TABLE OF CONTENTS Page No.

2. VARIABILITY AND UNCERTAINTY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2.1. VARIABILITY VERSUS UNCERTAINTY . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2.2. TYPES OF VARIABILITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 2.3. CONFRONTING VARIABILITY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.4. CONCERN ABOUT UNCERTAINTY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2.5. TYPES OF UNCERTAINTY AND REDUCING UNCERTAINTY . . . . . . . . . 4 2.6. ANALYZING VARIABILITY AND UNCERTAINTY . . . . . . . . . . . . . . . . . . . 4 2.7. PRESENTING RESULTS OF VARIABILITY AND UNCERTAINTY ANALYSIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 2.8. REFERENCES FOR CHAPTER 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 ADD pot ' Contaminant Concentration x Intake Rate x Exposure Duration Body Weight x Averaging Time Volume I  General Factors Chapter 2  Variability and Uncertainty Exposure Factors Handbook Page August 1997 2 1 ( Eqn. 2 1) 2. VARIABILITY AND UNCERTAINTY The chapters that follow will discuss exposure process of conducting risk assessments; because exposure factors and algorithms for estimating exposure. Exposure assessment is a component of risk assessment process, the factor values can be used to obtain a range of exposure general concepts apply equally to the exposure assessment estimates such as average, high end and bounding component. estimates. It is instructive here to return to the general equation for potential Average Daily Dose ( ADD ) that pot was introduced in the opening chapter of this handbook: While some authors have treated variability as a With the exception of the contaminant concentration, affecting exposure or risk, whereas variability arises from all parameters in the above equation are considered true heterogeneity across people, places or time. In other exposure factors and, thus, are treated in fair detail in other words, uncertainty can lead to inaccurate or biased chapters of this handbook. Each of the exposure factors estimates, whereas variability can affect the precision of the involves humans, either in terms of their characteristics estimates and the degree to which they can be generalized. ( e. g., body weight) or behaviors ( e. g., amount of time spent Most of the data presented in this handbook concerns in a specific location, which affects exposure duration). variability. While the topics of variability and uncertainty apply equally Variability and uncertainty can complement or to contaminant concentrations and the rest of the exposure confound one another. An instructive analogy has been factors in equation 2 1, the focus of this chapter is on drawn by the National Research Council ( NRC, 1994: variability and uncertainty as they relate to exposure factors. Chapter 10), based on the objective of estimating the Consequently, examples provided in this chapter relate distance between the earth and the moon. Prior to fairly primarily to exposure factors, although contaminant recent technology developments, it was difficult to make concentrations may be used when they better illustrate the accurate measurements of this distance, resulting in point under discussion. measurement uncertainty. Because the moon's orbit is This chapter also is intended to acquaint the elliptical, the distance is a variable quantity. If only a few exposure assessor with some of the fundamental concepts measurements were to be taken without knowledge of the and precepts related to variability and uncertainty, together elliptical pattern, then either of the following incorrect with methods and considerations for evaluating and conclusions might be reached: presenting the uncertainty associated with exposure estimates. Subsequent sections in this chapter are devoted ° That the measurements were faulty, thereby to the following topics: ascribing to uncertainty what was actually ° Distinction between variability and ° That the moon's orbit was random, thereby not uncertainty; allowing uncertainty to shed light on seemingly ° Types of variability; unexplainable differences that are in fact C Methods of confronting variability; variable and predictable. ° Types of uncertainty and reducing uncertainty; ° Analysis of variability and uncertainty; and A more fundamental error in the above situation ° Presenting results of variability/ uncertainty would be to incorrectly estimate the true distance, by analysis. assuming that a few observations were sufficient. This Fairly extensive treatises on the topic of uncertainty were invariant or only uncertain  is probably the most have been provided, for example, by Morgan and Henrion relevant to the exposure or risk assessor. ( 1990), the National Research Council ( NRC, 1994) and, Now consider a situation that relates to exposure, to a lesser extent, the U. S. EPA ( 1992; 1995). The topic such as estimating the average daily dose by one exposure commonly has been treated as it relates to the overall 2.1. VARIABILITY VERSUS UNCERTAINTY specific type or component of uncertainty, the U. S. EPA ( 1995) has advised the risk assessor ( and, by analogy, the exposure assessor) to distinguish between variability and uncertainty. Uncertainty represents a lack of knowledge about factors caused by variability; or latter pitfall  treating a highly variable quantity as if it Volume I  General Factors Chapter 2  Variability and Uncertainty Page Exposure Factors Handbook 2 2 August 1997 route  ingestion of contaminated drinking water. Suppose location might vary in response to weather conditions, or that it is possible to measure an individual's daily water between weekdays and weekends. consumption ( and concentration of the contaminant) At a more fundamental level, three types of exactly, thereby eliminating uncertainty in the measured variability can be distinguished: daily dose. The daily dose still has an inherent day to day variability, however, due to changes in the individual's daily ° Variability across locations ( Spatial water intake or the contaminant concentration in water. Variability); It is impractical to measure the individual's dose ° Variability over time ( Temporal Variability); every day. For this reason, the exposure assessor may and estimate the average daily dose ( ADD) based on a finite ° Variability among individuals ( Internumber of measurements, in an attempt to " average out" the individual Variability). day to day variability. The individual has a true ( but unknown) ADD, which has now been estimated based on a sample of measurements. Because the individual's true average is unknown, it is uncertain how close the estimate is to the true value. Thus, the variability across daily doses has been translated into uncertainty in the ADD. Although the individual's true ADD has no variability, the estimate of the ADD has some uncertainty. The above discussion pertains to the ADD for one person. Now consider a distribution of ADDs across individuals in a defined population ( e. g., the general U. S. population). In this case, variability refers to the range and distribution of ADDs across individuals in the population. By comparison, uncertainty refers to the exposure assessor's state of knowledge about that distribution, or about parameters describing the distribution ( e. g., mean, standard deviation, general shape, various percentiles). As noted by the National Research Council ( NRC, 1994), the realms of variability and uncertainty have fundamentally different ramifications for science and judgment. For example, uncertainty may force decisionmakers to judge how probable it is that exposures have been overestimated or underestimated for every member of the exposed population, whereas variability forces them to cope with the certainty that different individuals are subject to exposures both above and below any of the exposure levels chosen as a reference point.

2.2. TYPES OF VARIABILITY Variability in exposure is related to an individual's location, activity, and behavior or preferences at a particular point in time, as well as pollutant emission rates and physical/ chemical processes that affect concentrations in various media ( e. g., air, soil, food and water). The variations in pollutant specific emissions or processes, and in individual locations, activities or behaviors, are not necessarily independent of one another. For example, both personal activities and pollutant concentrations at a specific Spatial variability can occur both at regional ( macroscale) and local ( microscale) levels. For example, fish intake rates can vary depending on the region of the country. Higher consumption may occur among populations located near large bodies of water such as the Great Lakes or coastal areas. As another example, outdoor pollutant levels can be affected at the regional level by industrial activities and at the local level by activities of individuals. In general, higher exposures tend to be associated with closer proximity to the pollutant source, whether it be an industrial plant or related to a personal activity such as showering or gardening. In the context of exposure to airborne pollutants, the concept of a " microenvironment" has been introduced ( Duan, 1982) to denote a specific locality ( e. g., a residential lot or a room in a specific building) where the airborne concentration can be treated as homogeneous ( i. e., invariant) at a particular point in time. Temporal variability refers to variations over time, whether long or short term. Seasonal fluctuations in weather, pesticide applications, use of woodburning appliances and fraction of time spent outdoors are examples of longer term variability. Examples of shorter term variability are differences in industrial or personal activities on weekdays versus weekends or at different times of the day. Inter individual variability can be either of two types: ( 1) human characteristics such as age or body weight, and ( 2) human behaviors such as location and activity patterns. Each of these variabilities, in turn, may be related to several underlying phenomena that vary. For example, the natural variability in human weight is due to a combination of genetic, nutritional, and other lifestyle or environmental factors. Variability arising from independent factors that combine multiplicatively generally will lead to an approximately lognormal distribution across the population, or across spatial/ temporal dimensions. Volume I  General Factors Chapter 2  Variability and Uncertainty Exposure Factors Handbook Page August 1997 2 3 2.3. CONFRONTING VARIABILITY According to the National Research Council ( NRC reliably in light of the variability ( e. g., when the variability 1994), variability can be confronted in four basic ways is known to be relatively small, as in the case of adult body ( Table 2 1) when dealing with science policy questions weight). surrounding issues such as exposure or risk assessment. The first is to ignore the variability and hope for the best. This strategy tends to work best when the variability is relatively small. For example, the assumption that all adults weigh 70 kg is likely to be correct within ± 25% for most adults. The second strategy involves disaggregating the time period ( e. g., the period of peak exposure), one spatial variability in some explicit way, in order to better understand it or reduce it. Mathematical models are appropriate in some cases, as in fitting a sine wave to the annual outdoor concentration cycle for a particular pollutant and location. In other cases, particularly those involving human characteristics or behaviors, it is easier to disaggregate the data by considering all the relevant subgroups or subpopulations. For example, distributions of body weight could be developed separately for adults, 2.4. CONCERN ABOUT UNCERTAINTY adolescents and children, and even for males and females within each of these subgroups. Temporal and spatial analogies for this concept involve measurements on appropriate time scales and choosing appropriate subregions or microenvironments. The third strategy is to use the average value of a quantity that varies. Although this strategy might appear as tantamount to ignoring variability, it needs to be based on a decision that the average value can be estimated The fourth strategy involves using the maximum or minimum value for an exposure factor. In this case, the variability is characterized by the range between the extreme values and a measure of central tendency. This is perhaps the most common method of dealing with variability in exposure or risk assessment  to focus on one region ( e. g., in close proximity to the pollutant source of concern), or one subpopulation ( e. g., exercising asthmatics). As noted by the U. S. EPA ( 1992), when an exposure assessor develops estimates of high end individual exposure and dose, care must be taken not to set all factors to values that maximize exposure or dose  such an approach will almost always lead to an overestimate.

Why should the exposure assessor be concerned with uncertainty? As noted by the U. S. EPA ( 1992), exposure assessment can involve a broad array of information sources and analysis techniques. Even in situations where actual exposure related measurements exist, assumptions or inferences will still be required because data are not likely to be available for all aspects of the exposure assessment. Moreover, the data that are available may be of questionable or unknown quality. Thus, exposure assessors have a responsibility to present not just numbers, but also a clear and explicit explanation of the implications and limitations of their analyses.

Table 2 1. Four Strategies for Confronting Variability Strategy Example Comment Ignore variability Assume that all adults weigh Works best when variability is small 70 kg Disaggregate the Develop distributions of body Variability will be smaller in each group variability weight for age/ gender groups Use the average value Use average body weight for Can the average be estimated reliably given what is adults known about the variability?

Use a maximum or Use a lower end value from Conservative approach  can lead to unrealistically minimum value the weight distribution high exposure estimate if taken for all factors Volume I  General Factors Chapter 2  Variability and Uncertainty Page Exposure Factors Handbook 2 4 August 1997 Morgan and Henrion ( 1990) provide an argument by assessment or risk characterization) at which they can analogy. When scientists report quantities that they have occur. A more abstract and generalized approach preferred measured, they are expected to routinely report an estimate by some scientists is to partition all uncertainties among the of the probable error associated with such measurements. three categories of bias, randomness and true variability. Because uncertainties inherent in policy analysis ( of which These ideas are discussed later in some examples. exposure assessment is a part) tend to be even greater than The U. S. EPA ( 1992) has classified uncertainty in those in the natural sciences, exposure assessors also should exposure assessment into three broad categories: be expected to report or comment on the uncertainties associated with their estimates. 1. Uncertainty regarding missing or incomplete Additional reasons for addressing uncertainty in information needed to fully define exposure and exposure or risk assessments ( U. S. EPA, 1992, Morgan and dose ( Scenario Uncertainty). Henrion, 1990) include the following: 2. Uncertainty regarding some parameter ° Uncertain information from different sources of 3. Uncertainty regarding gaps in scientific theory different quality often must be combined for the required to make predictions on the basis of assessment; causal inferences ( Model Uncertainty). ° Decisions need to be made about whether or how to expend resources to acquire additional Identification of the sources of uncertainty in an exposure information,; assessment is the first step in determining how to reduce ° Biases may result in so called " best estimates" that uncertainty. The types of uncertainty listed above can that in actuality are not very accurate; and be further defined by examining their principal causes. ° Important factors and potential sources of Sources and examples for each type of uncertainty are disagreement in a problem can be identified. summarized in Table 2 2.

Addressing uncertainty will increase the likelihood fundamentally tied to a lack of knowledge concerning that results of an assessment or analysis will be used in an important exposure factors, strategies for reducing appropriate manner. Problems rarely are solved to uncertainty necessarily involve reduction or elimination of everyone's satisfaction, and decisions rarely are reached on knowledge gaps. Example strategies to reduce uncertainty the basis of a single piece of evidence. Results of prior include ( 1) collection of new data using a larger sample analyses can shed light on current assessments, particularly size, an unbiased sample design, a more direct measurement if they are couched in the context of prevailing uncertainty method or a more appropriate target population, and ( 2) use at the time of analysis. Exposure assessment tends to be an of more sophisticated modeling and analysis tools. iterative process, beginning with a screening level assessment that may identify the need for more in depth assessment. One of the primary goals of the more detailed assessment is to reduce uncertainty in estimated exposures. Exposure assessments often are developed in a This objective can be achieved more efficiently if guided by phased approach. The initial phase usually screens out the presentation and discussion of factors thought to be exposure scenarios or pathways that are not expected to primarily responsible for uncertainty in prior estimates. pose much risk, to eliminate them from more detailed,

2.5. TYPES OF UNCERTAINTY AND REDUCING UNCERTAINTY The problem of uncertainty in exposure or risk screening level analyses usually are included in the final assessment is relatively large, and can quickly become too exposure assessment, the final document may contain complex for facile treatment unless it is divided into smaller scenarios that differ quite markedly in and more manageable topics. One method of division ( Bogen, 1990) involves classifying sources of uncertainty according to the step in the risk assessment process ( hazard identification, dose response assessment, exposure ( Parameter Uncertainty).

Because uncertainty in exposure assessments is 2.6. ANALYZING VARIABILITY AND UNCERTAINTY resource intensive review. Screening level assessments typically examine exposures that would fall on or beyond the high end of the expected exposure distribution. Because Volume I  General Factors Chapter 2  Variability and Uncertainty Exposure Factors Handbook Page August 1997 2 5 Table 2 2. Three Types of Uncertainty and Associated Sources and Examples Type of Uncertainty Sources Examples Scenario Uncertainty Descriptive errors Incorrect or insufficient information Aggregation errors Spatial or temporal approximations Judgment errors Selection of an incorrect model Incomplete analysis Overlooking an important pathway Parameter Uncertainty Measurement errors Imprecise or biased measurements Sampling errors Small or unrepresentative samples Variability In time, space or activities Surrogate data Structurally related chemicals Model Uncertainty Relationship errors Incorrect inference on the basis for correlations Modeling errors Excluding relevant variables sophistication, data quality, and amenability to quantitative the assessor may use order of magnitude bounding expressions of variability or uncertainty. estimates of parameter ranges ( e. g., from 0.1 to 10 liters for According to the U. S. EPA ( 1992), uncertainty daily water intake). Another method describes the range for characterization and uncertainty assessment are two ways of each parameter including the lower and upper bounds as describing uncertainty at different degrees of sophistication. well as a " best estimate" ( e. g., 1.4 liters per day) determined Uncertainty characterization usually involves a qualitative by available data or professional judgement. discussion of the thought processes used to select or reject When sensitivity analysis indicates that a parameter specific data, estimates, scenarios, etc. Uncertainty profoundly influences exposure estimates, the assessor assessment is a more quantitative process that may range should develop a probabilistic description of its range. If from simpler measures ( e. g., ranges) and simpler analytical there are enough data to support their use, standard techniques ( e. g., sensitivity analysis) to more complex statistical methods are preferred. If the data are inadequate, measures and techniques. Its goal is to provide decision expert judgment can be used to generate a subjective makers with information concerning the quality of an probabilistic representation. Such judgments should be assessment, including the potential variability in the developed in a consistent, well documented manner. estimated exposures, major data gaps, and the effect that Morgan and Henrion ( 1990) and Rish ( 1988) describe these data gaps have on the exposure estimates developed. techniques to solicit expert judgment. A distinction between variability and uncertainty was Most approaches to quantitative analysis examine made in Section 2.1. Although the quantitative process how variability and uncertainty in values of specific mentioned above applies more directly to variability and the parameters translate into the overall uncertainty of the qualitative approach more so to uncertainty, there is some assessment. Details may be found in reviews such as Cox degree of overlap. In general, either method provides the and Baybutt ( 1981), Whitmore ( 1985), Inman and Helton assessor or decision maker with insights to better evaluate ( 1988), Seller ( 1987), and Rish and Marnicio ( 1988). the assessment in the context of available data and These approaches can generally be described ( in order of assumptions. The following paragraphs describe some of increasing complexity and data needs) as: ( 1) sensitivity the more common procedures for analyzing variability and analysis; ( 2) analytical uncertainty propagation; uncertainty in exposure assessments. Principles that pertain ( 3) probabilistic uncertainty analysis; or ( 4) classical to presenting the results of variability/ uncertainty analysis statistical methods ( U. S. EPA 1992). The four approaches are discussed in the next section. are summarized in Table 2 3. Several approaches can be used to characterize uncertainty in parameter values. When uncertainty is high, Volume I  General Factors Chapter 2  Variability and Uncertainty Page Exposure Factors Handbook 2 6 August 1997 Table 2 3. Approaches to Quantitative Analysis of Uncertainty Approach Description Example Sensitivity Analysis Changing one input variable at a time while leaving others constant, to examine effect on output Fix each input at lower ( then upper) bound while holding others at nominal values ( e. g., medians)

Analytical Uncertainty Propagation Examining how uncertainty in individual parameters affects the overall uncertainty of the exposure assessment Analytically or numerically obtain a partial derivative of the exposure equation with respect to each input parameter Probabilistic Uncertainty Analysis Varying each of the input variables over various values of their respective probability distributions Assign probability density function to each parameter; randomly sample values from each distribution and insert them in the exposure equation ( Monte Carlo)

Classical Statistical Methods Estimating the population exposure distribution directly, based on measured values from a representative sample Compute confidence interval estimates for various percentiles of the exposure distribution 2.7. PRESENTING RESULTS OF VARIABILITY AND UNCERTAINTY ANALYSIS Comprehensive qualitative analysis and rigorous Although assessors have always used descriptors to quantitative analysis are of little value for use in the communicate the kind of scenario being addressed, the decision making process, if their results are not clearly 1992 Exposure Guidelines establish clear quantitative presented. In this chapter, variability ( the receipt of definitions for these risk descriptors. These definitions different levels of exposure by different individuals) has were established to ensure that consistent terminology is been distinguished from uncertainty ( the lack of knowledge used throughout the Agency. The risk descriptors defined about the correct value for a specific exposure measure or in the Guidelines include descriptors of individual risk and estimate). Most of the data that are presented in this population risk. Individual risk descriptors are intended to handbook deal with variability directly, through inclusion of address questions dealing with risks borne by individuals statistics that pertain to the distributions for various within a population, including not only measures of central exposure factors. tendency ( e. g., average or median), but also those risks at Not all approaches historically used to construct the high end of the distribution. Population risk descriptors measures or estimates of exposure have attempted to refer to an assessment of the extent of harm to the distinguish between variability and uncertainty. The population being addressed. It can be either an estimate of assessor is advised to use a variety of exposure descriptors, the number of cases of a particular effect that might occur and where possible, the full population distribution, when in a population ( or population segment), or a description of presenting the results. This information will provide risk what fraction of the population receives exposures, doses, managers with a better understanding of how exposures are or risks greater than a specified value. The data presented distributed over the population and how variability in in the Exposure Factors Handbook is one of the tools population activities influences this distribution. available to exposure assessors to construct the various risk Although incomplete analysis is essentially descriptors. unquantifiable as a source of uncertainty, it should not be However, it is not sufficient to merely present the ignored. At a minimum, the assessor should describe the results using different exposure descriptors. Risk managers rationale for excluding particular exposure scenarios; should also be presented with an analysis of the characterize the uncertainty in these decisions as high, uncertainties surrounding these descriptors. Uncertainty medium, or low; and state whether they were based on data, may be presented using simple or very sophisticated analogy, or professional judgment. Where uncertainty is techniques, depending on the requirements of the high, a sensitivity analysis can be used to credible upper limits on exposure by way of a series of " what if" questions. Volume I  General Factors Chapter 2  Variability and Uncertainty Exposure Factors Handbook Page August 1997 2 7 assessment and the amount of data available. It is beyond Table 2 2 summarizes the three types of uncertainty, the scope of this handbook to discuss the mechanics of associated sources, and examples. Table 2 3 summarizes uncertainty analysis in detail. At a minimum, the assessor four approaches to analyze uncertainty quantitatively. should address uncertainty qualitatively by answering These are described further in the 1992 Exposure questions such as: Guidelines.

° What is the basis or rationale for selecting these assumptions/ parameters, such as data, Bogen, K. T. ( 1990) Uncertainty in environmental health modeling, scientific judgment, Agency policy, risk assessment. Garland Publishing, New York, " what if" considerations, etc.? NY.

° What is the range or variability of the key analysis. A comparative survey. Risk Anal. parameters? How were the parameter values 1( 4): 251 258. selected for use in the assessment? Were Duan, N. ( 1982) Microenvironment types: A model for average, median, or upper percentile values human exposure to air pollution. Environ. Intl. chosen? If other choices had been made, how 8: 305 309. would the results have differed? Inman, R. L.; Helton, J. C. ( 1988) An investigation of ° What is the assessor's confidence ( including computer models. Risk Anal. 8( 1): 71 91. qualitative confidence aspects) in the key Morgan, M. G.; Henrion, M. ( 1990) Uncertainty: A guide parameters and the overall assessment? What to dealing with uncertainty in quantitative risk and are the quality and the extent of the data base( s) policy analysis. Cambridge University Press, New supporting the selection of the chosen values? York, NY.

Any exposure estimate developed by an assessor will judgment in risk assessment. National Academy have associated assumptions about the setting, chemical, Press, Washington, DC. population characteristics, and how contact with the Rish, W. R. ( 1988) Approach to uncertainty in risk chemical occurs through various exposure routes and analysis. Oak Ridge National Laboratory. pathways. The exposure assessor will need to examine ORNL/ TM 10746. many sources of information that bear either directly or Rish, W. R.; Marnicio, R. J. ( 1988) Review of studies indirectly on these components of the exposure assessment. related to uncertainty in risk analysis. Oak Ridge In addition, the assessor will be required to make many National Laboratory. ORNL/ TM 10776. decisions regarding the use of existing information in Seller, F. A. ( 1987) Error propagation for large errors. constructing scenarios and setting up the exposure Risk Anal. 7( 4): 509 518. equations. In presenting the scenario results, the assessor U. S. EPA ( 1992) Guidelines for exposure assessment. should strive for a balanced and impartial treatment of the Washington, DC: Office of Research and evidence bearing on the conclusions with the key Development, Office of Health and Environmental assumptions highlighted. For these key assumptions, one Assessment. EPA/ 600/ 2 92/ 001. should cite data sources and explain any adjustments of the U. S. EPA ( 1995) Guidance for risk characterization. data. Science Policy Council, Washington, DC. The exposure assessor also should qualitatively Whitmore, R. W. ( 1985) Methodology for describe the rationale for selection of any conceptual or characterization of uncertainty in exposure mathematical models that may have been used. This assessments. EPA/ 600/ 8 86/ 009. discussion should address their verification and validation status, how well they represent the situation being assessed ( e. g., average versus high end estimates), and any plausible alternatives in terms of their acceptance by the scientific community. 2.8. REFERENCES FOR CHAPTER 2 Cox, D. C.; Baybutt, P. C. ( 1981) Methods for uncertainty uncertainty and sensitivity analysis techniques for National Research Council ( NRC). ( 1994) Science and


Comment Info: =================

General Comment:Dear Mr. Zeller:

I am personally requesting that the comment period for the Food and Drug Administration's ("FDA") Proposed Rule Deeming Tobacco Products to be Subject to the Federal Food, Drug, and Cosmetic Act, as amended by the Family Smoking and Prevention and Tobacco Control Act (the "Proposed Rule") published at 79 Fed. Reg. 23,142 and Federal Register No. 2014-09491 be extended by the FDA for an additional 105 days, from its current 75-day period, to 180 days.

I am an individual consumer of the electronic cigarette products mentioned in the Proposed Rule and thus have a personal interest in having enough time to reply.

The Proposed Rule details out many significant issues that may impact my ability to remain a non-smoker should the Proposed Rule go into effect as written.

The Proposed Rule contains numerous questions that are important and relevant to me as a consumer of electronic cigarette products, I want to address each question as fully and thoughtfully as possible.

I have spent many hours researching and mapping these issues against current regulations, however doing so takes a great deal of time.

I am aware that the FDA at their liberty created the Proposed Rule over the course of many years, I believe it only fitting to allow me six months to formulate thoughtful comments and answers to it. This is my only opportunity, as a consumer, to provide my personal feedback.

Electronic cigarettes have been instrumental in my successful effort to quit use of combustible tobacco, I strongly believe the availability of this product has saved my life.

My personal story in brief is one of being a traditional smoker of 1.5 to 2 packs of cigarettes a day for 30 years, on my introduction to electronic cigarettes I had 9 packs of cigarettes in my possession which I will never light thanks to the electronic cigarette.  My desire to quit combustible cigarettes has been a long and difficult one, I have used every available OTC and prescription product available to me without success.  My repeated failures had me terrified that I would die from my smoking addiction.  I do not fear that I will die prematurely now thanks to the electronic cigarette, my ability to breath freely is so greatly improved now that I no longer wake gasping for air.

I realize that the FDA has the authority under 21 CFR 10.40 to extend the public comment time frame and that the FDA has exercised this authority on numerous occasions in the past. I am personally asking that you do so now so that I and all whom have similar interests in electronic cigarettes have the opportunity to provide comments and answer the questions in this proposed regulation.

Thank you for considering my request, I am more than happy to discuss my concerns with you further.

Maurice F. Pudlo II.


[Federal Register Volume 85, Number 133 (Friday, July 10, 2020)]
[Notices]
[Pages 41622-41623]
[FR Doc No: 2020-14890]

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DEPARTMENT OF HOMELAND SECURITY

Federal Emergency Management Agency

[Docket ID: FEMA-2020-0027; OMB No. 1660-0144]

Agency Information Collection Activities: Proposed Collection;
Comment Request; Individual & Community Preparedness Division (ICPD)
Youth Preparedness Council (YPC) Application Form

AGENCY: Federal Emergency Management Agency, DHS.

ACTION: 60-Day Notice and request for comments.

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SUMMARY: The Federal Emergency Management Agency, as part of its
continuing effort to reduce paperwork and respondent burden, invites
the general public to take this opportunity to comment on a revision of
a currently approved information collection. In accordance with the
Paperwork Reduction Act of 1995, this notice seeks comments concerning
this collection allowing potential candidates to apply for FEMA's Youth
Preparedness Council.

DATES: Comments must be submitted on or before September 8, 2020.

ADDRESSES: Submit comments at www.regulations.gov under Docket ID FEMA-
2020-0027. Follow the instructions for submitting comments.
    All submissions received must include the agency name and Docket
ID, and will be posted, without change, to the Federal eRulemaking
Portal at http://www.regulations.gov, and will include any personal
information you provide. Therefore, submitting this information makes
it public. You may wish to read the Privacy and Security Notice that is
available via a link on the homepage of www.regulations.gov.

FOR FURTHER INFORMATION CONTACT: Gretchen Wesche, Youth Preparedness
Lead, Individual and Community Preparedness Division, Federal Emergency
Management Agency<EMAIL_ADDRESS>You may contact the
Information Management Division for copies of the proposed collection
of information at email address<EMAIL_ADDRESS>
SUPPLEMENTARY INFORMATION: The FEMA Youth Preparedness Council (YPC)
was formed to bring together youth leaders from across the country who
are highly interested and engaged in advocating youth preparedness and
making a difference in their communities. This collection meets the
requirements of 6 U.S.C. Sec. 742, National Preparedness, and
Presidential Policy Directive--8 (PPD-8) which emphasize the need for
involvement from all sectors of society in preparing for and responding
to threats and hazards.

Collection of Information

    Title: Individual & Community Preparedness Division (ICPD) Youth
Preparedness Council (YPC) Application Form.
    Type of Information Collection: Revision of a currently approved
information collection.
    OMB Number: 1660-0144.
    FEMA Forms: FEMA Form 008-0-0-24. Title: Individual & Community
Preparedness Division (ICPD) Youth Preparedness Council (YPC)
Application Form.
    Abstract: This application form is used to select interested
council members based on dedication to public service, efforts in
making a difference in their community, and potential for expanding
their impact as a national advocate for youth preparedness.
    Affected Public: Individuals or households, State, local or Tribal
government.
    Estimated Number of Respondents: 200.
    Estimated Number of Responses: 200.
    Estimated Total Annual Burden Hours: 283.
    Estimated Total Annual Respondent Cost: $2,997.
    Estimated Respondents' Operation and Maintenance Costs: $0.
    Estimated Respondents' Capital and Start-Up Costs: $0.
    Estimated Total Annual Cost to the Federal Government: $72,796.

Comments

    Comments may be submitted as indicated in the ADDRESSES caption
above. Comments are solicited to (a) evaluate whether the proposed data
collection is necessary for the proper performance of the agency,
including whether the information shall have practical utility; (b)
evaluate the accuracy of the agency's estimate of the burden of the
proposed collection of information, including the validity of

the methodology and assumptions used; (c) enhance the quality, utility,
and clarity of the information to be collected; and (d) minimize the
burden of the collection of information on those who are to respond,
including through the use of appropriate automated, electronic,
mechanical, or other technological collection techniques or other forms
of information technology, e.g., permitting electronic submission of
responses.

Maile Arthur,
Acting Records Management Branch Chief, Office of the Chief
Administrative Officer, Mission Support, Federal Emergency Management
Agency, Department of Homeland Security.
[FR Doc. 2020-14890 Filed 7-9-20; 8:45 am]
BILLING CODE 9111-27-P


[Federal Register Volume 81, Number 154 (Wednesday, August 10, 2016)]
[Notices]
[Pages 52896-52899]
[FR Doc No: 2016-18977]

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DEPARTMENT OF HOMELAND SECURITY

Federal Emergency Management Agency

[Docket ID FEMA-2016-0002; Internal Agency Docket No. FEMA-B-1642]

Proposed Flood Hazard Determinations

AGENCY: Federal Emergency Management Agency, DHS.

ACTION: Notice.

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SUMMARY: Comments are requested on proposed flood hazard
determinations, which may include additions or modifications of any
Base Flood Elevation (BFE), base flood depth, Special Flood Hazard Area
(SFHA) boundary or zone designation, or regulatory floodway on the
Flood Insurance Rate Maps (FIRMs), and where applicable, in the
supporting Flood Insurance Study (FIS) reports for the communities
listed in the table below. The purpose of this notice is to seek
general information and comment regarding the preliminary FIRM, and
where applicable, the FIS report that the Federal Emergency Management
Agency (FEMA) has provided to the affected communities. The FIRM and
FIS report are the basis of the floodplain management measures that the
community is required either to adopt or to show evidence of having in
effect in order to qualify or remain qualified for participation in the
National Flood Insurance Program (NFIP). In addition, the FIRM and FIS
report, once effective, will be used by insurance agents and others to
calculate appropriate flood insurance premium rates for new

buildings and the contents of those buildings.

DATES: Comments are to be submitted on or before November 8, 2016.

ADDRESSES: The Preliminary FIRM, and where applicable, the FIS report
for each community are available for inspection at both the online
location and the respective Community Map Repository address listed in
the tables below. Additionally, the current effective FIRM and FIS
report for each community are accessible online through the FEMA Map
Service Center at www.msc.fema.gov for comparison.
    You may submit comments, identified by Docket No. FEMA-B-1642, to
Rick Sacbibit, Chief, Engineering Services Branch, Federal Insurance
and Mitigation Administration, FEMA, 400 C Street SW., Washington, DC
20472,<PHONE_NUMBER>, or (email<EMAIL_ADDRESS>
FOR FURTHER INFORMATION CONTACT: Rick Sacbibit, Chief, Engineering
Services Branch, Federal Insurance and Mitigation Administration, FEMA,
400 C Street SW., Washington, DC 20472,<PHONE_NUMBER>, or (email)
<EMAIL_ADDRESS>or visit the FEMA Map Information
eXchange (FMIX) online at www.floodmaps.fema.gov/fhm/fmx_main.html.

SUPPLEMENTARY INFORMATION: FEMA proposes to make flood hazard
determinations for each community listed below, in accordance with
section 110 of the Flood Disaster Protection Act of 1973, 42 U.S.C.
4104, and 44 CFR 67.4(a).
    These proposed flood hazard determinations, together with the
floodplain management criteria required by 44 CFR 60.3, are the minimum
that are required. They should not be construed to mean that the
community must change any existing ordinances that are more stringent
in their floodplain management requirements. The community may at any
time enact stricter requirements of its own or pursuant to policies
established by other Federal, State, or regional entities. These flood
hazard determinations are used to meet the floodplain management
requirements of the NFIP and also are used to calculate the appropriate
flood insurance premium rates for new buildings built after the FIRM
and FIS report become effective.
    The communities affected by the flood hazard determinations are
provided in the tables below. Any request for reconsideration of the
revised flood hazard information shown on the Preliminary FIRM and FIS
report that satisfies the data requirements outlined in 44 CFR 67.6(b)
is considered an appeal. Comments unrelated to the flood hazard
determinations also will be considered before the FIRM and FIS report
become effective.
    Use of a Scientific Resolution Panel (SRP) is available to
communities in support of the appeal resolution process. SRPs are
independent panels of experts in hydrology, hydraulics, and other
pertinent sciences established to review conflicting scientific and
technical data and provide recommendations for resolution. Use of the
SRP only may be exercised after FEMA and local communities have been
engaged in a collaborative consultation process for at least 60 days
without a mutually acceptable resolution of an appeal. Additional
information regarding the SRP process can be found online at http://floodsrp.org/pdfs/srp_fact_sheet.pdf.
    The watersheds and/or communities affected are listed in the tables
below. The Preliminary FIRM, and where applicable, FIS report for each
community are available for inspection at both the online location and
the respective Community Map Repository address listed in the tables.
For communities with multiple ongoing Preliminary studies, the studies
can be identified by the unique project number and Preliminary FIRM
date listed in the tables. Additionally, the current effective FIRM and
FIS report for each community are accessible online through the FEMA
Map Service Center at www.msc.fema.gov for comparison.

(Catalog of Federal Domestic Assistance No. 97.022, ``Flood
Insurance.'')

    Dated: August 2, 2016.
Roy E. Wright,
Deputy Associate Administrator for Insurance and Mitigation, Department
of Homeland Security, Federal Emergency Management Agency.
I. Watershed-based studies:

------------------------------------------------------------------------
                                             Community map repository
               Community                             address
------------------------------------------------------------------------
                         Lower Sabine Watershed
------------------------------------------------------------------------
      Maps Available for Inspection Online at: http://www.fema.gov/preliminaryfloodhazarddata preliminaryfloodhazarddata
------------------------------------------------------------------------
           Calcasieu Parish, Louisiana and Incorporated Areas
------------------------------------------------------------------------
Unincorporated Areas of Calcasieu        Planning and Development
 Parish.                                  Department, 901 Lakeshore
                                          Drive, Lake Charles, LA 70601.
------------------------------------------------------------------------

II. Non-watershed-based studies:

------------------------------------------------------------------------
                                             Community map repository
               Community                             address
------------------------------------------------------------------------
              Camden County, Georgia and Incorporated Areas
------------------------------------------------------------------------
      Maps Available for Inspection Online at: http://www.fema.gov/preliminaryfloodhazarddata preliminaryfloodhazarddata
------------------------------------------------------------------------
        Project: 12-04-0913S Preliminary Date: December 15, 2015
------------------------------------------------------------------------
City of Kingsland......................  City Hall, 107 South Lee
                                          Street, Kingsland, GA 31548.
City of St. Marys......................  Community Development
                                          Department, 418 Osborne
                                          Street, St. Marys, GA 31558.
City of Woodbine.......................  City Hall, 310 Bedell Avenue,
                                          Woodbine, GA 31569.
Unincorporated Areas of Camden County..  Camden County Planning and
                                          Development Department, 107
                                          Gross Road, Suite 3,
                                          Kingsland, GA 31548.
------------------------------------------------------------------------

            Effingham County, Georgia and Incorporated Areas
------------------------------------------------------------------------
      Maps Available for Inspection Online at: http://www.fema.gov/preliminaryfloodhazarddata preliminaryfloodhazarddata
------------------------------------------------------------------------
        Project: 12-04-0917S Preliminary Date: November 16, 2015
------------------------------------------------------------------------
City of Rincon.........................  City Hall, Building and Zoning
                                          Department, 302 South Columbia
                                          Avenue, Rincon, GA 31326.
Unincorporated Areas of Effingham        Effingham County Courthouse,
 County.                                  GIS Department, 901 North Pine
                                          Street, Suite 206,
                                          Springfield, GA 31329.
------------------------------------------------------------------------
              Glynn County, Georgia and Incorporated Areas
------------------------------------------------------------------------
      Maps Available for Inspection Online at: http://www.fema.gov/preliminaryfloodhazarddata preliminaryfloodhazarddata
------------------------------------------------------------------------
        Project: 12-04-0916S Preliminary Date: December 11, 2015
------------------------------------------------------------------------
City of Brunswick......................  City Hall, 601 Gloucester
                                          Street, Brunswick, GA 31520.
Jekyll Island State Park Authority.....  Fire and EMS Department, 200
                                          Stable Road, Jekyll Island, GA
                                          31527.
Unincorporated Areas of Glynn County...  Glynn County Offices, Harold
                                          Pate Building, 1725 Reynolds
                                          Street, 2nd Floor, Brunswick,
                                          GA 31520.
------------------------------------------------------------------------
               Long County, Georgia and Incorporated Areas
------------------------------------------------------------------------
      Maps Available for Inspection Online at:http://www.fema.gov/preliminaryfloodhazarddata preliminaryfloodhazarddata
------------------------------------------------------------------------
        Project: 12-04-0919S Preliminary Date: November 16, 2015
------------------------------------------------------------------------
Unincorporated Areas of Long County....  Long County Code Enforcement
                                          Office, 285 South McDonald
                                          Street, Ludowici, GA 31316.
------------------------------------------------------------------------
              Washington County, Maine (All Jurisdictions)
------------------------------------------------------------------------
      Maps Available for Inspection Online at: http://www.fema.gov/preliminaryfloodhazarddata preliminaryfloodhazarddata
------------------------------------------------------------------------
          Project: 13-01-1510S Preliminary Date: March 4, 2016
------------------------------------------------------------------------
Baring Plantation......................  Land Use Planning Commission,
                                          106 Hogan Road, Suite 8,
                                          Bangor, ME 04401.
City of Calais.........................  City Building, 11 Church
                                          Street, Calais, ME 04619.
City of Eastport.......................  City Hall, 78 High Street,
                                          Eastport, ME 04631.
Grand Lake Stream Plantation...........  Land Use Planning Commission,
                                          106 Hogan Road, Suite 8,
                                          Bangor, ME 04401.
Passamaquoddy Tribe At Pleasant Point..  Passamaquoddy Tribal Office,
                                          136 County Road, Perry, ME
                                          04667.
Town of Addison........................  Town Hall, 334 Water Street,
                                          Addison, ME 04606.
Town of Alexander......................  Town Hall, 50 Cooper Road,
                                          Alexander, ME 04694.
Town of Baileyville....................  Town Office, 63 Broadway
                                          Street, Baileyville, ME 04694.
Town of Beals..........................  Town Office, 11 Big Pond Road,
                                          Beals, ME 04611.
Town of Charlotte......................  Town Office, 1098 Ayers
                                          Junction Road, Charlotte, ME
                                          04666.
Town of Cherryfield....................  Town Office, 12 Municipal Way,
                                          Cherryfield, ME 04622.
Town of Columbia.......................  Town Hall, 106 Epping Road,
                                          Columbia, ME 04623.
Town of Columbia Falls.................  Town Office, 8 Point Street,
                                          Columbia Falls, ME 04623.
Town of Crawford.......................  First Selectman's Office, 359
                                          Crawford Arm Road, Crawford,
                                          ME 04694.
Town of Cutler.........................  Town Office, 2655 Cutler Road,
                                          Cutler, ME 04626.
Town of Danforth.......................  Town Office, 18 Central Street,
                                          Danforth, ME 04424.
Town of Dennysville....................  Town Office, 2 Main Street,
                                          Dennysville, ME 04628.
Town of East Machias...................  Town Office, 32 Cutler Road,
                                          East Machias, ME 04630.
Town of Harrington.....................  Town Office, 114 East Main
                                          Street, Harrington, ME 04643.
Town of Jonesboro......................  Town Office, 23 Station Road,
                                          Jonesboro, ME 04648.
Town of Jonesport......................  Town Office, 70 Snare Creek
                                          Lane, Jonesport, ME 04649.
Town of Lubec..........................  Town Office, 40 School Street,
                                          Lubec, ME 04652.
Town of Machias........................  Town Office, 7 Court Street,
                                          Suite 1, Machias, ME 04654.
Town of Machiasport....................  Town Office, 8 Unity Square,
                                          Machiasport, ME 04655.
Town of Marshfield.....................  Town Office, 187 Northfield
                                          Road, Marshfield, ME 04654.
Town of Milbridge......................  Town Office, 22 School Street,
                                          Milbridge, ME 04658.
Town of Northfield.....................  Town Hall, 1940 Northfield
                                          Road, Northfield, ME 04654.
Town of Pembroke.......................  Town Office, 48 Old County
                                          Road, Pembroke, ME 04666.
Town of Perry..........................  Town Office, 898 U.S. Route 1,
                                          Perry, ME 04667.
Town of Princeton......................  Town Office, 15 Depot Street,
                                          Princeton, ME 04668.
Town of Robbinston.....................  Town Office, 904 U.S. Route 1,
                                          Robbinston, ME 04671.
Town of Roque Bluffs...................  Town Hall, 3 Roque Bluffs Road,
                                          Roque Bluffs, ME 04654.
Town of Steuben........................  Town Office, 294 U.S. Route 1,
                                          Steuben, ME 04680.
Town of Talmadge.......................  Chairperson's Office, 47
                                          Talmadge Road, Talmadge, ME
                                          04492.
Town of Topsfield......................  Town Office, 48 North Road,
                                          Topsfield, ME 04490.

Town of Vanceboro......................  Town Office, 101 High Street,
                                          Vanceboro, ME 04491.
Town of Wesley.........................  Town Office, 2 Whining Pines
                                          Drive, Wesley, ME 04686.
Town of Whiting........................  Town Office, 169 U.S. Route 1,
                                          Whiting, ME 04691.
Town of Whitneyville...................  Town Office, 42 South Main
                                          Street, Whitneyville, ME
                                          04654.
Township of Brookton...................  Land Use Planning Commission,
                                          106 Hogan Road, Suite 8,
                                          Bangor, ME 04401.
Township of Edmunds....................  Land Use Planning Commission,
                                          106 Hogan Road, Suite 8,
                                          Bangor, ME 04401.
Township of Lambert Lake...............  Land Use Planning Commission,
                                          106 Hogan Road, Suite 8,
                                          Bangor, ME 04401.
Township of Trescott...................  Land Use Planning Commission,
                                          106 Hogan Road, Suite 8,
                                          Bangor, ME 04401.
------------------------------------------------------------------------
             Dunn County, North Dakota Unincorporated Areas
------------------------------------------------------------------------
      Maps Available for Inspection Online at:http://www.fema.gov/preliminaryfloodhazarddata preliminaryfloodhazarddata
------------------------------------------------------------------------
          Project: 16-08-0347S Preliminary Date: March 10, 2016
Unincorporated Areas of Dunn County....  Dunn County Courthouse, 205
                                          Owens Street, Manning, ND
                                          58642.
------------------------------------------------------------------------

[FR Doc. 2016-18977 Filed 8-9-16; 8:45 am]
 BILLING CODE 9110-12-P