AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 1 of 194
Antimicrobial Exposure Assessment
Task Force II (AEATF II)
VOLUME 5
Governing Document
for a Multi-Year
Antimicrobial Chemical
Exposure Monitoring Program
Interim Draft Document
February 13, 2008
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TABLE OF CONTENTS
1	Introduction	4
1.1	Overview of Antimicrobial Pesticides and Their Benefits	4
1.2	Regulatory Need for Estimation of Exposures to Antimicrobial Pesticides	8
1.3	Purpose of the Governing Document	10
2	Specific Objectives of the AEATF II Monitoring Program	12
3	AEATF II and BHED™	14
4	Regulatory Need for Generic Exposure Data	15
5	Description of AEATF II Monitoring Program and Scenarios	18
6	Limitations of Existing Data and Justification for Supplemental or Confirmatory
Data	20
7	Alternatives to Additional Human Monitoring	26
8	Ethical Considerations	27
8.1	Subject Recruitment Process	27
8.1.1	Identification and Recruitment of Potential Subjects	28
8.1.2	Exclusion of Vulnerable Group(s)	32
8.2	Informed Consent Process	33
8.3	Subj ect Remunerati on	36
8.4	IRB Review Process	38
8.5	Additional Efforts to Protect Human Subjects	40
9	Study Benefits	41
9.1	Benefits to Subjects	42
9.2	Benefits to Society	42
9.3	Likelihood of Realization of Benefits	43
10	Study Risks	43
10.1	Description of Potential Risks to Subjects	43
10.2	Risks of Heat-Related Illness	44
10.3	Risks of Exposure to Surrogate Antimicrobial Pesticides	45
10.4	Risks of Exposure to Face/Neck and Hand Wash Solution	45
10.5	Psychological Risks	46
11	Procedures for Monitoring and Preventing Risk to Subjects	47
11.1	Medical Management and Stop Rule	48
11.2	Additional Procedures for Monitoring or Preventing Risk to Subjects	49
12	Risk Assessment for Anticipated Exposures to Proposed Surrogate Chemicals	50
13	Risk Versus Benefit Comparison	50
14	Characterization of Potential Study Participants, Exposure Monitoring Methods and
Ancillary Information	51
14.1	Subject Characteristics	51
14.2	Exposure Monitoring Techniques	52
14.3	Role of Ancillary Study Information	56
15	Incorporation of Existing Data into BHED™	57
16	Monitoring Event Selection	58
16.1	Predicting Future Generic Exposures with Monitoring Events	58
16.2	Determining the Number of Monitoring Events	60
16.2.1	The Two-Stage ME Selection Process	60
16.2.2	The Two-Stage Random Sampling Reference Model	61
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16.2.3	Benchmark Objective	62
16.2.4	Sample Size	63
16.3 General Diversity Selection Guidelines	63
16.3.1	Stratified Diversity Selection	64
16.3.2	Diversity Selection of First-Stage Units	65
16.3.3	Diversity Selection of Second-Stage Units	65
17	Description and Role of AEATF II Studies	66
18	Documentation Procedures	67
19	Quality Assurance Procedures	68
20	Quality Control Procedures	68
21	Reporting Process	70
22	Scenario Monographs	71
23	Evaluation of Data Adequacy for Completed BHED™ Scenarios	72
23.1	Benchmark Adequacy of the Completed Scenario	72
23.2	The Impact of Ignoring Clusters	73
24	References	75
Appendix A: AEATF II Scoping Document:	79
Appendix B. Antimicrobial Product Use Sites and Categories	92
Appendix C. Glossary of Terms	110
Appendix D. AEATF II Acceptance Criteria for Existing Studies	119
Appendix E. Designing Monitoring Events to Predict Future Exposure under
Antimicrobial Handling Scenarios	124
Appendix F: Evaluation of Existing PHED Applicator Exposure Data for Hand-Held
Aerosol Spray	141
Appendix G: List of Current AEATF II Standard Operating Procedures (SOPs)	192
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1 Introduction
Microorganisms grow anywhere moisture and nutrients are available.
Antimicrobial pesticides are essential to control microorganisms that otherwise
would result in economic losses, wasted resources, and human and animal
illness. Generally, U.S. Environmental Protection Agency (EPA) regulates as
pesticides those antimicrobials that target microorganism growth on inanimate
objects. Pesticides and pesticide products are defined by EPA in the Federal
Insecticide, Fungicide and Rodenticide Act (FIFRA; EPA 1989), 40 CFR (Code of
Federal Regulations), Section 2(u), Parts 152.3 and 152.15. Other categories of
chemicals that control microorganisms used as drugs and in human and animal
food and human personal care and cosmetic products are regulated by the U.S.
Food and Drug Administration (FDA). Only those categories regulated by EPA
are discussed here.
1.1 Overview of Antimicrobial Pesticides and Their Benefits
Antimicrobials are broadly grouped as "public health" or "nonpublic health"
depending on whether or not claims are made to control microorganisms
pathogenic to man and which occur on inanimate objects. However, that simple
grouping does not adequately identify the uses or benefits of antimicrobial
pesticides.
A. Public health antimicrobial pesticides are those that carry claims to control
on environmental surfaces microorganisms that are pathogenic to man. Claims
to sanitize, disinfect, or sterilize are considered de facto claims to control
microorganisms pathogenic to man (including bacteria, fungi, and viruses).
However, these products are used across a very broad range of use sites and
applications, including everything from hospital surfaces to home bathrooms,
from restaurant food processing and handling areas to the home kitchen, from
municipal drinking water systems and municipal swimming pools to the backyard
swimming pool, and from commercial or hospital laundries to everyday home
laundry use. These products are regularly used in homes, offices, schools,
hospitals, restaurants, food processing facilities, and a large variety of industrial
facilities as well as farm and animal premises. These products also are used to
help ensure that the water we drink is not contaminated by pathogenic
microorganisms.
In order to obtain an EPA registration, all antimicrobial products that make a
public health claim must submit efficacy data based on specific application
instructions and conducted according to strict protocols and must document a
very high level of performance under stringent conditions. Efficacy testing is a
requirement and is defined under FIFRA in 40 CFR Part 158.640. These
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products help to provide protection against food-borne diseases produced by
Salmonella or E. coli. as well as against pathogens such as Staphylococcus.
Norovirus, SARS, and HIV/AIDS virus.
These products include common and well-known chemicals such as hydrogen
peroxide and sodium hypochlorite, as well as a large number of other
compounds. The following is a partial list of sites where public health
antimicrobial pesticides can be used:
•	Hospitals, nursing homes, medical and dental offices, sick
rooms, and hospices
•	Homeless and emergency shelters, locker rooms, and
communal living quarters
•	Meat and poultry, seafood, processed food, beverage and dairy,
and other food storage and processing facilities, agricultural
premises, animal premises and farms
•	Restaurants, cafeterias, and institutional food services industry
•	Residences, schools, public facilities, senior and child day care
facilities
•	Public water treatment facilities, personal and emergency water
treatments
•	Swimming pools, hot tubs, whirlpools, and related facilities
B. Nonpublic health antimicrobial pesticides are all antimicrobial pesticides
other than those that claim to control microorganisms pathogenic to man. These
include antimicrobial pesticides to control, on environmental surfaces, diseases
pathogenic to animals but not to man (such as hoof and mouth disease, bird flu
in poultry houses, various diseases in kennels or veterinary facilities). However,
this grouping also includes a diverse range of products that provide protection
against microbial degradation, contamination or fouling to inanimate articles,
substances, systems or processes. Essentially any organic system in the
presence of moisture is subject to attack by microorganisms, and prevention of
such attack helps preserve critical resources, extend the useful life of the items,
minimize disposal, and improve the overall utility of those articles, substances,
systems, and processes. In many cases, the use of an antimicrobial also can
minimize or obviate the need for the use of other chemicals or treatments later on
that can result in greater human or environmental exposure. These
antimicrobials also are used to improve energy efficiency. Included within this
category are the following types of antimicrobial pesticides:
1. Material preservatives: Virtually all water-based products are subject to
microbial decay. If microbial growth is uncontrolled, the in-service or shelf life of
manufactured goods is significantly reduced, resulting in economic losses and
wasted resources. Following is a partial list of products that must be preserved
to prevent premature deterioration and decay. The need to dispose of spoiled
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products wastes resources and could increase substantially the burden on the
environment.
Latex emulsions
Paints and coatings
Pigment dispersions
Slurries
Adhesives, caulks and joint compounds
Printing ink
Non-clothing textiles (e.g., fire hoses, tarpaulins, cordage, and canvas)
Leather and suede
Cotton and wool fabrics
Paper and package coatings and additives
Lumber, wood, plywood, particleboard, and other cellulose-derived
materials
Plastics, vinyls and polyurethane
Polymer emulsions
Detergents, cleaners and other consumer products
Jet fuel and other petroleum-derived fuels
Concrete admixtures
Many of these products would be impractical without antimicrobials to preserve
them. As an example, latex paints are easier to clean up, have lower odor and
lower levels of volatile organic carbons than oil and solvent-based formulations.
However, bacteria can proliferate in the water-based latex medium. Bacterial
action produces enzymes which can destroy the thickeners in paint overnight.
Gases resulting from bacterial metabolism not only result in foul odors, but also
bursting cans, an obvious safety hazard. Incorporating an antimicrobial prevents
bacterial growth in cans containing latex paint. In fact, antimicrobials made this
product possible.
Similar situations exist for a wide variety of products, including water-based
adhesives, latex emulsions, pigment dispersion, caulking compounds, and
others. Spoilage of any of these products can result in gas formation, offensive
odors, color changes, viscosity loss, and pH drift, any one of which may mean
loss of functionality. These products, which along with paint represent nearly $20
billion to the US economy, require the use of antimicrobials.
2. Poultry houses, Egg Producing Facilities, Milking Houses and Other
Agricultural Premises
Disinfectants, virucides, fungicides, and sanitizers control or eliminate animal
pathogens. This has become increasingly important as increased international
movement has led to the spread of devastating animal diseases such as foot and
mouth disease, Newcastle disease, and avian flu.
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3.	Water Treatment
a.	Comfort Cooling. HVAC. etc. - Water must be treated to control the
growth of microorganisms that, left uncontrolled, could reduce efficiency and
increase energy usage, pit and corrode equipment as well as causing fouling and
malodors.
b.	Cooling Water Systems - Water is used for cooling industrial processes
and as a means of heat exchange. Any industrial processor that produces heat,
either incidentally, as in, nuclear power plants, other utilities, or those sites
running heavy equipment, must use coolants to maintain desirable temperature
ranges and prevent overheating. Otherwise, systems become fouled, equipment
is damaged, energy consumption increases, and processes fail. For example,
electrical utilities and many manufacturing facilities use water for process cooling.
To minimize consumption, the water is cooled and re-circulated. If untreated,
microbial deposits will form in the system resulting in reduced efficiency yielding
increased production costs, increased energy consumption, and increased water
requirements. In extreme cases, biological fouling can compromise the integrity
of the industrial equipment due to the corrosivity of bacterial waste products.
c.	Industrial Process Waters - Many processes depend upon water as a
key component of processing (e.g., pulp and paper mills). Treatment is
necessary to prevent odor, clogging and fouling of systems, protect equipment
from corrosion, and reduce energy needs and treatment of water prior to
discharge. Unrestrained microorganism growth in pulp and paper mills interferes
with paper quality by degrading and staining pulps, causing transparent slime
spots, decreasing durability, and chemically degrading fibers.
4.	Marine Antifoulants
Any submerged surface is rapidly fouled with micro- and macro-organisms. On
ships and boats, fouled bottoms decrease maneuverability and safety, increase
energy consumption, while reducing speed and performance. Antifoulants
dramatically decrease the growth of fouling organisms for up to five years. They
also reduce the spread of invasive alien species, which can have highly
detrimental economic and environmental impacts and also can pose threats to
human, animal and plant life. When incorporated into paint on the hull of ships,
antimicrobials prevent biological deposits. A slime layer only one millimeter thick
on the hull can reduce speed by 15% and increase fuel costs by more than $1
million in a single year. Heavier deposits not only cause further speed reductions
and loss of maneuverability, they can result in corrosion and limit the life of the
coating, requiring premature dry-docking. With every six-month extension of the
time between dry-docking for the world's fleet, the use of antimicrobials results in
estimated annual cost savings of over $800 million.
5.	Metalworking Fluids
Metalworking fluids are used at thousands of manufacturing facilities to cool and
lubricate metal parts being drilled, milled, ground, or otherwise worked.
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Functioning also to prevent corrosion and flush metal chips from the worksite, the
fluids are particularly prone to microbial contamination. Microbial growth causes
offensive odors and plugs equipment lines leading to corrosion and blemishes on
the finished surfaces, loss of productivity from slowed equipment speeds and
necessitating more frequent changes of fluid resulting in unnecessary fluid
replacement costs as well as increased fluid disposal. Antimicrobials are
essential for optimizing fluid life, fluid functionality, and worker comfort and
productivity. While this is effectively a material preservative use, it is considered
separately from the US EPA regulatory perspective.
6. Wood Treatment
Wood rots readily and its organic components provide all the nutrients that
bacteria and fungi require for growth. Failure to control decay organisms will
result in structural failure, reduced life cycle, and increased disposal
requirements. The use of wood preservative chemicals protects a significant
resource (wood) and can extend the useful life of wood products from just 2-5
years to more than 20 years, resulting in a significant protection of existing
forests. Treatment with antimicrobials is vital for wood used structurally in
buildings. Wood treatment chemicals also can be used to prevent growth of
algae and molds on the surfaces of wood and to prevent the permanent staining
of cut lumber by microorganisms, i.e., sapstain. Wood treatment antimicrobials
are used on newly cut wood surfaces, kiln dried wood, milled wood and other
building materials. A wide variety of seasoned/unseasoned, indoor/outdoor, and
terrestrial/marine/aquatic wood items and surfaces are treated with wood
preservatives. The types of wood products include fresh-cut logs or lumber,
seasoned building materials, utility poles and fence posts and rails (prior to or
after being placed in service), structural members, structures, dwellings,
transportation vehicles, crop growing/harvesting/shipping/storage containers,
lawn furniture, playground equipment, garden/landscape timbers, and log homes.
1.2 Regulatory Need for Estimation of Exposures to Antimicrobial
Pesticides
EPA regulates pesticides under the statutory authority of the Federal Insecticide,
Fungicide, and Rodenticide Act (FIFRA). Currently, antimicrobials registered
prior to November 1, 1984, are going through a re-registration process. Starting
in 2007, all antimicrobials also will be reviewed on a 15-year cycle as part of
EPA's "registration review" program. In both programs, EPA must determine
whether, when used according to the labeled directions, there is a reasonable
certainty of no harm to humans and no unreasonable risks to the environment.
In addition, new products, new uses and major amendments to existing
antimicrobial products must undergo similar review and determination.
Antimicrobial pesticides are managed by the U.S. EPA's Office of Pesticide
Programs (OPP), Antimicrobials Division.
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EPA has typically based its exposure assessments for antimicrobials on rules of
thumb, some based on registrant reports of industrial hygiene or other non-
pesticide guideline exposure information and some based on EPA-derived
information. Following passage of the Food Quality Protection Act of 1996, EPA
produced a number of screening level occupational and residential risk
assessment guidelines in the form of draft standard operating procedures.
Although data exist, albeit with limitations, to estimate potential exposures to
agricultural handlers, i.e., the Pesticide Handlers Exposure Database (PHED;
EPA 1988), no such database exists for occupational subjects handling
antimicrobials, outside of limited data (Popendorf et al., 1992) generated by the
Chemical Manufacturers Association (CMA, now the American Chemistry
Council or ACC). Further, only limited antimicrobial exposure monitoring data
exist to support quantitative exposure analyses to this class of pesticides. In the
past ten years, a few occupational exposure monitoring studies involving
antimicrobials have been submitted to EPA; however, they have limited utility as
they cover only certain use patterns. Some of the data generated from these
studies have a high degree of uncertainty due to low numbers of samples for a
particular use pattern or insufficient sensitivity in analytical detection. Because
most antimicrobial pesticides are used in indoor environments, the potential
exposure from the use of these products could be substantially different from
handling agricultural pesticides outdoors. Thus, EPA must either to try to use
agricultural exposure data for industrial and consumer antimicrobial-related
assessments or use assumptions and predictive models that have not been
validated to support their exposure assessments and related decision making
processes.
In 2001 (letter from Margaret Stasikowski, Director, Health Effects Division to
Daniel Fay, Valent USA Corporation, 16 March 2001), EPA outlined its
prospective plans regarding the existing agricultural exposure data contained in
the Pesticide Handlers Exposure Database (PHED). The letter stated EPA's
intention to drastically overhaul PHED version 1.1 because many of the existing
exposure studies in the database were outdated or scientifically inadequate by
"today's standards". In addition, many exposure scenarios that are being
assessed by the Agency are under-represented in PHED version 1.1. This is
particularly apparent with antimicrobial pesticides, where potential exposures are
very different from those associated with agricultural pesticides. Thus, there is a
clear need to generate better exposure data to improve the quality of human
health risks assessments for antimicrobial products. That need has been
repeatedly identified in regulatory decisions.
As key elements in the risk assessment process, exposure data allow for
estimation of absorbed dose, which is then compared to a relevant toxicological
endpoint from an animal dosing study. The algorithm to calculate the average
daily dose to a worker is relatively simple. The inputs require an estimate of how
much chemical is going to be handled during a work shift, a body weight, and a
measure of exposure potential based upon the activity conducted by the worker
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(by exposure route). Although there are ranges and uncertainties associated
with each of these inputs, the measure of exposure for a particular job function or
activity is where the greatest uncertainty lies.
The Agency has acknowledged that while the use of existing data and
assumptions in its human health risk assessment process for antimicrobial
products is necessary, it would also lead to overly protective labeling, a
requirement for chemical companies to develop costly product-specific
confirmatory exposure data, and even the suspension of certain uses. Thus,
according to EPA, the creation of a consortium to develop generic exposure data
on occupational activities would be a cost-effective means of generating a large
amount of high quality credible data (Stasikowski 2001).
On November 1, 2004, the American Chemistry Council (ACC) Biocides Panel
established the Antimicrobial Exposure Assessment Task Force II (AEATF II) to
measure exposure of subjects in mixing and loading operations in industrial
settings and professionals involved in application of products containing biocides
in industrial, institutional and residential settings. The AEATF II currently
consists of forty-three member companies. The purpose of this task force is to
develop generic exposure data on a broad range of use pattern/application
method combinations as well as specific post-application exposures (e.g.,
measurements of residue deposition on treated surfaces and the post-application
transferability of these residues using EPA-recommended environmental
sampling methods). Each specific set of related tasks, antimicrobial formulations,
equipment, engineering controls, and worker and/or consumer practices
considered by AEATF II is termed a scenario. These data obtained for each
antimicrobial-handling scenario addressed by AEATF II will be used to support
EPA registration and re-registration of most antimicrobial active ingredients in the
future. The concept behind a group of companies working together to generate
jointly-owned data is to reduce individual company's costs, generate more data
than would be possible by a single company or even small group of companies
alone, while providing consistency in design and execution, and obtaining
coordinated scientific input from appropriate regulatory agencies (U.S. EPA,
California Department of Pesticide Regulation or CDPR, Health Canada's Pest
Management Regulatory Agency or PMRA, and European regulatory authorities).
1.3 Purpose of the Governing Document
The purpose of this document is to provide the U.S. EPA, CDPR, PMRA and the
Human Studies Review Board (HSRB) with a description of the overall scope of
the AEATF II program, demonstrate the need for additional human exposure
monitoring data, and explain the proposed methodology for the exposure
monitoring studies proposed for conduct by the AEATF II. This document also
describes the plans of the AEATF II to develop a generic database, i.e., the
Biocide Handlers Exposure Database (BHED™). By providing this background
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information, the AEATF II intends to present a scientifically valid basis for
conducting the proposed human exposure monitoring studies.
This draft version of the "Governing Document" focuses on the technical and
ethical aspects of the AEATF II program. The governing document is being
submitted to EPA (and other regulatory agencies), and the HSRB, in conjunction
with each specific study protocol for proposed AEATF II exposure monitoring
studies. It is anticipated that future versions of this document will be issued to
incorporate comments and guidance provided by the EPA's Office of Pesticide
Programs (OPP) and the HSRB.
It is important to note that the scientific and ethical aspects of the AEATF II
program are addressed, more specifically, as part of each proposed protocol
being submitted to the EPA and HSRB. Thus, this document will be
supplemented by important study protocol-specific scientific (e.g., study or
scenario-specific study design and sample size determination) and ethical (e.g.,
how a particular AEATF II study will address recruitment, informing, seeking
consent, and minimizing risks to study participants) considerations. The ethical
components of the AEATF II program are based, in part, on recommendations
made by the National Academy of Sciences Committee on the Use of Third Party
Toxicity Research with Human Research Participants (e.g., demonstrated need
for the knowledge to be obtained from intentional human dosing studies,
justification and documentation of a research design and statistical analysis that
are adequate to address an important scientific or policy question, an acceptable
balance of risks and benefits and minimization of risks to participants, equitable
selection of participants, free and informed consent of participants, review by an
appropriately constituted IRB or its foreign equivalent) to ensure that AEATF II
exposure studies, which are to be conducted under EPA Guideline 875 Series A,
will meet the highest scientific and ethical standards.
The AEATF II program also addresses relevant feedback provided in the report
of the HSRB meeting of June 27-30, 2006 (Fisher 2006) which discusses an
initial review of five study protocols submitted by the Agricultural Handlers
Exposure Task Force (AHETF), another multi-year exposure monitoring effort.
The AEATF II program has also been informed by the recent April 18-20, 2007
HSRB meeting (http://www.epa.gov/osa/hsrb/apr-18-20-20Q7-public-
meeting.htm) and EPA's "Draft Framework for Developing Best Practices for
Recruiting, Screening, and Informing Human Subjects, and Obtaining Consent
for Occupational Exposure Studies with Pesticides" presented at this meeting.
Furthermore, the AEATF II program incorporates recent recommendations
provided by the EPA's Science Advisory Panel (EPA 2007).
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2 Specific Objectives of the AEATF II Monitoring
Program
The primary objective of the AEATF II is to generate handler exposure monitoring
studies to estimate characterize exposures distributions for a multitude of
occupational / industrial and consumer exposure scenarios involving
antimicrobial-containing products. The data from these studies will fill gaps in the
current antimicrobial exposure dataset and allow for more precise estimations of
potential dermal and inhalation occupational risks to workers and consumers
handling products containing antimicrobial agents. The study results will be
placed into a computer software database (i.e., the Biocide Handlers Exposure
Database or BHED™) allowing the data to be used generically for risk
assessments of all antimicrobial agents. The AEATF II will exercise the rights
associated with submission of data under the Federal Insecticide, Fungicide, and
Rodenticide Act (FIFRA) in connection with BHED™. The database will be
available to both AEATF II company members and regulatory agencies for
registration and re-registration purposes.
The AEATF II study program has been designed to cover the most common
types of occupational and residential handling scenarios involving antimicrobials.
Initially, EPA identified application methods and use scenarios based on a review
of antimicrobial product labels and/or Agency areas of interest, in conjunction
with 12 "Use Site Groups" that EPA has used historically to delineate
antimicrobials use sites. Some application methods have been combined and
the following Use Site Groups and 14 application methods/use scenarios have
been agreed upon by the EPA, Canadian, and California regulatory agencies and
members of the AEATF II. The EPA Use Site Groups and Application
Methods/Use scenarios include the following (see Appendices A and B for
additional explanation and information):
EPA Use Site Groups
1.	Agricultural Premises and Equipment
2.	Food Handling/Storage Establishments Premises/Equipment
3.	Commercial, Institutional & Industrial Premises/Equipment
4.	Residential and Public Access Premises
5.	Medical Premises and Equipment
6.	Human Drinking Water Systems
7.	Industrial Process Water Systems
8.	Material Preservatives
9.	Antifoulant Coatings
10.	Wood Preservatives
11.	Swimming Pools
12.	Aquatic Areas
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Application Methods/Use Scenarios
1.	Aerosol Spray
2.	High to Low Pressure Spray
3.	Pour Liquid
4.	Pump Liquid
5.	Pour Solid
6.	Place Solid
7.	Mop
8.	Wipe
9.	Fog
10.	Brush/Roll
11.	Airless Spray
12.	Immerse/Dip/Soak
13.	Pressure Treat
14.	Metalworking Fluid
Post-application scenarios are still under discussion, with the possibility of
conducting two studies - one to evaluate exposure (e.g., transferable residue
measurements) to antimicrobials on soft surfaces (such as carpet) and one to
evaluate exposure to antimicrobials on hard surfaces (such as countertops or
wood decking).
All human subject monitoring studies will be conducted using standard industrial
hygiene passive dosimetry techniques, consisting of both dermal and inhalation
monitoring. All Task Force studies will be conducted according to current EPA
Office of Pesticide Programs' Harmonized Test Guidelines - Series 875
Occupational and Residential Exposure Test Guidelines (Series 875 A and B for
handler and re-entry, respectively) and conducted under Good Laboratory
Practice standards per 40 CFR Part 160. All monitoring studies will be
conducted in compliance with all applicable provisions of EPA's regulations
providing for the protection of human subjects of research, 40 CFR Part 26. The
Task Force is designing study protocols that would allow study results to be
broadly acceptable to both North American and European regulatory authorities.
Industry-wide generic task forces go through various defined stages, with the
data generation phase of the task force typically lasting approximately eight
years. The limit of expenditures for AEATF II is set at $9 million. This is based on
the assumption that a total of 19 core studies will be conducted, with each study
containing 15 to 25 sets of individual measurements. The support costs for doing
this work, such as analytical method development, database construction, legal,
task force management, etc., are included in the stated dollar amount. This
sizeable investment by the antimicrobial industry confirms the commitment to
generate the data needed to accurately assess risks to persons using
antimicrobial products.
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3 AEATF II and BHED™
The Antimicrobial Exposure Assessment Task Force II (AEATF II) was
established to generate data for antimicrobial pesticide exposure scenarios to
meet EPA data requirements for registration. AEATF II member companies have
ongoing data requirements resulting from chemical and product-specific existing
and announced data call-in notices, anticipated re-registration obligations via
confirmatory data demands, prospective registration review obligations and
requirements based on registration applications. The member companies
agreed to jointly develop generic data in support of their respective registration
obligations since existing data are not adequate.
The primary AEATF II goal is the collection of worker exposure monitoring data
and its incorporation into a new generic database that can be used to estimate
exposure distributions. The database will be a proprietary product of the Task
Force and will be called BHED™ (Biocide Handlers Exposure Database).
BHED™ will be submitted to EPA and other regulatory agencies, and used by
those regulators to conduct detailed quantitative exposure assessments to
support safety determinations for occupational pesticide uses.
Generic databases were developed over the last twenty years in response to a
regulatory need to assess the occupational risks associated with a wide range of
pesticide handling situations. The concept was discussed first in an American
Chemical Society Symposium in 1984 (Reinert and Severn, 1985; Hackathorn
and Eberhart, 1985; Honeycutt, 1985) and its development encouraged by a
FIFRA Scientific Advisory Panel in 1986. In 1992, the Pesticide Handlers
Exposure Database (PHED) was first released following a joint effort by pesticide
manufacturers, the EPA, and Canadian regulators (Honeycutt, 1986; Lunchick,
1994, Reinert, 1986, Leighton and Nielson 1995, Nielson et al. 1995). Since
then, PHED has been used extensively in a generic manner and has successfully
supported many occupational risk assessments. However, much of the data in
PHED are derived from exposure studies that are considered outdated or
scientifically inadequate by current standards (Stasikowski, 2001). In addition,
many antimicrobial handler scenarios of interest to EPA are absent or under-
represented in PHED. Other regulatory agencies have expressed similar
dissatisfaction with the limitations of PHED data. A major purpose of BHED™ is
to address deficiencies in existing data such as those included in PHED. And in
2007, EPA convened another Science Advisory Panel SAP (SAP) to discuss the
need for new data to replace PHED and the panel agreed with EPA that
"additional data could significantly improve the Agency's ability to assess worker
exposure" (SAP, 2007). A major purpose of the BHED™ is to address PHED
deficiencies (and limitations of other existing data sources).
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Like PHED, BHED™ will be populated with exposure data for subjects who
handle antimicrobial pesticides as part of their normal job (occupational) or task
(consumer), so their participation as subjects in the studies underlying BHED™
will not add appreciably to their typical exposure from handling pesticides. All
AEATF II studies are designed and conducted in accordance with the latest U.S.
EPA guidelines for occupational exposure studies.
The development of BHED™ is funded and directed by the AEATF II. However,
an AEATF II Regulatory Agency Advisory Committee (RAAC) has been
established to promote active participation by interested regulatory agencies. The
committee is comprised of representatives of the U.S. EPA, the Canadian Pest
Management Regulatory Agency (PMRA), the California Department of Pesticide
Regulation (CDPR), and European regulatory authorities. This committee meets
on an ad hoc basis to review the program progress and provide technical input to
the AEATF II.
4 Regulatory Need for Generic Exposure Data
FIFRA requires the U.S. Environmental Protection Agency to assure that any
pesticide registered in the United States does not have unreasonable adverse
effects	on	subjects	handling	that	pesticide
(http://www.epa.gov/pesticides/regulating/laws.htm). The Pest Control Products
Act (PCPA; http://www.pmra-arla.gc.ca/english/legis/pcpa-e.html) requires a
similar determination by Health Canada. This safety determination is generally
made by means of quantitative risk assessment and risk management
procedures. Risk assessments require a detailed evaluation of the toxicity of the
pesticide and an estimation or measurement of the exposure potential for users
(and/or amount of pesticide absorbed by the individual as a consequence of its
use). Exposure or absorbed dose estimates are quantitatively compared to no-
effect exposure levels (often from experimental animals) for hazards identified in
standardized toxicology studies. During the risk evaluation, the likelihood of the
expression of any toxicological effect on the subjects and a comparison of the
risks and benefits are considered. This basic paradigm (hazard identification,
dose-response assessment, exposure assessment, and risk characterization)
was summarized by the National Academy of Sciences and has become the
standard for risk assessment by regulatory agencies (NAS, 1983; NAS, 2006).
More recently, the pesticide handler risk assessment process was fully described
in a summary document prepared for an EPA SAP review of exposure
methodologies (EPA 2007).
The AEATF II database, BHED™, is intended to provide the regulatory agencies
with the handler potential exposure data necessary for them to perform the
exposure assessment portion of safety determinations. Toxicology data and
benefit information are product-specific and must be provided by individual
pesticide product registrants.
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When estimating exposure to persons who handle pesticides, a major challenge
to overcome is that several parameters contribute to the likelihood and level of
exposure. These include things such as handling liquids versus solids, how the
product is packaged, using open versus closed systems, application with various
equipment types, how much product is handled, whether or not personal
protective equipment (PPE) is worn, and whether the worker mixes/loads or
applies the product or does both. The number of combinations of these
parameters makes it impossible to generate human exposure data for all
situations, so a number of simplifying approaches have been adopted. These
include:
1)	Establishing various 'scenarios' (see Appendix A) that cover common
combinations of these parameters and generating data for those
scenarios;
2)	Restricting some scenarios to include the higher exposure portions of
them (e.g., professional janitorial personnel performing mopping tasks
using higher exposure potential technologies such as string and bucket
mop systems);
3)	Generating data with subjects wearing minimal PPE;
4)	Using data for one chemical/product as a surrogate for another (similar)
product; and
5)	Assembling data into a generic database (e.g., BHED) for use as
surrogate data applicable to many products or for multiple job functions
performed by one person.
Since the early 1980's it has been the consensus of the scientific community that
the amount of residue that contacts a worker's clothing and skin, and the amount
of residue that is available for inhalation, are primarily a function of physical
rather than chemical factors. That is, the chemical nature of the active ingredient
in a pesticide product has little influence on the extent of exposure compared to
physical parameters associated with the use of the product. The physical
parameters include formulation type (e.g., liquid or granule product), method of
application, and the way in which a person handles the pesticide during mixing,
loading and application. Because of this, exposure potential is considered
"generic" since it is independent of the specific active ingredient (Hackathorn,
1985; Honeycutt, 1985 and 1986; Reinert, 1985). Generic exposure data may
therefore be used in lieu of product-specific data for most safety assessments.
However, some situations, such as exposure to volatile compounds, (e.g.,
chlorine dioxide) require consideration of chemical-specific adjustment factors or
modeling approaches (e.g., indoor air models).
The use of generic data enhances the efficiency of regulatory agencies in
conducting exposure assessments. Rather than relying on individual studies to
evaluate case-by-case uses of each pesticide product, a single, comprehensive
database of high quality data applicable to most products can be used. The
broad applicability of generic data and the resulting efficiency of their use in
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regulatory safety assessments led to the widespread acceptance of PHED.
PHED components were created by assembling exposure data from studies that
had already been conducted and submitted to the EPA.
Most of the pesticide exposure data available for inclusion in the initial 1992
version of PHED had been conducted by individual pesticide manufacturers who
designed their studies to support the registration of a specific product or a group
of similar products. It was very common for these companies to generate a set
of exposure data that represented the worst case for exposure potential
incorporating design features such as the maximum use rate, minimum PPE, and
minimum engineering controls. If a risk assessment was acceptable for such a
situation, then it was argued that lower use rates, additional PPE, and additional
engineering controls would certainly also pass a risk assessment. However, this
meant it was common for a study to involve 15 or more measurements of
essentially the same situation where each person handled the same product, in
the same packaging, in similar amounts, using the same equipment, and for
similar periods of time. While these studies are useful for product-specific cases,
they are not always generically useful. Nevertheless, many of these types of
studies were assembled to form PHED and collectively the database did seem to
improve the risk assessment process as regulators could often rely on larger
data sets to estimate potential exposure.
However, the available studies for inclusion in the PHED, in hindsight, were not
designed, a priori, to meet the needs of a generic database and thus, have some
technical limitations. In addition, it is now an older database and many use
practices have changed. Further, it has limited applicability to most antimicrobial
pesticide uses. Exposure monitoring methods have also changed. The basic
passive dosimetry methodology has long been accepted as a standard,
reproducible procedure that provides accurate and reliable data that does not
underestimate exposure (Ross et al., 2007). Even though the passive dosimetry
methodology is still a very sound measure of exposure, there have been some
improvements. In particular, much of the data in PHED are based on patch
dosimetry and exposures were often not measured on all body areas for each
monitoring unit or event, i.e., ME. However, PHED provided reasonable
estimates of exposure based on the technology of the 1980's. Today, whole-
body garment dosimetry is used instead of patches to improve the ability to
estimate the distribution of total body exposure.
There is general consensus among regulatory agencies that the most efficient
means of generating handler exposure data is to pool technical resources and
assemble a generic database. This consensus and the extremely limited
availability of data for antimicrobial pesticides led to the formation of the AEATF II
in November, 2004. The task force database, BHED™, will be designed to
reflect a logical set of use scenarios with adequate data in each scenario to
provide reliable estimates of exposure potential and its distribution. Individual
measurements will involve separate subjects and more diversity in equipment
and conditions than in PHED, especially for the amount of product handled.
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5 Description of AEATF II Monitoring Program and
Scenarios
The primary purpose of the AEATF II monitoring program is to develop a new
generation of more accurate and useful information and data on worker and
consumer exposures to antimicrobials. A secondary purpose is to incorporate
these data into a generic database (BHED™). These data will consist of dermal
and inhalation exposure estimates derived from monitoring subjects who handle
pesticides under a variety of circumstances, using various pesticides and
equipment types. AEATF II refers to each unique handling situation as a
'scenario' and anticipates the database will contain sufficient data to support
exposure assessments for 14 distinct handling situations, or scenarios (see
attached "AEATF II Scoping Document" provided as Appendix A; Appendix B
provides a detailed description of each use site identified in the Scoping
Document; Appendix C provides a glossary of terms).
In general, each An antimicrobial scenario is defined as a set of related tasks,
pesticide formulations, equipment, engineering controls, and worker and/or
consumer practices. For example, two scenarios of interest are "mopping
application" and "wiping application." The scenarios of interest to the Task Force
fall into two general categories:
1.	Scenarios that are addressed by simulated-condition studies based on
discrete or segmented tasks (mixing, loading and application methods)
that can used, separately or in combination, to estimate exposures
occurring in a variety of use conditions; and
2.	Complex and/or multi-task scenarios that are addressed using in situ (e.g.,
on-site, observational) studies.
The basic element in both simulated-condition and in situ studies is the
monitoring unit or monitoring event (ME). Each ME will consist of measuring
dermal and inhalation exposure potential for a single subject for a time period
that represents a typical workday. The general approach is to obtain, for each
scenario, a variety of MEs using different subjects and a diverse set of conditions
that will reflect current and projected antimicrobial mixing/loading and application
practices in North America. Diversity in characteristics that are either known or
assumed to be exposure-related will be emphasized. The measured exposures
from each scenario-specific set of MEs can then be used to represent the future
handler-day exposures to arbitrary (i.e. generic) antimicrobial compounds. For
each scenario, the basic objective always is that the set of MEs adequately
characterize both the typical and the more extreme exposures expected for a
single workday. The design of scenario-specific studies and the construction of
MEs are described in Section 16 and in Appendix E.
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Collectively, all scenario-specific studies that generate MEs to be included in
BHED™ are referred to as the AEATF II monitoring (or testing) program.
BHED™ will be used to support North American registrations for existing and
new pesticide products as required by FIFRA in the United States and the Pest
Control Products Act (PCPA) in Canada.
An AEATF II scenario represented by the set MEs in BHED™ may or may not
correspond exactly to set of antimicrobial-handling tasks being considered for
regulatory evaluation. Scenarios that are complex and consist of multiple non-
separable tasks will be addressed by in situ (observational) studies. The MEs
from these studies can be used directly for regulatory evaluation. In some
situations, however, the number of possible combinations of tasks would too
large to address each by a separate scenario. As a result, some AEATF II
scenarios correspond to single discrete tasks (e.g. mopping, wiping, mixing, etc.)
that will be addressed by simulated-condition studies. When regulatory interest
is only in the discrete task (e.g., mopping only) then the scenario in BHET™ is
directly applicable. However, when interest is in a combination of these tasks
(e.g. mixing plus mopping) then results from several AEATF II scenarios must be
combined.
A single scenario, such as "mopping", may be defined as a specific task, i.e., the
mop-based application of a label-specified end-use formulation containing an
antimicrobial chemical. It is common in institutional settings today that
automated dispensing systems provide the applicator with ready-to-use mop
solutions, and the applicator does not mix and load the end-use mop solution in a
bucket. Therefore, the applicator's exposure during a single workday in these
conditions would arise only from the task of application and intermittent disposing
or emptying the dirty mop bucket solution. The distribution of daily exposures
under the "mopping" scenario would then adequately describe the handler's daily
exposure to the antimicrobial. In other circumstances, however, a mop applicator
could also be manually mixing and loading the mop solution, i.e., preparing the
end-use dilution by adding a concentrate to water in a bucket. In these cases,
the daily exposure for an antimicrobial handler would arise from two discrete
tasks, i.e., mopping (including dirty mop solution disposal) and mixing/loading of
mop solution. To provide data for regulatory agencies to address the addition of
this discrete task (mixing and loading), the AEATF II will conduct separate
studies of mop application (which would include discrete measurement of
exposures associated with mopping and dirty mop bucket solution emptying) and
of mixing and loading via open pouring of liquids.
At times, user's of the BHED™ data may need to consider the distribution of a
combined exposure from multiple tasks represented by separate scenarios. The
arithmetic mean of a combined single-day exposure is simply the sum of the
arithmetic means for each separate task. However, other aspects of the
combined distribution depend on how exposures for the same individual from
different tasks are correlated. If the exposures are perfectly correlated (i.e. the
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correlation is 1) then any percentile of the combined distribution is the sum of the
percentiles for each task separately. If the same-person-different-task exposures
are independent, however, then the combined percentiles are less extreme than
the sum of the separate percentiles. This 'shrinkage' of the combined distribution
is rather minimal and is practically non-detectable if one task's mean exposure is
much larger than any of the other tasks mean values. Thus, unless a separate
estimate of the between-task correlation is available, a practical recommendation
for most BHED™ users would be to simply assume that the tasks are maximally
correlated and add all percentiles. This approach would likely be acceptable in
the context of regulatory-decision making when relying upon BHED™, given the
overestimation (more conservative) bias associated with summed upper-
percentiles. More importantly, the development of normalized exposure data for
discrete tasks provides the flexibility to construct or assemble and assess multi-
task exposures and thus, greater utility for a generic exposure database.
In some instances, there may exist, a discrete task or set of tasks that falls
outside all the scenarios for which monitoring is planned. This is most often
because the task is rare or would be expected to give non-detectable exposure
levels. When reasonable, users of BHED™ might choose to ignore the task or
use another scenario as a surrogate for the missing task. For example, in the
case of mop application, in some cases, a person may pour a concentrated
formulation containing an antimicrobial into a mop bucket containing water to
create a label-specified end-use dilution. The exposures (dermal and inhalation)
that may occur during this liquid pouring task can be addressed with the separate
"open liquid pouring" study data. The "open liquid pouring" data could be used
directly as a conservative surrogate for pouring a concentrate into a mop bucket.
In this example, it is important to adjust the surrogate exposures distribution for
the amount of active ingredient handled in the specific mop bucket pouring
situation being assessed.
6 Limitations of Existing Data and Justification for
Supplemental or Confirmatory Data
Since 1992, the EPA has conducted agricultural mixer/loader and applicator
exposure and risk assessments relying primarily on the exposure data in PHED.
PHED version 1.01 was initially released in February 1992. It was followed by
PHED version 1.1 in February 1995. PHED version 1.1 was described by the
Agency as an incremental improvement over the 1.01 version (Pesticide
Handlers Exposure Database, User's Guide Version 1.1, Health Canada, U.S.
Environmental Protection Agency, American Crop Protection Association,
February 1995). The forward to Version 1.1 User's Guide cautions the user that
the database still has some limitations and should not be considered a panacea
in estimating pesticide handler exposure. Noting the limitations, the guide states
that a goal was to release a PHED version 2.0 in 1997. However, no subsequent
version of PHED has been released.
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By 2000, the U.S. Environmental Protection Agency began evaluating
alternatives to PHED. The EPA has outlined its intentions regarding PHED
(Letter from Margaret Stasikowski, Director, Office of Pesticide Programs, Health
Effects Division, to Daniel Fay, Valent USA Corporation, 16 March 2001). EPA
has acknowledged the need to "overhaul" PHED version 1.1 because many of
the existing exposure studies in the database are outdated or scientifically
inadequate by "today's standards". In addition, many antimicrobial pesticide
exposure scenarios that are being assessed by the Agency are under-
represented or not even included in PHED version 1.1.
In summary, PHED suffers from a number of limitations regarding its use as a
generic exposure database, including:
•	Inadequate number of measurements for one or more body areas;
•	Inadequate quality assurance or quality control data;
•	Use of patch dosimeters instead of whole-body dosimeters;
•	Lack of whole body dermal estimates for subjects (i.e., not all body parts
monitored for dermal exposure in most studies);
•	Many (>70%) non-quantifiable residues on inner dosimeters;
•	Lack of diversity for test conditions (e.g., same subjects used repeatedly
or all subjects handling the same amount of product); and
•	Lack of representativeness of test conditions (e.g., equipment or
procedures that are no longer in common use).
Issues regarding the adequacy of the data in PHED can be illustrated by reviews
of the Registration Eligibility Decision (RED) documents issued by EPA as part of
the recently completed FQPA re-registration process. These documents have
characterized the existing PHED data as low confidence for the following
important use patterns. Confidence ratings are based on "number of replicates"
(quantity) and "QA/QC Grades" (quality). In general, low confidence scenarios
have fewer than 15 replicates and/or barely acceptable laboratory fortification
recovery data (or worse).
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For reference, PHED confidence ratings can be summarized as:
Confidence
Rating
Number of
Measurements

QA/QC Grading
High
>= 15 per body
part
And
Good laboratory plus good
field fortification data (or
better)
(Grade AB)
Medium
>= 15 per body
part
And
Moderate laboratory
fortification data plus
either poor field fortification or
moderate storage stability data
(Grade ABC)
Low
< 15 per body
part
Or
Barely acceptable (or
unacceptable) laboratory
fortification data
(Grades D or E = All Grades)
In addition, it should be noted that PHED provides dermal exposure estimates,
and confidence ratings, for several distinct clothing situations:
•	"no clothes" (i.e., based on outer dosimeters or clothing)
•	single layer of clothing, no gloves (most scenarios)
•	single layer of clothing, with gloves (some scenarios)
•	coveralls over single layer of clothing, with gloves (some scenarios)
Therefore, PHED can have low confidence for one clothing/PPE situation and
high confidence for another within an exposure scenario. While protection or
penetration factors can be used to estimate protected exposure from non-
protected exposure results, or vice versa, this may create additional uncertainty
for exposure estimates and may not be appropriate for all risk assessments.
PHED data with potential relevance to antimicrobial scenarios are as follows:
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PHED Scenario (#)
Comments re:
PHED Scenario
AEATF II Application Method
Liquid (3)
Mixing/Loading (M/L); open
mixing
Pour Liquid
Pump Liquid (6)
M/L; closed mixing
Pump Liquid
Paintbrush/Roller (22)
Brush application only
Brush / Roll
Aerosol Spray (10)
Application only
Aerosol Spray
High Pressure Spray (19)
Application only
High Pressure Spray
High Pressure Spray (35)
M/L, Liquid, open pouring; and
application
Pour Liquid and High Pressure
Spray
Lo Pressure Spray (32)
M/L; Liquid; open pouring; and
application
Pour Liquid and Low Pressure
Spray
Low Pressure Spray (33)
M/L; Wettable Powder; and
application
Pour Solid and Low Pressure
Spray
Low Pressure Spray (18)
Application only; handwand
equipment
Low Pressure Spray
Airless Spray (23)
Application only; house stain
Airless Spray
Pour Solid (1)
M/L; Dry flowable; open mixing
Pour Solid
Pour Solid (2)
M/L; Granular; open mixing
Pour Solid
Pour Solid (4)
M/L; Wettable powder; open
bag
Pour Solid
In addition to data available in PHED, another source of existing data being used
by regulatory agencies in the case of antimicrobials is that represented by an
exposure monitoring program conducted by the CMA (Popendorf et al. 1992).
On 4 March 1987, a Data Call-In Notice was issued for submission of data for
antimicrobial pesticide active ingredients. In response, the CMA developed a
generic biocide exposure assessment protocol and conducted a study, Chemical
Manufacturers Association Antimicrobial Exposure Assessment Study
(conducted by Dr. William Popendorf at the University of Iowa; Popendorf et al.
1992) based on the protocol. The CMA effort originally considered a list of ten
pesticide active ingredients. This list was reduced to 9, considering several
criteria. Exposures to seven of these nine chemicals were assessed, as well as
exposure to zinc chloride, which was used as a surrogate tracer for a process
and chemical which could not otherwise be assessed. In total, 88 separate MEs
were obtained for six end-use settings and nine application methods (pour liquid,
pump, pour solid, place solid, aerosol spray, high pressure spray, low pressure
spray, mop and wipe) to assess both dermal and inhalation exposures.
Based on EPA's review (Mostaghimi 1995), CMA's study met some
requirements, but was lacking in other areas. Specifically, areas in which the
Amended Report complied with the procedures specified by the EPA's dermal
and inhalation exposure guidelines included the following:
1. Most of the dermal samples had detection limits low enough to allow
accurate reporting of the sample, according to EPA guidelines.
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2.	Some of the field recovery data were acceptable; five chemicals had
acceptable recoveries from gloves, and two chemicals had acceptable
recoveries from air, and the results were corrected for losses in the field
using correction factors determined from the recovery data.
3.	The materials used in the analyses were acceptable in most cases and
were adequate for further analysis. To assess dermal exposure, gauze
pads were used for dry residues, cotton gloves were used for assessing
exposure to hands, and placement of dermal pads was found to be
acceptable. For inhalation exposure, standard flow rates were used for air
impingers and personal sampling pumps, standard NIOSH factors were
applied to respirators to estimate reduction of exposure inside the
respirators; and
4.	Documentation of data collected during laboratory and field operations
was adequate based on both CMA's description of their data gathering
efforts and presentation of data provided in Appendix C of CMA's
Amended Report (Popendorf et al. 1992). In addition, replicate-specific
notes were provided for any unusual problems that may have contributed
to error.
However, the following areas were found to be lacking:
1.	Good Laboratory Practices, especially in the area of providing quality
assurance, must be followed more closely;
2.	A majority of extraction efficiencies were below the minimum level
suggested in the guidelines. Perhaps more importantly, the percent field
recoveries (which represent the amount recovered under actual conditions
encountered in the study) of many of the chemicals were lower than the
minimum needed to assess exposure. Therefore, either different active
ingredients would need to be used in future studies, or new analytical
methods to increase recoveries should be employed.
3.	A significant proportion of air monitoring samples were lower than the
detection limit; and
4.	None of the application method/end use settings had the minimum
number of replicates (i.e., 15) recommended in EPA's guidelines.
The limited number of MEs combined with poor recovery data severely limits the
conclusions that can be drawn from CMA's study. Therefore, the EPA and other
regulatory agency reviews indicated that additional data for all application
method/use setting combinations should be obtained to support more confident
inferences about exposures in a variety of settings.
The deficiencies identified by EPA in CMA's report were corroborated by other
reviewers. First, the California Department of Pesticide Regulation (CA DPR)
notes that the exposure data cannot be used as generic data for all
antimicrobials because recoveries were low, precision of the measurements were
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not established, and CMA did not establish the validity of generalizing the
information among applications and end-use settings (Powell et al., 1995).
Canada also reviewed the study and made similar conclusions (Worgan and
Rozario, 1993).
In summary, in order to assess potential risks from exposure to antimicrobials,
EPA has extremely limited data on which to rely. In fact, EPA has repeatedly
identified that data as inadequate.
In each of the following example Re-registration Eligibility Decisions issued
during 2005 and 2006, EPA has stated that "the risk assessment noted
deficiencies in the surrogate dermal and inhalation exposure data available from
the Chemical Manufacturers Association (CMA) data base. Therefore, the
Agency is requiring confirmatory data to support the uses assessed with the
CMA exposure data within this risk assessment."
-	PHMB. September 2005. EPA739-R-05-003
-	Benzisothiazoline-3-one. September 2005. EPA739-R-05-007
-	Para-Tertiary-Amylphenol, Potassium Sodium Salt. January 2005.
EPA738-R-05-001
-	Azadioxabicyclooctane. September 2005. EPA739-R-05-010
-	Chlorine Dioxide and Sodium Chlorite. August 2006. EPA738-R-
06-007
-	Pine Oil. September 2006. (publication number unavailable)
-	Aliphatic Alkyl Quaternaries (DDAC). August 2006. EPA739-R-06-
008
-	Alkyl Dimethyl Benzyl Ammonium Chloride (ADBAC). August
2006. EPA7389-R-06-009
The above list is not exhaustive but is intended to point out that the Agency has
clearly and repeatedly required additional exposure data for assessing risks from
occupational and residential uses of antimicrobial pesticides.
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7 Alternatives to Additional Human Monitoring
Regulatory agencies are charged with assuring that registered uses of a
pesticide will not cause unreasonable adverse effects to pesticide handlers. As
part of such determinations, regulators and risk assessors must be able to
estimate with confidence likely levels of occupational exposure. Excluding new
human monitoring studies, the information available to make reliable
approximations of exposure currently comes primarily from generic data
contained in PHED and CMA data (Popendorf, 1992), but also from pesticide-
specific exposure studies, modeling, and published literature. There is a general
paucity of published literature relevant to antimicrobial exposure; and the few
relevant publications were not conducted under GLP, did not typically measure
whole body exposure, and the raw data for verifying results is generally not
available. Further, there are no known reliable (validated) models to estimate
dermal exposure to antimicrobial users. The use of animal data is obviously not
an option for studies that monitor occupational exposure to individuals engaged
in their normal work activities.
Therefore, the only alternative to the conduct of new human monitoring studies
appears to be:
•	The continued use of the existing information sources (PHED and
Popendorf et al. 1992, other published literature, and predictive modeling);
and
•	The acquisitions of additional handler exposure data from other existing
product-specific studies that meet established acceptance criteria and that
have generic applicability.
The limitations of PHED and the other current sources of exposure assessment
data have been discussed briefly above. The limitations of existing data are
being evaluated by AEATF II on a scenario-by-scenario basis using acceptance
criteria (see Appendix D) developed via a consensus process with regulatory
agencies (U.S. EPA, Health Canada and California EPA). Existing data can also
inform the design and sample size (see Appendix E for the AEATF II general
study design approach) for proposed studies, where additional data are
determined to be needed. Appendix F provides an example evaluation in the
case of applicator dermal and inhalation exposure data available in PHED for
hand-held aerosols. This example includes a comparison of the PHED data to
key acceptance criteria adopted by the AEATF II (see Appendix D).
Under the first stage of the AEATF II program, and prior to the conduct of
scenario-specific exposure monitoring studies with human volunteers, the AEATF
II reviews existing handler exposure data from various sources and considers
acquiring data that meet established acceptance criteria. A recent SAP (2007)
evaluated the AEATF II acceptance criteria and concluded:
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The Panel viewed the selection criteria proposed by AHETF
and AEATF II to be reasonable for generating exposure data
for using in exposure assessments, with the following
caveats. The monitoring duration requirement may be too
stringent. Some provision to allow the inclusion of data from
settings where only short-term uses are the norm may need
to be added.
Although some useful worker exposure studies may be acquired by AEATF II,
most of the existing data are not sufficient to meet the generic data needs
identified in advance by the AEATF II and the Regulatory Agency Advisory
Committee. While there may be other data that have been submitted to EPA and
may be suitable for a generic data base, they are proprietary and AEATF II does
not have access to them. Consequently, at this point, no viable alternatives to
performing additional human monitoring studies exist for most scenarios.
It should also be pointed out that pre-requisite studies for AEATF II testing do not
require research with human subjects. These pre-requisite studies include
analytical method validations, field recovery validations, and toxicity studies that
support the registrations of the test materials used. Therefore, the exposure
measurements (monitoring units or events, i.e., MEs) proposed by this document
reflect the entirety of human participation.
8 Ethical Considerations
All AEATF II studies will be conducted in compliance with the applicable
requirements of 40 CFR Part 26, EPA's regulations for "Protections for Human
Subjects of Research", and, if they are conducted in California, with the
applicable requirements of California Code of Regulations Title 3 Section 6710.
Ethical considerations are scenario and study protocol-specific, however, general
considerations are discussed below.
8.1 Subject Recruitment Process
AEATF II studies require IRB, EPA/HSRB and sometimes CDPR approval of the
protocol and process before subjects are recruited and the worker exposure
monitoring study is initiated. The subject recruitment process must be tailored to
each scenario-specific study. AEATF II studies will typically incorporate the
elements described in the section as components of the recruitment process.
Recruitment is conducted by selecting trained or experienced antimicrobial
chemical handlers from subjects (workers or consumers, depending on the
scenario and products being studied) identified by personal contact through local
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service businesses or research organizations. Recruitment materials such as
advertisements or fliers may be used. The Principal Investigator (Study Director)
approves the selection of all study sites and subjects, generally after visiting the
proposed sites and talking to potential volunteers. Informed consent discussions
are conducted by the Principal Investigator, generally shortly before study
initiation.
8.1.1 Identification and Recruitment of Potential Subjects
It is important to acknowledge that each study protocol must include specifically
defined processes for the identification and recruitment of potential subjects.
This protocol specificity includes for example, eligibility criteria.
Population Base
In general, AEATF II proposed studies will involve adult subjects that meet
specified inclusion/exclusion criteria and who will be recruited from the
professional handler and/or consumer user population in defined geographic
locations within the United States (U.S.), Canada and possibly, for a few studies,
from European countries, and defined geographic locations therein. Persons
with professional training and/or experience will be initially contacted by the Field
Coordinator using a phone interview script. Recruitment of subjects will be
through a) word-of-mouth and telephone contact, b) relevant service companies
or recruitment agencies that have been provided with a flyer that describes the
study and contains a phone number and name of an AEATF II study contact
person; or c) direct contact with service providers who are asked if AEATF II may
have their permission to ask their employees if they might be interested in
participating in the study independently from their employer where AEATF II
provides the chemical and use equipment, or at the employer's place of
business, if the employer is providing the antimicrobial and use equipment.
Interested subjects should contact the Field Coordinator directly.
Enrollment of Alternate Subjects
Alternate subjects will be enrolled into each study and the number of alternates
enrolled will depend on an individual study's objective regarding the number of
monitoring units (or monitoring events, i.e., MEs). Typically, enrollment of three
to six alternative subjects is anticipated. All subjects will be informed during the
interview process that a small number of subjects will be designated as
alternates and are expected to be present at the test site on a given day, but
might not participate in that day's activity. An alternate will be monitored if the
assigned subject does not present or if the assigned subject drops out for any
reason. If a subject begins monitoring but stops less than a specified time period
into a given study, the dosimetry from that subject will not be analyzed and the
alternate will be used. Dosimetry from any subject that complete a minimum
specified duration (to be specified in each study protocol) or more will be
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analyzed and the results assigned to the nearest target task duration interval,
i.e., subjects who completed as least 20 minutes of a given task (e.g., surface
wiping), would be assigned to a pre-specified 30 minute target task duration
group. The alternate subjects not tested the first day will be asked if they are
available to fully participate the next day. Alternate subjects will be compensated
for coming to the test site. Alternate subjects will serve as back-up for any
enrolled subjects who fail to appear on a given day, for subjects that decide to
withdraw prior or during the test, for female subjects testing positive in the
pregnancy test, or for any other personal circumstance.
Inclusion and Exclusion Criteria
The Principal Investigator is responsible for ensuring that study-specific inclusion
criteria are met when participants are recruited. The subjects will be asked to fill
out a demographic questionnaire and asked health-related questions. Females
will be asked to take a pregnancy test. The responses and results will provide
the basis for inclusion or exclusion from the study.
Inclusion
•	Males or females, 18 to 65 years of age
•	In good health
•	Willingness to sign the Informed Consent Form
•	Speak and read English or Spanish (or, if feasible, another
predominant language selected for a specific study based on the
associated potential subjects' demographics)
Exclusion Criteria
•	Skin conditions on the palmar surface of the hands (e.g., psoriasis,
eczema, cuts or abrasions)
•	Pregnancy, as shown by a urine pregnancy test
•	Lactation
•	Allergies to household chemical-based products, soaps or isopropyl
alcohol
•	Declines to sign the Informed Consent Form or the Health
Questionnaire
•	Does not read and understand English or Spanish (or, if feasible,
another predominant language selected for a specific study based on the
associated potential subject's demographics)
•	Is less than 18 or more than 65 years old
•	Is not in generally good health
•	Severe respiratory disorders (e.g., moderate or severe asthma,
emphysema)
•	Cardiovascular disease (e.g., history of myocardial infarcts, stroke,
congestive heart failure or uncontrolled high blood pressure)
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• Is an employee of the contract laboratories conducting the study, or
is related by blood or marriage to personnel in the contract
laboratories.
Willingness to Participate
Participants must be freely willing to participate in a study of this type and have
no interest in the conduct or outcome of the study (e.g., they cannot work for a
pesticide manufacturer who is a member of AEATF II, or for the Principal
Investigator or any other sub-investigator, or for any party with a substantial or
contractual interest in the research, nor can they be relatives of any
investigators).
Experience
Most AEATF II studies will involve only professional workers (e.g., janitorial
professionals, wood treatment facility workers, machinists at metal working
shops) with experience specific to the tasks being investigated. This will ensure,
in the case of subjects, that they have met basic safety trained requirements, as
dictated by their employer, prior to handling pesticides. Further, if professional
pesticide products are used in the study, only professional subjects would be
involved in the study. In some studies, products that could be used by workers
or consumers will be involved; thus, potential subjects could include consumers
with relevant experience in performing a scenario-specific task
Age
All monitored subjects will be at least 18 years of age, and no older than 65.
Subjects will be asked for a Government-issued photo-ID to confirm their age.
Health Status of Participants
Only subjects who consider themselves to be in good health will be eligible. This
will be affirmed by the subject's responses to the health-related questions. The
subject-provided responses and information help the Study Director to exclude
subjects who are not in good general health, allergic, mentally ill, cognitively
impaired, chronically ill, or terminally ill. This will help limit the risks of adverse
effects due to pesticide handling.
Work Periods
All monitoring periods will be designed to represent the typical duration of the
specific task or activity being monitored during a normal workday. Generally, this
will involve monitoring periods from 30 minutes to eight hours in length, since
most AEATF II scenario-specific activities are performed intermittently during the
work day. Data sources will be identified and evaluated regarding product
use/usage information to inform study designs with respect to product application
sites and surfaces, application methods, amounts handled, and duration of tasks
or work periods. An example source of publicly available professional "habits
and practices" information is that from the International Sanitary Supply
Association (ISSA; www.issa.com). ISSA is the leading international trade
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association for the cleaning industry. ISSA's worldwide membership includes
more than 4,800 distributors, manufacturer, building service contractor and in-
house service provider members. ISSA cleaning operations observational
survey data (time and motion studies) were used to inform AEATF II study
designs, e.g., predominant mop technology, cleaning task durations, for the mop
and wipe applicator exposure studies. Another example source of product use
information, including task duration or work periods, is a proprietary survey
conducted by the Chemical Specialty Products Association (www.cspa.org).
Antimicrobial Exposure Joint Venture (AEJV), which has collected data focusing
on consumer antimicrobial cleaning product use in residential settings.
Product Label Non-Conformance
All subjects will be required to perform pesticide handling tasks in conformance
with the label requirements. BHED® is designed to reflect exposure to workers
and/or consumers who follow legal and proper handling of pesticides and not
who misuse the product or otherwise violate the label. In particular, subjects
must wear the Personal Protective Equipment (PPE) required by the label and
researchers will remind participants to use that PPE should they be observed not
wearing the PPE during exposure monitoring. Any subjects who will not follow
the label requirements during the study will be asked to discontinue their
participation and their exposure samples will not be collected. A subject will be
reminded once if found not wearing PPE. A second infraction is grounds for
subject removal from the study.
Pregnant or Nursing
The pregnancy status of all potential female participants will be ascertained
through the use of a supervised over-the-counter urine pregnancy test conducted
within 24 hours prior to the initiation of monitoring. Any pregnant subjects will be
excluded from the study. In addition, women who are nursing will be excluded.
Speak and Read either English or Spanish
English and Spanish are by far the most common languages used by
occupational pesticide handlers in North America. Translators for other
languages are often difficult to locate where antimicrobial products are used,
making it difficult to ensure fully informed and fully voluntary consent for speakers
of other languages. Thus, AEATF II anticipates that it will not enroll participants
who are not fluent in either English or Spanish. If a language other than English
or Spanish has high incidence (>15%) amongst potential subjects for a specific
study, translation of study materials, the availability of translators, and the
additional language-speaking technical staff person (e.g., present during the
study's field phase) will be considered by AEATF II.
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8.1.2 Exclusion of Vulnerable Group(s)
AEATF II prohibits most of the vulnerable groups as participants, including:
people who are ill, cognitively impaired, pregnant, minors, employees or relatives
of the Principal Investigator, etc. As described above, local site coordinators are
generally used to locate suitable sites and potential participants - they are
identified as a research site in applications to IIRB. AEATF II will occasionally
allow a local site coordinator, or an employee of the site coordinator, to be a
participant in a study. In this case, the subject must meet all of the criteria listed
above, including the requirement that he/she be experienced in the particular
task being monitored. AEATF II will only use such research staff if they also
have experience handling pesticides in a commercial environment, for example
as the owner of a separate commercial facility or in a previous job. This group
(i.e., employees of research site) may be vulnerable to coercion since the local
site coordinator receives the benefit of payment for his services.
However, as described in the next section, AEATF II takes special care to
prevent coercion of these subjects by having their supervisor/employer confirm
they won't be coerced and that their participation decision will have no impact on
their employment or work opportunities.
AEATF II does not intend to recruit limited or non-readers, however, a fair
percentage of the workforce (and consumer population) has Spanish as their
primary language. When AEATF II knows in advance that a Spanish speaker
may be recruited for a particular study, this potentially vulnerable category will be
identified in the application to IIRB. AEATF II has procedures in place to deal
with candidates and subjects who prefer to use Spanish. These procedures are
discussed in the following section.
Another potentially vulnerable group that might be part of the target population is
poor/uninsured (health care insurance) subjects. AEATF II does not intentionally
recruit these individuals and will not inquire as to the economic or insurance
status (health care insurance) of potential study participants. Therefore, this
category will not be identified to the IRB as one that is intended to be recruited.
As discussed below, the remuneration being offered (generally for just one day of
participation) is believed to be not high enough to induce otherwise reluctant
subjects to participate, so the economic status of participants in these studies is
not a concern. The level of remuneration will be consistent with pay in a
particular region of the country if there are obvious differences in wages between
regions. In addition, AEATF II will cover all costs of injury or illness that subjects
experience because of participating in the study (that are not covered by the
subject's or their employer's insurance).
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Another potentially vulnerable group that might be part of the target population is
illegal workers. For example, illegal workers may feel obligated to participate
(e.g., in order to protect their job) or be reluctant to accept medical treatment.
Federal laws give employers the responsibility for ensuring their workers are
legal, but AEATF II does not employ subjects. AEATF II will therefore assume
workers are legal and will not ask about their status. In addition, should
researchers become aware of an illegal worker they will not share that
information. Workers who might be illegal will be protected from coercion
primarily via the mechanism described below where the Study Director will
discuss the voluntary nature of study participation with the worker's
supervisor/employer.
8.2 Informed Consent Process
Two fundamentally different recruitment situations may occur. If a study is being
conducted on an active worksite where subjects are normally employed to do
their job, the following preliminaries occur before subjects meet the Principal
Investigator for studies that occur at normal worksites. When potential sites have
been selected and potential participants have been identified by the Field
Coordinator, a flyer describing the study is distributed to potential participants.
Before any contact with potential subjects the Principal Investigator has a
discussion with the direct supervisor of each potential participant to ensure that
the supervisor has no interest in whether the subjects do or do not choose to
participate, and further, that the supervisor understands that subjects should not
feel any coercion to participate in the study. The supervisor must confirm there
will be no adverse impact on a worker who does not volunteer, or withdraws from
the study, for any reason. This extra care to prevent coercion from employers
will be documented on a form which the supervisor, business owner, or
commercial applicator must sign. Prospective volunteers are introduced to the
Principal Investigator, and their language of choice is determined. Then, each
volunteer is provided with the supervisor's signed form, the IRB-approved
consent form, and a full explanation of the study, its requirements, and any
potential risks as discussed below for studies conducted away from subjects'
normal worksite. This occurs during a confidential and private discussion with
the Principal Investigator at the worker's location if the study is being conducted
at a work site under the worker's supervisor's control.
If subjects are recruited to work at a site not under their supervisor's control, i.e.,
away from their normal worksite, and not under their supervisor, another
paradigm is used. The Field Coordinator will be contacted by individuals that
have been made aware of the study by a flyer posted at their place of
employment. Using an IRB-approved phone script, the language preference of
the subject will be identified, and interested potential subjects will be scheduled
for a meeting with the Principal Investigator or foreign language-speaking
designee.
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Interested volunteers will be screened and enrolled into the study based on one-
on-one conversation held at the office of the Principal Investigator. A Spanish-
speaking technical designee will be available to ensure communication with
anyone preferring Spanish over English. The Principal Investigator will share
information on the study design with interested participants, and provide them
with copies of the IRB approved Informed Consent Form and answer their
questions. The Principal Investigator will describe the study to the volunteer in
great detail and encourage each potential subject to ask questions and request
clarification at any time during this process as well as in all activities that follow.
The Principal Investigator will provide each potential subject with a copy of the
product label and MSDS and answer any questions regarding the product to be
tested. The Principal Investigator will go over the Inclusion and Exclusion Criteria
for the study and answer any questions that the potential subjects have. They will
be provided with copies of the Informed Consent Form, the Subject Self-
Reporting Demographic Form and the State of California Department of Pesticide
Regulation "Experimental Subject's Bill of Rights" and encouraged to take them
home with them to discuss with family and friends.
The Principal Investigator will explain to potential subjects wishing to remain in
consideration that they may withdraw from the research study at any time without
penalty to their compensation. The Principal Investigator will then read the
"Experimental Subject's Bill of Rights" to the potential subjects. The amount and
form of compensation, the potential risks and discomforts and treatment, and
compensation for injury will be more fully explained and potential subjects
encouraged to ask questions. If the potential subjects do not have any questions
and are interested in participating in this research study, they will then be asked
to sign the Informed Consent Form and then fill out the Subject Self-Reporting
Demographic Form. The Principal Investigator will check the potential subject's
driver license or state-issued identification card to verify age to exclude minors,
and identity as required by California DPR, and review the package of
information provided for completeness against the protocol's inclusion/exclusion
criteria. The Principal Investigator will retain the final right to refuse participation
to any potential subject; however, following signing the informed consent form,
any potential subject not actually monitored will be given the minimum
compensation. For female subjects, final eligibility will be determined on each
study day following a pregnancy test.
Volunteers are advised of their right to withdraw from the study at any time and
for any reason without jeopardizing their position with their employer. Volunteers
are also informed during the confidential consenting process that they will receive
compensation after they volunteer to participate in the study, even if they
withdraw for any reason or the sponsor does not use them for any reason.
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AEATF II consent forms are unique to individual studies, but all have very similar
structure and contain the following:
•	Study title
•	Protocol number
•	Study sponsor
•	Investigator name
•	Study site(s)
•	Study-related phone number(s)
•	Sub-investigators
•	Statement of the purpose of the study
•	List of procedures involving the subjects
•	Detailed list of risks and discomforts
•	Statement regarding disclosure of new findings
•	Statement of benefits of participation
•	Statement of no cost to the subjects for participation
•	Statement of payment for participation
•	Statement of alternatives indicating this is not a medical treatment study
and the alternative is to not participate in this study
•	Full explanation of confidentiality of worker information
•	Statement of compensation for injury
•	Source of funding
•	Voluntary participation and withdrawal
•	List of resources who may be contacted to obtain answers to questions
•	A section for signatures of the participant and the person conducting the
informed consent discussion
During the discussions between potential participants and the Principal
Investigator, ample time is provided for questions and the Principal Investigator
will provide any additional information or clarification that is requested. These
discussions typically take place at the worker's location, in a private setting,
generally in a meeting room of a facility or commercial application company.
Consent is generally obtained within one to three days of actual study conduct,
but sometimes earlier. If the worker agrees to participate he/she is asked to
sign and date the informed consent form and the Principal Investigator provides
a copy of the signed form to the worker. Within 24 hours prior to participation,
any women who are selected to participate will be asked to take a urine
pregnancy test (over the counter variety) and will be allowed to participate only
if the test is negative. This test will be supervised by a female researcher. To
protect the privacy of the worker, the test results are not revealed to the
employer or co-subjects. If the worker chooses to proceed with the study then
a female researcher will confirm the test is negative and record this in the study
raw data. No positive test results will be documented and the worker will be
allowed to withdraw from the study without stating a reason (and still receive
appropriate remuneration).
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For subjects whose preferred reading language is Spanish, AEATF II obtains an
IRB-approved translation of the consent form and ensures that a Spanish-
speaker familiar with the study protocol is present during the informed consent
process and during study conduct. In all cases, the Principal Investigator will
conduct discussions in English, but the participant will sign the version of the
consent form in his preferred reading language. The Spanish speaker may be
an employee at the study site, but more typically will be supplied by the
Principal Investigator and will be brought into the discussion if the subject's
preferred language is not English. A Spanish-speaker familiar with the study
protocol will also be utilized during the study should any issues arise which
can't be resolved directly with the worker.
In all situations, if the Principal Investigator is not comfortable that the worker
fully understands the discussions and the contents of the consent form, the
worker will be excluded from consideration to participate in the study. This will
be ascertained by providing repeated opportunities to ask questions and by
asking questions of the potential volunteers that would require a response that
indicates understanding of key issues. For example:
•	Q: When can you withdraw from the study?
A: Whenever I want.
•	Q: What will your supervisor have you do if you don't volunteer?
A: My regular job.
•	Q: What will you wear so we can measure inhalation exposure?
A: An air pump on my belt.
•	Q: Will researchers tell you how to do your job?
A: No.
Subjects' ability to read and understand either English or Spanish will be
confirmed by their answers to the Subject Self-Reporting Demographic Form.
The process for obtaining informed consent is fully documented in each AEATF II
study protocol.
8.3 Subject Remuneration
In almost all cases, AEATF II is studying the potential exposure to pesticides for
subjects who are performing their usual activities. This would be generally true
for both scripted and non-scripted activities. Thus, pesticide handling would be
conducted even if they weren't participating in the study.
AEATF II has selected a standard remuneration amount for all AEATF II studies
and participants since the inconvenience involved is essentially the same for
participants in all studies. In addition, AEATF II chooses not to offer an hourly
rate since it prefers that subjects perform their typical tasks and wants to avoid
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any incentive for subjects to choose a particular task since they could "earn more
money". The researchers utilized by AEATF II all have experience in dressing
and undressing subjects and the complete process takes only about 20 to 30
minutes throughout the work day. This represents the primary inconvenience
associated with participation in an AEATF II study.
While any standard amount of remuneration could represent a very different
proportion of various subjects' typical daily pay, fairness suggests that each
worker should receive the same amount of remuneration since the amount of
inconvenience is essentially the same.
AEATF II selected the amount of $100 at the outset of the task force project and
still believes this is an appropriate amount, although compensation may be
varied if the local economy requires more or less for cost of living. This is
equivalent to approximately $15/hour for a full day's work which is similar to other
amounts from other studies that have recently been approved by HSRB. AEATF
II believes that $100 is not sufficiently high as to create undue influence to
participate in the study, especially since subjects are generally limited to one day
of study participation.
Individuals that are not tested including anyone signing the informed consent
form but not subsequently being monitored will be compensated for their time
and inconvenience at the rate of $50 per day. Subjects participating in the study
will be compensated $100 for the single day that they are monitored. The values
for compensation are based roughly on a day's wage of $100 and represents
potential lost time from work, travel time and incidental expenses incurred in
study participation. Compensation will be in the form of cash at the completion of
participation.
Generally, a particular person will be allowed to participate in the study only one
time. This study design principal provides data for separate exposure
measurements that reflect different subjects in order to capture variability
between subjects. However, the same worker could participate more than once
in a study (or in two studies) as long as the worker performs a different task. For
example, one person could be monitored for exposure as a mixer/loader on one
day and as an applicator on another day (assuming the experience and other
criteria are met). In this case, that person would receive a $100 payment on
each of those two days.
It is important to note that subjects who are professional workers and who are
participating in any AEATF II studies that are being conducted "in situ" (i.e.,
exposure monitoring studies at workplaces such as a metal working shop) are
"on the job" and will receive their normal salary and all other compensation they
are due, including compensation for any overtime worked according to local laws.
This compensation is the responsibility of the worker's employer and not AEATF
II.
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In addition to their normal compensation, AEATF II will provide a payment of
$100 (U.S. dollars if in the United States or comparable compensation if in
Canada or Europe) to each worker who volunteers to be monitored for exposure.
This payment is in appreciation for the extra effort and inconvenience associated
with subjects participating in the study which includes wearing the inner
dosimeter (long underwear, requires undressing in a private area); allowing
researchers to wash their hands and wipe their faces; allowing researchers to
remove the inner dosimeters at the end of the monitoring period; and wearing a
personal air sampling pump throughout the workday.
8.4 IRB Review Process
AEATF II generally uses the Independent Institutional Review Board (IIRB) in
Plantation, Florida (www.iirb.com) to review each of its study protocols for ethical
compliance. Initial review submissions from AEATF II to IIRB typically include
the following:
•	The submission package to the IRB includes the study protocol and
appendices including, test substance MSDS, summary of toxicology
information and estimated risk for exposure anticipated in that study based
on U.S. EPA's Registration Eligibility Decision documents (REDs).
Additionally it includes experimental subjects' bill of rights, subjects self-
reporting demographic form, flyers soliciting prospective subjects and
scripts used to verbally describe the study to prospective subjects. All
documents provided to subjects will be translated into another language if
the subject demographics warrant, i.e., if >15% of the population uses
another language in any study region.
•	Initial Review Submission Form (IIRB form revised 01-2006; this is part of
the IRB correspondence file required by 40 CFR 26.1125).
The IIRB form identifies AEATF II as the sponsor and the Study Director as the
Principal Investigator. It also identifies study site(s) (generally local site
coordinator research facilities) and provides details about subject recruitment,
consent, and payment. Hospitalization procedures are also provided which
identify the nearest emergency medical facility to the study site(s) and indicate
that 911 (or other local emergency number) will be used as the primary method
for obtaining medical attention should any worker experience adverse effects
during a study. IIRB also maintains files containing the Principal Investigator's
curricula vitae and documentation of human subjects training which support the
submission.
IIRB will review all new study protocols at regular convened meetings. When
studies are to be conducted in California, AEATF II will also submit study
protocols and related information to the California Department of Pesticide
Regulation (CDPR) for their review and approval under CCR Title 3 Section
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6710. Any changes required by CDPR will be incorporated into the study
protocol, which will then be reviewed and approved by IIRB. Only upon receipt of
IIRB-approved protocol and consent forms will CDPR grant final approval for the
study to be conducted in California. Further changes in the protocol and
associated materials may also be required by EPA, and would also lead to re-
review by the IIRB.
All protocol changes (amendments and deviations) shall be reported to the IIRB
in writing by letter, fax or email. Proposed changes (amendments) deemed
necessary to eliminate apparent immediate hazards to the human subjects may
be implemented without prior IIRB approval. All other amendments must be
reviewed and approved by the IIRB prior to implementation, or as specifically
instructed by IIRB policy in this regard. Approval will be granted in accordance
with IIRB policy and procedures, and may be granted by telephone provided it is
documented in writing in the study raw data. The IIRB may provide expedited
review of minor changes as defined by 40 CFR Part 26.1110 at its discretion.
Unplanned changes (deviations) which occur during conduct of the study cannot,
by definition, be reviewed and approved by the IIRB prior to implementation.
Deviations will be reported in writing by letter, fax or email as soon as possible
following the change. The Principal Investigator shall follow written instructions
provided by the IIRB for prompt reporting to the IIRB, appropriate institutional
officials, and the EPA of unanticipated problems involving risks to human
subjects or others.
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8.5 Additional Efforts to Protect Human Subjects
The AEATF II takes many steps to ensure the safety of the subjects being
monitored. As outlined above, protocols and consent forms are approved by an
IRB (and DPR, if needed), informed consent is obtained for all study participants,
consent is obtained in writing in the worker's preferred language, certain
vulnerable groups are not recruited, pregnant and nursing women are excluded,
and participants are informed they may withdraw at any time. Other steps that
AEATF II takes to ensure the safety of study participants are summarized below;
each study protocol will define "stop criteria" and medical management
procedures.
The objective of the AEATF II is to generate data collected under actual use
conditions and following all label requirements. Subjects are never asked to
wear less protective clothing than they would ordinarily wear, even if the clothing
is not required on the product label. In cases where a worker normally wears
PPE not required by the label, the AEATF II either allows them to wear the extra
clothing (or equipment) or they are excused from the study, depending on the
specific goals of the study. The AEATF II may also provide some PPE items
required on the product label (e.g., protective eyewear) to ensure they meet
requirements.
Copies of the material safety data sheet (MSDS) and product label are made
available to members of the study team and study participants. During the
consent process, the Principal Investigator will provide these documents for
review to potential volunteers and will discuss the possible acute toxicity effects
associated with the pesticide product in the study. AEATF II study participants
will also be reminded of standard practices that should be followed to reduce
exposure to pesticides. For example, label-required PPE such as the
requirement to wear protective eyewear and to remove clothing that get
drenched with chemical from an accidental spill.
During study conduct, researchers will ensure compliance with safety
requirements on the product label. For example, subjects will be reminded to
use the label-specified PPE and to follow use directions on the label. Each
worker will be observed by a researcher during the entire monitoring period and
the Principal Investigator will be present on all days of monitoring. All
researchers who have interactions with the subjects have completed a course in
The Protection of Human Research Subjects, e.g., Certified Investigator Training
Initiative (CITI), which reinforces the ethical requirements of conducting studies
involving human participants.
Study participants are asked to wear an extra layer of clothing (whole body inner
dosimeter) under their normal work attire. Efforts are made to schedule studies
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during cooler times of the year and/or indoors as much as practical to help
minimize potential for heat stress. The informed consent form identifies heat-
related illness as a potential health hazard that may be associated with
participating in the study, so AEATF II is very careful to prevent such illness.
First, the Principal Investigators and study observers are trained to recognize
symptoms of possible heat stress. Second, researchers always have plenty of
water and sports drinks on hand for the subjects who are encouraged to drink
liquids during the monitoring period. Third, a poster "Controlling Heat Stress
Made Simple" will be prominently displayed at the study site. Most importantly,
environmental conditions (temperature and humidity) are continually monitored
and operating procedures are in place to reduce the possibility that participants
are subject to heat stress.
Finally, the Principal Investigators know in advance where to take subjects who
might be overheated or who have other medical concerns. If any participant is
injured or experiences illness as a result of being in a study, medical treatment
will be available at a nearby health care facility. If necessary, AEATF II will
arrange transportation to receive medical attention. AEATF II will cover the costs
of reasonable and appropriate medical attention that are not covered by the
participant's own insurance or by a third party. Treatment records will not
become part of the research records for this study.
9 Study Benefits
A critical principle of ethical research is that the risks to the subjects must be
outweighed by the benefits to the subject and to society. To approve proposed
research with human subjects, an Institutional Review Board must determine that
"risks to subjects are reasonable in relation to anticipated benefits, if any, to
subjects, and the importance of the knowledge that may reasonably be expected
to result" (40 CFR §26.1111(a)(2)). The low incremental risk anticipated for
pesticide handlers participating as subjects in the AEATF II monitoring program
are outweighed by the societal benefits expected to be gained from increased
knowledge of typical exposure levels in representative antimicrobial chemical use
scenarios.
A critical principle of ethical research is that the risks to the subjects must be
outweighed by the benefits of the research to the subjects and to society. The
Common Rule codifies this principle: "Risks to subjects are reasonable in relation
to anticipated benefits, if any, to subjects, and the importance of the knowledge
that may reasonably be expected to result" (DHHS, 2001). If the benefits of
monitoring pesticide exposure in the field to subjects do not outweigh the risks,
then the program should not be conducted. AEATF II argues that the risks
involved with pesticide handlers participating in the monitoring program, who
expose themselves to pesticides as part of their daily lives, are minimal and are
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outweighed by the societal benefits gained by knowledge of expected exposure
levels and by the eventual benefits of safe pesticide use.
9.1 Benefits to Subjects
None of the studies in the AEATF II monitoring program will provide direct
benefits to the study participants. Information from this monitoring program will
be used to estimate the exposure and health risk to handlers (workers, or for
some scenarios, consumers) who are involved in mixing, loading and applying
antimicrobial chemical products. This may lead to safer pesticide handling
practices that indirectly benefit the participants and other antimicrobial pesticide
handlers. Individual workers may request their exposure results relative to the
average and extremes observed in the study. This information may inform them
that their work practices produce more or less exposure than average and may
inspire them to modify behavior to reduce their exposure.
9.2 Benefits to Society
The AEATF II exposure monitoring program will significantly improve the ability of
EPA and other regulatory agencies to estimate the risks to professional pesticide
handlers from handling antimicrobial pesticides. Knowledge gained from the
monitoring program will be applicable to a variety of antimicrobial pesticides, and
will be used to assess risks of new pesticides and new uses of registered
pesticides. Knowledge gained from the monitoring program could also be used
by EPA to impose stricter safety standards on currently used pesticides, when
appropriate (Resnick, 2005).
The data developed in the AEATF II monitoring program will improve the
scientific basis for EPA's occupational risk assessments. Worker exposures will
be measured under realistic conditions. The data collection parameters will
reflect current antimicrobial practices, equipment, and techniques. Monitoring
techniques are of high quality and have been standardized for use across the
AEATF II monitoring program. BHED™ will become the best available data to
support assessments of antimicrobial pesticide handler exposure.
BHED™ will not repeat the limitations of PHED. In particular, BHED™ will
include all data on each individual sampled, not just data on individual body
parts. Improved estimates of whole-worker exposure, including estimates of the
potential distribution between subjects, will now be possible.
To the extent the generic database approach proves successful, it may reduce
the need for product-specific worker exposure studies conducted by individual
registrants for new products and uses.
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9.3 Likelihood of Realization of Benefits
The collection of worker exposure data that can address the data needs of the
regulatory community and membership of the AEATF II is considered extremely
likely. It is also highly likely that regulators and risk assessors will use these data
extensively. This has been the case for previous FIFRA joint data development
task forces of many types, including those developing data for generic exposure
assessment. Regulatory agencies are strongly committed to using generic
exposure databases as an important component of risk assessments. The use
of worker exposure data in a generic manner has been generally accepted since
the concept was discussed and supported by a FIFRA Scientific Advisory Panel
in 1986. In addition, the successful development and release of PHED in 1992
and its subsequent use by regulators to support many occupational risk
assessments strongly suggests that the BHED™ database will find even greater
use and its benefit realized.
10 Study Risks
Most of the studies designed within the AEATF II program are intended to reflect
what would be considered "normal" activity patterns for many subjects and
individuals handling biocidal products. There are some situations in which an
activity is semi-scripted, within the range of expected practices, to provide
diversity in parameters that may be related to exposure including the amount of
active ingredient handled and the duration of tasks. However, in each of the
proposed studies, careful consideration is given to the potential study-specific
risks to the individuals involved and what specific efforts will be made to minimize
or eliminate these risks. General risk considerations are presented in this
section. Each proposed study protocol will indicate study-specific risk
considerations and communication of those risks to potential study subjects as
part of the informed consent process. If a subject is injured as a result of being in
an AEATF II study, medical treatment will be available from a near-by health care
facility that knows about the study. The study sponsors (i.e., AEATF II) will cover
any cost associated with a subject's medical treatment that is not covered by
their own insurance or by a third party.
10.1 Description of Potential Risks to Subjects
The risks of the study can be broadly separated into two general categories,
those due to potential exposure to an active ingredient and those due to physical
stress that may arise from certain activities. Each must be considered to
determine what can be done to avoid unnecessary risks.
Physical risks can arise from climatic conditions, extra clothing (in the form of
wearing two complete layers of clothing, the inner and outer dosimeters), and
exaggerations of normal activities. Some of these aspects can be controlled by
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location and ventilation, yet other aspects are directly a result of the study design
and cannot be easily altered without invalidating the data collected. However,
those aspects that cannot be easily altered should be carefully evaluated, based
on existing data (e.g., habits and practices or product use survey data) and
expert opinion, to minimize the exaggeration of activity (e.g., upper-bound for
total time spent performing a given tasks, such as surface wiping associated with
cleaning activities during a day) without compromising the study results. The
exaggeration of activity patterns can lead to concerns related to potential
ergonomic issues (e.g., fatigue and heat stress). These need to be considered
on a case by case basis for the application method / study scenario.
The other aspect of risk is chemical resulting from exposure to an active
ingredient or solvent used to remove the chemical from skin. This can be
controlled to some extent by selecting active ingredients that have less toxic
profiles and have already been evaluated and approved for the application being
investigated. In addition, preference is for actives that have been evaluated and
do not require personal protective equipment for their usage in the application.
This criterion generally assures that the product has been evaluated with very
health protective assumptions and is approved already for this application. The
counter to this is that some exaggeration of usage may be required to obtain
detection of the active ingredient on the dosimeters. An example of this is
pouring liquids; typically a pouring event is 1 to 5 minutes and the circumstances
are such that detection of the active ingredient on a dermal dosimeter is unlikely,
even with extremely low detection limits. Hence to be sure that exposure is
actually being measured, it is necessary to increase the amount of product
poured and the length of time that the activity is carried out. For the evaluation it
may be necessary to pour liquids from several consecutive containers for an
extended time period. Based on the results of existing studies, it is anticipated
that the time and amount poured can be scaled to obtain detection on
dosimeters, but avoid unnecessary potential for exposure.
10.2Risks of Heat-Related Illness
Heat stress is the build-up in the body of heat generated by the muscles during
work and heat coming from the environment. Heat illness (e.g., heat exhaustion
and heat stroke) can result when the body is subjected to more heat than it can
accommodate. Weather, workload, clothing/PPE, and lack of worker
conditioning can increase the risk of a worker experiencing heat-induced
illnesses. In addition to causing serious physiological conditions, early symptoms
of heat illness such as dizziness and confusion can lead to an increased risk of
occupational accidents above that which is already present. Therefore, AEATF II
takes special care to monitor subjects for signs of heat stress. All study
observers are trained to recognize signs and symptoms of heat stress, and the
Principal Investigator (Study Director) and all observers promote drinking water
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and taking rest breaks. Researchers will stop study participation for subjects
who experience heat-related illness.
10.3 Risks of Exposure to Surrogate Antimicrobial Pesticides
Toxicology Hazard to Subjects
For each specific active ingredient chosen, AEATF II reviews the available
toxicology data to assure no undue hazard. Government-authored summaries of
the data are given to an IRB as part of the review package. The surrogate
chemical / active ingredient selection criteria include selection of active
ingredients that have low toxicity profiles, with good warning properties and
reversible effects. This selection process, however, is limited by the fact that the
active ingredient and the specific product used need to be approved for the
application method by the US EPA. By making this restriction, there is
assurance that the product has had at least a screening-level risk assessment
completed in the past.
Likelihood of Serious or Irreversible Effects
All of the applications being evaluated by AEATF II involve short-term exposures,
in most cases an exposure period of less than 8 hours. Hence, the main
concerns will be for acute exposure potential. As a result AEATF II focuses on
reviewing the likely exposures to the active ingredient and assures there is no
undue risk from acute exposure. Further, constant monitoring of the exposure
scenario and options for immediate termination by the participant or the study
observer are included, and every effort is made to avoid injury or over-exposure.
The subjects selected to participate in a study will be experienced in the use of
the equipment and types of products involved in that particular study. Any
subject with known allergic reaction to the product and specific pesticide used in
the study will be excluded from participating. At high concentration some
antimicrobial chemicals can produce dermal irritation, but this is not commonly
seen at the end-use dilutions being handled in AEATF II studies. Any severe
dermatitis or allergic reactions would result in stopping a subject's participation in
the study and providing access to any necessary medical treatment, including
transportation, if needed, to local medical care facility(ies) identified prior to a
study's initiation.
10.4Risks of Exposure to Face/Neck and Hand Wash Solution
Risk from irritation due to exposure to the washing solution (e.g., 50% isopropyl
alcohol and water) used on the face/neck and hands can occur if the subjects
have existing abrasions. Subjects will be informed prior to the study that the
washing solution (e.g., alcohol/water mixture) used to rinse their hands and wipe
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their face and neck may sting, if they have any cuts or abrasions on their hands
or face.
At breaks during AEATF II studies and at the termination of the study, the
subjects will have their hands washed by study personnel using a washing
solution (e.g., 50% isopropyl alcohol/water). Further, at the end of the study after
the final wash solution samples are collected, subjects will proceed to wash their
hands thoroughly with soap and water.
The Principal Investigator (or designee) will examine subject's hands at the time
of each sampling event and note any observed irritation to the skin. Any subject
showing an adverse skin reaction will be asked to immediately stop further
participation. The subject's exposed skin will be gently washed with clean water
and mild soap to remove the test product, and the area will be gently dried with a
clean towel.
10.5 Psych o logical Risks
Study subjects may find it embarrassing to have a researcher present with them
while they change from their clothes into and out of the cotton inner and outer
dermal dosimetry (work) clothing provided by AEATF II. This is necessary to
make sure that the special dosimeter underwear fits properly, and that it and the
outer dosimetry clothing doesn't get contaminated when the test is over. The
researcher who helps will be of the same sex, and will be the only other person
with the subject. The subjects will be wearing their own underwear all the time.
Embarrassment risk from disrobing is expected to be low because the
researchers are same-sex, and experienced.
If the subject is female, they might be surprised to learn the results of the
required pregnancy test on the day of the research. No one but them and one
female researcher will know those results, and they will not be recorded.
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11 Procedures for Monitoring and Preventing Risk to
Subjects
During all AEATF II studies, the Study Director (Principal Investigator) and the
field investigators share the responsibility for awareness of heat illness and toxic
responses in study participants. All such researchers are required to complete
training on the ethical treatment of test subjects. Prior to study conduct, the
Principal Investigator will assess the availability of medical assistance in the
locality of the study and identify appropriate emergency medical facilities that
may be utilized. This information is included in the Institutional Review Board
(IRB) application. IRB protocol and consent form approvals are prerequisites to
submission to EPA or HSRB. During each study, every participant will always
have a researcher assigned to observe his/her handling practices and this
"observer" will have the primary responsibility for detecting adverse effects.
Typically this observer is close enough to the worker to have a conversation.
Observers are trained to recognize heat stress and are informed of the most
likely acute effects of overexposure to the pesticide being used in the study.
Should an adverse reaction occur during an AEATF II study, emergency
procedures will be implemented. These procedures typically include halting
subject participation, removing the subject from the offending environment, and
calling 911 for medical assistance if needed. In addition, AEATF II has an
adverse effects reporting policy in place to notify EPA of potential new findings as
required by FIFRA Section 6(a)(2).
As mentioned above, the primary means of preventing toxic effects is to require
subjects to wear appropriate clothing and all required PPE. During study
conduct, observers will remind subjects that PPE must be properly worn when
handling the pesticide. Non-compliance on the part of the worker will result in
discontinuing the monitoring for that worker.
For heat stress, the following procedures will be followed by researchers to
prevent illness in study participants:
•	Ensure plenty of water and sports drinks are available for the subjects.
•	During worker orientation, remind the subjects of the risk of heat stress,
suggest they drink some water before they start work, and let them know
how/where they can get water during the monitoring period.
•	Urge subjects to drink water during the monitoring period and remind them
that thirst does not give a good indication of how much water a person
needs to drink. There is no need to take hand washes or stop inhalation
monitoring during a water break.
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•	Observe subjects during the monitoring period and be aware of the signs
and symptoms listed below.
•	Require subjects to take rest breaks when early signs or symptoms of
heat illness are present (e.g., headaches, dizziness, fainting, weakness
and moist skin, mood changes, mental confusion, upset stomach or
vomiting; for example, http://www.osha.gov/Publications/osha3154.pdf.
•	Regularly monitor temperature and relative humidity.
•	Stop the monitoring as discussed below.
11.1 Medical Management and Stop Rule
The subjects will be checked for allergic and irritant skin reactions, particularly
redness, eczema, itching or pain. The subjects will be asked to immediately
report any adverse effect including skin reaction to the Principal Investigator (or
designee). Any subject showing an adverse skin reaction will be asked to
immediately stop further participation. As noted previously, the subject's
exposed skin will be gently washed with clean water and mild soap to remove the
test product, and the area will be gently dried with a clean towel.
Since subjects will wear an extra layer of clothing, the risk of heat related illness
may be increased. The Principal Investigator will discuss the symptoms of heat
stress with the subjects. Study personnel will monitor subjects for symptoms and
signs of heat stress, and will monitor the ambient temperature, relative humidity,
and heat index (HI). Generally, if the HI exceeds 95 degrees Fahrenheit (F) the
research will be discontinued.
Study personnel will be instructed to inform the Principal Investigator immediately
of any skin reactions, heat stress, or other unanticipated adverse effects
observed or reported during conduct of the study. The medical management
procedures set forth in AEATF SOP # AEATF 11 .C will be implemented for any
instance where the subject's work is halted for medical reasons (other than solely
because of a heat stress index above 95), and for any post-study reports of
illness, skin reactions or other unanticipated adverse effects. If two or more
subjects withdraw or are withdrawn from the study for the same medical reasons,
the study will be suspended until the cause of the withdrawal is fully investigated
and determined. If two or more subjects develop an adverse skin reaction after
they leave the study site, all subjects will be contacted by the Principal
Investigator to determine whether further medical management is appropriate.
The Principal Investigator will maintain a record of adverse health observations
and reports, and follow Sponsor, IIRB, EPA and California DPR policies for
medical event reporting. Sufficient personnel will be present at the study site to
maintain an appropriate level of technical support, scientific supervision and
observations relevant to the safety of test subjects.
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11.2 Additional Procedures for Monitoring or Preventing Risk to
Subjects
If an OSHA permissible exposure level exists for an inactive ingredient, an
evaluation will conducted by AEATF II to assure exposure during the study is
less than the limit. In addition the aim is to keep exposures as low as possible
while getting less than 40% of measurements below the detection limit (so that a
majority of measurements are above the detection limit for statistical inferences
and exposure assessment). This specific aspect is what drives the need for
preliminary evaluation of existing data to determine adequacy of detection limits.
Each protocol will address emergency procedures if an adverse reaction occurs.
Where the study is conducted and what the application method is will influence
this to a certain degree, but the objective is to have the needed assistance
available during the conduct of the study. This would include evaluating potential
physical hazards (i.e., ergonomic concerns) throughout the study as well as
potential exposures to active ingredients.
As noted earlier each principal investigator assesses the availability of medical
assistance in the locality of the study. For example there are certain local
regulations and practices that need to be accounted for in designing these
studies as a few of the AEATF II studies could be conducted outside of the US.
For example, the conduct of an indoor "pour liquid" study is being evaluated for
conduct in the Netherlands at a contract laboratory facility. Open pouring of
liquids in indoor settings represents an exposure scenario that could be
realistically simulated in a laboratory setting. In some cases AEATF II must meet
local regulations that do not always allow AEATF II to be completely consistent
across various studies. However, the same objective always exists, to collect
useful, scientifically defensible data of the highest quality possible, while
minimizing exposure and protecting subjects.
As discussed later in this document, scripting in AEATF II studies will be
minimized and will primarily involve design features that ensure monitoring
intervals that represent a typical day's duration (i.e., not excessively short or
long) and coverage of the practical range for amount of product handled within
each use scenario. However, study participants will be using familiar equipment
in a manner that is typical for them. Therefore, AEATF II believes the increased
risk of heat-related illness in certain conditions is the only added risk that study
participants will likely encounter.
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12 Risk Assessment for Anticipated Exposures to
Proposed Surrogate Chemicals
AEATF II monitors exposure to subjects who handle commercially available
antimicrobial pesticide products. In general, useful surrogate chemicals [e.g.,
didecyl dimethyl ammonium chloride (DDAC), CAS No. 7173-51-5] have multiple
uses (e.g., multiple use sites and application methods), formulation types,
minimal PPE requirements (i.e., low acute toxicity), and reliable and validated
analytical methods. AEATF II will utilize extant risk assessments conducted by
EPA for the antimicrobial pesticide to be used in each study to inform the
potential for excessive antimicrobial pesticide risk that subjects may experience
as a result of participation in an AEATF II exposure monitoring study. If a risk
assessment does not exist for the exposure scenario with that chemical, AEATF
II will conduct an assessment using EPA-recommended methods.
13 Risk Versus Benefit Comparison
By monitoring exposure to professional antimicrobial handlers (or consumers)
who follow their normal practices, but wear an additional layer of clothing (as an
inner dosimeter which traps chemical that penetrates the work clothing), AEATF
ll's monitoring program generally presents a reduced risk to subjects. The risk of
dermal toxicity is actually reduced and the added risk of heat illness is mitigated
by a medical management program which emphasizes measures to prevent
heat-related illness. The potential benefits to antimicrobial workers as a whole
and to consumers and society in general, for example, in the form of more
accurate measurements of potential exposure to antimicrobial pesticides to
inform safety evaluations, versus study-specific risks, will be included in the
discussion of each study protocol.
Against the slight risks are balanced substantial benefits. Products containing
antimicrobial chemicals are used extensively in hospitals, schools, homes, etc. to
control pathogenic bacteria and viruses known to produce increased morbidity
and mortality in humans, domestic animals and pets. Measuring exposure of
subjects in this research study will produce reliable data about the dermal and
inhalation exposure of subjects and the general population performing these
tasks. The resulting data will improve the completeness and accuracy of the
database used by the EPA to assess exposure to these chemicals. The ability to
accurately predict risk may allow other chemical classes of antimicrobials to also
be registered based on exposure estimates generated from the data to be
produced by this study.
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14 Characterization of Potential Study Participants,
Exposure Monitoring Methods and Ancillary
Information
Appendix A identifies the antimicrobial pesticide handler scenarios that will be
covered by AEATF ll's generic exposure database, BHED™. However, it is
important to point out several restrictions that will be placed on the subjects to be
included in those scenarios.
14.1 Subject Characteristics
Age of Subjects
For ethical reasons, all study participants must be at least 18 years of age.
Health Status of Subjects
Only subjects who consider themselves to be in good health will be considered
for participation in AEATF II studies.
Reproductive Status of Female Subjects
Women who are nursing or pregnant will be excluded from the study. Non-
pregnancy will be confirmed by an over-the-counter urine test just prior to women
participating as study subjects for studies involving intentional exposure
Experience of Subjects
Only subjects who have experience performing the particular task will be allowed
to participate.
Monitoring Period Duration
All monitoring events (MEs) will be designed to represent a normal workday for
the particular task being monitored. Generally, this will involve monitoring
periods of at least half of a normal work day to overcome the criticism of early
exposure studies where many of the sampling regimes monitored subjects for
only a few minutes. Avoiding very short monitoring intervals will ensure that daily
exposure estimates are not biased by unusual conditions during that short
interval. Some work tasks (e.g., mopping) are performed intermittently through a
work day. When monitoring exposure for such tasks, the work schedule will be
compressed to obtain the typical duration of exposure or amount of active
ingredient handled in a normal work day.
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Product Label Conformance
All subjects will be required to perform pesticide handling tasks in conformance
with the label requirements. BHED is designed to reflect exposure to subjects
who follow legal and proper handling of pesticides and do not misuse the product
or otherwise violate the label procedures. In particular, subjects must wear the
PPE required by the label and researchers will remind participants to use that
PPE should they be observed not wearing the PPE during exposure monitoring.
If there are any special cases where it is proposed that an AEATF II study data
set is developed using measurements for a non-pesticidal surrogate chemical, all
handling will be based on OSHA-specified PPE as identified on the Material
Safety Data Sheet and/or other workplace safety requirements.
14.2Exposure Monitoring Techniques
Techniques to monitor pesticide handler exposure fall into three main categories.
These are area (environmental or industrial hygiene) monitoring, passive
dosimetry measures taken on the individual, and biomonitoring taken from
individuals.
Area Monitoring
The oldest and least accurate exposure monitoring technique to estimate
individual exposure is area monitoring. This monitoring primarily consists of air
monitoring in the general vicinity of subjects and sometimes surface monitoring
of the pesticide in the workplace. This technique is a traditional industrial
hygiene measure and can be used to monitor the pesticide manufacturing
workplace to ensure that environmental levels are controlled, but it is not
particularly useful in quantifying total worker exposure. This method may give a
reasonable approximation of inhalation exposure potential, but does not allow a
quantification of dermal exposure. Past monitoring studies have consistently
demonstrated that the dermal route is the most significant route of exposure to
pesticide handlers (Wolfe, 1976).
Passive Dosimetry
Passive dermal dosimetry taken on subjects consists of (1) patch (e.g., gauze
pad) dosimetry; (2) whole body garment dosimetry and, (3) hand/face dosimetry
techniques. Hand washes and patch dosimetry, or the use of whole body
dosimeters are methods for quantifying the amount of pesticide that contacts the
skin or clothing of a worker, and provides a measure of external (dermal)
exposure. The use of whole body dosimeters, which are usually sectioned into
standard body part areas (e.g., upper arms, lower arms, upper legs, lower legs,
front and rear torso) prior to extraction and analysis, prevents the need to
extrapolate from a small patch size to the whole body part. Personal air
monitoring devices have been used to characterize exposures via the inhalation
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route by collecting a known volume of air in the breathing zone of the worker and
analyzing for the mass of pesticide of interest present.
1.	Patch Dosimetry
Patch dosimetry was first utilized in the mid 1950s for pesticides. With
patch dosimetry the potential exposure of the subjects' skin and clothing is
measured using a number of absorbent cloth or paper patches, attached
to body regions, inside and outside clothing. Placement of patches to
represent the entire body (head/face/neck, upper and lower arms and
legs, and front and rear torso) are needed on each individual monitored.
The surface area covered by the patches represents <10% of the total
body surface area. After a defined period of exposure, the patches are
removed and analyzed for pesticide content. The quantity of a pesticide
on a patch of known area is then related to the area of body region on the
assumption of uniformity of deposition over that area. Body part surface
areas can be obtained from standard reference texts and exposure
guidance documents (EPA 1999).
The assumption of uniform deposition is probably the principal
disadvantage of the patch technique. This is illustrated by the
extrapolation of the value given by half the limit of quantification (LOQ) to
the total body part; this may give a substantial under or over-estimate of
exposure. The patch method may give significant under- or over-
estimates of exposure, depending on whether the patches have captured
the non-uniform, random deposition of concentrate splashes or spray
droplets. Individual body region exposure values are then added to give a
total potential exposure expressed in mg/hour or mg/lb of product handled
or applied.
2.	Whole Body Dosimetry
The whole body dosimeter method came into use during the late
1970s/early 1980s (Abbott et al., 1987). The method involves the use of
clothing, usually two layers of cotton or cotton/blend material, which act as
the pesticide collection media. The outer layer of clothing should be
representative of what the subjects normally wear. The inner layer,
usually 'long johns', represents the skin. The method overcame one of the
inherent problems of the patch method, i.e. the assumption of uniformity of
pesticide deposition on the skin and clothing. Exposure of the head is
assessed by use of a hood or hat preferably made of the same material,
or a patch attached to a hat. A face wipe technique can also be used, in
which the skin of the face and anterior and posterior neck is wiped with
cotton swabs containing a suitable solvent to remove the pesticide
residues.
PPE required by the product label are worn over the sampling clothing.
The selection of sampling clothing should err on the cautious side by
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utilizing the minimum clothing that might be worn under the prevailing
conditions. The use of the whole body method overcomes the perceived
problem of non-uniformity of deposition. Furthermore, extrapolation from
small target areas to larger body regions is not necessary. For these
reasons, the method is believed to give a more accurate estimate of
potential and actual dermal exposure.
3. Hand Wash
EPA (1996) reviewed the literature on studies that had included hand
exposure measurements and concluded that their contribution to total
exposure ranged from around 40% to 98%, depending upon the
application method. The methods for measuring hand exposure include
lightweight absorbent gloves, and swabbing or rinsing the hands in various
solvents (EPA 1996). Mild detergent solutions can be used in the
handwash technique, for example 'Aerosol' OT. However, AEATF II
intends to use a wash solution that will have a high solubility for the test
material. This may result in varying the solvent from study to study. For
example, in the first 2 studies proposed by AEATF II, 50%
isopropanol/water will be used to remove a quaternary ammonium
compound from the skin. All these methods have their advantages and
limitations and it is difficult to evaluate the accuracy of any procedure.
The generally held view is that the use of gloves results in a significant
over-estimation of total dermal exposure, owing to the retention of more of
the pesticide than would otherwise be retained by the skin. Gloves also
contain foreign materials such as sizing, which may be co-extracted with
the pesticide. At low levels of contamination this may cause analytical
difficulties. However, glove contamination with dirt and grease arising
from the worker's activities are a more likely cause of analytical problems.
It is important to use a solvent that adequately solvates the active
ingredient. This can be deduced from water and solvent solubility.
Inevitably there is a loss of standardization of the intervals at which hand
wash samples are taken. However, it does give some information on the
extent of hand exposure that might be of value in overall data
interpretation.
Measurement of hand exposure through hand washes has become
standard in exposure monitoring because it is consistent and mimics the
method of hand decontamination under normal work conditions. Hand
washing not only provides the best measurement of exposure, it is also
more accurate than using collection media like cotton gloves. In
monitoring via hand washes, residue only accumulates on the skin surface
(as in the real world), rather than on a multi-layer porous medium that, due
to the permeable nature of the surface, has a far greater capacity to
accumulate and store residues. However, even hand washes can
significantly overestimate exposure because most of the residue
measured as exposure should actually slough off or be washed off the
skin surface following normal hygiene (washing) during and at the end of a
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work shift. Further, several lines of evidence suggest that material
washed from hands is not all bioavailable: 1) The amount washed off in
well controlled rat dermal absorption studies shows that for most
compounds the percentage taken into skin does not change from 1-8
hours post application (Thongsinthusak et al., 1999); 2) Only a fraction of
the amount applied is dermally absorbed, with an average dermal
absorption of about 10% for pesticides applied in solution to humans
(Ross et al., 2000); 3) Much of the pesticide to which subjects are
exposed can be adsorbed to dust, and in this form it is not as available to
skin for absorption, thereby further reducing availability (Driver et al.,
1989); 4) Hand washes are taken before breaks, before meals, and at the
end of shifts so that material washed off early in the day has no
opportunity for absorption throughout the work day but is counted as part
of the exposure; and, 5) If gloves are not worn, hands frequently receive
the highest dose density, and percent dermal absorption is typically
inversely proportional to dose density (Ross et al., 2001).
Inhalation Monitoring
For pesticides that are poorly absorbed via the skin, the inhalation route can
become the most important route of absorption. An important review of personal
sampling methodology for field monitoring of airborne pesticides was published
by Lewis (1976). A personal air sampling method is the most appropriate for the
determination of potential inhalation exposure of subjects. Several techniques
are available such as solid adsorbents for vapors and sizing and filter cassettes
for particles, all attached to battery powered personal sampling pumps. A
personal sampling technique involving sampling devices located in the breathing
zone and sampling pumps is preferred, because it is a practical way to get a
representative sample. Breathing rates for the calculation of inhalation exposure
from airborne concentration data can be obtained from standard reference texts
such as EPA's Exposure Factors Handbook (1999).
The inhalable fraction (all material capable of being drawn into the nose and
mouth) is the most biologically relevant fraction to measure. An example of a
suitable device is the Institute of Occupational Medicine (IOM) personal sampling
head designed specifically to collect this fraction (Vincent and Mark, 1987). For
use of this device, a sampling flow rate of 2 L/min is a specific requirement.
Examples of suitable adsorbent materials for some volatile compounds are
activated charcoal, 'Tenax' and XAD-2 resins mounted in stainless steel or glass
tubes. The choice of material should be determined by analytical retention
(trapping efficiency) and extractability studies. Concurrent sampling for
particulates and vapor can be achieved by mounting the filter sampling head in
front of the vapor trap in a 'sampling train'. This train allows retention of any
vapor stripped off the filter on the resin. The material on the filter can be
analyzed both gravimetrically and/or chemically and an estimate made of the
pesticide content of the particulate sample. Where use of such a sampling train
is needed, laboratory validation of the sampling efficacy, particularly of the
adsorbent resin, is necessary owing to the possibility of stripping material from
the resin by the relatively high flow rate of 2 L/min.
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Biomonitoring
Biomonitoring, also known as biological monitoring, typically uses the amount of
pesticide (or its metabolites) detected in the urine of exposed individuals to
obtain an accurate measurement of the total amount of pesticide actually
absorbed by the worker via all routes (inhalation, dermal, and incidental oral
ingestion). In order to use biomonitoring quantitatively, one must have primate
(preferably human) pharmacokinetic data. Although biomonitoring provides total
absorbed doses (i.e., pesticide levels in the body), it does not explain the
contributions of each specific exposure pathway, i.e., biomonitoring data cannot
generally be used generically. However, biomonitoring data prevent the need to
extrapolate from external dosimetry to internal dose, and can serve as valuable
validation tools for passive dosimetry.
Nature of Testing Guidelines
Regulatory agencies frequently collaborate to make exposure monitoring
guidelines harmonized. A good example is the Series 875 guidelines of US EPA
that were designed with multinational input starting with a meeting in The Hague
in 1992 and punctuated with meetings in Ottawa, Toronto, and Washington, DC
that culminated with the issuance of OECD and EPA guidelines that are very
similar (OECD, 1997; EPA, 1997).
Justification for Passive Dosimetry
Because it is difficult to isolate and validate particular dermal dosimetry methods,
the best validation is a comparison of the sum of passive dosimetry methods
against the biomonitored dose. The data examined in a recent review of both
proprietary and published studies demonstrated an excellent correlation between
passive dosimetry and biomonitoring (Ross et al., 2007). Passive dosimetry as a
measure of dosage appears to be consistent with biomonitoring with no bias, i.e.,
there is no tendency to over or under estimate exposure. This evaluation
demonstrated that the total absorbed dose (or daily dosage) estimated using
passive dosimetry for important handler and reentry scenarios is generally similar
to the measurements for those same scenarios made using human urinary
biomonitoring methods. Further, this is strongly supported by statistical analysis
of individual worker passive dosimetry: biomonitoring ratio and variance within
and between studies. The passive dosimetry techniques currently employed
yield a reproducible, standard methodology that accurately and reliably quantifies
exposure and does not underestimate daily absorbed dose.
14.3 Role of Ancillary Study Information
Every exposure monitoring study collects data that characterizes the
environmental conditions and behaviors that may have some influence on worker
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exposure. The environmental data includes temperature, humidity, airflow or
wind speed and directionality, light levels, detailed descriptions of the equipment
used to mix/load or apply the chemical, measurements of the amount of chemical
used dilution rates, water source, chemical source, etc. Behavior of each
individual monitored including work rate, personal hygiene, neatness or attention
to detail, personal habits e.g., tobacco, chewing gum, method of using gloves,
evidence of fatigue, etc. are all recorded either with field notes and/or with
photography including video. Although most of this information cannot be used
to quantify individual exposure, it can be extremely useful in understanding how
conditions/behaviors observed during the study compare with "normal" conditions
or behaviors, and how any unusual conditions may have contributed to
differences in exposure.
15 Incorporation of Existing Data into BHED™
To establish the need for additional exposure monitoring data involving human
subjects, AEATF II conducted a systematic review of all available, relevant data
for each scenario proposed for inclusion in the multi-year program. This process
included publicly available data (e.g., specific data subsets from PHED) and
proprietary data sources (e.g., CMA study). Each of potential data source has
the potential to provide scenario-specific exposure data (MEs) and associated
supporting information for inclusion in BHED™. A data evaluation process was
developed for the evaluation of existing data sources and involves the following
steps:
•	Development of data acceptability criteria: The existing data
acceptability criteria addressed general study design and exposure
monitoring techniques, including the analytical and quality control aspects
of the studies. They are detailed in Appendix D.
•	Primary review: A process that involved the screening of handler
exposure data from PHED version 1.1, publicly available data, and
compensable data owned by AEATF II members.
•	Secondary review: A detailed evaluation of data that passed the
screening process for acceptability under the acceptance criteria with
decision records for each study review.
•	Final review: A process that involved guidance by regulatory agencies
including the U.S. EPA, Health Canada, and California EPA, on
acceptance of the data for use within BHED™.
Much of the existing data are deemed unsuitable for a generic database due to
poor QA/QC (generally low or insufficient field fortification recoveries), a
preponderance of non-quantifiable residues, or the use of testing conditions that
do not represent current pesticide handling practices in North America. Another
key technical issue that eliminated some existing data was the decision to
exclude exposure data for subjects who wore more than a single layer of
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clothing. This decision was discussed with the Regulatory Agency Advisory
Committee who agreed that a modern generic database would be most useful if it
contained exposure data for minimal clothing and PPE situations. Regulators
prefer to estimate protected exposures (e.g., dermal exposure under coveralls
plus normal clothing) from unprotected exposure measurements (e.g., dermal
exposure under just one layer of normal clothing) than vice versa. Therefore,
BHED™ has been designed so that clothing/PPE protection factors can be
estimated by a user from the two dosimetry clothing layers in order to estimate
protected exposures (typically workers), or consumer (unprotected) exposures.
16 Monitoring Event Selection
Each AEATF II antimicrobial-handling scenario will be addressed by one (or
possibly more than one) study. The purpose of each study is to obtain
monitoring events (ME) for incorporation into BHEDTM. The specific details of a
study design will necessarily differ from scenario to scenario. The scenario
design documents and study protocols will provide the rationale and description
of the specific ME selection procedures. This section summarizes those aspects
of the ME design common to all scenarios. Appendix E provides a more
extensive description of the concepts and procedures for selection and
construction of monitoring events.
16.1 Predicting Future Generic Exposures with Monitoring
Events
For the purposes of the AEATF II monitoring program, the basic element of a
scenario is considered to be the handler-day (HD). Each handler-day
corresponds to a particular worker and the scenario-related activities that he
performs during a single work day. Regulatory interest for each antimicrobial-
handling scenario is centered on predicting occupational exposure under a
specific set of generic future handler-day conditions. In particular, it is desired to
characterize exposures resulting from the future use of an arbitrary (and perhaps
currently non-existent) antimicrobial active ingredient at some arbitrary, but
quantifiable, amount of active ingredient contact.
An ME is the basic tool used by the AEATF II Monitoring Program to predict
exposures. Each ME is a set of scenario-specific handler-day (HD) conditions
that have been experimentally selected (i.e., chosen, simulated, or constructed)
to represent expected future HD conditions. Every ME is also monitored to
obtain a measurement of the actual exposure resulting from the simulated or
selected HD conditions.
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An ME can predict future exposure only if the handling conditions of the ME
represent future HD conditions. Because each ME is expensive, it will be
possible in practice to construct only a small number (N) of MEs. Obviously, a
set of only N MEs cannot predict every possible future HD condition. The
successful use of a small set of MEs to represent the diversity expected among
future handler-days is aided by three factors:
1.	Dermal and inhalation exposure to the chemicals are considered generic
(i.e., independent of the particular active ingredient used). This generic
principle permits use of a small set of surrogate active ingredients to
predict exposure from other active ingredients.
2.	Exposure is considered to be proportional to the true amount of active
ingredient contacted by the antimicrobial handler. The exposures
obtained from MEs are expressed relative to a measurable normalizing
factor (NF) is expected to be proportional to amount of active ingredient
contact. Then exposures for any future NF level of interest can be
predicted by multiplying the normalized exposures by this future level.
3.	Expert knowledge of possible handler conditions expected throughout the
scenario if obtainable. This permits construction of MEs from HD
conditions selected (i.e., simulated or chosen) to represent a diverse set of
future handler-day conditions.
If the ME conditions can be appropriately chosen then a useful set of MEs can be
constructed and used as a predictor of future HD exposure in an aggregate
sense.
An exposure distribution is a reasonable aggregate description of future handler-
day exposures for a scenario. The future HD distribution describes the likely
exposure that would result if one were to randomly pick a future HD among those
using ai X when the level of the normalizing factor is HX. There are actually a
series of predicted exposure distributions, one for each possible value of HX.
However, since any predicted exposure can be computed from the normalized
exposure, it is simpler to focus only on the distribution of normalized exposure.
The complete normalized exposure distribution is rarely needed. Regulatory
interest most often focused on just two general aspects of this distribution:
• The middle values such as the arithmetic mean or the median. These
exposure values tend to characterize average or 'typical' exposure levels.
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• The larger values of exposure possible, such as the 95th percentile of the
distribution. This aspect better characterize the extreme, one-time, worker
exposures.
It is desired that the set of predicted exposures obtained from the set of MEs
adequately characterize the middle and larger values of the future HD
distribution. Technically, a set of constructed MEs cannot be a random sample
from a distribution of future HD conditions. But some random sampling
interpretation might still be a convenient and reasonable model for how the set of
predicted exposures from the MEs relate to the future (normalized) exposures for
an arbitrary antimicrobial. This permits the use of conventional statistics, such as
means and percentiles, calculated from the observed ME exposures to
approximate the 'middle' and 'larger' exposures expected in future HDs. For the
AEATF II Monitoring Program, confidence in this approximation is improved by
using a reasonable reference random sampling model (16.2.2) rather than
assuming just simple random sampling. In addition, diversity selection (16.3),
using both purposive and random components, is used whenever possible.
Diversity selection is an attempt to obtain, as much as is practical for small
sample sizes, a diversity of conditions that are expected to influence exposure,
either directly or indirectly. This increases the likelihood that the range of
conditions in the future HD population expected to impact exposure is reflected in
the 'pseudo-sample' of MEs as well.
16.2 Determining the Number of Monitoring Events
16.2.1 The Two-Stage ME Selection Process
Although the details of will vary from scenario to scenario, the ME selection
process will always have the same general two-stage structure. The first stage
consists of selecting or constructing specific locations and specifying a range of
dates for monitoring at each location. Each such local area and range of
potential monitoring dates is termed a monitoring site.
The second stage consists of selecting one or more subjects and handling
conditions within each site and constructing the MEs. For simulated condition
studies the MEs are created by assigning appropriate subjects to scenario tasks
under conditions that are expected to exist in the future HD population. For in
situ studies, appropriate handler-days are selected from among existing subjects
and conditions that are expected to represent future HD conditions.
In general, Nc sites are selected at the first stage and NM monitoring events
(MEs) will be obtained within each site at the second stage. When NM is greater
than one, the set of MEs at the same site is termed a cluster. In general, MEs in
the same cluster are expected to be more similar than those in different clusters.
This correlation usually means that the smallest total sample sizes (i.e. total
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number of MEs) are attainable when there is only a single ME per site. On the
other hand, there are often substantial overhead costs per site that make multi-
ME sites more efficient.
16.2.2 The Two-Stage Random Sampling Reference Model
In the strictest sense, sample sizes can only be determined using statistical
theory alone when either
1.	There is assumed random, representative sampling from a population and
the goal is to estimate some characteristic of that population; or
2.	There is assumed randomization of experimental units to treatments and
the goal is only to compare or to contrast treatments in some manner.
Only in these two situations will statistical theory predict how increasing sample
size decreases estimation error. In other experimental situations, sample size
must be determined using one of the two 'random' situations above as a
reference model. The random reference model is constructed so that it reflects
the actual situation (i.e., a mixture of random and non-random selection) as
closely as is practical.
The sample size that is appropriate for the reference model is then used for the
actual study design. In a real sense, then, the reference random sampling model
is used to establish benchmark sample sizes that can satisfy benchmark
objectives. Although rarely stated explicitly, the use of reference sampling
models and benchmark objectives are quite common.
Because all AEATF II scenarios have a two-stage selection structure, they will all
use the same reference sampling model. For each scenario, two-stage random
nested (or cluster) sampling is the reference model used for the combination of
purposive and random two-stage diversity selection that actually occurs. This
reference model assumes that:
1.	Exposure, normalized by the potential active ingredient contact factor, is
lognormally distributed with geometric standard deviation GSD.
2.	There are Nc clusters (i.e. sites) and NM MEs per cluster. The total
number of MEs in a scenario is, therefore, N = NCXNM.
3.	The within cluster (i.e., within-site) correlation of (log) normalized exposure
is equal to ICC.
The reference sampling model incorporates a two-stage selection structure and
the potential for correlation within clusters, but ignores any effects of diversity
selection. The ICC is irrelevant to the future distribution of normalized exposure,
per se. However, this intra-cluster correlation is a necessary part of the
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reference sampling model because the MEs are obtained in clusters (i.e. there
are multiple MEs per site).
16.2.3 Benchmark Objective
The benchmark objective for all AEATF II monitoring program scenarios will have
the general form:
If there are Nc clusters and NM MEs per cluster and the
underlying lognormal two-stage reference sampling model
were actually true, then selected parameter estimates will be
within K-fold of the true values at least 95% of the time.
If the true parameter of the sampling model is denoted by 0 and its sample
estimate by T, then T is within K-fold of 0 whenever
(1)	fRA = Max ( T/ 0, 0 / T ) < K
The quantity fRA is called the fold relative accuracy of T. To satisfy the condition
(1)	above 95% of the time requires that the 95th percentile of fRA, fRA95, be no
greater than K. If the 2.5th and 97.5th percentiles of the sampling distribution of
T are denoted T2.5 and T97.5, respectively, then this benchmark objective can also
be stated as:
(2)	fRA95 = Max ( T97.5 / 0, 0/ T2 5 ) ^ K
EPA provides guidance to AEATF II on the minimum degree of benchmark
accuracy needed for regulatory use in particular scenarios. The current
consensus is that estimates of the geometric mean, the arithmetic mean, and the
95th percentile should be accurate to within approximately 3-fold of their true
value.
It should always be kept in mind, however, that this objective is specified in terms
of the reference random sampling model. This reference sampling model does
have the same two-stage nesting structure as the actual ME selection approach.
The lognormal distribution assumption is also reasonable, robust, and consistent
with existing data. However, the reference distribution assumes simple random
sampling at each stage. It does not, and cannot, incorporate the combination of
purposive and random diversity sampling actually used. As discussed in
Appendix E, the consequence of diversity sampling is expected to be a tendency
for the sampling variation of normalized exposure to be overestimated. The
sample should over-represent extremes and under-represent the more common
values. Such diversity-oriented data collected for this scenario, but analyzed with
respect to the two-stage reference distribution, is expected to have minimal bias
for central tendency. In contrast, upper percentiles of exposure are expected to
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be, on the average, too large. There is no way to determine the actual
magnitude of such overestimation. In this case, overestimation of upper
percentiles is of minimal concern: for practical exposure assessments,
overestimation of exposures is a conservative practice utilized by regulatory
agencies. A tendency to both consider and even overestimate upper percentiles
is consistent with this practice.
16.2.4 Sample Size
Under the reference two-stage random sampling model described above, the
only quantities needed to determine relative accuracy of population parameter
estimates are reasonable values for GSDnE and ICC. Such values could be
based on existing exposure data for scenario-specific tasks, surrogate exposure
data from similar tasks, and/or reasonable assumptions based on subject-matter
expertise.
Given values for GSDnE and ICC, fRA95, can be computed for any combination of
Nc and NM and compared with K. Calculation of the 95% percentile of fold
relative accuracy is complex, however, and is usually best accomplished using
Monte Carlo simulation methods. When the number of MEs per cluster, Nm, is
the same for all clusters, a straightforward simulation approach can be used to
determine fRA95. This procedure is:
1.	Simulate a set of normalized exposure data for Nc clusters and Nm
monitoring events per cluster using the two-stage reference
sampling model.
2.	From each set of simulated data, calculate T, the estimate of 0
3.	Repeat steps 1 and 2 above M times to get M values of the
estimate T
4.	From these M T-values calculate T2.5 and T97.5, the 2.5th and 97.5th
percentiles of T, respectively.
5.	Calculate the 95th percentile of fold relative accuracy, fRA95, using
formula (2) above.
The number of simulations, M, should be some large number such as 1,000 or
10,000. This process can be continued until a combination of Nc and NM are
found that satisfy to benchmark objective.
16.3 General Diversity Selection Guidelines
In general, the objective of diversity selection is simply to obtain a diverse set of
handler-day conditions from among those conditions possible in when an
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arbitrary ai is used in future scenario-related tasks. These selected HD
conditions are then used to construct monitoring events. Diversity selection is
conducted independently at each of the two stages of selection. Thus, a diverse
set of sites is selected followed by a diverse set of ME conditions within each
site.
In the AEATF II Monitoring Program, the term diversity selection is preferred in
lieu of the phrase diversity sampling. This is to emphasize the fact that the future
HD conditions used for MEs are selected from either existing or from synthesized
conditions (or from both). This selection of conditions can employ both
purposive and random elements. When there are multiple diverse configurations
available, random selection from among such configurations can reduce the
likelihood of intentional selection bias. On the other hand, when some possible
ME configurations are more diverse or more cost effective than others, it might
be preferable to select these purposively.
Diversity should always be with respect to characteristics that are expected to
impact exposure. Diversity selection attempts to create a sample that contains
as many of the different conditions as possible that exist in the population. If the
diversifying conditions are associated with exposure, then a diversity sample will
tend to be more variable with respect to exposure than would a same-sized
representative sample. In effect it will be analogous to representative sampling
from a distribution that is more diverse than the actual future one.
Whenever possible, the characteristics used should be meta-factors. Meta-
factors are characteristics that indirectly influence a number of other
characteristics. For example, a worker is a meta-factor because substituting one
worker for another alters a number of factors (e.g., behavior, physical
appearance, stamina) that might affect exposure. Other common meta-factors
are geographic location and time-of-year. Not every characteristic that may
impact exposure can be, or even should be, considered in diversity selection.
The number of possible combinations of factors that may impact exposure will
always greatly exceed the number of planned MEs. Consequently, only a few
characteristics, preferably meta-factors, can be used effectively in diversity
selection.
16.3.1 Stratified Diversity Selection
As discussed in Appendix E, there are a number of acceptable approaches that
can be used to achieve diversity among ME handler-day conditions. Among the
formal methods, stratified diversity selection is often the simplest to implement.
In this approach available selectable units (e.g., sites, MEs) are partitioned into
strata based on characteristics likely to impact exposure. Each possible
selection unit must belong to one and only one stratum. The number of strata
must be at least as large as the number of units that will be selected. (For
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example, if there are three units to be selected, then there should be at least
three strata.) Diversity could be achieved by selecting (purposively or randomly)
no more than one unit from each stratum. If there are more strata than units to
be selected, then a subset of the strata should be selected first. This could be
either purposively (to increase diversity) or randomly (to reduce intentional
selection bias).
16.3.2	Diversity Selection of First-Stage Units
At the first stage of ME selection sites are the 'selectable' units. Diversity
selection of sites means obtaining sites that are different from each other, on the
average, with respect to some characteristic(s) expected to impact exposure. If
sites are constructed environments, then they can be built to be different from
each other with respect to important characteristic(s). If there are a number of
possible sites available and a set is to be selected (randomly or purposively),
then stratified diversity selection of sites, based on the important
characteristic(s), is a feasible approach
16.3.3	Diversity Selection of Second-Stage Units
The second stage selection units are the final MEs. The MEs should be
diversified independently within each selected site. In most cases within-site
diversity selection of MEs focuses only on two characteristics: subject and
normalizing factor.
Handling-day exposures for the same individual (on different days) are expected
to be correlated since worker characteristics and behaviors are repeated. This
is not true for different workers. Worker behaviors are expected to have great
impact on exposure. Consequently, diversity is always increased by simply
requiring that each ME be constructed using a different individual.
MEs should also be diverse with respect to the normalization factor that is
deemed appropriate for the scenario. One feasible approach is to partition the
possible levels of NF into NM strata and construct one ME from each stratum. In
some cases (e.g. simulated-condition studies) there is a pool of available workers
that can be assigned to any NF stratum. If all possible configurations of
assignment are equivalent, then workers could be randomly allocated to strata. If
some allocations are non-equivalent (e.g. more cost effective or there are
scheduling issues) then a purposive assignment of individuals to NF levels might
be preferable.
In other cases (e.g. In Situ/observational studies) worker availability depends on
the particular NF level chosen. Some individuals may only work with higher NF
levels and some with only lower NF, say. Selection of workers could still be
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random, although random choice would be within each NF stratum. However,
when such associations between subject and NF levels exist, purposive
allocation might result in a more cost effective and practical configuration.
17 Description and Role of AEATF II Studies
In the context of the BHED™ exposure monitoring program a 'study' takes on a
specialized role. It is that component of the program actually conducting MEs in
accordance with the spirit of Good Laboratory Practice (GLP) standards issued
by EPA (40 CFR 160). AEATF II studies meet the definition of study in the GLPs
at 40 CFR §160.3, which reads in pertinent part: "Study means any experiment at
one or more test sites, in which a test substance is studied in a test system under
laboratory conditions or in the environment to determine or help predict its effects
. . . or other characteristics in humans ... or media." Each AEATF II study will
involve conducting MEs under one or a number of scenarios. For example, a
study might be designed primarily for mopping application, but exposure of the
mixer/loaders who prepare the mop liquid mixture will be a different study.
Because it has a very restricted, albeit important, function within the BHED™
program, the study protocol need not contain extensive program information that
is not relevant to the conduct of its particular MEs. However, each study protocol
will reference the AEATF II program "governing document."
In most cases, AEATF II study timing and location are not dictated by the
seasonality of work to be performed. However, finding sites and making
arrangements for the studies is often challenging, particularly in observational
studies (e.g., subjects at a wood preservative treatment facility) where no
scripting of subjects' activities while handling pesticides would be allowed.
Further, the AEATF II must identify sufficient usage to define and follow a
representative day of the specific pesticide handling activity for each participant
(or monitoring unit or event, i.e. ME). Since some studies consist of monitoring
participants performing activities that are governed by variable schedules, etc., it
is nearly impossible to provide full protocol details (e.g., specific site, surrogate
compound, application rate) required by the Good Laboratory Practices
regulations and still satisfy the review schedule of U.S. EPA and the HSRB,
which must be done many months before a study can be conducted. In contrast,
for studies that can be conducted in an experimental manner, wherein a
surrogate environment (e.g., experimental chamber) can be used and various
parameters controlled, a more definitive protocol design can be provided.
All MEs required by the sampling design for most use scenarios can be collected
in a single study, and most individual AEATF II study protocols will describe a
single-study and single-year monitoring program designed to generate a range of
exposure monitoring data for all discrete activities associated with that use
scenario. An individual protocol typically represents a single, stand-alone study,
representing MEs performing a single activity. In some cases data from more
than one study will be combined for a given scenario.
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Each exposure study is performed in accordance with long-standing EPA
guidelines for conducting occupational and consumer exposure studies (Durham,
1962; Wolfe, 1967; WHO, 1975 and 1982, OECD, 1981; NACA, 1985; Chester,
1993; Worgan, 1995) as described in Series 875: Occupational and Residential
Exposure Test Guidelines (U.S. EPA, 1986 and 1996) and in accordance with
U.S. EPA FIFRA Good Laboratory Practice Standards (GLPs), 40 CFR, Part 160
(U.S. EPA, 1989). These guidelines are consistent with guidelines used in other
countries such as Canada, Australia, and members of the European Union.
All of the individual study protocols will have many elements in common (albeit
with scenario- and study-specific aspects) in order to have consistency and
uniformity in the data sets. Exposure monitoring protocols differ mainly in the
specific product used, equipment used, timing of the study, location and activity
performed.
18 Documentation Procedures
Exposure monitoring studies conducted by the AEATF II are designed to
measure potential exposure to subjects as they perform specific antimicrobial
pesticide handling activities. As specified in AEATF II Standard Operating
Procedures (SOPs; see current master list in Appendix G) and each study
protocol (and as required by GLPs) all aspects of study conduct are fully
documented. Most of the information collected during each study is entered by
hand on paper by researchers on standard data forms provided by AEATF II.
Much of the information that is collected during the study is also entered into the
generic database, BHED™, for use in data analysis and for examination by
database users in conjunction with data from other AEATF II studies. Information
about subjects will be recorded under their unique ID code, and not in connection
with their name or any other identifying information.
As required by GLPs, all raw data entries are made in ink and are signed and
dated by the person who entered the data. In addition, data corrections must be
made by marking a single line through the incorrect information, writing the
correct information instead, and entering the reason for the change, typically as
one of a set of standard codes that explains why the correction was made.
Again, that entry must be initialed and dated by the researcher making the entry.
Raw data, including viodeography, are collected in a study notebook and study
file, which is retained indefinitely in AEATF II archives. In addition, a certified
copy of the data set is made during report writing and report review so that the
original does not have to be shipped between author and Quality Assurance, and
in case the original is lost during transit to archives.
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19 Quality Assurance Procedures
GLPs require rigorous quality assurance procedures to assure the quality and
integrity of the data. All aspects of the studies are monitored by appropriate
quality assurance units (QAUs) while studies are in progress to ensure
compliance with FIFRA GLP regulations (40 CFR Part 160) and adherence to the
protocol and relevant Standard Operating Procedures. This generally involves
three different QAUs: one from the exposure monitoring contractor that conducts
the study, one from the analytical laboratory that determines the level of
antimicrobial pesticide residues in samples, and one from AEATF II (the
sponsor). For each study, the following specific activities, among others, are
conducted by these QAUs:
•	AEATF II QAU inspects all contract research organizations and
laboratories prior to use in a study to ensure that those researchers
operate in compliance with GLPs
•	AEATF II, Field Contractor and Analytical Contractor QAUs each review
protocols prior to finalization
•	AEATF II QAU performs periodic study inspections, while contractor QAUs
perform periodic study inspections of their respective (analytical or field)
portions
•	Field Contractor QAU audits the raw data file in the field and Field Report
•	Analytical Contractor QAU audits the raw analytical data and Analytical
Report
•	AEATF II QAU reviews and audits the final report which includes the Field
Report and Analytical Report as appendices
Each QAU submits an inspection report(s) to the Study Director and AEATF II
Sponsor's Representative and any exceptions to full GLP compliance are
summarized in the Final Report associated with each protocol.
20 Quality Control Procedures
In addition to the formal quality assurance efforts discussed above, there are a
number of important quality control procedures which are followed in order to
assure that exposure measurements are accurate and precise and to define what
those exposure measurements represent. These include complete validation of
all analytical methods; extensive documentation of exactly what the subject does
while handling the antimicrobial pesticide product; field fortification and control
samples designed to estimate stability of chemical residues during sampling,
transit, and storage; laboratory fortification and control samples designed to
establish efficiency of the analytical methods on a day-to-day basis; and detailed
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guidelines on the use of calibration curves to determine chemical residues found
on all sample matrices.
In the field during each study, a chemist prepares exposure matrix samples that
are fortified with a known amount of active ingredient. These matrices include
whole body dosimeters WBD (cotton long underwear and outer work clothing),
hand wash solvent solution, face/neck wipes moistened with solvent solution,
and inhalation tubes (referred to as OVS tubes which stands for OSHA Versatile
Samplers). OVS tubes are fortified in the laboratory by injecting diluted analytical
grade active ingredient onto the sorbent in the tube while all other matrices are
typically fortified in the field with a solution or suspension of diluted test
substance (from individual vials prepared in the laboratory). Each matrix type is
generally fortified at three levels of active ingredient designed to span the range
of residues anticipated to be collected from subjects. At each level, triplicate
samples are fortified. In addition, control samples are prepared for each matrix
to determine whether background levels of active may be present. Control
samples serve as a form of negative control. In general, field control and
fortification samples are collected on at least two days during each study and
whenever significantly different weather conditions are expected.
Fortified WBD and OVS tubes are "weathered" in the field since these sample
types involve collection of residues during the monitoring period. For WBD, this
involves laying a fortified section of long underwear onto a table in a sunny
location and covering that sample with a single layer of outer shirt material.
Fortified shirt material is not overlaid to simulate outer garment weathering. For
OVS tubes, this involves drawing air through the tube in the same manner as
done for subjects. Fortified hand wash and face/neck wipe samples are not
weathered since these samples are collected at specific time points during the
monitoring period and immediately placed into frozen storage.
Analysis of field fortification samples provides a "recovery" value which will
quantify stability of the active ingredient during sample collection (for weathered
samples), storage in the field, shipment to the laboratory, and storage in the
laboratory freezer. Therefore, field fortification samples serve as a form of
positive controls. Field fortification samples are analyzed along with worker
exposure samples and it is assumed that the worker samples experience similar
stability as the field fortification samples. Therefore, residues found in worker
samples are adjusted by appropriate average field fortification results to estimate
the residues actually collected in the field. These practices are now very
standard in pesticide exposure monitoring and are discussed in detail in
internationally accepted testing guidelines.
Similar quality control procedures are followed in the laboratory, including control
and fortification samples which are designed to detect background residues,
monitor the performance of the method, and detect matrix or reagent
interferences which may be present. These samples serve as a form of positive
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and negative controls. In addition to the detailed analytical methods for each
surrogate and each matrix, all analyses must follow detailed AEATF II analytical
guidelines which specify procedures related to standard curves, extract handling,
documentation, etc. These procedures are specified in OPPTS Guideline Series
875.
21 Reporting Process
A detailed report is generated for each study, a "final report" in GLP terminology.
These reports include a text and tabular summary, and detailed appendices
including a Field Report and an Analytical Report. These reports are formally
submitted to EPA, CDPR, and PMRA as they are completed. In general, these
reports detail exactly what was done in the study, the results of analysis of
residues, and what information will be entered into BHED™. However, individual
study reports which do not represent data for a complete scenario will not include
an analysis or interpretation of the exposure data generated.
Field reports document the conduct of exposure monitoring, including:
•	Identification of the location of the study, and the environmental conditions
during the exposure monitoring period(s)
•	Descriptions of the subjects in the study
•	Description of the test substance and packaging
•	A record of the mixing, loading, and/or application, including a description
of the subjects, equipment, and worker activities
•	A summary of worker observations identifying any specific occurrences
that may contribute to unusual worker exposure
•	Descriptions of the work clothing and personal protective equipment worn
by each worker
•	A detailed summary of the amount of test substance handled or applied
for each worker
•	A detailed summary of the length of time each worker was monitored
•	A complete description of the field recovery evaluation with a summary of
specific handling and weathering of all field samples
•	A complete description of collection, handling, storage, and shipping of
samples.
•	A complete description of the ethical conduct of the field study, including
all elements required by 40 CFR 26.1303
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Analytical reports of individual field studies will document the handling and
analysis of residues in all samples collected in the study, including:
•	Results of analysis (e.g., |jg/sample)
•	A detailed description of the analytical instrumentation and methods
•	Example calculations
•	A summary of field and laboratory fortification recovery data
•	Representative chromatograms of control, treated, fortified samples and
calibration standards
•	A typical standard curve
Study reports summarize the field and analytical aspects and include calculations
of adjusted residues found in all collected samples (i.e., adjusted for field
fortification recovery); total dermal exposure for each worker; and the air
concentration of active ingredient associated with each worker's monitoring
period. Study reports are formatted in accordance with EPA requirements and
include all required components.
22 Scenario Monographs
As part of the documentation supporting BHED™, AEATF II will generate
scenario monographs for the benefit of regulators and other potential database
users. Each monograph will include a description of the scenario as well as an
assessment of the data adequacy within that scenario. More specifically, the
monograph for each scenario will include:
•	Detail definition of the scenario, including any restrictions.
•	Representative use information for AEATF II member products to define
application methods, rates, use sites, etc.
•	Information about the diversity of work practices (equipment and
procedures) currently in use in North America
•	Summary of any existing data acquired by AEATF II
•	Scenario design summaries for AEATF II studies
•	Data tables presenting the monitoring data collected for each ME
•	Statistical evaluation of the adequacy of ME data with respect to the
benchmark objective
AEATF II may also include in the monograph additional recommendations
concerning the use of the ME data. Scenario monographs will also be formally
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submitted to the regulatory agencies when AEATF II determines the data
collection for a particular scenario is complete.
23 Evaluation of Data Adequacy for Completed BHED™
Scenarios
The ultimate purpose of the monitoring program is to make the individual ME
exposure data from all scenarios available to users of BHED™, i.e., to provide a
generic pesticide handler exposure database. AEATF II will not analyze the
scenario data for the purposes of exposure characterization or risk assessment
as part of this data development program. Regulators and other potential users
of the generic database will conduct such analyses. However, as part of the
generic database development and documentation activities, AEATF II will
evaluate how well the collected data meet the pre-specified benchmark
adequacy objective. In addition, the AEATF II will quantify the impact of ignoring
clusters and treating the data as a simple random sample. The results of this
evaluation will be included in the scenario monograph (see section 22).
Whenever appropriate, AEATF II will include in the monograph additional
recommendations concerning the use of the ME data.
23.1 Benchmark Adequacy of the Completed Scenario
As defined in Section 16.2.3, the benchmark objective for each scenario is that
selected lognormal-based estimates of the normalized single-day exposure
reference distribution be accurate to within K-fold, at least 95% of the time. The
benchmark estimates of interest are the arithmetic mean and the 95th percentile.
In principle, the value of K could be scenario-specific although the current
consensus is that for regulatory purposes K=3 is an acceptable default for all
scenarios. In each scenario design plan will be a brief discussion of why K=3 is
appropriate for that scenario, or alternatively the rationale for choosing another
value of K.
As emphasized in section 16.2 above, it important to keep in mind that, like the
sample size determination, this statistical adequacy benchmark is relevant only
within the context of the reference random sampling model defined in Section
16.2.2. In particular, the monitoring data will be treated as if it were collected as
a two-stage random sample from an infinite lognormal population. Technically,
there is no statistical theory that can be applied to non-random samples (or even
to random samples for which the probability structure is unspecified). Nearly all
monitoring data used for regulatory purposes is of this type. As has always been
the case, statistical conclusions based on such data imply the qualification: "to
the extent that the data can be viewed as deriving from a true random sample."
As pointed out in 16.2 above, diversity selection is expected to yield MEs that
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tend to overestimate the true variation among future exposures. This suggests
that the estimates of upper percentiles will tend to be overestimated (and lower
percentiles underestimated) in the resulting monitoring data. With the small
sample sizes used in this scenario, however, such estimation bias is probably
trivial relative to ordinary uncertainties due to sampling, whether random or
purposive.
This benchmark is also necessarily based on pre-data assumptions about the
true nature of the exposure variation. It would be unlikely for all these
assumptions to be exactly satisfied for every scenario. Although slight deviations
will have little or no impact, large deviations from the assumptions might result in
data that deviate too far from the benchmark objective. Consequently, it is also
of value to assess the benchmark requirement using the ME data actually
obtained. The K-fold benchmark above is specified in terms of the true variation
structure and the resulting probability that certain characteristics would be
observed in the data. Once the data are available, however, such probability
statements are less relevant than confidence statements calculated from the
actual data. Consequently, evaluation of the benchmark objectives will be based
solely on confidence intervals.
To assess this benchmark goal, a 95 percent bound on relative accuracy will be
calculated from confidence intervals for the arithmetic mean and the 95th
percentile. For a particular parameter, 0, let T denote its estimate calculated
from the fit of a cluster sampling (variance component) model to the normalized
exposure data. Further, let 0a and 0b denote the upper and lower limits,
respectively, of a 95% confidence interval for 0. In most cases, the confidence
interval, (0a, 0b), will be a parametric bootstrap percentile interval obtained by
resampling from a lognormal cluster sampling model. The 95 percent upper
confidence bound on realized fold relative accuracy (fRA) is then calculated as:
UCLgs{fRA) = Max ( T / 0a, 0b / T )
The values of UCL95{fRA) will then be compared with the pre-specified relative
accuracy benchmark objective, K.
23.2 The Impact of Ignoring Clusters
As described in Section 16 and Appendix E, the AEATF II monitoring design
involves selecting MEs in two-stages: Nc Sites are selected in the first stage and
a cluster of NM MEs are selected in the second stage. Thus, a cluster is a set of
MEs obtained in a single study at a particular geographic location (e.g., building)
over a limited period of time (e.g. several days). Clusters are not a property of
the future handler-day exposure distribution, per se, but merely necessary
artifacts of the sampling process. Exposures for MEs in the same cluster are
likely correlated to some degree. If so, then estimates of parameters should
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accommodate this correlation. If a user ignores clusters (i.e., assumes the data
are a simple random sample), then some parameter estimates may be biased
and the confidence intervals may be too small. On the other hand, for the MEs of
a particular scenario, such biases may be small and of little practical importance.
When this is the case, analyses of the data can be simplified considerably. As
an aid to regulators and other potential BHED™ users, the impact of ignoring
clusters will be examined.
Estimates and confidence intervals for parameters of the normalized exposure
distribution will be calculated using a model containing random cluster effects.
From this analysis the variance components and intraclass correlation (ICC) and
their confidence intervals will be estimated. In addition, the parameter estimates
will be calculated assuming no cluster effect (i.e., assuming simple random
sampling). These simplified estimates will be compared to those obtained under
the cluster-sampling model. The differences, if any, obtained by ignoring clusters
will then be summarized for the benefit of BHED™ users.
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24 References
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Appendix A: AEATF II Scoping Document:
American Chemistry Council
Antimicrobials Exposure Assessment Task Force II (AEATF II)
Background and Scoping Summary
April 23, 2007
INTRODUCTION
On November 1, 2004, the American Chemistry Council Biocides Panel established an
Antimicrobial Exposure Assessment Task Force II (AEATF II or Task Force) to conduct
exposure monitoring studies involving the mixing, loading and application of products
containing antimicrobials or industrial biocides.1 The Task Force also has planned to
develop methodologies to assess post-application exposure to applied products
containing biocides, and will continue to work with EPA, CDPR and PMRA to determine
the most useful approach, based on current regulatory needs. The Task Force aims to
design study protocols that will make study results broadly acceptable to both North
American and European regulatory authorities. The Task Force currently consists of 43
companies.
The AEATF II will generate generic exposure data on a broad range of use
pattern/application methods to support the Registration, Reregistration and Registration
Review of most antimicrobial active ingredients. Regulatory agencies now conduct most
risk assessments for antimicrobial uses employing the stringent risk assessment criteria
evolved from implementing the Food Quality Protection Act of 1996 (FQPA). There is a
very limited amount of empirical exposure data for antimicrobial uses and EPA and other
regulators routinely have used highly conservative estimates of exposures to assess
antimicrobial risks.
Given the wide use of antimicrobials, developing generic exposure data is the most cost-
effective and efficient approach to the needs of this industry. Moreover, given the highly
segmented markets and diverse users of the same or similar antimicrobial products, a
generic approach is the only practical way that data of the quality required by EPA can
be generated. To this end, many of the studies are being designed to collect generic
data that can be applied to the widest possible range of use scenarios.
Following is a brief overview of the range of antimicrobial use sites, as identified by EPA
and adopted by the AEATF II, and of the application methods, segmented into separate
1 The general terms "antimicrobials and "biocides" are used interchangeably in this
document.
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tasks to the extent possible, identified by the AEATF II with the concurrence of EPA,
PMRA and CDPR.
EPA ANTIMICROBIAL USE SITE GROUPS
During preliminary discussions on the conduct of antimicrobial exposure assessment
studies with EPA, a range of application methods were identified as appropriate for
covering the 12 broad antimicrobial Use Site Groups that have been used traditionally by
EPA's Office of Pesticide Programs (OPP) in regulating antimicrobials. The EPA Use
Site Groups are set forth in Table 1.
EPA relies on these groupings to determine data requirements for various antimicrobials
based on use. To this end, EPA further subdivides the groupings into food and non-food
categories and indoor and outdoor categories in order to determine mammalian toxicity
and environmental and ecological toxicity data required to support various uses. The
Use Site Groups are a helpful way to identify the range of uses for which antimicrobials
are employed and, in fact, have been used by North American regulators and the Task
Force to define the scope of the Task Force's work. There are multiple sites within each
grouping. Attachment B to this Governing Document is the 1997 listing of individual use
sites in each EPA Use Site Group. This is the most recent list of use sites that has been
made available by EPA.
APPLICATION METHODS FOR STUDIES
The application methods selected for the studies are the most common methods and
include the following: pump liquid, pour liquid; pour solid; place solid (collectively
referred to as mixer/loader activities by EPA); mop, wipe, aerosol spray, spray,
soak/immerse, fog, brush and roll, airless spray, and pressure treat. These application
methods are described in detail in Attachment 2, Glossary.
Table 1 includes a listing of the Use Site Groups and the application methods typically
associated with each.
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Tablel.
USE SITE GROUPS
APPLICATION METHODS
Agricultural Premises and Equipment
pump, pour liquid, aerosol spray,
spray, mop, wipe, fog, soak/immerse
Food Handling/Storage Establishments
spray,
Premises and Equipment
pump, pour liquid, aerosol spray,
mop, wipe, fog, soak/immerse
Commercial, Institutional & Industrial
spray, Premises and Equipment
pump, pour liquid, aerosol spray,
soak/immerse, mop, wipe, fog,
Residential and Public Access Premises
pump, pour liquid, aerosol spray,
spray, mop, wipe, fog, soak/immerse
Medical Premises and Equipment
aerosol spray, spray, mop, wipe, fog,
soak/immerse
Human Drinking Water Systems
pump
Industrial Process Water Systems
pump, pour liquid
Material Preservatives
pump, pour liquid, pour solid, place
solid, spray, soak/immersion, airless
spray, brush/roll
Antifoulant Coatings
airless spray, brush/roll
Wood Preservatives
pressure treatment, soak/immersion,
brush/roll, spray
Swimming Pools
pump, pour liquid, pour solid, place
solid
Aquatic Areas
pump, pour liquid, pour solid, place
solid
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TWO MAJOR GROUPINGS FOR AEATF II STUDIES
The studies planned by the Task Force fall into two general categories: (1) simulated
studies based on discrete or segmented tasks (mixing, loading and application methods)
that can used to estimate exposures occurring in a variety of use scenarios; (2) in situ
(e.g., on-site, observational) studies for complex and/or multi-task scenarios.
Studies Based on Segmented Tasks/Application Methods
AEATF II believes that by reasonably segmenting tasks involved in the application of
antimicrobials, it will be possible to combine separate tasks as appropriate for various
determining exposures in a variety of use scenarios. These studies will involve indoor,
scripted scenarios. This approach will make the generic unit exposure data collected by
the Task Force useful over the range of antimicrobial use sites and more flexible in utility
to potentially changing use patterns. To this end, users of the AEATF II study results
can use information from published and proprietary sources to establish values for other
exposure factors or variables (e.g., the amount of time spent in a particular task in
various occupational settings and residences, the average amount (or range) of a given
product applied) in conjunction with the monitoring data to estimate typical exposures.
Then the segmented exposure value associated with one discrete task can be combined
with the values for other tasks that occur in a particular scenario to further estimate the
exposure that could occur during a typical work day.
In Situ (Observational) Studies for Complex or Multi-Task Scenarios
Four of the AEATF II studies are being proposed for conduct in situ, as observational
studies, given the complex combination of tasks, functions, etc. The unit exposure data
collected from these studies are not intended to be combined, but instead will be
representative of similar use scenarios.
List of AEATF II Planned Studies
Table 2 includes a list of the studies that the AEATF II plans to conduct, in the order of
priority currently anticipated. Many of these studies will be conducted with simulated
exposures. Those that are expected to be conducted as observational studies are so
noted in the following table.
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Table 2.
Page 83 of 194
AEATF II PROPOSED LIST OF STUDIES IN ORDER OF PRIORITY
A.	APPLICATOR/BYSTANDER EXPOSURE RESEARCH
Mop Study
Wipe Study
Wood Pressure Treatment Study (observational)
Aerosol Spray Study
Pour Liquid Study
Metal Working Fluid Study (observational)
Pour Solid Study
Brush/Roller Study (observational)
Airless Spray Study (observational)
High Pressure to Low Pressure Spray Studies
Immersion/Dip/Soak Study
Pump Liquid Study
Place Solid Study
Fogging Study
B.	POST-APPLICATION EXPOSURE RESEARCH (approach to be determined)
Hard Surface
Soft Surface
STUDY DESCRIPTIONS
The following studies are discussed in the order of priority, as currently determined by
AEATF II in conjunction with US EPA, PMRA and CDPR.
Mop
Mopping involves the application of a diluted or ready-to-use antimicrobial solution to a
floor for disinfection or sanitization.2 Mopping occurs in the five EPA Use Site Groups
that involve application of disinfectants and sanitizers to inanimate surfaces: agricultural
premises and equipment, food handling/storage establishment premises and equipment,
commercial/institutional/industrial premises and equipment, residential/public access
premises, medical premises and equipment. The mopping data represent a single or
discrete task that can be combined with other segments or tasks to estimate exposures
from combinations of activities that represent typical work days in a variety of occupation
settings or typical residential use events. The Task Force will simulate mopping
2 The terms "disinfect" and "sanitize" and variations of these terms are used as used by EPA in
regulating antimicrobial pesticides. Each implies a specific level of antimicrobial efficacy, depending on
the type of application method, and disinfect typically indicates a higher level of antimicrobial efficacy
than sanitize. These terms do not have the same meanings in other regulatory or non-regulatory contexts.
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activities, as it will be necessary to establish mopping times sufficient to obtain data,
while limiting activity to the single task of mopping. This would be impossible in the vast
majority of real-life occupational settings. Moreover, many of the facilities where
extensive mopping might occur have legal and ethical considerations that would limit
availability to the facility to researchers and associated monitors (e.g., food processing
facilities and hospitals).
There are numerous types of mopping equipment, including for example, string mops
used in conjunction with various types of wringer equipment, sponge mops, ready-to-use
systems with disposable, impregnated mop cloths, etc. AEATF II, based on an
evaluation of equipment, has concluded that string mops represent a reasonable worst
case and will use this equipment along with buckets with hand-activated mechanical
wringers.
There are data available estimating the amount of time spent mopping in various
occupational settings (e.g., hospitals, hotels, homes), as well as the amount of time
spent wiping, spraying, etc. These data can be used to aggregate exposures from
various functions involving the application of antimicrobials in different occupational and
residential settings to determine estimated total exposures covering a typical work day or
residential usage event.
Wipe
Wiping involves the application of diluted antimicrobial products to surfaces other than
floors in the five EPA Use Site Groups involving use of sanitizers and disinfectants on
inanimate surfaces: agricultural premises and equipment, food handling/storage
establishment premises and equipment, commercial/institutional/industrial premises and
equipment, residential/public access premises, medical premises and equipment. The
primary contact during use of wipes is dermally to the hand. Wping can occur after
trigger-spray application, wipe after dipping a wipe, sponge or other material in a
container, or ready-to-use wipes impregnated with antimicrobial. AEATF II currently is
planning to conduct two sets of MEs in simulated environments, one covering the use of
pre-impregnated wipes and another involving use of a trigger spray followed by wiping
with a dry cotton cloth. Use of wipes in conjunction with full-hand immersion will not be
employed in this study, because full-hand immersion will be monitored in the
dip/immersion study.
As previously noted, the AEATF II will use data from published and proprietary sources
to establish the amount of time spent in wiping activities in various occupational settings
and residences in conjunction with the monitoring data to estimate typical exposures.
The segmented exposure associated with wiping activity can be combined with others to
further estimate the exposure that could occur during a typical work day in a variety of
occupational settings.
Aerosol Spray
Aerosol spray is another application method employed in the five Use Site Groupings
where there is application of sanitizers and disinfectants to inanimate surfaces:
agricultural premises and equipment, food handling/storage establishment premises and
equipment, commercial/institutional/industrial premises and equipment, residential/public
access premises, medical premises and equipment. This study under simulated
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conditions will monitor exposures resulting from spraying from aerosol cans onto
surfaces, but will not include any wiping activities. To the extent that wiping can occur in
conjunction with an aerosol product, the AEATF II believes that it will have sufficient data
from the wipe study to combine with the aerosol study data to estimate exposures from
such combined activities. These data can be used along with data on work day
segments to estimate total exposures for various occupational settings and residential
use scenarios, as needed.
Whether the aerosol generator is prepackaged in a pressurized can or a refillable can
with a separate pressurized air supply makes no difference for purposes of monitoring
exposure, because both systems are producing aerosols using the same principle of
physics. Only the amount of chemical handled varies by packaging. Thus, refillable
containers with separate pressurized air supply, which are the higher volume use
method of application, should be employed for an exposure monitoring study. The
distance that aerosol generation occurs from the body and the aerosol particle size are
probably more important determinants of exposure than whether the aerosol is
dispensed from a can or remotely. Key parameters that are likely to affect exposure
(e.g., amount of product sprayed, air exchange rate) will be carefully recorded so that
there is a basis for extrapolating from one use method to another.
Pressure Treatment of Wood
This study is not based on an application method, but rather is one type of treatment
cover by the EPA Use Site Group "Wood Preservation." In contrast to the majority of
studies to be conducted by the AEATF II, the data derived from the study of pressure
treatment of wood cannot be used in conjunction with data from any other Task Force
study in order to estimate exposure. The data derived from this study will be stand-
alone data applicable only to wood pressure treatment use scenarios. This study is
being proposed for conduct as an observational exposure monitoring study. Wood
treatment immersion will not be studied by the AEATF II because the only exposure
expected would be industrial bystander exposure. Industrial bystander exposure will be
addressed or characterized in the wood pressure treatment and metalworking fluid
preservation studies.
There are at least four GLP-compliant, EPA-accepted studies on pressure treatment of
wood with the three "heavy duty wood treatment compounds" (chromated copper
arsenate or CCA, creosote and pentachlorophenol). EPA's continuing interest in
exposures resulting from this scenario probably is best explained by the estimate that 40
percent or more of the annual US volume of pesticide production is consumed in the
pressure treatment of wood. EPA, therefore, has again requested that industry provide
these data.
The AEATF II will rely on the North American regulators to identify tasks of special
interest for study. Most of the tasks to be monitored are not directly involved in the
application of the pesticide compounds, but instead involve secondary exposures
associated with the treatment activities. Active ingredients have not yet been finally
selected, but likely will reflect the new generation of wood treatment compounds that
combine organic and metal-based components.
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Pour Liquid
Pour liquid data to cover the pouring of registered pesticide products could be used in
conjunction with the data from a number of other application studies, including: mop,
wipe, spray, immerse/dip, pump and fog. There are two general types of containers now
used for pesticides: "glug" and "no-glug". There are data that suggest "no-glug"
containers (those with an air bypass that prevents "glugging" and concomitant
backsplash) produce significantly less exposure to the pourer than do containers without
this feature, which led EPA to issue its recent regulation requiring certain pesticides to
be sold in no-glug containers. The AEATF II study intends to generate data comparing
no-glug containers as a supplement to the existing studies on open pour exposures in
the PHED database. Moreover, the AEATF II data will cover smaller sized containers
that are frequently used for antimicrobials, but are not well represented in the PHED
data.
Metalworkinq Fluid Preservative
EPA has singled out this material preservative use for study because of the Agency's
contention that exposures to the preservatives used in MWFs are among the highest of
all occupational exposures to biocides. A great deal of information exists in the public
literature with regard to ambient levels of MWFs, but not to the preservatives in the fluid.
There also are limited data on dermal exposures. Occupational exposures also are
regulated by the Occupational Safety and Health Administration (OSHA) and have been
well studied by numerous government and private organizations. However, there are no
EPA guideline-responsive, GLP data on this particular use. Dermal and inhalation
exposures will be monitored in the new study for machine operators using the preserved
fluids, and may also be monitored for others present in the facility (i.e., bystanders).
This study, therefore, may be used to provide surrogate data to cover a range of
industrial bystander exposure scenarios, e.g., pulp and paper mills, drift from cooling
water installations, etc. Size of the aerosol and distance from the source probably could
determine exposure to persons in the vicinity, and these data will be recorded. It is
AEATF ll's belief that many of the secondary applicator exposure scenarios will be
addressed with data generated from the primary applicator exposure studies. Uses such
as paint, adhesives, caulking, etc. produce exposure to dilute concentrations of
antimicrobial, and with judgment one can compare the unit exposure from the
appropriate primary applicator scenario to many of these secondary applicator
scenarios, i.e., exposure measured where the product makes a pesticidal claim can be
applied to products that do not.
Pour Solid
PHED data clearly show that exposure (both dermal and inhalation) is inversely
proportional to the particle size (and resulting surface area) of the solid being handled.
PHED lists results for wettable powders (also applicable to dusts), dry flowables, and
granulars that are all different solid formulations with increasing particle size and
decreasing unit exposure in the order listed. The AEATF II expects to conduct a study
using a dust or wettable powder and a granular formulation to bracket the range of
particle sizes and resulting exposures currently in PHED.
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Further, consideration may be given to observations of Heitbrink et al., (1992) regarding
generation of aerosols during pouring of powders. Pour solid data could be combined
with data from other application methods, as appropriate to estimate exposures in
various occupational settings.
Brush and Roller
One of the most common applications for industrial biocides is for preservation of paints,
coatings, caulks, adhesives and similar materials. EPA has historically used exposure to
paints as the reasonable worst case for exposures to these and similar items. The vast
majority of these paints and other materials are not themselves pesticides, that is, they
do make any pesticidal claims. However, some paints and coatings are registered
pesticides in that they claim to protect the substrates to which they are applied from
microbial deterioration, e.g., antifoulant coatings and wood stains.
The Task Force plans to monitor the application of preserved paint where interior spaces
are being painted. Rollers cover more surface area in a given time period than brushes
and regulatory agencies assume exposure per unit applied is the same as brushes.
Published data are currently inadequate to characterize exposure potential from roller
application, but suggest exposure may be lower than brush application. A combination
observational study (including both brush and roller methods) is therefore being
proposed, because typically both methods are used during a typical or normal day of
paint product use.
Airless Spray
Airless spray is used in the application of antifoulant paints, wood preservatives, and
preserved paints. In fact, the use of airless spray equipment (e.g., Wagner) is growing
rapidly in the application of paints in many interior commercial and even residential
settings. The Task Force is proposing to conduct an observational study to monitor
interior painting events using airless spray equipment. It is important to note that this
study may differ significantly than others planned by the Task Force because it likely will
involve the use of both respiratory and dermal personal protective equipment, as
specified by either or both the spray equipment manufacturer and paint manufacturer (of
a non-pesticidal paint).
High Pressure to Low Pressure Spray
Although distinctions are sometimes made between high and low pressure spraying, two
variables affect spray particle size: pressure and orifice size. Small particle sizes (<30
microns mass median diameter) tend to produce higher exposure than larger particles
because they stay suspended longer in the air and can be produced even with low
pressure. A nomogram describing the pressure/orifice relationship to particle size would
be useful and may be prepared during this work. A good deal of the equipment used for
spray application is hand-held. Thus, another critical determinant of exposure is whether
the spray emits above or below the shoulder.
Higher-pressure spray is used with material preservative, wood preservative and
antifoulant coating uses. Lower pressure spray also may be indicated for these uses, is
one of the most widely used application methods for sanitizers and disinfectants, and
includes applications as diverse as trigger sprays and foam generators. However, there
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are no commonly accepted parameters for what constitutes high or low-pressure sprays.
Therefore, a large indoor, scripted-activity study (minimum 60 MEs) will be designed to
account for the range of equipment types typically used in various applications and use
sites and the range of typical particle sizes that might be generated. The distance from
the generation source is likely also to be a critical determinant of exposure.
Data from this work will be used for estimating non-aerosol spray exposures to sanitizers
and disinfectants in agricultural premises and equipment, food handling/storage
establishment premises and equipment, commercial/institutional/industrial premises and
equipment, residential/public access premises, and medical premises and equipment.
Exposure from non-aerosol spray activity may be combined with exposure from other
scripted tasks, as appropriate, to estimate total occupational or non-occupational
exposure for a particular use scenario. The data also will be used for preserved paint,
antifoulant coatings and wood preservative applications for spray uses that do not
employ airless spray equipment. Such exposures will not be combined with other
exposures from other tasks, but instead will be used to estimate typical occupational or
non-occupational use scenarios.
Soak and Immerse
The terms soak and immerse can be used in a variety of contexts for antimicrobial
application. There are industrial uses involving soaking or immersion (various types of
wood and anti-sapstain treatment) that are mechanized and may use large volumes of
antimicrobial but present only a potential for exposure to subjects as bystanders. On the
other hand, low volume uses, such as dish sanitizers in restaurants and bars,
commercial or institutional laundry sanitizers, disinfectants for halters and other stable or
livestock equipment, etc. that are non-mechanized and involve repeated hand
immersion, may offer more potential for exposure. The latter types of exposure will be
monitored in a scripted study. The unit exposure data derived from this study may be
combined with data from other discrete tasks to estimate total workday exposures for the
agricultural premises and equipment, food handling/storage establishment premises and
equipment, commercial/institutional/industrial premises and equipment, residential/public
access premises, and medical premises and equipment Use Site Groups. Use in the
wood treatment industry that involves primarily bystander exposure could be addressed
by either the metal working fluid study or some subset of the monitoring units (or
monitoring events) from the wood pressure treatment study.
Pump Liquid
Some of the largest volume uses of antimicrobials involve use of pump systems, e.g.,
application in oilfield and municipal water treatment facilities. However, these systems
are closed metering systems using dry lock connections, with virtually no opportunity for
worker exposure. Other examples of closed pump systems include tank truck unloading,
automatic dispensing systems, metering pump systems for totes and drums, and tubeset
pumps. Data on these various systems have been shared with EPA, to support the
AEATF II position that additional data should not be required by EPA for pump liquid
applications. In any case, there are probably sufficient data in the PHED database to
cover all antimicrobial use patterns and all product types where closed or similar
systems are not in place to eliminate or mitigate exposure. An analysis will be
performed by the AEATF II to further assess the adequacy of the available data. In
addition, a final decision in part depends on the EPA and the other North American
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regulators' final position on whether occupational risk assessments will be required for
subjects that use closed pump systems. Pump liquid data, if required, could be
combined with data from other application methods, as appropriate to estimate
exposures in various occupational settings.
Place Solid
Registrants have developed various "place solid" products to reduce the potential for
exposure to dry flowable products. The most common "solid" delivery systems are
powders/granulars in sealed, water-soluble bags and "tablets." EPA is requesting data
because it has only one data record in the PHED database. However, the AEATF II
believes that it is unnecessary to require a study with this application method. One of
the most common antimicrobial pesticide uses employing tablets is application of
sanitizers or algaecides to swimming pools. To the extent that a home owner might
apply a single tablet on a weekly or semi-weekly basis, EPA has conceded that
exposure is likely to be non-detectable. When a professional pool treater or other
occupational applicator uses tablets, multiple tables may be applied over the course of
the day. The AEATF II believes in such cases it is appropriate to require occupational
users to wear chemical-resistant gloves, which again would reduce exposures to non-
detect levels. There should be no need for these data and no need to do an
occupational risk assessment if the requirement for gloves for occupational users
appears on product labels. Place solid data, if required, could be combined with data
from other application methods, as appropriate to estimate occupational exposure.
Fog
Fogging is used to treat large or irregularly shaped areas. Most fogging is done using
remote operation, where applicator exposure is negligible. However, there are
backpacks sold for occupational, indoor antimicrobial fogging applications, and EPA has
requested data for fogging data using antimicrobials. However, the AEATF II believes
that to the extent fogging is done using handheld equipment, respiratory and dermal
PPE should be a standard requirement. Therefore, in either the case of remotely
controlled foggers or hand-held fogging with PPE requirements, the potential for
occupational exposure would be negligible. Further, there are no registered residential
uses for antimicrobial foggers. As a result, the AEATF II believes that the requirement
for fogging data for antimicrobials should be eliminated. Fogging data, if required, could
be used for the following EPA Use Site Groups: agricultural premises and equipment,
food handling/storage establishment premises and equipment,
commercial/institutional/industrial premises and equipment, residential/public access
premises, and medical premises and equipment.
POST-APPLICATION EXPOSURE STUDIES
Currently EPA uses the Residential Exposure Assessment Standard Operating
Procedures (SOPs) as codified in SOP 12 (Smegal et al., 2001) and incorporated into
software tools such as (REx - available at www.infoscientific.com and PI RAT - available
from http://epa.gov/opptintr/exposure/pubs/piratdl.htm) to estimate potential reentry
exposures. Dependent on the toxicity of the antimicrobial, use of default exposure
estimates for post application exposure may be adequate.
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The typical primary route of post-application exposure is dermal. It is possible to
generate generic post-application dermal exposure data that would be generally
applicable to a range of possible exposure scenarios (e.g., dermal contact with sanitized
floor surfaces; incidental dermal contact with disinfected work surfaces; dermal contact
with treated articles). Other task forces have developed data to evaluate post-
application exposure (also known as reentry exposure) for environmental surfaces such
as turf (Outdoor Residential Exposure Task Force; ORETF), and plant foliage surfaces
(Agricultural Reentry Task Force; ARTF). Post-application exposure monitoring studies
typically involve concurrent measurement of residues transferred from a treated surface
as a function of time using a non-human transfer medium (discussed in the following
paragraph) and the quantity of chemical transferred to full body dosimetry garments
worn by individuals contacting a treated surface with a known intensity, for specific time
duration. The dermal exposure rate (e.g., mg/hr) measured using dosimetry garments is
divided by the concurrently measured surface transferable residues (e.g., mg/cm2) to
achieve a generic transfer coefficient (TC). This coefficient, which is also referred to as
a "contact rate," is typically expressed in units of cm2/hr.
In conjunction with measuring human dermal exposure following contact with a treated
surface, a post-application exposure study also determines temporal transferable
residue (measurements taken across time) from the treated surface using a generic
method (a roller was used by ORETF and leaf washes were used by the ARTF). The
AEATF II will need to develop or adapt an existing method for measuring transferable
residues. Transferable residues are chemical-specific (due to different adsorption and
dissipation characteristics that are unique to each chemical used on a matrix).
Therefore, chemical-specific transferable residues must be generated by the individual
registrant. These studies cost approximately 5 to 10% of what a human exposure
monitoring study costs.
The AEATF II initially proposed to develop TCs by conducting one study with hard
surfaces (e.g., floor or countertop) and one with soft surfaces (e.g., textile such as carpet
or upholstery). EPA has requested that the Task Force defer any further work on post-
application exposures until it has conferred with other North American regulators to more
clearly determine how it will assess post-application exposures in the future.
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REFERENCES
AEATF II (2004a). American Chemistry Council Antimicrobial Exposure Assessment
Task Force II. Glossary of Terms: Application Methods and Use Patterns.
AEATF II (2004b). American Chemistry Council Antimicrobial Exposure Assessment
Task Force II. Justification for Changes to EPA's Initial List of Application Methods.
AEATF II (2004c). American Chemistry Council Antimicrobial Exposure Assessment
Task Force II. Mixer/Loader (Preparation Worker) and Applicator Exposure Monitoring
Study Design Parameters.
AEATF II (2004d). American Chemistry Council Antimicrobial Exposure Assessment
Task Force II. Post Application Exposure Estimates: AEATF II Data Development
Needs.
Heitbrink WA, Baron PA, Willeke K (1992). An investigation of dust generation by free
falling powders. Am. Indust. Hygiene Assoc. J 53: 617-624.
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Appendix B. Antimicrobial Product Use Sites and
Categories
I.
Agricultural premises and equipment
II.
Food handling/storage establishment premises and equipment
III.
Commercial, institutional and industrial premises and equipment
IV.
Residential and public access premises
V.
Medical premises and equipment
VI.
Human drinking water systems
VII.
Materials preservatives
VIII.
Industrial processes and water systems
IX.
Antifouling coatings
X.
Wood preservatives
XI.
Swimming Pools
XII.
Aquatic areas
I. Agricultural premises and equipment
a. Food area premises and equipment - indirect food contact
AGRICULTURAL/FARM PREMISES
AGRICULTURAL/FARM
STRUCTURES/BUILDINGS AND EQUIPMENT
barnsIarnyards/auction^^
BEEF/RANGE/FEEDER CATTLE (MEAT)
BEEHIVES/BEE COLONY (DISEASED/NUISANCE)
BEEHIVES-EMPTY
CALVES (MEAT)
DAIRY CATTLE (LACTATING OR UNSPECIFIED)
DAIRY CATTLE (NON-LACTATING)
DAIRY FARM MILK HANDLING
FACILITIES/EQUIPMENT
DAIRY FARM MILK STORAGE
ROOMS/HOUSES/SHEDS
INDOOR FOOD,
TERRESTRIAL FOOD
INDOOR FOOD,
TERRESTRIAL FOOD
ilNDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
indoorToocT
INDOOR FOOD"
INDOOR FOOD
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DAIRY FARM MILKING EQUIPMENT
DAIRY FARM MILKING STALLS/PARLORS
DAIRY GOATS (LACTATING OR UNSPECIFIED)
'DAIRY GOATS (NON-LACTATING)
EMPTY CONTAINERS TO BE USED FOR RAW
AGRICULTURAL COMMODITIES
FISH, FRESHWATER (MEAT)
FISH, SALTWATER (MEAT)
FISH HATCHERY BUILDINGS/AREAS (NON-
AQUATIC)
FISH ROE (CAVIAR)(MEAT)
GAME ANIMAL (MEAT)
GOATS (MEAT)
hogTpIgTswneImeaTT^
Kl DslMEATj	¦
; LAMET(MEAfy^^
LIVESTOCK
MUSHROOM HOUSES-EMPTY
PREMISES/EQUIPMENT
PREMISES/EQUIPMENT
POULTRY (EGG/MEAT)
POULTRY (MEAT)
INDOOR FOOD
RABBITS (MEAT)
SEED HOUSES/STORES/STORAGE
AREAS/WAREHOUSES
SHEEP (MEAT)
SHELLFISH (MEAT)
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
GREENHOUSE FOOD,
INDOOR NON-FOOD
INDOOR FOOD,
TERRESTRIAL FEED
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
INDOOR FOOD
b. Direct food contact
ANIMAL DRINKING WATER
POULTRY DRINKING WATER
INDOOR FOOD
INDOOR FOOD
93

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c. Nonfood area premises and equipment
AGRICULTURAL/FARM EQUIPMENT/SHOE BATHS
EGG HANDLING EQUIPMENT (HATCHING)
EGG HANDLING ROOMS (HATCHING)
EGG PLANTS/HATCHERIES/BROODER ROOMS/SHOE
BATHS (HATCHING)
EGGWASHIN^^
FUR FARM EQUIPMENT/PREMISES
INDOOR NON-
FOOD
INDOOR
FOOD
INDOOR
FOOD
NON-
NON-
INDOOR
FOOD
INDOOR
FOOD
SlNDOOR
FOOD
* Use of a product on sites in this category will be considered a food use and
registration must be supported by data sufficient to support establishment of a
tolerance or exemption from the requirement of a tolerance under the Federal
Food, Drug and Cosmetic Act. The Agency will consider label modifications
which clarify practices such that use of the product is unlikely to result in
pesticide residues in food. Uses will be considered nonfood if food is covered or
removed during application and the treated surfaces are rinsed with potable
water prior to any contact with food. Registrants are advised to contact the
Agency if they are uncertain as to whether a proposed application is a food use.
II. Food handling/storage establishments premises and equipment
a. Food area premises and equipment - indirect food contact *
AIRTIGHT STORAGE (FLAT)-EMPTY
AIRTIGHT STORAGE (SMALL)-EMPTY
AIRTIGHT STORAGE-EMPTY
COMMERCIAL SHIPPING CONTAINERS-FEED/FOOD-EMPTY
COMMERCIAL TRANSPORTATION FACILITIES-FEED/FOOD-
EMPTY
CONTACT)
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
94

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?DAIRIES/CHEESE PROCESSING PLANT PREMISES (NONFOOD
CONTACT)
EATING ESTABLISHMENTS (FOOD CONTACT)
EATING ESTABLISHMENTS EQUIPMENT/UTENSILS (FOOD
CONTACT)
EATING ESTABLISHMENTS FOOD HANDLING AREAS (FOOD
CONTACT)
EATING ESTABLISHMENTS FOOD SERVING AREAS (FOOD
CONTACT)
EGG HANDLING EQUIPMENT (COMMERCIAL)
EGGhiANDijNG~ROOMS~(COMMERCiALj^^^^^^^^^^^—
EGG PACKING PLANTS (COMMERCIAL)
EMPTY CONTAINERS TO BE USED FOR PROCESSED
FEED/FOOD
FEED MILLS/FEED PROCESSING PLANTS
FEED/FOOD STORAGE AREAS-EMPTY
FISH/SEAFOOD PROCESSING PLANT EQUIPMENT (FOOD
CONTACT)
FISH/SEAFOOD PROCESSING PLANT PREMISES (NONFOOD
CONTACT)
FOOD CATERING FACILITIES PREMISES
food!5ispensTng1equip^^
FOODlviARKETING/SfORAGE/DlsfRI^^
UTENSILS (FOOD CONTACT)
FOOD PROCESSING PLANT EQUIPMENT (FOOD CONTACT)
FOOD PROCESSING PLANT NON-FOOD HANDLING AREAS
INDOOR
FOOD
INDOOR
FOOD
ilNDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR^
FOOD
ilNDOOR
FOOD
ilNDOOR
FOOD
INDOOR
FOOD
ilNDOOR
FOOD
indoor"
FOOD
INDOOR
FOOD
IlNDOOR
FOOD
ilNDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
(FOOD
95

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FOOD PROCESSING PLANT PREMISES (NONFOOD CONTACT)
FOODlfroMs/MARKEfs/S^
food/grocery/marketing/storag™
FACILITY
HANDLING EQUIPMENT
GRAIN/CEREAL/FLOUR BINS-EMPTY
GRAIN/CEREAL/FLOUR ELEVATORS-EMPTY
MEAT PROCESSING PLANT EQUIPMENT (FOOD CONTACT)
MEAT PROCESSING PLANT PREMISES (NONFOOD CONTACT)
MEAT/FISH MARKETS PREMISES
POULTRY PROCESSING PLANT EQUIPMENT (FOOD CONTACT)
poultryTrocessing^laWpre^s^
CONTACT)
PROCESSING/HANDLING EQUIPMENT (FOOD CONTACT
SURFACES
b. Direct food contact
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
EGG WASHING TREATMENTS (COMMERCIAL)
FRUIT AND VEGETABLE RINSES
INDOOR FOOD
INDOOR FOOD
c. Areas without potential for food contact
SEATING ESTABLISHMENTS (NONFOOD CONTACT)
EATING ESTABLISHMENTS FOOD HANDLING AREAS
(NONFOOD CONTACT)
INDOOR NON-|
FOOD	I
INDOORNON^I
FOOD
96

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EATING ESTABLISHMENTS FOOD SERVING AREAS
(NONFOOD CONTACT)
EATINGESTABLISHMENTSNON-FOODAREAS(NONFOOD
CONTACT)
.HYDROSTATic~STERinZER~WATERl5YSTEMS^^^^^^—
TOBACCO PROCESSING PLANT PREMISES/EQUIPMENT
PASTEURIZER/WARMER/CANNERY/RETORT WATER
SYSTEMS
PROCESSING/HANDLING EQUIPMENT (NONFOOD
(CONTACT)
INDOOR NON-
FOOD
INDOOR NON-
FOOD
INDOOR NON-
FOOD
ilNDOOR NON-
FOOD
INDOOR NON-j
FOOD	|
INDOORNON-
FOOD
* Use of a product on sites in this category will be considered a food use and
registration must be supported by data sufficient to support establishment of a
tolerance or exemption from the requirement of a tolerance under the Federal
Food, Drug and Cosmetic Act. The Agency will consider label modifications
which clarify practices such that use of the product is unlikely to result in
pesticide residues in food. Uses will be considered nonfood if food is covered or
removed during application and the treated surfaces are rinsed with potable
water prior to any contact with food. Registrants are advised to contact the
Agency if they are uncertain as to whether a proposed application is a food use.
III. Commercial, institutional and industrial premises and equipment
a. Indoor
AIRTIGHT STORAGE (FLAT)-EMPTY
AIRTIGHT STORAGE (SMALL)-EMPTY
AIRTIGHT STORAGE-EMPTY
CARPETS (COMMERCIAL SANITIZER)
COMMERCIAL/INSTITUTIONAL/INDUSTRIAL FLOORS
COMMERCIALTINSTmJf^
PREMISES/EQUIPMENT (INDOOR)
COMMERCIAL STORAGE/WAREHOUSES PREMISES
(INDOOR)
COMMERCIAL TRANSPORTATION FACILITIES-
INDOOR
NON-FOOD
INDOOR
NON-FOOD
INDOOR
NON-FOOD
INDOOR
iNON-FOOD
INDOOR
NON-FOOD
INDOOR^
NON-FOOD
INDOOR
INON-FOOD
INDOOR
97

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NONFEED/NONFOOD
DIAPERS (COMMERCIAL LAUNDRY)
DUST MOPS/CLOTHS/TOOL COVERS/DUSTERS
(LAUNDRY/DRYCLEAN)
LAUNDRY (COMMERCIAL)
LAUNDRY (DRYCLEANING)
LAUNDRY EQUIPMENT
MACHINERY (NON-FOOD)
NONFEED/NONFOOD COMMODITIES (TEMPORARY
STORAGE)
NONFEED/NONFOOD CONTAINERS-EMPTY/FULL
NONFEED/NONFOOD STORAGE AREAS-EMPTY/FULL
STORAGE/PROCESSING/HANDLING EQUIPMENT
iREFUSE/SOUD^Sfil^ANSRORfAfiON^-
FACILITIES/HANDLING EQUIPMENT
NON-FOOD
INDOOR
NON-FOOD
NON-FOOD
INDOOR
NON-FOOD
INDOOR
NON-FOOD
INDOOR
NON-FOOD
INDOOR
NON-FOOD
INDOOR
NON-FOOD
INDOOR
NON-FOOD
INDOOR
NON-FOOD
INDOOR
NON-FOOD
INDOOR
NON-FOOD
b. Outdoor
COMMERCIAL/INSTITUTIONAL/INDUSTRIAL
PREMISES/EQUIPMENT (OUTDOOR)
IV. Residential and public access premises
a. Indirect food contact *
HOUSEHOLD/DOMESTIC DWELLINGS
[TERRESTRIAL
NON-FOOD
INDOOR FOOD, INDOOR
RESIDENTIAL
HOUSEHOLD/DOMESTIC DWELLINGS INDOOR INDOOR FOOD
FOOD HANDLING AREAS	j
b. Nonfood indoor
AMPHIBIANS (PET)
INDOOR
98

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ANIMALS (LABORATORY/RESEARCH)
BIRDS (PET)
iCATS (ADULTS/KITTENS) (PET)
CATS (LABORATORY/RESEARCH)
DOGS (SHOW/MILITARY/SPECIAL)
DOGS/CANINES (ADULTS/PUPPIES) (PET)
donkeW^^^
FERRETS (PET)
FISH (PET)
FOX
GOATS (WOOL/ANGORA ANIMAL)
greenhousbIiv^^
HORSES (SHOW/RACE/SPECIAL/PONIES)
MINK
MONKEYS (PET)
MULES (WORK)
RABBITS (PET)
RESIDENTIAL
INDOOR NON-
FOOD
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR NON-
FOOD
INDOOR NON-
FOOD
INDOOR
RESIDENTIAL
INDOOR NON-
FOOD
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR NON-
FOOD
INDOOR NON-
FOOD
INDOORNON^
FOOD
INDOORNON^
FOOD
INDOOR NON-
FOOD
INDOOR
RESIDENTIAL
INDOOR NON-
FOOD
INDOOR NON-
FOOD
INDOORNON^
FOOD
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
99

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RODENTS (GUINEA
PIGS/HAMSTERS/GERBILS/MICE/RATS) (PET)
SHEEP (WOOL ANIMAL)
SHE~EP7DESERT~BiGHORN^^^^^^^^^^^^^^
AIR TREATMENTS (COMMERCIAL/HOUSEHOLD)
BATHROOM PREMISES/HARD SURFACES
CARPETS (HOUSEHOLD SANITIZER)
. D I
DIAPERS (HOUSEHOLD/COIN-OPERATED LAUNDRY)
DIAPERS (PRESOAK)
DOMESTIC/COMMERCIAL NONPOTABLE WATER
(WATERBED WATER)
FILTERS (AIR/AIR CONDITIONER/FURNACE)
HOUSEHOLD TRASH COMPACTOR/FOOD DISPOSAL
H 0
h o useIholdTdomWstic^dwellTngsT^
NONFOOD HANDLING AREAS
HOUSEHOLD/DOMESTIC DWELLINGS INDOOR
PREMISES
HUMAN BEDDING/MATTRESSES
HUMAN CAMPING EQUIPMENT
h u maFTfacegear^^^^^^-
INDOOR
RESIDENTIAL
INDOOR NON-
FOOD
INDOOR NON-
FOOD
indoorTjon^
FOOD
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR^^
PRESIDENTIAL
INDOOR
RESIDENTIAL
AQUATIC NON-
FOOD
RESIDENTIAL,
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
PRESIDENTIAL
INDOOR
RESIDENTIAL
RESIDENTIAL
100

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HUMAN FOOTWEAR
HUMAN GROOMING INSTRUMENTS
(BRUSHES,COMBS)
HUMAN HEADGEAR
HUMAN WIGS
HUMIDIFIER WATER
LAUNDRY (HOUSEHOLD/COIN-OPERATED)
PORTABLE/CHEMICAL TOILETS/LATRINE BUCKETS
:REFljSE/SOLiD~WASTE~CONTAiNERS~(GARBAGE^—
CANS)
REFUSE/SOLID WASTE SITES (INDOOR)
REFUSE/SOLID WASTE TRANSPORTATION
FACILITIES/HANDLING EQUIPMENT
RESIDENTIAL FLOORS (ANTIMICROBIALS ONLY)
TOILET BOWLS (INTERIOR SURFACES)
TO I i^Ytanks/WATER^^^
URINALS (INTERIOR SURFACES)
VEHICULAR HOLDING TANKS
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
(RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
INDOOR
RESIDENTIAL
c. Nonfood indoor/outdoor
'ANIMAL KENNELS/SLEEPING QUARTERS (INDOOR NON-FOOD,
(COMMERCIAL)
HOUSEHOLD/DOMESTIC DWELLINGS
OUTDOOR PREMISES
PET LIVING/SLEEPING QUARTERS
TERRESTRIAL NON-FOOD
OUTDOOR RESIDENTIAL
INDOOR RESIDENTIAL,
OUTDOOR RESIDENTIAL
101

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
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V. Medical premises and equipment
(AIR TREATMENTS (HOSPITAL)
BARBER/BEAUTY SHOP EQUIPMENT (BARBER
CHAIR/CABINETS)
BARBER/BEAUTY SHOP INSTRUMENTS
(SHAVERS/SCISSORS)
B10 LOGlCAirslPECTMEhJSlo"^^
SAMPLES)
^CARPETSTHOSPiTAirSANrnZERj^^^^^^^^^^^-
CUSPIDORS/SPITTOONS
DIAPERS (HOSPITAL LAUNDRY)
HOSPiTAL^ONDUCTiVEFLOORS^^^^^^^^-
HOSPITAL CRITICAL ITEMS (SURGICAL
INSTRUMENTS/PACEMAKERS)
: H 0
HOSPITAL NONCRITICAL ITEMS (BEDPANS/FURNITURE)
HOSPITAL SEMICRITICAL ITEMS
(CATHETERS/INHALATION EQUIPMENT
hospitalMedicalInst^^
FLOORS
HOSPITALS/MEDICAL INSTITUTIONS CRITICAL PREMISES
(BURN WARDS, OPERATING ROOM AREA
HOSPITALS/INlEDICAri^^
PREMISES
SHOSPITALS/MEDICAL INSTITUTIONS PATIENT PREMISES
HOSPITALS/MEDICAL INSTITUTIONS PREMISES
(HUMAN/VETERINARY)
H 0
PREMISES/CONTENTS/UTENSILS
HUMAN WASTE (TYPHOID STOOLS/FECES/URINE)
IINDOOR
MEDICAL
INDOOR
MEDICAL
INDOOR
MEDICAL
INDOOR
MEDICAL
INDOOR
MEDICAL
INDOOR
MEDICAL
INDOOR
MEDICAL
INDOOR
MEDICAL
INDOOR
MEDICAL
INDOOR
MEDICAL
INDOOR
iMEDICAL
INDOOR
MEDICAL
INDOOR
MEDICAL
INDOOR
iMEDICAL
INDOOR
MEDICAL
INDOOR
MEDICAL
IINDOOR
MEDICAL
INDOOR
MEDICAL
INDOOR
MEDICAL
INDOOR"
103

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LAUNDRY (HOSPITAL)
MOrguesMortuarFeS/aUTOPSy/EMBALMiNG
EQUIPMENT
MORGUES/MORTUARIES/AUTOPSY/EMBALMING
INSTRUMENTS
MORGUES/MORTUARIES/AUTOPSY/EMBALMING ROOM
PREMISES
VOMITUS
MEDICAL
INDOOR
[MEDICAL
'INDOOR^
MEDICAL
INDOOR "
MEDICAL
INDOOR "
MEDICAL
INDOOR
MEDICAL
INDOOR
(MEDICAL,
llNDOOR NON-
FOOD
INDOOR
MEDICAL
VI. Human drinking water systems *
PUBLIC WATER SYSTEMS	INDOOR FOOD
INDIVIDUAL WATER SYSTEMS	(INDOOR FOOD
EMERGENCY WATER SYSTEMS	INDOOR FOOD
WATER PURIFIER UNITS	INDOOR FOOD
* Use of a product on sites in this category will be considered a food use and
registration must be supported by data sufficient to support establishment of a
tolerance or exemption from the requirement of a tolerance under the Federal
Food, Drug and Cosmetic Act. The Agency will consider label modifications
which clarify practices such that use of the product is unlikely to result in
pesticide residues in food. Uses will be considered nonfood if food is covered or
removed during application and the treated surfaces are rinsed with potable
water prior to any contact with food. Registrants are advised to contact the
Agency if they are uncertain as to whether a proposed application is a food use.
VII. Materials preservatives
a. Indoor Food
ADHESIVES, INDUSTRIAL (INDIRECT FOOD CONTACT INDOOR
SURFACES)	FOOD
COATINGS, INDUSTRIAL	INDOOR
104

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FOOD
PAINTS (FINGER)
PAPERMAKING (FOOD CONTACT)
iPLASTIC-MAKING
b. Indoor Nonfood
INDOOR
FOOD
INDOOR
FOOD
INDOOR
FOOD
ADHESIVES, INDUSTRIAL (NONFOOD CONTACT)
CAULKS
DIAPERS, DISPOSABLE
FEATHERS/FELT/FELT PRODUCTS/FURS
FUELS/OIL STORAGE TANK BOTTOM WATER
FUELS/OIL (CRUDE)
HIDES/LEATHER/LEATHER PRODUCTS (SURFACES)
JANITORIAL PRODUCTS (IN-CONTAINER)
: M ETAL WO R RT^		
PAINTS (IN-CAN)
PAPER (STORED)
PAPERMAKING (NONFOOD CONTACT)
PLASTIC/PVC/VINYL PRODUCTS
SIZES(ING)
SLURRIES
SPECIALTY PRODUCTS
TEXTILES/CORDAGE PRODUCTS
TEXTILE-/TEXTILE FIBERS-MAKING
INDOOR
INDOOR
INDOOR
NON-
NON-
NON-
FOOD
FOOD
FOOD
INDOOR
indoor"
INDOOR
INDOOR
INDOOR
INDOOR
NON-
NON-
NON-
NON-
NON-
NON-
FOOD
FOOD
FOOD
FOOD
FOOD
FOOD
INDOOR NON-FOOD
INDOOR
INDOOR
INDOOR
INDOOR
INDOOR
INDOOR
INDOOR
INDOOR
INDOOR
NON-
NON-
NON-
NON-
NON-
NON-
NON-
NON-
NON-
FOOD
FOOD
FOOD
FOOD
FOOD
FOOD
FOOD
FOOD
FOOD
b. Indoor/Outdoor Nonfood
COATINGS, INDUSTRIAL
AQUATIC NON-
FOOD
INDUSTRIAL,
INDOOR NON-
FOOD, INDOOR
RESIDENTIAL,
(OUTDOOR
RESIDENTIAL,
105

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i	TERRESTRIAL
1	NON-FOOD	I
D|s^ERS|^Ns/^^uLS|^Ns/s^LUT|(:)NS/SUSpENSj0Ns |NDoor NON- I
.FOOD,
(TERRESTRIAL |
NON-FOOD CROP
^	AQUATIC NON- I
|FOOD	|
(RESIDENTIAL,
[indoor non-
food,
(TERRESTRIAL
NON-FOOD CROP
* Use of a product on sites in this category will be considered a food use and
registration must be supported by data sufficient to support establishment of a
tolerance or exemption from the requirement of a tolerance under the Federal
Food, Drug and Cosmetic Act. The Agency will consider label modifications
which clarify practices such that use of the product is unlikely to result in
pesticide residues in food. Uses will be considered nonfood if food is covered or
removed during application and the treated surfaces are rinsed with potable
water prior to any contact with food. Registrants are advised to contact the
Agency if they are uncertain as to whether a proposed application is a food use.
VIII. Industrial processes and water systems
a. Indoor Nonfood
iPASTEURIZER/CAN WARMER/CANNERY/RETORT	INDOOR NON-
WATER SYSTEMS	FOOD
HYDROSTATIC STERILIZER WATER SYSTEMS	INDOOR NON- '
FOOD	j
FOOD	j
INDOOR NON-	1
FOOD	[
INDOORNON-
FOOD	j
INDOORNON-
FOOD	I
REyE^EOSMOS\s\NAJER¥f^fB^^^^~^^^ wdoornon^-I
FOOD	1
LEATHER PROCESSING WATER/LIQUORS
PHOTO PROCESSING WASH WATER
RECIRCULATING ELECTRODEPOSITION SYSTEMS
106

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b. Aquatic/Outdoor exposure
(air^conditioMr/re^
CONDENSATE WATER SYSTEMS
AIR WASHER WATER SYSTEMS
COAL SLURRY SYSTEMS
COMMERCIALTIN^
WATER [RECIRCULATING]
COMMERCIAL/INDUSTRIAL COOLING
WATER [ONCE-THROUGH]
D R
EVAPORATIVE CONDENSER WATER
SYSTEMS
(INFLUENT WATER FILTRATION SYSTEMS
TEXTILE MILL WATER SYSTEMS
INDUSTRIAL SCRUBBING SYSTEM
INDUSTRIAL WASTEWATER TREATMENT
[SYSTEMS
LABORATORY EQUIPMENT WATER BATHS
: P U
gasToiTdriujngI^^
[OFFSHORE]
GAS/OIL DRILLING MUDS/PACKER FLUIDS
[TERRESTRIAL]
GAS/OIL PIPELINES MAINTENANCE
'SEWAGE SYSTEMS
AQUATIC NON-FOOD
INDUSTRIAL
AQUATIC NON-FOOD
INDUSTRIAL
AQUATIC NON-FOOD
INDUSTRIAL
AQUATIC NON-FOOD
INDUSTRIAL, INDOOR NON-
FOOD
AQUATIC NON-FOOD
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
AQUATIC NON-FOOD
'INDUSTRIAL, INDOOR NON-
FOOD
AQUATIC NON-FOOD
INDUSTRIAL
AQUATIC NON-FOOD
INDUSTRIAL
AQUATIC NON-FOOD
INDUSTRIAL, INDOOR NON-
iFOOD
AQUATIC NON-FOOD
INDUSTRIAL
aquaticnonTood^
INDUSTRIAL
AQUAflC^NON^FOOF
INDUSTRIAL
TERRESTmATNONToOD
AQUATIC NON-FOOD
INDUSTRIAL, TERRESTRIAL
NON-FOOD
AQ UATICNON-FOOD
INDUSTRIAL
107

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c. Environmentally contained
GAS/OIL RECOVERY INJECTION WATER SYSTEMS INDOOR NON-FOOD j
GAS/OIL FRACTURING FLUID SYSTEMS	INDOOR NON-FOOD I
IX. Antifoulinq coatings
BOATS/SHIPS HULL/BOTTOM
CRAB/LOBSTER POTS
FRESHWATER STRUCTURES/EQUIPMENT
MARINE STRUCTURES/EQUIPMENT
WOOD PROTECTION TREATMENT TO WOOD
X. Wood preservatives
a. Heavy duty
SEASONED WOOD PRESSURE/THERMAL
TREATMENT
(JOINERY)
s e A§(5jq§]5^555^^
TREATMENT(REMEDIAL)
UNSEASONED FOREST PRODUCTS TREATMENT
(SAPSTAIN)
b. Ready to Use
SEASONED WOOD NONPRESSURE TREATMENT
(READY-TO-USE)
XI.	Swimming Pools
SWIMMING POOL WATER SYSTEMS AQUATIC NON-FOOD RESIDENTIAL
XII.	Aguatic areas
AGRICULTURAL DRAINAGE SYSTEMS
COMMERCIAL FISHERY WATER SYSTEMS
INTERMITTENTLY FLOODED AREAS/WATER
ANTIFOULANT
iANTIFOULANT
ANTIFOULANT
ANTIFOULANT
ANTIFOULANT
WOOD
PRESERVATIVES
WOOD
PRESERVATIVES
WOOD
PRESERVATIVES
WOOD
PRESERVATIVES
WOOD
PRESERVATIVES
AQUATIC FOOD
AQUATIC FOOD	j
NON-FOOD OUTDOOR
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IRRIGATION SYSTEMS
LAKES/PONDS/RESERVOIRS (WITH HUMAN
OR WILDLIFE USE)
ornMentaTponds^
STREAMS/RIVERS/CHANNELED WATER
LAKES/PONDS/RESERVOIRS (WITHOUT
HUMAN OR WILDLIFE USE)
AQUATIC FOOD
aquMcTood
AQUATIC NONFOOD	j
AQUATIC FOOD, AQUATIC '
NON-FOOD OUTDOOR
AQUATIC NON-FOOD j
INDUSTRIAL
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Appendix C. Glossary of Terms
AMERICAN CHEMISTRY COUNCIL
ANTIMICROBIAL EXPOSURE ASSESSMENT TASK FORCE II
GLOSSARY of TERMS
(derived in part from 40CFR Part 158W)
May 2007
PART I.
ANTIMICROBIAL APPLICATION METHODS
PART II.
EPA ANTIMICROBIAL USE SITE GROUPS
PART III.
GENERAL TERMS
I. ANTIMICROBIAL APPLICATION METHODS
AEROSOL SPRAY - A suspension of fine solid or liquid particles in gas that is
dispensed from a pressurized container. The suspension is relatively stable, that is, the
particles will remain suspended for a period of time barring an external influence.
Standard-setting organizations, ISO, ACGIH, and BMRC, have established inspirable
(able to enter the respiratory system) and reparable (able to enter the alveolar area of
the lung) levels for aerosols. Generally, particles under 8 to 10 microns are considered
respirable. One micron particles are considered 95 percent inspirable, 10 micron
particles are 70 percent inspirable, and 100 micron particles are considered to be 20
percent inspirable. For example, disinfectant aerosol sprays contain less than 1%
droplets 10 microns or smaller. Median size typically is 100 microns (mass median
diameter or mmd), normally distributed. However, government risk assessors usually
assume that all measured air levels are not only inspirable but also respirable. Thus, the
only time when it would be critical to distinguish particle size would be if a particular
chemical had an inhalation toxicology study that showed damage to the alveolar region
of the lung.
AIRLESS SPRAY-A spray application that occurs by directly creating pressure to drive
a liquid out of a nozzle for transfer through the air to a final target surface. Typical
pressures for paints/coatings are in the range of 5,000 psi with orifice diameters of
approximately 0.018 inches. Airless spray particles must be large enough to reach the
target surface and small enough to achieve uniform deposition.
BRUSH- Application of a liquid material to a surface area, such as a wall, by repeatedly
inserting a brush (e.g., a paint brush) into a container for loading and then brushing it
back and forth across the surface to be covered or treated.
FOGGING - An application that requires a device that generates very small liquid
particulate for transfer through the air, so it can penetrate into areas difficult to physically
reach. These devices require some type of mechanical pump to generate the needed
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pressure to drive the biocide through the nozzles. A "dry fog" has droplets ranging in
size from 10-15 microns in volume. A "wet fog" or "mist" has droplets ranging in size
from 30-60 microns in volume. A "fine spray" has droplets larger than 60 microns in
volume.
IMMERSION/DIP/ SOAK - Interchangeable terms. Differences in applicator exposure
potential are attributable primarily to scale, but also may be associated with use patterns
employing this application method and common industry practices.
Wood treatment. The American Wood Preservers' Association (AWPA) 2001
Standards define dip as "application of a liquid preservative to a wood by immersing the
wood in the liquid for a short period of time," typically 3 to 20 minutes. Soaking involves
leaving the lumber in the solution for a longer period of time (for example, 12-48 hours)
in an attempt to get the chemical to go below the surface. Typically, these operations
are large scale, highly automated processes where stacks of wood are mechanically
lowered into baths. The stacks are inserted, removed and stacked in an automated
manner with very little human exposure.
Sanitizer/Disinfectant. Items requiring disinfection or sanitization may be
immersed in an antimicrobial solution. Examples include flatware, glassware, barber
and hair salon articles, etc. The length of time immersed has no impact on the amount
of absorption by non-porous articles. For example, a non-porous material soaked in an
antimicrobial chemical does not retain the chemical or have any residual antimicrobial
activity. A good example would be dishes sanitized in sodium hypochlorite by soaking.
The dishes are sanitized but retain no parent chemical or antimicrobial activity once dry.
MOP - Application of a liquid material to a large surface area, such as a floor. This can
be performed by repeatedly inserting an implement made of absorbent material (e.g.,
string mop head) fastened to a handle into a bucket and wiping it back and forth across
the surface to be treated. Alternatively, "ready-to-use" mop technologies can be used,
for example, pre-impregnated absorbent materials attached to a "mop head" with a
handle, or spray delivery systems integrated with the mop head and handle. The ready-
to-use systems do not require dipping into a bucket. All of these mop technologies
transfer the antimicrobial product from the liquid formulation to the surface.
PLACE SOLID - Application of a solid biocide material into a container or final
application that is accomplished in a single action. The form of the solid may be water-
soluble packets, water-permeable containers, tablets, single dose delivery containers, or
other solid permeable or soluble delivery forms. The application occurs in a single step
without a continuous flow from one container to another.
POUR LIQUID - A biocide in a liquid form is poured from a container, either manually or
with some equipment, into another container or mixing apparatus without the use of
devices that create a vacuum or pressure (i.e. pumps) to facilitate or force the transfer of
the liquid.
POUR SOLID - A solid biocide material (flake, pellet, powder, etc.) is transferred in a
continuous flow from one container to another, either manually or with the aid of
equipment.
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PRESSURE TREATMENT - This is a special application method used in wood
preservation using vacuum and/or external pressure to drive a biocide product deep into
a product matrix. . The process involves sealing product within a pressurized container
(retort) for various lengths of time, pulling a vacuum, and then introducing treating
solution that is forced into the wood as air pressure is reintroduced into the retort.
PUMP - Transfer of a liquid antimicrobial from the original container to another by
pumping as part of the transfer for (1) subsequent use to formulate other pesticides or
for industrial use or (2) end use applications, such as recirculating water treatment,
paper mill slimicide application, metalworking fluid preservation, etc. Gravity or hand
pumps and automated metering pumps are typically used. This type of application is
anticipated to use hoses and various connection devices to facilitate the transfer in most
situations.
ROLL - Application of a liquid material to a surface area, such as a wall, by repeatedly
inserting a cylindrical device covered with an absorbent material (e.g., a paint roller) into
a container, and rolling the cylinder back and forth across the surface to be covered or
treated.
SPRAY - A spray application occurs when a liquid is forced through an orifice under
pressure for dispersal to a target object or surface. There is no accepted standard for
biocide applications that distinguishes between high pressure and low pressure sprays.
Pressure and orifice size are the variables that impact particle size, which is important
depending on the specific application. Following are some typical examples of spray
applications.
Industrial Use. High pressure sprays are delivered by electric pumps at
pressures ranging from 500 to 50,000 psi. Droplet size may be less than 10 microns.
Industrial Use. Low pressure sprays used in industrial applications may be either
manual or electric at pressures ranging from 1 to 500 psi. Droplet size is usually above
10 microns.
Wood Preservation. A high pressure spray nozzle delivers a wide range of
particle sizes, depending on liquid pressure and nozzle opening. For example, to
generate a "fog," typical liquid pressures are 500-1500 psi and nozzle orifices are 0.005
inch or smaller. High pressure spray delivers low volume of liquid using a higher
concentration of the chemical. The equipment creates a "fog" or "mist" (low particle size)
that the lumber passes through. Treated lumber is almost dry to the touch immediately
after the spray process; there is no dripping. Generally high-pressure systems have a
vacuum that returns overspray to a holding tank for re-use. This method of application
results in low exposures via inhalation when a vacuum is used and low exposures for
dermal contact because lumber is almost dry to touch with a lower opportunity for
transfer than a wet surface. This method is growing in popularity.
Wood preservation. Low pressure spray delivers higher volumes of liquid and
actually "floods" the surface of the wood with a solution that is lower in concentration of
chemical through larger sized nozzles than a high pressure spray. This results in a
board that drips as though it were dipped in a bulk dip vat.
Sanitizer/Food Processing. Low pressure sprays are commonly used for
sanitizer applications. There are a number of different application devices including: (1)
hand pressurized (garden type) sprayers. (2) trigger spray bottles; (3) low pressure
spray or foam devices (typically connected to the water system in the plant and operate
at 20 -100 psi; antimicrobial is injected into the water stream and sprayed; either hose-
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end devices or dispensed through a centralized system within a facility); (4) "Cleaning in
Place" or CIP (automated cleaning/sanitization procedures conducted in large food
processing establishments; cleaning equipment is actually built in to the food handling
equipment itself; a complete cycle of pre-cleaning, cleaning, rinsing and finally sanitizing
is conducted automatically through all areas of the food processing line; typically, these
operations are completely enclosed; for example, pipes are flushed with the cleaning
solution; tanks are cleaned and sanitized using a dishwasher type spray arm at the top
of the tank which sprays the chemical solution onto the tank walls.)
Textile Treatment. Antimicrobial formulation used in a fabric treatment in which it
is essentially dispensed in a series of small streams at low pressure onto the surface of
the fabric, with the excess running off. Aerosol formation is typically low.
WIPE - Application of a liquid material to a surface area, such as a counter or wall, by
use of a small hand held piece of absorbent material (e.g., a sponge or woven or non-
woven fabric) pre-wetted, sprayed or dipped into a container and wiping it back and forth
across the surface to be treated. Industrial uses of wipes include in-factory kiss rolls,
dry-wipe lines, doctor bars, or consumer-like wipes used by building restoration and
maintenance personnel.
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PART II. ANTIMICROBIAL USE PATTERNS
AGRICULTURAL PREMISES AND EQUIPMENT - Includes only application of
disinfectants, sanitizers, fungicides, etc. to reduce or eliminate infectious or other
undesired microorganisms on inanimate surfaces in farm and livestock premises, (e.g.,
pens, parlors, stalls, barns, etc.), and on equipment, (e.g., forks, shovels, halters,
feeders, troughs, milking equipment, etc.)
ANTIFOULANT COATINGS - Antifoulant paints for underwater structures and
underwater equipment including ship and boat bottoms and hulls, crab and lobster pots,
and structures and equipment used on fish farms.
AQUATIC AREAS - Application of antimicrobials to control slime-forming bacteria, fungi
and algae in lakes, ponds, streams, drainage ditches and other bodies of water.
COMMERCIAL, INSTITUTIONAL AND INDUSTRIAL PREMISES AND EQUIPMENT -
Includes only application of disinfectants, sanitizers, fungicides, etc. to reduce or
eliminate infectious or other undesired microorganisms, on inanimate surfaces, in
commercial (e.g., hotels, motels, theaters, office buildings, airports, etc.), industrial
(factories, mills, plants, etc.), and institutional (schools, camps, public offices, prisons,
etc.) premises. Equipment includes ceilings, doors, doorknobs, fixtures, floors,
woodwork, walls, and windows.
FOOD HANDLING/STORAGE PREMISES AND EQUIPMENT - Includes only
application of disinfectants, sanitizers, fungicides, etc. to reduce or eliminate infectious
or other undesired microorganisms, on inanimate surfaces, as part of good
housekeeping or good manufacturing practice programs, in food/feed processing plants
(e.g., meat, poultry, diary, seafood, beverage, etc.); eating establishments and food
storage and transportation facilities (e.g., stores, markets, vending machines, trucks,
shipping containers, etc.)
HUMAN DRINKING WATER SYSTEMS - Includes application of disinfectants to public
water systems, including water supplies and components (e.g., pipes, casings, reservoir
surfaces, filter sands, etc.); individual water systems (homes, farms, institutions, camps,
industrial facilities, etc.); emergency water systems and water purifier systems (e.g.,
campers, travelers, military, etc.).
INDUSTRIAL WATER SYSTEMS - Application to commercial and industrial systems
(e.g., cooling towers, evaporative condensers, air washers, heat exchangers), pulp and
paper mill systems, gas/oil recovery systems, drainage, wastewater and sewage
systems, and specialized uses (e.g., immersion ultrasonic tank water, laboratory
equipment water baths, photo processing water, electro-deposition systems, etc.)
MATERIAL PRESERVATIVES - Bacteriostats, microbiostats, and fungistats added to
industrial process intermediate materials (e.g., dispersions, slurries, emulsions,
solutions, etc.) and resulting products (e.g., paints, coatings, adhesives, textiles, paper,
etc.) to control growth of slime-forming microorganisms (e.g., papermaking) and prevent
deterioration or spoilage of material during storage and/or in-use life.
EPA makes no distinction for purposes of exposure assessment between preserved
materials (in-can) and exempt treated articles, that is, articles that make a claim of
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protection for the articles themselves. EPA regards all exposures associated with the
application of a pesticide to be applicator exposures. As a result, EPA regards the
application of a preserved material, whether or not it makes a pesticidal claim, as
secondary application for which it requires exposure data. For example, painter studies
are required, but EPA does not care whether the paint used in the study make pesticidal
claims, because it considers use of all paints that contain antimicrobials, even if only for
in-can preservation, to be secondary pesticide application. As a result, all applications of
paints and coatings, other than those specific to antifoulants and wood preservatives,
are included in this category. (However, for purposes of exposure monitoring, there may
be some possibility of combining replicates from these three use patterns.) Similarly,
machine operators in contact with metalworking fluids are considered to be secondary
applicators.
When exposure to the preserved article occurs following application of the pesticide, as
is the case with most preserved articles, EPA may be interested in obtaining post-
application exposure data.
MEDICAL PREMISES AND EQUIPMENT - Includes only application of disinfectants,
sanitizers, fungicides, etc. to reduce or eliminate infectious or other undesired
microorganisms, on inanimate surfaces in medical environments. Premises include
hospitals, clinics, dental and medical offices, veterinaries, nursing homes, "sick rooms,"
etc. Equipment is limited to non-critical care equipment, that is, equipment that does not
contact the patient or contacts the patient's intact skin (e.g., furniture, carts, bedpans,
telephones, etc.) It is not clear from the EPA definition whether residential "sick rooms"
are included within this use pattern or the preceding use pattern.
RECREATIONAL WATER - Antimicrobial treatment of "hydrologically isolated and
contained manmade bodies of water," including swimming pools, Jacuzzis and hot tubs.
Exposure monitoring is limited to the applicator of the antimicrobial to the recreational
water. Exposure of a bather or swimmer to the antimicrobial is considered post-
application exposure and is determined by use of the EPA's "Swim Model."
RESIDENTIAL AND PUBLIC ACCESS PREMISES - Includes only application of
disinfectants, sanitizers, fungicides, etc. to reduce or eliminate infectious or other
undesired microorganisms, on inanimate surfaces in private residences and public
access areas. (There is no clear distinction between EPA's use of the terms institutional
premises and public access premises.)
SWIMMING POOLS — see Recreational Water
WOOD PRESERVATIVES - Preservative treatments for all types of wood, applied by
pressure or vacuum treatment, remedial applications (i.e., application to utility poles,
support timbers, etc. while in-service); non-pressure treatments (e.g., joinery and
millwork), anti-sapstain treatments and ready-to-use coatings.
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PART III. GENERAL TERMS
Adequacy of BHED™ Data - Each handler scenario within BHED™ will contain
sufficient monitoring units (MUs; also referred to as monitoring events, i.e., MEs) to
achieve a pre-determined level of accuracy for statistical descriptors (e.g., mean,
geometric mean, and 95th percentile) of the distribution of exposure. Generally, the data
set will be considered accurate if these measures are within 3-fold of the true value and
the number of MEs collected will be chosen to achieve this level of accuracy.
AEATF II = Agricultural Handlers Exposure Task Force, L.L.C. - A consortium of 43
companies that formed a FIFRA joint data development task force to design and develop
a database of exposure measurements for agricultural subjects during mixing, loading,
and/or application of pesticides. The exposure data will cover important types of
mixing/loading systems, application equipment, and formulations. The results will satisfy
FIFRA data requirements and be used to assess handler, and for some scenarios
bystander, exposure potential and associated risk assessments for antimicrobial
pesticide products marketed by AEATF II members. AEATF II was formed in November,
2004.
Biomonitoring - Measurement of a pesticide or its metabolite(s) in the body of a
pesticide handler and the conversion to an equivalent absorbed dose based on
knowledge of metabolism and pharmacokinetics. This generally includes measurement
of chemical in blood or urine, but does not include measurement of biological effects
such as cholinesterase levels. The result is an estimate of total exposure from the
dermal, inhalation, and oral routes combined.
Cluster - A set of monitoring units or events (MUs or MEs) from the same scenario
considered a higher-level sampling unit for the purpose of statistical design and
analysis. Exposures between MEs from the same cluster (e.g., building location) tend to
be more similar than those between MEs from different clusters.
Distribution of Exposure - A statistical description of the probability that a given
exposure level is attained; derived from a set of monitoring units (or monitoring events)
within a given scenario and generally described by standard measures such as the
arithmetic mean, geometric mean, and percentile values.
Engineering Controls - Equipment or equipment modifications which eliminate or
reduce exposure to a chemical, such as enclosed cabs, ventilation, or closed transfer
systems.
Exposure Monitoring - Using passive dosimetry techniques to measure dermal and
inhalation exposure to professional, occupational pesticide handlers as they perform
their typical activities. Researchers will use a variety of pesticide residue collection
devices (cloth dosimeters, hand washes, face/neck wipes, and sorbent tubes) and
determine the quantity of active ingredient on each device by chemical residue analysis.
GLP (Good Laboratory Practice Standards) - Federal regulations (40 CFR 160) that
prescribe good laboratory practices for conducting studies that support pesticide
registrations. The standards address the scientific integrity of study conduct and data
collection, including specific requirements for study management, equipment calibration,
facilities maintenance, record keeping, reporting, and quality assurance.
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Handling - Generally refers to mixing, loading, transferring, or applying pesticides.
However, handling also includes the following common tasks: handling opened
containers; disposing of pesticides or pesticide containers; and cleaning, adjusting,
handling, or repairing the parts of mixing, loading, or application equipment that may
contain pesticide residues.
IRB (Institutional Review Board) - An independent board that reviews and approves
study proposals and oversees research to ensure the protection of human subjects who
volunteer to participate in those studies. IRB responsibilities and authorities are defined
at 40 CFR Part 26.
Monitoring Program (or Testing Program) - The testing program consists of all the
MUs (or MEs) from the studies that will be conducted by AEATF II to monitor exposure
to antimicrobial pesticide handlers and that will be used to develop a generic database to
support pesticide registrations. The planned testing program will cover pesticide
handling and bystander scenarios.
Monitoring Unit (MU) or Monitoring Event (ME) - All exposure monitoring activities
pertaining to a single worker for a time period that represents a typical workday,
including the exposure measurements for the worker involved. A specified number of
monitoring events (MEs) will be conducted for each scenario to adequately define the
distribution of exposure expected for that scenario. MEs defined in different scenarios
may be collected in a single study.
Passive Dosimetry - Techniques for measuring pesticide exposure to human subjects
which do not involve invasive collection techniques such as collecting urine or blood.
AEATF II studies involve whole-body garments that serve to collect dermal residues,
hand washes to collect hand residues, face/neck wipes to collect residues on the face
and neck areas, and sorbent tubes to collect air in the breathing zone of a worker.
Additional cloth dosimeters may be used to measure exposure to the feet or to the head
area with and without headgear.
PPE (Personal Protective Equipment) - Devices and apparel that are worn to protect
the body from contact with pesticides or pesticide residues, including but not limited to
coveralls, chemical-resistant suits, chemical-resistant gloves, chemical-resistant
footwear, respiratory protection devices, chemical-resistant aprons, chemical-resistant
headgear, and protective eyewear (See 40 CFR 170.240).
Purposive Diversity Sampling - The type of non-random sampling used for each
scenario in the AEATF II monitoring program. Sampling is purposive because certain
important conditions are selectively sampled. Diversity (or heterogeneity) sampling
means that the purposive sampling is targeted to achieve a diversity of major factors that
are likely to influence exposure, including amount of active ingredient handled, subjects,
and location.
Regulatory Agency Advisory Committee (RAAC) - comprised of representatives of
the U.S. EPA, the Canadian Pest Management Regulatory Agency (PMRA), the
California Department of Pesticide Regulation (CDPR), and European regulatory
authorities. This committee meets on an ad hoc basis to review the program progress
and provide technical input to the AEATF II
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Scenario - A specific pesticide handling situation that will be represented by data with
defined common properties; generally a combination of a work task(s), pesticide
formulation, equipment, engineering controls, and work practices. For example, a
scenario of interest is 'mopping indoor surfaces with defined application equipment and
related tasks, e.g., filling a mop bucket with a defined end-use mop solution using an
automated dispensing system and disposing of dirty mop solution'. Tasks that are
common across more than one exposure scenario, e.g., pouring liquids into containers,
may be specifically addressed in a separate study (e.g., mixing/loading or pouring of
liquids, such as filling a mop bucket with end-use liquid solution using an automated
dispensing system, or preparing an end-use mop solution, prior to mopping application).
Scripting, Scripted Study - Scripting is the partial control of the conditions in a
particular study. A scripted study is considered to "involve intentional exposure" within
the meaning of the regulatory definition at 40 CFR 26.1102(i). Subjects are asked to
conduct their work activities under a set of scripted conditions very similar but not
identical to those they experience in their normal work activities. Scripted or semi-
scripted tasks may also refer to repetitive operations performed by workers or
consumers (e.g., wiping countertops) that are not expected to vary significantly from one
person (or location) to another.
Study - A convenient grouping of monitoring units or events (MEs) covered by one
protocol and one final report. Typically a study will address one or more tasks
associated with a specifically defined exposure scenario and will be conducted over a
short period of time (1 to 2 weeks), with one surrogate chemical. Tasks that are
common across more than one exposure scenario, e.g., pouring liquids into containers,
may be specifically addressed in a separate study.
Surrogate Chemical - A pesticide active ingredient which is present in test materials
which are handled during collection of an monitoring unit or event (MU or ME). AEATF II
develops validated analytical methods for each surrogate chemical and each exposure
matrix so residues collected can be determined. AEATF II chooses surrogates which
have low volatility and are commercially available in suitable formulations and
packaging. Since exposure to handlers is a generic function, exposure measurements
from these chemicals are suitable for estimating exposure to other pesticide active
ingredients.
Target Population (or Universe) - Each element of the target population is a potential
task (or set of tasks) performed by a worker under a particular scenario in a day. Each
element is defined by a set of all conditions that might have any impact at all on that
worker's exposure. These conditions include the particular chemical product tested, the
worker, his behavior, and all relevant environmental conditions. Each ME is assumed to
be a realization of an element from the target population.
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Appendix D. AEATF II Acceptance Criteria for Existing
Studies
Data Review and Study Acceptance Criteria
For Inclusion of Existing Antimicrobial Exposure Monitoring Studies In The
Antimicrobial Exposure Assessment Task Force II (AEATF II) Database
November 28, 2006
I. DATA REVIEW PROCESS
All existing antimicrobial exposure monitoring studies, whether offered by
a third party for sale or from the public domain, will undergo a 3-step review
process to determine whether they meet the selection criteria listed in this
document. In addition to the specific review process outlined below, a continued
dialogue will take place with U.S. EPA to discuss each exposure scenario to be
studied and the general study design elements (e.g., worker tasks, equipment,
locations, replicates) proposed by AEATF II. This discussion will serve to inform
the existing study review team as to the minimum study design and data
collection requirements needed for an existing study to be deemed acceptable to
fulfill a given data requirement. The non-acceptance of a given study, via the
AEATF II study review process, does not imply that it is not suitable for use by
any individual member company to fulfill a specific data requirement, only that
the AEATF II has made the determination that the study will not be purchased for
broader use by the AEATF II member companies.
A. Preliminary Review
1.	The preliminary review will be conducted by the study submitter (or a
designated representative) and provided to AEATF II along with a complete copy
of the study report at the time the study is submitted to the Task Force for
consideration.
2.	The AEATF II will consider all studies, including any that are presently in
PHED version 1.1 or version 2. The studies in PHED version 1.1 are all more
than 15 years old and are not subject to data compensation requirements.
However, these data were originally submitted to PHED without attribution to
compound or company ownership. If any of these data fulfill acceptance criteria,
they could potentially provide very beneficial information that would complement
data developed by AEATF II.
3.	Raw data for a study must be made available, if requested.
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4.	A list of potential studies and all preliminary review forms and reports should
be submitted by dates requested by AEATF II.
5.	The purpose of the preliminary review will be to eliminate the submission of
studies that clearly do not meet the selection criteria, and to serve as a check on
the availability and submission of supporting information.
6.	AEATF II will provide an Excel spreadsheet to the submitter for use in
summarizing the study details and data.
7.	AEATF II will provide a confidentiality agreement to the submitter to protect the
proprietary nature of the data and the study.
B. Intermediate Review
1.	The intermediate review will be conducted by a qualified AEATF II contractor,
hired and trained for this purpose.
2.	The purpose of the intermediate review will be to verify the accuracy of the
preliminary review and, where necessary, provide a more detailed discussion
summarizing each specific area of the criteria, including whether each criterion
was met and possible deficiencies in the study data.
3.	The intermediate review will be evaluated and a determination made as to
whether the study or any of the data could be used in the AEATF II database.
Only studies that have met the design considerations will be presented to EPA,
PMRA and CDPR for final review.
C. Final Review
1.	A Committee consisting of representatives from the AEATF II and EPA, PMRA
and CDPR will make the final review and decision on whether a study is
accepted for purchase.
2.	The intermediate review by the contractor of studies will be made available to
the Committee and will serve as the basis for the final review.
3.	Studies or portions of studies selected after final review will then be
considered for purchase by the AEATF II for inclusion in the Task Force
database.
4.	Reports for studies that the Committee deems not acceptable for the AEATF II
database will be returned to the submitter with an explanation as to why the
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study did not meet the selection criteria. Reports of studies that are purchased
by AEATF II will be placed in the AEATF II archives.
D. Appeals Process
Study contributors whose studies are not accepted for possible purchase may
appeal that decision, but should do so within 30 days of such notification.
II.	STUDY ACCEPTANCE CRITERIA: STUDY DESIGN CONSIDERATIONS
1.	All monitored activities and equipment must be described in detail and
representative of typical antimicrobial handling practices.
2.	It should be clear that the individuals monitored 1) either are normally
employed in the mixing/loading and/or application of antimicrobial products or
pesticide products and handled them comparably, or, 2) if consumers (i.e., non-
professionals), are applying antimicrobials products by methods they would use
in the course of their normal activities. .
3.	Appropriate supporting information such as the formulation type, mixing and
application method, application rate, duration of the work cycle, amount of Al
handled/replicate, etc. must be available.
4.	The use of protective equipment (PPE) is acceptable but must be part of
normal work practices.
5.	The study location and environmental/weather conditions during the
monitoring period should be available.
6.	All elements of a given study may not have been conducted under GLP, but
must have critical elements of GLP e.g., protocol, final report, and raw data
available in order to be considered by the AEATF II.
III.	STUDY ACCEPTANCE CRITERIA: EXPOSURE MONITORING
A. Field Aspects
1.	Field recoveries should have been collected on a site-specific basis for time
periods and environmental conditions representative of those during collection of
field activity exposure samples.
2.	Field fortification data should include at least triplicate samples at two rates
and triplicate samples of controls; however, duplicate samples will be considered
with justification.
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3.	Dermal exposure monitoring techniques should be specified and should
include one of the following approaches. Note that glove washes of chemical
resistant gloves are not an allowable method.
a)	whole-body dosimeters inside and/or outside of typical clothing plus hand
(cotton gloves can substitute for hand exposure) and head/face exposure
determinations,
b)	a minimum of 10 patch dosimeters attached inside or outside normal work
clothing to the chest, back, both upper arms, both lower arms, both upper legs,
both lower legs, plus hand (cotton gloves can substitute for hand wash) and
head/face exposure determinations (exceptions for head/face and upper arms
and upper or lower legs and bilateral measurements will be considered on a case
by case basis). Conversion and use criteria have been developed by the NAFTA
harmonization group and should be considered for adaptation of the PHED data.
c)	combination of patches and clothing that are representative of the whole body,
including hand and head/face exposure determinations.
4.	Inhalation exposure - Inhalation data are required if the vapor pressure of the
chemical under study is >10-4 mm Hg or if the chemical is used in an
environment that results in significant volatilization (e.g., around steam pipes or
in metal working fluids), or if the method produces inspirable aerosols. If data
were collected, inhalation exposure should have been measured by sampling the
person's breathing zone.
5.	Exposure monitoring duration - The monitoring period should be at least half
of a normal work period duration or mix/load and/or apply at least half of the daily
amount normally used.
6.	If the exposure monitoring duration does not meet the requirement of item
number 5, then the number of non-detects/less than LOQ values should account
for less than 40% for dermal exposure. This cut-off is specified because the
distribution of exposures can be reasonably extrapolated from a data set with up
to 40% non-detects. Data sets with >50% non-detects produce a degree of
uncertainty deemed unacceptable for a generic database.
If the exposure monitoring duration and number of non-detects/less than LOQ
values do not meet the criteria in items 5 and 6, then the LOQ should be no more
than 20 ng/cm2 for average dermal exposure (across body part areas) and no
more than 500 ppb for hand wash solution. The LOQ cutoffs are conservative in
that if all data were at the LOQ, the resulting calculated exposure (at % LOQ)
would yield an MOE of >100 for a compound with a systemic (absorbed dose)
NOAEL >1 mg/kg.
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B.	Analytical Aspects - QA/QC
1.	Analytical methods should have been validated for each analyte and substrate
by the performing laboratory including establishment of the method's working
concentration range to cover values anticipated in the field studies, determination
of detector response over a reasonable standard concentration range, and
determination of the accuracy and precision of the method within the analytical
environment.
2.	The study should include both field fortification samples and concurrent
laboratory spikes.
3.	The average recoveries of lab spikes should be between 70-120 percent and
the precision value (coefficient of variation; CV) should be less than or equal to
20 percent.
4.	Recovery of field fortification samples should be 50-120% with a C.V. <25%.
5.	Exposure samples should have been analyzed in such a manner that the
stability of each analyte in each substrate was assessed for the entire time period
from collection to analysis.
C.	Biomonitoring
Biological monitoring studies will be accepted for further review if they meet the
selection criteria (excluding passive dosimetry) and there is a primate (human or
monkey) dermal absorption study for the chemical monitored and
pharmacokinetic data identifying the major excretory metabolite or parent
compound.
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Appendix E. Designing Monitoring Events to Predict
Future Exposure under Antimicrobial Handling
Scenarios
Background
Future Exposure and Monitoring Events
An antimicrobial handling scenario is a well-defined worker exposure situation,
usually characterized by specific antimicrobial handling tasks and equipment.
For the purposes of the AEATF II monitoring program, the basic element of a
scenario is considered to be the handler-day (HD). Each handler-day
corresponds to a particular worker and the scenario-related activities that he
performs during a single work day.
Implicitly associated with each HD is a complex set of conditions denoted simply
by C. The practically infinite number of components of C includes, but is not
limited to worker behaviors, active ingredient used, amount of chemical
contacted, surfaces treated, and numerous environmental factors. Some, but
certainly not all, of these conditions can actually be observed and measured.
Each particular set of HD conditions, C, results in a particular worker exposure,
E=E(C). In principle, although always subject to some measurement error,
handler-day exposures (e.g., dermal or inhalation) can be obtained by actual
monitoring.
Regulatory interest for each antimicrobial handling scenario is focused on
predicting occupational exposure under a specific set of generic future handler-
day conditions. In particular, it is desired to characterize exposures resulting
from the future use of an arbitrary (and perhaps currently non-existent)
antimicrobial active ingredient assuming some arbitrary, but quantifiable, amount
of active ingredient contact.
A monitoring event (or ME) is the basic tool used by the AEATF II Monitoring
Program to predict exposures under. An ME is a set of scenario-specific
handler-day conditions that have been experimentally selected (i.e., chosen,
simulated, or constructed) to represent expected future HD conditions. Each ME
is monitored to yield a set of exposure measurements. Therefore each ME
provides a measurement of the actual exposure resulting from the simulated or
selected HD conditions. The ME will also provide a predicted future exposure if
the handling conditions of the ME are similar to future HD conditions.
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The Generic Active Ingredient Principle
The most obvious handler-day condition is the identity of the active ingredient
(ai) to be used in the scenario task(s). Every experimental monitoring event must
use at least one active ingredient. It might seem, therefore, that prediction of
future exposure to a particular ai would require that every ME use that active
ingredient. If this were true, a generic exposure database for arbitrary active
ingredients would not be feasible.
Fortunately, exposure is not always chemical-specific. For compounds with low
volatility (which include all the antimicrobials considered), a generally accepted
generic principle is:
If all other conditions are the same, the magnitude of exposure
does not depend on the particular active ingredient used
More formally, if Ai and A2 are any two active ingredients and if the exposure
resulting from any active ingredient X under conditions C is denoted by E(X, C),
then the generic principle is simply:
(1)	E(A1,C) = E(A2, C) = E(C)
The practical importance of the generic assumption is that it permits an ME
based on one surrogate chemical to be used to predict HD exposure to other
active ingredients under the same set of handling conditions.
Normalized Exposure
For prediction purposes, it is useful to express handler-day exposure relative to
the value of a normalizing factor (NF). If H is the value of the normalizing factor
and C represents all other HD conditions then:
(2)	nE(C) = E(C)/H
is called normalized exposure. The quantity nE is also often referred to as unit
exposure because it is viewed as exposure 'per unit' of the normalizing factor.
In the AEATF II Monitoring Program the normalizing factor is always an
experimentally measurable quantity that is expected to be proportional to the
potential contact the worker has with active ingredient. Potential ai contact (or
PaiC) is defined as the amount of active ingredient that a worker is expected to
come into contact with during a workday. Because it is always expected to be at
least proportional to PaiC, an AEATF II normalizing factor is a relative measure
of active ingredient contact.
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It is generally assumed that under identical conditions exposure is proportional to
potential ai contact. That is, if Pi and P2 are different amounts of PaiC, and C
represents other HD conditions, then the proportionality principle states that:
(3)	E(P2, C)/E(Pi,C) = P2/Pi
Exposure may not be directly to proportional to contact in extreme situations
(e.g., skin saturation). However, such a relationship is expected to hold for the
levels of active ingredient contact that occur in practice. If the normalizing factor
is expected to be proportional to PaiC then the proportionality principle
relationship holds for the NF as well since:
(4)	H2/Hi =(k-P2)/(k-Pi)= P2/Pi
Thus, under the same conditions, C, exposure for any value, H2, of the
normalizing factor can be obtained from an ME based on a different value of NF,
Hi say, since:
(5)	E(H2, C) = (H2/Hi) E(Hi, C) = H2 { E(Hi, C)/Hi } = H2 nE(C)
For most antimicrobial scenarios, a reasonable normalizing factor is the amount
of active ingredient 'handled' (AaiH) by a worker during the workday.
However, for some scenarios (e.g., the pump liquid scenario) a worker might
actually process (i.e., 'handle') a large amount of active ingredient, but may have
the opportunity to contact only a small fraction of this amount. In such cases,
there may be other measures of PaiC that are more appropriate than AaiH.
It is important to note that the term normalized (or unit) exposure is not always
defined as a relative measure of ai contact. A familiar example occurs in studies
of exposure to agricultural reentry workers. Here, exposure, E, is often
normalized by duration of the reentry activities to give exposure per hour worked.
Unless the concentration of active ingredient on treated foliage is always
constant, the normalizing factor 'hours worked' is not expected to be proportional
to contact with ai. However, the quantity:
(6)	D = (hours worked) x (dislodgeable foliar ai residue)
is expected to be proportional to the amount of ai contacted by the reentry
worker. In agricultural reentry studies, the quantity E/D is often called the
transfer coefficient (TC) and corresponds to normalized exposure as defined by
AEATF II.
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Using MEs to Predict Future Exposure
The generic and proportionality principles together imply that, under the same
conditions, the normalized exposure from any ME can be used to obtain a
predicted future HD exposure (pE) for any arbitrary chemical, X, at any
arbitrary level of the normalizing factor, Hx, simply as:
(7)	pE(Hx, C) = Hx nE(C)
Although this relationship permits a single ME to predict exposure for a broader
range of future handler-days, it cannot describe all future exposures. Even when
Hx is specified, the number of possible 'other conditions' (i.e., different Cs), is
extremely large. (Although some of these Cs are more likely than others to occur
in the future HD population.) Because each ME is expensive, it will only be
possible in practice to construct MEs having a limited set of Cs. This set of N
MEs will then be used to obtain a set of N predicted exposures using (7):
pE(Hx,Ci) = HxnE(Ci)
pE(Hx , C2) = Hx nE(C2)
pE(Hx , C3) = Hx nE(C3)
•
pE(Hx , CN) = Hx nE(CN)
Obviously, a set of only N predicted exposures cannot cover every possible
future HD condition. Nor is it reasonable to expect that a small set of N MEs will
provide experimental material to develop statistical models for exposure as a
function of C. In fact, only some, but by no means all, of the components of each
C can be controlled or measured when constructing MEs. The unknown
components might have the biggest impact on exposure.
Nevertheless, this set of pEs will need to be sufficient to allow regulatory issues
to be addressed in a practical manner. If some components of C that can be
controlled are chosen appropriately, then a useful set of MEs can still be
constructed. In this case the resulting set of pEs will be used as a predictor of
future HD exposure in an aggregate sense.
The Future Exposure Distribution
An exposure distribution provides a natural aggregate description of future
handler-day exposures for a scenario. It is the most common way to think about
the set of exposures resulting from all possible future HD conditions. The future
HD distribution (Figure 1) describes the likely exposure that would result if one
were to randomly pick a future HD among those using ai X when the level of the
normalizing factor is Hx.
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Middle Exposure Levels
Exposures
Distribution of Fu
Larger Exposure
Levels
Exposure
Figure 1. The distribution of future handler-day exposures
The complete exposure distribution is rarely considered. Regulatory interest is
most often focused on two general aspects of this distribution:
•	The middle values such as the arithmetic mean or the median. These
exposure values tend to characterize average or 'typical' exposure levels.
•	The larger values of exposure possible, such as the 95th percentile of the
distribution. This aspect better characterizes the extreme, one-time,
worker exposures.
Obviously the exposures can vary proportionally with the value of the normalizing
factor, H. Therefore there are actually a series of predicted exposure
distributions, one for each possible value of HX. Since any predicted exposure
can be computed from the normalized exposure, it is simpler to focus only on the
distribution of normalized exposure.
The Set of MEs as a Pseudo-Random Sample
The set of predicted exposures obtained from the constructed set of MEs should
adequately characterize the middle and larger values of the future HD
distribution. This might appear simple, since it is quite common practice to treat
any set of values as a random sample from a distribution. Thus, one could treat
the set of pEs as a simple random sample from the future exposure distribution.
This cannot be strictly the case since exposure is a function of the HD conditions,
C, and the likelihood of the various C's in a future HD population (for X and Hx)
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are not known in advance. Therefore the C's for the MEs cannot be randomly
chosen with probability proportional to the future population frequencies.
But some random sampling interpretation might still be a convenient and
reasonable model for how the set of predicted exposures from the MEs might
relate to the future exposures for an arbitrary ai and Hx. Confidence in this
approximation is increased by using a nested reference random sampling model
rather than assuming just simple random sampling. In addition, diversity
selection (using both purposive and random components) is used whenever
possible. This increases the likelihood that the range of conditions in the future
HD population expected to impact exposure is reflected in the 'pseudo-sample' of
MEs as well.
Diversity Selection
Diversity selection is an attempt to make the set of MEs (and resulting pEs)
more useful for regulatory purposes when they are treated as random sample.
Often some factors that are likely to influence exposure are known or can at least
be reasonably hypothesized. Diversity selection results from any procedure that
improves the chance that different MEs differ with respect to such factors. It is
an attempt to obtain, as much as is practical for small sample sizes, a diversity of
conditions that are expected to influence exposure, either directly or indirectly.
With a small set of MEs, it is more practical to construct MEs that differ that to
reproduce the (unknown) frequencies of selected future HD conditions.
In the AEATF II Monitoring Program, the term diversity selection is preferred in
lieu of the phrase diversity sampling. This is to emphasize the fact that the
future HD conditions used for MEs are selected from either existing or from
synthesized conditions (or from both). This selection of conditions can employ
both purposive and random elements. When there are multiple diverse
configurations available, random selection from among such configurations can
reduce the likelihood of intentional selection bias. On the other hand, when
some possible ME configurations are more diverse or more cost effective than
others, it might be preferable to select these purposively.
Diversity selection attempts to create a sample that contains as many of the
different conditions as possible that exist in the population. If the diversifying
conditions are associated with exposure, then a diversity sample will tend to be
more variable with respect to exposure than would a same-sized representative
sample. In effect it will be analogous to representative sampling from a
distribution that is more diverse than the actual future one (Figure 2). As a result,
a diversity selection sample should tend to have more extreme exposures (both
higher and lower) and fewer exposures 'in the middle'. Thus, a diversity
selection sample will tend to estimate central tendencies of the exposure
distribution better than it will either upper or lower percentiles. To the extent that
the diversifying conditions are associated with exposure, diversity selection will
tend to under-predict lower percentiles and over-predict upper percentiles. (This
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effect is illustrated by envisioning a normal, or even lognormal, distribution
compared with its most extreme 'diversity selection' counterpart, a uniform
distribution covering a similar range.) For regulatory purposes the important
aspects of the distribution of exposures are the central tendencies and the upper
percentiles. In addition, overestimation of these characteristics is less of a
problem than underestimation.
DiversitySfelection Tends
toRoduce Less'Middle'
True Distribution of
Future Exposures
and More' Bet reme'
Values
Normalized Exposure
Figure 2. Diversity selection tends to make the distribution of future handler-day
exposure appear more diverse than it is.
Design Objectives and Sample Size
The Two-Stage ME Selection Process
Obtaining potential workers and scenario-specific handling-day conditions
needed to create monitoring events is a complicated process. Of necessity, the
specific selection process used will vary from scenario to scenario. This is
especially true for the two major categories of AEATF II studies: simulated-
condition studies and in situ studies. Simulated-condition MEs are created
synthetically whereas in situ MEs must be located from among existing handler-
day conditions in facilities willing to participate.
However, as shown in Table 1, the ME construction process for both types of
studies can be envisioned as occurring in two successive stages of selection.
The first stage consists of selecting or constructing specific locations and
specifying a range of dates for monitoring at each location. Each such local area
and range of potential monitoring dates is termed a monitoring site. For in situ
studies, a site might consist of a particular wood-treating facility during one
particular week. In contrast, a site in a simulated-condition study might be a
week-long period of monitoring activities in a particular leased office building.
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Table 1
The general two-stage structure for selecting MEs in AEATF II studies
First Stage Units
(Monitoring Sites):
Second Stage
Units
(Monitoring
Events):
The second stage consists of selecting one or more subjects and handling
conditions within each site and constructing the MEs. For simulated-condition
studies the MEs are created by assigning appropriate subjects to scenario tasks
under conditions that are expected to exist in the future HD population. For in
situ studies, appropriate handler-days are selected from among existing subjects
and conditions that are also expected to represent future HD conditions.
In general, Nc sites are selected at the first stage and NM monitoring events will
be obtained within each site at the second stage. When NM is greater than one,
the set of MEs at the same site is termed a 'cluster'. In general, MEs in the same
cluster are expected to be more similar than those in different clusters. This
correlation usually means that the smallest total sample sizes (i.e. total number
of MEs) are attainable when there is only a single ME per site. On the other
hand, there are often substantial overhead costs per site that make multi-ME
sites more efficient.
Study Type Used for Scenario:
Simulated-Condition In Situ (Observational)
Synthetic environments
constructed (or vacant
facilities leased)
expressly for the
purpose of the study
Existing facilities where
scenario-related tasks
occur and that agree to
participate in the study
Monitoring events (ME)
constructed at the sites
using subjects selected
from a volunteer pool
Monitoring events (ME)
selected for observation
from among those
occurring at the site
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The Two-Stage Random Sampling Reference Model
In the strictest sense, sample sizes can only be determined using statistical
theory alone when either
1.	There is assumed random, representative sampling from a population and
the goal is to estimate some characteristic of that population; or
2.	There is assumed randomization of experimental units to treatments and
the goal is only to compare or to contrast treatments in some manner.
Only in these two situations will statistical theory predict how increasing sample
size decreases estimation error. In other experimental situations, sample size
must be determined using one of the two 'random' situations above as a
reference model. The random reference model is defined so that it reflects the
actual situation (e.g., a mixture of random and non-random selection) as closely
as is practical. The sample size that is appropriate for the reference model is
then used for the actual study design. In a real sense, then, the reference
random sampling model is used to establish benchmark sample sizes that can
satisfy benchmark objectives. Although rarely stated explicitly, the use of
reference sampling models and benchmark objectives are quite common.
Because all AEATF II scenario studies have a two-stage selection structure, they
all assume the same reference sampling model. For each scenario, two-stage
random nested (or cluster) sampling is the reference model used for the
combination of purposive and random two-stage diversity selection that actually
occurs. This reference model assumes that:
1.	Exposure, normalized by the potential active ingredient contact factor, is
lognormally distributed with geometric standard deviation GSD.
Equivalent^, the logarithm of normalized exposure is normally distributed
with standard deviation Log(GSD).
2.	There are Nc clusters (i.e. sites) and NM MEs per cluster. The total
number of MEs in this scenario is, therefore, N=NCXNM.
3.	The within cluster (i.e., within-site) correlation of log normalized exposure
is equal to ICC.
The reference sampling model incorporates a two-stage selection structure and
the potential for within-cluster correlation, but ignores any effects of diversity
selection. Thus, for determining sample sizes, normalized exposures, nE, are
assumed to follow the nested variance component model
(8)	Log ( Ey / Hy) = Log nEy = Log GMnE + Qi + Wy
where
Ey = the exposure obtained for ME j in cluster i
Hjj = the value of the normalizing factor for worker for ME j in cluster i
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nEy = the exposure for ME j in cluster i normalized by NF
GMnE = the population geometric mean for normalized exposure
Qi = a random effect of cluster i
Wy = a random effect of ME j within cluster i
The random effects Qi and Wy are normally distributed with means 0 and
variances VQ and Vw, respectively.
The population variance of log nE is then equal to V = VQ + Vw and the square
root of V is the true population standard deviation, SD. The quantity GSDnE =
antilog (SD) is the true population geometric standard deviation of normalized
exposure. The intra-cluster correlation (i.e., the intraclass correlation due to
clusters) is defined as
(9)	ICC = VQ / V = 1 - Vw / V
The ICC is irrelevant to the future distribution of normalized exposure, per se.
However, this intra-cluster correlation is a necessary part of the reference
sampling model because the MEs are obtained in clusters (i.e. there are multiple
MEs per site).
Relative Accuracy and Fold Relative Accuracy
The benchmark objective of the AEATF II monitoring program will be to achieve
adequate relative accuracy of selected parameter estimates if the reference
sampling model described above were used. This benchmark target can be
stated more precisely as:
If there are Nc clusters and NM MEs per cluster and the
underlying lognormal two-stage reference sampling model
were actually true, then selected parameter estimates will be
within K-fold of the true values at least 95% of the time.
If 0 denotes the distributional parameter of interest and T is the estimate of that
parameter obtained from monitoring data, then the relative accuracy of T is
defined simply as:
(10)	RA(T|0) = T/0
Satisfying the benchmark objective above requires that there be at least a 95%
chance that T/0 is between 1/K and K. More formally this is stated as:
(11)	Prob {1/K < RA(T|0)< K} > 0.95
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It is more convenient, however, to consider relative accuracy expressed as a 'fold
relative difference'. This is because statements such as "T is within K-fold of 0"
are more intuitive than the formulation given in (11). The 'fold relative accuracy',
fRA, is defined as:
(12)	fRA(T|0) = Max{ RA(T|0), 1/RA(T|0)} = Max ( T/ 0, 0 / T )
Then, statement (11) is equivalent to
(13)	Prob { fRA(T\Q) < K}> 0.95
and simply says that the estimate, T, will be within K-fold of the true parameter,
0, at least 95% of the time. The 95th percentile of fRA, fRA95, is the specific fold-
accuracy value that satisfies (13). Consequently, the benchmark adequacy goal
reduces to requiring that:
(14)	fRA95< K
If we denote the 2.5th and 97.5th percentiles of the sampling distribution of T by
T2.5 and T97.5, respectively, then the 95th percentile of fold relative accuracy can
also be calculated from
(15)	fRA95 = Max(T97.5/0, 0/T2.s)
Benchmark Objective for Antimicrobial Scenarios
The default benchmark objective for all antimicrobial scenarios in the AEATF II
Monitoring Program is that a sample from the hypothetical reference sampling
distribution above be of adequate size to describe selected measures of the
(normalized) exposure distribution with a pre-determined level of accuracy. EPA
provides guidance to AEATF II on the minimum degree of accuracy needed for
regulatory use in particular scenarios. The current consensus is that estimates of
the geometric mean, the arithmetic mean, and the 95th percentile generally
should be accurate to within approximately 3-fold of their true value.
It should always be kept in mind, however, that this objective is specified in terms
of the reference random sampling distribution. This reference sampling model
does have the same two-stage nesting structure as the actual sampling
approach. The lognormal distribution assumption is also reasonable, robust, and
consistent with existing data. However, the reference distribution assumes
simple random sampling at each stage. It does not, and cannot, incorporate the
combination of purposive and random diversity sampling actually used.
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As noted above, the consequence of diversity sampling is expected to be a
tendency for the sampling variation of normalized exposure to be overestimated.
The sample should tend to over-represent extremes and under-represent the
more common values. Such diversity-oriented data collected for this scenario,
but analyzed with respect to the two-stage reference distribution, is expected to
have minimal bias for central tendency. In contrast, upper percentiles of
exposure are expected to be, on the average, too large. There is no way to
determine the actual magnitude of such overestimation. For regulatory
purposes, however, overestimation of upper percentiles is of minimal concern:
for practical exposure assessments, overestimation of exposures is a
conservative practice utilized by regulatory agencies. A tendency to both
consider and even overestimate upper percentiles is consistent with this practice.
Parameter Estimates Used for Benchmark Objectives
As defined above, relative accuracy applies to the particular quantity, T, that is
used to estimate the reference distribution parameter 0. Thus, it is important to
consider which types of estimates of the geometric mean, arithmetic mean, and
95th percentile are used to evaluate fRA95. The relative accuracies could differ
depending on the particular estimates used.
There are often multiple choices for the parameter estimates. The estimators
can be broadly grouped into either empirical or parametric. Empirical estimates
are the commonly-used statistics available in spreadsheet programs. They do
not (explicitly) assume any distribution. However, they can sometimes require
simple random sampling for greatest efficiency. Parametric estimates
incorporate the fact that the reference distribution is lognormal and could also
account for cluster sampling being used.
The most straightforward parameter is the geometric mean (GMhe)- In the
balanced case, the simple empirical estimate of GMpe can be calculated by
averaging the log-transformed normalized exposures and then taking the antilog
of this value. In this case, the empirical and parametric estimates of GMpe are
identical. If the number of MEs per cluster varies, however, one could consider
geometric means with different degrees of weighting by cluster size. The
arithmetic mean can also be calculated empirically by summing up the
normalized exposures and dividing by the total number of MEs. Again, when the
cluster sizes differ, other types of weighted empirical arithmetic means exist. In
the unbalanced case, neither the weighted nor the unweighted estimates of GMpe
or AMnE are universally best. Consequently, for the purposes of sample size
determination, the simple (and most common) versions of the empirical
geometric and arithmetic means seem preferable. Empirical percentiles could,
theoretically be calculated in the conventional manner. However, when there is
cluster sampling and the number of MEs are not large, empirical estimates of the
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extreme upper (or lower) percentiles are not especially efficient. The parametric
percentiles (see below) are preferred in this case.
Parametric estimates are those closely aligned with the sampling model used. In
this case one uses the fit to the variance component model described in (8)
above to get estimates for the geometric mean (GMhe) and the total geometric
standard deviation (GSDhe)- To estimate the arithmetic mean (AMhe) and 95th
percentile (nE95) one could then use the lognormal relationships:
AMnE = GMnE x Exp { % (logeGSDnE)2 }
(16)
nE95 - GMnE x Exp { Z95 logeGSDnE }
where Z95 is the 95th percentile of the standard normal distribution. For simplicity,
these will be labeled the 'parametric cluster sampling estimates'.
It can be argued that few if any users of the AEATF II monitoring data will choose
to (or be able to) fit variance component models to the data. They will probably
ignore the sampling model and use more conventional estimates. In this case
empirical estimates of GMnE and AMnE defined above would probably be used.
Potential data users might also be less inclined to use empirical percentiles,
especially with smaller sample sizes. The lognormal percentile estimate of nE95
in (16) above would then still be used but perhaps with the mixed model GSDnE
estimate replaced with the more conventional GSDnE (i.e., the back-transformed
simple standard deviation of log exposures.) For convenience, estimates that
assume lognormality but not cluster sampling will be labeled 'simple random
sampling parametric percentiles'.
Any or all of the above estimators could be evaluated. However, for the
purposes of determining sample sizes, it is recommended that focus be on the
following estimators:
•	GMnE - simple empirical estimate
•	AMnE - simple empirical estimate
•	nE95 - parametric cluster sampling estimate
The Determination of Sample Size
As stated above, the benchmark adequacy goal reduces to requiring that the
95% percentile of fold relative accuracy, fRA95, be less than or equal to K. Under
the reference two-stage random sampling model described above, the only
quantities needed to determine relative accuracy of population parameter
estimates are reasonable values for GSDnE and ICC. Such values could be
based on existing exposure data for scenario-specific tasks, surrogate exposure
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data from similar tasks, and/or reasonable assumptions based on subject-matter
expertise.
Given these values, fRA95, can be computed for any combination of the Nc and
Nm. Calculation of the 95% percentile of fold relative accuracy is complex and is
usually best accomplished using Monte Carlo simulation methods. When the
number of MEs per cluster, Nm, is the same for all clusters, the geometric mean,
fRA95 can be calculated directly from the GSDnE and ICC as:
where N is the total number of MEs (i.e., N=NcxNm). For parameters other than
the geometric mean, a straightforward simulation approach can be used to
determine fRA95. This procedure is:
1.	Simulate a set of normalized exposure data for Nc clusters and Nm
monitoring units per cluster using the reference sampling model
defined in (8) above.
2.	From each set of simulated data, calculate T, the estimate of 0
3.	Repeat steps 1 and 2 above M times to get M values of the
estimate T
4.	From these M T-values calculate T2.5 and T97.5, the 2.5th and 97.5th
percentiles of T, respectively.
5.	Calculate the 95th percentile of fold relative accuracy, fRA95, using
formula (15) above.
The number of simulations, M, should be some large number such as 1,000 or
10,000. This process can be continued until a combination of Nc and NM are
found that satisfy to benchmark objective.
General Guidelines for Diversity Selection of Monitoring Events
Although diversity selection is simple in theory, practical implementation is often
complex and usually scenario specific. This section presents diversity selection
procedures and recommendations that apply generally to all scenarios.
Scenario-specific design documents and study protocols will provide details of
ME selection and construction.
As described previously, the objective of diversity selection is to obtain a diverse
set of handler-day conditions from among those conditions possible when an
arbitrary ai is used in future scenario-related tasks. These selected HD
conditions are then used to construct monitoring events. Diversity selection is
(17)
JRA95 = exp< 1.96 In GSDt
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done independently at each stage of 'sampling'. Thus, a diverse set of sites is
selected followed by a diverse set of ME conditions within each site.
Diversity should always be with respect to characteristics (i.e. particular
components of C) that are expected to impact exposure. Whenever possible, the
characteristics used should be meta-factors. Meta-factors are characteristics
that indirectly influence a number of other characteristics. For example, a
worker is a meta-factor because substituting one worker for another alters a
number of factors (e.g., behavior, physical appearance, stamina) that might affect
exposure. Other common meta-factors are geographic location and time-of-year.
Not every characteristic that may impact exposure can be, or even should be,
considered in diversity selection. The number of possible combinations of factors
that may impact exposure will always greatly exceed the number of planned
MEs. Consequently, only a few characteristics, preferably meta-factors, can be
used effectively in diversity selection.
Diversity Selection Approaches
There are a number of ways to achieve diversity among ME handler-day
conditions. The most straightforward approach is to purposively select MEs that
appear to be sufficiently different with respect to the characteristics of interest.
Documentation for such direct purposive selection should include the
characteristics considered and how much these characteristics differ among the
ME. Although flexible, and likely to achieve a set of MEs with a great amount of
diversity, this approach is subjective and, therefore, difficult to reproduce.
More formal approaches are also possible. A general, albeit quite sophisticated,
approach is to define diversity scores for each possible configuration of the
characteristics of interest. A total configuration score might be defined as a
function of the dissimilarity between possible pairs of units. Then, one simply
selects (or synthetically constructs) those configurations that result in the
greatest diversity score. If multiple configurations have the highest score, a
random selection among these is possible. While achieving diversity in an
objective and reproducible manner, this approach is quite complex and difficult to
implement.
A formal approach that is both common and simple to implement is stratified
diversity selection. In this approach available selectable units (e.g., sites, MEs)
are partitioned into strata based on characteristics likely to impact exposure.
Each possible selection unit must belong to one and only one stratum. The
number of strata must be at least as large as the number of units that will be
selected. For example, if there are three units to be selected, then there should
be at least three strata. Diversity could be achieved by selecting (purposively or
randomly) no more than one unit from each stratum. If there are more strata
than units to be selected, then a subset of the strata should be selected first.
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This could be either purposively (to increase diversity) or randomly (to reduce
intentional selection bias).
Stratified diversity selection is similar to the method of stratification used in
population sampling. Unlike the case with stratified sampling, however, diversity
is increased by selecting only a single unit from each stratum. There is no
attempt to sample or to weight results in proportion to stratum size. In fact
stratum size in the future HD population is usually unknown.
Diversity Selection of First-Stage Units
At the first stage of ME selection, sites are the 'selectable' units. As defined
previously, site is considered a particular experimental location and timeframe for
monitoring. Diversity selection of sites means obtaining sites that are different
from each other, on the average, with respect to some characteristic(s) expected
to impact exposure. Thus, there should be little surprise if exposure, on the
average, differs between sites. If sites are constructed environments, then they
can be built to be different from each other with respect to important
characteristic(s). If there are a number of possible sites available and a set is to
be selected (randomly or purposively), then stratified diversity selection of sites,
based on the important characteristic(s), is a feasible approach
Diversity Selection of Second-Stage Units
Ultimately the second stage selection units are the final MEs. The MEs should
be diversified independently within each selected site. In most cases within-site
diversity selection of MEs focuses only on two characteristics: subject and
normalizing factor.
Handling-day exposures for the same individual are expected to be correlated.
That is, many components of C relating to same worker will be identical, even on
different days. In contrast, different individuals are less correlated. Worker
behaviors are expected to have great impact on exposure. Consequently,
diversity is increased by simply requiring that each ME be constructed using a
different individual.
MEs should also be diverse with respect to the normalization factor that is
deemed appropriate for the scenario. One feasible approach is to partition the
possible levels of NF into strata and construct one ME from each NF stratum.
In some cases (e.g. simulated-condition studies) there is a pool of available
workers that can be assigned to any NF stratum. If all possible configurations of
assignment are equivalent, then workers could be randomly allocated to strata. If
some allocations are non-equivalent (e.g. more cost effective or there are
scheduling issues) then a purposive assignment of individuals to NF levels might
be preferable.
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In other cases (e.g. In Situ/observational studies) worker availability depends on
the particular NF level chosen. Some individuals may only work with higher NF
levels and some with only lower NF, say. Selection of workers could still be
random, although random choice might be restricted to within each NF stratum.
However, when such associations between subject and NF levels exist,
purposive allocation might result in a more cost effective and practical
configuration.
Rationale for Using the Normalizing Factor in Diversity Selection
It might at first appear pointless to select MEs with differing levels of the
normalizing factor when diversity of normalized exposures is desired. If the NF is
approximately proportional to the amount of potential ai contact, then normalized
exposure should be independent of the levels of NF. Consequently, it should
make no difference whether all MEs are at the same level or at different levels of
the NF.
This would be true if the value of the normalizing factor had no impact on the
other ME conditions selected. However, this might not be true. Because amount
of active ingredient contact is so important to exposure, it is likely that the NF is
also a meta-factor. That is, it is not unreasonable to expect that different values
of the NF will be naturally associated with specific sets of handler-day conditions,
C. Suppose, for example, that the normalizing factor for wiping application
exposure was correlated with duration of task. It is conceivable that some worker
behaviors (e.g. fatigue) and diversity of surfaces wiped might be different for
shorter duration MEs than for longer duration MEs. By insuring that the levels of
NF are varied, the set of MEs indirectly captures diversity in those components of
C that are naturally associated with the normalizing factor.
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Appendix F: Evaluation of Existing PHED Applicator
Exposure Data for Hand-Held Aerosol Spray
The Pesticide Handlers Exposure Database (PHED, version 1.1) contains two
studies involving the monitoring of dermal and inhalation exposure during the use
of a pressurized aerosol container. The current HED PHED Surrogate Guide
uses the data only from Study 521 for aerosols (Scenario 10). The two studies
were accessed in PHED by subsetting the applicator file for method of
application equal to aerosol can. The two studies were identified as Study 456
and 521 and both involved the application of an insecticide. A general review of
these studies is provided in the "PHED SCENARIO DISCUSSION" section of this
report. This is followed by the "ACCEPTANCE CRITERIA EVALUATION"
section of this report, wherein the following information and "data acceptance
criteria" were evaluated:
1.	Meta information: Scenario (e.g., hand held aerosols) study(ies) code(s),
total number of replicates or monitoring events, range of AaiH, dermal and
inhalation sampling durations, average limits of quantitation (LOQ's) for
dermal and inhalation exposure, percentage of samples with undetectable
residues body area.
2.	Results of selected AEATF ll/AHETF data acceptance criteria applied to
the scenario-specific study data set(s):
a.	Identification of the number of monitoring events classified in PHED
as A and B grade; A and B grade data indicate compliance with the
criteria: the average recoveries of lab spikes should be between 70-
120 percent and the precision value (coefficient of variation; CV)
should be less than or equal to 20 percent AND recovery of field
fortification samples should be 50-120% with a C.V. +/-25%;
b.	The number monitoring events where non-detects/less than LOQ
values account for less than 40% of dermal exposure; and
c.	The number of monitoring events with a minimum of 10 dermal
patch dosimeters attached inside or outside normal work clothing to
the chest, back, both upper arms, both lower arms, both upper legs,
both lower legs, plus hand (cotton gloves can substitute for hand
wash) and head/face exposure determinations.
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PHED SCENARIO DISCUSSION
Method of Application
PHED Study 456 involved the application of one 15-ounce aerosol can of
insecticide per house in each of 15 houses in Kansas City, Missouri. Three study
volunteers treated five houses each. The aerosol cans contained 1% of the
active ingredient under study, equivalent to 4.33 grams a.i. per can. Applicators
held the aerosol can in one hand and sprayed the contents of the container into
cracks and crevices, along baseboards, under sinks, behind appliances, and in
other areas were insects would be expected to hide.
PHED Study 521 involved the application of one 16-ounce aerosol can of
insecticide per house in each of 15 houses in Vero Beach, Florida. Five study
volunteers treated three houses each. The aerosol cans contained 1% active
ingredient, equivalent to 4.54 grams a.i. per can. Applicators held the aerosol
can in one hand and sprayed the contents into cracks and crevices, along
baseboards, under sinks, behind appliances, and in other areas where insects
were expected to hide.
Exposure Monitoring Methodology
Both Study 456 and Study 521 used gauze patches for dermal exposure
monitoring. Volunteers wore a single layer of clothing that included a long-
sleeved shirt, long pants, and shoes. The dermal gauze patches were in holders
with an open diameter of 5.6 cm, and were placed under the single layer of
clothing on the participant's upper arms, forearms, chest, back, thighs, and lower
legs. These dosimeters provide dermal exposure estimates under a single layer
of clothing.
A second set of dermal dosimeters were placed outside the clothing, but so as
not to occlude the inner dosimeters. The outer dermal dosimeters were also
placed on the upper arms, forearms, chest, back, thighs, and lower legs. This
set-up provides dermal dosimetry data needed to estimate actual dermal
exposure for a variety of clothing possibilities ranging from long-sleeved shirt and
long pants to short pants and a short-sleeved shirt. Head exposure was
monitored by the placement of a gauze dosimeter on a ball cap just above the bill
of the hat.
Hand exposure was monitored using hand-rinses. Applicator's hands were
rinsed at the completion of application in each house. Each hand was rinsed
separately using 200 ml_ of ethanol and each hand was rinsed twice in a total of
400 ml_ of ethanol. The total rinsate from the four rinses (two for each hand)
were combined for analysis. Volunteers in Study 456 wore chemical-resistant
gloves during all 15 replications; the results of this study represent hand
exposure under protective gloves. Volunteers in Study 521 wore no gloves, and
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the results represent exposure to unprotected hands. Taken together, both
studies support a comparison of protected and unprotected hand exposure
during aerosol can use.
Inhalation exposure was monitored using personal air samplers with the
sampling cassette placed on the collar near the participant's breathing zone. Air
was drawn through the sampling cassettes at a flow rate of 1 liter per minute.
The air pumps were sampled before and after each monitoring period.
PHED Data Quality Grades
Data in PHED are graded for quality based on analytical quality assurance. The
data are assigned to one of five grades, A through E, based on the recovery of
the active ingredient from fortified field samples, fortified laboratory samples, and
storage stability samples. Grade A and B data meet the minimum analytical
quality assurance requirements as described in EPA's Subdivision U of the
Pesticide Assessment Guidelines. Grade A and B data have laboratory
recoveries of 80% to 110% with a coefficient of variation of 25% or less. The
field recoveries are between 50% and 120%. Grade C data have laboratory
recoveries of 70% to 120% with a coefficient of variation of 33% or less. Grade
C data must also have either field recoveries of 30% to 120%, or the data must
have storage stability recoveries of 50% to 120%. Grade D data have laboratory
recoveries of 60% to 120% with a coefficient of variation of 33% or less. Field
recovery or storage stability data are not required for a grade D classification.
Grade E data do not meet any of these standards. To support the registration of
a pesticide, the data subset should contain a minimum of 15 replications for each
body area except the feet. The data should also meet the minimum analytical
quality assurance requirements of grades A or B. The Health Effects Division
uses the number of replicates in a scenario and the data quality grades to rate
the PHED data for a given scenario as high confidence, medium confidence, or
low confidence data.
Study 521 contains 15 replications of hand, dermal, and inhalation data that were
graded A. The hand data in Study 456 were graded A, but the dermal and
inhalation data were graded C. The HED PHED Surrogate Guide lists aerosol
application as Scenario 10. Because of the grading, Scenario 10 lists only the 15
replicates from Study 521 and gives them a high confidence rating.
Study 456 Dermal Exposure
The dermal exposures from Study 456 are presented below. The dermal
exposure is presented both as the "no clothing" scenario and as long-sleeved
shirt and long pants to permit analysis of multiple clothing scenarios. The
exposure data are presented in micrograms and were not normalized by the
amount of a.i. handled. As previously noted, all replicates in Study 456 involved
handling 4.33 grams of active ingredient.
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Page 144 of 194
« Specifications »
Subset Specifications for STUDY456.APPL
With Study Code Equal to 456
Subset originated from AEROSAL.APPL
With Application Method Equal to 4
Subset originated from APPL.FILE
SUMMARY STATISTICS FOR CALCULATED DERMAL EXPOSURES
SCENARIO: No clothing (total deposition)
PATCH
LOCATION
HEAD (ALL)
NECK.FRONT
NECK.BACK
UPPER ARMS
508.4372
DISTRIB.
TYPE
Lognormal
Lognormal
Lognormal
Median
288.6
14.25
13.86
Lognormal
15
MICROGRAMS
Mean Coef of Var Geo. Mean Obs.
435.5867 90.9793 209.1935
30.07	126.9042 11.7512
20.5847 80.8261 13.0283
776.97	1129.177 125.0676
15
15
15
CHEST
15
BACK
FOREARMS
15
THIGHS
LOWER LEGS
FEET
HANDS
TOTAL DERM:
Lognormal 337.25
Lognormal
Lognormal
Lognormal
Lognormal
447.3
362.395
255.94
86.87
711.6567 126.9042	278.1117
664.3233 80.826 420.4601	15
714.9083 137.7725	276.778
2025.6265 2583.435
328.0107
137.564
0
0
4171.8814
97.1166
90.5475
210.1775
97.689
15
15
2025.6265
95% C.I. on Mean: Dermal: [-29183.6113, 37527.3741]
Number of Records: 15
Data File: APPLICATOR	Subset Name: STUDY456.APPL
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The dermal exposure to all body areas had a lognormal distribution. The total
geometric mean dermal exposure was 2.03 mg/replicate. Note that this dermal
exposure represents exposure outside the clothing and because of the use of
protective gloves, there are no data for the hands.
The dermal exposure under a single layer of clothing and protective gloves is
presented below.
SUMMARY STATISTICS FOR CALCULATED DERMAL EXPOSURES
SCENARIO: Long pants, long sleeves, gloves
PATCH
DISTRIB.

MICROGRAMS


LOCATION
TYPE
Median
Mean
Coef of Var
• Geo. Mean
Obs.
HEAD (ALL)
Lognormal
288.6
435.5867
90.9793
209.1935
15
NECK.FRONT
Lognormal
14.25
30.07
126.9042
11.7512
15
NECK.BACK
Lognormal
13.86
20.5847
80.8261
13.0283
15
UPPER ARMS
Other
43.65
43.65
0
43.6502
15
CHEST
Other
53.25
53.25
0
53.2503
15
BACK
Other
53.25
53.25
0
53.2503
15
FOREARMS
Other
18.15
18.3113
3.4121
18.3022
15
THIGHS
Other
57.3
57.3
0
57.3003
15
LOWER LEGS
Other
35.7
37.128
9.5542
36.9913
15
FEET



0


HANDS
Other
5
15.7067
152.4528
9.0385
15
TOTAL DERM:
500.273
583.01
764.8374

505.7561

95% C.I. on Mean: Dermal: [-5623.8395, 7153.5143]
Number of Records: 15
Data File: APPLICATOR	Subset Name: STUDY456.APPL
The dermal exposure to the head and neck are the same as in the "no clothing"
scenario because they are based on the same outer dosimeters. The dermal
exposure to the upper arms, chest, back, and thighs is based on residue levels
below the limit of quantification and therefore are based on half of the LOQ as
per PHED and HED guidelines. It can be determined that all 15 observations for
these body areas were below the LOQ because the coefficient of variation is 0.
The forearms had only one study participant with detectable residues and then
only to the right forearm dosimeter. The lower legs had one replication with
detectable residues to both dosimeters and two additional replicates with
detectable residues to the left lower leg dosimeter. The dermal dosimeter LOQ
in Study 456 was 0.03 |jg/cm2. The hand wash LOQ was 10 |jg per sample. The
total dermal exposure for an individual wearing long pants, a long-sleeved shirt,
and protective gloves is 0.50 mg based on the PHED "best fit" guideline.
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Study 521 Dermal Exposure
The potential dermal exposure under the "no clothing scenario is presented
below.
« Specifications »
Subset Specifications for STUDY521 .APPL
With Study Code Equal to 521
Subset originated from AEROSAL.APPL
With Application Method Equal to 4
Subset originated from APPL.FILE
SUMMARY STATISTICS FOR CALCULATED DERMAL EXPOSURES
SCENARIO: No
i clothing (total deposition)




PATCH
DISTRIB.
MICROGRAMS


LOCATION
TYPE
Median
Mean CoefofVar
Geo. Mean
Obs.
HEAD (ALL)
Lognormal
419.9
697.6927
124.9606
410.258
15
NECK.FRONT
Lognormal
21
71.499
217.76
25.1292
15
NECK.BACK
Lognormal
21.34
26.1235
80.9252
19.9517
15
UPPER ARMS
Lognormal
1063.896
1320.4028
69.3397
999.3333
15
CHEST
Lognormal
497
1692.143
217.7599
594.7233
15
BACK
Lognormal
688.7
843.0777
80.9252
643.8954
15
FOREARMS
Lognormal
752.62
800.2295
82.2052
488.1726
15
THIGHS
Lognormal
223.47
483.612
124.2601
299.811
15
LOWER LEGS
Lognormal
169.456
627.3363
177.4108
248.3608
15
FEET


0



HANDS
Lognormal
1100 1210.2667
51.0748
1056.7992
15
TOTAL DERM:

4786.4345
4957.382
7772.3832
4786.4345

95% C.I. on Mean: Dermal: [-60276.6132, 75821.3796]
Number of Records: 15
Data File: APPLICATOR	Subset Name: STUDY521 .APPL
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The total potential exposure under the "no clothing scenario" is 4.79 mg/replicate.
All body areas had a lognormal distribution. Because hand exposure is included
in the Study 521 data the hand exposure must be subtracted from the total
potential exposure to permit a direct comparison with Study 456. The geometric
mean hand exposure was 1.057 mg and the dermal exposure excluding the
hands is 3.73 mg/replicate. The total potential dermal exposure in Study 456
was 2.03 mg/replicate.
The actual dermal exposure to an individual wearing long pants and a long
sleeved shirt is presented below.
SUMMARY STATISTICS FOR CALCULATED DERMAL EXPOSURES
SCENARIO: Long pants, long sleeves, no gloves
PATCH DISTRIB.	MICROGRAMS
LOCATION TYPE	Median	Mean CoefofVar	Geo. Mean Obs.
HEAD (ALL) Lognormal	419.9	697.6927 124.9606	410.258 15
NECK.FRONT Lognormal	21	71.499 217.76	25.1292 15
NECK.BACK Lognormal	21.34	26.1235 80.9252	19.9517 15
UPPER ARMS Other	59.073	59.073 0	59.075 15
CHEST Other	72.065	72.065 0	72.0675 15
BACK Other	72.065	72.065 0	72.0675 15
FOREARMS Other	24.563	27.3783 39.8253	26.2578 15
THIGHS Other	77.546	77.546 0	77.5487 15
LOWER LEGS Other	48.314	48.314 0	48.3157 15
FEET	0
HANDS Lognormal	1100	1210.2667 51.0748	1056.7992 15
TOTAL DERM:	1865.7641	1915.866 2362.0232	1867.4703
95% C.I. on Mean: Dermal: [-14926.1143, 19650.1607]
Number of Records: 15
Data File: APPLICATOR	Subset Name: STUDY521 .APPL
The exposure pattern under a single layer of clothing in Study 521 is similar to
that reported in Study 456. All covered body areas except the forearms had
residue levels on all dosimeters that were below the study's LOQ. Among the
forearm dosimeters there was one replicate with quantifiable residues on the left
forearm dosimeter. The limit of quantification in Study 521 was 0.0406 |jg/cm2
for the dermal dosimeters and 100 |jg/replicate for the hand rinses. The dermal
exposure under a single layer of clothing from Study 521 can be compared to
exposure in Study 456 by subtracting the 1.058 mg hand exposure from the total
dermal exposure of 1.866 mg. The total dermal exposure excluding the hands in
Study 521 is 0.809 mg/replicate compared to the total dermal exposure excluding
the hands of 0.495 mg/replicate.
By combining the dermal exposure data from Studies 456 and 521 it is possible
to estimate the reduction in exposure attributable to the use of protective gloves.
Although EPA does not routinely consider the use of protective gloves for
homeowner uses of aerosols, the use of protective gloves may possibly be
considered for occupational uses of aerosol containers.
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Combined Dermal Exposure Estimate
The combined dermal exposure data based on Studies 456 and 521 are
presented below. The first scenario represents exposure when wearing a long-
sleeved shirt, long pants, and no gloves. The second scenario represents
exposure when wearing a long-sleeved shirt, long pants, and protective gloves.
The difference between the two estimates provides insight into the protection
provided by chemical-resistant gloves.
« Specifications »
Subset Specifications for AEROSAL.APPL
With Application Method Equal to 4
Subset originated from APPL.FILE
SUMMARY STATISTICS FOR CALCULATED DERMAL EXPOSURES
SCENARIO: Long pants, long sleeves, no gloves
PATCH	DISTRIB.	MICROGRAMS
LOCATION
TYPE
Median
Mean CoefofVar
Geo. Mean
Obs.
HEAD (ALL)
Lognormal
353.6
566.6397
119.763
292.9561
30
NECK.FRONT
Lognormal
20.1
50.7845
223.2098
17.1842
30
NECK.BACK
Lognormal
18.095
23.3541
80.9408
16.1226
30
UPPER ARMS
Other
51.3615
51.3615
15.2708
50.7803
30
CHEST
Other
62.6575
62.6575
15.2708
61.9485
30
BACK
Other
62.6575
62.6575
15.2708
61.9485
30
FOREARMS
Other
22.5665
22.8448
38.8679
21.922
30
THIGHS
Other
67.423
67.423
15.2709
66.66
30
LOWER LEGS
Other
48.314
42.721
14.5118
42.276
30
FEET



0


HANDS
Lognormal
1100
1210.2667
51.0748
1056.7992
15
TOTAL DERM:
1698.0421
1806.775
2160.7103

1688.5974

95% C.I. on Mean: Dermal: [-10432.2269, 14753.6475]
Number of Records: 30
Data File: APPLICATOR	Subset Name: AEROSAL.APPL
SUMMARY STATISTICS FOR CALCULATED DERMAL EXPOSURES
SCENARIO: Long pants, long sleeves, gloves
PATCH DISTRIB.	MICROGRAMS
LOCATION
TYPE
Median
Mean 1
Coef of Var
Geo. Mean
Obs
HEAD (ALL)
Lognormal
353.6
566.6397
119.763
292.9561
30
NECK.FRONT
Lognormal
20.1
50.7845
223.2098
17.1842
30
NECK.BACK
Lognormal
18.095
23.3541
80.9408
16.1226
30
UPPER ARMS
Other
51.3615
51.3615
15.2708
50.7803
30
CHEST
Other
62.6575
62.6575
15.2708
61.9485
30
BACK
Other
62.6575
62.6575
15.2708
61.9485
30
FOREARMS
Other
22.5665
22.8448
38.8679
21.922
30
THIGHS
Other
67.423
67.423
15.2709
66.66
30
LOWER LEGS
Other
48.314
42.721
14.5118
42.276
30
FEET



0


HANDS
Other
5
15.7067
152.4528
9.0385
15
TOTAL DERM:
646.2429
711.775
966.1503

640.8367

148

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 149 of 194
95% C.I. on Mean: Dermal: [-6835.8234, 8768.124]
Number of Records: 30
Data File: APPLICATOR	Subset Name: AEROSAL.APPL
Based on the PHED analysis the use of protective gloves reduces the dermal
exposure from 1.7 mg/aerosol can to 0.65 mg/aerosol can, where an aerosol can
is 15 to 16 ounces.
Inhalation Exposure
PHED was used to estimate the inhalation exposure potential for Studies 456
and 521 separately and combined. PHED requires the user to select a breathing
volume. Past analysis by OPP's Health Effects Division HED assumed a
breathing volume of 29 liters/minute. For this analysis a breathing volume of
approximately 17 liters/minute was used (U.S. EPA Exposure Factors Handbook;
http://www.epa.gov/ncea/efh/).
The inhalation exposure from Study 456 is as follows:
« Specifications »
Subset Specifications for STUDY456.APPL
With Study Code Equal to 456
Subset originated from AEROSAL.APPL
With Application Method Equal to 4
Subset originated from APPL.FILE
SUMMARY STATISTICS FOR INHALATION EXPOSURES
DISTRIB.	NANOGRAMS
TYPE Median Mean	Coef of Var Geo. Mean	Obs.
EXPOSURE Lognormal 27523.8095 26580.3734 49.7805	22356.8193 15
95% C.I. on Geo. Mean: [5704.4462, 87620.6649]
Number of Records: 15
Data File: APPLICATOR	Subset Name: STUDY456.APPL
The inhalation exposure in Study 456 was 22 |jg/replicate or aerosol can. The
inhalation exposure is 1.3% of the dermal exposure when gloves are not worn.
149

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 150 of 194
The inhalation exposure from Study 521 is as follows:
« Specifications »
Subset Specifications for STUDY521 .APPL
With Study Code Equal to 521
Subset originated from AEROSAL.APPL
With Application Method Equal to 4
Subset originated from APPL.FILE
SUMMARY STATISTICS FOR INHALATION EXPOSURES
DISTRIB.	NANOGRAMS
TYPE Median Mean	Coef of Var Geo. Mean	Obs.
EXPOSURE Other 7456.1404 10594.0506 61.6887	9345.3422 15
95% C.I. on Geo. Mean: [3720.0299, 23477.0745]
Number of Records: 15
Data File: APPLICATOR	Subset Name: STUDY521 .APPL
The inhalation exposure in Study 521 was 9.3 |jg/replicate. The inhalation
exposure is similar to the exposure monitored in Study 456 and represents 0.5%
of the dermal exposure when gloves are not worn.
The combined inhalation exposure from both studies is presented below.
« Specifications »
Subset Specifications for AEROSAL.APPL
With Application Method Equal to 4
Subset originated from APPL.FILE
SUMMARY STATISTICS FOR INHALATION EXPOSURES
DISTRIB.	NANOGRAMS
TYPE Median Mean	Coef of Var	Geo. Mean Obs.
EXPOSURE Other 13379.6296 18587.212 70.4015	14454.4846 30
95% C.I. on Geo. Mean: [3433.5175, 60850.7529]
Number of Records: 30
Data File: APPLICATOR	Subset Name: AEROSAL.APPL
The inhalation exposure is 14 |jg/aerosol can when the container is 15 to 16
ounces.
150

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 151 of 194
Conclusions
PHED contains two studies that monitored dermal and inhalation exposure
during the application of the entire contents of one container per replicate. EPA's
PHED Surrogate Guide (Scenario 10) uses the data only from Study 521.
Study 456 provides data for hands protected by gloves while Study 521 presents
data for unprotected hands. This permits an estimate of exposure reduction
when gloves are worn (for scenarios where protective glove use is reasonable.)
A significant limitation of these existing data is that the use conditions for both
studies, including the number of cans applied per replicate and the AaiH, were
very similar. This prevents evaluating any potential relationship between
exposure and either the number of cans used or the AaiH. PHED study 521
provides MUs that meet key AEATF II acceptance criteria, but additional
monitoring events should be considered to provide a wider range of amount of
formulation sprayed (AaiH) under conditions relevant to antimicrobial aerosol
product use.
151

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 152 of 194
Attachment 1. Individual Replicate Dosimeter Residue Levels
« AEROSAL.APPL »
Total Al Total
Record Applied US Gal
I.D. (lb)
Sprayed
0456*B*4
.0094
1200
0456*B*5
.0094
1200
0456*C*1
.0094
1200
0456*C*2
.0094
1200
0456*C*3
.0094
1200
0456*C*4
.0094
1200
0456*C*5
.0094
1200
0521*B*02
.0100
.1250
0521*D*02
.0100
.1250
0456* A*01
.0094
.1200
0456*A*02
.0094
.1200
0521*A*02
.0100
.1250
0521*C*01
.0100
.1250
0521*A*03
.0100
.1250
0521*C*02
.0100
.1250
0521*C*03
.0100
.1250
0521*E*01
.0100
.1250
0521*E*02
.0100
.1250
0521*E*03
.0100
.1250
0521*A*01
.0100
.1250
0456*A*3
.0094
1200
0456*A*4
.0094
1200
0456*A*5
.0094
1200
0456*B*1
.0094
1200
0456*B*2
.0094
1200
0456*B*3
.0094
1200
0521*B*01
.0100
.1250
0521*D*01
.0100
.1250
0521*D*03
.0100
.1250
0521*B*03
.0100
.1250
« AEROSAL.APPL »
Air Smpl Air Quan. Air Air
Record Time Limit Volume Amount
I.D. (min
) (ug)
(I)
(ug)

0456*B*4
28.0
.1000
30.8
3.0300
0456*B*5
18.0
.1000
19.4
1.3900
0456*C*1
15.0
.1000
16.2
.8900
0456*C*2
21.0
.1000
22.6
1.2500
0456*C*3
19.0
.1000
19.7
1.3700
0456*C*4
26.0
.1000
27.0
.5800
0456*C*5
13.0
.1000
13.5
.7800
0521*B*02
28.0
1.0000
33.0
ND
0521*D*02
19.0
1.0000
22.4
ND
0456* A*01
30.0
.1000
31.5
1.7000
0456*A*02
28.0
.1000
29.4
.2200
0521*A*02
33.0
1.0000
38.9
ND
0521*C*01
32.0
1.0000
34.9
ND
0521*A*03
31.0
1.0000
35.3
ND
0521*C*02
27.0
1.0000
31.9
1.6143
0521*C*03
32.0
1.0000
36.5
ND
0521*E*01
31.0
1.0000
33.8
1.3600
0521*E*02
32.0
1.0000
37.8
ND
152

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 153 of 194
0521*E*03
36.0
1.0000
41.0
ND
0521*A*01
28.0
1.0000
30.5
ND
0456*A*3
33.0
.1000
34.6
2.6700
0456*A*4
30.0
.1000
32.7
2.0300
0456*A*5
25.0
.1000
27.2
2.6000
0456*B*1
23.0
.1000
25.0
2.6200
0456*B*2
30.0
.1000
32.7
2.2500
0456*B*3
31.0
.1000
34.1
1.8900
0521*B*01
27.0
1.0000
29.4
ND
0521*D*01
26.0
1.0000
28.3
1.6000
0521*D*03
22.0
1.0000
25.1
ND
0521*B*03
18.0
1.0000
20.5
ND
« AEROSAL.APPL » (H)P
Outside Inside Dermal Avg Hand
Record Both Hands Both Hands Smpl Time Quan. Limit
I D. (ug) (ug) (hrs) (ug/sq cm)
0456*B*4

ND
.470
10.0000
0456*B*5

ND
.310
10.0000
0456*C*1

ND
.250
10.0000
0456*C*2
21.6000
.350
10.0000
0456*C*3
97.6000
.320
10.0000
0456*C*4

ND
.430
10.0000
0456*C*5

ND
.220
10.0000
0521*B*02
430.0000

.470
100.0000
0521*D*02
981.0000

.320
100.0000
0456* A*01

ND
.500
10.0000
0456*A*02

ND
.470
10.0000
0521*A*02
1240.0000

.550
100.0000
0521*C*01
1750.0000

.530
100.0000
0521*A*03
1070.0000

.520
100.0000
0521*C*02
645.0000

.450
100.0000
0521*C*03
2690.0000

.530
100.0000
0521*E*01
1530.0000

.520
100.0000
0521*E*02
299.0000

.530
100.0000
0521*E*03
1060.0000

.600
100.0000
0521*A*01
1100.0000

.470
100.0000
0456*A*3
22.4000
.550
10.0000
0456*A*4
24.8000
.500
10.0000
0456*A*5

ND
.420
10.0000
0456*B*1
19.2000
.380
10.0000
0456*B*2

ND
.500
10.0000
0456*B*3

ND
.520
10.0000
0521*B*01
1150.0000

.450
100.0000
0521*D*01
2010.0000

.430
100.0000
0521*D*03
1440.0000

.370
100.0000
0521*B*03
759.0000

.300
100.0000
Note: Avg. Hand Quantification is pg/sample.
The 100 |jg LOQ for study 521 was erroneously entered into PHED as 100 |jg. The correct value is 10 |jg.
« AEROSAL.APPL » (H)Page 1 (V
UpprArm UpprArm UpprArm UpprArm Avg Dermal
Record In Rght In Left Out Rght Out Left Quan. Limit
I.D. (ug/sq cm) (ug/sq cm) (ug/sq cm) (ug/sq cm) (ug/sq cm)
0456*B*4
ND
ND
.2880
.2050
.0300
0456*B*5
ND
ND
.3250
.2090
.0300
0456*C*1
ND
ND
.0340
.0140
.0300
0456*C*2
ND
ND
.0180
.0280
.0300
153

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 154 of 194
0456*C*3
ND
ND
ND
ND
.0300
0456*C*4
ND
ND
.0650
.1610
.0300
0456*C*5
ND
ND
.0170
.0320
.0300
0521*B*02
ND
ND
.1770
ND
.0406
0521*D*02
ND
ND
.9990
.4340
.0406
0456* A*01
ND
ND
1.1970
.1930
.0300
0456*A*02
ND
ND
.7630
.0730
.0300
0521*A*02
ND
ND
.5030
.9990
.0406
0521*C*01
ND
ND
.1400
.3760
.0406
0521*A*03
ND
ND
.1360
.0830
.0406
0521*C*02
ND
ND
.4300
.7920
.0406
0521*C*03
ND
ND
.7430
.9660
.0406
0521*E*01
ND
ND
.4710
.1790
.0406
0521*E*02
ND
ND
.7880
.3670
.0406
0521*E*03
ND
ND
.1560
.3000
.0406
0521*A*01
ND
ND
.9700
.0620
.0406
0456*A*3
ND
ND
.1970
.8200
.0300
0456*A*4
ND
ND
.9730
.3980
.0300
0456*A*5
ND
ND
.0780
.1390
.0300
0456*B*1
ND
ND
.7500
.2530
.0300
0456*B*2
ND
ND
1.3070
2.5330
.0300
0456*B*3
ND
ND
.2180
.3230
.0300
0521*B*01
ND
ND
.7110
ND
.0406
0521*D*01
ND
ND
.7630
1.4940
.0406
0521*D*03
ND
ND
.1830
.1830
.0406
0521*B*03
ND
ND
.1020
.0650
.0406
« AEROSAL.APPL »
Forearm Forearm Forearm Forearm
Record In Rght In Left Out Rght Out Left
I.D. (ug/sq cm) (ug/sq cm) (ug/sq cm) (ug/sq cm)
0456*B*4
ND
ND
.1860
1.0100
0456*B*5
ND
ND
.1830
1.3750
0456*C*1
ND
ND
.0180
.0240
0456*C*2
.0190
ND
.0330
.0500
0456*C*3
ND
ND
ND
ND
0456*C*4
ND
ND
.0750
.0370
0456*C*5
ND
ND
.0460
.0800
0521*B*02
ND
ND
ND
ND
0521*D*02
ND
ND
ND
1.3400
0456* A*01
ND
ND
2.8240
.5200
0456*A*02
ND
ND
.4640
.1350
0521*A*02
ND
ND
.3290
.6740
0521*C*01
ND
ND
.2740
.9700
0521*A*03
ND
ND
1.2630
.1420
0521*C*02
ND
ND
.5810
1.5790
0521*C*03
ND
ND
1.4290
.3690
0521*E*01
ND
ND
.4300
1.2300
0521*E*02
ND
ND
.8930
.2900
0521*E*03
ND
ND
.0510
.1920
0521*A*01
ND
ND
4.1410
.2540
0456*A*3
ND
ND
.3060
.7240
0456*A*4
ND
ND
.0960
.2350
0456*A*5
ND
ND
.0370
.5380
0456*B*1
ND
ND
1.3150
.7400
0456*B*2
ND
ND
.6510
5.3930
0456*B*3
ND
ND
.2000
.4000
0521*B*01
ND
ND
.4590
.4140
0521*D*01
ND
.0900
.9180
1.1000
0521*D*03
ND
ND
.1730
.2090
0521*B*03
ND
ND
.0550
ND
154

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 155 of 194
« AEROSAL.APPL »
Chest Chest Back Back
Record In Left Out Rght In Rght Out Left
I.D. (ug/sq cm) (ug/sq cm) (ug/sq cm) (ug/sq cm)
0456*B*4
ND
.4940
ND
.1650
0456*B*5
ND
.2270
ND
.4470
0456*C*1
ND
.0130
ND
.0200
0456*C*2
ND
ND
ND
.0230
0456*C*3
ND
.0190
ND
.1210
0456*C*4
ND
ND
ND
.0270
0456*C*5
ND
ND
ND
.0280
0521*B*02
ND
ND
ND
ND
0521*D*02
ND
.1310
ND
.0910
0456* A*01
ND
.1310
ND
.1260
0456*A*02
ND
.2610
ND
.0900
0521*A*02
ND
.0850
ND
.2960
0521*C*01
ND
.1370
ND
.2510
0521*A*03
ND
ND
ND
.1440
0521*C*02
ND
.4790
ND
.8440
0521*C*03
ND
.3900
ND
.3480
0521*E*01
ND
.4990
ND
.1640
0521*E*02
ND
.3170
ND
.3170
0521*E*03
ND
.1120
ND
.3090
0521*A*01
ND
4.1820
ND
.1940
0456*A*3
ND
.3880
ND
.3190
0456*A*4
ND
.0340
ND
.3690
0456*A*5
ND
.0190
ND
.0930
0456*B*1
ND
.3710
ND
.4000
0456*B*2
ND
.9100
ND
.3300
0456*B*3
ND
.0950
ND
.2490
0521*B*01
ND
.2610
ND
.1170
0521*D*01
ND
.3560
ND
.1970
0521*D*03
ND
.1400
ND
.1260
0521*B*03
ND
ND
ND
.1440
« AEROSAL.APPL »
Thigh Thigh Thigh Thigh
Record In Rght In Left Out Rght Out Left
I.D. (ug/sq cm) (ug/sq cm) (ug/sq cm) (ug/sq cm)
0456*B*4
ND
ND
.1570
.1650
0456*B*5
ND
ND
.1250
.0780
0456*C*1
ND
ND
ND
ND
0456*C*2
ND
ND
.0150
.0140
0456*C*3
ND
ND
.0240
.0270
0456*C*4
ND
ND
ND
.0210
0456*C*5
ND
ND
ND
ND
0521*B*02
ND
ND
ND
ND
0521*D*02
ND
ND
.0820
ND
0456* A*01
ND
ND
.3070
.1510
0456*A*02
ND
ND
.1560
.0520
0521*A*02
ND
ND
.0850
.0970
0521*C*01
ND
ND
.1430
.1470
0521*A*03
ND
ND
.0450
.0610
0521*C*02
ND
ND
.2410
.3380
0521*C*03
ND
ND
.1300
1.1040
0521*E*01
ND
ND
.1060
.0630
0521*E*02
ND
ND
.0590
.0530
0521*E*03
ND
ND
.0730
.0530
155

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 156 of 194
0521*A*01
ND
ND
.0500
.0670
0456*A*3
ND
ND
.1600
.4260
0456*A*4
ND
ND
.0670
.0800
0456*A*5
ND
ND
.0310
.0440
0456*B*1
ND
ND
.1240
.0490
0456*B*2
ND
ND
.0730
.0610
0456*B*3
ND
ND
.0490
.0450
0521*B*01
ND
ND
.0650
ND
0521*D*01
ND
ND
.1190
.3890
0521*D*03
ND
ND
ND
.0860
0521*B*03
ND
ND
ND
ND
« AEROSAL.APPL »
Shin Shin Shin Shin
Record In Rght In Left Out Rght Out Left
I.D. (ug/sq cm) (ug/sq cm) (ug/sq cm) (ug/sq cm)
0456*B*4
.0170
.0240
.1270
.1270
0456*B*5
ND
ND
.0590
.0400
0456*C*1
ND
ND
.0130
.0140
0456*C*2
ND
ND
.0260
.0440
0456*C*3
ND
ND
.0290
.0380
0456*C*4
ND
ND
ND
.0170
0456*C*5
ND
ND
ND
ND
0521*B*02
ND
ND
.1220
ND
0521*D*02
ND
ND
.0490
ND
0456* A*01
ND
ND
.2060
.0380
0456*A*02
ND
ND
.0800
.0310
0521*A*02
ND
ND
.1220
ND
0521*C*01
ND
ND
1.8640
.0500
0521*A*03
ND
ND
.1120
.2550
0521*C*02
ND
ND
.5360
.2680
0521*C*03
ND
ND
2.8060
.6210
0521*E*01
ND
ND
.0860
.0500
0521*E*02
ND
ND
.0590
.0450
0521*E*03
ND
ND
.0430
ND
0521*A*01
ND
ND
ND
.0690
0456*A*3
ND
.0190
.0110
.1500
0456*A*4
ND
ND
ND
.0200
0456*A*5
ND
ND
.0220
ND
0456*B*1
ND
.0180
.0810
.0250
0456*B*2
ND
ND
.0750
.3130
0456*B*3
ND
ND
.0330
.0400
0521*B*01
ND
ND
ND
.1120
0521*D*01
ND
ND
.1860
.1100
0521*D*03
ND
ND
ND
.1600
0521*B*03
ND
ND
ND
ND
156

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 157 of 194
ACCEPTANCE CRITERIA EVALUATION:
PHED SCENARIO 10: AEROSOL APPLICATION (APPL)

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 158 of 194
Study Code 456: Handheld Aerosols
Task: Evaluate handheld aerosols (specifically study code 456) from the applicator file of the Pesticide Handlers Exposure
Database. The following criteria are reviewed to determine if the study code is complete enough for future use.
1.	Are the dermal grades (covered/uncovered) for all study codes listed as "A" or "B"?	No
2.	Are the airborne grades for all study codes listed as "A" or "B"?	No
3.	Are the hand grades for all study codes listed as "A" or "B"?	No
4.	Is the percentage of non-detect values for all body part depositions less than 40%
when determining whole body exposures?	Total Deposition:
Single Layer Clothing: No
5.	Are the 10 selected body parts (head, neck (front and back), both upper arms,
both forearms, chest, back, upper legs, lower legs, and hands) available
to determine whole body exposures?	Total Deposition/No Normalization
Traditional-	No
Substitution method - Yes
Total Deposition/Normalized by lb ai
handled
Traditional-	No
Substitution method - Yes
Single layer clothing (non protective),
long sleeve/long pants/no glove/no head
protection/
No normalization
Traditional-	No
Substitution method - Yes
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 159 of 194
Single layer clothing (non protective),
long sleeve/long pants/no glove/no head
protection/
Normalized by lb ai handled
Traditional-	No
Substitution method - Yes
Summary:
Number of Replicates:
Range of lbs AI Handled:
Range of inhalation sampling durations:
Range of dermal sampling durations:
Average Dermal LOQ:
Average Inhalation LOQ:
Inhalation Rate/Minute:
Non-Detect Handling:
Hand Protection:
Head Protection:
15
9.40E-03 lbs ai - 9.40E-03 lbs ai
13 minutes - 33 minutes
0.22 hrs - 0.55 hrs
3.02 ug/cm2
10.0 ug
16	L/minute
Half LOQ Values
No
No
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 160 of 194
Section 1: Clothing Layer: Total Deposition
Table 1.1 is a listing of Non-Detect Counts of total deposition. For each column, the number of non-detect values and the
number of replicates with a value is listed.
Head
Neck
(front/
back)
4/15=27%
0/0=NA%
0/0=NA%
Upper
Arms
Right
Left
Chest
Right
Left
Back
Right
Left
1/15=7% 3/15=20%
1/15=7% 0/0=NA%
0/0=NA%
0/15 = 0%
Forearm
s
Right
Left
1/15
=7%
1/15
=7%
Table 1.1. Non-Detect Counts of body part values (total deposition)
Percentage Non-Detects: 21/165 = 13%
Thighs
Right
Left
3/15=20%
2/15=13%
Lower
Legs
shin right
shin left
calf right
calf left
ankle right
ankle left
3/15 =20%
2/15=13%
0/0=NA%
0/0=NA%
0/0=NA%
0/0=NA%
Feet
Hands
0/0=NA% 0/0=NA%
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 161 of 194
1a. No Normalization - Total Deposition
Table 1.2 is a listing of all replicates with a study code of 456. The exposure values are results of no normalization and
total deposition. No replicates had a whole body exposure using the traditional exposure evaluation method. The
Substitution Body Method resulted in all 15 replicates having a whole body exposure value.
Whole
Body
Exposure
Sampl
Replicat e
e Time
(hrs) al Method)
(ug)
Whole
Body
Exposure
Inhalatio
n
Average
Dermal
Average
Hand
/T .... (Substitutio Exposur ~ .... .. Quantificatio
(Tradition v D ,	r Quantification	. . .,
n Body
Method)
e
(ug)
Limit (ug/cm )
n Limit
(ug/cm2)
Dermal Dermal
Airborne Grade Grade
Grade Uncovere Covere
Hand
Grad
e
456-A-3
0.55
7.58e+03
4.07E+0
4
3.0e-02
10
c
c
A
456-A-4
0.50
4.57e+03
2.98E+0
4
3.0e-02
10
c
c
A
456-A-5
0.42
1.76e+03
3.82E+0
4
3.0e-02
10
c
c
A
456-A-1
0.50
8.45e+03
2.59E+0
4
3.0e-02
10
c
c
A
456-A-2
0.47
4.53e+03
3.35E+0
4
3.0e-02
10
c
c
A
456-B-1
0.38
7.09e+03
3.85E+0
4
3.0e-02
10
c
c
A
456-B-2
0.50
1.81e+03
3.30E+0
4
3.0e-02
10
c
c
A
456-B-3
0.52
3.20e+03
2.75E+0
4
3.0e-02
10
c
c
A
456-B-4
0.47
5.61 e+03
4.41 E+0
3.0e-02
10
c
c
A
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 162 of 194
4
456-B-5
0.31
5.90e+03
2.06E+0
4
3.0e-02
10
C
c
A
456-C-1
0.25
343
1.32E+0
4
3.0e-02
10
c
c
A
456-C-2
0.35
449
1.85E+0
4
3.0e-02
10
c
c
A
456-C-3
0.32
1.05e+03
2.11E+0
4
3.0e-02
10
c
c
A
456-C-4
0.43
723
8.92E+0
4
3.0e-02
10
c
c
A
456-C-5
0.22
470
1.20E+0
A
3.0e-02
10
c
c
A
Table 1.2. Exposure values using no normalization and total deposition.
Table 1.3 displays the body parts and their corresponding geometric mean exposure values in ug using the Body Part
Substitution Method.
Head Neck Neck Upper Chest Back Foreai"m	Thiahs	Lower Feet Hands
I IUdU /c t\ /i i \ a /1 l"oL DdUI\	I I IIUI lo	§	I L	I Idl lUo
(front) (back) Arms s	a	Legs
209 11.8 13.0 508 278 420 277	210	97.7	NA 188
Table 1.3. Body parts and corresponding geometric mean exposure values (ug)
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 163 of 194
Figure 1.1 shows a log-log graph of whole body exposures vs. total lbs Al handled, -phis graph is a result of substitution
body part method, no normalization and total deposition. No data exists for the traditional body part method.
100,000 H
PHED Exposures vs Total Lbs Al Handled
^ 10,Mo-
ra
o>
OT
O
a.
X
LU
1,000-;
a
a
9
&
100-
rvrvrrrr	i—rTTrnm	l—frriTfiif"
0.001	0.01	0.1
Total Lbs Al Handled (lb ai}
vrvrvrrrr
i
0.000
Whole Body Exposure vs. Total Lbs Al Handled (not normalized, total deposition)
Figure 1.1
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 164 of 194
1b. Normalized by Lb Al Handled - Total Deposition.
Table 1.4 is a listing of all replicates with a study code of 456. These values are based on normalization by Lbs Al
Handled and total deposition. No replicates had a whole body exposure using the traditional exposure evaluation method.
The Substitution Body Method resulted in all 15 replicates having a whole body exposure value.
Replicate
Sample
Time
(hrs)
Whole
Body
Exposure
(Traditional
Method)
Whole Body
Exposure
(Substitution
Body
Method)
Average	Average
Inhalation Dermal	Hand
Exposure Quantification	Quantification
(ug) Limit	Limit
(ug/cm2)	(ug/cm2)
Airborne
Grade
Dermal Dermal
Grade Grade
Uncovered Covered
Hand
Grade
456-A-3
0.55
8.06e+05
7.87E+06
3.0e-02
10
c
c
A
456-A-4
0.50
4.86e+05
6.34E+06
3.0e-02
10
c
c
A
456-A-5
0.42
1.88e+05
9.74E+06
3.0e-02
10
c
c
A
456-A-1
0.50
8.99e+05
5.51 E+06
3.0e-02
10
c
c
A
456-A-2
0.47
4.82e+05
7.64E+06
3.0e-02
10
c
c
A
456-B-1
0.38
7.54e+05
1.07E+07
3.0e-02
10
c
c
A
456-B-2
0.50
1.93e+06
7.03E+06
3.0e-02
10
c
c
A
456-B-3
0.52
3.40e+05
5.66E+06
3.0e-02
10
c
c
A
456-B-4
0.47
5.97e+05
1.00E+07
3.0e-02
10
c
c
A
456-B-5
0.31
6.27e+05
7.30E+06
3.0e-02
10
c
c
A
456-C-1
0.25
3.65e+04
5.61 E+06
3.0e-02
10
c
c
A
456-C-2
0.35
4.78e+04
5.63E+06
3.0e-02
10
c
c
A
456-C-3
0.32
1.12e+04
7.08E+06
3.0e-02
10
c
c
A
456-C-4
0.43
7.69e+04
2.19E+06
3.0e-02
10
c
c
A
456-C-5
0.22
5.00e+04
5.89E+06
3.0e-02
10
c
c
A
Table 1.4.
Exposure values normalized by lbs Al handled and
total deposition.




Page 164 of 194

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 165 of 194
Table 1.5 displays the body parts and their corresponding geometric mean exposure values in ug using the Body Part
Substitution Method.
Head Neck front	Upper Arms Chest Back Forearm jhjghs Lower pegt Hands
back	s	a	Legs
55®E0 3.13E03 3.47E03 1.36E05 7-4'|E0 H2E05 7.38E04 5.60E04 2.60E04 NA 5.00E04
4	4
Table 1.5. Body parts and corresponding geometric mean exposure values (ug)
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 166 of 194
Figure 1.2 shows a log-log graph of whole body exposures vs. total lbs Al handled, -phis graph is a result of substitution
body part method, normalized by lb ai handled and total deposition. No data exists for the traditional body part method.
10,000,000-3
^ 1.000,000-
ci
Q>
o
Q.
X
LU
100,000^
10,030-
0.000
PHED Exposures vs Total Lbs Al Handled
9
a
a
m
rTTfmrr"
0 001
rnrrrmr
T~l—IT"HTTTTf
0.01
Total Lbs Al Handled (lb ai)
riTirnr
o.i
i
Figure 1.2 Whole Body Exposure vs. Total Lbs Al Handled (normalized, total deposition)
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 167 of 194
Section 2. Clothing Layer: Long Sleeves, Long Pants, No gloves.
Table 2.1 is a listing of Non-Detect Counts with a clothing layer of long sleeves, long pants and no gloves. For each
column, the number of non-detect values and the number of replicates with a value is listed.







Lower









Leas



Neck (front/
back)
Upper Arms
Chest
Back
Forearms
Thiahs
shin right
shin left
calf right
calf left
ankle right
ankle left


Head
Right
Left
Right
Left
Right
Left
Right
Left
Right
Left
Feet
Hands
14/15
15/15=100 =93%
% 12/15=80%
15/15=100 0/0=NA% 0/0=NA% 0/0=NA%
0/	0/0=NA%
0/0=NA%
0/0=NA%
long sleeves, long pants, no gloves)
Percentage Non-Detects: 179/195 = 92%
Page 167 of 194
15/15100	o/o=NA%	15/15=100	14/15=93%
4/15=27% ' ; wic-inn	15/15=100	%	15/15=100
15/15-1°% 15/15-100 %	0/Q = NA	%
/O
Table 2.1. Non-Detect Counts of body part values (permeable layer clothing -

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 168 of 194
2a. No Normalization - Permeable Clothing
Table 2.2 is a listing of all replicates with a study code of 456. The exposure values are results of no normalization with
permeable clothing - long pants, long sleeves and no gloves. No replicates had a whole body exposure using the
traditional exposure evaluation method. The Substitution Body Method resulted in all 15 replicates having a whole body
exposure value.
Replicate
Sample
Time
(hrs)
Whole
Body
Exposure
(Traditional
Method)
Whole Body
Exposure
(Substitution
Body
Method)
Inhalation
Exposure
(ug)
Average
Dermal
Quantification
Limit
(ug/cm2)
Average
Hand
Quantification
Limit
(ug/cm2)
Airborne
Grade
Dermal
Grade
Uncovered
Dermal
Grade
Covered
Hand
Grade
456-A-3
0.55
1.51e+03
4.07E+04
3.0e-02
10
C
c
A
456-A-4
0.50
761
2.98E+04
3.0e-02
10
C
c
A
456-A-5
0.42
552
3.82E+04
3.0e-02
10
c
c
A
456-A-1
0.50
1,23e+03
2.59E+04
3.0e-02
10
c
c
A
456-A-2
0.47
1,20e+03
3.35E+04
3.0e-02
10
c
c
A
456-B-1
0.38
630
3.85E+04
3.0e-02
10
c
c
A
456-B-2
0.50
1.55e+03
3.30E+04
3.0e-02
10
c
c
A
456-B-3
0.52
590
2.75E+04
3.0e-02
10
c
c
A
456-B-4
0.47
713
4.41 E+04
3.0e-02
10
c
c
A
456-B-5
0.31
913
2.06E+04
3.0e-02
10
c
c
A
456-C-1
0.25
297
1.32E+04
3.0e-02
10
c
c
A
456-C-2
0.35
302
1.85E+04
3.0e-02
10
c
c
A
456-C-3
0.32
578
2.11 E+04
3.0e-02
10
c
c
A
456-C-4
0.43
298
8.92E+04
3.0e-02
10
c
c
A
456-C-5
0.22
298
1.20E+04
3.0e-02
10
c
c
A
Table 2.2.
Exposure values using no normalization with permeable clothing -
long sleeves, long pants, no gloves.

Page 168 of 194

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 169 of 194
Table 2.3 displays the body parts and their corresponding geometric mean exposure values in ug using the Body Part
Substitution Method.
Head Neck front	Upper Arms Chest Back Forearm jhjghs Lower pegt Hands
back	s	a	Legs
209	11.8	13.0	43.7	53.2 53.2	18.3 573	37.0 NA 12.4
Table 2.3. Body parts and corresponding geometric mean exposure values (ug)
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 170 of 194
Figure 2.1 shows a log-log graph of whole body exposures vs. total lbs Al handled, -phis graph is a result of substitution
body part method, no normalization with permeable layer clothing consisting of long sleeves, long pants and no gloves.
No data exists for the traditional body part method.
10.000-
PHED Exposures vs Total Lbs Al Handled

¦
0



1
a


a
=
a>
cn
o
a.
K
LU
1.000-
100-
0.000
0.001
0.01
0.1
Total Lbs Al Handled (lb ai)
Figure 2.1 Whole Body Exposure vs. Total Lbs Al Handled (not normalized, permeable single layer clothing - long
sleeves, long pants, no gloves)
Page 170 of 194

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 171 of 194
2b. Normalized by Lb Al Handled - Permeable Clothing.
Table 2.4 is a listing of all replicates with a study code of 456. These values are based on normalization by Lbs Al
Handled with permeable single layer clothing (long sleeves, long pants, no gloves). n0 replicates had a whole body
exposure using the traditional exposure evaluation method. The Substitution Body Method resulted in all 15 replicates
having a whole body exposure value.
Replicate
Sample
Time
(hrs)
Whole
Body
Exposure
(Traditional
Method)
Whole Body
Exposure
(Substitution
Body
Method)
Average	Average
Inhalation Dermal	Hand
Exposure Quantification	Quantification
(ug) Limit	Limit
(ug/cm2)	(ug/cm2)
Airborne
Grade
Dermal Dermal
Grade Grade
Uncovered Covered
Hand
Grade
456-A-3
0.55
-
1.61e+05
7.87E+06
3.0e-02
10
c
c
A
456-A-4
0.50
-
8.10e+04
6.34E+06
3.0e-02
10
c
c
A
456-A-5
0.42
-
5.87e+04
9.74E+06
3.0e-02
10
c
c
A
456-A-1
0.50
-
1.31e+04
5.51 E+06
3.0e-02
10
c
c
A
456-A-2
0.47
-
1,28e+04
7.64E+06
3.0e-02
10
c
c
A
456-B-1
0.38
-
6.71 e+04
1.07E+07
3.0e-02
10
c
c
A
456-B-2
0.50
-
1,65e+05
7.03E+06
3.0e-02
10
c
c
A
456-B-3
0.52
-
6.27e+04
5.66E+06
3.0e-02
10
c
c
A
456-B-4
0.47
-
7.59e+04
1.00E+07
3.0e-02
10
c
c
A
456-B-5
0.31
-
9.72e+04
7.30E+06
3.0e-02
10
c
c
A
456-C-1
0.25
-
3.16e+04
5.61 E+06
3.0e-02
10
c
c
A
456-C-2
0.35
-
3.21 e+04
5.63E+06
3.0e-02
10
c
c
A
456-C-3
0.32
-
6.15e+04
7.08E+06
3.0e-02
10
c
c
A
456-C-4
0.43
-
3.17e+04
2.19E+06
3.0e-02
10
c
c
A
456-C-5
0.22
-
3.17e+04
5.89E+06
3.0e-02
10
c
c
A
Table 2.4. Exposure values normalized by lbs Al handled with permeable clothing - long sleeves, long pants, no gloves.
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 172 of 194
Table 2.5 displays the body parts and their corresponding geometric mean exposure values in ug using the Body Part
Substitution Method.
Head Neck front	Upper Arms Chest Back Forearm jhjghs Lower pegt Hands
back	s	a	Legs
55®E0 3.13E03 3.47E03 1.16E04 1-42E0 1 42E04 4.88E03 1-53E04 9.86E03 NA 3.31 E03
4	4
Table 2.5. Body parts and corresponding geometric mean exposure values (ug)
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 173 of 194
Figure 2.2 shows a log-log graph of whole body exposures vs. total lbs Al handled, -phis graph is a result of substitution
body part method, normalized by lb ai handled with permeable layer clothing - long sleeves, long pants, no gloves. No
data exists for the traditional body part method.
I.OM.OOO-d
OS
Q>
i_
3
ft
D
Q.
x
LU
100,000-
10,000-
0.000
PHED Exposures vs Total Lbs Al Handled
9
3
a
1
TTTTrmr-
0.001
'fYTiTvrrrr	vrvrvrrni-
0.01	0.1
Total Lbs Al Handled (lb ai}
1~~|—TTTTTTTT
Figure 2.2 Whole Body Exposure vs. Total Lbs Al Handled (normalized, permeable single layer clothing - long sleeves,
long shirt, no gloves)
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 174 of 194
Attachment A: Body Part Substitutions.
Table A.1 shows a listing of the 10 body parts inspected and the list of possible body part substitutions if no deposition
was recorded. There are 2 methods described. The traditional body part method is used in the DOS version of PHED
while the body part substitution method is an alternative used for a possible web based version of PHED:
Body Part
Traditional PHED Substitution
Body Part Substitution Method
Head
Back, Chest Shoulders
Neck (front and back)
Neck (front)
Chest
Shoulders, Upper Arms, Head
Neck (back)
Back
Shoulders, Upper Arms, Head
Upper Arms
None
Back, Chest;


If no results, Forearms
Forearms
None
Chest, Upper Arms, Back


If no results: Shoulders
Chest
None
Shoulder, Upper arm, Neck (front)


If no results: Head
Back
None
Shoulders, Upper Arms, Neck (back)


If no results: Head
Thighs
None
Shin, Calf
Lower Legs
None
Hip, Thigh
Hands
None
Forearms
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 175 of 194
Draft - Do not cite or quote
Study Code 521: Handheld Aerosols
Task: Evaluate handheld aerosols (specifically study code 521) from the applicator file of the Pesticide Handlers Exposure
Database. The following criteria are reviewed to determine if the study code is complete enough for future use.
1.	Are the dermal grades (covered/uncovered) for all study codes listed as "A" or "B"?	Yes
2.	Are the airborne grades for all study codes listed as "A" or "B"?	Yes
3.	Are the hand grades for all study codes listed as "A" or "B"?
4.	Is the percentage of non-detect values for all body part depositions less than 40%
when determining whole body exposures?	Total Deposition:
Single Layer Clothing: No
5.	Are the 10 selected body parts (head, neck (front and back), both upper arms,
both forearms, chest, back, upper legs, lower legs, and hands) available
to determine whole body exposures?	Total Deposition/No Normalization
Traditional-	Yes
Substitution method -	Yes
Total Deposition/Normalized by lb ai
handled
Traditional -
Substitution method -	Yes
Single layer clothing (non protective),
long sleeve/long pants/no glove/no head
protection/ yes
No normalization
Traditional -
Substitution method - Yes
Page 175 of 194
Yes

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Summary:
Number of Replicates:	15
Range of lbs Al Handled:	0.01 lbs ai - 0.01 lbs ai
Range of inhalation sampling durations:	18 minutes - 36 minutes
Range of dermal sampling durations: 0.30 hrs - 0.60 hrs
Average Dermal LOQ:	4.06e-02 ug/cm2
Average Inhalation LOQ:	1.00 ug
Average Hand LOQ: 100 ug/cm2
Inhalation Rate/Minute:	16 L/minute
Non-Detect Handling:	Half LOQ Values
Hand Protection:
No
Page 176 of 194
Page 176 of 194
Single layer clothing (non protective),
long sleeve/long pants/no glove/no head
protection/
Normalized by lb ai handled
Traditional -
Substitution method - Yes
Yes

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 177 of 194
Section 1: Clothing Layer: Total Deposition
Table 1.1 is a listing of Non-Detect Counts of total deposition. For each column, the number of non-detect values and the
number of replicates with a value is listed.
Head
Neck (front/
back)
Upper
Arms
Right
Left
Chest
Right
Left
Back
Right
Left
Forearms
Right
Left
Thighs
Right
Left
1/15=7%
15/15=100
%
15/15=100
%
0/15=0%
2/15=13%
3/15=20%
0/0=NA%
0/0=NA%
0/15 = 0%
2/15
=13%
2/15
=13%
3/15=20%
4/15=27%
Table 1.1. Non-Detect Counts of body part values (total deposition)
Lower
Legs
shin right
shin left
calf right
calf left
ankle right
ankle left
4/15 =27%
5/15=33%
0/0=NA%
0/0=NA%
0/0=NA%
0/0=NA%
Feet
Hands
Right
Left
Both
0/0=NA%
0/0=NA%
0/0=NA%
0/15=0%
Percentage Non-Detects: 56/210 = 27%
Page 177 of 194

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 178 of 194
1a. No Normalization - Total Deposition
Table 1.2 is a listing of all replicates with a study code of 521. The exposure values are results of no normalization and
total deposition. No replicates had a whole body exposure using the traditional exposure evaluation method. The
Substitution Body Method resulted in all 15 replicates having a whole body exposure value.
Whole
Body
Exposure
Sampl
Replicat e
e Time
(hrs) al Method)
(ug)
Whole
Body
Exposure
Inhalatio
n
Average
Dermal
Average
Hand
/T .... (Substitutio Exposur ~ .... .. Quantificatio
(Tradition v D ,	r Quantification	. . .,
n Body
Method)
e
(ug)
Limit (ug/cm )
n Limit
(ug/cm2)
Dermal Dermal
Airborne Grade Grade
Grade Uncovere Covere
Hand
Grad
e
521-A-1
0.47
2.18E+04
N/A
7.34E+0
3
4.06E-02
100
A
A
A
521-A-2
0.55
6.57E+03
N/A
6.78E+0
3
4.06E-02
100
A
A
A
521-A-3
0.52
3.65E+03
N/A
7.02E+0
3
4.06E-02
100
A
A
A
521-B-1
0.45
4.88E+03
N/A
7.34E+0
3
4.06E-02
100
A
A
A
521-B-2
0.47
4.59E+03
N/A
6.78E+0
3
4.06E-02
100
A
A
A
521-B-3
0.30
1.99E+03
N/A
7.02E+0
3
4.06E-02
100
A
A
A
521-C-1
0.53
8.15E+03
N/A
7.34E+0
3
4.06E-02
100
A
A
A
521-C-2
0.45
1.14E+04
N/A
2.19E+0
4
4.06E-02
100
A
A
A
521-C-3
0.53
1.72E+04
N/A
7.02E+0
4.06E-02
100
A
A
A
Page 178 of 194

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 179 of 194
521-D-1
0.43
1.02E+04
N/A
2.35E+0
4
4.06E-02
100
A
A
A
521-D-2
0.32
5.21 E+03
N/A
6.78E+0
3
4.06E-02
100
A
A
A
521-D-3
0.37
3.84E+03
N/A
7.02E+0
3
4.06E-02
100
A
A
A
521-E-1
0.52
6.83E+03
N/A
2.00E+0
4
4.06E-02
100
A
A
A
521-E-2
0.53
6.17E+03
N/A
6.78E+0
3
4.06E-02
100
A
A
A
521-E-3
0.60
4.10E+03
N/A
7.02E+0
Q
4.06E-02
100
A
A
A
Table 1.2. Exposure values using no normalization and total deposition.
Table 1.3 displays the body parts and their corresponding geometric mean exposure values in ug.
Head Neck front back Upper Arms Chest Back Forearm jhjghs
410	25.1	20.0	999	595 644	488 300
Table 1.3. Body parts and corresponding geometric mean exposure values (ug)
Lower
Legs
248
Feet Hands
NA 1.06E+03
Page 179 of 194

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 180 of 194
Figure 1.1 shows a log-log graph of whole body exposures vs. total lbs Al handled. This graph is a result of no
normalization and total deposition.
100.000
Q)
[fl
o
c.
x
LU
10.000
1.OD0
PHED Exposures vs Total Lbs Al Handled
0.000
Total Lbs Al Handled (lb ai
Figure 1.1
Whole Body Exposure vs. Total Lbs Al Handled (not normalized, total deposition)
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 181 of 194
1b. Normalized by Lb Al Handled - Total Deposition.
Table 1.4 is a listing of all replicates with a study code of 521. These values are based on normalization by Lbs Al
Handled and total deposition.
Whole Whole Body	A	A
R .	F	3	Average Average
Sample	0 ^	/c :T°^u,re	Inhalation Dermal Hand	...	Dermal	Dermal	,
„ .. . -r.	Exposure	(Substitution	~ ..	~ ..	Airborne	~	~ , Hand
Replicate Time	r.... ,	„ ,	Exposure	Quantification	Quantification	~ ,	Grade	Grade ~ ,
r \	(Traditional	Body	, > .... ....	Grade	..	,	^ , Grade
	Method)	Method)	 , L;ml' , , L!m",,	Uncovered	Covered
(ug)	(ug)	(iig/cm2) (ug/cm2)
521-A-1
0.47
2.18E+06
N/A
7.34E+05
4.06E-02
100
A
A
A
521-A-2
0.55
6.57E+05
N/A
6.78E+05
4.06E-02
100
A
A
A
521-A-3
0.52
3.65E+05
N/A
7.02E+05
4.06E-02
100
A
A
A
521-B-1
0.45
4.88E+05
N/A
7.34E+05
4.06E-02
100
A
A
A
521-B-2
0.47
4.59E+05
N/A
6.78E+05
4.06E-02
100
A
A
A
521-B-3
0.30
1.99E+05
N/A
7.02E+05
4.06E-02
100
A
A
A
521-C-1
0.53
8.15E+05
N/A
7.34E+05
4.06E-02
100
A
A
A
521-C-2
0.45
1.14E+06
N/A
2.19E+06
4.06E-02
100
A
A
A
521 -C-3
0.53
1.72E+06
N/A
7.02E+05
4.06E-02
100
A
A
A
521-D-1
0.43
1.02E+06
N/A
2.35E+06
4.06E-02
100
A
A
A
521-D-2
0.32
5.21 E+05
N/A
6.78E+05
4.06E-02
100
A
A
A
521-D-3
0.37
3.84E+05
N/A
7.02E+05
4.06E-02
100
A
A
A
521-E-1
0.52
6.83E+05
N/A
2.00E+06
4.06E-02
100
A
A
A
521-E-2
0.53
6.17E+05
N/A
6.78E+05
4.06E-02
100
A
A
A
521-E-3
0.60
4.10E+05
N/A
7.02E+05
4.06E-02
100
A
A
A
Table 1.4. Exposure values normalized by lbs Al handled and total deposition.
Page 181 of 194

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 182 of 194
Table 1.5 displays the body parts and their corresponding geometric mean exposure values in ug.
Head Neck front
Neck
back
Upper
Arms
4.10E+0
4
2.51 E+03 2.00E+03 9.99E+04
Chest
5.95E+0
Back
6.44E+04
Forearm
s
4.88E+0
Thighs
3.00E+0
4	4
Table 1.5. Body parts and corresponding geometric mean exposure values (ug)
Lower
Legs
2.48E+04
Feet Hands
NA 1.06E+05
Page 182 of 194

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 183 of 194
Figure 1.2 shows a log-log graph of whole body exposures vs. total lbs Al handled.
10,000,000-

m
iS>
D
a.
K
LU
1,000,000-
100,003 -
o.ooo
PHED Exposures vs Total Lbs Al Handled
"i—rvvYnnr
o.ooi
—i—i—r-rrvrriT^
0.1
Total Lbs Al Handled (lb ai)
Figure 1.2 Whole Body Exposure vs. Total Lbs Al Handled (normalized, total deposition)
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 184 of 194
Section 2. Clothing Layer: Long Sleeves, Long Pants, No gloves.
Table 2.1 is a listing of Non-Detect Counts with a clothing layer of long sleeves, long pants and no gloves. For each
column, the number of non-detect values and the number of replicates with a value is listed.







Lower Leas









shin right

Hands

Neck (front/
back)
Upper Arms
Chest
Back
Forearms
Thiahs
shin left

Right
Left
Both
Head
Right
Right
Right
Right
Right
calf right
Feet

Left
Left
Left
Left
Left
calf left








ankle right








ankle left


1/15=7%
15/15=100%
15/15=100%
15/15=100
%
15/15=100
%
0/0=NA%
15/15=100
%
15/15=100
%
0/0 = NA
15/15
=100%
14/15=93%
15/15=100
%
15/15=100
%
15/15
=100%
15/15=100
%
0/0=NA%
0/0=NA%
0/0=NA%
0/0=NA%
0/0=NA%
0/15=0%
0/0=NA%
0/0=NA%
Table 2.1. Non-Detect Counts of body part values (permeable layer clothing - long sleeves, long pants, no gloves)
Percentage Non-Detects: 180/210 = 86%
Page 184 of 194

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 185 of 194
2a. No Normalization - Permeable Clothing
Table 2.2 is a listing of all replicates with a study code of 521. The exposure values are results of no normalization with
permeable clothing - long pants, long sleeves and no gloves.
Replicate
521-A-1
521-A-2
521-A-3
521-B-1
521-B-2
521-B-3
521-C-1
521-C-2
521-C-3
521-D-1
521-D-2
521-D-3
521-E-1
521-E-2
521-E-3
Table 2.2.
Sample
Time
(hrs)
0.47
0.55
0.52
0.45
0.47
0.30
0.53
0.45
0.53
0.43
0.32
0.37
0.52
0.53
0.60
Exposure
Whole
Body
Exposure
(Traditional
Method)
(ug)
2.13E+03
2.26E+03
1.61 E+03
1.98E+03
4.24E+03
1.35E+03
2.79E+03
1.91 E+03
4.95E+03
2.78E+03
1.59E+03
2.07E+03
2.40E+03
1.54E+03
1.84E+03
values using
Whole Body
Exposure
(Substitution
Body
Method)
(ug)
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Inhalation
Exposure
(ug)
7.34E+03
6.78E+03
7.02E+03
7.34E+03
6.78E+03
7.02E+03
7.34E+03
2.19E+04
7.02E+03
2.35E+04
6.78E+03
7.02E+03
2.00E+04
6.78E+03
7.02E+03
Average
Dermal
Quantification
Limit
(ug/cm2)
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
Average
Hand
Quantification
Limit
(ug/cm2)
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Airborne
Grade
Dermal Dermal
Grade Grade
Uncovered Covered
Hand
Grade
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
no normalization with permeable clothing - long sleeves, long pants, no gloves.
Page 185 of 194

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 186 of 194
Table 2.3 displays the body parts and their corresponding geometric mean exposure values in ug.
Head Neck front ^eC,'< Upper Arms Chest Back Forearm jhjghs Lower pegt Hands
back	s	a	Legs
410	25.1	20.0	59.1	72.1 72.1	26.3 775	48.3	1.09E+03
Table 2.3. Body parts and corresponding geometric mean exposure values (ug)
Page 186 of 194

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 187 of 194
Figure 2.1 shows a log-log graph of whole body exposures vs. total lbs Al handled, -phis graph is a result of the traditional
body part method, no normalization with permeable layer clothing consisting of long sleeves, long pants and no gloves.
PHED Exposures vs Total Lbs Al Handled
IO.vXW-






&


&



a



§

a
i i
i i
i i
i i
=
a)
w
o
a.
K
LU
1,000-
o.ooo
0.001
0.01
Total Lbs Al Handled (lb ai)
T
0.1
Figure 2.1 Whole Body Exposure vs. Total Lbs Al Handled (not normalized, permeable single layer clothing - long
sleeves, long pants, no gloves)
Page 187 of 194

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 188 of 194
2b. Normalized by Lb Al Handled - Permeable Clothing.
Table 2.4 is a listing of all replicates with a study code of 521. These values are based on normalization by Lbs Al
Handled with permeable single layer clothing (long sleeves, long pants, no gloves).
Replicate
521-A-1
521-A-2
521-A-3
521-B-1
521-B-2
521-B-3
521-C-1
521-C-2
521-C-3
521-D-1
521-D-2
521-D-3
521-E-1
521-E-2
521-E-3
Table 2.4.
Sample
Time
(hrs)
0.47
0.55
0.52
0.45
0.47
0.30
0.53
0.45
0.53
0.43
0.32
0.37
0.52
0.53
0.60
Exposure
Whole
Body
Exposure
(Traditional
Method)
(ug)
2.13E+05
2.26E+05
1.61 E+05
1.98E+05
4.24E+05
1.35E+05
2.79E+05
1.91 E+05
4.95E+05
2.78E+05
1.59E+05
2.07E+05
2.40E+05
1.54E+05
1.84E+05
Whole Body
Exposure
(Substitution
Body
Method)
(ug)
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
N/A
Average	Average
Inhalation Dermal	Hand
Exposure Quantification	Quantification
(ug) Limit	Limit
(ug/cm2)	(ug/cm2)
7.34E+05
6.78E+05
7.02E+05
7.34E+05
6.78E+05
7.02E+05
7.34E+05
2.19E+06
7.02E+05
2.35E+06
6.78E+05
7.02E+05
2.00E+05
6.78E+05
7.02E+05
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
4.06E-02
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
Airborne
Grade
Dermal Dermal
Grade Grade
Uncovered Covered
Hand
Grade
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
A
values normalized by lbs Al handled with permeable clothing - long sleeves, long pants, no gloves.
Page 188 of 194

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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 189 of 194
Table 2.5 displays the body parts and their corresponding geometric mean exposure values in ug.
Head Neck front hGC^ Upper Qhest Back Forearm jhjghs Lower pegt Hands
back	Arms	s	a	Legs
7 91F+0	9 fi^F+n 7.75E+0
4.10E+04 2.51 E+03 2.00E+03 5.91 E+03 ^ 7.21 E+03 ^	3 4.83E+03 NA 1.06E+05
Table 2.5. Body parts and corresponding geometric mean exposure values (ug)
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 190 of 194
Figure 2.2 shows a log-log graph of whole body exposures vs. total lbs Al handled, -phis graph is a result of the traditional
method, normalized by lb ai handled with permeable layer clothing - long sleeves, long pants, no gloves.
PHED Exposures vs Total Lbs Al Handled
1,000,000-
01
m
iS>
D
a.
K
LU
100,000-





£
p

1
1
P

1
1 1
1
i


?
1


a
i
¦
i
i

0.000
T
0.001
0.01
0.1
Total Lbs Al Handled (lb ai)
Figure 2.2 Whole Body Exposure vs. Total Lbs Al Handled (normalized, permeable single layer clothing - long sleeves,
long shirt, no gloves)
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 191 of 194
Attachment A: Body Part Substitutions.
Table A.1 shows a listing of the 10 body parts inspected and the list of possible body part substitutions if no deposition
was recorded. There are 2 methods described. The traditional body part method is used in the DOS version of PHED
while the body part substitution method is an alternative used for a possible web based version of PHED:
Body Part
Traditional PHED Substitution
Body Part Substitution Method
Head
Back, Chest Shoulders
Neck (front and back)
Neck (front)
Chest
Shoulders, Upper Arms, Head
Neck (back)
Back
Shoulders, Upper Arms, Head
Upper Arms
None
Back, Chest;


If no results, Forearms
Forearms
None
Chest, Upper Arms, Back


If no results: Shoulders
Chest
None
Shoulder, Upper arm, Neck (front)


If no results: Head
Back
None
Shoulders, Upper Arms, Neck (back)


If no results: Head
Thighs
None
Shin, Calf
Lower Legs
None
Hip, Thigh
Hands
None
Forearms
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 192 of 194
Appendix G: List of Current AEATF II Standard
Operating Procedures (SOPs)
Chapter 1 - Administration
AEATF 11-1 AO
AEATF 11-1 B.O
AEATF 11-1 C.O
AEATF 11-1 D.O
Organizational Structure
Personnel Responsibilities
Study Director Selection
Inspection of AEATF II Facilities/Data
Chapter 2 - Protocols
AEATF II-2A.0
AEATF II-2B.0
AEATF II-2C.0
Study Authorization and Approval
Study Number Assignment
Protocols
Chapter 3 - Standard Operating Procedures
AEATF II-3A.0
AEATF II-3B.0
SOP Preparation, Approval, Maintenance, and Distribution
Use of AEATF II and Contractor SOPs
Chapter 4 - Study Reports
AEATF II-4A.0
AEATF II-4B.0
Study Report Preparation
Final Report Issue
Chapter 5 - Quality Assurance Unit
AEATF II-5A.0	QA Personnel Administration
AEATF II-5B.0	AEATF II QAU Responsibilities
AEATF II-5C.0	QAU Records
AEATF II-5D.0	QA Master Schedule
AEATF II-5E.0	Protocol and Amendment Review
AEATF II-5F.0	Inspection/Audit Types and Frequency
AEATF II-5G.0	Study Inspections
AEATF II-5H.0	Data Audits
AEATF II-5I.0	Facility Inspections
AEATF II-5J.0	Report Audits
AEATF II-5K.0	Inspection Report Distribution
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program	Page 193 of 194
Chapter 6 - Archives
AEATF II-6A.0 Storage of Raw Data
AEATF II-6B.0 Access to Archived Data
AEATF II-6C.0 Specimen and Wet Sample Storage
Chapter 7 - Test, Control and Reference Substance
AEATF II-7A.0
AEATF II-7B.0
AEATF II-7C.0
AEATF II-7D.0
AEATF II-7E.0
Test, Reference, and Control Substance Receipt and
Shipment
Test, Control and Reference Substance Labeling
Disposal of Test, Control, and Reference Substances
Test, Control, and Reference Substance Chain of Custody
Test and Reference Substance Analyses
Chapter 8 - Matrix Samples
AEATF II-8A.1	Whole Body Sampling - Inner Dosimeters
AEATF II-8B.1	Hand Wash Samples
AEATF II-8C.1	Dermal Face/Neck Wipe Samples
AEATF II-8D.0	Collection of Air Samples Using OVS Tubes
AEATF II-8E.0	Fortification of Matrix Samples
AEATF II-8F.0	Sample Identification
AEATF II-8G.1	Whole Body Sampling - Outer Dosimeters
Chapter 9 - Documentation
AEATF II-9A.0	Body Surface Areas
AEATF II-9B.1	Field Fortification Adjustment Factors
AEATF II-9C.0	Numerical Formatting and Handling
AEATF II-9D.0	Analytical Method Number Assignment
AEATF II-9E.0	Raw Data Collection
AEATF II-9F.0	Data Corrections
AEATF II-9G.0	Raw Data Handling
AEATF II-9H.0	Preparation of True Copies
Chapter 10 - Field Study Procedures
AEATF II-10A.0	Rotameter Calibration
AEATF 11-1 OB.0	Packing, Handling, and Shipping of Samples
AEATF 11-1 OC.O	Worker and Study Observations
AEATF 11-1 OD.O	Application Equipment Operation Verification
AEATF 11-1 OE.O	Worker Sample Collection Sequence
AEATF 11-1 OF.0	GPI Electronic Digital Flow Meter
AEATF 11-1 OG.O	Personal Air Sampling Pump Calibration
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AEATF II Vol. 5 Governing Document for a Multi-Year Antimicrobial Chemical Exposure Monitoring Program
Page 194 of 194
Chapter 11 - Human Subject Management
AEATF 11-11A.0 - Pregnancy Testing
AEATF 11-11 B.O - Heat Stress
AEATF 11-11C.0 - Emergency Procedures
AEATF 11-11D.0 - Reportable Findings
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