EPA-540-R-070-002 OSWER 9285.7-82 January 2009



### Risk Assessment Guidance for Superfund Volume I: Human Heal th Evaluation Manual (Part F, Supplemental Guidance fo r Inhalation Risk Assessment)

Final

Office of Superfund Remediation and Technology Innovation Environmental Protection Agency Washington, D.C.TABLE OF CONTENTS

1. INTRODUCTION ......................................................................................................................1 1.1 Background....................................................................................................................1 1.2 Purpose and Scope .........................................................................................................2 1.3 Effects on Other Office of Superfund Remediation and Technology Innovation Guidance................................................................................................3

2. BACKGROUND ON DERIVATION OF INHALATION TOXICITY VALUES ..............4 2.1 Application of Inhalation Dosimetry .............................................................................4 2.1.1 Default Approach - Extrapolation from Experimental Animal Data..............5 2.1.2 Default Approach - Extrapolat ion from Human Occupational Data ..............9 2.2 Derivation of the Inhalation Unit Risk.........................................................................10 2.3 Derivation of the Reference Concentration .................................................................10

3. CHARACTERIZING EXPOSURE .......................................................................................13 3.1 Introduction............................................................................................................... ...13 3.2 Estimating Exposure Concentrati ons for Assessing Cancer Risks..............................13 3.3 Estimating Exposure Concentrations for Calculating Hazard Quotients.....................14 3.3.1 Step 1: Assess Duration ................................................................................14 3.3.2 Step 2: Assess Exposure Pattern...................................................................15 3.3.3 Step 3: Estimate Exposure Concentration.....................................................17 3.4 Estimating Exposure Concentrations in Multiple Microenvironments .......................18 3.4.1 Using Microenvironments to Estimate an Average Exposure Concentration for a Specific Exposure Period.......................................................18 3.4.2 Estimating an Average Exposur e Concentration Across Multiple Exposure Periods ...................................................................................................19

4. SELECTING APPROPRIATE TOXICITY VALUES ........................................................20 4.1 Sources for Inhalation Toxicity Data...........................................................................20 4.2 Recommended Procedure for Asse ssing Risk in the Absence of Inhalation Toxicity Values...........................................................................................21

5. ESTIMATING RISKS ............................................................................................................22 5.1 Cancer Risks Characterized by an Inhalation Unit Risk..............................................22 5.2 Hazard Quotients .........................................................................................................2 4

6. EXAMPLE EXPOSURE SCENARIOS ................................................................................24 6.1 Residential Receptor ....................................................................................................24 6.2 Commercial-Industrial/Occupational Receptor ...........................................................25 6.3 Construction Worker....................................................................................................25 6.4 Trespasser/Recreational Receptor................................................................................25

i7. TARGET CONCENTRATIONS FOR SCREENING ANALYSIS OF INHALATION PATHWAYS ......................................................................26 7.1 Target Contaminant Concentrations in Air..................................................................26 7.2 Screening Levels for Other Media...............................................................................26 7.2.1 Soil Screening Levels ...................................................................................27 7.2.2 Tap Water Screening Levels.........................................................................28 7.2.3 Soil Gas or Ground Water Screen ing Values for Vapor Intrusion ...............28

8. DEVELOPING AGGREGATE AND CUMULATIVE RISK ESTIMATES ....................28 8.1 Estimating Cumulative Risk and H azards Across Multiple Chemicals.......................28 8.1.1 Cancer Risks .................................................................................................29 8.1.2 Hazard Quotients ..........................................................................................29 8.2 Aggregating Risk and Hazard Quotients Across Exposure Routes.............................29

9. RISK CHARACTERIZATION ..............................................................................................30 9.1 Highly Exposed or Susceptible Populations and Life Stages ......................................30 9.1.1 Children.........................................................................................................30 9.1.2 Workers.........................................................................................................31 9.2 Uncertainties in Inhalation Risk Assessment...............................................................31 9.2.1 Development of Exposure Concentrations ..................................................32 9.2.2 Toxicity Assessment .....................................................................................32 9.2.3 Estimating Cancer Risks...............................................................................33 9.2.4 Estimating Risk and Hazard from Multiple Chemicals and Exposure Pathways .......................................................................................33

10. REFERENCES .......................................................................................................................34

APPENDIX A ............................................................................................................................ A-1

APPENDIX B .............................................................................................................................B- 1

APPENDIX C ............................................................................................................................C- 1

iiLIST OF TABLES

Table 1: RAGS Part A Equation Describing the Estimation of Inhalation Exposure .....................2

Table 2: Contaminant Properties and Dosimetric Adjustment Factors ...........................................7

Table 3: The Use of Uncertainty Factor s in Deriving an Inhalation Reference Concentration...................................................................................................................12

Table 4: Recommended Procedur e for Calculating Risk-Based Screening Concentrations for Contaminants in Air........................................................................................................27

LIST OF FIGURES

Figure 1: Human Re spiratory Tract .................................................................................................8

Figure 2: Recommended Procedure for Deriving E xposure Concentrations and Hazard Quotients for Inhalation Exposure Scenarios.....................................................................................16

Figure 3: Guidance on Assessing Risk from Early-Life Exposures for Chemicals Acting by a Mutagenic Mode of Action for Carcinogenicity........................................23

LIST OF EQUATIONS

Equation 1: NOAEL [ADJ] .................................................................................................................5

Equation 2: NOAEL [HEC] from Animal Data ..................................................................................6

Equation 3: NOAEL [HEC] from Human Data .................................................................................10

Equation 4: Inhalation Unit Risk ............................................................................................... ....10

Equation 5: Reference Concentration ............................................................................................ 11

Equation 6: Exposure Concentration for Assessing Cancer Risks ................................................14

Equation 7: Exposure Concentratio n for Acute Exposure Scenarios ............................................17

Equation 8: Exposure Concentration Chr onic for Subchronic Exposure Scenarios......................18

Equation 9: Exposure Concentratio n for a Specific Exposure Period, Microenvironments.............................................................................................................. ..........19

iiiLIST OF EQUATIONS (CONT.)

Equation 10: Exposure Concentration Across Multiple Exposure Periods, Microenvironments.............................................................................................................. ..........19

Equation 11: Cancer Risk ..............................................................................................................22

Equation 12: Hazard Quotient ................................................................................................... ....24

ivACKNOWLEDGEME NTS

This guidance was developed by the Inhalation Risk W o rkgroup, which included regional and headquarters staff in EPA’s Off i ce of Superf und Rem e diation and Technology Innovatio n (OSRTI), the Office of Research and Developm ent (ORD), the Office of Children’s Health Protectio n (OCHP), The Office of Air and Ra d i ation (OAR), and the O ffice of Solid W a ste and Em ergency Response (OSW ER). Dave Crawford of OSRTI headquarters and Michael Sivak of EPA Region 2 provided project m a nagem e nt and techni cal coordination of its development.

OSRTI would like to acknowledge the efforts of all the Inhalation Risk Workgroup m e mbers who supported the developm e n t of the guidance by providing t echnical input regard ing its content and
scope:
Marcia Bailey, Region 10 Deirdre Murphy, OAR/OAQPS Bob Benson, Region 8 Henry Schuver, OSW E R/OSW Dave Crawford, OSW E R/OSRTI Michael Sivak, Region 2 Arunas Draugelis, Region 5 John Stanek, ORD/NCEA Brenda Foos, OCHP Daniel Stralka, Region 9 Gary Fourem an, OR D/NCEA Tim o thy Ta ylor, OSW E R/OSW Susan Griffin, Region 8 John W h alan, ORD/NCEA Ofia Hodoh, Region 4 Erik W i nchester, ORD/OSP Jennifer Hubbard, Region 3 Ann Johnson, OA/OPEI Form er Members: Jerem y Johnson, Region 7 Cheryl Overstreet, Region 6 Kevin Koporec, Region 4 Neil Stiber, ORD/OS P Sarah Levinson, Region 1

OSRTI would also like to acknowledge the efforts of the external peer review panel m e m b ers who provided input on the draf t version of the docum ent:

Sandra Baird, Massachusetts Depart m e nt of Environm ental Protection Selene Chou, Agency for Toxic Substances and D i sease Registry Lynne Haber, Toxicology Excellence for Risk Assessm ent Anita Meyer, US Ar m y Corps of Engineers Peter Valberg, Gradient Corporation

Henry Roman, Eric Ruder, and Tyra W a lsh of I ndustrial Econom ics, Incorporated in Ca m b ridge, MA provided techn i cal assis t ance to EPA in th e develo pment of th is g u idance und er Contract Num b er 68-W

- 01-05.

vLIST OF ACRONYM S

μg Microgram
μm Microm eter ADAF Age Dependent Adjustm e nt Factor AT Averaging Tim e ATSDR Agency for Toxic Substances and D i sease Reg i s t ry BMCL Benchm ark Concentration, Lower confidence lim it BMD Benchm ark Dose BW Body W e ight CA Contam inant Concentration in Air CERCLA Com prehensive Environm ental Res ponse, Com p ensation, and Liability Act CSF Cancer Slop e Factor DAF Dosim e tric Adjustm e nt Factor ED Exposure Duration EC Exposure Concentration EF Exposure Frequency EPA Environm ental Protection Agency ER Extra-respiratory ET Exposure Tim e ETh Extrathoracic F r Fractional D e position in region r F total Total particle deposi tion in resp ira t or y trac t H b/g- anim al Ani m al Blood:Gas Partition Coefficient H b/g- hu m a n Hum an Blood:Gas Par tition Coefficient HEAST Health Effects Assessm ent Summary Table HEC Hum a n Equivalent Concentration HI Hazard Index HQ Hazard Quotien t ICRP Intern ational Comm issi on for Radiological P r otection IR Inhalation R a te IRIS Integrated R i sk Inform ation System IUR Inhala tion U n it Risk kg Kilogram LEC 10 Lower lim it on Effective Concentration, using a 10 percent response level LOAEL Lowest Observable Adverse Effect Level ME Microenvironm e nt MF Modifying Factor mg Milligr am MOA Mode of Action MRL Minim al Risk Level MW Molecu lar W e ight NCEA National Center for Environm ental Assessm ent NOAE L No Observable Adverse Effect Level ORD Office of Research and Developm ent OSRTI Office of Superfund Rem e di ation and Technology Innovation

viLIST OF ACRONYM S (CONT.)

OSWER Office of Solid W aste and Em ergency Response PBPK Physiologically Based P h arm acokinetic POD Point of Departure
ppm Parts Per Million PPRTV Provisional Peer Re view ed Toxicity Value PRG Prelim inary Rem ediation Goal PU Pulm onary Q-alv Alveolar ventilation rate QSAR Quantita tive Structu r e-A ctiv ity Rela tionship RAGS Risk Assessm e nt Guida nce for Superfund RBC Risk-Based Concentration RfC Reference Concentration RfD Reference Dose RGDR Regional Gas Dose Ratio RDDR Regional Deposited Dose Ratio RME Reasonable Maxim u m Exposure SA Surface Area SSL Soil Screening Level STSC Superfund Health Risk Technical Support Center TB Tracheobron chial TOT Total Respiratory System UF Uncerta inty Factor V e Minute Volum e

vii1. INTRODUCTION

The Environmental Protection Agency’s (EPA’s) Superfund Program has updated its approach for determining risk from inhaled chemicals to be consistent with the inhalation dosimetry methodology described in Methods for Derivation of Inhalation Refe rence Concentrations and Application of Inhalation Dosimetry (USEPA, 1994; hereafter, the Inhalation Dosimetry Methodology ). 1 This document provides Superfund site risk assessors with guidance that should he lp more consistently address the Inhalation Dosimetry Methodology

. This document outlines recommended processes c onsisting of a series of steps as well as recommended equations for EPA Regions to consider when estimating inhalation exposure and risk at Comprehensive Environmental Response, Compen sation, and Liability Act (CERCLA) sites. This guidance is intended to provide a recomm ended methodology for consis tently addressing the inhalation pathway in risk assessments for Superfund sites.

Some of the statutory provisions described in this document cont ain legally binding requirements. However, this document does not substitute for those provisions or regulations, nor is it a regulation itself. Thus, it cannot impose legally binding re quirements on EPA, Stat es, or the regulated community, and may not apply to a particular situation based upon the circumstances. Any decisions regarding a particular remedy selection decision will be made based on the statute and regulations, and EPA decisionmakers retain the di scretion to adopt appro aches on a case-by-case basis that differ from this guidance where appropria te. EPA may change this guidance in the future.

1.1 Background

EPA’s Risk Assessment Guidance for Superfund (RAGS), Part A (USEPA, 1989; hereafter, RAGS, Part A ) outlined a previously recommended approach for conducting site-spe cific baseline risk assessments for inhaled contaminants. 2 According to the original RAGS approach, the inhalation exposure estimate was typically derived in terms of a chronic, daily “air intake” (mg/kg-day) using the following general approach. The intake of the chemical was estimated as a function of the concentration of the chemical in air (CA), inhalation rate (IR), body weight (BW), and the exposure scenario. Age-specific values for BW and IR were used when evaluating childhood exposures. Table 1 presents the RAGS, Part A equation for calculating intake for inhalation exposure. Inhalation toxicity values were “c onverted” into similar units for the risk quantificati on step. Cancer risk was estimated by multiplying the chronic daily intake of the chemical from the air by the “inhalation cancer slope factor” (CSF i ); the Hazard Quotient ( HQ) for non-cancer effects was estimated by dividing the intake of the ch emical by an “inhalation reference dose” (RfD i ). 3

The approach outlined in RAGS, Part A was developed befo re EPA issued the Inhalation Dosimetry Methodology , which describes the Agency’s refined recommended approach for interpreting

1 The Inhalation Dosimetry Methodology can be found at the following web address: http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=71993

. 2 See sections 6.6.3, 7.2.3, 7.3.3, and 8.2 of RAGS, Part A

.
3 EPA defines an HQ in RAGS, Part A as: “The ratio of a single substance exposure level over a specified time period (e.g., subchronic) to a reference dose (RfD) for that substa nce derived from a similar exposure period” (USEPA, 1989).

12 inhalation toxicity studies in labo ratory animals or studies of o ccupational exposures of humans to airborne chemicals. Under the Inhalation Dosimetry Methodology , the experimental exposures are typically extrapolated to a Huma n Equivalent Concentration (HEC), and a reference concentration (RfC) is typically calculated by dividing the HEC by uncertainty factors (UFs). As described in the Agency’s Guidelines for Cancer Risk Assessment (USEPA, 2005a), the HEC developed in accordance with the Inhalation Dosimetry Methodology typically is also us ed in developing an inhalation unit risk (IUR) for cancer risk assessment (which may also be calle d an inhalation cancer slope factor). 4 The procedure that was used to calculate the published RfC or IUR is described in the Integrated Risk Information System (IRIS) prof ile or other toxicologica l reference document for a chemical.

TABLE 1 RAGS, PART A EQUATION DESCRIBING THE ESTIMATION OF INHALATION EXPOSURE Equation Location in RAGS, Part A Intake (mg/kg-d) = CA x (IR/BW) x (ET x EF x ED)/AT Exhibit 6-16, Page 6-44 Key: CA (mg/m 3 ) = contaminant concentration in air; IR (m 3 /hr) = inhalation rate; BW (kg) = body weight; ET (hours/day) = exposure time; EF (days/year) = exposure frequency; ED (years) = exposure duration; and AT (days) = averaging time (period over which exposure is averaged).
The Superfund Program has updated its inhalation ri sk paradigm to be compatible with the Inhalation Dosimetry Methodology , which represents the Agency's current methodology for inhalation dosimetry and derivation of inhalation toxicity values. 5 This document recommends that when estimating risk via inhalation, risk assessors should use the concen tration of the chemical in air as the exposure metric (e.g., mg/m 3 ), rather than inhalation intake of a contaminant in air based on IR and BW (e.g., mg/kg-day).

1.2 Purpose and Scope

The intake equation described above ( RAGS, Part A , Exhibit 6-16) is not consistent with the principles of EPA’s Inhalation Dosimetry Methodology because the amount of the chemical that reaches the target site is not a si mple function of IR and BW. Inst ead, the interaction of the inhaled contaminant with the respiratory tract is affected by factors such as species-specific relationships of exposure concentrations (ECs) to deposited/deliver ed doses and physiochemical characteristics of the inhaled contaminant. The Inhalation Dosimetry Methodology also considers the target site where the toxic effect occurs (e.g., the respiratory tract or a location in the body remote from the portal-ofentry) when applying dosimetric adjustments to experimental concen trations (USEPA, 1994). Therefore, this RAGS, Part A equation is not recommended for estimating exposures to inhaled contaminants.

4 The phrase “inhalation cancer slope factor,” as used in this guidance, refers generally to the risk per a measure of inhalation exposure. Inhalation exposure in cancer bioassays or occupational studies from which slope factors may be derived is most commonly expressed as an exposure concentration (e.g., μg agent/m 3 air). Please note that this differs from past use of the phrase “inhalation cancer slope factor” or “CSF i ” by the Superfund program to refer to a cancer slope expressed as an “inhalation intake” (e.g., RAGS, Part A (USEPA, 1989)).

5 For additional information about the Superfund program’s adoption of the Inhalation Dosimetry Methodology , please refer to the summary of a 2003 Superfund workshop on inhalation risk assessment: http://www.epa.gov/oswer/riskassessment /pdf/finalinhalationriskworkshop.pdf

.The purpose of this document is to provide a r ecommended approach for developing the information necessary to assist risk assessment and risk mana gement decision-making at waste sites involving potential risks from inhalation exposures. 6, 7 This includes providing equa tions that may be used in conducting baseline risk assessment s and in calculating risk-based concentrations (RBCs). It is intended that RAGS, Part F will replace those portions of RAGS, Part A , which addressed inhalation risk.

1.3 Effects on Other Office of Superfund Reme diation and Technology Innovation Guidance

EPA recommends that the intake equation presented in RAGS, Part A (USEPA, 1989, Exhibit 6-16) should no longer be used when evaluating risk fro m the inhalation pathway. Implementation of a risk assessment approach consistent with the Inhalation Dosimetry Methodology will also affect the following guidance documents: RAGS, Part B , Section 3.3: Volatilization and Particulate Emission Factors (USEPA, 1991); and the Office of Solid Waste and Emergency Response’s (OSWER’s) Draft Guidance for Evaluating the Vapor Intrusion to Indoor Air Pathway from Groundwater and Soils (USEPA, 2002a; hereafter the Vapor Intrusion Guidance ). EPA no longer recommends using the equations in Section 3.3 of RAGS, Part B nor the inhalation toxicity values generated using simple route-to-route extra polation, such as those pr esented in the 2002 draft Vapor Intrusion Guidance and related documents. 8

This guidance does not affect th e equations pertaining to risk from inhaled chemicals in the Soil Screening Guidance (USEPA, 1996), Section 2.4, or the Supplemental Guidance for Developing Soil Screening Levels for Superfund Sites (USEPA, 2002b), Sections 4.2.3, 5.3.2 and Appendix B, other than to clarify that the IURs and RfCs used in the equations are based on continuous exposure (24 hours per day). If the exposure sc enario of interest is less than 24 hours per day, the scenariospecific exposure time (ET) in hours per day should be used in the equatio ns and the averaging time should be in units of hours (see Equations 6 and 8 in this document). RAGS, Part D (USEPA, 2001) is also not affected by RAGS, Part F , as it includes sufficient fl exibility to accommodate the revisions described in th is guidance. In additi on, the screening values pr esented on the “Regional Screening Levels for Chemical Contaminants at Superfund Sites” screening level/preliminary remediation goal table are consistent with RAGS, Part F (USEPA, 2008a). 9 Readers can contact EPA headquarters with questions about the compatibility of sp ecific Superfund documents with RAGS, Part F

.

6 Note that the assessment of risk from inhaled nanoparticles is outside the scope of this document.

7 If a site contains asbestos contamination, risk assessors should contact EPA’s Technical Review Workgroup for Metals and Asbestos for assistance.

8 Related documents include the Johnson and Ettinger (1991) Model for Subs urface Vapor Intrusion into Buildings spreadsheet models ( http://www.epa.gov/oswer/riskassessment/airmodel/johnson_ettinger.htm ) and the accompanying User’s Guide for Evaluating Subsurface Vapor Intrusion into Buildings (USEPA, 2004a).

This table can be found on EPA Regions 3, 6, and 9 websites ( http://www.epa.gov/reg3hwmd/risk/human/rbconcentration_table/index.htm ; http://www.epa.gov/earth1r6/6pd/rcra_c/pd-n/screen.htm ; and http://www.epa.gov/ region09/waste/sfund/prg/index.html ).

3 92. BACKGROUND ON DERIVATION OF INHALATION TOXICITY VALUES

For all exposure routes, there are generally two approaches for deriving toxicity values. One involves the derivation of a reference value (e.g., RfC or RfD), wh ile the other involves derivation of a predictive cancer risk estimate (e.g., an oral or i nhalation CSF, such as an IUR). For the inhalation route, both approaches rely on EPA’s Inhalation Dosimetry Methodology for the extrapolation of experimental concentrations to HECs. This extrapolation is described in Section 2.1 and its subsections. The approaches for deriving a toxicity value from the HEC are described in Sections 2.2 and 2.3 and differ depending on the type of toxicity value (e.g., RfC, IUR). This information is provided for background purposes only. The procedures outlined in Section 2 are typically performed by IRIS chemical managers or by inha lation toxicologists at the National Center for Environmental Assessment’s (NCEA’s) Superf und Health Risk Technical Support Center (STSC) rather than as part of a baseline risk assessment.

2.1 Application of Inhalation Dosimetry

The Inhalation Dosimetry Methodology recognizes a hierarchy of approaches that can be used for determining the HEC that is used to derive the RfC or IUR. Generally, the pr eferred approach is to use physiologically-based pharmacokinetic (PBPK) models. 10 With sufficient data, a PBPK model is capable of calculating the amount of the chemical that reaches the target organ in an animal from any exposure scenario and then estimating what human exposure would result in this same amount of chemical reaching the target organ (i.e., the HE C). PBPK models can also be used to derive continuous ECs from human and animal studies with less-than-continuous exposures. Because constructing a valid PBPK model is an informa tion-intensive process that typically requires substantial chemical-specific data, this approach has rarely been used (USEPA, 2004b); an example can be found in the IRIS file fo r vinyl chloride (USEPA, 2000a). In cases where a complete PBPK model is not available, an intermediate model rely ing on certain chemical-specific data may be used (USEPA, 1994). 11

If the database to support the pref erred approach is inadequate, an alternative approach, called the Default Chemical Category-Specific Method can be used. This method in corporates the use of limited or categorical chemical-specific and ph ysiological information. The default method is discussed below, followed by the procedures outlined in the Inhalation Dosimetry Methodology for deriving the RfC and IUR as they apply to the interpretation of animal and human data.

10 EPA defines PBPK models in the IRIS glossary as a model that estimates the dose to a target tissue or organ by taking into account the rate of absorption into the body, distribution among target organs and tissues, metabolism, and excretion (USEPA, 2008b). For further information about PBPK modeling, please refer to Approaches for the Application of Physiologically Based Pharmacokinetic Models and Supporting Data in Risk Assessment (USEPA, 2006a).

11 The Inhalation Dosimetry Methodology recognizes the existence of alternate approaches in addition to the two presented in this guidance. The PBPK approach is generally pr eferred. In the absence of such a model, alternate models may be more optimal than the default approach when defa ult assumptions or parameters can be replaced by more detailed, biologically-motivated descriptions or actual data, respectively. For instance, a model may be considered more optimal if it incorporates chemical or species-specific in formation or if it accounts for mechanistic determinants. See Table 3-6 in the Inhalation Dosimetry Methodology for more details on the hierarchy of approaches (EPA, 1994, page 3­ 40).

42.1.1 Default Approach - Extrapolation from Experimental Animal Data

The default method involves a two-step procedure th at uses limited or categorical chemical-specific and physiological information to calculate the HEC. First, the chosen point of departure (POD) from the experimental data for a chemical is adjusted to derive a concentration intended to represent an equivalent dose under conditions of continuous exposure (7 days a week, 24 hours a day). 12 In the second step, this concentration is then multiplie d by a Dosimetric Adjustment Factor (DAF) to generate the HEC. Further details on each step are outlined below.

2.1.1.1 Duration Adjustment to Continuous Exposure

Most of the inhalation studies of laboratory animals used to deri ve RfCs and IURs involve an exposure regimen of four to six hours per day, five to seven days per week, for 13 weeks or more (equivalent to 10 percent or more of the lifetime of the animal). The POD concentration from an animal study is mathematically ad justed to reflect an equivalent dose under conditions of continuous
exposure. 13 Adjustment of duration to a continuous exposure scenario is re gularly applied as a default procedure to studies with repeated exposures but not to single-exposure inhalation toxicity studies in animals (USEPA, 1994). Operationa lly, this is accomplis hed by applying a c x t product (where “ c” is concentration, and “ t” is duration of exposure) for both the number of hours in a daily exposure period and the number of days per week that the exposure is experienced. For example, if exposure in a particular study wa s 6 hours per day, 5 days per wee k, the experimental exposure is multiplied by 6/24 x 5/7 to calculate an equivale nt continuous exposure. The general equation provided in the Inhalation Dosimetry Methodology (USEPA, 1994, Equation 4-2) for calculating duration-adjusted expos ure levels in mg/m 3 for experimental animals is presented below.

NOA E L [A D J ] = E x D x W (Equation 1)

Where: NOAEL [A DJ] (m g/m 3 ) = the NOAEL or analogous exposure leve l obtained with an alternate approach (e.g., LOAEL , LEC 10 ), adj usted for duration of experime n tal regimen; E (mg/ m 3 ) = the NOAEL or analogous exposure level observed in the experimental study; D (h/h) = number of hours exposed/24 hours; an d W (days/days) = numb e r of days of exposure/7days.

Using the example above, the assumption is that the product of c x t , not concentration alone, is associated with the toxicity observed. This is roughl y equivalent to implying th at if an effect occurs from a chemical at an exposure of 6 hours per day at 40 parts per million (ppm), that same effect will

12 Examples of PODs include the no-obser ved-adverse-effect level (NOAEL); the lowest-observed-adverse-effect level (LOAEL); Benchmark Concentration, Lower confidence limit (BMCL); and the Lower limit on an Effective Concentration using a 10 percent response level (LEC 10 ). For definitions of the various PODs, please refer to the IRIS glossary ( http://www.epa.gov/ncea /iris/help_gloss.htm ).

13 Continuous exposure refers to 24 hours per day, 7 days per week.

5occur at an exposure of 24 hours per day at 10 ppm. 14 Note that this adjustment always produces a lower concentration value than that administered to experimental animals. Thus, as stated in A Review of the Reference Dose and Reference Concentration Processes (hereafter, the RfD/RfC Review ), application of this procedur e results in an automatic margin of protectiveness for chemicals for which concentration alone may be the more appropriate dose metric, and it reflects the maximum dose for chemicals for which total or cumulative dose is the appropriate measure (USEPA, 2002c). If a different procedure is used to calculate the continuous exposure , it should be fu lly discussed in the relevant technical support document for the chemical (e.g., IRIS prof ile, Provisional Peer Reviewed Toxicity Values (PPRTVs) Assessmen t). For additional discussion, including the uncertainties associated with this approach, see Section 4.3.2 of the Inhalation Dosimetry Methodology and Section 4.4.2.1 of the RfD/RfC Review (USEPA, 2002c).

2.1.1.2 Dosimetric Adjustment to Hu man Equivalent Concentration

Typically, the adjusted POD concentration from the animal study is next conve rted to an HEC using the following equation (U SEPA, 1994, Equation 4-3):

NOAEL [HEC] = NOAEL [ADJ] x DAF (Equation 2)

Where: NOAEL [HEC] (mg/m 3 ) = the NOAEL or analogous exposure level obtained with an alternate approach, dosimetrically adjusted to an HEC; NOAEL [ADJ] (mg/m 3 ) = the NOAEL or analogous exposure level obtained with an alternate approach, adjusted for duration of experimental regimen; and DAF = Dosimetric Adjustment Factor for the specific site of effects (e.g., respiratory tract region or extra-respiratory).

The DAF is typically based on rati os of animal and human physiol ogic parameters. The specific DAF used depends on the nature of the contaminant (e.g., particle or gas) and the target site where the toxic effect occurs (e.g., respiratory tract ora location in the body remote from the portal-ofentry). For example, the DAF can be based on either the Regional Gas Dose Ratio (RGDR), for gases with respiratory effects, or the Regional Deposited Dose Ratio (RDDR) for particles.

Table 2 provides information on the site of effects for the different ch emical types. It also lists the physiologic parameters considered when calcu lating the DAF for specific regions of the body. 15 In addition, the table provides referenc es to the equations from the Inhalation Dosimetry Methodology used in deriving the DAFs. Figure 1 provides a sche matic of the human respiratory tract, illustrating each of the different regions.

14 This assumption is based on Haber = s Law, which states that A the incidence and/or severity of an adverse health effect depends on the total exposure to a potentially toxic substance. Total exposure ( K ) is the concentrati on of the substance ( c ) times the duration time of exposure ( t ), (i.e., c x t=K ) @ (Gaylor, 2000).

15 The three main regions of the respiratory tract include the following: 1) Extrathoracic (includes nose, mouth, nasopharynx, oropharynx, laryngopharynx, and larynx); 2) Tracheobronchial (includes trachea, bronchi, and bronchioles); and 3) Pulmonary (includes respiratory bronch ioles, alveolar ducts, alveolar sacs and the alveoli).

67 TABLE 2 CONTAMINANT PROPERTIES AND DOSIMETRIC ADJUSTMENT FACTORS a

Chemical Type Site of Effects Parameters Considered in Derivation of DAF for Regions of the Body b DAF Equation Numbers in Inhalation Dosimetry Methodology c

Category 1 Gases (e.g., acrolein, hydrogen fluoride, chlorine) Respiratory -Minute volume (ETh, TB) -Surface area (ETh, TB, PU) -Mass transport coefficient (TB, PU) -Fraction of inhaled chemical penetrating the respiratory region (PU) -Alveolar ventilation rate (PU) 4-18 (ETh), 4-21 & 4-22 (TB), 4-28 (PU)

Category 2 Gases (e.g., acetonitrile, xylene, propanol, isoamyl alcohol) Respiratory and Remote -Mass transport coefficients (ETh, TB) -Blood:gas partition coefficient (ET, TB, ER) -Cardiac output (ETh, TB, ER) -Alveolar ventilation rate (PU) -Surface Area (PU) -Minute volume (ER) 4-18 (ETh), 4-21 & 4-22 (TB), 4-28 (PU), 4-48 (ER) d,e

Category 3 Gases (e.g., benzene, styrene) Remote Blood:gas partition coefficient (ER) 4-48 d

Particles Respiratory and Remote -Minute volume (TOT, ER) -Surface area (TOT) -Fractional deposition of particle (TOT, ER) -Body weight (ER) -Inhaled concentration (ER) 4-14 (TOT), 4-15 (ER)

a Due to the complexities inherent in evaluating the health effects associated with exposure to gases, no definitive or comprehensive list of Category 1, 2, or 3 gases is availa ble. Risk assessors should consult with an inhalation toxicologist in order to classify a specific gas as Category 1, 2, or 3, since there is overlap between the sites of effects and the parameters considered in deriving the DAF for different regions of the respiratory tract.
b Additional discussion of the terms used in this table can be found in the Inhalation Dosimetry Methodology

. c The Inhalation Dosimetry Methodology provides equations for deriving DAFs for the different contaminant categories. The equations listed in this table are the default equations for each specific region in the body.
d This refers to Equation 4-48 that is found on page 4-60 of the Inhalation Dosimetry Methodology

. e The equations presented for Category 2 gases in the Inhalation Dosimetry Methodology contain errors. Therefore, this table refers to the equations for Category 1 and 3 ga ses, which are expected to cover respiratory and remote effects from Category 2 gases. Acronyms: ETh = Extrathoracic; TB = Tracheobronchial; PU = Pulmonary; ER = Extra-respiratory; TOT = Total respiratory system.8 FIGURE 1 HUMAN RESPIRATORY TRACT

Source: EPA (1994), Figure 3-1, Page 3-5.

Category 1 gases are highly water-so luble and/or are rapidly irrevers ibly reactive in the respiratory tract (e.g., acrolein, hydrogen fluorid e, chlorine). They do not significantly accumulate in the blood, and therefore their effects are usually exclus ively respiratory (USE PA, 1994). The DAF for Category 1 gases consists of an RGDR and is based on the animal to human ratio of the minute volume (V e ) divided by the surface area (SA) of the region of the respiratory tract where the effect

occurs. 16 See Appendix A, Sections 1, 2, and 3 of this guidance for examples of specific Category 1 DAF equations.

16 For the purposes of this document, the V e is defined as the total ventilation pe r minute and equals the product of the tidal volume (the air volume entering or leaving the lung s with a single breath) a nd the respiratory frequency.Category 3 gases are relatively water-insoluble and are unreactive in the respiratory tract (e.g., benzene, styrene). Their toxicity is generally at sites remote to the resp iratory tract (USEPA, 1994). The DAF for Category 3 gases is based on the ratio of the animal blood:gas partition coefficient (H b/g-animal ) and the human blood:gas partition coefficient (H b/g-human ). See Appendix A, Section 4 of this guidance for an example of a Category 3 DAF equation.

Category 2 gases are moderately wate r-soluble and may be rapidly reve rsibly reactive or moderately to slowly irreversibly reactive in respiratory tract tissue (e.g., acetonitrile, xylene, propanol, isoamyl alcohol). These gases have potential for significant accumulation in the blood, so they can exhibit both respiratory and remote toxicity (USEPA, 1994) . The DAF for respiratory effects of Category 2 gases consists of an RGDR and is base d on the animal to human ratio of the V e and the SA of the region of the respiratory tract wher e the effect occurs, as for Category 1 gases. The DAF for extrarespiratory (ER) effects of a Category 2 gas is based on the ratio of the H b/g-animal and the H b/g-human , as for Category 3 gases.

Particles also vary by solubility and reactivity. Ho wever, the default equations used to estimate the predicted regional deposition fractions for par ticles are based on non-soluble, non-hygroscopic particles (USEPA, 1994, Section 4.3.5.3). The DAF for a particle causing an effect in the respiratory tract is the RDDR r . The RDDR r is based on the animal to human ratio of the V e and the fractional deposition of the particle in that region (F r ), divided by the SA r of the region where the effect occurs. This derivation, from the Inhalation Dosimetry Methodology, conservatively assumes that 100 percent of the deposited dose re mains in the respiratory tract; clearance mechanisms are not considered. The DAF for a particle causing an ER effect, the RDDR ER , is based on the animal to human ratio of the V e and the total deposition of the partic le in the entire respiratory tract (F total ), divided by BW (USEPA, 1994). The RDDR ER

assumes that 100 percent of the deposited dose in the entire respiratory tract is available for uptake into the systemic circulation. See Appendix A, Section 5 for examples of specific particle DAF equations.

2.1.2 Default Approach - Extrapolation from Human Occupational Data

When human data are available to derive an RfC, duration adjustments are often required to account for differences in exposure scenar ios (e.g., extrapolation from an 8 hour/day occupational exposure to a continuous chronic exposure). Th e default approach recommended by the Inhalation Dosimetry Methodology for adjusting the POD concentration (e .g., the no observable a dverse effect level (NOAEL)) obtained from human study data is provided belo w in Equation 3 (USEPA, 1994, Equation 4-49). 17,18

17 If sufficient data are available, a PBPK model or interm ediate approach using chemical -specific information may be employed in preference to the default method for extrapolating human occupational data to an HEC.

18 EPA’s IRIS glossary defines an adverse effect as the following: “A biochemical change, functional impairment, or pathologic lesion that affects the performance of the whole organism, or reduces an organism's ability to respond to an additional environmental challenge” (USEPA, 2008b).

9NOAEL [HEC] = NOAEL x (VEho/VEh) x 5 days/7 days (Equation 3)

Where: NOAEL [HEC] (mg/m 3 ) = the NOAEL or analogous exposure level obtained with an alternate approach, dosimetrically adjusted to an ambient HEC; NOAEL (mg/m 3 ) = occupational exposure level (time-weighted average over an 8-hour exposure period); VEho = human occupational default minute volume over 8 hours (10 m 3 ); and VEh = human ambient default minute volume over 24 hours (20 m 3 ).

2.2 Derivation of the Inhalation Unit Risk

The default approach for determining pred ictive cancer risk recommended by EPA’s Guidelines for Carcinogen Risk Assessment (USEPA, 2005a; hereafter, Cancer Guidelines ) is a linear extrapolation from exposures observed in the animal or human occupational study. 19 This approach involves drawing a straight line from the POD to the orig in. The default linear ex trapolation approach isgenerally considered to be conservatively protective of public health, including sensitive subpopulations (USEPA, 2005a). The slope of this line is commonly called the slope factor, and when the units are risk per μg/m 3 , it is also called the IUR. EPA defi nes an IUR in the IRIS glossary as “the upper-bound excess lifetime cancer risk estimated to result from continuous exposure to an agent at a concen tration of 1 μg/m 3 in air” (USEPA, 2008b). Equati on 4 below presents a linear extrapolation from a POD of 10 percent response (LEC 10 ). 20

IUR = 0.1/LEC 10[HEC] (Equation 4)

Where: IUR ( μ g/m 3 ) -1 = Inhalation Unit Risk; and LEC 10[HEC] ( μ g/m 3 ) = the lowest effective concentration using a 10 percent response level, dosimetrically adjusted to an HEC.

2.3 Derivation of the Reference Concentration

EPA defines an RfC in the IRIS glossary as “an estimate (with uncertain ty spanning perhaps an order of magnitude) of a con tinuous inhalation exposure to th e human population (including sensitive subgroups) that is likely to be without appreciable ri sk of deleterious effects during a lifetime” (USEPA, 2008b). The RfC is derived after a review of the health effects database for a chemical and identification of the most sensitive a nd relevant endpoint along with the principal study or studies demonstrating that e ndpoint. EPA Chemical Managers us e UFs to account for recognized

According to the Cancer Guidelines , “[a] nonlinear approach should be selected when there are sufficient data to ascertain the mode of action [MOA] and conclude that it is not linear at low doses and the agent does not demonstrate mutagenic or other activity consistent with linearity at lo w doses” (USEPA, 2005a, page 3-22). In addition, [l]inear extrapolation should be used when there are MOA data to i ndicate that the dose-response curve is expected to have a linear component below the POD” (USEPA, 2005a, page 3-21). This information will appear on the IRIS profile or other toxicological information source fo r a chemical. Chemicals with a muta genic MOA are thought to pose a higher risk during early life. Procedures fo r assessing cancer risk from these che micals are outlined in Section 5.1.

20 The POD used in Equation 4 is an LEC 10 , which is the lower 95 percent conf idence limit on the concentration corresponding to a 10 percent response rate (i.e., the EC 10 ). Other PODs may be substitute d for this value, which could be associated with alternative response levels (e.g., 1 percent, 5 percent).

10 19uncertainties in the extrapolations from the experimental data condi tions to an estimate appropriate to the assumed human scenario (U SEPA, 1994). See Table 3 for a desc ription of the standard UFs. The formula used for deriving the RfC from the HEC is provided below.

RfC = NOAEL [HEC] /(UF) 1 (Equation 5)

Where: RfC (mg/m 3 ) = Reference Concentration NOAEL [HEC] (mg/m 3 ) = The NOAEL or analogous exposure level obtained with an alternate approach, dosimetrically adjusted to an HEC; and UF = Uncertainty factor(s) applied to account for the extrapolations required from the characteristics of the experimental regimen.

1 Some toxicological information sources for RfCs will incorporate an additional factor to account for deficiencies in the available data set, called a modifying fa ctor (MF). In 2002, ho wever, EPA published the RfD/RfC Review, which recommended that the use of MFs be discontinued be cause their purpose is “sufficiently subsumed in the general database UF” (USEPA, 2002c, page xviii). Therefor e, RfCs published subsequent to this document will not include MFs.

11TABLE 3 THE USE OF UNCERTAINTY FACTORS IN DERIVING AN INHALATION REFERENCE CONCENTRATION Standard UFs Processes Cons idered in the UF Purview H = Human to sensitive human: Extrapolation of valid experimental results from studies using prolonged exposure to average healthy humans. Intended to account for the variation in sensitivity among the members of the human population. -Pharmacokinetics/Pharmacodynamics -Sensitivity 2 -Differences in body weight (age, obesity) -Concomitant exposures -Activity pattern -Does not account fo r idiosyncrasies A = Animal to human: Extrapolation from valid results of long-term studies on laboratory animals when results of studies of human exposure are not available or are inadequate. Intended to account for the uncertainty in extrapolating laboratory animal data to the case of average healthy humans. -Pharmacokinetics/Pharmacodynamics -Relevance of laboratory animal model -Species sensitivity

S = Subchronic to chronic: Extrapolation from less-thanchronic exposure results on laboratory animals or humans when there are no useful long-term human data. Intended to account for the uncertainty in extrapolating from less than chronic NOAELs to chronic NOAELs. -Accumulation/Cumulative damage -Pharmacokinetics/ Pharmacodynamics -Severity of effect -Recovery -Duration of study -Consistency of effect with duration L = LOAEL to NOAEL: Derivation from a LOAEL instead of a NOAEL. Intended to account for the uncertainty in extrapolating fr om LOAELs to NOAELs. -Severity -Pharmacokinetics/Pharmacodynamics -Slope of dose-response curve -Trend, consistency of effect -Relationship of endpoints -Functional vs. histopathological evidence -Exposure uncertainties D = Incomplete to complete data: Extrapolation from valid results in laboratory animals when the data are “incomplete.” Intended to account for the inability of any single laboratory animal study to adequately address all possible adverse outcomes in humans. 1 -Quality of critical study -Data gaps -Power of critical study/supporting studies -Exposure uncertainties

1 The RfD/RfC Review indicates that this UF accounts for the potential for deriving an underprotective RfD/RfC as a result of an incomplete characterization of the chemical’s toxicity or if th e existing data suggest that a lo wer reference value might resul t if additional data were available (considering both the lacking and av ailable data for particular organ systems as well as life st age) (USEPA, 2002c). 2 The RfD/RfC Review also stresses that susceptible populations and life st ages are accounted for with this UF (USEPA, 2002c). Source: USEPA, 1994, Table 4-9, page 4-77.

123. CHARACTERIZING EXPOSURE

3.1 Introduction

This section describes an approach for characterizing exposure in a ba seline risk assessment that is consistent with the Inhalation Dosimetry Methodology . The approach involves the estimation of exposure concentrations (ECs) for ea ch receptor exposed to contamin ants via inhalation in the risk assessment. ECs are time-weighted average con centrations derived from measured or modeled contaminant concentrations in air at a site, adju sted based on the characteristics of the exposure scenario being evaluated. 21,22

Equations for estimating ECs are provided below. This document does not provide default input values for the exposure parameters referenced in these equations. EPA recommends the use of sitespecific exposure values consistent with the expo sure pathways and receptors at a site wherever practicable and appropriate. If a risk assessor opts to rely on default exposure i nput values, current Superfund-supported values may be found at th e exposure assessment portion of the Superfund website: ( http://www.epa.gov/oswer/risk assessment/superfund_hh_exposure.htm ).

3.2 Estimating Exposure Concentrations for Assessing Cancer Risks

The estimation of an EC when assessing cancer risks characterized by an IUR involves the CA measured at an exposure point at a site as well as scenario-specific parameters, such as the exposure duration and frequency. 23 The EC typically takes the form of a CA that is time-weighted over the duration of exposure and incorporates information on activity patterns for the sp ecific site or the use of professional judgment. The equation for estima ting an EC for use with an IUR is presented below.

21 The default method for deriving inhalation toxicity values also involves calculating time-weighted ECs, as discussed in Sections 2.1.1.1 and 2.1.2.

22 The ECs in this document are in units of μg/m 3 . Inhalation toxicity values presented on IRIS are typically expressed in units of μg/m 3 or mg/m 3 , which are mass units. Some regulatory contexts require the use of volumetric units such as ppm. The conversion from mass units to volumetric units depends on the molecular weight (MW) of the material as well as the ambient temperature and atmospheric pressure. To convert from ppm to mg/m 3 , the following equation can be used: ppm × MW

= mg / m 3 ; where MW is the molecular weight of the gas and V is the volume of 1 gram molecular V weight of the airborne contaminant. This is derived by the formula V = RT/P; where R is the ideal gas constant, T is the temperature in Kelvin (K = 273.16 + T°C) and P is the pressure in mm Hg. The value of R is 62.4 when T is in Kelvin, (K = 273.16 + T°C), the pressure is expressed in units of mm Hg and the volume is in liters. The value of R differs if the temperature is expressed degrees Fahrenheit (°F) or if other units of pressure are used (e.g., atmospheres, kilopascals).

23 ECs are typically based on either estimated (i.e., modele d) or measured contaminan t concentrations in air.

13EC = (CA x ET x EF x ED)/AT (Equation 6)

Where: EC ( μ g/m 3 ) = exposure concentration; CA ( μ g/m 3 ) = contaminant concentration in air; ET (hours/day) = exposure time; EF (days/year) = exposure frequency; ED (years) = exposure duration; and AT (lifet ime in years x 365 days/year x 24 hours/day) = averaging time

3.3 Estimating Exposure Concentrations for Calculating Hazard Quotients

When estimating ECs for non-cancer or cancer h azards characterized by an HQ, risk assessors should match each exposure scenario at a site to the appropriate EC equation, based on the scenario duration and frequency of exposure. 24 Figure 2 presents a flowchart to assist risk assessors with this process and provides recommended e quations that can be used to estimate the EC for each type of scenario. 25 As shown in Figure 2, the recommended pr ocess for estimating ECs to be used in calculating an HQ involves the following three steps: 1) assess the duration of the exposure scenario; 2) assess the exposure pattern of the exposure scen ario; and 3) estimate the scenario-specific EC.

3.3.1 Step 1: Assess Duration

The first step in the recommended process of estima ting an EC for use in calculating an HQ involves assessing the duration of the exposure scenario at a site. Step 1 in Figure 2 indicates that the risk assessor first should decide whet her the duration of th e exposure scenario is generally acute, subchronic, or chronic. Toxicologists have long b een aware that effects from a single or short-term exposure can differ markedly from effects resulti ng from repeated exposures. The response by the exposed person depends upon factors such as whether the chemical accumulates in the body, whether it overwhelms the body’s mechanisms of detoxification or elim ination, or whether it produces irreversible effects (E aton & Klaassen, 2001). Therefore, ideally, the chemical-specific elements of metabolism and kinetics , reversibility of effects, and r ecovery time should be considered as part of this recommended pro cess when defining the duration of a site-specific exposure scenario.

24 Traditionally, the HQ approach was limited to non-cancer h azard assessment. However, the HQ approach may also be appropriate for carcinogens with a non-linear mode of action. The 2005 Cancer Guidelines state the following on this subject: "For cases where the tumors aris e through a nonlinear mode of action, an oral reference dose or an inhalation reference concentration, or both, should be developed in accordance with EPA’s established practice for developing such values ... this approach expands the past focus of such reference values (previously reserved for effects other than cancer) to include carcinogenic effects determined to have a nonlinear mode of action" (USEPA, 2005a; page 3-24).

25 Figure 2 was developed for the evaluation of inhalation expos ures. While the concepts presented in this flowchart may be useful for assessing other exposure routes (e.g., oral or dermal), these other routes are beyond the scope of this document, and therefore, are not explicitly considered. Caution should be used when using Figure 2 to evaluate other exposure routes, as considerations beyond those outlined in th e flowchart may apply (e.g., time to reach steady state for dermal exposures).

14To the extent possible, exposure durations (EDs) ev aluated in a site-specific risk assessment should be consistent with the ED repres ented by the toxicity value. Howe ver, frequencies or durations of human exposures often are not as clearly defined as those in animal studies with controlled exposures, particularly for intermittent exposures . For example, the emission of some volatile chemicals into the ambient air may vary with temperature and season, providing fluctuating exposures for humans living near the source. Theref ore, risk assessors should use best professional judgment to determine if the ED in a given scenario is reasonably similar to the duration associated with the toxicity value. Risk assessors should desc ribe the uncertainties associated with their choice of toxicity value in the risk characterization sec tion of the risk assessment (see Section 9.2.2 of this document). For situations where duration-appropriate toxicity values are not available, please follow the procedures outlined in Section 4.2 and Appendix C of this document.

The specific definition for each exposure duration category may vary depending on the source of the toxicity value being used. For Tier 1 toxicity values obtained from EPA’s IRIS database, acute exposures are defined as lasting 24 hours or less; subchronic expos ures are defined as repeated exposures by the oral, dermal, or inhalation rout e for more than 30 days, up to approximately 10 percent of the human lifespan; a nd chronic exposures are defined as repeated exposures for more than approximately 10 percent of the human lifespan (USEPA, 2008b). 26, 27

After deciding which duration the exposure scenario most closely matches, risk assessors should then proceed to Step 2, following the path of the sele cted duration. Note that if an acute duration is selected, risk assessors should proc eed directly to Step 3 to estim ate an acute EC for each acute exposure period.

3.3.2 Step 2: Assess Exposure Pattern

Step 2 of the recommended process for estimating an EC for use in a hazard quotient involves assessing the exposure pattern for each exposure scen ario at a site. This entails comparing the exposure time and frequency at a si te to that of a typical subchr onic or chronic toxicity test. 28

26 Note that other sources of toxicity values may define exposures differently. For example, the Agency for Toxic Substances and Disease Registry (ATSDR) (which publishes Minimal Risk Levels (MRLs)) defines acute exposures as occurring from one to 14 days, intermediate exposures as greater than 14 to 364 days, and chronic exposures as 365 days or longer. However, the toxicity values are based on th e same underlying toxicological concepts described in this section.

27 Exposures with a duration lasting between 24 hours and 30 days should be treated as subchronic for the purposes of this document.

28 Exposure regimens vary from study to study. Risk assessors should use best professional judgment to determine if the exposure pattern in a given scenario is reasonably simila r to a typical regimen for a subchronic or chronic study.

15FIGURE 2RECOMMENDED PRMMENDED PROCEDURE FOCEDURE FOR DERIVING EXPOSURECONCENTRATIONS AND HAZARD QUOTIENTS FORINHALATION EXPOSURE SCENARIOS

S s s s e s n oIs the

A a t iduration of the exposureduration of the exposure

:

1 r uAcutescenarios generally acute,scenarios generally acute,Chronic Chronic

p

eS t D(e.g., minutes/subchronic, orsubchronic, or(e.g., many years)*(e.g., many years)*

Shours to days)*chronic?chronic?SubchronicSubchronic

e r n(e.g., weeks to years)*(e.g., weeks toyears)*

2 : A s s e s s E x p o s u r e P a t t 2 : A s s e s s E x p o s u r e P a t tNoIs theAre there Are thereEF generallyEF generally1 or more periods1 or more periodsat least as frequent as aat least as frequent as aof exposure, each of which isof exposure, each of which isNochronictoxicity test or anchronicgenerally at least asgenerally at least as frequent frequentoccupational studyoccupational studyas asubchronictoxicity testsubchronictoxicity test(e.g., 6-8 hrs/day,(e.g., 6-8 hrs/day,(e.g., 6-8 hrs/day,(e.g., 6-8 hrs/day,5 days/wk,5 days/wk,5 days/wk)?H50 wks/yr)?†

a t e E C e C S t e pCalculateacuteEC & HQs forCalculateEC & HQs forYesYesCalculatesubchronicEC & HQs forsubchronicEC & HQs forCalculatechronicEC & HQchronicEC & HQ

t i meach acute exposure periodeach acute exposure periodeach subchronic exposure periodeach subchronic exposure periodEquation 8Equation 7Equation 7Equation 8Equation 8Equation 12

E sEquation 12Equation 12Equation 12[Repeat for each chemical]

t e p 3 : p :[Repeat for each chemical][Repeat for each chemical]*The specific definition for each duration category may vary depending on the source of the toxicity value being used.For Tier1 toxicity values obtained from IRIS:acuteexposures are defined as those lasting 24 hours or less;subchronicexposures are defined as repeated exposures for more than 30 days, up to approximately 10 percent of the life span in humans; andchronicexposures are defined as repeated exposures for more than approximately 10 percent of the life span in humans (EPA, 2008b).For the purposes of this document, short-term exposures, defined by the IRIS glossary as repeated exposures for more than 24 hours, up to 30 days, should be treated as subchronic.HExposure regimens vary from study to study. Risk assessors should use best professional judgment to determine if the exposure pattern in a given scenario is reasonably similar to atypical regimen for a chronic or subchronic study.[Repeat for each chemical]16For exposure scenarios with a subc hronic duration, risk assessors s hould follow the center path on the flowchart. Step 2 in this path asks whether there are one or more peri ods of exposure, each of which is generally as frequent as a subchronic toxi city test (e.g., 6-8 hours per day, 5 days per week). If the exposure scenario matches this descriptio n, risk assessors should proceed to Step 3 and estimate a subchronic EC for each subchronic exposur e period. However, if the exposure pattern contains periods that are significantly shorter and/ or involve significantly less frequent exposures than indicated in the flow chart, risk assessors should derive acute ECs for each of these exposure periods. If it is difficult to determine whether a specific exposure scenario is best modeled as a subchronic exposure or as a series of independent acute exposures, due to uncertainty in the time required to return to baseline foll owing exposure, risk assessors ma y want to derive ECs using both approaches.

If the exposure scenario has a chronic duration, risk assessors should follow the right hand path on the flowchart. Step 2 in this path asks whether the exposure frequency (EF) is generally as frequent as a chronic animal toxicity test or a human occupational study (e .g., 6-8 hours per day, 5 days per week, for 50 weeks per year). If the exposure s cenario matches this description, risk assessors should proceed to Step 3 and estim ate a single chronic EC. Howe ver, if the scenario differs significantly from this pattern, risk assessors shoul d proceed to the se cond question under the subchronic duration path and proceed as outlined above.

3.3.3 Step 3: Estimate Exposure Concentration

Step 3 of the recommended process involves estimati ng the EC for the specific exposure scenario based on the decisions made in Steps 1 and 2. For acute exposur es, the EC is equal to the CA. Risk assessors can estimate an acute EC for each acute exposure period at a site using Equation 7. For longer-term exposures, risk assessors should take into c onsideration the exposure time, fre quency, and duration for each receptor being evaluated as well as the peri od over which the exposure is averaged (i.e., the averaging time (AT)) to arrive at a time-weighted EC. If there are one or more exposure periods that are generally as frequent as a subchronic toxicity test, risk assesso rs should use Equation 8 to estimate a subchronic EC for each of these exposure periods. (Exposure peri ods with significantly less freque ncy should be treated as acute exposures.) If the exposure pattern is generally as frequent as a chroni c toxicity test of an occupational study, risk assessors should use Equation 8 to estimate a single chronic EC for the duration of the exposure.

Acute Exposures

EC = CA (Equation 7)

Where: EC ( μ g/m 3 ) = exposure concentration; CA ( μ g/m 3 ) = contaminant concentration in air;

17Chronic or Subchronic Exposures

EC = (CA x ET x EF x ED)/AT (Equation 8)

Where: EC ( μ g/m 3 ) = exposure concentration; CA ( μ g/m 3 ) = contaminant concentration in air; ET (hours/day) = exposure time; EF (days/year) = exposure frequency; ED (years) = exposure duration; and AT (ED in years x 365 days/year x 24 hours/day) = averaging time

Note: If the duration of the exposure period is less than one year, the units in the above equation can be changed to the following: EF (days/week); ED (weeks/exposure period); and AT (hours/exposure period).

It is important to use the EC equation that most closely matches the exposur e pattern and duration at a site. For instance, if the exposure pattern at a site consists of a series of short (e.g., 4-hour) periods of high exposure separated by several days of no exposure, the approach ou tlined above recommends estimating an acute EC for each acute exposure period. If the chronic EC equation (Equation 8) were to be used instead, the result would be an average EC value that may lead to an underestimate of risk since the inhaled concentrations could be higher than acut e toxicity values during periods of
exposure.

3.4 Estimating Exposure Concentratio ns in Multiple Microenvironments

When detailed information on the activity patterns of a receptor at a si te is available, risk assessors can use these data to estimate the EC for either non-carcinogenic or carcinogenic effects. The activity pattern data describe how much time a receptor spends, on average, in different microenvironments (MEs), each of which may ha ve a different contaminant concentration level. 29 By combining data on the contaminant concentrati on level in each ME and the activity pattern data, the risk assessor can calculate a tim e-weighted average EC for a recepto r. Because activity patterns (and hence, MEs) can vary over a receptor’s lifetim e, EPA recommends that risk assessors pursuing the ME approach first calculate a time-weighted average EC for each expos ure period characterized by a specific activity pattern (e.g., separate ECs for a school-aged child reside nt and a working adult resident). These exposure period -specific ECs can then be combined into a longer term or lifetime average EC by weighting the EC by the duration of each exposure period. The following sections further explain these two steps.

3.4.1 Using Microenvironments to Estimate an Average Exposure Concen tration for a Specific Exposure Period

The ME approach can be used to estimate an av erage EC for a particular exposure period during which a receptor has a specified act ivity pattern. As a simplified example, a residential receptor may

29 EPA defines a microenvironment in Air Quality Criteria for Particulate Matter: Volume II as a defined space that can be treated as a well-characterized, relatively homogeneous lo cation with respect to pollutant concentration for a specified time period (e.g., rooms in homes, restaurants, schools, offices, inside vehicles, or outdoors) (USEPA, 2004b).

18be exposed to a higher concentration of a contaminan t in air in the bathroom for 30 minutes per day while showering, and exposed to a lower concentra tion in the rest of the house for the remaining 23.5 hours per day. In this case, risk assessors can use the CA value experienced in each ME weighted by the amount of time spent in each ME to estimate an average EC for the period of residency in that house using Equation 9. 30 This approach may also be used to address exposures to contaminants in outdoor and indoor environments at sites where both indoor and outdoor samples have been collected or where the vapor intrusion pathway has been characterized.

n EC j = 

# ∑ ( CA i x ET i x EF i 

## ) x ED j /AT j (Equation 9)

i =

1 Where: EC j ( μ g/m 3 ) = average exposure concentration for exposure period j; CA i ( μ g/m 3 ) = contaminant concentration in air in ME i; ET i (hours/day) = exposure time spent in ME i; EF i (days/year) = exposure frequency for ME i; ED j (years) = exposure duration for exposure period j; and AT j (hours) = averaging time = ED j x 24 hours/day x 365 days/year.

3.4.2 Estimating an Average Exposure Concentration Across Multiple Exposure Periods

To derive an average EC for a receptor over mu ltiple exposure periods, the average EC from each period (as calculated above in Equation 9) can be weighted by the fraction of the total exposure time that each period represents, using Equation 10. For example, when estimating cancer risks, the risk assessor may calculate a lifetime average EC where the weights of the individual exposure periods are the duration of the period, ED j , divided by the total li fetime of the receptor. Alternatively, when estimating an HQ, risk assessors can use Equation 10 to calculate less-than-lifetime average ECs across multiple exposure periods. In that case, th e AT will equal the sum of the individual EDs for all of the exposure periods.

n EC LT = 

# ∑ 

# ( EC j x ED j 

# ) /AT (Equation 10)

i =

1 Where: EC LT ( μ g/m 3 ) = long-term average exposure concentration; EC j ( μ g/m 3 ) = average exposure concentration of a contaminant in air for exposure period j; ED j (years) = duration of exposure period j; and AT (years) 1 = averaging time.

1 When evaluating cancer risk, the AT is equal to lifetime in years. When evaluating non-canc er hazard, the AT is equal to the sum of the EDs for each exposure period.

30 If one or more MEs involve acute exposures, risk assessors should conduct a supplemental analysis comparing the CA for each of those MEs to a corresponding acute toxicity value to ensure that receptors are protected from potential acute health effects.

194. SELECTING APPROPRIATE TOXICITY VALUES

After characterizing the exposure sc enarios and estimating ECs for each receptor at a site, the risk assessor should select appropriate inhalation toxi city values for each inhaled contaminant. For estimating cancer risks, this typically involves identifying and evaluating available published cancer potency estimates. For estimating HQs, this typica lly involves identifying and evaluating reference values that match the characterization of the expos ure scenario from Figure 2 (i.e., acute, subchronic, or chronic reference values).

This section provides guidance for the selection of toxicity values appropriate for assessing risk under inhalation exposure scen arios. It descri bes sources for the most cu rrent inhalation data and provides guidance for proceeding when published inhalation toxicity data are not available.

4.1 Sources for Inhalation Toxicity Data

The OSWER Directive, Human Health Toxicity Values in Superfund Risk Assessment (USEPA, 2003), provides a recommended hierarc hy of toxicological data sources to guide risk assessors when selecting appropriate toxicity values. This document sets out a recommended three-tiered framework for selecting human toxic ity values. Tier 1 consists of EPA’s IRIS, Tier 2 consists of EPA’s PPRTVs, and Tier 3 include s other toxicity valu es as recommended by NCEA, such as the California EPA toxicity values, the Agency for T oxic Substances and Diseas e Registry’s (ATSDR’s) Minimal Risk Levels (MRLs), and Health Effects Assessment Summary Table (HEAST) toxicity values. Priority in Tier 3 should be given to sources that are the mo st current and those that are peer reviewed. Consultation with th e Superfund Headquarters office is recommended regarding the use of Tier 3 values for Superfund response decisions wh en the contaminant appears to be a risk driver for the site.

The most up-to-date information on Superfund-su pported cancer potency estimates and chronic and subchronic cancer and non-cancer reference values for inhaled contaminants are available on the Superfund risk assessment website ( www.epa .gov/oswer/riskassessment/superfund_toxicity.htm ). Superfund-recommended sources for acute non-cancer toxicity values can be found at www.epa.gov/oswer/riskassessment/superfund_acute.htm

. 31

In situations where the desired reference value (e. g., acute, subchronic, chronic) is not available, risk assessors may use a reference value based on the ne xt longer duration of exposure as a conservative estimate that would be protective for a shorter-term ED (USEPA, 2002c). For example, if a risk assessor determines that an ED at a site is subchr onic, but no subchronic toxicity value is available, a chronic RfC can be used to assess hazard.

EPA recommends that toxicity values published in Superfund-supported sources should generally be used in the risk equations presen ted in this guidance, without m odification. This includes IURs on IRIS that were calculated from oral values usi ng a default ventilation ra te and BW (see Appendix B for a list of these chemicals). It is not generally appropriate to make adju stments to these values

31 In selecting an acute toxicity value, risk assessors shoul d consider the duration associated with their estimate of exposure (e.g., a 1-hour versus a 24-hour air sample). Use of a toxicity value specified for a longer duration than that of the exposure estimate may overestimate hazard, while th e use of a shorter duration acute reference value may underestimate hazard.

20based on IR and BW using the intake equation, becau se the amount of the chem ical that reaches the target site through the inhalation pa thway is not a simple function of these parameters (see Section 1.2). Use of the toxicity values listed in Appendix B should be noted in the uncertain ty section of the risk assessment (see Section 9).

4.2 Recommended Procedures for Asse ssing Risk in the Absence of Inhalation Toxicity Values

The following section provides gu idance on recommended procedures for situations where inhalation toxicity values are not available in any of the toxicity data sources described in Section 4.1.

If RfC and IUR values are not available for an inhaled contaminant, risk assessors should first contact NCEA’s STSC for guidance. 32 Risk assessors working on S uperfund sites can contact STSC to determine whether a provisional peer-reviewed t oxicity value (PPRTV) exists for a contaminant; if not, the risk assessor, in cooperation with the appropriate EPA Regional office may request that STSC develop a PPRTV document or that STSC deve lop an inhalation toxicity value as a “consult”. The latter would be specific to the site in que stion only. Additional information on STSC’s current process for developing alternat ive toxicity values is described in Appendix C.

If STSC indicates that no quantit ative toxicity information for the inhalation route is available, the risk assessor should conduct a qualit ative evaluation of this exposure route. The risk assessor should discuss in the uncertainty section of the risk assess ment report the implications of not quantitatively assessing risks due to inhalation exposures to chem icals lacking inhalation toxicity data. See the section on Risk Characterizati on (Section 9) in this guida nce for more information.

Performing simple route-to-route extrapolation without the assist ance of STSC is generally not appropriate because hazard may be misrepresented when data from one route are substituted for another without any considerati on of the pharmacokinetic differences between the routes (USEPA, 1998). The following circumstances, outlined in the Inhalation Dosimetry Methodology (page 4-6), are specific examples of s ituations when route-to-route extrapolat ion from oral toxicity values might not be appropriate, even for use during screening:

• When groups of chemicals are expected to have different toxici ty by the two routes

− for example, metals, irritants, and sensitizers;

• When a first-pass effect by the respiratory tract is expected;

• When a first-pass effect by the liver is expected;

• When a respiratory tract effect is established, but dosimetrycomparison cannot be clearly established between the two routes;

• When the respiratory tract was not adequa tely studied in the oral studies; and

• When short-term inhalation studies, dermal irri tation, in vitro studies, or characteristics of the chemical indicate the potential for portal-o f-entry effects at the respiratory tract, but studies themselves are not adequate for inhalation toxicity value development.

32 All contact with STSC should be performed by an EPA regional risk assessor. States and other entities should first contact their EPA regional risk assessor with questions on inha lation toxicity values. Regional risk assessors can then contact STSC on their behalf.

21The Cancer Guidelines (USEPA, 2005a) includes the following statement regarding route-to-route extrapolation:

“When a qualitative extrapolation can be supported, quantitative extrapolation may still be problematic due to the absence of adequate data . The differences in bi ological processes among routes of exposure (oral, inhalation, dermal) can be great because of, for ex ample, first-pass effects and different results from different exposure patterns. There is no generally applicable method for accounting for these differences in uptake processes in a quantitative route-to-route extrapolation of dose-response data in the absence of good data on the agent of interest. Therefore, route-to-route extrapolation of dose data relies on a case-by-cas e analysis of available data” (page 3-10).

5. ESTIMATING RISKS

This section provides updated equations recomme nded for estimating excess cancer risks and HQs from inhaled contaminants of concern at Superfund sites. Plea se see Section 8.2.1 of RAGS, Part A for further information about how to interp ret calculated excess cancer risks and HQs.

5.1 Cancer Risks Characterized by an Inhalation Unit Risk

The excess cancer risk for a receptor exposed via the inhalation pathway can be estimated with the following equation:

Risk = IUR x EC (Equation 11)

Where: IUR ( μ g/m 3 ) -1 = Inhalation Unit Risk; and EC ( μ g/m 3 ) = exposure concentration (See Equation 6).

When estimated ECs are above the POD used for the low dose extrapolation described in Section 2.3, a linear concentration-res ponse relationship may not hold. 33 In such situations, the risk assessor should not use toxicity values developed through low dose extrapolation techniques. Instead, the risk assessor may report semi-quantitative ri sk estimates (e.g., risks are greater than 10 -2 ) or estimate risk using the original model underlying the toxic ity value, which can be found in the technical support document for the value (e.g., IR IS profile, PPRTV Assessment).

When estimating cancer risks for children, risk asse ssors should be aware of chemicals that pose a higher risk of cancer when expos ure occurs during earl y life. If eviden ce exists suggesting differences in risk across age groups for a chemi cal, this typically will be considered in the derivation of the toxicity value and described in the chemical’s technical support document.

33 Reviews of chemical-specific IRIS files indicate that the risk level corresponding to the concentration level above which the IUR should not be used often falls at or near 10 -2 . However, this risk level varies by chemical and, therefore, risk assessors should refer to the toxicity value’s technical support document for information on the concentration range for which the IUR was intended to be used.

22Chemicals that have been determined to cause cancer by a mutagenic mode of action (MOA) are thought to pose a higher risk during early life. An EPA-recommended procedure exists for assessing risks from these chemicals. Figure 3 summarizes the recommendations of the Supplemental Guidance for Assessing Susceptibility fr om Early-Life Exposure to Carcinogens (USEPA, 2005b; hereafter Supplemental Cancer Guidelines ) on how to adjust childhood risk calculations to account for chemicals with a mutagenic MOA for carcinogenicity. Please refer to the Supplemental Cancer Guidelines (USEPA, 2005b) for a list of chemicals with a mutagenic MOA that were used in the development of that document.

In addition, EPA’s website for the “Handbook for Im plementing the Supplemental Cancer Guidance at Waste and Cleanup Sites” contains an up-to-dat e list of chemicals that EPA has determined to have a mutagenic MOA ( http://www.epa.gov/oswer/riskassessment/sghandbook/index.htm ). As chemicals receive new asse ssments for mutagenicity, this informa tion will appear in the IRIS profile or PPRTV assessment.

FIGURE 3 GUIDANCE ON ASSESSING RISK FROM EARLY-LIFE EXPOSURES FOR CHEMICALS ACTING BY A MUTAGENIC MODE OF ACTION FOR CARCINOGENICITY

If a chemical has been determined to cause cancer by a mutagenic MOA, it is possible that exposures to that chemical in early-life may result in higher lifetime cancer risks than a comparable duration adult exposure. In risk assessments of exposure to chemicals for which a mutagenic MOA for carcinogenicity has been determined by EPA and a linear low-dose extrapolation performed, one of the following generally pertains: 1) If chemical-specific data on su sceptibility from early-life exposures were available for derivation of CSFs, those slope factors are used for risk characterization, and Age Dependent Adjustment Factors (ADAFs) are not applied. 2) If chemical-specific data on susceptibility fr om early-life exposures were not available, the ADAFs are applied in calculating or es timating risks associat ed with early-life exposures (USEPA, 2005c).

If the latter case applies, the Supplemental Guidance for Assessing Susceptibility from Early-Life Exposure to Carcinogens (USEPA, 2005b) recommends the following default ADAFs be applied in risk assessments:

• 10-fold adjustment for exposures during the first 2 years of life;

• 3-fold adjustment for exposures from ages 2 to <16 years of age; and

• No adjustment for exposures af ter turning 16 years of age.

In such cases, Equation 11 can be altered to in clude the ADAFs in the fo llowing way: Risk = (IUR x EC <2 x ADAF <2 ) + (IUR x EC 2-16 x ADAF 2-16 ) + (IUR x EC >16 )

Sources: USEPA, 2005b and USEPA, 2005c. Note: All communications and factsheets pertaining to the implementation of the 2005 Cancer Guidelines can be found at www.epa.gov/osa/spc/cancer_guidelines.htm

.

235.2 Hazard Quotients

The HQ for the inhalation pathway can be cal culated with the follo wing general equation:

HQ = EC/(Toxicity Valu e 1 x 1000 μg/mg) (Equation 12)

Where: HQ (unitless) = Hazard Quotient; EC ( μ g/ m 3 ) = exposure concentratio n (See Equations 7 or 8); Toxicity Value (mg/m 3 ) = Inhalation toxicity valu e (e.g., RfC) that is appropriate for the exposure scenario (acute, su bchronic, or chronic).

1 R i s k a s s e s s o r s s h o u l d r e f e r t o t h e f l o w c h a r t ( F igure 2) to s e l e ct an ap propr i a te i nha lati on t o xicit y va lu e for the expos ure sce n a rio at a site in order to calc ul ate the HQ.

6. EXAMPLE EXPOSURE SCENARIOS

This section of the guidance includes examples of the types of exposure scenarios risk assessors may encounter when evaluating inhalatio n exposures at waste sites. Each scenario includes sample values for exposure parameters and reviews the pr ocess of estimating the EC and risks for cancer and other health effects. Thes e examples are provided for illustr ative purposes only and are not representative of every exposure scenario that could be encountered at a site. Furthermore, risk assessors should use site-specific values for exposu re parameters if practicable when estimating ECs and risk levels or HQs. This w ould typically require some inform ation on activity patterns for the specific site or the use of professi onal judgment. If default values ar e to be used for certain exposure parameters, please consult the Superfund webs ite for up-to-date in formation on Superfundrecommended default exposure parameters. 34

6.1 Residential Receptor

An example of a residential scenario could consis t of inhalation exposure fo r up to 24 hours per day, up to 350 days per year for 6 to 30 years. When estimating cancer risk for this type of scenario, Equation 6 is recommended to calculate an EC a nd Equation 11 is recommended to estimate risk. For estimating hazard quotients for cancer or non-cancer effects, this scenario can be evaluated using the steps outlined in Figure 2. The duration of this scenario ranges from 6 to 30 years, which can be considered chronic (because it consists of rep eated exposures for approximately 10 percent of a receptor’s lifespan). The frequency of this scenario is generally as frequent as a chronic toxicity test and therefore Equation 8 is recommended to deri ve a chronic EC and Equation 12 with a chronic toxicity value is recommended to calculate an HQ. If information about mu ltiple MEs is available, risk assessors should proceed according to Section 3.4 to estimate ECs to use in estimating cancer risks or HQs.

When assessing the risk under the re sidential scenario for children, the risk a ssessor should keep in mind that exposure parameters, sp ecifically thos e related to activity pa tterns (e.g., exposure time, frequency, and duration) may be different for children and adults at the same site. For example, due

34 http://www.epa.gov/oswer/riskassessment/superfund_hh_exposure.htm

.

24to outdoor play patterns, children may spend more time near the source of contamination than adults, and thus would have higher exposure time and/or expos ure frequency values than adults living in the same location. 35 For indoor vapor intrusion from the s ubsurface, very young child ren might be more highly exposed due to substant ial time spent indoors.

Beyond the consideration of activ ity patterns, MEs, and chemi cals with a mutagenic MOA for carcinogenicity (as described in Section 5.1), no ad ditional adjustments to account for specific child receptors should be made to the default values. Appendix A of this document is intended to illustrate that the use of default values sufficien tly covers age-related variation in DAF or HEC values derived using the EPA Inhalation Dosimetry Methodology’s default approach.

6.2 Commercial-Industrial/O ccupational Receptor

An example of a commercial-industrial or occupa tional inhalation exposure scenario could be characterized by full-time workers (e.g., 8 hours per day, 5 days per week) in an indoor setting, such as an office building, exposed via vapor intrusion of subsurface contamination on a daily basis for 5 to 25 years. When estimating can cer risk for this type of scen ario, Equation 6 is recommended to calculate an EC and Equation 11 is recommended to estimate risk. Following the flowchart in Figure 2, the duration and e xposure pattern of this s cenario would typically be considered chronic. Therefore, Equation 8 is recommended to derive a chronic EC and Equation 12 is recommended (with a chronic RfC) when calculatin g an HQ for cancer or non-cancer effects. If information about multiple MEs is available, risk assessors should proceed according to Section 3.4 when deriving ECs to use in estimating cancer risks or HQs. Exposure parameters should be adjusted to consider the exposure time, frequency and dura tion for this scenario, which may differ from a residential scenario. Risk assessors should also use appropr iate exposure parameters for outdoor workers who, similar to children, may spend more time near a source of contamination than indoor workers.

6.3 Construction Worker

One example of a construction work er scenario could involve a long- term project (1-2 years) with workers exposed regularly to contaminant vapors and fugitive dust (8 hours per day, 5 days per week). When estimating cancer risk for this type of scenario, Equations 6 and 11 are recommended to calculate an EC and the risk estimate, resp ectively. Following the flow chart in Figure 2, the duration of this exposure scenario would typically be considered subchronic. In addition, this exposure is generally as frequent as a subchr onic toxicity test. Therefore, Equation 8 is recommended to derive a subchronic EC, a nd Equation 12 is recommended for use with a subchronic toxicity value to calcul ate the HQ. If information about multiple MEs is available, risk assessors should proceed according to Section 3.4 when deriving ECs to use in estimating cancer risks or HQs.

6.4 Trespasser/Recreational Receptor

An example trespasser/recreational scenario could c onsist of an exposure of 1 to 2 hours per day, for 100 days per year or less. When estimating cancer risk for this type of scenario, Equations 6 and 11

35 For additional information about early-lifestage age groups to consider when assessing children’s exposure to environmental contaminants, please consult EPA’s Guidance on Selecting Age Groups for Monitoring and Assessing Childhood Exposures to Environmental Contaminants (EPA, 2005d).

25are recommended to calculate an EC and the risk estimate, respectively. Following the steps in Figure 2 for cancer or non-cancer effects characte rized by an RfC, each exposure period should be assessed separately because this exposure lasts onl y one to two hours each da y for an average of two days per week. Therefore, Equation 7 is r ecommended to derive acute ECs for each exposure period. In addition, Equation 12 is recommended for use with an acute toxicity value to calculate HQs for each exposure period.

7. TARGET CONCENTRATIONS FOR S CREENING ANALYSIS OF INHALATION PATHWAYS

For purposes of this guidance, risk-based screening levels are values that may be compared to the contaminant concentration in air to help risk assessors identify potential contaminants of concern. Screening levels can also be calculated for comp arison with samples from source media at a site, such as soil. Screening levels are generally not appropriate for use as clean-up levels; they are intended to aid in initial evalua tion of contaminants and exposure pathways of concern prior to proceeding with a baseline risk assessment. 36 If contaminant concentrations in air exceed the riskbased screening levels appropriate for the receptor population of interest, risk assessors should gather site-specific information to determine the need for any remedial action. The following sections outline a recommended approach for calcula ting screening levels in air as well as source media.

7.1 Target Contaminant Concentrations in Air

The equations recommended for estimating ECs and risk (Equations 6 through 12) can be used to calculate target contaminant concentrations in ai r by following the four step s outlined below in Table 4. 37

If air samples from a site are found to be belo w the target concentration, the risk assessor can generally conclude that this pathway does not pose an unacceptable level of risk from the contaminant. If the concentrations are found to ex ceed the screening levels, the risk assessor should evaluate the inhalation pathway further by gather ing additional site-specific data on contaminant levels, site conditions, and receptor characteristics.

7.2 Screening Levels for Other Media

Inhalation risk-based screening le vels may also be calculated fo r media other than air, including soils, tap water, soil gas, and ground water. Th e soil gas and ground water values may be derived specifically to address concerns about vapor intrusion from subs urface contamination into indoor
spaces.

36 EPA regions, states, or other agencies may support unique sc reening levels for specific purposes that may differ from the method presented in this document. Generally, when using screening levels it is important that risk assessors understand the target risks, toxicity, and exposure assumpti ons as well as migration-attenuation assumptions on which they are based, and to apply them for their intended use.

37 Target contaminant concentrations in air calculated according to the procedure outlined in this document are generally protective for direct inhalation exposures. This process should not be used to calculate concentrations in air to be protective of indirect exposures (e.g., ingestion of crops contaminated through air delivery or vapor phase transfer, ingestion of livestock or fish contaminated indir ectly through air deposition or vapor phase transfer).

26TABLE 4 RECOMMENDED PROCEDURE FOR CALCULATING RISK-BASED SCREENING CONCENTRATIONS FOR CONTAMINANTS IN AIR Cancer Risk-Based Hazard-Based 1 Step 1: Select Target Levels Select target cancer risk (e.g., 1 x 10 ­ 6 ). Select target HQ (e.g., 1).

Step 2: Identify Toxicity Value 2 Identify inhalation cancer potency value (e.g., IUR). If none exists, proceed with hazard-based screening level calculation. Identify inhalation reference value (e.g., RfC) to match exposure scenario (acute, subchronic, or chronic). If none exist, proceed with cancer screening level calculation. Step 3: Calculate CA Using target cancer risk from Step 1 along with the receptor- and scenario-specific exposure parameter values, calculate CA; the following equation is recommended: CA = (AT x Target Risk)/(IUR x ET x EF x ED) Using target HQ from Step 1 alongwith the receptor- and scenariospecific exposure parameter values, calculate CA; the following equation is recommended: CA = (AT x Target HQ x RfC x 1000 μg/mg)/(ET x EF x ED) Step 4: Select Screening Concentration Select minimum of predicted cancer risk- and hazard-based values as screening concentrations. 3 Repeat for each receptor/scenario combination of interest.
1 Hazard-based screening concentrations ar e typically derived from reference values such as RfCs. These values may be available for non-cancer effects but may include cancer, if a nonlinear MOA is thought to operate for a chemical.
2 If no inhalation toxicity value is available for a chemical, contact STSC for further direction on how to proceed.
3 Screening levels estimated from the equations presented in Step 3 could yield conc entrations that exceed the maximum possible vapor concentration for a chemical. In such cases, it may be useful to calculate the maximum possible vapor concentration of the pure contaminant at the temperature of interest, using the following formula: C max = S x H x 10 3 L/m 3 , where S = solubility at 25 ◦ C (or temperature of interest) and H (unitless) = Henry’s Law Constant at 25 ◦ C (or temperature of interest). This equation is ba sed on an established relationship (see, for example, Schwartzenbach et al. 1993), that allows the Henry’s Law Constant to be estimated as the ratio of a compound’s vapor pressure and aqueous solubility for compounds that are slightly to moderately soluble in water. When the dimensionless Henry's Law constant, H, is used, the relatio nship described above can be used to calculate the vapor concentration of a saturated solution of a given compound, assuming equilibrium between the vapor and aqueous phases.

7.2.1 Soil Screening Levels

When evaluating risk in a source medium, such as so il, it is typically possibl e to calculate screening levels for that medium that are expected to be protective of inhalati on exposures based on the expected transfer of a contaminant from the source medium to the air. Soil Screening Levels (SSLs) can be described as “ris k-based soil concentrations derived for individual chemicals of concern from standardized sets of equations . These equations combine EPA chemical toxicity data with parameters defined by assumed future land uses and exposure scenarios, including receptor characteristics and potential exposure pathways” (USEPA, 2002b). These SSLs may be used for screening analyses and may serve as the basis for the development of Preliminary Remediation Goals (PRGs). Refer to the Soil Screening Guidance (USEPA, 1996) and the Supplemental Guidance for Developing Soil Screening Levels for Superfund Sites (USEPA, 2002b) for recommended equations that can be used to calcul ate SSLs for volatilization of chemicals from soil to air and for particulate emissions.

277.2.2 Tap Water Screening Values

Contaminated tap water may pose risk by the inha lation route if the contaminants present are volatile. Screening levels can be calculated for tap water that account for inhalation exposures resulting from the household use of water (e .g., showering, laundering, di shwashing). Risk assessors should consult their loca l EPA regional risk assessor fo r direction on how to calculate appropriate screening leve ls for tap water.

7.2.3 Soil Gas or Ground Water Screening Values for Vapor Intrusion

If there is concern at a site about the possibility of migration of vapor-f orming chemicals from contaminated soil gas or ground water into the indoor air of overlying buildi ngs (“vapor intrusion”), screening values can be calculated for these media. Risk assessors should first follow the procedure outlined in Section 7.1 and Table 4 to calculate a ri sk-based target concentration for the contaminant in air.

For the calculation of a soil gas sc reening-level concentration, the ta rget air concentration is then divided by an assumed screening-level attenuation f actor. The attenuation factor (the ratio of indoor air divided by subsurface source concentration) re presents the factor by which subsurface vapor concentrations migrating into indoor air spaces are reduced due to a variety of attenuating mechanisms.

For the calculation of a ground water screening-level concentration, th e target air concentration is divided by an assumed screening-level attenuation f actor, and the resulting so il gas concentration is converted to a corresponding ground water concen tration, assuming equilibrium between the aqueous and vapor phases at the water table.

Risk assessors should consult thei r local EPA regional risk assessor for direction on how to calculate appropriate screening levels for soil gas and ground wate r when vapor intrusion is an issue at a site.

8. DEVELOPING AGGREGATE AND CUMULATIVE RISK ESTIMATES

EPA’s current approach to estimating cumulative risk or hazard at a site from multiple chemicals, set forth in RAGS, Part A (USEPA, 1989), is not affected by the Inhalation Dosimetry Methodology and therefore is not being updated at this time. In addition, the aggreg ation of risks and hazards across multiple exposure routes should remain unchange d. The recommended appro aches for aggregating risk and hazard estimates are outlined below.

8.1 Estimating Cumulative Risks and Hazards Across Multiple Chemicals

The recommended method for estimating cumulative risk and hazard at a site from exposure to multiple chemicals is described in RAGS, Part A , Section 8.2.2. This meth od is based on the default approaches described in Guidelines for the Health Risk Assessment of Chemical Mixtures (USEPA, 1986). Additional information on this method was subsequently published in the Supplementary Guidance for Conducting Health Risk Assessment of Chemical Mixtures (USEPA, 2000b). The recommended methods to use with quantitative can cer risk estimates as well as with HQs are outlined below.

288.1.1 Cancer Risks

When evaluating predicted cancer risks from multiple contaminants, risk assessors should estimate the cancer risk for each substance and then sum thes e risks. This yields an estimate of total cancer risk, which represents the cumulative predicte d cancer risk for the chemicals at a site.

Risk assessors should note, however, that this recommended method assumes “independence of action by the compounds involved (i.e., that there are no synergistic or antagonistic chemical interactions and that all chemicals produce the same effect, i.e., cance r)” (USEPA, 1989). In addition, this simple additive approach is generall y most appropriate for total cancer risks less than 0.1. If these assumptions are incorrect, over- or under-estimation of actual multiple-substance risk could result (USEPA, 1989).

8.1.2 Hazard Quotients

When the evaluation involves multiple chemicals a ssessed via HQs, risk assessors typically first calculate the HQ for each substance, and then sum th e individual HQ values. This generally yields an estimated hazard index (HI) for the multiple chemicals assessed via a hazard-based approach. Separate HIs should be calculated for each type of exposure period (i.e., chronic, subchronic, acute). If an HI is greater than 1, it is generally appropriate to derive se parate HIs for each target organ of concern (for more information, see RAGS, Part A , page 8-14). 38 When multiple acute exposures are present at a site, risk assessors s hould evaluate each acute exposure event separately. Hazards from multiple chemicals generally should be summed only when the exposures to these chemicals occur simultaneously. 39

8.2 Aggregating Risk and Hazard Quotients Across Exposure Routes

Guidance for combining the multi-chemical risk estimates and hazard quotients across exposure pathways is described in RAGS, Part A , Section 8.3 (USEPA, 1989). In order to determine whether risks or HIs should be combined across exposure pathways, risk assessors should first identify reasonable exposure pathway combinations. Then, ri sk assessors should exam ine whether it is likely that the same individuals would consistently face the reasonable maximu m exposure (RME) by more than one pathway.

38 This recommended method assumes that “the dose for each individual component is at a level at which effects are not expected to occur, be observable, or be of concern; however, when the doses are combined, effects of concern may be expected or observed in response to the higher dose level of the mixture” (EPA, 2000b, page 12). Another assumption of the HI approach is that the compounds induce the same effect by the same mechanism of action. Therefore, “application of the HI equation to a number of compounds that are not exp ected to induce the same type of effects or that do not act by the same mechanism, although appropriate as a screening-level approach, could overestimate the potential for effects” (EPA, 1989, page 8-14). This is generally less of a concern if one to two substances are responsible for driving the HI above 1.

39 In cases where a single chemical is present at a site and receptors are exposed through a series of acute exposure events, the highest single EC should be compared to an acu te reference value of the appropriate duration to assess hazard.

29The recommended approach for estimating excess cancer risk from exposure via multiple routes is to first estimate cancer risk from each exposure pathway and then sum across the multiple routes. 40

For the effects assessed via a reference value, risk assessors should calc ulate the HI for each exposure pathway and sum across the multiple routes . Separate total HIs should be calculated for each type of exposure peri od (i.e., chronic, subchronic or acute). If the HI exceeds one, there may be concern for potential adverse effects and risk asse ssors should consider deriving separate HIs for each target organ of concern.

9. RISK CHARACTERIZATION

Risk characterization is the final, summarizing step in conducting a risk assessment. Generally, the purpose of the risk characteriza tion section of a report is to: 41

• Describe the key findings of the risk assessment in a tr ansparent manner, including identifying hazard, characterizing the dose-resp onse relationship, and describing receptor
exposures;

• Identify and describe the scientific and policy assumptions used in the assessment;

• Characterize uncertainties in results; and

• Provide an overall conclusion about the ri sks present at a site (USEPA, 2000c).

A well-crafted risk characterization section puts risk calculations into contex t for risk managers so that they may effectively weigh and interpret risk assessment results (i.e., it is the interface between risk assessment and risk management). A few of the key issues and uncertainties involved in calculating risks from inhalation exposures are outlined below.

9.1 Highly Exposed or Susceptible Populations and Life Stages

EPA recommends that the risk char acterization portion of the risk assessment explain any particular susceptibilities to inhaled toxicants or potential for increased inha lation exposures among the various receptor groups at a site. 42 We discuss below two possible exam ples, children and worker receptors, though this discussion could apply to other receptor characteristics as well (e .g., age, disease, gender, genetic characteristics).

9.1.1 Children

One population group that could potentially be more hi ghly exposed to inhalation exposures at a site is children. As discussed in Section 6.2, exposur e parameters related to activity patterns (e.g., exposure time, frequency, and duration) and MEs, ma y vary across age groups. For example, due to outdoor play patterns, children ma y spend more time near the sour ce of contaminati on than adults,

40 Note that this approach is generally most appropriat e for total cancer risks of less than 0.1 (EPA, 1989).

41 For specific information on the format of risk characterizations, refer to Elements to Consider when Drafting EPA Risk Characterizations (EPA, 1995c).

42 EPA’s IRIS glossary defines susceptibility as the following: “Increased likelihood of an adverse effect, often discussed in terms of relationship to a factor that can be used to describe a human subpopulation (e.g., life stage, demographic feature, or genetic characteristic)” (EPA, 2008b).

30and thus would have higher exposure time and/or expos ure frequency values than adults living in the same location. Therefore, it is im portant to carefully describe site -specific exposures to children, and assumptions made in risk calculations. 43

If chemical-specific data on suscep tibility to the toxic effects from early life exposures are available, these data are considered when developing toxicity values that specifically address differential toxicity to the young (e.g., vinyl chloride) (USEPA , 2005c). Toxicity values derived using the default approach from the Inhalation Dosimetry Methodology are developed for the human population as a whole, including sensitive subgroups . Therefore, as described in Section 6 of Appendix A, no quantitative adjustment of toxicity values derived us ing the default approach in the Inhalation Dosimetry Methodology is recommended for specific ag e groups to account for different ventilation rates or body we ights of specific age groups.

When evaluating risk to carcinogenic chemicals with a demonstrated mutagenic MOA but which lack chemical-specific information on susceptibili ty from early life exposures, EPA recommends a quantitative adjustment of the toxi city value to account for early life susceptibility, as described in the Supplemental Cancer Guidelines (see USEPA, 2005b & 2005c; and S ection 5.1 of this guidance for further information).

9.1.2 Workers

Workers could have increased exposure under certain occupati onal scenarios. Some outdoor workers might spend more time near a source of cont amination in the course of their job and this should be reflected in adjustments to the exposure parameters (e.g., ET, Exposure Frequency (EF), and ED) describing the worker exposure scen ario. Toxicity values derived using the Inhalation Dosimetry Methodology are developed for the human populati on as a whole, including sensitive populations and life stages. In the default Inhalation Dosimetry Methodology approach, typical variation in IRs between periods of high activity and rest is consider ed. However, if workers have especially high levels of exertion with correspondingly high ventilati on rates, these workers could be at the upper end of the risk range, particularly if they are exposed to Category 1 gases, which have direct effects in the respiratory tract. This implication should be recognized in the risk characterization section.

9.2 Uncertainties in Inhalation Risk Assessment

This guidance recommends including an assessment of the key uncertainties that may significantly impact risk estimates for inhaled chemicals. This should ensure transparen cy, clarity, reasonableness and consistency in risk assessments, as recommended by EPA’s Policy for Risk Characterization (USEPA, 1995a). Other sources of uncertainty may be present and other EPA documents provide guidance on characterizing uncerta inty in risk the assessmen t process (USEPA, 1992, 1995a, 1995b, 1995c, 1997a, 1997b). Key uncertainties related to inhala tion risk assessment, wh ich is the focus of this section, include the developmen t of ECs, choice of toxicity valu e, lack of quan titative toxicity information via inhalation, and the approach to estimating and aggregating risks. According to EPA’s Guidance for Risk Characterization , the discussion of uncertainty “should reflect the type and complexity of the risk assessment, with the level of effort for analysis and discussion of uncertainty

43 For additional information on children’s health risk assessment, please consult A Framework for Assessing Health Risks of Environmental Exposures to Children (EPA, 2006b).

31corresponding to the level of effort for the asse ssment” (USEPA, 1995b). Ther efore, risk assessors should provide a qualitative and/or quantitative evaluation of ke y uncertainties pertaining to inhalation risk, and their impact on the outcome of th e assessment, consistent w ith the level of effort of the specific risk assessment.

9.2.1 Development of Exposure Concentrations

As described in Section 3 of this guidance, w ith the exception of acute exposures, time-weighted averages are typically used to represent intermittent or variable inhalation exposures to receptors at a site. This recommended approach is consistent with the duration adjustment approach (based on Haber’s Law) that is generally used in deriving the toxicity va lues (see Section 2.1.1.1 for further information). As mentioned in Section 3, when ev aluating situations in wh ich the exposure is longterm, yet there are short periods of significantly higher exposure, those periods should also be assessed using appropriate short-term toxicity valu es. This ensures that periods of much higher exposure can be appropriately assessed and not “diluted out” in the as sessment of longer-term
exposure.
When information on multiple MEs exists at a site , risk assessors may choose to estimate ECs as outlined in Section 3.4. However, this typically requires sufficient time-activity information of receptors at a site to accu rately determine the time spent in each ME. Incomplete or low quality data on time-activity pattern may introduce uncertainty in to the estimation of the ECs for MEs. Risk assessors should describe the quality and completeness of these data.

The recommended method for determining the CA at a site can potentially in troduce uncertainty into the EC calculations. For instance, if contaminant c oncentrations in air are measured, risk assessors should consider uncertainties related to how well the se t of air samples available at a site represents the duration and time period being assessed as well as measurement uncertainty related to the methods and equipment used. In addition, risk assessors should describe any potential confounding of indoor air samples by other sources of contamin ants (e.g., household products). If contaminant concentrations in air are modeled, (e.g., by EPA’s spreadsheet models for vapor intrusion) risk assessors should address model-re lated uncertainties and their potential impact on the estimate of contaminant concentrations in air. Considerations of particle size at the site versus particle size used to derive the toxicity value ar e also important.

9.2.2 Toxicity Assessment

Section 4.1 of this document indicates that some IURs on IRIS were developed through extrapolation from oral CSFs (see Appendix B of this document). The use of toxicity values derived through simple route-to-route extrapolation introduces additional uncertainty into risk calculations. Therefore, risk assessors should indicate when extrapolated IURs are used and should characterize the potential impact of the un certainty associated with using these values, if known.

Section 4.2 and Appendix C of this guidance reco mmends contacting STSC to help identify appropriate toxicity values for conducting a risk assessment at S uperfund sites in the absence of published inhalation toxicity values. If STSC is unable to recommend a toxicity value, risk assessors should acknowledge the resulting uncertainty in risk associated with the chemical(s) lacking inhalation toxicity data. If STSC provides risk assessors with a toxicity value based on a PBPK

32model, model uncertainty should be discussed. In addition, if STSC provides risk assessors with one or more structurally analogous chem icals, risk assessors can use toxi city data for these chemicals to help characterize the potential magnitude of the inhalation risk associated with the chemical(s) lacking data. In this case, risk assessors should acknowledge the uncertainty associated with relying on toxicity data for analogous chemicals to characterize risk at the site.

Risk assessors should also acknowledge chemicals that lack duration-appropriat e toxicity values and discuss the potential impacts of substituting alternative toxicity values for HQ calculations. For instance, if the ED is determined to be subchr onic but no subchronic inha lation RfC or analogous toxicity value is available for that chemical, the risk assesso r should address the uncertainty associated with calculating an HQ using a toxicity value for a different durati on, such as chronic, or the impact of not quantifying those risks. In addition, if risk assessors use an acute toxicity value that does not match the duration of the acute ex posure being assessed, the possibility of under or overestimating hazard should be discussed.

When conducting a screening-level risk assessment us ing screening values such as those described in Section 7, it is important to further evaluate an d clearly describe the quality and uncertainties associated with the inhalation toxicity values us ed in the risk assessment if measured sample contaminant concentrations at a site exceed these screening values.

9.2.3 Estimating Cancer Risks

For high exposures, for example those within the ra nge of epidemiological studies (usually those predicted to have risks greater than 10 -2 ), the IUR derived from the linear extrapolation below the range of observation is generally not appropriate fo r use (see Section 5.1 of this document for further information). 44 Risk assessors should provide specific information in the risk characterization describing how these high exposures were addressed in the risk assess ment. For instance, if a risk assessor chose to provide a semi-quantitative ap proach (e.g., indicating that risks are above 10 -2 ), this should be indicated, along with a descript ion of the uncertainties involved in not fully quantifying risk associated with ex posure to this chemical. If a risk assessor chose to use the original model in the IRIS file or other techni cal background document, the risk characterization section should include a description of any uncer tainties in the model used and could contain examples of the risks estimated.

9.2.4 Estimating Risk and Haza rd from Multiple Chemicals and Exposure Pathways

Risk assessors should also describe uncertainties involved in aggregating risk and hazard across multiple chemicals and exposure pathways. For inst ance, the approaches described in Section 8 of this document are associated wi th several assumptions (e.g., inde pendence of action and doses for individual compounds at levels not expected to be of concern). If these assumptions are not met, aggregation may not be appropriate . This should be fully describe d in the risk characterization section and any uncertainties involved in the lack of quantitative information should be indicated.

44 Also refer to Section 8.2.1 of RAGS, Part A for further discussion of this topic (EPA, 1989, page 8-6).

3310. REFERENCES

Eaton, D.L. and Klaassen, C.D. (2001). “Principles of Toxicology” in Casarett and Doull’s Toxicology: The Basic Science of Poisons , Klaassen, C.D., editor. McGraw-Hill Publishing Division, 6 th Edition, page 14.

Gaylor, D.W. (2000). The Use of Haber’s Law in Standard Setting and Risk Assessment. Toxicology 149:17-19. Johnson, P.C. and Ettinger, R.A. (1991). Heuristic Model for Predicting the Intrusion Rate of Contami nant Vapors into Buildings. Environmental Science and Technology 25: 1445-1452. http://www.epa.gov/oswer/riskasse ssment/airmodel/johnson_ettinger.htm

Schwarzenbach, R.P., P.M. Gsch wend, and D.M. Imboden. (1993). Environmental Organic Chemistry . John Wiley & Sons, Inc.: New York.

U.S. EPA. (1986). Guidelines for Health Risk Assessment of Chemical Mixtures . Risk Assessment Forum, Washington, D.C. EPA/630/R-98/002. http://www.epa.gov/ncea/raf/pdfs/chem_mix/chemmix_1986.pdf

U.S. EPA. (1989). Risk Assessment Guidance for Superfund, Volume 1, Part A. Office of Emergency and Remedial Response, Washington, D.C. EPA/540/1-89/002. http://www.epa.gov/oswer/riskassessment/ragsa/index.htm

U.S. EPA. (1991). Risk Assessment Guidance for Superfund, Volume 1, Part B. Office of Emergency and Remedial Response, Washington, D.C. EPA/540/R-92/003. http://www.epa.gov/oswer/riskassessment/ragsb/

U.S. EPA. (1992). Memorandum: Guidance on Risk Characte rization for Risk Managers and Risk Assessors . From F. Henry Habicht II, Deputy Admi nistrator, U.S. EPA, Washington, DC. http://www.epa.gov/oswer/riskassessment/pdf/habicht.pdf

U.S. EPA. (1994). Methods of Derivation of Inhalation Reference Concen trations and Application of Inhalation Dosimetry . Office of Research and Development, Research Triangle Park, NC. EPA/600/8-90/066F. http://cfpub.epa.gov/n cea/cfm/recordisplay.cfm?deid=71993

. U.S. EPA. (1995a). Policy for Risk Characterization . From Carol Browner, Administrator, U.S. EPA, Washington, DC.

U.S. EPA. (1995b) Guidance for Risk Characterization . Science Policy Council. February. http://www.epa.gov/osa/spc/pdfs/rcguide.pdf

U.S. EPA. (1995c). Elements to Consider when Drafting EPA Risk Characterizations. March. http://www.epa.gov/osa/spc/pdfs/rcelemen.pdf

U.S. EPA. (1996). Soil Screening Guidance: User’s Guide, Second Edition . Office of Solid Waste and Emergency Response, Wa shington, D.C. EPA/540/R95/128. http://www.epa.gov/superfund/resources/soil/ssg496.pdf

U.S. EPA. (1997a). Exposure Factors Handbook . Office of Research and Development,

34Washington, DC. EPA/600/P-95/002Fa. h ttp://www.epa.gov/ncea/pdfs/efh/front.pdf

U.S. EPA. (1997b). Policy for Use of Probabilistic Analysis in Risk Assessment . From Fred Hansen, Deputy Administrator, Washington, DC.

U.S. EPA. (1998). Route-to-Route Extrapolations . Memorandum from John E. Whalan and Hugh M. Pettigrew to Margaret Stasikowski. Office of Prevention, Pesticides, and Toxic Substances. October 10, 1998.

U.S. EPA. (2000a). Integrated Risk Information Sy stem Summaries: Vinyl Chloride . Office of Research and Development, Washington, D.C. http://www.epa.gov/iris/subst/1001.htm

U.S. EPA. (2000b). Supplementary Guidance fo r Conducting Health Risk Assessment of Chemical Mixtures . EPA/630/R-00/002. http://www.epa.gov/ncea/raf/pdfs/chem_mix/chem_mix_08_2001.pdf

U.S. EPA. (2000c). Risk Characterization Handbook . Science Policy Council, Washington, D.C. EPA-100-B-00-002. http://www.epa .gov/osa/spc/pdfs/rchandbk.pdf

U.S. EPA. (2001). R isk Assessment Guidance fo r Superfund, Volume 1, Part D. Office of Emergency and Remedial Response, Wa shington, D.C. Publication 9285.7-47. http://www.epa.gov/oswer/riskassessment/ragsd/index.htm

U.S. EPA. (2002a). Draft Guidance for Evaluating the Vapor Intrusion to Indoor Air Pathway from Groundwater and Soils (Subsurface Vapor Intrusion Guidance). Office of Solid Waste and Emergency Response, Washington, D.C. http://www.epa.gov/epawaste/hazard/ correctiveaction/ei s/vapor/complete.pdf

U.S. EPA. (2002b). Supplemental Guidance for Developing Soil Screening Levels for Superfund Sites . Office of Solid Waste and Emergency Response, Washington, D.C. Publication 9335.4-24. http://www.epa.gov/superfund/h ealth/conmedia/soil/pdfs/ssg_main.pdf

U.S. EPA. (2002c). A Review of the Reference Dose and Reference Concentration Processes . Risk Assessment Forum, Washington, DC, EPA/630/P-02/002F. http://cfpub.epa.gov/ncea/raf/recordisplay.cfm?deid=55365

U.S. EPA. (2003). Human Health Toxicity Values in Superfund Risk Assessment . Office of Solid Waste and Emergency Response, Washington, D.C. Publication 9285.7-53. http://rais.ornl.gov/homepage/hhmemo.pdf

. U.S. EPA. (2004a). User’s Guide for Evaluating Subsurface Vapor Intrusion Into Buildings

. Office of Emergency and Remedial Response, Washington, D.C.

U.S. EPA. (2004b). Air Quality Criteria for Part iculate Matter: Volume II. Office of Research and Development, Washington, D.C. EPA/600/P-95/001bF.

U.S. EPA. (2005a). Guidelines for Carcinogen Risk Assessment , Risk Assessment Forum, Washington, D.C. EPA/630/P-03/001F. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=116283

35U.S. EPA. (2005b). Supplemental Guidance for Assessing Cancer Susceptibility from Early-Life Exposure to Carcinogens . Risk Assessment Forum, Wash ington, DC. EPA/630/R-30/003F. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=160003

U.S. EPA. (2005c). Implementation of the Cancer Guid elines and Accompanying Supplemental Guidance – Science Policy Council Cancer Guidelines Implementation Workgroup Communication I: Application of the mode of action framework in mutagenicity determinations for carcinogenicity. Memorandum from William H. Farland, Chair, Science Policy Council to Science Policy Co uncil Steering Committee October 4, 2005. http://www.epa.gov/osa/spc/pdfs/canguid1.pdf

U.S. EPA. (2005d). Guidance on Selecting Age Groups fo r Monitoring and Assessing Childhood Exposures to Environmental Contaminants . Risk Assessment Forum, Washington, DC. EPA/630/P-03/003F. http://cfpub.epa.gov/n cea/cfm/recordisplay.cfm?deid=146583

. U.S. EPA. (2006a). Approaches for the Application of Ph ysiologically Based Pharmacokinetic (PBPK) Models and Supporting Data in Risk Assessment. National Center for Environmental Assessment, Washington, DC. EPA/600/R-05/043F. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=157668

. U.S. EPA. (2006b). A Framework for Assessing Health Ri sks of Environmental Exposures to Children. National Center for Environmental A ssessment, Washington, DC. EPA/600/R05/093F. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=158363

. U.S. EPA. (2008a). Regional Screening Levels for Chemic al Contaminants at Superfund Sites

. http://www.epa.gov/reg3hwmd/risk/huma n/rb-concentration_table/index.htm

. U.S. EPA. (2008b). Integrated Risk Information System, Glossary of Terms . Office of Research and Development. Searched September, 2008. http://www.epa.gov/iris/h elp_gloss.htm#content

36APPENDICESTABLE OF CONTENTS

APPENDIX A: ANALYSIS OF DEFAULT APPROACH FOR HEC DERIVATION AS COMPARED TO POPULATION- AND LIFE STAGE-SPECIFIC CALCULATIONS

INTRODUCTION ...................................................................................................................... A-1

1. EXAMPLE 1: CATEGORY 1 GAS, EXTR ATHORACIC EFFECTS, ACROLEIN ........... A-3

2. EXAMPLE 2: CATEGORY 1 GAS, TRACHEOBRONCHIAL EFFECTS, HYPOTHETICAL CHEMICAL.......................................................................... A-4

3. EXAMPLE 3: CATEGORY 1 GAS, PULMONARY EFFECTS, HYPOTHETICAL CHEMICAL ............................................................................................ A-5

4. CATEGORY 3 GASES .......................................................................................................... A-7

5. PARTICLE DEPOSITION ACROSS AGE GROUPS .......................................................... A-7

6. CONCLUSIONS................................................................................................................. .. A-10

7. REFERENCES CITED......................................................................................................... A-1 1

8. ADDITIONAL SOURCES OF RELATED INFORMATION ............................................ A-13

APPENDIX B: CHEMICALS ON IRIS WITH EXTRAPOLATED INHALATION UNIT RISKS

APPENDIX C: STSC’S PROCESS FOR DERIVING ALTERNATIVE INHALATION TOXICITY VALUESLIST OF TABLES

Table A-1 Calculation of LOAEL [H E C ] Values for Hum a ns of Different Ages and Activity Patterns for the Extrathoracic Region

................................................ A-4

Table A-2 Calculation of NOAE L [H EC] Values for Hum a ns of Different Ages and Activ ity Patterns for the Tracheobronchial Region

......................................... A-5

Table A-3 Calculation of NOAE L [H EC] Values for Hum a ns of Different Ages and Activity Patterns for the Pulm onary Region

.................................................... A-6

Table A-4 Particle Deposition Across Age Groups

.................................................................... A-9

Table B-1 Chem icals with Extrapolat ed Inhalation Unit Risks on Iris

....................................... B-2

LIST OF E Q UATIONS

Equation A-1 RGDR ET h
.............................................................................................................. A-3

Equation A-2 RGDR TB ............................................................................................................... A-4

Equation A-3 RGDR PU ............................................................................................................... A-5

Equation A-4 Category 3 DAF

................................................................................................... A -7

Equation A-5 RDDR r .................................................................................................................. A-7

Equation A-6 RDDR ER ............................................................................................................... A-8APPEND IX AAPPE NDI X A

ANALYSIS OF DEFAULT A PPROACH FOR HEC DE RIVA TION AS COMP ARE D TO POPULAT I ON- AND LIFEST AGE- SPECIFI C CALCULATIONS

NOTE : The Agency ’s in halatio n dosi m et ry m e tho dol og y (U SEPA, 1 994; hereafter, “t he In hal ati on Dosi metry Meth odo logy ” ) is a tech nical repo rt tha t de scribes t h e de rivati on of hu man equ i valen t concent r ati ons (H ECs ) fro m anim a l (or hu man) studies, as well as the other steps involved in devel opi n g a ch ron i c Re fe rence C oncentration (RfC). This ap pend ix is include d to illust rate t h e HEC deri vati o n using the In hala tio n Dosi metry Met hod ology ’s defa ult
approac h (w ith the reco mm e n ded defa ult va l u es for hu m a ns ), and to also il lustra te the i m pact of su bstit u ting al ternate age- and activity-specific hu man values into the defa ult ca lc ulati ons. The d e fault app r oac h is e m ployed for che m icals for wh ic h m o re che m ica l -spec i fic dosi m etric and phar m acokineti c data a r e not a v ailable, thus precluding the use of m o re

a d v a n c e d mo d e l s fo r d e ri v i ng the H E C. The calculati ons in this ap pend ix d o no t re presen t a refi ned or opt i m al m o del fo r assessing in tra-hu m a n va riab il ity (e.g., age- a nd acti v it y-spe c ific risks ) , and are not intende d t o im pl y t h at r i s k a s s e s s o r s should dev i ate fro m the Inh a l a tio n D o simetr y Met hod olo g y by subs tit utin g alterna t e val u e s into the defa u lt calcu lati ons. A g e

- s p e c i f i c d a t a a r e l i m i t e d

. B e c a use o f the s e li m i tat i ons, t h e calcula tio n s m a de for di ffe rent ages a nd ex posure groups in this appe ndi x are not rec o mm e n ded for use in quant ita tive ris k assessm e n t (i.e., they are onl y fo r the purpose o f illust rati on ), but m a y be use f ul in discussi o n s of uncertain ty and variabi l i t y associated w ith the de faul t approac h

.

It is also note d that, as of this writ ing, the A g ency is i nvo lve d in a rout ine reevaluati on o f scienti f ic adva nce m en ts in the fiel d, with conside r ati on o f the need for i m p r ove m e nt t o the Inha lat i on Dosimetry Met hodo logy

. An y revisi ons will co nside r curre nt un dersta ndin g of in hala tion d o si m e try and differe n ces across and wit h in species, as well as the Agency ’s risk assess m e n t nee d s. In orde r to t r anspare n tl y an d quant itati vel y address chil d r en’s in halat i o n dosi m e t ry and risk assessm e n t, th is guid a nce docu m e n t will be up date d (on

- li ne) wh en Agency m e t hodo log y upda tes are available t h at a r e specific t o early li fe. Until that ti m e , the 1994 Inha lat i o n Dosimetry Method olo g y is the
appro p riate Ag ency m e t hodo l ogy.

INTRODUCTION

This appendix consists of exa m ples and discu ssions illu stra ting th e curren t def a ult ch em ical category-specific approach to inhalation dosim etry for the various categories of gases and particles as described in Methods for Derivation of I nhalation Reference Concentra tions and Application of Inhalation Dosimetry (USEPA, 1994; hereafter, the Inhalation Dosim e try Methodology ). Th is default inhalation dosimetry approach is used to convert toxicological an d epidem iological study data to an HEC that can then be used to derive chronic RfCs for the hum an population (inclusive of susceptible populations and life stages, such as child ren) and also in the developm ent of Inhalation Unit Risks (IURs) (USEPA, 2005). The default appr oach does not rely on age- or activity-specific values for physiological param e ters when calcul a ti ng H E C s ; how e ver the def a

ult approa ch has been designed by EPA to derive reference values th at are protective acro ss the entire population.

The appendix includes six sections. S ections 1 th rough 3 address Category 1 gases. These sections provide example calculations for Category 1 highly reactive, high wa te r solub i lity gases that ar e typically ab sorbed in th e upper airways, exhib iti ng adv e rs e effects in the extratho racic (ETh), tracheobronchial (TB), and pulm o nary (PU) regions of the respirat ory tract, respectively. These

exam ples include com p arisons of HEC calculatio ns based on default param e ters with those derived using ag e- and activity-s p ecific p a ram e ters for th e resp iratory reg i on affecte d. Section 4 addresses Category 3 low reactivity, lim ited water solub ility ga ses that exhibit sys t em ic effects outside the respirato r y tract. Sec tio n 5 addr esse s changes in partic le dep o sition in th e resp ir atory tra c t acro s s age groups. The conclusions ar e summ arized in Section 6.

A-1When reviewing the examples, please note the following:

• An RfC derived using the Inhalation Dosime try Methodology is defined as “an estimate (with uncertainty spanning perhaps an order of magnitude) of a c ontinuous inhalation exposure to the human population (including se nsitive subgroups) that is likely to be without an appreciable risk of deleterious effects during a lifetime” (USEPA, 2008).

• All examples in this appendix are based on the Inhalation Dosimetry Methodology . EPA is committed to periodically reviewing and updating the Inhalation Dosimetry Methodology to ensure that it reflects the current state of the science and that it yields toxicity values that sufficiently cover potential ag e- and activity-related variati on in inhalation exposure. A review and update is currently underway.

• The examples in this appendix are all based on calculating HECs from a point of departure (POD) for non-cancer effects (e.g., a No Observ ed Adverse Effect Le vel (NOAEL), Lowest Observed Adverse Effect Level (LOAEL), or Benchmark Concentration, Lower confidence limit (BMCL)). These calculations could also be performed in an identical manner for carcinogens using a POD for cancer risk esti mate derivation (e.g., a Lower limit on the Effective Concentra tion (LEC) value).

• The default animal and human values for minute volume (V e ) and surface area (SA) used in these examples were obtained from Methods for Derivation of Inhalation Reference Concentrations and Applicati on of Inhalation Dosimetry (USEPA, 1994). 45 The age- and activity-specific V e values were obtained from the International Commission on Radiological Protection (ICRP) Publication 66, Human Respiratory Tract Model for Radiological Protection (ICRP, 1994). 46 Age-specific SA values used in Examples 1 and 2 were calculated using scaled estimates fo r the mass and thickness of respiratory regionspecific target tissue from ICRP (1994); Valu es for Example 3 were calculated from an allometric scaling equation presented in a publication by Zeltner et al. (1987). EPA’s Office of Research and Devel opment (ORD) selected these da ta following review of the available physiological data for the age groups indicated in the examples.

• Chemical-specific data from the Integrated Risk Information System (IR IS) file for acrolein were used in the ETh example (Example 1). However, the other two examples, which focus on effects in the TB and PU regions, respectively, use hypothetical data for the POD because there are currently no chemicals on IR IS exhibiting Critical Effects (for RfC derivation) in those regions. 47 The conclusions of these two examples are unaffected by the use of hypothetical data because the results are driven by the values of parameters that are not chemical-specific (i.e., SA and V e ).

45 The minute volume is the total ventilation per minute and equals the product of the tidal volume (the air volume entering or leaving the lungs with a sing le breath) and the respiratory frequency.

46 For further information on inhalation rates in humans under different scenarios, refer to Chapter 5 of EPA’s Exposure Factors Handbook (EPA, 1997).

47 Hypothetical examples for the TB and PU regions were incl uded in this appendix because currently no RfCs for gases on IRIS are calculated based on animal studies showing hea lth effects occurring in thes e regions of the respiratory system A-21. EXAMP LE 1: CAT E GORY 1 GAS, EXT RATHORACIC EFF E CTS, ACROLEIN

The Dosim e tric Adjustment Factor (DAF) for a Category 1 gases, the R e gional Gas Dose Ratio (RGDR), is based on the anim al to hum an ratio of the V e divided by the SA of the r e gion of the

r e s p ir a t or y tr a c t whe r e t h e e ffe c t oc c u rs. For acrol ein, the effect occurs in the ETh region. The DAF is typically calculated using the follo wing equation (USEPA, 1994, Equation 4-18):



### ⎛ V ⎞

e 

### ⎜ ⎜ ⎟ ⎟ 0.14 L/min ⎝ SA ETh 

### ⎠ animal 15 cm 2 

### RGDR ETh 

### = ⎛ V ⎞ = 13.8 L/min = 0.14 (Equation A-1)

e 

### ⎜ ⎜ ⎟ ⎟ 2 

### ⎝ SA ETh 

### ⎠ human 200 cm

The default Inhalation Dosimetry Methodology -recomm ended values f o r the V e an d SA ETh of the W i star rat (the anim al in the principa l study for acrolein) are 0.14 L/m i n (0.20 m 3 /day) and 15 cm 2

, respectively (USEPA, 1994). EPA’s defa ult human values are 13.8 L/ m i n (20 m 3 /day) for V e and 200 c m 2 for SA ET h ( U SE PA, 1994). The RGDR for the ETh region (RGDR ETh ) was calculated using these values for the rat and the hum an as shown in Equation A-1. In the laboratory anim al study on acrolein, the LOAEL adjusted fo r continuous exposure (LO A E L [ ADJ] ) of 0.16 m g / m 3 (USEPA, 2003) is used as the point of departure. The LOAEL [H E C ] is the LOAEL [ ADJ] m u ltiplied by th e RGDR ETh
. To illustrate any potentia l a g e

- o r a c t i v ity

- r e l a t e d v a r i a tio n in t

h e L O A E L [H E C ] that m i ght result f r om using hum an param e ter values other than the defau lts, sca l ed e s tim ates f o r the m a ss and thickne ss of ETh target tissue from ICRP (1994) at diffe rent ages are used to calculate the SA ETh values in Table A-1. Age- and activity-related V e reported in ICRP (1994) ar e based on daily tim e-budgeted reference values. Table A-1 shows li ttle va ria tion in the resu ltant LOAEL [H E C ] across the groups in this exam ple. The default proc edure produces the lowest LO AEL [H E C ] va lue in Table A-1 and is, therefore, sufficient to cover all of these groups.

A-3TABLE A-1 C O MP AR ISO N OF TH E H E C- D E F AULT (EPA, 199 4) WIT H EX AMPLE LO A E L [HEC] VA LU ES FOR HU MA NS OF DI FFERENT A G E S AND A C TI VITY PATTE RNS FOR THE EX TRAT HORA CIC REGI ON

Total V e (hu m an) ( L /m in ) a SA ET h
(hu m an) (cm 2 ) b (V e /S A ETh ) hu m a n ( L /m in

- c m 2 ) RGD R ETh LOAEL [HEC] (mg/ m 3 ) Outdoor Wor k er, Male 17.5 470 0.037 0.25 0.04 Sede ntary Wor k er, Male 15.4 470 0.033 0.28 0.04 Sede n t ary W o r k er, Fe male 12.6 407 0.031 0.30 0.05 15 Year-Ol d Male 14.0 439 0.032 0.29 0.05 15 Year-Ol d Fe male 10.9 397 0.027 0.35 0.06 10 Year-Ol d 10.6 293 0.036 0.26 0.04 5 Year-Ol d 6.1 198 0.031 0.30 0.05 1 Year-Ol d 3.6 97.1 0.037 0.25 0.04 3 Month-Ol d 2.0 65.8 0.030 0.31 0.05

HEC - De fa ult 13.8 200 0.069 0.14 0.02

a These v a lu es ar e from th e ICRP publication, Tab l es 8, 27, B.16 a, B.16b and B.17 (ICRP, 1994). b These values ar e from th e ICRP publ ication, Tab l es 1 and 5 (ICR P , 1994).

2. EXAMP LE 2: CAT E GORY 1 GAS, TRACHEOBRONCHIAL E FFECTS, HYPOTHETICAL CHEMICAL

The DAF for a Category 1 gas or va por exhibiting effects in the TB region is based on the anim al to hum a n ratio of the V e di vided by the SA of the TB region fo r each species. The DAF is typically calculated using the following equation:
⎛ V ⎞

e ⎜ ⎜ ⎟ ⎟ 0.14 L/min

RGDR TB = ⎝ SA TB ⎠ animal

= 22.5 cm 2

= 1.4 (Equation A-2) 48 ⎛ V ⎞ 13.8 L/min

e ⎜ ⎜ SA ⎟ ⎟ 3200 cm 2 ⎝ TB ⎠ human This exam ple assum e s that the hypothetical chem ical has been tested on W i star rats and therefore utilizes th e EPA ani m al default values f o r that strain

. T h e V e value used is 0.14 L/ m i n (0.20 m 3 /day) and the default SA TB is 22.5 c m 2 (USEPA, 1994). EPA’s defa ult hum an values are 13.8 L/ m i n (20

m 3 /day) for V e and 3200 cm 2 for SA TB (USEPA, 1994). The RGDR for the TB region (RGDR TB ) is calcu lated u s ing thes e v a lues f o r the rat and th e hum a n, as shown in Equation A-2. The exam pl e also assum e s a NOAEL adjusted for continuous exposure (NOAEL [ ADJ] ) of 0.16 m g /m 3 as the point of departure. The NOAE L [H E C ] is the NOAE L [ ADJ] m u ltiplied b y the RGDR TB
.

Table A-2 shows little varia tion ac ro ss age and activ ity grou ps in the NOAEL [H E C ]
. The varia tion from the default (less than a facto r of 2) is less than the default value of 10 used for the uncertainty factor for intraspecies variab ility when deriving the RfC. Appli cation of the norm a l procedure for

48 Th is equati on is the reduce d , defaul t versi o n of Eq uati on 4-19 of the Inh a l a tio n Dosime tr y Metho dol ogy

. Equa tio n 4-19 is reduced t o th is for m c onsist e nt wit h the de rivat i on o f the reduced for m o f the RGDR eq uatio n of
extrat ho racic effects describe d in section 4.3

. 6.1 and Appen d ix I o f the In h a lat i on D o sime try Meth odo lo gy

. A-4determ ining the RfC will accomm odate th e observed variation. In addition, RfCs a nd IURs are developed f o r chronic exposure and will generally involve an exposure for m u ltiple years.

TABLE A-2 C O MP AR ISO N OF TH E H E C- D E F AULT (EPA, 199 4) WIT H EX AMPLE LO A E L [HEC] VA LU ES FOR HU MA NS OF DI FFERENT A G E S AND A C TI VITY PATTE RNS FOR THE T R ACHEOB R ONCHI A L RE GION
Total V e (hu m an) ( L /m in ) a SA T B (hu m an) (cm 2 ) b (V e /S A TB ) hu m a n ( L /m in

- c m 2 ) RGD R TB NOA E L [HEC ] (mg/ m 3 ) Outdoor W o r k er M 17.5 2660 0.0066 0.94 0.15 Sede ntary W o r k er M 15.4 2660 0.0058 1.1 0.18 Sede ntary W o r k er F 12.6 2640 0.0048 1.3 0.21 15 year M 14.0 2520 0.0056 1.1 0.18 15 year F 10.9 2250 0.0048 1.3 0.21 10 Year 10.6 1830 0.0058 1.1 0.18 5 Year 6.1 1340 0.0046 1.4 0.22 1 Year 3.6 857 0.0042 1.5 0.24 3 Months 2.0 712 0.0028 2.2 0.35

HEC

- de fa ul t 13.8 3200 0.0043 1.4 0.22

a These v a lu es ar e from th e ICRP publication, Tab l es 8, 27, B.16 a, B.16b and B.17 (ICRP, 1994).

b These values ar e from th e ICRP publ ication, Tab l es 1 and 5 (ICR P , 1994).

3. EXAMP LE 3: CAT E GORY 1 GAS, PUL M ONARY EFFE CTS, HYPOTHETICAL CHEMICAL

The DAF for a Category 1 gas or vapor with an effect in the PU re gion is based on th e anim al to hum a n ratio of the alveolar ve ntila tio n rate (Q-a lv ) divided by the SA of the PU region (SA PU ) for each species

. The Q-alv is approxim a tely equal to the V e multiplied by 0.7. This adjustm e nt accounts for the anatom ic/physiolo gic deadspace in the PU region, m a king the Q-alv eq uivalen t to the am ount of inspired ai r available for gas exchange (W est, 2000). The D A F for this region of the respirato r y tract is typ i ca lly ca lculate d using the f o llowing eq uation : 

### ⎛ ⎞ ⎜ ⎜ Q

− alv ⎟ ⎟ 0.1 L/min

2 

### ⎝ SA PU 

### ⎠ 0.34 m RGDR PU 

### = ⎛ Q

− alv ⎞ animal

= 9.7 L/min = 1.6 (Equation A-3) 49 

### ⎜ ⎜ ⎟ ⎟ 2 

### ⎝ SA PU 

### ⎠ human 54 m

This exam ple assum e s that the hypothetical chem ical has been tested on W i star rats and therefore utilizes the EPA ani m al default values for that strain. The V e valued used is 0.14 L/m i n (0.20

m 3 /day), which when multip lied by 0.7, yields a Q-al v of 0.1 L/ m i n. The exam ple uses the EPA def a ult ra t S A PU of 0.34 m 2 (USEPA, 1994). EPA’s default hum an values are 13.8 L/m i n ( 20

49 This equa tion is the reduce d , defaul t versi o n of Eq uati on 4-23 of the Inh a l a tio n Dosime tr y Metho dol ogy

. Equa tio n 4-23 is reduced t o th is for m c onsist e nt wit h the de rivat i on o f the reduced for m o f the RGDR eq uatio n of
extrat ho racic effects describe d in section 4.3

. 6.1 and Appen d ix I o f the In h a lat i on D o sime try Meth odo lo gy

. A-5m 3 /day) for V e (which yi elds a Q-alv of 9.7 L/ m i n) and 54 m 2 for SA PU (USEPA, 1994). The RGDR for the PU re gion (RGDR PU ) is calculated using these values fo r the rat and the hum an, a s shown in Equation A-3. The example also assum e s a NOAEL [ ADJ] of 0.16 m g / m 3 as the point of departure

. The NOAE L [H E C ] is the NOAE L [ ADJ] m u ltiplied b y the RGDR PU
. Table A-3 below provides the Q- alv values for hum a ns base d on the daily tim e -budgeted V e for di ffe r e nt a g es a nd a c t i v ity l e ve l s from the ICRP pub lication (1994). SA data for the PU region in the ICRP publication are es tim a ted using an allom e tric scaling m o del f itted to data f r om a morphom e tric analys is of SA PU in a sample of seven children (ranging in age from 26 days to 5 years) and eight adults (Zeltner et al., 1987). ORD selected the Ze ltner analysis for this exam ple because these SA PU data are based on e m pirical m o rphom etric m easur em ents of hum a n lungs as opposed to scaled estim ates determ ined from lung m o dels (such as those done by Yu and Xu, 1987 or Yu and Yoon, 1991). In addition, the child ren an d adult SA PU values calculated in the Zeltner analysis are supported by several independent studies that m e asured SA PU in children (Langston et al., 1984) or in adults using sim ilar morphom e tric techni ques (Crapo et al., 1982 & 1983; Stone et al., 1992; Mercer et al., 1994).

Table A-3 shows little variation in the resultant NOAEL [H E C ] across the grou ps in this exa m ple. The default procedure produces the lowest NOAE L [H E C ] value in Table A-3 and is , therefore, suf f i cient to cover all of these groups.

TABLE A

- 3
C O MP AR ISO N OF TH E H E C- D E F AULT (EPA, 199 4) WIT H EX AMPLE LO A E L [HEC] VA LU ES FOR HU MA NS OF DI FFERENT A G E S AND A C TI VITY PATTE RNS FOR THE PU LMON AR Y REGI ON

Total V e ( L /m in ) a Q-a l v ( hum a n ) ( L /m in ) b SA PU (hu m an) (m 2 ) (Q -al v / S A PU ) hu m a n ( L /m in -m 2 ) RGD R PU NOA E L HEC (mg/ m 3 ) Outdoor W o r k er, Male 17.5 12 139 0.088 3.3 0.53

Sede ntary W o r k er, Male 15.4 11 139 0.078 3.7 0.59

Sede ntary W o r k er, Fe male 12.6 8.8 114 0.077 3.8 0.61

15 Year-Ol d Male 14.0 9.8 108 0.091 3.2 0.51 15 Year-Ol d Fe male 10.9 7.6 100 0.076 3.8 0.61

10 Year-Ol d 10.6 7.4 62.0 0.12 2.4 0.38 5 Year-Ol d 6.1 4.3 37.3 0.11 2.6 0.42 1 Year-Ol d 3.6 2.5 18.5 0.14 2.1 0.34 3 Month-Ol d 2.0 1.4 11.0 0.13 2.2 0.35

HEC- Defaul t 13.8 9.7 54.0 0.18 1.6 0.26

a These v a lu es ar e from th e ICRP publication, Tab l es 8, 27, B.16 a, B.16b and B.17 (ICRP, 1994). b These values ar e from Zeltn er et al. (1987)

.

A-64. CATEGORY 3 GASES

The DAF for a Category 3 gas or vapor is based on the ratio of the animal blood:gas partition coefficient to the human blood:gas partition coe fficient and is typically calculated using the following equation: 

# ( H DAF = b / g 

# ) animal 

# ( (Equation A-4) H b / g 

# ) human

coefficient is primarily determ ined by the solubility of the gas in an aqueous The blood:gas partition medium as well as the protein and lipid content of the blood. There is little r eason to suspect that the blood:gas partition coefficient for a non-metabolized chemical will vary greatly across the human population. The limited data availa ble indicate no difference in th e blood:gas partition coefficient with age for methylene chloride in mice (Thomas et al., 1996), and for sevofl urane, isoflurane, and halothane in humans (Malviya and Lerman, 1990). Two studies examining the solubility of volatile anesthetics (isoflurane, enflurane, halothane, and methoxyflurane) in the blood and body tissues found higher blood:gas partition coefficients in adu lts compared with child ren (Lerman, et al., 1984 & 1986). Any variability in the blood:gas partition co efficient with age is expected to be less than the default value of 10 used for the uncertainty fact or for intraspecies variability when deriving the RfC. Any variability in the blood:g as partition coefficient with age is also not expected to cause a large overestimate or underestimate in the calculated cancer risk.

Because of the limited data available, the Inhalation Dosimetry Methodology makes the science policy decision to use a value of one for the ratio of the partition coefficients when the animal to human ratio exceeds one or when the animal or hu man value is unknown. At this time, all chemicals on IRIS for which both human and animal data are available have an animal to human ratio of partition coefficient greater than 1. 50 Therefore, the default assump tion of one is a conservative approach that is not likely to unde restimate the chemical-specific DAF.

5. PARTICLE DEPOSITION ACROSS AGE GROUPS

The DAF for a particle causing an effect in the respiratory tract, the Regional Dose Deposition Ratio (RDDR r ), is based on the animal to human ratio of the V e and the fractional deposition of the particle in that region (F r ), divided by the surface area of the region where the effect occurs (SA r ) (USEPA, 1994). Inherent in this derivation is the assumption that 100 percent of the deposited dose remains in the respiratory tract and a ny clearance mechanisms are not considered. The RDDR r is typically calculated using the following equation: ⎛ V ⎞

e ⎜ ⎜ SA × F
r ⎟ ⎟

RDDR = ⎝ r ⎠ animal (Equation A-5)

r ⎛ V ⎞

e ⎜ ⎜ × F
r ⎟ ⎟ ⎝ SA
r ⎠ human

50 While 1,4-dioxane has not yet been evaluated on IRIS, it provides an exception to this statement, in that the blood:gas partition coefficient is 2750 for mice, 1850 for rats, and 3650 for humans, yielding an animal to human ratio of 0.75 for mice and 0.51 for rats (Reitz et al., 1990). A-7The DAF for a particle causing an ex tra-respiratory (ER) effect, the RDDR ER , is based on the animal to human ratio of the V e and the total deposition of the partic le in the entire respiratory tract (F total ), divided by body weight (BW) (USEPA, 1994). The RDDR ER assumes that 100 percent of the deposited dose in the entire respiratory tract is ava ilable for uptake into the systemic circulation. The following general equation can be used to estimate the RDDR ER : ⎛ V
e ⎞ ⎜ × ⎜ F

BW total ⎟ ⎟ ⎝ ⎠

ER animal RDDR = (Equation A-6) ⎛ V ⎞ ⎜ e × ⎜ F

BW total ⎟ ⎟ ⎝ ⎠ human

The information on particle deposition in various age groups is quite limited. A discussion of the current state of the science can be found in the Air Quality Criteria for Particulate Matter Volume II
, Section 6.2.3.2 (USEPA, 2004; hereafter, PM Criteria Document ).

Experimental and modeling results are summarized in Table A-4. The re sults for experimental studies are mixed, some suggesting higher depositi on in children and others finding no difference across age groups. Bennett and Zeman (1998) and Schiller-Scotland et al. (1994) found no difference between total deposition of particles in the respiratory tract of children (aged 7 to14 and 6 to12, respectively) and adults for 1 to 2 micrometer particles. Sch iller-Scotland et al . did find twoto three-fold higher total particulate deposition in 6 to 12 year olds for particles of 2 to 3 micrometers in size. In addition, Bennett et al . (1997) found that deposition in the ETh region was 50 percent greater in children than adults. The PM Criteria Document concludes that “these...studies ...do not provide unequivocal evidence for significant differences in deposition between adults and children” (USEPA, 2004, page 6-29). The docu ment notes, however, that children may have higher activity levels and higher associated minute ventilation pe r lung size, potentially causing a greater size-specific dose of particles to the lung.

Modeled results suggest a higher deposition of partic les in the TB region of children when compared to adults, depending on the particle size (Xu a nd Yu (1986); Hofmann et al. (1989); Musante and Martonen (1999); Phalen and Oldham (2001); Asghari an et al. (2004); Ja rabek et al. (2005); Ginsberg et al. (2005)). Mixed results again are found in modeling studies for total deposition and deposition in other respiratory regions. In gene ral, where differences are observed in either experimental or modeled studies, variability in deposition between age groups has been reported to be most often in the range of 1- to 3-fold grea ter for children than for adults, but ranging from equivalency or less up to 7-fold greater. 51

51 A modeling analysis examining deposition fraction per unit area at various airway generations of the lung as a function of age for various particle sizes (ranging from 0.01 to 10 μ m) reported comparisons between a 3-month old and 21-year old that ranged from equivalency up to a 14-fold difference in this metric for some specific airway generations (Asgharian et al., 2004).

A-8TABLE A-4PARTICLE DEPOSITIONACROSS AGE GROUPSStudyParticleSizeResultsExperimental StudiesBecquemin et al. (1991)VariousNasal deposition higher in adults(up to 1.8-foldhigher at rest and up to 3.4-fold higher during exercise) thanchildren –meaning thatthoracic airways of children are less protectedthan those of adults.Bennett et al. (1997)4.5μm-ETh deposition of particles 50 percent greaterin children (higher foryounger ages).-No significantdifference in total respiratorytract deposition.Bennett and Zeman (1998)1-2μmNo difference between 7-14 year olds and adults intotal deposition of particles in the respiratorytract.Schiller-Scotland et al. (1994)1-2μmNo difference between 6-12 year olds and adults intotal deposition of particles in the respiratorytract.2-3μmTwo- to three-fold higher total deposition ofparticles in 6-12 year olds versusadults.Modeled StudiesAsgharian et al. (2004)0.01-10μm-Up to 1.2-foldhigher total deposition in 3month olds compared to adults in the TB region.-Up to 1.5-foldhigher total deposition in 8 year olds comparedto adults in the alveolar region.Total deposition higher in adults than 3and 23month olds (up to 2-fold).-Estimates of deposition fraction per unit area at various airwaygenerations of the lung and various particlesizes highest for 3 montholds compared to adults (up to 14-fold).Higher deposition alsoseen for 23month olds (up to 5-fold) and 8year olds (up to3-fold)compared withadults.No difference in deposition in 14 yearolds compared to adults.Cheng et al. (1995)0.0046-0.2μmNasal casts of children’s airways found increased deposition efficiencyfor ultrafine particleswith decreasingage, suggestingthat youngchildrenmayreceive a higher dose of ultrafine particles to theupper airways.Ginsberg et al. (2005)0.001-10μm-Higher deposition in 3montholds compared with adults for coarse and fine particles in theupper TB (up to 2-fold) and PU(up to 4­fold) regions.-Higher deposition in adultsin the lower TB region.Hoffmann et al. (1989)1-2μm-1.5- to 2-fold higher total deposition in the TB region for particles in resting 8year olds versus adults.-40-50 percent lower total deposition of particles in 8 year oldsunder conditions of exercise.Jarabek et al. (2005)0.3-6μm-Retainedmass in the TB region normalized toregional SA was comparedacross age groups.-Up to 2-fold lower deposition in 3month oldscompared to adults.-Up to 2-fold higher deposition in 3 year olds and 14 year oldscompared to adults.Musante andMartonen (1999)0.25-5μm-Total depositionwas generallyhigher in children (ages 7, 22,48, and 98months) than adults(e.g., total lung deposition in 48-montholds was 38 percent higher thanadults for 1μmparticles).-TB depositionmonotonicallydecreased asa function ofage (i.e.,younger children had increased TB deposition).-PU depositiongreatest in the 48and 98-monthchildren.Musante andMartonen (2000)2μm3-fold higher deposition of particles in thePU region for 7 month olds versusadults.Oldhamet al. (1997)VariousAirwaymodelsof trachea and bronchial airways showed total deposition in children (ages 4 and 7)greater than adult (up toapproximately7-fold higher for 4year oldscompared to adultsfor 4.5 μmparticles).Phalen and Oldham(2001)0.1-10μm-No difference in total depositionof particles in 2year olds versus adults.-Somewhat higher (13-81 percent; dependingon particlesize)deposition of particles in the TB region.-Lower deposition of particles in the PU region.Xu and Yu (1986)VariousIncreased totaldeposition (up to 1.5-fold higher) in children aged 6months, 2 years, and 8years compared withadults for particles ofvarying sizes.A-96. CONCL USIONS

The exam pl es and discu ssions inclu d ed in this appendix suggest that the Inhalation Dosimetr y Methodology’s default approaches for deri vation of the HEC for Category 1 gases with ef f ects in the ETh, TB, and PU regions and for Category 3 gases t ypically are sufficient to cover variation across hum a n age- and activity-level groups. The process for deriving an RfC from the HEC includes applying an uncer tain ty f actor (UF) to accoun t f o r with in -species va r i ability, add i ng f u rthe r protection. When deriving an IUR for a carcinogen, UFs are not use d. However the procedures for
est i m at i ng an I U R i n cor por at e conser vati ve assu mpt i ons t h at would likely accommodate the degree of variation observed in these ex am ples.

Experim e ntal and m odeling results f o r particles suggest the potential for sm all differences in deposition of particles in the resp iratory tract as a function of age. The assumption that 100 percen t of the deposited dose is available for uptake into the system ic circula tion (f or re mote acting toxican ts), or f o r activ ity in the r e spira t ory tr act (f or lo c a l toxicity) is lik ely to result in a n overestim ation of dose to the target tissue. Any s m all variation in deposition am ong age groups should be considered against the potential m a gnitude of such overestim ation. These differences in calculated deposition are sm all relative to the de fault 10-fold UF that accounts for intra-species variability in the derivation of the RfC. In addition, RfCs and IURs a r e developed for chronic
exposure an d will generally invo lve an exposure for m u ltiple y e ars. No add ition a l co rrection of the toxicity values for these age groups is needed when the RfC or IUR is used in a risk assessm ent. Calcula tions in th ese ex a m ples are based on em pirical data from s ources listed and referenced in ICRP Publication 66 (IC RP, 1994). While ORD selected the ICRP values as the best estim ates for these exam ples, other published values for V e and SA exist. The use of al t e r n at e valu es m a y change the LOAEL [H E C ] calculated for the various populations and lif e stages a nd m a y show more or less variability in results across the age and activity groups. In additi on, the exa m ples f o r the T B and P U regions are based on a hypothetical chem ical, since currently no RfCs for gases on IRIS are calculated based on anim al studies showing hea lth effects occurring in these regions of the respiratory system

. Given the param e ter values us ed in the default m e thod for calculating the H E C
, it is likely that the process woul d yield results suf f icient to cove r populations and life stages with varying activities and phys iologic ch aracteristics.

Note that the available data, albeit lim ited, genera lly support these conclus i ons. A s recom m e nded by the Reference Dose (RfD)/RfC Technical Panel (USEPA, 2002), EPA has been exploring issues involving dose to the young from inhalation exposures , both theoretically and experim e ntal ly as w e ll as further co nsidering th e existing an im al-to-human extrapolation procedures described in current

m e thodologies (e.g., USEPA, 1994). This is esp ecially im portant because of the significant developm ental changes that occur in the lung from birth well into adolescence (Pinkerton and Joad, 2000). The review and updating of th ese m e thodologies will be based on the best availabl e science.

A-107. REFERENCES CITED

Asgharian, B.; Ménache, M.G.; Miller, F.J. (2004). Modeling age-related particle deposition in humans

. Journal of Aerosol Medicine 17:213-224.

Becquemin, M.H.; Swift, D.L., et al. (1991). Particle deposition and re sistance in the noses of adults and children . The European Respiratory Journal 4:694-702.

Bennett, W. D.; Zeman, K. L., et al. (1997). Extrathoracic deposition of inhaled, coarse particles (4.5 m) in children vs. adults . In: Cherry, N.; Ogden, T., Ed s. Inhaled pa rticles VIII: proceedings of an international symposium on inhaled particles organized by the British Occupational Hygiene Society ; August 1996; Cambridge, UK. Annals of Occupational Hygiene 41(Suppl 1): 497-502.

Bennett, W. D.; Zeman, K. L. (1998). Deposition of fine particles in children spontaneously breathing at rest . Inhalation Toxicology 10: 831-842.

Cheng, Y.-S.; Smith, S.M., et al. (1995). Deposition of ultrafine aerosols and thoron progeny in replicas of nasal airways of young children . Aerosol Science and Technology 23: 541-552.

Crapo, J.D.; Young, S.L.; et al. (1983). Morphometric characteristics of cells in the alveolar region of mammalian lungs . American Review of Respiratory Disease 128: S42-S46.

Crapo, J.D.; Barry, B.E.; et al. (1982). Cell characteristics of the normal human lung. American Review of Respiratory Disease 5: 740-745.

Ginsberg, G.L.; Foos, B.P.; et al. (2005). Review and analysis of inhalat ion dosimetry methods for application of children’s risk assessment . Journal of Toxicology a nd Environmental Health, Part A 68: 573-615.

Hofmann, W.; Martonen, T. B.; Graham, R. C. (1989). Predicted deposition of nonhygroscopic aerosols in the human lung as a function of subject age . Journal of Aerosol Medicine 2: 49­ 68.

International Commission on Ra diological Protection (1994). ICRP Publication 66: Human Respiratory Tract Model fo r Radiological Protection . Annals of the ICRP, Volume 24/1-3, Tables B-16A and B-16B.

Jarabek, A.M.; Asgharian, B.; Miller, F.J. (2005). Dosimetric Adjustments for Interspecies Extrapolation of Inhaled P oorly Soluble Particles . Inhalation Toxico logy 17(7): 317-334.

Langston, C.; Kida, K.; et al. (1984). Human lung growth in late gestation and in the neonate. American Review of Respiratory Disease 129: 607-613.

Lerman, J.; Gregory, G.A.; et al. (1984). Age and solubility of vola tile anesthetics in blood

. Anesthesiology 61(2): 139-43.

A-11Lerman, J.; Schmitt-Bantel, B.I.; et al. (1986). Effect of age on the solubi lity of volatile anesthetics in human tissues. Anesthesiology 65(3): 307-11.

Malviya, S.; Lerman, J. (1990). The blood/gas solubilities of sevoflu rane, isoflurane, halothane, and serum constituent concentrations in neonates and adults. Anesthesiology 72(5): 793-6.

Mercer, R.R.; Russell, M.L.; Crapo, J.D. (1994). Alveolar Septal Structure in different species

. Journal of Applied Physiology 77 : 1060-1066.

Musante, C. J.; Martonen, T. B. (2000). Computer simulations of particle deposition in the developing human lung. Journal of the Air and Waste Management Association 50: 1426­ 1432.

Musante, C. J.; Martonen, T. B. (1999). Predicted deposition patterns of ambient particulate air pollutants in children’s lungs under resting conditions . In: Proceedings of the third colloquium on particulate ai r pollution and human health ; June, 1999; Durham, NC. Irvine, CA: University of California, Air Pollu tion Health Effects La boratory, p. 7-15 - 7-20.

Oldham, M. J.; Mannix, R. C.,; et al. (1997) Deposition of monodisperse particles in hollow models representing adult and child-size tracheobronchial airways. Health Physics 72: 827-834.

Phalen, R. F.; Oldham, M. J. (2001). Methods for modeling particle de position as a function of age. Respiratory Physiology 128: 119-130.

Pinkerton, K.E.; Joad, J.P. (2000). The mammalian respiratory syst em and critical windows of exposure for children’s health. Environmental Health Pers pectives 108(Suppl 4): 457-62.

Reitz, R.H.; McCrosky, P.S., et al. (1990). Development of a physiologically based pharmacokinetic model for risk assessment with 1,4-dioxane. Toxicology and Applie d Pharmacology 105: 37­ 54.

Schiller-Scotland, C.F.; Hl awa, R.; et al. (1994). Experimental data for total deposition in the respiratory tract of children . Toxicological Lett ers 72(1-3): 137-44.

Stone, K.C., Mercer, R.R. et al. (1992). Allometric relationships of cell numbers and size in the mammalian lung. American Journal of Respiratory Cell Molecular Biology 6: 235-243.

Thomas, R.W.; Yang, R.S.; et al. (1996). PBPK modeling/Monte Carlo simulation of methylene chloride kinetic changes in mice in relati on to age and acute, subchronic, and chronic inhalation exposure . Environmental Health Pers pectives 104(8): 858-65.

U.S. EPA. (1997). Exposure Factors Handbook . Office of Research and Development, Washington, DC. EPA/600/P-95/002Fa. http://www.epa.gov/ncea/pdfs/efh/front.pdf

A-12U.S. EPA. (1994). Methods for Derivation of Inhalation Re ference Concentrations and Application of Inhalation Dosimetry . Office of Research and Development. Research Triangle Park, NC. EPA/600/8-90/066F. http://cfpub.epa.gov/n cea/cfm/recordisplay.cfm?deid=71993

. U.S. EPA. (2002). A Review of the Reference Dose and Reference Concentration Processes . Risk Assessment Forum, Washington, DC, EPA/630/P-02/002F. http://cfpub.epa.gov/ncea/raf/recordisplay.cfm?deid=55365

U.S. EPA. (2003). Integrated Risk Informati on System Summaries: Acrolein . Office of Research and Development, Washington, D.C. http://www.epa.gov/iris/subst/0364.htm

U.S. EPA. (2004). Air Quality Criteria for Part iculate Matter: Volume II. EPA/600/P-99/002aD. http://cfpub.epa.gov/ncea/CFM /recordisplay.cfm?deid=2832

U.S. EPA. (2005). Guidelines for Carcinogen Risk Assessment , Risk Assessment Forum, Washington, D.C. EPA/630/P-03/001F. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=116283

U.S. EPA. (2008). Integrated Ri sk Information System (IRIS) Glossary of Terms. Searched September 2008. http://www.epa.gov/iris/help_gloss.htm

West, J.B. (2000). Respiratory Physiology: The Essentials . Lippincott, Williams & Wilkins. 6 th Edition.

Xu, G.B., Yu, C.P. (1986). Effects of age on deposition of i nhaled aerosols in the human lung

. Aerosol science and Technology 5: 349-357.

Yu, C.P., Xu, G.B. (1987). Predictive models for deposition of inhaled diesel exhaust particles in humans and laboratory species . Research Report of the Health Effects Institute 10:3-22.

Yu, C.P., Yoon, K.J. (1991). Retention modeling of diesel exhaust particles in rats and humans

. Research Report of the Health Effects Institute 40:1-24.

Zeltner, T.B., Caduff, J.H., et al. (1987). The postnatal development and growth of the human lung. I. Morphometry. Respiratory Physiology 67: 247-267.

8. ADDITIONAL SOURCES OF RELATED INFORMATION

De Winter-Sorkina. R., Cassee, F.R. (2002). From concentration to dos e: factors influencing airborne particulate matter deposition in humans and rats. RIVM Report 650010031/2002.

Gehr et al. (1978). The normal human lung: ultrastructure and morphometric estimation of the

A-13diffusion capacity . Respiration Physiology 18: 519-522.

Various Authors. (2008). EPA Workshop on Children’s Inhalation Dosimetry and Health Effects for Risk Assessment . Journal of Toxicology and Envi ronmental Health, Part A 71:147-248.

Zoetis, T., Hurtt, M.E. (2003). Species comparison of lung development . Birth Defects Research 68: 121-124.

A-14APPE NDI X BAPPENDIX B

CHEMICALS ON IRIS WITH EXTRAP OLATED INHALATION UNIT RISKS

Table B-1 contains chemicals on the Environmenta l Protection Agency’s (EPA’s) Integrated Risk Information System (IRIS) with Inhalation Unit Risk (IUR) values calculated by extrapolation using the default ventilation rate and body weight from the oral Can cer Slope Factor (CSF). These chemicals cause tumors remote from the respiratory tract. Also listed is the year EPA verified the cancer assessment. The list wa s compiled in September 2008.

EPA recommends that extrapolated IURs should be used with risk Equations 6 and 11 in the main document without additional modification for calculat ion of cancer risk by the inhalation route of exposure. It is generally not a ppropriate to make adjustments based on ventilatio n rate and body weight using the intake equation, because the amount of the chemical that reaches the target site of the chemical through the inhalation pathway is not a simple function of the inhalation rate and body weight. Risk assessors should outline the uncertainti es involved in using extr apolated IURs in the risk characterization section of the risk assessment.

B-1TABLE B-1 CHEMICALS WITH EXTRAPOLATED INHALATION UNIT RISKS ON IRIS Chemical Year of Verification Acrylamide 1 1988 Aldrin 1987 Aramite 1991 Azobenzene 1988 Bromoform 1989 Chlordane 1997 Chloroform 1 1987 DDT 1987 1,2-Dichloroethane 1986 Dieldrin 1987 1,2-Diphenylhydrazine 1986 Heptachlor 1987 Heptachlor epoxide 1987 Hexachlorobenzene 1989 Hexachlorobutadiene 1 1986 Alpha-hexachlorocyclohexane 1986 Beta-hexachlorocyclohexane 1986 Technical-hexachlorocyclohexane 1986 Hexachlorodibenzo-p-dioxin mixture 1987 Hexachloroethane 1986 N-nitroso-di-n-butylamine 1986 N-nitrosodiethylamine 1986 N-nitrosodimethylamine 1986 N-nitrosopyrrolidine 1986 Polychlorinated biphenyls 1996 1,1,2,2-Tetrachloroethane 1986 1,1,1,2-Tetrachloroethane 1988 Toxaphene 1987 1,1,2-Trichloroethane 1986 2,4,6-Trichlorophenol 1989
1 Note that this chemical’s IUR is currently under review.

B-2APPE NDI X CAPPE NDI X C

STSC’s PROCESS FO R DE RIVI NG AL TERNATIVE INHALATI ON TOXICITY VAL UES

If Reference Concentration (RfC) and/or Inha lation Unit Risk (IUR) values f o r

an inhaled
contam inant are no t av ailable from the sources in the Environ m ental Prote c tion Agenc y ’s (EPA’s) Office of Solid W a ste and Em ergency Response (O SW ER) hierarchy, risk assessors should first contact the National Center for Environm ental Assessm ent’s (NCEA’s) Superfund Health Risk Technical Support Center (STSC) for guidance. 52 Risk assessors working on Superfund sites can contact STSC to determ i n e whether a provisiona l p eer-reviewed toxicity value (PPRTV) exists for a
contam inant; if not, the risk asse ssor, in cooperation with the ap propriate EP A Regional office m a y request that STSC develop a PPRTV docum ent or that STSC develop an i nhala tion toxicity value as a “consult.” The latter w ould be spec ific to the site in question only.

As a first choice, if hum an or whole an im al st udies exist providing a suitab l e No Observable Adverse Ef fect Leve l (N OAEL)/Lowest Observ a b le Adverse Effect Level (LOAEL) or Point of Departure (POD) f r om a Benchm ark Dose (BMD) analysis, th is data normally will be u s ed by STSC to develop an inhalation toxicity value. If, in addi tion, a suitable hum an in halation physiologically based pharm acokinetic (PBPK) m o del exists that can b e utilized to r e f i ne the dos e m e tric to th e targe t org a n, then this inf o rm a tion generally will be included in developing an inhalation toxicity value.

If no appropriate whole anim al or hum a n studies exist, but an a ppropriate peer reviewed hum a n inhalation P B PK model exists that has been valid ated by experim e ntal results, then STSC usually will a t tem p t to de riv e an inhalation toxicity va lu e f r om this model. If n one exis ts, b u t a suitable PBPK ani m al inhalation models exists, STSC m a y attem p t de vel oping a hum a n m odel and deriving an inhalation value.

PBPK m ode ling quantitatively describes the absorp t i on/ me t a bol i s m/ di s t ri but i on and elim ination of the chem ical from a point of entry (ora l, inhala tion, derm al) to the ta r g e t organ(s). In som e cases, an oral PBPK model can be extrapo l ated to the inha lation pathw a y, but care must be taken to consider direct pulm onary effects that m a y not be evident by oral dosing.

As a next approach, STSC typically will evalu a te de velopm ent of an inhalation toxic ity valu e u s in g a suitab l e su rrogate ch em ical base d on a quan titative structu r e-ac tiv ity re lationshi p (QSAR) m odel with struc t ur al selec tion c r iteria and solu b i l ity /to xicity considerations. ST SC m a y evaluate possible surrogate chem icals based on seve ral available structu r al m odels and provide a com p arison. Selection of the appropriate surrogate m a y depend on the weight of evidence of these models.

52 All contact w i th STSC shoul d be perfor m e d by an EPA re g i onal risk assessor. States and other ent ities s houl d first co ntact t h eir E P A re gio n a l risk assessor with quest ions on inhala tion t oxici ty values. Regional risk assessors can then conta c t STSC o n the i r behal f

. C-1If STSC use s any of the m e thods for developing toxicity values other than from human or whole anim al data, the va lue n o rm ally will be pres ente d as a “scre e ning” valu e with the caveat that it should not be used as a risk driver for a site wit hout consultation with the S T SC. The uncertainties associated w ith using toxicity values derived through PBPK modeling or QSAR, or with using a surrogate value should be described in the risk ch aracterization porti on of the risk assessm ent (see Section 9). Risk assessors are discouraged from perform i ng si mplistic route-to-route extrapolations from oral data using default assum p tions a bout Inhalation Rate (IR) and body weight (BW )

. 53

53 If STSC i ndica tes that no quan titati ve t oxic ity in fo rm at io n f

o r

t

h e i n h a l a t i o n r o u t e i s av ai l a bl e, t h e r i sk assesso r sh ou l d conduc t a q u ali t ative e v alua tio n of th is exp o s u re rou t e. The risk assessor sh ould discuss i n t

h e un cer t a i n t y sect i o n o f t

h e risk assess m e n t re port t h e i m plicati ons of n o t q u ant itati vel y assessing ris k s due to in hal a tion exp o sure s to c h e m ica l s lackin g in halat i on t oxici ty data

. See th e sect ion o n Ri sk Ch aract erizat ion (Section 9) in the m a in text of th i s guida nce for

m o re i n for m ati on.

C-2