermal or inhalation 

exposure and the wiping duration (see Appendix B). 

The basis for the exposure extrapolation by AaiH is explained by the following: 

 Exposure = K(AiaH)^slope 

If slope = 0 then exposure is independent of the AaiH. If slope = 1 then exposure is 

directly proportional (1:1) to AaiH. If slope is positive, not zero and not 1 then the 

exposure tends to increase with the AiaH but not proportionally, so that, for example, 

doubling the AiaH will not tend to double the exposure. If the slope confidence interval 

excludes both 1 and 0 then the statistical evidence rejects both proportionality and 

independence and shows that the exposure tends to increase with the AiaH but not 

proportionally (see Tables 10 and 11 for results of proportionality test). This implies that 

using the normalized exposure results to estimate exposures for different pesticides or 

different concentrations is an approximation that tends to overestimate exposure at the 

high end of AaiH. Section 2.4 below also provides the threshold of AaiH where exposure 
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based on estimated AaiH lower than the threshold results in an under-estimate of 

exposure and estimated AaiH higher than the threshold results in an over-estimate of 

exposure (i.e., protective of human health). 

• 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 

wiping activities. This wipe study was conducted during the same time period as the 

previously reviewed AEATF II mop study (but not on the same days). Therefore, the 

“lessons learned” (e.g., impact of the room size, ventilation, etc on air concentrations) 

from the previous HSRB review of the mop study could not be incorporated into this 

study as the wipe study was completed prior to the HSRB comments on the mop study. 

• October 2010 HSRB statistical suggestions – The HSRB raised several issues 

concerning the statistical analysis of the completed AEATF II mop study that are also 

relevant to this wipe study. During the October 2010 HSRB review of the AEATF II’s 

mop study, one or more of the Board members suggested additional statistical analysis 

including reviewing the quadratic model, degrees of freedom, and non-parametric 

bootstrap methods. Section 2.4 below and Appendices A and B explore these suggested 

alternatives. 

1.3.2 Protocol Amendments 

The study report (page 116) lists 7 protocol amendments. The amendments range from 

changing the building selection criteria to improving clarity in definitions/statements to adding 

additional steps to insure enough study participants for the study to improved efficiency of the 

conduct of the study. Additionally, amendments were made to address study personnel changes. 

1.3.3 Protocol Deviations 

A total of 23 minor deviations were noted in the study (study report pages 117-118). The 

deviations included, but not limited to, washing hands and face prior to the monitoring period 

with 50:50 IPA:water instead of only Ivory soap; light levels not monitored; break times did not 

follow protocol exactly; slight under-dilution of the trigger bottle spray solution in clusters 2 and 

3 (1/65th DDAC/water instead of the target 1/64th dilution); etc. For a detailed description of the 

protocol deviations the reader is referred to 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 wipe study was conducted in Fresno County, CA. Pictures and 

floor plans for both scenarios are provided in Appendices H (page 324) through J (page 
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330) of the study report. Each cluster is a different building. The buildings are an office 

building, a Rite Aid, and a retired teacher’s memorial building. These are the same 

buildings used in the previously conducted AEATF II mop study; separated by time and 

different test subjects. 

• 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 (total of 2.54% + 1.69% = 4.23%). There is a discrepancy on page 

32 of the study report, listing the total DDAC and ADBAC concentration at 4.51% ai. 

Golden Pacific Laboratories (GPL) noted in a subsequent discussion that the certificate of 

analysis listed the total ai as 4.51% ai. GPL also noted that DDAC was determined to be 

at 2.58%, 2.5%, and 2.44% in clusters 1, 2, 3, respectively. The impact of the certificate 

of analysis listing the total ADBAC and DDAC as 4.51% is considered minor because 

the percent DDAC was determined for each cluster. 

• Test System: 

o RTU Wipes: The RTU wipes were prepared (solution preparation discussed in 

the bullets below) at least 1 week in advance of the monitoring and stored in 8.5 x 

5 inch plastic cylinders. Each wipe was 8 x 7 inches with the wipes connected to 

each other. A photo of RTU wipes and container are presented below in Figure 1. 

o Trigger Spray & Wipe: The trigger bottle was a 32 ounce GRIP AND GO! 

(Buckeye International, product #41076000) and the rags used for wiping were 

cotton (Bag-o-Rags). Photos of trigger spray bottle and wipe/rag are presented 

below in Figure 1a. 
Page 11 of 40 

 Figure 1. RTU Wipes and Wipe Container. 

Figure 1a. Trigger Spray Bottle and Wipe/Rag. 

• 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 pages 121-122 of the study report. 

• Sample Size: The study consisted of 3 clusters and 6 MEs per cluster (n=18) for each of 

the two wipe scenarios for a total of 36 MEs in the study. 
Page 12 of 40 

• Treatment Solutions: 

o RTU Wipes: The diluted treatment solution of Lemon Quat was prepared by the 

researchers for the RTU wipes in the laboratory (i.e., GPL). The Lemon Quat 

product was diluted with water 1:64 (0.0397% DDAC). Rolls of dry wipes (75 

wipes per roll) were treated with 500 mL of the water diluted product. The 

treated wipes were then shaken on a shaker for 30 minutes. The nominal 

concentration of each wipe was 2.61 mg DDAC/wipe. The measured 

concentrations for the wipes were 2.34, 2.90, and 2.55 mg DDAC/wipe in clusters 

1, 2, 3, respectively. The preparation of the treatment solution and RTU wipes 

were not part of the monitoring events. 

o Trigger Sprayers: 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 (in each of the two scenarios), the MEs 

were randomly assigned to 1 of the 6 purposively selected wiping times. The predetermined wiping times were: 

o 30 to <60 minutes 

o 60 to <90 minutes 

o 90 to <120 minutes 

o 120 to <150 minutes 

o 150 to <180 minutes 

o 180 to 210 minutes 

Actual wiping durations followed the predetermined sampling times closely. Individual 

wiping times for each of the MEs are reported in Table 2 below. The amount of DDAC 

handled by the 18 MEs in each scenario ranged from 0.00014 to 0.00160 lbs ai with a 

mean ± one standard deviation of 0.00074 ± 0.00044 lb ai for the RTU Wipes scenario 

and ranged from 0.00038 to 0.00474 lbs ai with a mean of 0.0014 ± 0.0010 lb ai for the 

trigger spray scenario. The 18 MEs in the RTU Wipes scenario used varying numbers of 

wipes ranging from 27 to 250 wipes per ME. The amount ai per ME for the Trigger 

Spray and Wipe scenario is the amount actually sprayed onto surfaces, determined by 

weighing the spray container before and after wiping. These data are also reported in 

Table 2 below. The correlation coefficients between AaiH and wiping duration were 0.8 

for RTU and 0.7 for spray and wipe. Some workers used more wipes or spray solution 

than others. For example, in the ready-to-use wipe study, in cluster 1 subject number 

W16 wiped for 165 minutes and used 156 wipes (0.0008 lb ai) while subject number 

W17 wiped for 162 minutes yet only used 88 wipes (0.00045 lb ai). 
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• Wiping Procedures: Appendix K on pages 333 to 351 of the study report records the 

observation notes taken during each ME for the RTU scenario and Appendix L pages 352 

to 371 for the trigger spray scenario. The workers were instructed to wipe “as they would 

normally do”. Typical wiping procedures/observations were that the workers cleaned 

various horizontal and vertical surfaces such as walls, counter tops, etc using up & down, 

side-to-side, and circular motions. 

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

reported for the MEs on pages 136 to 141 of the study report (note: humidity and/or 

temperature readings not available for 8 of the MEs). 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 142 

of study report (not available for cluster 2 for both scenarios). 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. Lighting 

levels were not measured. The HSRB noted at the October 2011 review of the AEATF II 

mop study that more attention should be given by the researchers to record the 

environmental conditions. However, this wipe study was conducted roughly at the same 

time period as the mop study. Therefore, limited information is available in this study 

too. 

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) which indicates no background contamination. The LOQs for the various 

matrices are air sampling tubes 10 ng/sample, neck/face wipe 50 ng/sample, WBD sections 3 

μg/sample, and hand wash 1 μg/sample. 

Laboratory Recoveries: Concurrent laboratory recoveries serve both scenarios (RTU & trigger 

spray). 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 in the study report starting on page 76 (individual recovery values 

can be viewed starting on page 144). The mean recoveries in cluster 1 for all matrices range 

from 103 ± 15 to 113 ± 17; cluster 2 ranged from 99 ± 5 to 113 ± 6; and cluster 3 ranged from 95 

± 4 to 108 ± 6. 

Field Recoveries: Field recoveries serve both scenarios (RTU & trigger spray). 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 78 of 

the study report (individual recovery values can be viewed starting on page 150). The mean 

recoveries in cluster 1 for all matrices range from 83 ± 11 to 107 ± 21; cluster 2 ranged from 93 
Page 14 of 40 

± 10 to 109 ± 12; and cluster 3 ranged from 92 ± 9 to 103 ± 5. 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 and long pants). 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), and face/neck 

wipes (also collected during the ME to wipe off sweat; see study report page 48). 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 (ND) 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 67 and 69 for equations). A removal efficiency study for hand washes 

and wipes was performed using the test substance, DDAC, in a previous study (Boatwright 2007, 

MRID 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 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 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 face/neck wash and hand wash): 
Page 15 of 40 

• 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 breaks. Collected residue, per standard practice, is adjusted for recovery from field 

fortification samples. 

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

/lb ai handled) are calculated by dividing the air 

concentrations by the amount of ai handled. When the need arises for the unit inhalation 

exposures to be in units of mg/lb ai (e.g., when assessing inhalation risks using an oral 

toxicological endpoint) the inhalation unit exposure is calculated as the (air conc (mg/m3) / lb ai) 

* breathing rate (1 m3/hour) * wipe duration (hours/day). 

2.3 Dermal and Inhalation Exposure Results 

Results -- A summary of the results of the 18 MEs for each scenario are presented in 

Tables 2 and 5 (long pants, long sleeved-shirts), Tables 3 and 6 (long pants, short-sleeved shirts), 

and Tables 4 and 6 (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 Tables 2 and 5). 

Appendices A and B provides alternative statistical models to estimate the exposure 

summary statistics, including: 

• Empirical simple random sampling model (see Appendices A and B Table 1); 

• Lognormal simple random sampling model (see Appendices A and B Tables 3 through 

6); and 

• Lognormal mixed model (see Appendices A and B Table 2 for a summary, and 

Appendices A and B Tables 3 through 6 for detailed results). 

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 
Page 16 of 40 

lognormal mixed model calculations and results (along with a discussion of the HSRB-suggested 

quadratic models) the reader is referred to Appendices A and B. 

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

observers. The study report indicates... “There were always three to four study personnel 

following the subject during a given monitoring event”, with one being the “observer”. 

Observations recorded during each ME are reported starting on page 333 of the study report and 

record the “real world” events during wiping as a worker would normally do. A review of these 

observations and resulting exposures did not indicate any obvious outliers in the data. 

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

the body parts sampled for the wipe pesticide application 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 

total exposure as 1⁄2 LOQ. For the ready-to-use wipes study, all of the hand wash and face/neck 

samples and 12 of the 18 air samples were greater than the LOQ. Also for the ready-to-use wipes 

study, 81 of the 108 inner WBD sectioned body parts and 20 of the 108 outer WBD sectioned 

body parts were less than the LOQ or not measured (because they were inner sections 

corresponding to an outer section that was below the LOQ). For the trigger spray and wipe study, 

all of the hand wash, face/neck samples and air samples were greater than the LOQ. Also for the 

trigger spray and wipe study, 38 of the 108 inner WBD sectioned body parts and 2 of the 108 

outer WBD sectioned body parts were less than the LOQ or not measured. 

The impact of the ND samples for the short pants, short-sleeved shirt, 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 

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

RTU Wipes Mean 2600 2620 2640 

RTU Wipes 95th% tile 5620 5640 5650 

Trigger Spray & Wipe Mean 1730 1740 1740 

Trigger Spray & Wipe 95th% tile 3310 3310 3320 

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

pants, short-sleeved shirt 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 ready-to-use wipes, for the long pants, long-sleeved shirt 

configuration, 98 percent of the total dermal exposure is attributed to the hand exposure and only 

82 percent of the total dermal exposure for the short pants, short-sleeved shirt scenario is 

attributed to the hands. For the trigger spray and wipe study, for the long pants, long-sleeved 

shirt configuration, 92 percent of the total dermal exposure is attributed to the hand exposure and 

only 51 percent of the total dermal exposure for the short pants, short-sleeved shirt scenario is 

attributed to the hands.
Page 17 of 40 

Table 2. RTU Wipes: Summary (Empirical) of Dermal and Inhalation Results -- Long Pants, Long-sleeved Shirt and No Glov

Cluster Subject 

Order 

Subject 

Number 

ID 

Task 

Duration 

(minutes) 

Surface 

Area 

(sq ft) 

Number 

Wipes 

Pounds ai 

Handled 

Dermal 

Exposure 

(mg) 

Inhalation

Exposure 

(mg/m3) 

U

Dermal 

(mg/lb ai

1 

WS-02 W45 37 1614.5 40 0.000206 0.6656 0.000048 322

WS-08 W13 73 1509.8 27 0.000139 0.7067 0.000289 507WS-10 W42 104 3504.0 103 0.000531 1.3874 0.000070 261WS-11 W32 131 2750.8 216 0.001113 1.6163 0.000143 145WS-05 W17 162 1790.1 88 0.000454 2.2305 0.000224 491WS-01 W16 165 5029.6 156 0.000805 2.8259 0.000058 351

Mean 112 2699.8 105 0.000542 1.5721 0.000139 346

Std 51 1378.3 71 0.000368 0.8500 0.000099 137

2 

WS-13 W37 61 557.0 37 0.000236 0.4229 0.000180 179

WS-20 W26 90 1752.0 165 0.001056 0.9662 0.000073 91WS-24 W29 120 2786.0 138 0.000882 1.2203 0.000146 138WS-21 W5 149 2663.0 131 0.000838 0.6179 0.000043 73WS-17 W14 180 703.0 222 0.001420 1.6167 0.000200 113WS-14 W41 182 1603.0 250 0.001598 0.8203 0.000011 51

Mean 130 1677.3 157 0.001005 0.9440 0.000109 108

Std 49 939.8 75 0.000482 0.4295 0.000077 46

3 

WS-32 W49 59 876.0 37 0.000208 0.4432 0.000035 213

WS-28 W2 89 1110.0 71 0.000399 1.3682 0.000070 342WS-30 W34 119 1160.0 123 0.000692 1.0243 0.000058 147WS-27 W39 133 1800.0 84 0.000472 1.2331 0.000015 261WS-31 W52 179 1899.0 177 0.000994 0.9362 0.000029 94WS-34 W8 201 4907.0 213 0.001197 2.5280 0.000430 211

Mean 130 1958.7 118 0.000660 1.2555 0.000106 211

Std 53 1500.1 67 0.000377 0.6997 0.000160 86

Overall 

Mean 124 2111.9 127 0.000736 1.2572 0.000118 222

Std 49 1295.1 71 0.000437 0.6931 0.000111 136

Median 126 1771.1 127 0.000748 1.1223 0.000070 195

Geo 

Mean 113 1781.4 104 0.000594 1.0926 0.000077 184

95th%tile 185 4925.4 226 0.001447 2.5727 0.000310 493
Page 18 of 40 

Table 3. RTU Wipes: Summary (Empirical) of Dermal Results -- Long Pants, Short-sleeved Shirt and No Glove Scenario.

Cluster Subject 

Order 

Subject 

Number 

ID 

Task 

Duration 

(minutes) 

Surface 

Area 

(sq ft) 

Number 

Wipes 

Pounds ai 

Handled 

Dermal 

Exposure (mg) 

Unit Expo

Derma

(mg/lb 

1 

WS-02 W45 37 1614.5 40 0.000206 0.6896 3

WS-08 W13 73 1509.8 27 0.000139 0.7701 5WS-10 W42 104 3504.0 103 0.000531 1.4518 2WS-11 W32 131 2750.8 216 0.001113 1.7303 1WS-05 W17 162 1790.1 88 0.000454 2.4105 5WS-01 W16 165 5029.6 156 0.000805 2.8987 3

Mean 112 2699.8 105 0.000542 1.6585 3

Std 51 1378.3 71 0.000368 0.8809 1

2 

WS-13 W37 61 557.0 37 0.000236 0.7139 3

WS-20 W26 90 1752.0 165 0.001056 1.0222 WS-24 W29 120 2786.0 138 0.000882 1.4383 1WS-21 W5 149 2663.0 131 0.000838 0.9229 1WS-17 W14 180 703.0 222 0.001420 1.7807 1WS-14 W41 182 1603.0 250 0.001598 0.9203 

Mean 130 1677.3 157 0.001005 1.1330 1

Std 49 939.8 75 0.000482 0.3975 

3 

WS-32 W49 59 876.0 37 0.000208 0.4496 2

WS-28 W2 89 1110.0 71 0.000399 1.3884 3WS-30 W34 119 1160.0 123 0.000692 1.0969 1WS-27 W39 133 1800.0 84 0.000472 1.2461 2WS-31 W52 179 1899.0 177 0.000994 1.0462 1WS-34 W8 201 4907.0 213 0.001197 3.0470 2

Mean 130 1958.7 118 0.000660 1.3790 2

Std 53 1500.1 67 0.000377 0.8780 

Overall 

Mean 124 2111.9 127 0.000736 1.3902 2

Std 49 1295.1 71 0.000437 0.7417 

Median 126 1771.1 127 0.000748 1.1715 2

Geo 

Mean 113 1781.4 104 0.000594 1.2279 2

95th%tile 185 4925.4 226 0.001447 2.9210 5
Page 19 of 40 

Table 4. RTU Wipes: Summary (Empirical) of Dermal Results -- Short Pants, Short-sleeved Shirt and No Glove Scenario.

Cluster Subject 

Order 

Subject 

Number 

ID 

Task 

Duration 

(minutes) 

Surface 

Area 

(sq ft) 

Number 

Wipes 

Pounds ai 

Handled 

Dermal 

Exposure (mg) 

Unit Exposures 

Dermal 

(mg/lb ai) 

1 

WS-02 W45 37 1614.5 40 0.000206 0.6911 3349.1

WS-08 W13 73 1509.8 27 0.000139 0.9411 6754.0WS-10 W42 104 3504.0 103 0.000531 1.4750 2776.2WS-11 W32 131 2750.8 216 0.001113 1.7399 1562.8WS-05 W17 162 1790.1 88 0.000454 2.4698 5438.2WS-01 W16 165 5029.6 156 0.000805 2.9026 3607.0

Mean 112 2699.8 105 0.000542 1.7032 3914.5

Std 51 1378.3 71 0.000368 0.8585 1877.4

2 

WS-13 W37 61 557.0 37 0.000236 0.7154 3032.8

WS-20 W26 90 1752.0 165 0.001056 1.0425 987.1WS-24 W29 120 2786.0 138 0.000882 2.1983 2492.8WS-21 W5 149 2663.0 131 0.000838 1.1079 1322.4WS-17 W14 180 703.0 222 0.001420 2.0777 1463.4WS-14 W41 182 1603.0 250 0.001598 0.9319 583.0

Mean 130 1677.3 157 0.001005 1.3456 1646.9

Std 49 939.8 75 0.000482 0.6292 931.9

3 

WS-32 W49 59 876.0 37 0.000208 0.4540 2183.5

WS-28 W2 89 1110.0 71 0.000399 1.3928 3490.4WS-30 W34 119 1160.0 123 0.000692 1.1675 1686.5WS-27 W39 133 1800.0 84 0.000472 1.2525 2654.8WS-31 W52 179 1899.0 177 0.000994 1.0657 1071.8WS-34 W8 201 4907.0 213 0.001197 3.2280 2696.4

Mean 130 1958.7 118 0.000660 1.4268 2297.2

Std 53 1500.1 67 0.000377 0.9402 848.3

Overall 

Mean 124 2111.9 127 0.000736 1.4919 2619.6

Std 49 1295.1 71 0.000437 0.7861 1570.4

Median 126 1771.1 127 0.000748 1.2100 2573.8

Geo 

Mean 113 1781.4 104 0.000594 1.3126 2211.3

95th%tile 185 4925.4 226 0.001447 2.9514 5635.5
Page 20 of 40 

Table 5. Trigger Spray & Wipe: Summary (Empirical) of Dermal and Inhalation Results -- Long Pants, Long-sleeved Shirt a

Cluster Subject 

Order 

Subject 

Number 

ID 

Task 

Duration 

(minutes) 

Surface 

Area 

(sq ft) 

Pounds ai 

Handled 

Dermal 

Exposure 

(mg) 

Inhalation 

Exposure 

(mg/m3) 

Derm

(mg/lb 

1 

WS-04 W50 51 1077.4 0.000419 1.4571 0.019400 3

WS-06 W24 70 640.0 0.000375 0.4272 0.009930 1WS-07 W27 93 1406.5 0.000928 2.5802 0.004130 2WS-09 W10 142 3243.7 0.001153 0.6361 0.011700 WS-12 W19 174 3628.7 0.001764 0.8415 0.023000 WS-03 W7 187 3186.3 0.002055 0.7894 0.017800 

Mean 120 2197.1 0.001116 1.1219 0.014327 1

Std 56 1298.2 0.000689 0.7933 0.006975 1

2 

WS-16 W6 60 1269.0 0.000672 0.4342 0.008640 

WS-23 W25 89 1444.0 0.000822 0.5088 0.003470 WS-18 W18 121 1130.0 0.001435 0.7107 0.005490 WS-22 W44 150 2501.0 0.002013 2.3867 0.015000 1WS-19 W12 180 3076.0 0.004742 2.1591 0.014100 WS-15 W56 209 3617.0 0.001973 1.0917 0.000859 

Mean 135 2172.8 0.001943 1.2152 0.007927 

Std 56 1043.5 0.001481 0.8535 0.005734 

3 

WS-36 W55 59 387.0 0.000399 0.8074 0.003300 2

WS-25 W35 60 1256.0 0.000747 0.7648 0.005560 1WS-35 W4 104 1072.0 0.001177 1.2772 0.005350 1WS-33 W1 137 2740.0 0.001307 1.0788 0.018900 WS-29 W40 153 421.0 0.001276 0.8842 0.004100 WS-26 W28 185 2047.0 0.001268 0.9754 0.005360 

Mean 116 1320.5 0.001029 0.9646 0.007095 1

Std 51 926.2 0.000373 0.1908 0.005850 

Overall 

Mean 124 1896.8 0.001363 1.1006 0.009783 1

Std 52 1115.4 0.001003 0.6491 0.006716 

Median 129 1425.3 0.001222 0.8629 0.007100 

Geo 

Mean 112 1547.1 0.001112 0.9554 0.007420 

95th%tile 190 3618.8 0.002458 2.4157 0.019940 2
Page 21 of 40 

Table 6. Trigger Spray & Wipe: Summary (Empirical) of Dermal Results -- Long Pants, Short-sleeved Shirt and No Glove S

Cluster Subject 

Order 

Subject 

Number 

ID 

Task 

Duration 

(minutes) 

Surface Area 

(sq ft) Pounds ai Handled

Dermal 

Exposure (mg) 

Unit Exposure

(mg/lb a

1 

WS-04 W50 51 1077.4 0.000419 2.0281 

WS-06 W24 70 640.0 0.000375 0.7222 WS-07 W27 93 1406.5 0.000928 2.7192 WS-09 W10 142 3243.7 0.001153 0.9741 WS-12 W19 174 3628.7 0.001764 1.1855 WS-03 W7 187 3186.3 0.002055 2.6234 

Mean 120 2197.1 0.001116 1.7088 

Std 56 1298.2 0.000689 0.8656 

2 

WS-16 W6 60 1269.0 0.000672 0.7702 

WS-23 W25 89 1444.0 0.000822 0.6868 WS-18 W18 121 1130.0 0.001435 1.0797 WS-22 W44 150 2501.0 0.002013 4.1687 WS-19 W12 180 3076.0 0.004742 5.9021 WS-15 W56 209 3617.0 0.001973 1.3197 

Mean 135 2172.8 0.001943 2.3212 

Std 56 1043.5 0.001481 2.1844 

3 

WS-36 W55 59 387.0 0.000399 0.8411 

WS-25 W35 60 1256.0 0.000747 1.2978 WS-35 W4 104 1072.0 0.001177 2.0282 WS-33 W1 137 2740.0 0.001307 1.3478 WS-29 W40 153 421.0 0.001276 1.3502 WS-26 W28 185 2047.0 0.001268 1.1904 

Mean 116 1320.5 0.001029 1.3426 

Std 51 926.2 0.000373 0.3865 

Overall 

Mean 124 1896.8 0.001363 1.7908 

Std 52 1115.4 0.001003 1.3566 

Median 129 1425.3 0.001222 1.3087 

Geo 

Mean 112 1547.1 0.001112 1.4736 

95th%tile 190 3618.8 0.002458 4.4287 
Page 22 of 40 

Table 7. Trigger Spray & Wipe: Summary (Empirical) of Dermal Results -- Short Pants, Short-sleeved Shirt and No Glove S

Cluster Subject 

Order 

Subject 

Number ID 

Task Duration 

(minutes) 

Surface Area 

(sq ft) 

Pounds ai 

Handled 

Dermal 

Exposure (mg) 

Unit Exp

(m

1 

WS-04 W50 51 1077.4 0.000419 2.1591 

WS-06 W24 70 640.0 0.000375 0.9432 WS-07 W27 93 1406.5 0.000928 2.7738 WS-09 W10 142 3243.7 0.001153 1.2061 WS-12 W19 174 3628.7 0.001764 1.7475 WS-03 W7 187 3186.3 0.002055 2.9414 

Mean 120 2197.1 0.001116 1.9619 

Std 56 1298.2 0.000689 0.8140 

2 

WS-16 W6 60 1269.0 0.000672 0.8237 

WS-23 W25 89 1444.0 0.000822 0.7361 WS-18 W18 121 1130.0 0.001435 1.1271 WS-22 W44 150 2501.0 0.002013 4.5297 WS-19 W12 180 3076.0 0.004742 6.1951 WS-15 W56 209 3617.0 0.001973 1.3512 

Mean 135 2172.8 0.001943 2.4605 

Std 56 1043.5 0.001481 2.3191 

3 

WS-36 W55 59 387.0 0.000399 0.8660 

WS-25 W35 60 1256.0 0.000747 1.8248 WS-35 W4 104 1072.0 0.001177 2.0637 WS-33 W1 137 2740.0 0.001307 1.6288 WS-29 W40 153 421.0 0.001276 1.4952 WS-26 W28 185 2047.0 0.001268 1.5134 

Mean 116 1320.5 0.001029 1.5653 

Std 51 926.2 0.000373 0.4041 

Overall Mean 124 1896.8 0.001363 1.9959 

Std 52 1115.4 0.001003 1.4024 

Median 129 1425.3 0.001222 1.5711 

Geo Mean 112 1547.1 0.001112 1.6762 

95th%tile 190 3618.8 0.002458 4.7795 
Page 23 of 40 

2.4 Evaluation of Scenario Benchmark Objective 

 Benchmark Objective -- The data from the two wipe studies have been analyzed to see if 

the two wipe scenarios meet the AEATF II objective of a relative 3-fold accuracy (i.e., K=3). 

Using the SAS code originally 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 wipe study results meet 

the 3-fold relative accuracy objective. Appendices A and B provide the detail benchmark 

analysis which is summarized as follows: 

 Benchmark Objective: fold Relative Accuracy (fRA) 

The 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 (RTU 

Wipes) and Figures 6 to 9 (Trigger Spray & Wipe) for the 3 clothing configurations as well as 

inhalation exposure. These plots support the assumed lognormal distributions for the normalized 

exposure. Note: The figure titles are provided both above and below the graphs because they 

were cut and pasted as file images. 

Quantile plot normalized long dermal exposure data with a lognormal distribution

Normalized by Pounds Active Ingredient Handled

-2 -1 0 1 2

6.0

6.5

7.0

7.5

8.0

8.5

9.0

log (Normalized Long Dermal Exposure)

Normal Quantiles

Figure 2. RTU Wipes: Quantile plot of normalized long dermal exposure data with a 

lognormal distribution normalized by pounds of Active Ingredient handled. 
Page 24 of 40 

Quantile plot normalized short dermal exposure data with a lognormal distribution

Normalized by Pounds Active Ingredient Handled

-2 -1 0 1 2

6.0

6.5

7.0

7.5

8.0

8.5

9.0

log (Normalized Short Dermal Exposure)

Normal Quantiles

Figure 3. RTU Wipes: Quantile plot of normalized short dermal exposure data with a 

lognormal distribution normalized by pounds of Active Ingredient handled. 

Quantile plot normalized long short dermal exposure data with a lognormal distribution

Normalized by Pounds Active Ingredient Handled

-2 -1 0 1 2

6.0

6.5

7.0

7.5

8.0

8.5

9.0

lnnrmdermls

Normal Quantiles

Figure 4. RTU Wipes: Quantile plot of normalized long short dermal exposure data with a 

lognormal distribution normalized by pounds of Active Ingredient handled. 
Page 25 of 40 

Quantile plot normalized inhalation exposure data with a lognormal distribution

Normalized by Pounds Active Ingredient Handled

-2 -1 0 1 2

-5

-4

-3

-2

-1

0

1

log (Normalized Inhalation Exposure)

Normal Quantiles

Figure 5. RTU Wipes: Quantile plot of normalized inhalation exposure data with a 

lognormal distribution normalized by pounds of Active Ingredient handled.

Quantile plot normalized long dermal exposure data with a lognormal distribution

Normalized by Pounds Active Ingredient Handled

-2 -1 0 1 2

5.5

6.0

6.5

7.0

7.5

8.0

8.5

log (Normalized Long Dermal Exposure)

Normal Quantiles

Figure 6. Trigger Spray & Wipe: Quantile plot of normalized long dermal exposure data 

with a lognormal distribution normalized by pounds of Active Ingredient handled.
Page 26 of 40 

Quantile plot normalized short dermal exposure data with a lognormal distribution

Normalized by Pounds Active Ingredient Handled

-2 -1 0 1 2

6.5

7.0

7.5

8.0

8.5

9.0

log (Normalized Short Dermal Exposure)

Normal Quantiles

Figure 7. Trigger Spray & Wipe: Quantile plot of normalized short dermal exposure data 

with a lognormal distribution normalized by pounds of Active Ingredient handled.

Quantile plot normalized long short dermal exposure data with a lognormal distribution

Normalized by Pounds Active Ingredient Handled

-2 -1 0 1 2

6.5

7.0

7.5

8.0

8.5

lnnrmdermls

Normal Quantiles

Figure 8. Trigger Spray & Wipe: Quantile plot of normalized long short dermal exposure 

data with a lognormal distribution normalized by pounds of Active Ingredient handled.
Page 27 of 40 

Quantile plot normalized inhalation exposure data with a lognormal distribution

Normalized by Pounds Active Ingredient Handled

-2 -1 0 1 2

-1

0

1

2

3

4

log (Normalized Inhalation Exposure)

Normal Quantiles

Figure 9. Trigger Spray & Wipe: Quantile plot of normalized inhalation exposure data 

with a lognormal distribution normalized by pounds of Active Ingredient handled.

 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 8 below presents the results for the ready-to-use wipes scenario, for the 

long pants, short-sleeved shirt and the inhalation exposures. Table 9 below presents the results 

for the trigger spray and wipe scenario, 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 Appendices A and B, Table 3 (long pants, long-sleeved shirt) and Appendices A and 

B, Table 4 (short pants, short-sleeved shirt). 
Page 28 of 40 

Table 8. RTU Wipes: 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 (mg/m3/lb ai) 95% CI fRA 

GMS 2068.5 1170.4 – 

3630.9 1.8 0.13 0.07 – 0.26 2.0 

GSDS 1.9 1.5 – 2.6 1.4 3.70 2.41 – 5.69 1.5 

GMM 2068.5 1170.4 – 

3630.9 1.8 0.13 0.07 – 0.26 2.0 

GSDM 1.9 1.5 – 2.9 1.5 3.73 2.43 – 5.92 1.6 

ICC 0.5 0.0 – 0.8 0.05 0.0 – 0.47 

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 2449.3 1356.7 – 

4526.5 1.8 0.29 0.12 – 0.71 2.5 

AMU 2505.4 1375.5 – 

4613.8 1.8 0.30 0.13 – 0.77 2.5 

AMM 2583.6 1397.7 – 

4916.1 1.9 0.31 0.13 – 0.81 2.6 

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 5526.7 2753.6 – 

14895.8 2.7 2.07 0.40 – 6.70 5.2 

P95U 5726.4 2726.2 – 

11872.3 2.1 1.11 0.40 – 2.94 2.8 

P95M 6194.8 2783.4 – 

14093.2 2.3 1.13 0.41 – 3.09 2.8 

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
Page 29 of 40 

Tables 3, 4, 5 and 6 of Appendices A and B also present confidence intervals computed 

using a non-parametric bootstrap approach instead of the bootstrap parametric approach, as 

suggested by HSRB reviewers of the mop study. The parametric bootstrap approach assumes that 

the exposure data were generated from the fitted lognormal mixed model. The non-parametric 

bootstrap approach assumes that the data were generated using a simple random sample from 

each cluster. For the RTU wipe scenario, the parametric and non-parametric bootstrap 

confidence intervals were generally similar for inhalation exposure, but the non-parametric 

bootstrap intervals tended to be narrower than the parametric bootstrap intervals for dermal 

exposure. For the Trigger Spray & Wipe scenario, the parametric and non-parametric bootstrap 

confidence intervals were generally similar for dermal exposure, but the non-parametric 

bootstrap intervals tended to be narrower than the parametric bootstrap intervals for inhalation 

exposure. 

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

for the wipe scenarios for all 3 clothing scenarios and inhalation exposures for all 3 statistical 

models, except (as highlighted in yellow in the tables) for the empirical 95th percentile for the 

inhalation exposure where the fold relative accuracy is 5.2 for the RTU Wipes scenario (Table 8 

above) and is 3.6 for the Trigger Spray & Wipe scenario (Table 9 above). 

Table 9. Trigger Spray & Wipe: 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 (mg/m3/lb ai) 95% CI fRA 

GMS 1325.1 1016.8 – 

1735.7 1.3 6.7 3.1 – 14.4 2.2 

GSDS 1.7 1.4 – 2.1 1.2 2.7 1.9 – 4.1 1.5 

GMM 1325.1 1016.8 – 

1735.7 1.3 6.7 3.1 – 14.4 2.2 

GSDM 1.7 1.4 – 2.1 1.2 2.9 1.9 – 4.7 1.6 

ICC 0.0 0.0 – 0.4 0.3 0.0 – 0.7 

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 1544.7 1150.0 – 

2021.2 1.3 10.2 4.5 – 25.2 2.5 

AMU 1531.9 1160.2 – 

2038.8 1.3 11.0 4.7 – 26.6 2.4 

AMM 1533.3 1162.6 – 

2050.8 1.3 11.6 4.8 – 29.9 2.6 

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 4841.8 2138.5 – 

6653.3 2.3 46.3 12.8 – 153.4 3.6 

P95U 3213.0 2138.3 – 

4753.6 1.5 34.8 12.6 – 92.8 2.8 

P95M 3222.2 2148.2 – 

4835.4 1.5 37.5 13.0 – 109.6 2.9 

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
Page 30 of 40 

Presumption of Proportionality -- EPA evaluated the presumption of proportionality 

between exposure and amount of active ingredient handled (AaiH). EPA tested proportionality 

using a statistical benchmark 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. If slope is positive, not zero and not 

1 then the exposure tends to increase with the AiaH but not proportionally, so that, for example, 

doubling the AiaH will not tend to double the exposure. If the slope confidence interval 

excludes both 1 and 0 then the statistical evidence rejects both proportionality and independence 

and shows that the exposure tends to increase with the AiaH but not proportionally. Note: the 

slope measures the change in log mg dermal exposure for each unit change in log lb ai. 

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

measures” model (see Appendix A page 36 or Appendix B page 34 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. Appendices A and B also provide an analysis of 

the proportionality for each of the three clothing configurations for each scenario. For the RTU 

Wipes scenario, all three clothing configurations did not show proportionality and did not show 

independence. However, for this same scenario, the alternative approach in the Appendix to 

Appendix A shows proportionality to the wiping duration, For the Trigger Spray and Wipe 

scenario, the results of the proportionality analysis for the three 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 

measures”) 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 measures model. 

The resulting regression slope and confidence intervals for the two wipe scenarios are 

summarized in Tables 10 and 11 and in Figures 10 to 13 (for the long pants, short-sleeved shirt 

dermal exposure and for inhalation exposure) below. To calculate the confidence intervals, the 

Kenwood-Rogers method was used to estimate the denominator degrees of freedom for the 

repeated measures models and for the mixed-effect regression with a non-zero estimated ICC. 

However, following comments from HSRB reviewers of the mop study analyses, we used the 

containment method to estimate the denominator degrees of freedom for the mixed-effect 

regression with a zero estimated ICC, since in those cases the Kenwood-Rogers method ignores 

the uncertainty of the estimated ICC and produces a confidence interval that is too narrow. 

Note that a confidence interval width of 1.4 (or less) indicates at least 80% statistical 

power, which was achieved for dermal exposures and almost achieved (width = 1.47 for RTU 

Wipes) for inhalation exposures. Although the slopes are positive, the results for the dermal 

models indicate that exposure is not directly proportional (1:1) to AaiH (i.e., the confidence 

interval does not include 1) and also indicate that exposure is not independent of AiaH (i.e., the 

confidence interval does not contain 0, except for the trigger spray and wipe scenario long pants 

and long-sleeves dermal exposure). The results for the inhalation models indicate that exposure 

is not directly proportional (1:1) to AaiH (i.e., the confidence interval does not include 1) and 

suggest that exposure is independent of AiaH (i.e., confidence interval contains 0). For more 
Page 31 of 40 

details including results for other normalizing variables, the reader is referred to Appendices A 

and B, Tables 8, 8b, 8c, 8d, and 8e. 

Table 10. RTU Wipes: Results of Analysis of Proportionality for Dermal and Inhalation Exposure.

Exposure 

Route Clothing Model Slope 

Confidence 

Interval 

Confidence 

Interval 

Width 

Dermal (mg) Long pants 

and long 

sleeves 

Mixed 0.56 0.28 – 0.85 0.57 

 Short pants 

and short 

sleeves 

Mixed 0.48 0.15 – 0.81 0.66 

 Long pants 

and short 

sleeves 

Mixed 0.50 0.21 – 0.80 0.59 

 Any Repeated 

Measures 

0.54 0.12 – 0.87 0.66 

Inhalation 

(mg/m3) 

 Mixed -0.15 -0.89 – 0.58 1.47 

Table 11. Trigger Spray & Wipe: Results of Analysis of Proportionality for Dermal and Inhalation Exposure.

Exposure 

Route Clothing Model Slope 

Confidence 

Interval 

Confidence 

Interval 

Width 

Dermal (mg) Long pants 

and long 

sleeves 

Mixed 0.37 -0.02 – 0.76 0.78 

 Short pants 

and short 

sleeves 

Mixed 0.57 0.21 – 0.93 0.73 

 Long pants 

and short 

sleeves 

Mixed 0.58 0.20 – 0.97 0.77 

 Any Repeated 

Measures 

0.49 0.03 – 0.96 0.93 

Inhalation 

(mg/m3) 

 Mixed 0.25 -0.46 – 0.96 1.42 
Page 32 of 40 

Figure 10. RTU Wipes: Mixed and simple linear regression plots for long short dermal 

exposure
Page 33 of 40 

Figure 11. RTU Wipes: Mixed and simple linear regression plots for inhalation exposure. 
Page 34 of 40 

Figure 12. Trigger Spray & Wipe: Mixed and simple linear regression plots for long short 

dermal exposure. 
Page 35 of 40 

Figure 13. Trigger Spray & Wipe: Mixed and simple linear regression plots for inhalation 

exposure. 

Threshold of AaiH for Over- or Under-Predicting Exposure -- Although the confidence 

intervals for the regression slopes are below one, it is shown in Appendices A and B that if the 

mixed model formulation is correct and the estimated regression slope is less than one, then the 

exposure will be over-predicted if the proportionality model is extrapolated to high levels of the 

amount of active ingredient and the exposure will be under-predicted at low levels of the amount 

of active ingredient. Tables 12 and 13 give the minimum amount of active ingredient handled for 

which the proportionality model will over-estimate the expected exposure. 
Page 36 of 40 

Table 12. RTU Wipes: Minimum Pounds of Active Ingredient for Which Normalized Exposure Model OverPredicts Dermal and Inhalation Exposure.

Exposure 

Route Clothing Model Slope Threshold Level (lb AiaH) 

Dermal (mg) Long pants 

and long 

sleeves 

Mixed 0.56 0.00033 

 Short pants 

and short 

sleeves 

Mixed 0.48 0.00039 

 Long pants 

and short 

sleeves 

Mixed 0.50 0.00038 

Inhalation 

(mg/m3) 

 Mixed -0.15 0.00028 

Table 13. Trigger Spray & Wipe: Minimum Pounds of Active Ingredient for Which Normalized Exposure 

Model Over-Predicts Dermal and Inhalation Exposure.

Exposure 

Route Clothing Model Slope Threshold Level (lb AiaH) 

Dermal (mg) Long pants 

and long 

sleeves 

Mixed 0.37 0.00081 

 Short pants 

and short 

sleeves 

Mixed 0.57 0.00080 

 Long pants 

and short 

sleeves 

Mixed 0.58 0.00078 

Inhalation 

(mg/m3

) 

 Mixed 0.25 0.00053 

In response to suggestions from HSRB reviewers of the mop study analyses, we also 

considered quadratic models for the relationship between the logarithm of exposure and the 

logarithm of the amount of active ingredient. Appendices A and B present the equations for the 

quadratic models and discuss their applicability for predicting exposures attributable to use of 

antimicrobial pesticides. For both scenarios, and in all cases, the quadratic coefficient was not 

statistically significantly different from zero, so we concluded that the quadratic models are not 

supported and that the simple linear models discussed here are preferred. 

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 (Christian 2007). This wipe study represents two 

exposure scenarios in the overall design of an AEATF II generic handler data base. This wipe 

study was designed to represent the high end of potential exposure for RTU wipes and trigger 
Page 37 of 40 

spray and wipe activities. 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 wiping 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 wiping surfaces 

inside buildings in Fresno are not substantially different than wiping surfaces inside other 

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

monitoring program, the assumption that indoor wiping of surfaces does not vary 

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

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 wiping surfaces. This includes the pesticide products that are packaged as RTU 

wipes or the products that indicate they can be applied by spray and wipe. 

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

configurations of long pants, long-sleeved shirts, and no gloves; long pants, short-sleeved 

shirts, and no gloves; as well as short pants, short sleeved-shirts, 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 wipers (e.g., wipers that did not volunteer), 

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

winter versus summer, night versus 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) The wipe study report noted: “There were always three to four study personnel following 

the subject during a given monitoring event”, with one being the “observer”. The HSRB 

review of the protocol discussed the Hawthorne Effect and cautioned the researchers on 

observing the workers as they worked. The Hawthorne Effect is 
Page 38 of 40 

(http://psychology.about.com/od/hindex/g/def_hawthorn.htm) ... “A term referring to the 

tendency of some people to work harder and perform better when they are participants in an 

experiment. Individuals may change their behavior due to the attention they are receiving 

from researchers rather than because of any manipulation of independent variables. This 

effect was first discovered and named by researchers at Harvard University who were 

studying the relationship between productivity and work environment. Researchers 

conducted these experiments at the Hawthorne Works plant of Western Electric. The study 

was originally commissioned to determine if increasing or decreasing the amount of light 

workers received increased or decreased worker productivity. The researchers found that 

productivity increased due to attention from the research team and not because of changes 

to the experimental variable. Later research into the Hawthorne effect has suggested that 

the original results may have been overstated. In 2009, researchers at the University of 

Chicago reanalyzed the original data and found that other factors also played a role in 

productivity and that the effect originally described was weak at best.” It is unknown what, 

if any, effect the observers had on the workers’s potential exposure. The AEATF II is again 

cautioned for future research on the need for less obtrusive observations during the 

monitoring event balanced with the need to collect information on the event itself. 

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

of the two wipe study scenarios show that dermal exposure tends to increase with AaiH but 

that the proportionality is not a one-to-one ratio. The choice of normalizing variable of 

AaiH is based upon considerations of suitability for product labeling and consistency 

between scenarios. The lack of a direct proportionality of exposure to AaiH when 

extrapolating to the high end of AaiH – the EPA regulates on the high end of AaiH – tends 

to overestimate the exposure, resulting in conservative risk assessments and human health 

protective regulatory decisions. Tables 12 and 13 above provide for the minimum amount 

of AaiH for the normalized exposures to be over-predicting exposures (i.e., protective of 

human health). Data will continue to be collected by the AEATF II to add to the knowledge 

base of normalized exposures. 

4.0 Conclusions 

EPA has reviewed the AEATF II wipe 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 wipe 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 wiping of surfaces using either RTU wipes or a trigger sprayer and subsequent 

wipe with a rag using 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 95th percentile for the 

inhalation exposure where the fold relative accuracy is 5.2 for the RTU Wipes scenario 

and is 3.6 for the Trigger Spray & Wipe scenario (see Tables 8 and 9). 

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

independence between exposure and AaiH for both dermal and inhalation routes of 
Page 39 of 40 

exposure. A direct proportionality (1:1 relationship) between inhalation or dermal 

exposure and AaiH was not established but the trend of dermal exposure increases as 

AaiH increases. Additionally, Tables 12 and 13 provide thresholds that are minimum 

AaiH values where exposure will be over-estimated when extrapolating the normalized 

exposure (mg/lb ai) to other chemical assessments (i.e., using these unit exposures as 

surrogates to assess other chemicals that handle more than the threshold). 

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 Wipe 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.

MRID 48375601. Selim, S., and Taylor, M. (2011) A Study for Measurement of Potential 

Dermal and Inhalation Exposure During Application of a Liquid Antimicrobial Pesticide Product 

Using Trigger Spray and Wipe or Ready-to-Use Wipes for Cleaning Indoor Surfaces. 

Unpublished study prepared by Golden Pacific Laboratories, LLC, under Project No. AEA02, 

Report No. 070264. 2000 p. (MRID 48375601) 

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 2 to MRID 

48210201. Unpublished study prepared by Golden Pacific Laboratories, LLC, under Project No. 

AEA03, Report No. 070265. 35 p. (MRID 48231901) 

Christian, M. 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. 

Popendorf W, Selim M, and Kross, B. 1990. Chemical Manufacturers Association Antimicrobial 

Exposure Assessment Study. MRID No. 41412201. 
Page 40 of 40 

Appendix A 

Statistical Review of the AEATF II Wipe Study for Ready-to-use Wipes 

(Attached in a separate electronic .pdf file) 

Appendix B 

Statistical Review of the AEATF II Wipe Study for Trigger Spray & Wipe 

(Attached in a separate electronic .pdf file)