TSD for Noncancer RELs June 2008


## Air Toxics Hot Spots
Risk Assessment Guidelines

Technical Support Document
For the Derivation of 

# Noncancer Reference Exposure Levels

Air Toxicology and Ep idemiology Branch

Office of Environmental Health Hazard Assessment California Environmental Protection Agency 1515 Clay Street, 16 th

## Floor
Oakland, California 94612



## As approved by the Scientific Review Panel, June 18, 2008

iTSD for Noncancer RELs June 2008

Project Lead: Andrew G. Salmon, M.A., D. Phil.
Reviewed by:
Melanie A. Marty, Ph.D.
Chief, Air Toxicology and Epidemiology Branch, OEHHA
George V. Alexeeff, Ph.D.
Deputy Director of Scientific Affairs, OEHHA

OEHHA also acknowledges the following contributors:

Amy Arcus, D.V.M. Robert Blaisdell, Ph.D. Joseph P. Brown, Ph.D. John Budroe, Ph.D. Shelley DuTeaux, Ph.D. MPH James F. Collins, Ph.D. Daryn E. Dodge, Ph.D.

Richard Lam, Ph.D. Melanie A. Marty, Ph.D. Mark Miller, MD Karen Riveles, Ph.D. MPH Andrew G. Salmon, M.A., D.Phil. Kathleen Vork, Ph.D. MPH Bruce Winder, Ph.D. Jianming Yang, Ph.D.
Air Toxicology and Epidemiology Branch
Office of Environmental Health Hazard Assessment

iiTSD for Noncancer RELs June 2008

CONTENTS

EXECUTIVE SUMMARY

........................................................................................................................ XI

1 INTRODUCTION

............................................................................................................................... ..1

1.1 OBJECTIVE

............................................................................................................................... .2

1.2 LEGISLATIVE MANDATES .....................................................................................................3

1.3 SUMMARY OF THE METHODOLOGICAL CHANGES FOR DEVELOPING ACUTE, EIGHT-HOUR AND CHRONIC RELS .................................................................6

2 REFERENCE EXPOSURE LEVEL (REL) DEVELOPMENT PROCESS .........................................8

2.1 LIST OF SUBSTANCES CONSIDERED ..................................................................................9

2.2 HAZARD INDEX APPROACH .................................................................................................9

3 POPULATIONS OF CONCERN

........................................................................................................ 12

3.1 CHILDREN AS A POPULATION OF CONCERN .................................................................13

3.2 DIFFERENCES BETWEEN CHILDREN AND ADULTS ......................................................14
3.2.1 Pharm acokinetic Differences

................................................................................... 15
3.2.2 Pharm acodynamic Differences

................................................................................ 23

3.3 RISK ASSESSMENT CONSIDERATIONS ............................................................................24

4 REL DEVELOPMENT METHODOLOGIES

.................................................................................... 26

4.1 CRITERIA FOR STUDIES UTILIZ ED TO IDENTIFY ADVERSE HEALTH EFFECTS ..............................................................................................................................2 6
4.1.1 Selection of Key Studies

.......................................................................................... 26

4.2 WEIGHT OF EVIDENCE EVALUATIONS AND CRITERIA FOR CAUSALITY ..............30
4.2.1 Strength of Association

............................................................................................ 31
4.2.2 Consistency of Association

...................................................................................... 32
4.2.3 Tem porality

.............................................................................................................. 33
4.2.4 Coherence and Biological Plausibility

..................................................................... 33
4.2.5 Dose-respon se

.......................................................................................................... 33
4.2.6 Specificity

................................................................................................................ 34
4.2.7 Experim ental Evidence

............................................................................................ 34

4.3 HAZARD IDENTIFICATION ..................................................................................................34

iiiTSD for Noncancer RELs June 2008

4.3.1 Definition of Adverse Effect

.................................................................................... 34
4.3.2 Nature of Adverse Effects

........................................................................................ 36
4.3.3 Severity of Effects

.................................................................................................... 36
4.3.4 Target Organs

........................................................................................................... 37

4.4 DOSE-RESPONSE ASSESSMENT .........................................................................................38
4.4.1 Estim ation of Threshold or Low Response Concentrations ..................................... 38
4.4.2 Extrapolatio n and Uncertainties in the Database ..................................................... 46
4.4.3 Types of Uncertainty and Variability

....................................................................... 46
4.4.4 Application of Mechanistic Data in Interspecies and Intraspe cies Extrapolation

............................................................................................................ 49
4.4.5 Extrapolating fro m LOAELs to NOAELs ............................................................... 52
4.4.6 Extrapolating from Study Dura tion to REL Reference Period ................................ 54
4.4.7 Accounting for Potentially Greater H uman Susceptibility ...................................... 57
4.4.8 Incre ased Susceptibility of Sensitive Individuals .................................................... 61
4.4.9 Uncertainty Associated with Defi ciencies in the Overall Database

........................ 66
4.4.10 Summ ary of Uncertainty Factors

............................................................................. 68

4.5 SUPPORTING DATA ...............................................................................................................68

5 ACUTE REFERENCE EXPOSURE LEVELS

................................................................................... 70

5.1 TIME FRAME OF INTEREST .................................................................................................70

5.2 EXPOSURE DURATION AND PATTERNS ..........................................................................70
5.2.1 Exposure Concentration Averaging Period

.............................................................. 71

5.3 HUMAN EQUIVALENT CONCENTRATION (HEC) PROCEDURE FOR ACUTE RELS

............................................................................................................................... .....73

5.4 EFFECTS OF EXPOSURE DURAT ION – SPE CIAL CONSIDERATIONS FOR ACUTE EFFECTS ...............................................................................................................73
5.4.1 Concentration and Tim e Extrapolation using Haber’s Law ..................................... 73
5.4.2 Tim e Extrapolation for Acute RELs Based on Developmental Studies .................. 77

5.5 LOAEL TO NOAEL EXTRAPOLATION ...............................................................................77

5.6 PRE-EXISTING ACUTE EXPOSURE GUIDELINES ............................................................79
5.6.1 The California Am bient Air Quality Standards (CAAQS) ...................................... 80
5.6.2 The Threshold Lim it Value-Time Weighted Average (TLV-TWA) and Short-Term Exposure Limit (STEL)

........................................................................ 80

ivTSD for Noncancer RELs June 2008

5.6.3 Various Emergency Exposure Guidance Levels ...................................................... 81

5.7 AREAS FOR FURTHER RESEARCH .....................................................................................82
5.7.1 Acute Toxicity Data

................................................................................................. 82
5.7.2 LOAEL to NOAE L Uncertainty Factor

................................................................... 82
5.7.3 Inter species Uncertainty Factor

............................................................................... 82
5.7.4 Uncertainty Factor for Databas e Deficiencies ......................................................... 83
5.7.5 Tim e Extrapolation for Acute RELs

........................................................................ 83
5.7.6 Additivity o f Adverse Effects

.................................................................................. 83

6 EIGHT-HOUR REFERENCE EXPOSURE LEVELS

....................................................................... 84

6.1 POPULATIONS AT RISK ........................................................................................................84

6.2 CHARACTERIZATION OF 8-HOUR EXPOSURES ..............................................................85
6.2.1 Eight-Hour Averaging P eriod for Chronic Toxicity ................................................ 85
6.2.2 Eight-Hour Averaging P eriod fo r Acute Recurrent Toxicity ................................... 86
6.2.3 Eight-Hour REL Expos ure Duration Adjustments for Developmental Toxicants

.................................................................................................................. 86

6.3 HUMAN EQUIVALENT CONCENTRATION (HEC) AND UNCERTAINTY FACTOR APPLICATIONS .................................................................................................87

6.4 HAZARD INDEX CALCULATION ........................................................................................87

7 CHRONIC REFERENCE EXPOSURE LEVELS

.............................................................................. 88

7.1 PRIORITY FOR EVALUATION OF CHEMICALS ...............................................................88

7.2 EXPOSURE CONCENTRATION AVERAGING PERIOD ....................................................88
7.2.1 Effects of Exposure Continuity and Duration

.......................................................... 89
7.2.2 Differences between Lifetim e and Less-than-Lifetime Exposures .......................... 89

7.3 LOAEL TO NOAEL EXTRAPOLATION ...............................................................................91

7.4 HYPERPLASIA .........................................................................................................................92

7.5 PRE-EXISTING CHRONIC EXPOSURE GUIDELINES .......................................................92 7.5.1 U.S. EPA Reference Co ncentrations

........................................................................ 92 7.5.2 U.S. EPA R eference Doses

...................................................................................... 92 7.5.3 Occupationa l Threshold Limit Values

..................................................................... 93 7.5.4 Calif ornia Ambient Air Quality Standards .............................................................. 93

REFERENCES

............................................................................................................................... .............94

vTSD for Noncancer RELs June 2008

APPENDIX A: LIST OF ACRONYMS .....................................................................................................1
A.1 LIST OF ACRONYMS........................................................................................................... ...........2

APPENDIX B: ACUTE , 8-HOUR, AND CHRONIC REFERENCE EXP OSURE LEVELS (RELs) SUMMARY TABLE........................................................................................................... .....1
INTRODUCTION TO REFERENCE EXPOSURE LEVELS SUMMARY TABLE .............................2 ACUTE, 8-HOUR, AND CHRONI C REFERENCE EXPOSURE LEVELS (RELs) SUMMARY TABLE ..............................................................................................................3

APPENDIX C: SUBSTANCES FOR WHICH EMISSIONS MUST BE QUANTIFIED ...........................

APPENDIX D: INDI VIDUAL ACUTE, 8-HOUR, AND CHRONIC REFERENCE EXPOSURE LEVEL SUMMARIES............................................................................................................................

D.1 SUMMARIES USING THIS VERSION OF THE HOT SPOTS RISK ASSESSMENT GUIDELINE S.....................................................................................................................

...... D.1.A. Acetaldehyde................................................................................................................ D.1.B. Acrolein ........................................................................................................................ D.1.C. Arsenic.......................................................................................................................... D.1.D Formaldehyde................................................................................................................ D.1.E. Manganese .................................................................................................................... D.1.F. Mercury.........................................................................................................................

APPENDIX E: TOXICOKINETICS ..........................................................................................................1

E.1 APPLICATIONS OF PHARMACOKINETIC ANALYSIS AND PBPK MODELING ............2

E.2 PUBLISHED SUMMARIES OF AGE-DEPENDENT TOXICOKINETICS.............................4 E.2.1 Age-dependent Toxicokinetic parameters. ................................................................ 4 E.2.2 PBPK Models of Inter-individual Variability.......................................................... 15

E.3 OEHHA STUDIES USING PBPK MODELING AND SPECIES DIFFERENCES: ...............19
E.3.1 Materials and Methods............................................................................................. 20
E.3.2 Results..................................................................................................................

.... 24
E.3.3 Discussion ...............................................................................................................

. 41 E.3.4 Uncertainty Factor for Variabil ity within the Hum an Population ........................... 46 E.3.5 Adequacy of the UFH-k for Younger Ages – Newer Analyses............................... 47

E.4 TOXICOKINETIC MODEL PARAMETER S FOR INDIVIDUAL CHEMICALS.................51

E.5 TOXICOKINETICS: BERKELEY MADONNA MODEL CODES ........................................67 E.5.1 Model Code for Furan 0-5 yr Child ......................................................................... 67
E.5.2 Model Code for MTBE 0-6 Yr Child....................................................................... 68 E.5.3 Model Code for PCE 0-6 yr Child ........................................................................... 71

viTSD for Noncancer RELs June 2008 E.5.4 Model Code for BaP vapor 0-6 yr Child.................................................................. 73 E.5.5 Model Code for NAP/NO RT 0-6 yr Child.............................................................. 76 E.5.6 Model Code for BD/BMO RT 0-5 yr Child............................................................. 86
E.5.7 Model Code for BD/BMO/DEB 0-5 Yr Child......................................................... 95 E.5.8 Model Code for Styrene/SO RT (Sar angapani et al., 2002) 0-5 yr Child .............. 101 E.5.9 Model Code for Vinyl Chloride 0-5 yr Child ........................................................ 109 E.5.10 Model Code for TCE 0-5 yr child.......................................................................... 112 E.5.11 Model Code for Styrene/SO (Csa nady et al., 2003) 0-6 yr Child .......................... 117 E.5.12 Model Code for DCM 0-5 yr Child ....................................................................... 121 E.5.13 Model Code for Ethylene/Ethylene oxide 0-6 yr Child ......................................... 124 E.5.14 Model Code for Styrene/SO RT Mode l of Csanady et al. (2003) Adult ............... 127 E.5.15 Model Code for Carbon tetrachloride 0-6 yr Child................................................ 132 E.5.16 Model Code for Toluene 0-6 yr Child ................................................................... 133 E.5.17 Model Code for Xylene 0-6 Yr Child .................................................................... 135 E.5.18 Model Code for Toluene-Xylene Mixed Exposure 0-6 Yr Child .......................... 137

APPENDIX F: ESTIMATING HUMAN EQUIVALENT CO NCENTRATIONS USING THE U.S. EPA DEFAULT APPROACH ...................................................................................................... 1
F.1 ESTIMATING HUMAN EQUIVALE NT CONCENTRATIONS USING THE U.S. EPA DEFAULT APPROACH ...............................................................................................1 F.1.1 Gases with Respiratory Effects.................................................................................. 1 F.1.2 Gases with Systemic Effects...................................................................................... 3
F.1.3 Particulates with Respiratory Effects

......................................................................... 3

F.2 HUMAN EQUIVALENT CONCENTRATION CALCULATION FOR CHILDREN..............4 F.2.1 Respiratory Differences be tween Children and Adults.............................................. 4
F.2.2 Calculation of Adult and Child HECs........................................................................ 8

F.3 CONC LUSIONS................................................................................................................ ........13

APPENDIX G: VALUE OF THE HABER’S LAW EXPONE NT (N) FOR VARIOUS GASES AND VAP ORS FOR ACUTE RELS DEVELOPED USING OE HHA (1999) PROCEDURES ..................................................................................................................... ................1

APPENDIX H. TARGET ORGANS OR SYST EMS USED IN ACUTE , 8-HOUR AND CHRONIC HAZARD INDEX CALCULATIONS

............................................................................... 1

viiTSD for Noncancer RELs June 2008

LIST OF FIGURES
Figure 1-1. Public and Peer Review Process for Establishi ng Reference Exposure Levels

.......... 5
Figure 2-1. REL Development Process

......................................................................................... 9
Figure 4-1 Log-probit modeling of dose-response data for silica 1 .............................................. 42
Figure 4-2. Interspe c ies Extrapolation

......................................................................................... 50
Figure 4-3 Intraspecies Extrapolation

.......................................................................................... 52
Figure E.3 1 Human/Animal Metric Ratios For Aliphatic Aldehydes. ................................................41
Figure F.2 1. Changes in Minute Volume /Tracheobronchial S urface Area with Age. ................10
Figure F.2 2. Increase in Number of Alveoli from Birth to Age 8. ..............................................11
Figure F.2 3. Decline in Minute Volume /Tracheobronchial S urface Area with Age...................12

LIST OF TABLES
Table 4.4.1. Possible D efault Uncertainty Fact ors used in Deriving A cute, 8-hour and Chronic RELs .........................................................................................................................47
Table 4.4.2. Che micals Studied by OEHHA in PBPK Analyses, Grouped by m odeled UFH-k for Infants and Children (see Appendix E) ................................................................66
Table 5.5.1. Relationship between E ffect Categories and Severity. .............................................79
Table 7.2.1. Average Life-span for Hu m ans VS. Experimental Animals ....................................90
TABLE B.1.1. OEHHA ACUTE (A), EIGHT-HOUR (8) AND CHRONIC (C) REFERE NCE EXPOSURE LEVEL (REL) SUMMARY ............................................................................................3
Table E.2.1. Compounds Showing Reduced E limination in Infants and/or Children 1 .................. 5

Table E.2.2. CYP1A2 Mediated Metabolic Pa rtial Clearances in Healthy Volunteers ................. 6

Table E.2.3. Inter-individual Variation in Toxicokinetics of Caffeine in Healthy Volunteers 1 .......................................................................................................................... 7

Table E.2.4. Toxicokinetics of Caffeine: Com parisons Between Healthy Adults and Different Subgroups............................................................................................................ 8

Table E.2.5. Inter-individual Variation in T oxicokinetics of The ophylline in Healthy Volunteers

..................................................................................................................... .... 10

viiiTSD for Noncancer RELs June 2008 Table E.2.6. Toxicokinetics of Theophylline: Comparisons between Healthy Adults and Different Subgroups.......................................................................................................... 11

Table E.2.7. Inter-individual Variation in Toxicokinetics of Theobrom ine and Paraxanthine in Healthy Volunteers ................................................................................. 13
Table E.2.8. Pathway-specific TK-UFs for Children after O ral Exposure and Neonates after Intravenous Exposure ............................................................................................... 14

Table E.3.1. PBPK Model Predictions for Selected Chem icals: Low End of Range (1 μ g/m 3 x 8 hr/d, 24 hr simulations)................................................................................ 25

Table E.3.2. PBPK Model Predictions for Se lected Chem icals: High End of Range (10 mg/m 3 x 8 hr/d, 24 hr simulations)............................................................................. 27

Table E.3.3. PBPK Model Predictions fo r Ethylbenzene with Hum an Age-Specific Regressions and Alternative Metabolic Parameters (1 μ g/m 3 x 8 hr/d, 24-48 hr simulations)................................................................................................................... .... 29

Table E.3.4. PBPK Model Predictions for Et hylbenzene with Age-Specific Param eters Modeling of Neonatal Rat (1 μ g/m 3 x 8 hr/d, 24-48 hr simulations)............................... 31

Table E.3.5. PBPK Model Predictions for Toluene with Age-Specific Regressions (1 μ g/m 3 x 8 hr/d, 24 hr simulations)................................................................................ 32
Table E.3.6. PBPK Model Predictions for Vinyl Chloride with Age-Specific Regressions (1 μ g/m 3 x 8 hr/d, 24 hr simulations)................................................................................ 33

Table E.3.7. PBPK Model Predictions for Na phthalene/ Naphthalene Oxides (NPO) with Age-Specific Regressions (Naphthalene 1 μ g/m 3 x 8 hr/d, 24 hr simulations) ............... 34

Table E.3.8. PBPK Model Predictions for Styrene/ Styrene Oxide with Age-Specific Regressions (1 μ g/m 3 x 8 hr/d, 24 hr simulations) ........................................................... 35

Table E.3.9. PBPK Model Predictions for Fo rmaldehyde with Age-Specific Param eters from Clewell et al. 2003: Modeling of Neonatal and Immature Rat (1 μ g/m 3 x 8 hr/d, 24 hr simulations)................................................................................ 36

Table E.3.10. PBPK Model Predictions for Fo rm aldehyde with Age-Specific Parameters: Modeling of Human Children (1 μ g/m 3 x 8 hr/d, 24 hr simulations). .............................. 37
Table E.3.11. DAFs Summary Based on PBPK Modeling of Internal Dosimetry...................... 38

Table E.3.12. Human/Rat PBPK Model Pr edictions for Aliphatic Aldehydes: (1 μ g/m 3 x 8 hr/d, 24 hr simulations)................................................................................ 40
Table E.3.13. Summary of Infants’ and Children’s PBPK M odeling by OEHHA with Selected Environmental Toxican ts by Inhalation Exposure ............................................. 43

ixTSD for Noncancer RELs June 2008 Table E.3.14. Comparison of Slope s of Mild and Lethal Effects a ............................................... 47

Table E.4.1. PBPK Model Parameters for Furan 0-6 Years of Age ........................................... 51

Table E.4.2. PBPK Model Parameters for MTBE 0-6 Years of Age .......................................... 52
Table E.4.3. PBPK Model Parameters for PCE 0-6 Years of Age .............................................. 53
Table E.4.4. PBPK Model Parameters for BaP 0-6 Years of Age............................................... 54

Table E.4.5. PBPK-RT Model Paramete rs for NAP/NO 0-5 Years of Age ................................ 55

Table E.4.6. PBPK-RT Mode l Param eters for BD/BMO 0-5 Years of Age ............................... 56

Table E.4.7. PBPK Model Parameters for BD/BMO/DEB 0-5 Years of Age ............................. 57

Table E.4.8. PBPK-RT Model Parameters for Styrene/SO 0-5 Years of Age ............................. 58

Table E.4.9 PBPK Model Parameters fo r Vinyl Chloride 0-5 Years of Age ............................. 59

Table E.4.10. PBPK Model Parameters for TCE and Metabolites 0-5 Years of Age ................. 60
Table E.4.11. PBPK Model Parameters for DCM 0-5 Years of Age .......................................... 61

Table E.4.12. PBPK Model Parameters for Ethylene/EO 0-6 Years of Age ............................... 62
Table E.4.13. PBPK-RT Model Parameters for Styrene/SO Adult ............................................ 63

Table E.4.14. PBPK Model Parameters for Carbon Tetrachloride 0-6 Years of Age ................ 64
Table E.4.15. PBPK Model Parameters for Toluene 0-6 Years of Age ..................................... 65
Table E.4.16. PBPK Model Parameters for Xylene 0-6 Years of Age ....................................... 66
Table F.1.1. Default Lung Surface Ar ea Estim ates (U.S. EPA, 1994).......................................... 2
Table F.1.2. Intercept and Sl ope Parameters for Estimating Minute Volume from Body Weight

......................................................................................................................... ........ 2

Table F.1.3. Parameters for De position Efficiency Equation ........................................................ 4
Table F.2.1. Relative Minute Volume (MV) to S urface Area (SA) Ratios for Pulmonary, Tracheobronchial, and Extrathoracic Spaces in Children................................................... 9
Table G.1 Value of the Haber’s Law Expone nt (n) for Various Gases and Vapors for Acute RELs Developed Usi ng OEHHA 1999 Pr ocedures ................................................. 2

xTSD for Noncancer RELs June 2008



## Executive Summary

This document describes the methodology used in developing acute, 8-hour and chronic Reference Exposure Levels (RELs) for use in risk assessments conducted under California’s Air Toxics Hot Spots and Toxi c Air Contaminants programs. RELs are concentrations of a chemical at or below which adverse noncancer health effects are not anticipated to occur for a specified exposure duration. The basic methodology for REL development used previously by the Office of Environmental Health Hazard Assessment (OEHHA) and other agencies undertaking public health risk assessment remains unchanged. This consists of id entification of a point of depa rture, such as an exposure level in an animal experiment or an epidem iological study at which no adverse effects (or at least minimal adverse effects) are observe d, or a benchmark dose (a statistical estimate of a low response rate, typically 5%, in th e dose response curve fo r the chemical of concern). Extrapolation from this point of de parture to a health protective level for the target human population is by means of explic it models where possi ble, but more often by means of uncertainty factors.

This document addresses the SB 25 mandate to ensure that OEHHA’s risk assessment

m ethods adequately protect infants and child ren, and incorporates scientific advances since the methodologies for acute and chronic RELs were first developed. Methods are added for developing 8-hr RELs in addition to the traditional acute REL for infrequent 1- hr exposures, and the chronic REL for long- term, continuous exposures. We harmonize the methodologies for acute, eight-hour and chro nic RELs to the extent possible. This document also defines special procedures for derivation of RELs based on certain toxicological endpoints such as trigeminal ne rve transmitted irritation of the eyes, nose, and upper airway.
The following sections summarize the speci fic changes in m ethodology relative to the previous version of the Hot Spots guidelines for evaluation of noncancer health effects. These changes are described in detail in the main body of this report.
Use of Specific Models Rather than Uncertainty Factors when Possible
There are many information gaps in the data available for evaluating noncancer health im pacts of chemicals and setting appropriate RELs. The standard approach has been to divide an animal no-observed-adverse-effect -level (NOAEL) by uncer tainty factors (UFs) to help ensure that public health is protec ted. In recent years such techniques as the benchmark dose method (BMD) and physiologi cally based pharmacokinetic (PBPK) modeling have taken advantage of available data to quantitatively address uncertainties in the standard approach to noncancer REL de rivation. OEHHA recommends the use of these techniques wherever possible in order to address quantitatively the adequacy of acute and chronic RELs to protect the health of both children and adults. However, in some cases the available dose-response data are not suitable fo r application of the benchmark dose approach. Furthermore, it must be noted that data are not available for many chemicals to use PBPK modeling. T hus, while PBPK is a useful tool, the

xiTSD for Noncancer RELs June 2008 traditional paradigm (e.g., NOAEL or BMD divide d by UFs) will still be most frequently used.
Value of Default Intraspecies Uncertainty Factor (UF H )
The uncertainty factor used to account for intras pecies (inter-individua l) va riability in the human population (UF H ) has previously been assigned a default value of 10. Investigators have proposed subdividing the intraspecies uncertainty factor into √ 10 for toxicokinetic (UF H-k ) and √ 10 for toxicodynamic (UF H-d ) subfactors. The toxicokinetic uncertainty factor is meant to cover differences in humans in dispos ition of the toxicant (absorption, distribution, metabolism, and elimination), while the toxicodynamic uncertainty factor is meant to account for diffe rences in response at the receptor level. However, it appears that a de fault toxicokinetic value of √ 10 may not be adequate for all chemicals, routes of elimination, or for the entire population, in particular the subpopulation of infants. A toxicokinetic s ubfactor of 10 is ther efore recommended to protect infants, unless data ar e available to indicate that this subpopulation is not at higher risk due to differences in toxicoki netics. There may also be cases where a toxicokinetic subfactor larger than 10 is warranted based on chemical-specific factors. Currently, there are scant data available to indicate whether or not the toxicodynamic subfactor of √ 10 adequately protects infants and child ren. It is known that the developing organism can be many-fold more sensitive to toxicants such as lead (Pb), mercury (Hg), and diethylstilbestrol (DES) than a mature or ganism. Differentiating the contribution of toxicokinetic (TK) and toxicodyna mic (TD) differences is diffic ult. Where data indicate, a toxicodynamic uncertainty factor (UF H-d ) larger than the traditional value of √ 10 may be used. For example, there are toxicologica l endpoints of particular concern for infants and children in terms of increased susceptibility such as neurotoxicity (OEHHA, 2001). Potential red flags or triggers that may indicate the need for the use of an increased UF to account for developmental toxicity include: ne urotoxicity and neurobehavioral deficits, effects on the thyroid, mutage nicity, carcinogenicity, immuno toxicity, structure activity relationship models, endocrine agonist or antagonist activity, changes in cell proliferation, alteration of signal transducti on and/or gene expressi on, or disruptions in maternal homeostasis. In addition, it is impor tant to recognize impacts on the respiratory system by compounds that may induce or exac erbate asthma, as children are more impacted by asthma than adults, and allergic asthma may be viewed as resulting from impacts on the developing immune and respiratory systems. The assessor may increase the intraspecies uncertainty f actor for toxicodynamics in th ese cases, particularly where no data exist for early life stage exposure.

Additional Three-fold Databa se Deficiency Fa ctor
The United States Environmental Protection Ag ency (U.S. EPA) applies a general UF to Reference Concentration s (RfCs) and Dose s (RfDs) for chemicals lacking adequate toxicological studies (U.S. EPA, 2002a) to account for the potent ial for deriving an under-protective RfD/RfC as a result of an inco mplete characterization of the chemical’s toxicity. Although this was not used in the previous version of th e Hot Spots guidance, OEHHA now recommends an additional three-fo ld UF to apply in developing a REL for chemicals with substantial toxicological da ta gaps, including, but not limited to,

xiiTSD for Noncancer RELs June 2008 developmental toxicity. In some cases, it may be appropriate to apply a database deficiency factor larger than three-fold. This partially addresses the mandate under SB 25 to ensure that acute, chronic and eight -hour RELs are protective of infants’ and children’s health. The need for the additional database deficiency UF will be evaluated on a chemical-by-chemical basis and justif ied in the individual REL summaries.
Available data on mechanisms of toxicity, re activity, potential for system ic distribution, and structure activity relationships, will be considered in the decision to apply the additional database deficiency UF. In additi on, where evidence of eff ects at lower levels exists but available data are inadequate to use for a quantitative dose-response assessment, consideration will be given to applying a database deficiency UF.
Use of Modified Haber’s Law for Duration Adjustments
Previously, OEHHA adjusted the lowest obs erved adverse effect level (LOAEL) or no observed adverse effect level (NOAEL) in a study by m eans of the modified Haber’s Law procedure if the exposure duration of the study was different from the exposure duration of concern for an acute (1-hour) REL. OEH HA continues to recommend this adjustment, where appropriate, in developing acute RELs (and eight-hour RELs based on acute studies) for systemic toxicity and other endpoints where cumulation over time is anticipated. The current recommendation is to use a default value of 3 for the concentration exponent ( n ), rather than 2 as before, inthe absence of compound-specific information.
The most sensitive health endpoint for a number of acute RELs and some chronic RELs is tr igeminal nerve transmitted irritation of the eyes, nose or upper respiratory system. Trigeminal mediated irritation is a receptor-mediated mechanism, sometimes referred to as the common “chemical sense.” It app ears that Haber’s Law does not apply to trigeminal irritation effects, so OEHHA will not use Haber’s Law adjustments for instances in which a trigeminal mechanism for eye, nasal and respiratory irritation can be determined for the chemical and concentration of concern.
U.S. EPA Human Equivalent Concentrations (HEC) Procedure and Interspecies Extrapolation
OEHHA’s previous guidelines endorsed the use of the U.S. EPA Human Equivalent Concentration (HEC) procedure for chronic RE Ls. This pro cedure adjusts the internal dose in an animal inhalation study to the human equivalent dose taking into account differences in breathing rates, surface area of the respiratory tract and deposition. The U.S. EPA HEC procedure has been used in the past instead of the toxicokinetic component of the intersp ecies uncertainty factor, resulting in a total UF A of √ 10. However, the HEC procedure only adjusts th e exposure and does not account for other aspects of kinetics such as absorption, di stribution, metabolism and excretion. OEHHA will continue to use the U.S. EPA HEC pro cedure when appropriate, but will retain a toxicokinetic factor of 2 as part of the overa ll interspecies uncertainty factor (i.e., a total UF A of 6) when it is used, to reflect the gr eater uncertainty involved in this procedure than in full compound- and species -specific pharmacokinetic models.

xiiiTSD for Noncancer RELs June 2008
Physiologically Based Pharmacokinetic Modeling (PBPK)
PBPK modeling provides a scie ntific m ethodology fo r assessing interspecies differences and intraspecies variability. The PBPK approach requires chemical specific information or estimation techniques for parameters su ch as blood:air partition coefficients. The PBPK approach is potentially more accurate than other approaches such as the U.S. EPA’s HEC procedure because it takes into acco unt more parameters and uses chemical specific information. However, it requires much more data and therefore cannot be applied in all cases. The PBPK approach involves greater uncertainty when required parameters are estimated rather than meas ured. Validation of PBPK models with independent data is required for them to be used with confidence. While in many cases the variability in a parameter can be adequate ly incorporated into the model where data exist to characterize the distribut ion of this parameter, there is still residual uncertainty. Sensitivity analyses should be conducted to as certain the importance of specific variables in the model output and gain understanding of model uncertainty. OEHHA will use this methodology when possible, instead of the de fault application of the pharmacokinetic portions of the intraspecies and interspecies uncertainty factors and in preference to the HEC procedure. This change will apply to a ll three types of Reference Exposure Levels.
Exposure Duration Adjustments fo r Developmental Toxicity Data
Developmental toxicity presents difficulties as a critical endpoint for REL developm ent. Developmental toxicants can act during narrow temporal wind ows of fetal and postnatal development, often with multiple and/or poorly understood mechanisms. These chemicals can cause very specific anatomical lesions, more general impacts such as growth retardation, or functional deficits (e.g., behavioral changes). The tissue dose during the window of vulnerability may be the cri tical factor rather th an the total dose, or vice versa. The developmental studies avai lable to determine an acute, eight-hour or chronic REL may provide little clue as to the mechanism, window of temporal vulnerability, or relative importance of tota l dose versus peak tissue concentration as a determinant of toxicity.

In order to ensure that RELs based on developmental endpoints are protective, OEHHA will not use Haber’s Law to adjust the NOA EL or LOAEL i n an animal developmental study where the exposure duration of the study and averaging time of the REL (e.g., 1 hr) are different. Instead, since the actual timing and duration of the sensitive period are unknown, the NOAEL will serve as the basis of the REL without a time extrapolation adjustment. This should help ensure that th e REL will be protective if the tissue or air concentration during a particular temporal window is more of a determinant of developmental toxicity than total dose.
Eight-hour Reference Exposure Levels
OEHHA has developed a methodol ogy for a new class of Refe rence Exposure Levels for eight-hour exposure. This new type of REL is needed for th e Hot Spots Program in order to refine the risk assessment approach for the large number of facilities that operate and emit chemicals for 8 hours per day, 5 to 7 da ys per week and to utilize the advanced

xivTSD for Noncancer RELs June 2008 features in air dispersion modeling. The air dispersi on modeling in the Hot Spots Program has traditionally modeled such emissions as if they were uniformly emitted over 24 hours a day, continuously. Advances in computer capabilities have made it feasible to model more accurately the gr ound level concentrations of these emission scenarios by using meteorology obtained during the time when the facilities are actually operating (generally daytime). The majority of th e highly populated areas in California have significant diurnal-nocturnal me teorological differences that can affect the magnitude of the modeled risk and location of receptors.
The chronic noncancer health impacts on offsite workers (individuals working at other worksites in areas im pacted by the facility emissions) have been traditionally assessed with the 24-hour chronic RELs. Because o ffsite workers generally work 8 hours not 24, the eight-hour RELs will ensure a more accurate assessment of the health impacts of their exposures. The eight-hour RELs will also be useful for assessing the health impacts of exposure of children in schools. The eight -hour RELs should be protective against repeated daily eight-hour exposures, so the pharmacokinetics will need to be carefully considered when setting the standards. Th e accumulation of the chemical or cumulative injury from repeated daily exposures will need to be considered if either the total dose or the area under the exposure x time curve is the determinant of toxicity (reflecting a possible role of cumulative injury). Theref ore, some, but not all eight-hour RELs will have the same basis as the corresponding chronic REL.

Children’s Health in Relation to Chronic and Eight-hour RELs
Children and infants show biochemical, physio logical and behavioral differences from adults, which can result in hi gher tissue doses for som e chemicals. The significance of the higher tissue doses can vary considerabl y, particularly for infants, depending on the mechanism of toxicity. This becomes espe cially important when developing RELs for eight-hour repeated or chronic continuous e xposures. The chronic and eight-hour RELs are intended to be “safe levels” of lifetime or repeated eight-hour exposure to a particular chemical. The dose received by inhalation or by non-inhalation routes can be greater for infants and children than for adults in the same setting. Further, th e internal dose and the toxicological consequences may be different fo r infants and children than it is for adults. For some chemicals it may be appropriate to use infant or child parameters for PBPK modeling, when PBPK modeling can be used fo r a chronic or eight-hour REL. For other chemicals, it may be more appropriate to ta ke into consideration the greater exposure of children during exposure assessment as part of the total lifetime daily dose, and adult parameters for PBPK modeling may be the most appropriate.
Chronic Oral Reference Exposure Levels (RELs) and Children’s Health
Some chemicals in the Air Toxics Hot Spot s Prog ram are evaluated for multi-pathway exposures; in particular, non-vol atile chemicals that deposit on surfaces such as soil or food crops, and/or bioaccumulate in breast mil k. Oral RELs are used in risk assessment to address these pathways. Oral RELs are expressed in terms of a “safe” dose in mg/kg body weight (BW)-day. Thus, the higher doses in mg/kg that children receive from oral or dermal pathway exposure, relative to adults, can be directly assessed, when

xvTSD for Noncancer RELs June 2008 appropriate, by using the appropr iate exposure variables for children (e.g., soil ingestion rates). Whenever possible, OEHHA will assess differences between children and adults using PBPK modeling when developing oral RELs. As in the case of the inhalation RELs, an intraspecies UF of 30 ( √ 10 x 10) instead of 10 may be considered in some cases to protect children’s health when insufficient data exist for PBPK modeling. Likewise, an additional UF may be considered for toxi codynamic susceptibility or where there are substantial data gaps.

xviTSD for Noncancer RELs June 2008



## 1 Introduction

Hazardous substances are routinel y released into the environmen t as a result of predictable continuous, intermittent or short-te rm emissions from facilities and predictable process upsets or leaks. As a result, the public living or worki ng in communities surrounding industrial facilities is at risk of being exposed to airborne toxicants. Local air pollution contro l officers, industrial facility operators, and others have a need fo r clear guidance regardi ng the acute and chronic health effects of hazardous substances emitted into the air.
Under the Air Toxics Hot Spots Act (Senat e Bill 1731, Statutes of 1992), the Office of Environm ental Health Hazard Assessment (OEH HA) was required to develop risk assessment guidelines for stationary sources of airborne toxicants. In an in itial response to this mandate, OEHHA followed the recommendations of a th en current National Academy of Sciences/ National Research Council review (NRC, 1994) of risk assessment practices by establishing uniform, science-based guidelines to be used in the derivation of acute and chronic Reference Exposure Levels (RELs) applicable to the ge neral public exposed routinely to hazardous substances released into the environment. The products of this original guidelines development process were presented in the previous versio ns of the Technical S upport Documents (TSDs) comprising the Air Toxics Hot Spots Risk Assessment Guidelines (OEHHA, 2000a). Application of these RELs in ri sk assessments is described in the Air Toxics Hot Spots Risk Assessment Guidance Manual (OEHHA, 2003).

This document builds on that earlier effort by updating the methodology f or developing RELs for noncancer health endpoints and incorporating ad ditional information that has since become available. In particular, it wi ll address the mandate of the Children’s Environmental Health Protection Act (Senate Bill 25, Escutia; Chapter 731, Statutes of 1999; “SB 25”) to specifically consider children in evaluating the health effect s of Toxic Air Contaminants (TACs). In recent years, there have been growing concerns re garding children’s expos ure to environmental chemicals; the California Legislature passed SB 25 to help address these concerns. OEHHA’s initial response was to develop a prioritization rationale for identifying those TACs most likely to show differential health impacts on infant s and children, and to identify the five highest priority TACs as mandated by the statute (OEHHA, 2001). The present document continues the process by presenting revised methodology for the development of RELs for use in the Air Toxics Hot Spots program that takes into account possible differen tial impacts of TACs or other Hot Spots chemicals on children’s health. Th is document also presents updates to the methodology for REL development that reflect advances in the scie nce of risk assessment since OEHHA’s methodologies for acute and chronic RELs were previously presented. These advances include issues explor ed in various reports by the U. S. EPA (U.S. EPA, 2000; U.S. EPA, 2002a; U.S. EPA, 2004; U.S. EPA, 2006a; U.S. EPA, 2006b; U.S. EPA, 2006c; U.S. EPA, 2007b) and by committees of the National Academ y of Sciences/National Research Council (NRC, 2001; NRC, 2007) issued since OEHHA completed development of the previous guidelines, as well as a variety of research pape rs and reviews published inthe general scientific literature.
Quantitative risk assessment is used to derive noncancer health values including acute, chronic and the newly defined eight-hour RE Ls. OE HHA has aimed for consistency between the

Technical Support Document 1 June, 2008TSD for Noncancer RELs June 2008 recommended methods for developing acute, eigh t-hour and chronic RELs, and therefore has consolidated the previously se parate guidance for acute and ch ronic RELs into a single TSD covering all three current types of RELs. Th e use of benchmark dose methodology, presented as an option in a previous document, is now recomm ended as the default method when data permit. Additional discussion of pharmacokinetic methods for interspecies extrapolation is presented, and, most importantly, these guidelines respond to new scientific understa nding of the diversity in exposure and sensitivity of the human population, especi ally infants and children.

1.1 Objective
The objective of this document is to present our revised m ethods for deriving acute, eight-hour and chronic inhalation RELs for hazardous airbor ne substances. RELs are used in risk assessments to evaluate the potential for adverse noncancer public health impacts from facility emissions or similar localized sources in the Air Toxics Hot S pots Program, and from widespread exposures in the Toxic Air Contaminan ts program. The REL is an exposure at or below which adverse noncancer health effects ar e not expected to occur in a human population, including sensitive subgroups (e.g., infants and ch ildren), exposed to that concentration for a specified duration. These health-based RELs ar e applicable to risk characterization of air releases, defined in Health and Safety Code (H&SC) Section 44303, as:

“ including actual or poten tial spilling, leaking, pumpi ng, pouring, emitting, emptying, discharging, injecting, escaping, leaching, dumpi ng, or disposing of a substance into the ambient air and that results from routine operati on of a facility or t hat is predictable, including, but not limited to continuous and intermittent releases and predictable process upsets or leaks .”
These health guidance values are designed to be p rotective against the noncancer health effects of exposure to airborne chemicals. OEHHA ha s also developed or endorsed cancer potency factors that can be used to pr otect the general pub lic against the cancer causing effects of carcinogenic TACs (OEHHA, 2005a). In some cases, a carcinogenic chemical can cause noncancer health impacts and thus may have both types of health values. The acute RELs are designed to protect against a 1- hour exposure duration occurring in frequently (e.g., no more than once every two weeks) (see Section 5.4.1). Chroni c RELs are designed to protect against longterm exposure for 24 hours a day, and are used in the Air Toxics Hot Spots risk assessments to evaluate exposures anywhere from about 9 years up to a lifetime. Chronic exposure studies are defined by U.S. EPA and Cal/EPA based on trad itional toxicological testing, as 12% of a standard lifetime (e.g., for humans, 8.4 years). This document updates our procedures for acute and chronic RELs in order to en sure that the potentially greater vulnerability of children and infants is taken into consideration. In addition, OEHHA is devel oping eight-hour RELs, designed to protect against routin e exposures of that duration (which approximates an average workday) that could occur as often as daily.
Existing risk assessment methodologies use an uncertainty factor of 10 for intraspecies (interindividual) variability inthe human population (UF H ) which is assumed to protect children as well as other sensitive subpopulations. Such assump tions are crude but data have generally been lacking to use anything other than this assumpti on for most chemicals. This document evaluates available information in order to determine if more specific guidance for protecting children can

Technical Support Document 2 June, 2008TSD for Noncancer RELs June 2008 be incorporated into our standard procedur es for determining noncancer guidance values protective of children.
One of the challenges in devel oping a standard public health pr otective approach for acute, eighthour and chronic RELs is the variab ility in ava ilable data for different chemicals. Some wellstudied chemicals have huma n data, extensive animal data, and data necessary for pharmacokinetic modeling of tissue dose, while ot her chemicals may have limited data based on animal studies. OEHHA needs an approach th at allows development of a public health protective acute, eight-hour or chronic REL accoun ting for the potential greater vulnerability of children. Child protective default procedures need to be available in the absence of chemical specific information. However, more scientif ically sophisticated methods can be employed when chemical specific data are available.

1.2 Legislative Mandates
OEHHA is responsible for conducting health e ffects assessm ents of airborne chemicals, including chemicals listed under Health and Safety Code (H&S C) Section 44321, that are used by the California Air Resources Board in its risk management activities. As defined under the Air Toxics “Hot Spots” Information and Asse ssment Act of 1987 (Assembly Bill 2588; Chapter 1252, Statutes of 1987; California H&SC Section 44300 et seq ., as amended), a risk assessment includes a comprehensive analysis of the dispersion of hazardous substances in the environment and the potential for human exposure, and a quantitative assessment of both individual and population-wide health risks associ ated with those levels of exposure. This document establishes a standardized procedure for ge nerating the health-based values (acute, eight-hour and chronic RELs) used for assessing noncancer risks within the risk assessment process.
In preparing this document, OEHHA is respondin g to state legislation enacted in 1992 and 1999. SB 1731 (Chapter 1162, Statutes of 1992) re quired OEHHA to develop risk assessment guidelines for implementing the “Hot Spots” Act. The original guidelines were published as Technical Support Documents in 1999 – 2000 and as a condensed Guidance Manual in 2003 (OEHHA, 2003). This revision is in response to the Children’s Environmental Health Protection Act (SB 25), which requires the California Envi ronmental Protection Agency (CalEPA) to consider children specifically in setting Am bient Air Quality Sta ndards (AAQS) and in developing criteria for Toxic Air Contaminants (TACs). SB 25 requires OEHHA to consider the following in its health effects assessments and recommendations:
(1) exposure patterns among infants and children that result in disproporti onately high exposure, (2) special susceptibility of infants and children, (3) effects of simultaneous exposures to compou nds with the same mechanisms of action, and (4) any interactions of air pollutants.
The law requires OEHHA to evaluate available information on the Ambient Air Quality Standards (AAQS) and to devel op a list of Toxic Air Contaminan ts (TACs) that “may cause infants and children to be especially suscepti ble to illness”. OEHHA developed the document Prioritization of Toxic Air Contaminants under th e Children’s Environmental Health Protection Act (OEHHA, 2001) to address the id entification of the first five TACs with special impacts on

Technical Support Document 3 June, 2008TSD for Noncancer RELs June 2008 infants and children. That document underwent pub lic comment and peer review by the State’s Scientific Review Panel (SRP) on Toxic Air Contaminants. The statute requires OEHHA to evaluate 15 toxic air contaminants per year to ensure that our health effects assessments are adequate to protect infants and children, and use these assessment s to update the list of TACs that may cause infants and children to be especia lly susceptible to illness. To help meet the requirements of SB 1731 and SB 25, OEHHA in this document describes and evaluates the methodology to estimate RELs that explicitly co nsider infants and children, and derives such levels for specific chemicals.
OEHHA and the California Air Resources Board (C ARB) have set up a proc edure to f acilitate the public comment and peer review process n ecessary for implementation of SB 1731 and SB 25 ( Figure 1-1 ). This process includes internal OEHHA review, consultation with the California Air Pollution Control Officers Association (CAP COA) and the California Air Resources Board (CARB), a public comment period, and public w ork shops. In addition, the Scientific Review Panel (SRP) on Toxic Air Contaminants, administer ed by the CARB, will revi ew this document. OEHHA staff will respond to public comments on the changed methods and chemical-specific RELs, and update and revise the document as ap propriate. The SRP will review the revised document, public comments and OEHHA’s responses , and provide scientif ic input, which will be incorporated into the final draft.

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FIGURE 1-1. PUBLIC AND PEER REVIEW PROCESS FOR ESTABLISHING REFERENCE EXPOSURE LEVELS

Prioritization of Compounds

Adoption of “Technical Support Document for the Determination of Reference Exposure Levels” Development of “Technical Support Document” for

the Determination of Reference Exposure Levels

Consultation with Califor nia Air Pollution Control Officers Association ( CAPCOA )

Draft Documentation for Public Comment

Public Worksho p

Review of document and response to comments by Scientific Review Panel on Toxic Air Contaminants Selection of Candidate Compound

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1.3 Summary of the Methodological Changes for Developing Acute, Eight-hour and Chronic RELs

• If sufficient data are available for RE L de velopment, then a benchmark dose approach will be preferred over the traditional NOAEL/UF approach, unless some specific feature or limitation of the data makes this impossible.

• If sufficient data are available, PBPK modeling (Appendix E) will be used to determine the tissue dose in a default human model if an animal toxicity study is used. The relationship determined by the PBPK mode l will replace the pharmacokinetic portion (UF A-k ) of the interspecies uncertainty factor (UF A ). A smaller residual UF A-K of 2 may be used where the PBPK model is only a partial model (e .g., DAF for analogue chemical). In cases where a PBPK model is not available, UF A-k is assigned a default value of √ 10, and the total UF A would be 10.

• The HEC pr ocedure (Appendix F) may be used in place of a part of the UF A-k , leaving a residual value of 2 for this sub-factor (s ince the default value of the toxicodynamic component interspecies uncertainty factor, UF A-d , is √ 10, this results in an overall value of UF A = 6 when a HEC calculation is used, or 10 where no model of any kind is applied) (OEHHA, 2003). A modified HEC procedure using children’s physiological values may be used as appropriate.

• The m echanism of toxicity and pharmacokinetic s for chemicals will be evaluated when developing chronic and 8-hr R ELs in order to help determine whether long-term total dose or shorter-term tissue con centration is the predominant f actor for toxicity. Infants and children are potentially more vul nerable because of pharmacokinetic, pharmacodynamic, and exposure differences. Th erefore if PBPK m odeling is used to determine human equivalent concentration fr om an animal study, ch ildren’s or infants’ physiological and biochemical parameters may be used in the modeling as appropriate.

• Since children m ay also be more vulnera ble because of metabo lism (activation or deactivation), excretion differences, or speci al sensitivities of developing organs and tissues, PBPK modeling may be needed to m odel children’s tissue doses when a worker study is used to determine a LOAEL or NOAEL.

• When an uncertainty factor approach is used due to the lack of data for compoundspecific m odels of toxicokinetics and toxicodyn amics, an overall intr aspecies uncertainty factor (UF H ) of 30 rather than 10 (t oxicokinetic component, UF H-k =10; toxicodynamic component, UF H-d= √ 10) will be used as a default procedure to protect infants’ and children’s health, for example, in cases where differences in metabolism and excretion are key to the toxicological ac tivity. For direct-acting chemic als whose site of action is the point of first contact, a UF H-k of √ 10 may be sufficient. Where significant concern for toxicodynamic differences larger than three-fold is present, a larger UF H-d may be applied, such that the total UF H could be larger than 30..

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• The LOAELs or NOAELs for RELs based on trigeminally-transmitted irritation will no longer be adjusted using modi fied Haber’s Law when the e xposure duration of the study is different from the exposure duration for whic h the REL is intended to be protective. In other cases, where the modified Haber’s law procedure is app licable, the default value of the concentration exponent, used when chemical specific information is unavailable, for time extrapolation from longer to shorter REL averaging time will be 3, rather than 2 as previously.

• In order to ensure that RELs based on developmental endpoints are protective, OEHHA will not use Haber’s Law to adjust the NOA EL or LOAEL in an animal developmental study where the exposure duration of the study and averaging time of the REL (e.g., 1 hr) are different. Instead, since the actual timing and duration of the sensitive period are unknown, the NOAEL will serve as the basis of the REL without a time extrapolation adjustment.

• If the available tox icology literature does not include developmental studies for a chemical, or has substantial toxicological data gaps, the toxicological endpoints associated with the chemical, the chemical’s reactivity, mechanism of toxicity, structure activity relationships and other factors, will be evaluated to decide if an additional database deficiency factor, with a default value of 3, will be applied. A larger value may, in some extenuating circumstances, be applied.

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## 2 Reference Exposure Level (REL) Development Process

Reference Exposure Levels (RELs) are concentra tions or doses at or below which adverse noncancer health effects are not likely to o ccur in the general human population, including sensitive subpopulations, for specified exposure durations. A central assumption is that a population threshold exists below which adverse effects will not occur in a population; however, such a threshold is not observable and can only be estimated. Areas of uncertainty in estimating effects among a diverse huma n population are addressed usin g extrapolation and UFs.

RELs are based on the most sensitive relevant health effect rep orted in the medical and toxicological literature (see Secti on 4.0). One of the issues in selecting the appropriate health end point for REL development is the difficulty in distinguishing “adverse” health effects from “precursor” effects, which may be purely bioche mical changes indicative of initial events in a chain of consequences which might (or might not ) result in disease, and “adaptive” responses. The latter reflect impacts of a biological process which is not of itself harmful or is within the capacity of normal biochemistry and physiology to accommodate without impairment of overall function of the organism. NRC (2007) has considered this issue and points out the need for a health-protective and case-specific approach to selection of endpoints, noting th at the concept of “adversity” is actually a continuum ranging from initial events such as contact and uptake of the toxicant, through distribution, metabolism and contact with the target tissue, to various grades of precursor event leading up to frank pathological changes. They poi nt out also that the degree of response over this continuum at a specific dos e level may vary widely between individuals, depending on their age, genetic constitution, nutriti on, prior health status and many other factors, not all of which can necessarily be predicted. OEHHA concurs in recommending a cautious selection of endpoint, emphasizing the importance of considering pr ecursor events and individual variability; this issue is discussed further in Section 4.3.2

. RELs are designed to protect the most sensitive individuals in the population in cluding infants and children by the selection of appropriate toxicological endpoi nts and extrapolation models, and by the inclusion of margins of safety in the form of various UFs. Since uncertainty factors are incorporated to address data gaps and uncertainties, exposures that exceed the REL do not automatically indicate an adverse health impact.
Figure 2-1 depicts the steps involved in developing RELs. A complete literature search is conducted f or each chemical, but the chemical summaries in Appendix D may only cite those studies contributing to the REL de velopment and reflecting relevant routes of exposure. After identifying critical studies and toxicological endpoints, we iden tify a point of departure on the dose-response curve for extrapol ating to the general human populat ion. Various procedures for dose and time extrapolation and use of uncerta inty factors are desc ribed in Section 4.

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FIGURE 2-1. REL DE VELOPMENT PROCESS

conduct literature search ⇓ choose best study, emphasizing human data ⇓ identify critical biological endpoint ⇓ estimate threshold for effect (benchmark or NOAEL) ⇓ temporal/dosimetric adjustments (time extrapolation, HEC, Children’s HEC, PBPK) ⇓
account for uncertainties in data (extrapolating animal data to humans; occupational studies to sensitive subgroups) ⇓ Reference Exposure Level (REL ) (listed in Appendix B & Appendix D )

NOAEL = No-Observed-Adverse-Effect Level; HEC = Human Equivalent Concentration; PBPK = physiologically-based pharmacokinetic models

2.1 List of Substances Considered
All substances listed by the California Air Res ources Board (CARB), whose em issions must be quantified for the Air Toxics “Hot Spots” Program, are considered for evaluation and development of RELs. The substances included on the Air Toxics “Hot Spots” Program List are those substances found on lists de veloped by the International Agen cy for Research on Cancer (IARC), the U.S. Environmental Protection Agen cy (U.S. EPA), the U.S. National Toxicology Program (NTP), the CARB ( i.e., the list used in the Toxic Air Contaminant Program), the Hazard Evaluation System and Information Servi ce (State of California), or on the Proposition 65 list of carcinogens and reproducti ve toxicants (State of Califor nia). The complete list of substances whose emissions must be qua ntified is contained in Appendix C.

2.2 Haz ard Index Approach
The Air Toxics “Hot Spots” Program uses RELs as indicators of pot ential adverse non cancer health effects. A “hazard index” (HI) approach is used to estimate potential health effects resulting from hazardous substances by compari ng measured or modeled exposure levels with RELs. (For a detailed description of this method, please refer to the document entitled The Air Toxics Hot Spots Program Guidance Manual for Preparation of Health Risk Assessments (OEHHA, 2003)), which is available online at:
http://www.oehha.ca.gov/air/hot _spots/pdf/HRAguidefinal.pdf

Technical Support Document 9 June, 2008TSD for Noncancer RELs June 2008 Cumulative exposure (to multiple chemicals and fr om multiple sources) has become a concern in recent years. For many facilities a large number of chemicals may be emitted or may be present in the air at the location of the individual receptor or exposed popul ation. To assess the cumulative impact of several chemicals present at the same time, it is important to consider the interaction of effects of the toxica nts. These interactions may resultin an overall effect that is equal to, less than, or greater than predicted from the effects observed with exposures to the individual chemicals (Ikeda, 1988; Jonker et al., 1990; DeVito et al., 2000). The potential for synergistic or antagonistic interactions has only been investigated for a small fraction of the millions of possible combinations of chemicals with potential human e xposure. Effects of multiple chemical exposures on human heal th remain an area for future study.
One of the specific mandates of SB25 is the c onsideration of cum ulativ e exposures to toxic chemicals, which has become a core concern for environmental justice in view of the tendency for disadvantaged communities to be located inareas with a high density of pollutant-emitting facilities, and near freeways and other heavily us ed traffic corridors with attendant local peak concentrations of mobile -source-related pollutants. They thus receive higher local pollutant exposures compared to the State-wide average. This adverse environmental milieu is often compounded by the presence of population factors tend ing towards more adve rse health impacts, such as less access to health care, poor nutriti on and poor housing. Cumulative exposures may consist of multiple sources of the same chemical impacting a single receptor, multiple chemical exposures from the same source, or combinations of these situati ons. The hazard index approach is useful in addressing the pr edicted effects of such cumulative exposures (Salmon, 2007).
In risk assessments using the HI approach for e ither acute, eight-hour or chronic exposures, the im pacts of exposures to multiple chemicals which impact the same target organ are treated as additive by default. The concept of a thre shold underlies the assumption of additivity in chemical interactions. Exposure to a single chemi cal in the air may not result in a toxic response if it is below the threshold nece ssary to elicit a response. Ho wever, simultaneous exposure to two similar chemicals at sub-threshold levels may re sult in a toxic response. This is taken into account by adding together the indi vidual ratios of the modeled con centration to the REL for all chemicals that impact the same target organ or system.
This may underestimate the effect in cases in whic h interactions are synerg istic, or overestim ate it if the effects are eith er not additive or antagonistic. Th ere are a few cases where synergism between different toxic chemical exposures ha s been identified, but most multiple exposure situations which have been examined quantitatively in fact do show simple additivity, at least at low to moderate doses. This is well illustrate d by the work on PCBs (DeVito et al., 2000; Crofton et al., 2005), which also shows that syne rgism or antagonism, perhaps related to enzyme induction or inhibition may be obser ved at higher doses. Additivity was also seen for phthalates causing male reproductive tract malformations in rats following co-exposure to di(n-butyl) phthalate (DHP) and diethylhexyl phthalate (DEH P) during sexual differentiation (Howdeshell et al., 2007). These observations support the use ofthe additivity assumption by default for lowdose exposures, but also indicate the need to consider synergistic or antagonistic interactions between chemicals in those special cases where they have been identified.
Another limitation of the HI approach to assess th e potential for health ef fects is the fact that different RELs have vastly different cumulative uncertainty factors depending on the quality of

Technical Support Document 10 June, 2008TSD for Noncancer RELs June 2008 the data. Thus the probability of adverse health impacts when the REL or HI is exceeded may be quite different with different chemicals.
For a particular target organ or system, the HI is calcu lated as fo llows (U.S. EPA, 2004):
HI = C 1 / REL 1 + C 2 / REL 2 + . . . C i / REL i where for i substances with th e same toxicological endpoint, HI = hazard index C i = concentration for the i th substance REL i = REL for the i th substance
Advances in computer capabilitie s and the developm ent of software programs, such as the Air Resources Board’s Hot Spots Analysis Reporti ng Program (HARP), have made assessment of chemical exposure from multiple stationary faci lities more practical. However, it should be borne in mind that both the cumulative exposures and the health impacts in children may be different from those in adults, because of phys iological, biochemical and behavioral factors (Hattis, 1996a; OEHHA, 2001; Miller et al., 2002).

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## 3 Populations of Concern

RELs developed since the beginning of the Ho t Spots Program are intended to protect the individuals who live or work in the vicinity of emissions of pot entially toxic substances. The general population consists of in dividuals with a wide range of susceptibility. An individual’s current level of susceptibility may be transitory or long lasting, and innate or induced by some prior exposure or event. Th e general population includes some people who are likely to be especially susceptible to developing adverse eff ects (e.g., infants, children, the elderly, pregnant women and those with acute or chronic illnesses). Individuals in the general population who may be at greater risk for developing advers e effects following chemical exposure include:

• those with increased exposure (e.g., infants, children, adults enga ged in physical activity),

• those undergoing physiological change (e.g., inf a nts, children and adolescents; pregnant women and their fetuses),

• individu als with impaired physiological c onditions (e.g., elderly persons, persons with existing diseases, persons who are immunosuppressed),

• individuals with lower levels of protective biological m echanisms due to genetic or epigenetic variability within th e population (U.S. EPA, 1994a) and

• m embers of communities impacted by multiple sources of exposure.
Less susceptible individuals are healthy adults without any gene tic or biological predisposition that m ay increase sensitivity to the chemical of concern. RELs are intended to protect both individuals at low risk for ch emical injury as well as iden tifiable sensitive subpopulations (groups of more highly suscepti ble individuals) from adverse h ealth effects in the event of exposure. There have been concerns that in fants and children in pa rticular may be more sensitive to some toxic agents, and that this di fference may not have been considered sufficiently in setting existing heal th protective standards. OEHHA ha s therefore been mandated under SB 25 to ensure that RELs are also protective of infants and childre n, and other sensitive subpopulations. More useful scientific information has become available in the last few years to evaluate the special vulnerabilities of infants and children and to thus ensure that the RELs are protective.
The elderly constitute another important group w here greater sensitivity to environmental toxicants may be anticipated. With aging, there is a general tendency for clearance mechanisms and other protective toxicokinetic processes to d ecline. There is also a tendency for reserve capacity, responsiveness of homeostatic mechanis ms and ability to repair cellular damage to decline with age. Thus the elderl y tend to show greater susceptibility to toxicants as a result of both toxicokinetic and toxicodynamic factors (E lDesoky, 2007). This has been shown as an important phenomenon for drugs, where adjustment of dose and even selection of therapeutic agents is modified for elderly patients (Gin sberg et al., 2005). The potentially enhanced sensitivity of older individuals has also been id entified as a cause for concern, and a stimulus for additional research and regulat ory activity, for environmental toxicants (Geller and Zenick,

Technical Support Document 12 June, 2008TSD for Noncancer RELs June 2008 2005). Although this document is primarily desi gned to address the mandate to consider the special susceptibilities of infants and children, th e same principles developed here can also be used in identifying and responding to concerns for the enhanced sensitivity of the elderly.
Because the true range of variability is unknow n, there m ay be a proportion of the population for whom the RELs will not be fully protective. It is OEHHA’s intent that the levels will protect nearly all individuals, including those who are identifiable at th e high end of susceptibility. However, they may not protect hypersensitive individuals (i.e.

, those who exhibit extremely rare or idiosyncratic responses that could not have been predicted fr om studying the health effects of the substance in animal studies, or population-based epidemiological studies of reasonable size).
While OEHHA has attempted to identify specifi c sensitive subgroups for each substance from the lite rature, it is not possible to identify a ll conditions predisposing toward adverse health effects following exposure to toxic substances. Because RELs pertain to inhalation exposures, the lungs are often the major target organ of t oxicity, and asthmatics are frequently identified as a sensitive subgroup. For most compounds, the range of inter-ind ividual variabil ity is poorly characterized. An exception is sulfur dioxide, wh ich has been studied in both normal as well as asthmatic individuals. In a study of asthmatic su bjects, there was a 7-fold distribution in the range of sulfur dioxide concentrations require d to produce bronchoconstriction (Horstman et al., 1986). Thus, it is reasonable to c onclude that asthmatics may be at least seven times as sensitive to the effects of sulfur dioxide as non-asthmatic individuals.
Hattis has presented an analysis of human vari ability in thresh old responses in pharmacodynamic and toxicological studies (Hattis, 1996a; Hattis, 1996b; Hattis et al., 1999). In many cases the variability in response in the general human population appears to be continuous and is well modeled by a log-normal distribution. The magnit ude of the variability depends greatly on the endpoint and on the slope of the dose-response curv e. In their analysis , some human threshold responses ranged over more than three orders of magnitude. Such continuous variability is hypothesized to reflect cumulative influences of a number of pol ymorphisms. These may be at various genetic loci, all of which individuall y have a small impact on the degree of dose dependence of the response, or there may be seve ral polymorphisms at a single locus, associated with a variety of different levels of response. In other cases the response may be primarily influenced by a single gene, with two relativ ely common variants havi ng markedly different properties. In this case the observed variability may appear to be heterogeneous, and is better described by a bimodal distribut ion or separate distributions.

3.1 Children as a Populatio n of Concern
In response to the potentially greater vulnerabil ity of infants and children to chem ical exposure compared to adults (reviewed by OEHHA 2001), revised procedures for development and reassessment of noncancer health standards are outlined here. These are intended to ensure that age-related sensitivities are taken into consider ation as far as possible in the development of noncancer health standards.
Many of the issues, which arise in ensuring adequate protection of children’s health, are the s ame for acute, eight-hour, and chronic RELs. In this document, our approach in addressing these issues will be two-fold.

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1. We have developed changes in the methodol ogy for REL derivation in order to ensure that these health values are pr otective of children’s health.
2. We have applied the changes in th e m ethodology to individual RELs.
Over time, we will add new RELs, and address the adequa cy of existing RELs that were developed with the initial methodologies. In recent years new methodologies have been developed to address uncertainti es more quantitatively in determ ining health-protective levels and to ensure public health protection. OE HHA recommends expanding the use of techniques such as the benchmark dose method and phys iologically based pharmacokinetic (PBPK) modeling wherever possible in order to improve th e protection of public hea lth with acute, eighthour and chronic RELs for all members of th e population, and for in fants and children in particular. As noted in the introduction, da ta gaps will prevent PBPK modeling for many chemicals, and in some cases, will make benchmark dose analysis difficult. Thus, the traditional UF approach remains an important method.

3.2 Differences betw een Children and Adults
Children’s potential vulnerability to toxic effects from chemicals can result from differences in exposure. For example:

• Children breathe m ore than adults on a per kg body weight basis and t hus inhale more of the pollutant.

• For non-inhalation routes of exposure, child ren are also m ore exposed on a per kg body weight basis than adults because they eat mo re food, drink more water, have more dermal contact with soil, and have hi gher rates of inadvertent soil ingestion than adults.

• Children m ay consume more of one type of food than adults and have a less diverse diet. Children may differ in terms of pharmacodynamics , particularly since m ore cell division and differentiation are occurring in children than in adults due to growth and organ development.

• Undifferentiated cells m ay be more prone to injury than are differentiated cells.

• Major organ developm ent occurs in utero and during early postnatal development.

• Disruption of m igration and diffe rentiation of one type of cell may alter that of another.

• Som e structures (e.g., the brain) conti nue to develop through adolescence.
Children and particularly neonates can be quite different pharm acokinetically from adults. Factors that affect absorption, distribution, metabolism, and elimination (ADME) of toxicants, often differ by age. Such factors include:

• Lung surface area available for absorption of gases, and airflow dyna mics that alter deposition of inhaled particulates.

• Activating or detoxifying enzym es such as cytochrome P450 enzymes and Phase II conjugating enzymes are known to be present in infants in amounts a nd ratios different from adults. Fetal forms of cytochrome P450 are present and ma y differ in activity towards many substrates compared with the adult forms.

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• Consequently, xenobiotic metabolism may occur through different pathways, be apportioned differently between competing pa thways, and occur more slowly than in adults.

• Elim ination may occur faster or mo re slowly than in adults.
These factors influencing vulnerability in childre n m ay change rapidly and may be present only for a period of weeks to months. In the case of prenatal development, periods of vulnerability could be as short as hours or da ys. In neonates, the variability in developmental stage appears to be wide for some processes including xenobiot ic metabolism and renal clearance (Islam and Schlipkoter, 1989). Consequently in ter-individual variability in su sceptibility in a particular age range may be much greater than in adults, and thus harder to characte rize. OEHHA addressed some of the behavioral, physiological and bioche mical differences between children and adults in OEHHA (2001) and in Miller et al. (2002).

3.2.1 Pharmacokinetic Differences

3.2.1.1 Absorption

3.2.1.1.1 Inhalation
The lungs are the major route of entry of vola tile airborne environm ental pollutants and the majority of airborne semivolatile and nonvola tile pollutants. Exposure to environmental pollutants during lung development has the potentia l to significantly affect the overall growth and function of the respiratory system in childr en. The effects of expos ure are likely to be different during each phase of development. Recent studies have found links between air pollution and preterm birth (Ritz and Yu, 1999; Sagiv et al., 2005; Wilhelm and Ritz, 2005), infant mortality (Loomis et al., 1999; Conceicao et al., 2001; Ha et al., 2001; Woodruff et al., 2006), deficits in lung function growth (Kunzli et al., 1997;Galizia and Kinney, 1999; Gauderman et al., 2004), and possibly, developm ent of asthma (Gauderman et al., 2005; McConnell et al., 2006). The lungs are structurally immature in ne onates and continue to mature throughout childhood (Fanucchi and Plopper, 1997; Plopper and Fanucchi, 2004; Fanucchi et al., 2006).
Lung development is a long-term, continuous proce ss that continues for up to eight years after birth. Lung function growth continues through adolescence. The deve lopm ent of the human lung can be divided into six stag es: embryonic, pseudo-glandular, ca nalicular, saccular, alveolar, and vascular maturation (Zeltner and Burri, 1987). The first four stages occur prior to birth during fetal development. By birth the alveolar stage has begun, and the newborn infant has about 10 million alveoli. By approximately ag e eight, when adult numbers of alveoli have developed, there are about 300 million alveoli. Concomitantly the alveolar surface area increases from about 3 m 2 at birth to about 75 m 2 in adults leading to anair-tissue gas exchange area some 25-fold larger in adults (Islam and Schlipkoter, 1989).
During the maturation time following birth, ther e are m ultifold increases in overall lung size, active cellular differentiation, cell division, bran ching morphogenesis, and alveolar formation (Tyrala et al., 1977; Harding et al., 2004). Ep isodic exposure to envi ronmental pollutants,

Technical Support Document 15 June, 2008TSD for Noncancer RELs June 2008 specifically ozone, compromises postnatal mor phogenesis of tracheobronchial airways in the monkey (Fanucchi et al., 2006).
Airways change in size and shap e with m aturation, altering de position patterns. In animal models, exposure to environmental ozone dur ing the early postnatal period alters the development of the distal pulmonary airways (Fanucchi et al., 2006). Lung function also continues to change, increasing until late adoles cence in both males and females. Chronic airway disease and decreased lung function in children exposed to ambient air pollution may be due to repeating cycles of injury and repair al tering normal lung maturation (Smiley-Jewell et al., 2000; Fanucchi et al., 2006).
Respiratory minute ventilation is increased in infants and children, resulting in a greater exposure per unit tim e on a weight basis and per unit surf ace area of lung, compared to adults. For inhalation exposures to equivale nt chemical concentrations, both indoor and outdoor, infants and children are at the same or greater risk of exposure based on thei r much higher minute ventilation on a body weight and lung surf ace area basis (i.e., mL/kg/m 2 /min) (Snodgrass, 1992).
The deposition of inspired particles in the lungs is dependent on particle size and anatom ical features of the respiratory tract. Depositi on occurs primarily thr ough impaction for coarser particles and through Brownian motion for finer part icles. Greater fractions of inhaled particles less than five μ m in diameter reach the distal airways co mpared to larger pa rticles. Particle deposition tends to be greater in children b ecause of the smaller diameters of the airways compared to adults, and models of particle depos ition indicate larger depo sition in the pulmonary region of 3 month old infants relative to adul ts (Ginsberg et al., 2004c; Snodgrass, 1992).

3.2.1.1.2 Other Routes
Ingestion is a major route by which infants and children are exposed to environmental chemicals (U.S. EPA, 2000). A number of fact ors m ay result in significant differences in the absorption of environmental pollutants by infants and children vs. adults. Most drugs ad ministered by the oral route are absorbed into the systemic circulati on by passive diffusion. The two factors most affecting this process are gastric pH and emptying time (Milsap and Jusko, 1994). Both processes vary with age from birth through infanc y and childhood. At birth the gastric acidity is neutral (pH 6-8) due to the pres ence of amniotic fluid in the stomach (Avery et al., 1966). Following birth, gastric acid appears in the first one to two days of life and increases during the first weeks to months approaching adult levels by three months of age (Miller, 1941). Premature infants may continue to have lowe r gastric acidity due to immature acid secretion. The pH of the stomach influences the absorbed dose of ionizable chemicals, thus altering the potential dose to the infant (Agunod et al., 1969).
Gastric emptying time influences th e fraction of an oral dose which is absorbed into the systemic circulation. The gastric emptyi ng rate in neonatal infants is variable and prolonged and is affected by both gestational and postnatal age (Signer, 1975; Siegel et al., 1984). Absorption rates for several chemicals (e.g., phenobarbital , digoxin, arabinose and xylose) increase throughout the first year of life. While delayed absorption seen in neonates is partially due to slower gastric emptying and gastrointestinal motility, other factors such as lower pancreatic

Technical Support Document 16 June, 2008TSD for Noncancer RELs June 2008 enzyme function and bile acid secretion as well as a higher gastrointestinal pH also play a role (Alcorn and McNamara, 2003).
Not all absorption processes depend on passive diffusion: som e toxic materials (especially metals) are carried by, or interfere with the operation of, physiologica l active transport processes, which show age-dependent changes. For instance , the decline in the ab sorption of lead by the gastrointestinal tract from 45% in children to 10% in adults probabl y reflects decreases in calcium receptors with age (Heath et al., 2003).
Skin permeability and hence dermal absorption change as the skin develops. Derm al absorption may be significantly higher in neonates due to an immature epidermis and increased skin hydration. The surface area/bodyweight ratio is also much higher in infants and children than adults (0.067 to 0.033 m 2 /kg vs . 0.025 m 2 /kg in adults) (Snodgrass, 1992). Severe toxicity has been observed in infants followi ng topical application of hexach lorophene (Tyrala et al., 1977) and isopropanol (McFadden and Haddow, 1969) due to higher absorbed dose in infants relative to adults on a body weight basis. Alternativel y, dermal administration may be the preferred therapeutic route in certain situations (e.g., theophylline in premature infants)

3.2.1.2 Distribution
Our knowledge of the distribution of chemical s in the body is perhaps best developed for pharm aceuticals, while much less is known about chemical distribution following environmental exposures. For this reason, th e discussion that follows relie s heavily on the pharmaceutical literature.

The distribution of absorbed chemicals in the infant and child is affected by a num ber of factors, primarily the concentration and t ypes of plasma proteins and the relative size of fluid, fat and tissue compartments of the body (Milsap and Ju sko, 1994). Total body water may be as high as 85 percent by weight in premature infants and 78 percent in full-term neonates versus 50-60 percent in adults (Friis-Hansen, 1961; Friis-Hans en, 1971). The percentage of body weight that is body water affects the volume of distribution of absorbed drugs and other chemicals. The apparent volume of distribution (Vd, measured in L/kg body weight) relates the amount of drug in the body to its plasma concentration. Chemi cals that are water-soluble have higher volumes of distribution, while those that are lipophilic have lower volumes of distribution in infants. For example, gentamycin, theophylline and phenytoin s how two to three-fold higher Vds in neonates than in adults. Conversely, the Vd in neonates for diazepam, which is more lipophilic, is only one-third that of the adult value (Milsap and Jusko, 1994).
The binding of absorbed chemicals to plasma proteins depends upon the quantity of binding proteins available, the binding or affinity constant of the chem ical for the protein(s), the number of available binding sites, and the presence of pathophysiological conditions, which may alter the binding interaction (Besunde r et al., 1988). The affinity of plasma albumin for acidic drugs increases along with total plasma protein concentra tion from birth into earlyinfancy (Morselli et al., 1980). The reduced plasma pr otein binding of drugs in new borns is probably due to lower total plasma protein concentration as well as such qualitative differences as persistence of fetal albumin with lower affinity for drugs and lower levels of γ -globulins and lipoproteins (Morselli et al., 1980). During early infancy plasma albumin, total protein concentrations, and α 1-acid

Technical Support Document 17 June, 2008TSD for Noncancer RELs June 2008 glycoprotein are lower and don’t reach adult values until one year of age (Brodersen et al., 1983; Herngren et al., 1983). Three of the drugs noted above (theophylline, diazepam and phenytoin) all exhibit lower protein binding (1 /3 to 1/10) in neonates versus adults (Morselli, 1976; Rane and Wilson, 1976; Morselli et al., 1980). In a ddition to the quantitative and qualitative differences in plasma proteins during early deve lopment, disturbances in acid-base balance and increased blood concentrations of endogenous substa nces such as free fatty acids and bilirubin can affect protein binding of drugs or the rele ase (i.e., displacement) of bound drugs or other exogenous chemicals. Lower levels of albumin and elevated free fatty acids and bilirubin in the neonate may result in a larger Vd of and hi gher unbound concentrations of trichloroacetic acid (TCA), a metabolite of perchloroethylene (P CE) and trichloroethylene (TCE), in the blood (Muller et al., 1972; Ginsberg, 2000).
For some chemicals, the route of exposure affect s the form of the chemical that appears in the blood. This in turn affects the binding and distribution of the ab sorbed chemical. For example, manganese appears to be absorbed from the gut primarily in the divalent form, with approximately 80% of it subsequently bound in plasma to ß 1 -globulin and albumin (Foradori et al., 1967). These manganese-protein complexes are efficiently removed from the blood during the first pass through the liver and returned to th e gut in bile for elimination, thus limiting their distribution. By contrast, the pul monary route of exposure results in much higher blood levels of manganese which are more widely distributed in the body (Roels et al., 1997). In the blood, unbound manganese may be converted by ceruloplasmin to the trivalent cation which is then bound by transferrin. Transferrin-manganese comp lexes are much less efficiently removed by the liver and thus survive first pass eliminati on to circulate to othe r tissues throughout the body (Gibbons et al., 1976).

Other factors that affect tissu e distribution of toxicants incl ude higher organ to body weight ratios in inf ants and children than adults, a nd the lack of a mature blood:brain and other tissue:blood barriers. Morphine is three to ten times more toxic to newborn than to adult rats due primarily to the higher permeability of the new born brain to morphine (Rozman and Klaassen, 1996), and the distribution of methylmercury to the br ain is greater if exposure occurs in utero or neonatally (Ballatori and Clarks on, 1982). Brain size in infants and children is much greater than in adults relative to body weight. A newborn’ s brain is one-third the size of an adult brain while its body weight is only about four percent that of adults (i.e., 3.0 vs. 70 kg) (Snodgrass, 1992). Cerebral blood flow is great er per brain weight in childre n vs. adults. A five-year old child has a cerebral flow of about 71 ml/min-100 g vs. 51 ml/min-100 g in an adult (Chiron et al., 1992). Thus not only is there a relatively greate r brain mass to body weight ratio in children, but the brain receives a higher blood flow.
Dosing of infants and children based on surf ace area instead o f body weight is generally preferred although this applies main ly to drugs that are distributed in extracellular body water. Environmental chemicals, which ar e often lipophilic, may pose a grea ter risk to children due to the possibility of enhanced dermal uptake due to increased skin surface area and permeability. In addition, lipophilic agents would have decreased volumes of distri bution in infants due to their lower body fat content compared to typical adults.

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3.2.1.3 Metabolism
The development of xenobiotic metabolizing enzyme s in utero and after birth affects the rates of activ ation of chemicals to toxic intermediates, and the detoxification and ultimately clearance of xenobiotic compounds. The most common metabo lic enzymes include the so-called Phase I enzymes, cytochrome P450 (CYP) isoforms, whic h are involved primarily in oxidative reactions, and the Phase II enzymes involved in conjuga ting the xenobiotic or, more commonly, its metabolite with endogenous substrate rendering th e molecule more amenable to excretion. Recent reviews have highlighted available info rmation on the ontogeny of the Phase I enzymes primarily in liver tissue, the main organ of xenobiotic metabolism (Cresteil, 1998; Hines and McCarver, 2002). The metabolic capacity of th e liver (as a function of body weight) generally increases rapidly to near adult levels early in life, but significant qua litative and quantitative differences exist in newborns and neonates. Most of the microsomal enzyme systems responsible for drug metabolism are present at birt h and their activities in crease with postnatal age (Morselli et al., 1980). Liver Phase I react ions (oxidation, reducti on, hydroxylation) develop rapidly during infancy (Stromland et al., 1994). The total cytochrome P450 (CYP) content of human liver microsomes is unchanged from fetal lif e through the first year of postnatal life and is approximately one-third the total adult conten t (Streissguth et al., 1991). There are fetal isoforms of the CYP enzymes, and the exogenous ch emical substrate kinetics of these forms are not well characterized. In general, the leve l of inducibility of fetal CYP forms is unknown (Pineiro-Carrero and Pineiro, 2004). The postu lated development of individual cytochrome P450 (CYP) forms during infancy and childhood ha s been summarized in a previous document (OEHHA, 2001, see Table 5). Except for CYP3A4 and CYP3A7 these data are based on immunological analyses for the presence of CYP mRNA and protein rather than on the metabolism of specific chemical substrates. Ingeneral, three groups of CYP P450 could be described:
(1) CYP3A7 and CYP4A1 presen t in fetal liver and activ e on endogenous substrates;
(2) an early neonatal group including C YP2D6 and CYP2E1 which surge within hours of birth; and
(3) a later developing neonatal group, CYP3A4, CY P2C’s, and CYP1A2 (Cresteil, 1998).
Treluyer et al. (1997) observed that treatm ent of infants with barbit urates resulted in induction of CYP2C activity and increased metabolism of diazep am and tolbutamide. Total CYP3A protein, a major cytochrome P450 enzyme responsible for biotransformation of many exogenous compounds, is relatively constant in neonates a nd adults, but the isoforms change. CYP3A7 expression peaks in the neonatal liver and declines over time to undete ctable levels in adult liver; CYP3A7 appears to be responsible for aryl hydrocarbon hydroxylase (AHH) activity in the fetus (Hakkola et al., 1998). CYP3A4 is the primary adult hepatic form of the 3A series, and is very low in neonatal liver increasing sl owly after birth; at one month there is about one-third of the CYP3A4 activity as an adult liver (Rice and Baro ne Jr., 2000). CYP2E1 is an important enzyme catalyzing metabolism of a number of envi ronmental contaminants including benzene, trichloroethylene and toluene. Following birth hepatic CYP2E1 increases gradually reaching about one-third of adult levels by one year of age and is essentially 100% of adult levels by 10 years of age (Rice, 1996). CYP2D6 levels are lo w in fetal hepatic tissu e and rise after birth

Technical Support Document 19 June, 2008TSD for Noncancer RELs June 2008 reaching about two-thirds of the adult levels in infant’s age one month to five-year old children (Treluyer et al., 1991). CYP2C9 and CYP2C19, the most abundant CYP 2 enzymes in adult human liver, appear in the week after birth, and are about 30% of adult levels up to one year of age (Treluyer et al., 1997). CYP1A2 appears betw een one and three months of age, and reaches about half of adult levels at one year (Hines and McCarver, 2 002). Evidence from both substrate activation and immunological detect ion indicates CYP1A1 is expre ssed in fetal liver, where it can activate such xenobiotics as benzo[a]pyrene and aflatoxin B1 (Hines and McCarver, 2002). CYP1A1 appears to be less important in adult live r but present in inducible form in extrahepatic tissues (Hakkola et al., 1998), wh ile CYP1B1 is present in bothadult and fetal extrahepatic tissues. Studies of pharmaceutical clearance de monstrate the ontogeny of cytochrome P450 in infants and children, including gender-based differe nces (e.g., caffeine demethylation) (Kearns et al., 2003).
While there has been some study of the developm ent of human CYP P450 enzymes and of the Phase II conjugation enzymes in the liver (reviewed in (Cresteil, 1998; Kearns et al., 2003; Hines and McCarver, 2002; McCarver and Hines, 2002)), there is less information about the timing of development of activity in other tissues. Watzka et al. (1999) observed sex- and age-related differences in CYP1A1 activity in the hu man brain, where enzyme activity increased dramatically from birth and reached adult levels by puberty. In the lung, animal studies have shown that exposure to environmental toxican ts (sidestream tobacco smoke) can induce cytochrome P450 enzymes resulting in earlier ac tivity (Gebremichael et al., 1995). The impacts on toxicity from activation of compounds by cyto chrome P450 enzymes in early life depends on the rate of detoxification as well as capacity for repair. In neonatal rabbits, repair of injury to pulmonary Clara cells by toxicants activated by cytochrome P450 enzymes is decreased resulting in permanent structural changes in the adult animal (Miles, 1983).
The activity of phase II conjugati on reactions, which are usually detox ifying, is generally lower at birth (Goldstein, 1983). Hence, there is concern that detoxifica tion and elimination of chemicals are slower in infants. Conjugation with glucuronic acid is significantly lower at birth with activity 2.5-fold below adult levels (Lehman and Fitzhugh, 1954). Glucuronidation generally matures to adult leve ls in two months, although gluc uronidation of some drugs does not reach adult levels until puberty (Calabrese, 1983). Reduced glucuronidation would result in slower removal of aniline, N-hydroxyarylamines, phenol, and benzene metabolites in neonates. Acetylation and sulfation reactions are generally high in newborn infants and rapidly reach adult levels. Thus, neonates may conjugate drugs or en vironmental chemicals with sulfate rather than glucuronic acid (e.g., acetaminophen) . Acetylation by the N-acetyl transferases and sulfation by sulfotransferases are generally hi gh in newborn infants and somewhat comparable to adult levels, although it may vary by tissue and by specific sulfotransferase (Renwick et al., 2000;McCarver and Hines, 2002). Infants are less susceptible to acetaminophen acute toxicity than adults due to their more active sulfation (Levy et al., 1975). There are several forms of glutathione (GSH) sulfotransferases (GSTs) with GST-P i prevalent in the fetus and decreasing postnatally. GSTalpha and GST-mu are detected in fetal liver and in crease over the first few years of life to adult levels (McCarver and Hines, 2002). GST-mu is involved in arene oxide detoxification. GSTalpha is two-fold more active in children 0.5 to 4 y ears of age than in adults. Plasma glutathione (GSH) is similar in children 0.5 to four year s of age and in adults (U.S. FDA, 2006). Blood esterase activity, which is less than half that of adults at birth, is more depressed in premature infants than in full-term infants and doesn’t reach the latter’s activity for ten to twelve months.

Technical Support Document 20 June, 2008TSD for Noncancer RELs June 2008 Esterase activity in newborns is two to ten-fold lower than the adult level. Low esterase activity coupled with lower volume of distribution may acc ount for prolonged effect of local anesthetics observed during delivery (Ecobichon and Stephe ns, 1973). Neonates and premature infants may be deficient in the detoxifica tion of organophosphorus (OP) inse cticides (Augustinsson and Barr, 1963; Cole et al., 2003; Costa et al., 2003; Costa et al., 2005). E poxide hydrolase, important in detoxifying reactive epoxide metabolites, is pres ent in fetal liver although at much reduced activity relative to adults (McCarver and Hines, 2002).
As a result of differing enzyme activity, some chem icals are metabolized by wholly different metabolic pathways depending on age. In infants, theophylline is N-methylated to caffeine, a minor pathway for adults in whom the majorityof theophylline dose is N-demethylated or Coxidized to monomethylxanthine s or methyl-uric acid. Severa l studies have evaluated agerelated pharmacokinetic differences in human s using information about drug disposition (Renwick and Lazarus, 1998; Renwick et al., 200 0; Ginsberg et al., 2002 ; Hattis et al., 2003). Calculation of internal doses as the area under the blood concentr ation times time curve (AUC) for the same doses (mg/kg) indicated that the majo r difference from adults occurs in preterm and full-term neonates and young infants (Renwick et al., 2000). Higher AUC internal doses in neonates and young infants versus adults were no ted for seven drugs which are substrates for glucuronidation, one with substrat e specificity for CYP1A2, and f our with substrate specificity for CYP3A4 metabolism, and inte r-individual variati on in elimination by these detoxification pathways did not differ by age group (Renwick et al., 2000). Ginsberg et al. (2002) evaluated pharmacokinetic information on 45 drugs in chil dren and adults metabolized by different cytochrome P450 pathways, Phase II conjugations, or eliminated unchanged by the kidney. These authors noted half-lives in infants three to nine-fold longer than those of adults. In evaluating the inter-individual vari ability by age, Hattis et al. (2003) noted that the largest interindividual variability occurre d in the youngest children, appare ntly due to variability in development of critical metabolism and eliminat ion pathways. Notably, these authors observed that for risk assessment modeling, unimodal dist ributions may be inadequate for young children and for overweight older children.
While the variations in pharmacokinetics with ag e are an important consideration in risk assessment, additional complexity is overl ain by genetic polymorphisms rendering some individuals more susceptible than others . Perera et al. (1999) showed that:

1. There is sig nificant transpl acental transfer of polycyclic aromatic hydrocarbons (PAHs) and environmental tobacco smoke constituents from mother to fetus.
2. PAH-DNA adducts in matern al and newborn white blood cells are increased from environmental exposure.
3. The fetus is more sensitive to genetic dam age than the mother.
4. Newborns with a specific restriction f rag ment length polymorphism (RFLP), CYP1A1 Msp1, had elevated numbers of adducts compared to those without the RFLP.
The report of Canalle et al. (2004) indicated that genetic varian ts in xenobiotic m etabolizing genes may play a significant role in the suscep tibility to acute lymphoblastic leukemia (ALL), the most frequent malignancy in children. The case-control st udy involved 113 Brazilian children with ALL and 221 matched controls. Carriers of the rare GSTP1 Val allele were at

Technical Support Document 21 June, 2008TSD for Noncancer RELs June 2008 higher risk of ALL (odds ratio (OR) = 2.7; 95% CI = 1.1-6.8; p = 0.04). No difference was seen for GSTM1, GSTT1 or for the mutant CYP1A1*2 and CYP2E1*3 variants. However, when the mutant CYP variants were analyzed in combin ation with GSTM1 and the risk elevating GSTP1, the risk of ALL was increased (OR = 10.3; 95% CI = 1.0-111.8; p = 0.05) suggesting a combined effect.

3.2.1.4 Excretion
Many drugs are more slowly eliminated in neonate s and infants than in adults (Kearns et al., 2003). A classic exam ple is the to xicity associated with chlora mphenicol in neonates resulting from a longer half-life (10 hr) compared to adu lts (2-5 hr) (Miles, 1983). This difference would also apply to some environmental contaminants in the drinking water. Differences in volume of distribution, metabolism, and the maturity of rena l and hepatic elimination processes all play a role. Premature infants may have very low gl omerular filtration rate s (GFRs) (0.6 to 0.8 mL/min) (Plunkett et al., 1992; Milsap and Jusko, 1994). Studies with a large number of drugs have shown that the large majority of these agen ts are more slowly eliminated in neonates and infants than in adults. While this may be part ly due to an increased volume of distribution for water-soluble drugs and their metabolites, additio nal factors may also be involved. At birth, glomerular function is more developed than tubu lar function and this persists for six months (Guignard et al., 1975; Hook and Hewitt, 1977; Arant Jr., 1978). At birth, the GFR is lower (2-4 ml/min), increases in the first few days (8-20 m l/min) and slowly increases to adult values by 8- 12 month old infants (Robillard et al., 1999; Kearns et al., 2003). Over the first two to three weeks of life, Guignard et al. ( 1975) reported a two-fold increase in insulin clearance. The GFR values in neonates ranged from 6.0 to 32.2 mL/min/m 2 with a mean value of 10.8 ± 1.0 mL/min/m 2 , n = 22. Premature infants may have GFRs as low as 0.6 to 0.8 mL/min (Plunkett et al., 1992; Milsap and Jusko, 1994). Early increases in GFR are re lated to: increases in cardiac output, decreases in peripheral vasc ular resistance, increases in m ean arterial pressure, increased surface area of the kidney for filtration, and increased membrane pore size (Morselli et al., 1980; Plunkett et al., 1992). For the first tw o to three months of life, GFR is lower than that of adults. Clearance values at 10 to 30 times lower than seen in adults have been reported for some compounds (e.g., aminoglycoside antib iotics) (Morselli etal., 1980; Morselli, 1989). These agerelated changes in renal function lead to d ecreased body clearance a nd prolonged blood halflives in neonates for any chemical that relies upon renal excretion for elimination.

Studies in animals have shown that newbor n and young animals have a reduced capacity to excrete chem icals into the bile compared to ad ult animals. Klaassen (1972) observed that the blood concentration of ouabain, a drug whose primary route of excretion is the bile, was sevenfold higher in seven-day old rats than in 39-da y old rats. Ouabain is 40-fold more toxic in newborn than adult rats. Similarly both indoc yanine green and sulfobr omophthalein and their respective glucuronides were excret ed more slowly in the bile of neonates than in adult rats (Klaassen, 1973). Ballatori and Clarkson (1982) found that the long half-l ife of methylmercury in neonatal rats was due to their inability to excr ete the chemical in the bile, which is the main elimination route in adults. It is anticipated that these findings are indicative of likely deficiencies in the biliary excretion of certain environmental chemicals in human neonates and young children (Hattis, 1996a).

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The use of various toxicokinetic factors in assess ing children’s risk is the subject of a recent comprehensive review (Ginsberg et al., 2004c). Th ese authors conclude that children are more toxicokinetically variable than adults because of their variable growth and maturation rates, in addition to the factors that creat e toxicokinetic variability in a dults that relate to genetics, nutrition, disease, body composition, and prescrip tion (and other) drug use. Children also present the problem of variable growth rates, wh ich can make even small age bins (subdivisions) relatively heterogeneous, especially if one in concerned about protec ting the tails of the distribution (e.g., 90th percentile). With greater variability, it is also more likely that a substantial fraction of a certain age group will lie outside the ha lf-log toxicokinetic variability range we normally allocate to the adult defaults.

3.2.2 Pharmacodynamic Differences
Much more information exists for pharmac okinetics as a function of age than for pharm acodynamics. Many changes in pharmacodynamics occur with age and the mechanisms underlying toxic effects are of great interest to toxicologists, however , quantitative data are sparse. The maturation of various systems, including the immune system , the nervous system, the reproductive system, the digestive system, and th e blood-brain barrier, refl ects qualitative and quantitative changes in receptors with ag e. Age-related differences in the LD 50 , which reflect changes in the dose-response curve with age, may be related to receptor changes. Examples of pharmacodynamic differences in the pharmaceutical literature include de velopment of Reye’s syndrome following aspirin administration in childr en but not adults (Bel ay et al., 1999), and greater risk for developing hypersensitivity reactions, including St evens-Johnson syndrome, when treated with lamotrigine (Guberman et al., 1999). Windows of susceptibility to various toxicants are seen during development. In human s, autism has been associated with thalidomide exposure during days 20 to 24 after conception (Stromland et al., 1994). Diphenylhydantoin, an anticonvulsant used to treat ep ilepsy, may cause human malfor mations including craniofacial anomalies and growth abnormalities (Eluma et al., 1984; Orup Jr. et al., 2003). In mice it causes different types and frequencies of malformati ons depending on when during gestation it is administered (Eluma et al., 1984; Buehler et al ., 1994). Other agents known to cause human developmental toxicity include am inopterin, diethylstilbestrol (DES ), ethyl alcohol in alcoholic beverages, etretinate, isotretinoin (reti noic acid), lead, and methylmercury.
In the case of ethyl alcohol, exposure in utero is associated with Fetal Alcohol Syndrome (FAS), a distinctive constellation of abnormalities at birth. In its more severe form, the syndrome is characterized by dysmorphogenesis of the head, h eart, limbs and brain, deficits in IQ and memory, and behavioral problems such as hype ractivity and adolescen t antisocial behavior (Streissguth et al., 1991). Similarly, lowered IQ and behavioral problems manifesting during childhood and later have also been associated with early life exposures to le ad (Needleman et al., 1990) and cigarette smoke (Williams et al., 1998; Maughan et al., 2001; Yolton et al., 2005). As a result, the insidious nature of exposure to toxic agents durin g development may become more evident later in life, years afte r cessation of the toxic exposure. Delayed neurotoxicity has been seen both in humans following developmental exposure to methylmercury in contaminated seafood, and in monkeys experimentally exposed to methylmercury in utero through puberty. Among humans with developmental exposure to me thylmercury, the manifestations of Minamata

Technical Support Document 23 June, 2008TSD for Noncancer RELs June 2008 disease were delayed for several years in some individuals following cessation of exposure, and got progressively worse in others (Harada, 1995). Compared to an unexposed cohort, individuals exposed to methylmercury 20-30 years previously experienced significant deficits in motor function and impairments in visual, auditory a nd somatosensory systems (reviewed in Rice and Barone (2000). Similarly in monkeys, signifi cant impairments of somatosensory and motor functions were observed up to 11 years follo wing cessation of methylmercury exposure compared to controls (Rice, 1996). Developmen tal neurotoxicity is al so a feature of human exposure to PCBs, as was initially noticed in children who suffered exposure to PCBs as a result of rice oil contamination, suchas the Yusho and YuCheng inci dents (Jacobson et al., 1990; Chen et al., 1994). Subsequent studies have shown ne urotoxic impacts of a wide range of PCBs and related compounds, by mechanisms involving both di rect impacts on the central nervous system and interference with neurodevelopment via disrup tion of the regulation and effects of thyroid hormones (Darras, 2008).
While the specifics of the mechanisms unde rlying the toxicodynam ic responses to these compounds have not been elucidated in most cases , the data generally in dicate a significantly greater vulnerability of developing versus matu re systems. In addition, it is important to recognize that the deleterious eff ects of exposure may not be imme diately apparent, and in fact, may not be evident until much later in life.

3.3 Risk Assessment Considerations The U.S. EPA recently developed a document entitled: A Fra mework for Assessing Health Risks of Environmental Exposures to Children (U.S. EPA, 2006c). This document presents considerations and questions for the risk assessor when evaluati ng the effects of life-stage at exposure on the toxic response or he alth outcome. A number of us eful questions that the risk assessor should consider when evaluating the da tabase on any chemical are discussed in the framework document. It should be noted that for the majority of chemicals in the Air Toxics Hot Spots Program, there will be limited data and th is matrix of questions will likely remain unanswered for the risk assessor. Some of the considerations for dose-response assessment are noted below:

• Are there lif e-stage specific outcomes in the da tabase for the chemical, particularly those with adequate information to conduct a quantitative does-response assessment?

• What is the most suscep tible life-stage eviden t in the available data or by inference from other information?

• Are there known windows of susceptibility or developm ental processes likely to be susceptible to the agent?

• Are there differences in the m echanism of t oxicity in immature and mature animals or humans?

• Are there kn own toxicodynamic differences by life-stage (for example, receptors, repair mechanisms, enzymes or processes involved in signal transduction or other key developmental processes)?

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• Are there likely differences in toxicokinetics th at can be modeled or estimated? Do those differences change over life-stages and how? Are there data to de scribe toxicokinetic differences coinciding with the most susceptible life-stage?

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## 4 REL Development Methodologies

OEHHA has developed uniform approaches for acute and chronic Reference Exposure Level (REL) development. The first descriptions of these approaches appeared in the Air Toxics Hot Spots Program Risk Assessment Guidelines, Part III Technical Support Document for the Determination of Noncancer Chronic Reference Exposure Levels, April 2000(OEHHA, 2000a) and the Air Toxics Hot Spots Program Risk Assessmen t Guidelines. Part 1: The Determination of Acute Reference Exposure Levels for Airborne Toxicants (OEHHA, 1999).
As noted in the Executive Summary and Introduction, OEHHA is updating these REL developm ent methodologies. A complete literatu re search is conducted for each chemical, but the chemical summaries in Appendix D may only cite those studies co ntributing to the REL development and reflecting relevant routes of e xposure. After identifying critical studies and toxicological endpoints, we id entify a point of departure on the dose-response curve for extrapolating to the general human populati on. Various procedures for dose and time extrapolation and use of uncertainty factors are described in Section 4.4.

4.1 Criter ia for Studies Utilized to Identify Adverse Health Effects
Although a wide variety of information may be re viewed, only certain key studies are used to develop RELs. The following criteria are used to determ ine the relevance and quality of data used for REL development.
Peer reviewed papers published in th e open scientific literature ar e the usual and preferred source of the data used in REL development, but othe r sources that may be used include government reports such as National Toxicology Program (NTP) studies, full laboratory reports of Good Laboratory Practices (GLP) complia nt or otherwise well-conducte d studies, and documents that have been reviewed by other impartial organizati ons but have not themselves been published in the literature, such as doctoral dissertations. These alternative sources are normally only used if they, or at least an appropriate summary of th em are publicly available online or by request. Occasionally it may be necessary to request addi tional data from the author of a published study: these data may be used in REL development, a nd will be detailed in the REL summary. Review papers are not used for REL development as they are considered second ary sources. Studies involving a single chemical ar e given preference over those with multiple simultaneous exposures, especially if these are not quantified. Studies us ing multiple exposure doses and clearly indicating dose-response information are preferred, but in some cases an inadequate toxicology database may necessitate the use of older studies in which such information is unclear. Such studies are used only if there is no other relevant study av ailable, and they are consistent with the general toxicology database.

4.1.1 Selection of Key Studies
An important step in the development of any REL is the iden tification of peer-reviewed research studies that contribute most sign ificantly to the weight of evid ence as to the degree of hazard presented to humans by a particular substan ce. The studies may i nvolve a human population studied in an epidemiological, c linical, or experimental exposur e setting, or they may involve

Technical Support Document 26 June, 2008TSD for Noncancer RELs June 2008 experimental studies with animals. These key st udies are given greatest weight in estimating the dose-response relationship for advers e effects, and in identifying the nature of the critical adverse effect.

4.1.1.1 Human Data
Human data are logically most relevant to as sessing hum an health effects associated with chemical exposures. Principles for evaluating human exposure studies fo r use in determining health-based exposure levels have been discussed (OEHHA, 1999; OEHHA, 2000a; OEHHA, 2003; OEHHA, 2005a). Whenever possible, RELs ha ve been based on human data with relevant routes of exposure (principally inhalation). Of the 51 acute RELs originally developed, 36 were based on human health effects (OEHHA, 1999), wh ile of the first 80 chronic RELs, 22 were based on human data (OEHHA, 2005a).
Human studies used in assessing health effect s of chem icals have included epidemiological studies, controlled exposure experi ments, and case reports. Each of these three study types can provide important information needed to protect pub lic health. When using these studies for risk assessment, several factors are important in eval uating their quality and in determining the level of certainty associated with thei r use. It should be noted that controlled studies of exposure in infants and children are rare outside of clinical trials.

4.1.1.1.1 Epidem iological Data
Epidemiological studies generally produce data on effects of chem ical exposure to a large number of persons. Areas of concern when interpreting epidemiological studies include exposure measurement, health effects measurement, and accounting for co-variables and confounding variables (Rothman and Greenland, 2005) . The population studied may consist of the general public or employees exposed in the wo rkplace to varying concentrations of airborne chemicals.
Exposure measures frequently represent the grea test weakness of available epidem iological studies. Continuous, long-term exposure monitoring of individual subjects is rarely available. Frequently it is necessary to use limited, s hort-term, exposure monitoring data, which in many cases are not specific to the individuals under stud y, in order to derive an estimate of what the individual exposures may have been. Occupatio nal exposures may vary over time as industrial hygiene practices change and individuals change jobs. Also, analytical methods have changed and in many cases improved over the years, and earlier measurements may be much less accurate, or not comparable to more recent data (due to different techniques and equipment for trapping and quantifying, especially for part icles and fibers, and recent development of biological monitoring methods). Thus, estimatin g exposure levels that existed in workplaces many years ago is difficult, and exposure measurements in population-based environmental studies may be even more problematic. Neverthe less, the degree to which air concentrations can be adequately estimated is critical in determ ining the usefulness of an epidemiological study.
Health effect measures in epidemiological studi es also frequently diffe r from those reported in experimental animal studies and must be carefully examined. Measurements of human health effects generally consist of reco rding observable effects, including clinical reports of disease or

Technical Support Document 27 June, 2008TSD for Noncancer RELs June 2008 disability. If tests are conducted specifically fo r a study, those tests are us ually non-invasive, but standard clinical hematology, X-ra ys and other standard medical re sults may also be available. Health effects data are comp ared with those compiled from a non-exposed group and may be presented as incidence, standard ized mortality ratios (SMR), odds ratio (OR) or relative risk (RR) ratios. Health effects with a long latency ma y be missed if the exposure duration or length of follow-up in the study is inadequate.
For epidemiological studies to be useful, co-v ariables and confounding va riables need to be controlled or rem oved from the study. Co-exposur e to other chemicals is also an important concern as a potentially conf ounding or modifying effect. O ccupational studies raise an additional concern in that genera lly healthy workers may be less se nsitive to the adverse effects of chemical exposures than some others in the general population, incl uding children, the elderly, carriers of genetic polymorphisms, which affect sensitivity, and persons with preexisting medical conditions. Gender-specific eff ects may be obscured by bias that may be present where a workplace is disproportionate by gender (NRC, 1986a).
“Negative” epidemiological studies (i.e., those not presenting an outcom e different from the null hypothesis, properly described as “non-positive”) pr esent additional difficulties in interpretation. Estimating the power of the study to detect advers e effects is important to indicate the maximum incidence consistent with the observed null result. In addition, statistica l confidence limits can be put around an observed null result. Alt hough non-positive epidemiological studies may be useful as supporting evidence in favor of a REL deri ved from another data se t, it is unlikely that such studies would themselves provide useful data for deriving a REL.

4.1.1.1.2 Controlled Hum an Exposure Studies
Controlled exposure studies have the advantages of having quan tified exposure concentrations and of being conducted with hum an subjects, thus combining two important features of human epidemiological and animal toxi city studies (Hackney and Linn, 1983). The limitations of such studies include:
(1) involve small sample sizes,
(2) have a very short exposure duration,
(3) use narrowly focused response measurements th at m ight miss significanthealth effects and
(4) usually only involve relatively healthy adults.
In spite of these potential shor tcom ings, controlled studies in human subjects, especially in sensitive subpopulations such as asthmatics, are given preference over anim al studies in the REL development process, particularly for acute RELs . Human studies were used only if they were consistent with the standard ethical practices of investigation at the time they were conducted. The preferred study is a modern, ethical study ap proved by an Institutional Review Board for Human Studies. Although data from exposur e of infants and children would help OEHHA address its mandate to protect children’s health , controlled studies of ex posures to infants and children are rare outside the contex t of clinical trials of potentia lly beneficial pharmaceuticals. Controlled exposures of children or infants to environmental ch emicals are difficult to justify

Technical Support Document 28 June, 2008TSD for Noncancer RELs June 2008 ethically, even at presumably safe levels, because their lack of maturity may result in increased and unpredicted susceptibility; al so, there are issues surrounding their free and informed consent with children.

4.1.1.1.3 Case Reports
Individual case reports of advers e effects as sociated with exposure s to a chemical can be useful, especially as qualitative confir mation that effects observed and qua ntified in animals also occur in exposed humans. Multiple case histories with the same endpoint are especially relevant. However, these reports are generally not appropriate for quantitative analysis because of the very small sample size and the usually unquantified e xposures (Goldstein, 1983). Only rarely would case reports be used as the basis for a proposed REL.

4.1.1.2 Animal Data
Animal toxicity studies are the most widely av ailable source of data for REL development. However, studies that address all the toxic endpoints of interest, which include , specifically, preand postnatal developmental toxicity as well as effects on adults, are not always available, and studies with the specific exposur e periods of one hour, ei ght hours, or with chronic exposure may not have been done.
Identification of the most appropria te anim al species requires cons ideration of all available data relevant to prediction of human effects from animal observations. Studies of the most sensitive species have frequently been selected as key st udies. Such an approach has the advantage of offering maximal protection, especially since humans may be more sensitive than laboratory animals in response to chemical exposure (Lehman and Fitzhugh, 1954). However, the animal species most sensitive to a substance is not necessa rily that most similar to humans in developing adverse effects from a particular exposure. In ge neral, of the animals used in laboratory studies, non-human primates are considered to be the mo st similar in response to exposures to toxic substances, but to date only the acute REL for hydrogen cyanide was developed using data from a controlled exposure of a non-human primate (the cynomolgus monkey, Macaca fascicularis ). Such studies are relatively rare; those that ar e conducted typically i nvolve less than lifetime exposure and a small number of individuals and thus have limited statistical power.
Selection of the animal model and key study can be influenced by what is known about hum an health effects, and relevant areas of similarity and dissimilarity betweenhumans and the test animal species (Calabrese, 1983). Comparis on of human and animal pharmacokinetics and metabolism may be useful in selecting the rele vant animal model for predicting human health effects. For example, hamsters and rabbits ha ve much greater metabolic rates than monkeys (Plopper et al., 1983). This may increase or decr ease their susceptibility to toxic substances relative to humans. However, in most instances it is not possible to determine which species responds most like humans.
An experimental study should have a clear rationale and protoc ol, use Good Laboratory Practice (GLP) standards (or equivalent), and use appropriate analysis methods, including statistical analysis (U.S. FDA, 2006). E xperimental study designs and cr iteria recommended by the NTP have been reviewed (Chhabra et al., 1990). Howeve r, the goal of protec ting public health must

Technical Support Document 29 June, 2008TSD for Noncancer RELs June 2008 be weighed with experimental design so that important endpoints are not missed and responses of relevant species are not ignored.
Previously some chronic RELs (e.g., naphthalene and 1,3-butadiene ) were calculated using data fro m the standard 2-year NTP chronic toxic ity/carcinogenicity study (OEHHA, 2000a). In many cases shorter screening studies, used for determ ining appropriate dose levels for the two-year study, are also reported and may contain additi onal useful information on noncancer toxic endpoints. In an NTP study usi ng the inhalation route, groups of 50 rats and mice (6-8 weeks old) of both sexes are exposed for two years to two or three concen trations of a chemical, and the animals are examined for changes in approxi mately 30 organs. Although the NTP study has been considered a gold standard for assessing chronic adverse e ffects, the protocol specifies young adult (8-10 week old rats or mice) animals as the starting point, so it does not include exposures of fetal, neonatal, pre-pubertal or ad olescent animals. Thus,the study design may miss or underestimate effects in young animals. Two curre nt animal tests most relevant to children’s health are (1) the developmenta l toxicity study, in which pregna nt females are exposed during specific periods of gestation, a nd (2) the two-generation reproductiv e study, in which parents and offspring are exposed to the chemical. The ab sence of one or both of these studies from a chemical’s database creates a serious data gap relating to children’s environmental health and may result in the application of a data deficiency uncertainty factor (UF D, typically √ 10, but possibly higher) to address a lack of developmental data (Section 4.4.9.1 ).

4.2 Weight of E vidence Evaluation s and Criteria for Causality A “weight-of-evidence” approach is generally used to describ e the body of evidence on whether or not exposure to a chemical causes a particular effect. Under this a pproach, the number and quality of toxicology and epidemio logical studies, as well as othe r sources of data on biological plausibility, are considered in making a scie ntific judgment (OEHHA, 2005b). OEHHA has not adopted a categorical ranking of the weight-of-evidence, but provi des a descriptive analysis of strengths and uncertainties of the evidence consider ed as part of the toxicity review supporting each REL. The U.S. EPA on the other hand has used a formal scheme of this type for their RfCs (U.S. EPA, 1994a).
Many of the proposed criteria for determinati on of causality are based on analyses of epidem iological studies (OEHHA, 2005b). Th ese same criteria are however of general applicability to animal toxicology studies, although the degree of emphasis and extent of likely problems differ between these two data types. In analyzing animal studies, the nature and extent of the exposure and the characte ristics of the exposed animals are generally well controlled. Under these circumstances, issues such as observation of a dose -response relationship, reproducibility of findings, and mechanism of acti on (including considerati on of its relevance to humans) are key elements of the weight-of-evid ence. On the other hand, for epidemiological studies the nature and extent of the exposur e is often uncertain quantitatively and even qualitatively, and the exposed population is subs tantially more diverse than in a controlled animal experiment. Selected me thodological issues that are considered in the review of the epidemiologic literature include:

Technical Support Document 30 June, 2008TSD for Noncancer RELs June 2008 1) the sample size of the study, which affect s the power to detect an effect;
2) the extent to which the analysis or desi gn takes into account potential conf ounders, or other risk factors;
3) over-adjustm ents for potential confounders, wh ich would lead to underestimating effects of the toxin;
4) selection bias, or whether the study groups we re com parable; including consideration of the “healthy worker effect” and survivor bias,
5) the potential for bias in ascertaining exposur e and, in particular, nondifferential exposure misclassification, which biases effect size estimates towards the null.
Criteria for evaluating a ssociations between exposure and he alth effects have been recommended by the International Agency for Research on Cancer (IARC, 2006) (http://monographs.iarc.fr/ENG/Preamble/inde x.php), and standard epidemiology texts (Lilienfeld and Lilienfeld, 1980; Rothman and Gr eenland, 1998). Much discussion has ensued over the last two centuries on causa l inference. Most epidemiologists utilize similar sets of causal guidelines, proposed by Bradford Hill (1971), which OEHHA has employed (OEHHA, 2005b).

It should be noted that the causa l criteria are gu idelines for judging whether a causal association exists b etween a factor and a disease, rather than hard-and-fast rules. Lilienfeld and Lilienfeld (1980) note that:

“ In medicine and public health, it w ould appe ar reasonable to adopt a pragmatic concept of causality. A causal relationship would be recognized to exist whenever evidence indicates that the factors form part of the complex of circ umstances that increases the probability of the occurrence of disease and that a diminution of one or more of these factors decreases the frequency of that disease. After all, the reason for determining the etiological factors of a disease is to apply this knowledge to prevent the disease. ”
Commonly used causal criteria, based on those of Bradford Hill (1971 ), are described briefly below. These considerations are described in more detail in Rothman and Greenland (1998), the Surgeon General’s Reports on Smoking (U.S . DHHS, 2004), and OEHHA’s environmental tobacco smoke (ETS) document (OEHHA, 2005b).

4.2.1 Strength of Association
A statistically significant strong as sociation, which is easier to dete ct if there is a high relative risk, between a factor and a di seas e is often viewed as an important criterion for inferring causality because, all othe r things being equal, a strong and statistically significant association makes alternative explanations for the disease le ss likely. However, as discussed in Rothman and Greenland (1998), the fact that a relative risk is small in magnitude does not exclude a casual association between the risk fact or and the outcome in question. Since it is more difficult to

Technical Support Document 31 June, 2008TSD for Noncancer RELs June 2008 detect (i.e., reach statistical significance) a small magnitude risk, they are just as likely to be causal as larger magnitude risks.
When assessing all evidence, it is important to consider the strength of the study design (particularly controlling for conf ounding variables, obtaining an unbiased sam ple, measurement error) and the level of statistical significance (i.e ., the ability to exclude a Type I [false positive] error). The power of the study to detect biologically meaningful effects (i.e ., the risk of a Type II [false negative] error) is important in consider ing studies that do not reach traditional (i.e., P<.05) statistical sign ificance, particularly if the biological endpoint is se rious. If the outcome is serious and the study small (i.e., low power), a larger P value (e.g., P< .10) may be adequate evidence for identifying an effect.
There are a number of examples of statistically s ignificant, small magnitude associations that are widely accepted as causal, such as causal links between air pollution and cardiovascular/pulmonary mortal ity and between second-hand smoke exposure and various cancers and heart disease. From a public health perspective, even a small magnitude increase in risk for a common disease can mean large numbe rs of people affected by the health outcome when exposure is frequent and widespread, as measured by the population attributable risk or attributable fraction. Small magnitude of associ ation must not be confused with statistical significance, which is much more important.

4.2.2 Consistency of Association
If several investigations find anasso ciation between a factor and a disease acr oss a range of populations, geographic locations, tim es, and under different circumst ances, then the factor is more likely to be causal. Consistency argues ag ainst hypotheses that the association is caused by some other factor(s) that varies across st udies. Unmeasured confounding is an unlikely explanation when the effect is observed consiste ntly across a number of studies in different populations, or when control ling for known confounders.

Relevant observations include sim ilarity of effects noted in differe nt studies. For example, if an effect was noted in only one of m a ny studies of a particular strain of laboratory rodent, or in only one of many epidemiological st udies, evidence for a causal asso ciation between the chemical exposure and the effect is weakened. Associations that are replicated in several studies of the same design and among different populations (or species for an imal studies) or geographical regions, using different epidemiological approaches, or considering different routes or sources of exposure are more likely to repres ent a causal rela tionship than isolated observations from single studies (IARC, 2006). If there ar e inconsistent results among inve stigations, possible reasons are sought (such as adequacy of sample size or control group, methods used to assess exposure, range in levels of exposure, over-correction for known confounde rs), and results of studies judged to be rigorous are emphasized over those of studies judged to be methodologically less rigorous. For example, studies with the best exposure assessment are more informative for assessing the associatio n than studies with limited exposure assessment, all else being equal.

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4.2.3 Temporality
Temporality means that the factor associated w ithcausing the disease occurs in time prior to development of the disease. The adverse health effect should occur at a time following exposure that is consistent with the natu re of the effect. For example, respiratory irritation immediately following exposure to an irritant vapor is tempora lly consistent, whereas effects noted years later may not be. On the other hand, tumors, noted immediately following exposure, might be temporally inconsistent with a causal relationshi p, but tumors arising after a latency period of months (in rodents) or years (in rodents or humans) would be temporally consistent. An issue of temporal association that is sometimes difficult to clarify is the distinctio n between an effect due to chronic exposure and an acute effect due to repeated acute exposures. It may be inappropriate to develop a chronic REL based on an endpoint that is essentially an acute health effect seen repeatedly with daily workplace exposure.

4.2.4 Coherence and Biological Plausibility
A causal interpretation cannot conflict with what is known about the biology of the disease. The availability of experim ental data or mechanis tic theories consistent with epidemiological observations strengthens conclusions of causa tion. For example, the presence of known carcinogens in tobacco smoke suppor ts the concept that exposure to tobacco smoke could cause increased cancer risk. Similarly, if the mechanism of action for a toxican t is consistent with development of a specific disease, then coherenc e and biological plausibility can be invoked. It should be noted that our understa nding of the biology of diseas e, and therefore biological plausibility, changes in light of new information which is constantly emerging from molecular biology (including epigenetics), and from new clinical and ep idemiological investigations revealing effect influenced by genetic polymor phisms, pre-existing disease, and so forth.

4.2.5 Dose-respo nse A basic tenet of toxicology is th at increasing exposure or dose generally increases the response to the toxicant. A progressivelyincreasing response with increa sed exposure m akes it difficult to argue that the factor is not associated with the di sease. To argue otherwise necessitates that an unknown factor varies consisten tly with the dose of the subs tance and the response under question. While increased risk with increasing le vels of exposure is cons idered to be a strong indication of causality, absence of a graded response does not exclud e a causal relationship (IARC, 2006). The dose-response curves for speci fic toxic effects may be non-monotonic. For instance, where the dose respons e shows saturation in an obs ervable or experimentally achievable exposure range, the effect of exposures in this range could be nearly maximal, with any additional exposure having litt le or no effect. In some inst ances, a response is seen strongly in susceptible subpopulations, a nd the dose-response is maskedby mixing susceptible and nonsusceptible individuals in a sample. Further, there are examples of U-shaped or inverted Ushaped dose-response curves, (e.g., for endocrine disrupters) (Almstrup et al., 2002; Lehmann et al., 2004). Finally, timing of exposure during devel opment may mask an overall increase in risk with increasing dose.

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4.2.6 Specificity
Specificity is generally interpreted to mean that a single cause is associated with a single effect. It may be useful for determining which microorgani sm is responsible for a particular disease, or associating a single carcinogenic chemical with a rare and ch aracteristic tumor (e.g., liver angiosarcoma and vinyl chloride , or mesothelioma and asbestos ). However, the concept of specificity is not a particularly helpful criterion when studying dis eases that are multi-factorial or toxic substances that contain a number of indi vidual constituents, eachof which may have several effects and/or target sites.

4.2.7 Experimental Evidence
While experiments are often conducted over a shor t period of tim e or unde r artificial conditions (compared to real-life exposures), experiments o ffer the opportunity to colle ct data under highly controlled conditions that allow strong causal conclusions to be drawn. Experimental data that are consistent with epid emiological results, and vice versa , strongly support conclusions of causality. There are also “natural experiment s” that can be studied with epidemiological methods, such as when exposure of a human populat ion to a substance declin es or ceases; if the effect attributed to that exposur e decreases, then there is evidence of causali ty. One example of this is the drop in heart disease death and lung cancer risk after smoking cessation.

4.3 Haz ard Identification

4.3.1 Definition of Adverse Effect
The general aim in developing health -prote ctive levels such as RELs is to define a level at which no impairment of the health of an exposed human is anticipated. Risk assessment guidance has therefore historically focused on th e identification of an adverse effect as critical in determining health-protective levels. Thus, U.S. EPA has used a general de finition of ‘adverse effect’ as “any effect resulting in functional impairment a nd/or pathological lesions that may affect the performance of the whole organism, or that reduce an organism’s ability to respond to an additional challenge” (U.S. EPA, 1994a).
However, the definition of an “adverse effect” ha s proved to be a source of significant difficulty and controv ersy. Not all effects reported for a substance are necessarily considered adverse; some adaptive biochemical responses such as en zyme induction are not considered necessarily adverse, unless they are identified as precursor events consistent with the mode of action for more obviously adverse pathophysio logical events (Sherwin, 1983; American Thoracic Society (ATS), 2000a).
Within the health-disease spectrum, health effect s could rang e from mild symptoms of ill health to exacerbations of terminal illn esses of diverse kinds; an inordina te depletion of cell, tissue, and organ reserves; subclinical dis ease; and mortality. Reserve loss involves both reversible and irreversible alterations of the cell population and includes metabolic abnormalities and alterations of the intercellular milieu. Therefore, the earliest adve rse effect is an altered ecology at the cellular level. Irreversible abnormalities that appear relatively minor may have a serious

Technical Support Document 34 June, 2008TSD for Noncancer RELs June 2008 impact on health by increasing susceptibility to disease in general, or by exacerbating other disease processes (Sherwin, 1983).
NRC (2007) has pointed out that this continuum of responses pr esents a basic difficulty in defining any particular effectas adverse or otherwise:
“Dividing effects into dichotomous categories of ‘adverse’ and ‘non-adve rse’ is problematic. Adverse effects usually develop along a continuu m, starting with the uptake of a toxicant, distribution and metabolism, cont act with a target organ, biologi c change, physiologic response and repair, and clinical disease. Thus with some doses and hosts, biologic changes occur, but the body has sufficient defense mechanisms for de toxification or adaptation, and there is little or no adverse cumulative effect, partic ularly at low doses. In othe r situations, biologic changes are measurable and are precursors of an adverse clin ical change, so an ad verse effect, or the precursor of an adverse effect, could be defined in terms of a chemicalmetabolite or biologic change that is an indicator of both exposure and effect. The same biologic change could have little impact at a small dose ( and so be termed ‘non-adverse’) but produce a much larger impact at a greater dose or in a more vulnerabl e person (and thus be termed ‘adverse’).”

The U.S. EPA considers both th e biological and statistical si gn ificance of effects when determining if the observed effect can be defined as adverse. Thei r determination also takes into account what is known about the underlying mode of action (U.S. EPA, 2002a). Biological significance is the determination that the obs erved effect (e.g., a biochemical change, a functional impairment, or a pathol ogical lesion) is likely to impai r the performance or reduce the ability of an individual to f unction or to respond to additional challenges from the agent. For some quantal endpoints (e.g., birth defects, tumo rs, or some discrete pathological changes), criteria are already established to decide the type and incidence of effects, which may be considered adverse, and statisti cal tools to support th e decision. However, changes in continuous measures such as body weight, enzyme changes, and physiological measures, are more difficult to use as endpoints because the amount of change considered to be biolog ically significant has not been well defined (U.S. EPA, 2002a).
In particular, relatively subtle alterations in such continuous m easures such as cellular proliferation, maturation, gene activation or suppression, and a ltered signal transduction, can lead to serious outcomes in developing humans. Thus it can be difficult, but important to the protection of developing infa nts and children, to determine the biological significance of seemingly minor alterations in an enzyme. So me changes in enzyme activity or levels can produce severe effects in a developing organism if they produce a change in signal transduction. For example, fetal exposure to chlorpyrifos alte rs receptor numbers and activity in serotonergic neurons in adults (Aldridge et al., 2004). Al so, brief inhibition of cyclooxygenase-2 during the perinatal period alters neurodevelopment and severe ly inhibits reproductive behavior in the adult male rat (Amateau and McCarthy, 2004).
OEHHA therefore follows NRC (2007) in re comm ending a cautious and health-protective approach to the consideration of whether a give n biological endpoint is a ppropriate to consider frankly “adverse,” or is a biol ogically significant precursor lesion, in which case it would be a suitable endpoint for consideration in a risk a ssessment, or is rather a non-adverse adaptive or incidental change. An example of the necessary decision process is show n in the determination

Technical Support Document 35 June, 2008TSD for Noncancer RELs June 2008 of a Public Health Goal for perchlorate in drin king water (Ting et al., 2006). Here the decision was made to use the precursor bi ochemical alteration of impaired iodine uptake, a known effect of the perchlorate ion resulting from inhibition of the active tr ansport protein responsible for iodide translocation, the NIS sympor ter. This is clearly shown at higher doses to impact thyroid hormone synthesis and this in turn is known to have severe impacts on central nervous system development in the human fetus and infant and on IQ deficits in the human newborn. It was concluded that even modest impacts on the iodi ne uptake process had the potential to impact sensitive targets, such as the fetus of a woman with suboptimal iodine intake.

4.3.2 Nature of Adverse Effects
The toxic effects of chemicals are of varying ty pes and degrees of severity. Following an acute (one-hour) exposure to a substance released into the atm osphere, effects on the upper and lower respiratory tract may be observed as so-called “p ortal of entry” effects. Toxic effects from airborne substances may also be due to exposure via the skin and ey es. Systemic effects, such as hemolysis or central nervous system injury, may result from absorption of material through the lungs, and, to a lesser exte nt, through the skin.

Toxic effects do not have to be observed immediatel y to be considered due to an acute exposure, but m ay instead appear hours to days after thatexposure. For example, a brief exposure to phosgene may result in pulmonary edema several hour s later. In the case of benzene, death may result from leucopenia days follo wing high-level acute exposure.
Certain chemicals, after a single exposure, have the potential to produce d elayed adverse effects. Often acute toxicity tests do not have a suffi cient follow-up period to allow thorough assessment of the potential for delayed health effects from single exposures. With respect to two kinds of delayed effects, cancer and reproductive or de velopmental harm, there is more information available. Carcinogenicity is tr eated separately in risk assessme nt and cancer potency factors for carcinogens are described in the Air Toxics Hot Spots Program Risk Assessment Guidelines Part II: Technical Support Document for Describi ng Available Cancer Potency Factors (OEHHA, 2005a). Reproductive and developmental toxicant s are considered here because substantial research effort has been devoted toward sp ecifically identifying such delayed effects.

Some substances exert their t oxic effects through their m etabolite s. For example, methylene chloride’s acute toxicity is mediated th rough its metabolite, carbon monoxide. Whenever possible, information on toxic metabolites is prov ided in the toxicity summaries. When detailed information is available on the relationship of dose of the parent chemical to level of metabolite and the metabolite level to degree of toxic response , this is taken into account in developing the RELs. However, RELs are always expressed in terms of the concentr ation of the parent compound, not the metabolite.

4.3.3 Severity of Effects
Adverse effects may occur with a ra nge of severity from mild (sen sory or subjective effects, or statistically significant incidence of precursor changes, which are re versible) to severe (clinically significant pathological changes, disabling or strongly objectionable sensory effects, persistent or irreversible histological or functional damage), or even to lif e-threatening. These effect levels

Technical Support Document 36 June, 2008TSD for Noncancer RELs June 2008 have been used in a variety of ways including in models of progressive dose-response such as that used in U.S. EPA’s categ orical regression methodology.
The endpoint of choice for determination of a REL, which is intended to protect the health of the community at large, will generally be a m ild effe ct. However, more severe effects may be used if these are in fact the most sensitive endpoint (for example irreversible developmental effects), or if no data on mild effects are available. U nder such circumstances, additional models or UFs may be used as described in the following sectio n in order to provide ad equate health protection for the majority of the exposed population.

4.3.4 Target Organs
The nature of the target organs or systems involved in a given toxi cological response is im portant since this is considered for hazard index (HI) calculations (Section 2.2 ). Consideration of the cum ulative impact of exposure to multiple chemicals is one of the requirements of SB25, and a key objective for environmen tal justice considerations. The target organs or systems are described by general cate gories that may include varied effect s: categories and effects currently used in existing acute and chronic RELS are s hown in Appendix H. For example, the target system, “respiratory system,” includes upper airway irritation as well as lower airway effects, such as bronchoconstriction. Obviously this list of specific endpoints is not exclusive, and may be augmented or amended as new RELs are deve loped. In order for the acute and chronic REL HI target organs to be consistent, developmenta l and reproductive effects, which were previously combined, have been separated into two categories. New target organ categories may need to be added, based on the toxicological data used to develop additional RELs.
For simplicity, this approach to HI calculatio n s assumes additivity when multiple toxicants impact the same organ system or biochemical ta rget. Other possible modes include independent (non-additive), synergistic or an tagonistic. The description of synergism or antagonism is difficult, and probably requires determination of joint dose-response functions on a compoundspecific basis. There are relatively few com pounds for which synergism or antagonism have been documented. It is unclear whether this is because such interactions are genuinely infrequent, or because the standard toxicological screens are not designed to identify these effects, and also because the database on the toxi cology of chemical mixtures is relatively small.
In using the additive HI approach it is n ecessa ry to define what constitutes the “same” toxicological endpoint, which when impacted by multiple toxicants results in effectively cumulative damage (Salmon, 2007). This might be the same molecular target, the same physiological process, or perhaps the same anat omical unit. The traditional basis has usually been the anatomical unit by default, since actu al mechanisms and physiological interactions between organs are frequently unknown. More recently, the availability of information on toxicological mechanisms has prompted discus sion of both broader and narrower frames of reference. The concept of a single molecular targ et is attractively simple, but may be too narrow when multiple control or functional systems give input to a single critical system or process downstream from the molecular targets of variou s toxicants. Because the precise relative contributions of exposure to multiple substances that principally affect different areas of the same physiologic system are unknown, the assumpti on of additivity across a single major organ system may either under- or over-estimate the eff ects of chemical interact ions in certain cases.

Technical Support Document 37 June, 2008TSD for Noncancer RELs June 2008 However, in most cases this approach provides an appropriate health pr otective assumption. We have indicated in Appendix B, Table B-1 whic h toxicological endpoints are relevant to the specific REL for each chemical. While the REL is based on the most sensitive endpoint, other toxicological endpoints are manifest ed at exposures close to that which induces the toxicological endpoint that serves as the basis for the REL. Therefore, some chemicals should be evaluated for impacts on multiple target organs or systems. In addition, predisposing conditions are known to increase susceptibility to some chemicals. Th e target organs for those predisposing conditions should also be included in the HI approach.

4.4 Dose-Response Assessment

4.4.1 Estima tion of Threshold or Low Response Concentrations

Noncancer health effects assessment has b een bas ed on the concept that a threshold concentration or dose exists belo w which no adverse effects would occur. While such thresholds are observed among individuals, the existence an d magnitude of a population threshold below which no members of the population would experien ce adverse effects cannot be demonstrated. In any study, the entire populati on of concern is not examined; ra ther a sample of the population from which inferences are drawn is studied. Therefore, it is not possible to distinguish whether a concentration is truly below a population threshold le vel for an adverse effect or is rather a level associated with a relatively low incidence of adve rse effects, which cannot be distinguished from background rates in the population.
There may also be cases where no threshold exis ts in the general population for a particular effect. This situation m ay occur for responses fo r which there is no theoretical threshold due to the mechanism of toxicity. The most accepted example of this is chemical carcinogenesis, particularly for genotoxic carcinogens . However, there may, at least in principle, be other types of toxicity which do not show a threshold at any dose level.

Even where a true threshold exis ts in the dose response of a part icular individual to a chem ical exposure, there may in fact be no identifiable th reshold in the response of the general population. This may occur in the case where some indivi duals in a diverse population show a threshold whereas others do not, which is at least theore tically possible if gene tic polymorphisms exist which inactivate a protective mechanism. Ho wever, the most likely case is where a true threshold in the response occurs in all individuals at low doses, but the background rate or extent of that toxic response in the population is already above zero du e to population-wide exposure to that pollutant or another causative factor which produces the same e nd-point or disease. In this case, any increment in exposure to the pollutant of concern will cause an increase in the prevalence or severity of the dis ease, in spite of the existence of a threshold in the individual dose-response relationship. A probable example of this is seen in the neurodevelopmental effects of lead exposure in children, which recent risk assessments have described using linear or other continuous dose-response f unctions (Carlisle and Dowling, 2006). The data available for criteria pollutants such as ozone or particulate matter are cons istent with linear no-threshold dose- response curves for cardiovascular mortalit y (Daniels et al., 2000; Schwartz et al., 2001; Schwela, 2000; Vedal et al., 2003).

Technical Support Document 38 June, 2008TSD for Noncancer RELs June 2008 Where these special cases are demonstrated to exist on the basis of popul ation health data, or appear likely based on mechanistic studies, it will be appropriate to use these data to develop risk-based or continuous-response models to desc ribe the population imp acts of exposure to these pollutants, rather than relying on the threshold dose-response de scription to identify a “safe” exposure level. It should be noted that la ck of a true threshold does not necessarily imply linearity of response at all dos es (although at sufficiently low dose levels any continuous nonthreshold dose-response curve will necessarily approach linearity) . Conversely, the observation of a non-linear dose-response curve does not nece ssarily imply the existence of a threshold. However, in the majority of cases for noncancer effects the existence of a threshold in the dose response is both plausible, and often, within the acknowledged limitation s, demonstrable (U.S. EPA, 1993). Therefore, the threshold assumption is regarded as the default for noncancer risk assessment, and is most often used.
Two major strategies are used for dose-response assessment methods to estimate “thresholds” of responses from study data. These are the benchmark dose (BMD) or benchmark concentration (BMC) approach and the no-observed-adverse- effect-level (NOAEL) approach. In both approaches, uncertainty factors (UF) are app lied to account for vari ous uncertainties in extrapolating from the study results to the genera l population. These are described in Sections 4.4.2 through 4.4.9.
Of the methods presented, the BMC approach is preferred. Quantal or continuous dose-response data for a to xicant (measured for at least two dos e levels and a control) are required to estimate levels using the BMC method. Supporting toxicological data will not, however, always be sufficient to permit this level of quantific ation. In most cases, the method will allow determination of a benchmark concentration evenwith relatively sparse data; however, obviously the confidence in the result will be lower in th is case. The alternative NOAEL method may give the appearance of providing a result more easily with poor data, but in fact the uncertainty in such a result can be extremely large, and the s ituation is not improved by the inability to quantify this uncertainty. OEHHA has used the BMC approach to develop two acute RELs (OEHHA, 1999; Collins et al., 2005). More recently a numbe r of chronic RELs have been developed using this approach (Collins et al., 2003; Collins et al., 2004). Based on recen t experience with the benchmark method, new REL values will be developed using the BMC approach whenever data of sufficient quality to suppor t this methodology are available.

4.4.1.1 Use of No-Observed-Adverse-Effect-Levels (NOAEL)
A No-Observed-Adverse-Effect-Level (NOAEL) in a hum an or animal study may be defined as an exposure level with no biologically or statis tically significant increas e in the frequency or severity of adverse effects among the exposed group relative to a control group. The NOAEL must be tempered by appropriate statistical interpretation. A NOAEL is sometimes incorrectly viewed as an estimate of a threshold level fo r adverse effects. However, a NOAEL could be associated with a substantial (1-20%) but undetected incidence of adverse effects among the exposed experimental group or population. This is so because only a subset of individuals from the population has been observed, and because the experiment may not have been designed to observe all adverse effects associated with th e substance. Therefore, one may not safely conclude that the study concentration or dose is not associated with any adverse effects (U.S.

Technical Support Document 39 June, 2008TSD for Noncancer RELs June 2008 EPA, 1994a). Alternatively, a NOAEL could be many-fold lower than a true population threshold due to study design and dose spaci ng (Gaylor, 1992; Leisenring and Ryan, 1992).
The U.S. EPA (1994a) determined that a NOAEL not associated with any biological ef fect (a “no-observed-effect-level” or NOEL) identified from a study with only one dose level is unsuitable for derivation of an RfC for chronic exposure. Because there is a limited availability of multi-dose studies for the variety of chemicals consid ered, OEHHA may use a NOAEL without an associated LOAEL (lowest-observed- adverse-effect-level) id entified in the same study (termed a free-standing NOAEL) in deriving a REL, but only if there are no other suitable studies, and so long as the overall health hazard data (including any case reports or studies with shorter durations) for that substance are consistent with the NOAEL study.

4.4.1.1.1 Derivation of Reference Exposur e Levels (RELs) Using NOAELs
Reference Exposure Levels are derived by the ap plication of UFs to th e NOAE L for a critical endpoint. The application and values of UF s, which are similar for the NOAEL and BMC approaches, are described below.

NOAEL / UF =REL

Prior to the determination of a NOAEL, the literature is exam ined to identif y the relevant endpoints. Toxicological endpoi nts are evaluated to determin e the most sensitive effect (occurring at the lowest exposur e level), and a dose-response rela tionship is determined. The most sensitive adverse effect of relevance to huma n health (termed the “critical effect”) is used as the basis of the REL, and as noted above this is usually a mild adverse effect.

4.4.1.1.2 Use of Lowest-Observed-Adve rse-E ffect-Levels (LOAEL)
A Lowest-Observed-Adverse-Effect-Level (LOA EL) m ay be defined as the lowest exposure level in a study or series of st udies with a biologically and/or st atistically significant increase in the frequency or severity of adverse effects among an exposed population relative to a control group. The highest exposure concentration whic h results in biological effects that are not considered adverse may be termed the lowest-obser ved-effect-level (LOEL); this is identical to the NOAEL (U.S. EPA, 1994a). If a NOAEL is not id entifiable from the liter ature, it must be estimated from the lowest exposure concentration reported to produce the a dverse effect; this is the lowest observed adverse effect level (LOAEL). An UF is applied to the LOAEL to estimate the NOAEL. Use of a LOAEL should be a la st resort; use of the BMC methodology is preferable whenever possible. Where experimental data showing intermediate response rates are very limited, this may place constraints on the be nchmark response rate and curve-fitting model used. However, even in these cases the overall un certainty is likely to be both smaller and better quantified by the BMC methodology than by a LOAEL-based derivation.
If there exist multiple, non-id entical NOAELs and LOAELs for the sam e compound and critical effect, the study of the best quality reporting th e highest value for a NOAEL (preferred) or the lowest value for the LOAEL is us ed for the development of RELs.

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4.4.1.2 Benchmark Concentration
The importance of a dose-response relationship in the evaluation of effects of che mical exposure is well-established. The NOAEL approach, does not explicitly incorporate information on the shape of the dose-response curve and is highly dependent on the test doses chosen by the original investigators. This led to explorations of th e concept that a concentr ation estimated to be associated with a predefined low risk could pr ovide an alternative to the NOAEL (Mantel and Bryan, 1961; Mantel et al., 1975; Crump, 1984; Dourson, 1986; Hartung, 1987; Gaylor, 1988; Gaylor et al., 1998). Crump (1984) proposed the term “benchmark dose” and extensively evaluated this concept. In this document, the term benchmark concentration (BMC) is used since inhalation toxicology data ar e usually described in term s of air concentrations.

The BMC method allows a mathematical and stat istical approach to the calculation of RELs (Crum p, 1984; Lewis and Alexee ff, 1989; Alexeeff et al., 1992; Al exeeff et al., 1993; Barnes et al., 1995; Collins et al., 2005; Starr et al., 2005). In this document, the BMC is defined as the 95% lower confidence limit of the concentration expected to produ ce toxic responses in a chosen percentage of subjects (the benchmark respons e rate) exposed at th is dose. A suitable mathematical function is fitted to the concentr ation versus response relationship using likelihood methodology. The function used is selected accord ing to defined quality of fit criteria. The concentration expected to produce the benchm ark response rate, and the lower confidence bound on that concentration are identified from the fitted cu rve. In the case of quantal data in an animal toxicity experiment, the benchmark response rate is usually selected at 5% (see Section 4.4.1.2.1 below). Other types of data, including continuou s m easures of toxic response, and data from epidemiological studies, require an appropriate benchmark response rate to be identified on a case-by-case basis. An example of the benchm ark dose methodology is graphically depicted in Figure 4-1.

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FIGURE 4-1 LOG-PROBIT MODELING OF DOSE-RESPONSE DATA FOR SILICA 1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

0 2 4 6 8 10 12 14 16Fraction Affected

Dose (mg/m 3 -y) Lo g Dose/Probit Model with 0.95 Confidence Level

BMDL BMD Probit BMD Lower Bound

1 Data from (Hnizdo et al., 1993; Collins et al., 2005).
In spite of its advantages, there are sources of uncertainty in the experim entally derived BMC value. For example, the studies used to esti mate the BMC have usually been performed with animals rather than humans e.g., (Kuwabara et al ., 2006). Also, the experimental duration of exposure may differ from that which is of intere st for the establishment of RELs. Additionally, the dose of toxicant delivered to the target ti ssue may differ between species and among humans and may depend on the type of activity in which the individual is engaged. Another area of uncertainty is that there can be a large degree of variability in the num ber of people who respond at any exposure. For example, there may be over a 10-fold variability in the irritation threshold (the concentration of a substan ce at which irritation of the eyes , nose and/or throat is first detectable) for chlorine (Anglen, 1981). In order to estimate a health protective level such as a REL for the population of concern, the BMC is ther efore modified by UFs, except where explicit extrapolation models are available to allow for these differences.

BMC / UF = REL
Most frequently, the characteristics of the BMC ar e chosen so that its properties are similar to that of the NOAEL described below. Thus, similar UFs ( Table 4.4.1 ) are applied with both approaches. Specific data sets m ay however resu lt in the use of UFs diff erent from what would be used with a standard NOAEL, determined on a case-by-case basis; th e rationale would be described in each toxicity summary for the individual chemicals.

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4.4.1.2.1 Selection of Appropriate Benchm ark Concentration Response Rate
A response range of 1% to 5% approximates the lower lim it of adverse eff ect detection likely to occur in typical human epidemiological studies , and in large laboratory animal studies the detectable response rate is typically in the 5 to 10% range (Gaylor, 1992) . In 1995, using animal developmental toxicity data, the U.S. EPA conclude d that a 1% response rate was likely to be too low to be detected and therefore too uncertain to use as a point of departure, while either 5% (BMC 05 ) or 10% (BMC 10 ) response rates were adequate for the purposes of estimating a benchmark concentration (Barne s et al., 1995). One reason for this conclusion was the large difference (29-fold) between observed NOAELs and the 1% benchmark using developmental toxicity data. Subsequently, the U.S. EPA ( 2007a ) used a 10% response rate for benchmark concentrations when deriving chro nic inhalation reference concentra tions (RfCs). More recently, RfC determinations for various endpoints by the U. S. EPA have used either 5% or 10% as the benchmark response rate, depending on the statisti cal uncertainty in the data (U.S. EPA, 2002a; U.S. EPA, 2004). OEHHA has used the 5% resp onse rate in several chronic RELs, and showed that the lower 95% confidence bound on the BMC 05 typically appears equivalent for risk assessment purposes to a NOAEL in well design ed and conducted animal studies where a quantal measure of toxic respons e is reported (Lewis and Alex eeff, 1989; Alexeeff et al., 1992; Alexeeff et al., 1993; Barnes et al., 1995; Collin s et al., 2004; Collins et al., 2005; Starr et al., 2005; Alexeeff et al., 2006; Brown et al., 2006). Therefore, OEHHA t ypically uses a 5% response rate as the default for determin ation of the BMC from quantal data ( i.e. the effect is either present or it is not) in animals (Fowles et al., 1999).
Other response rates may be selected if the data indica te that this is a ppropriate. For instance, large epidemiological studies examining a relativel y severe endpoint such as clinical disease may support the use of a 1% response criterion, as in the case of the chronic REL recently developed for respirable crystalline silica (C ollins et al., 2005). In that ca se, the size of the epidemiological database was large and thus there was high confid ence in the response at low exposures. In the case of a steep dose-response relationship, the sel ection of response rate is less influential on the final value. For acute lethality studies, 1 and 5% response rate benchmark concentrations differed, on average, by less than 2-fold from the respective NOAEL (Fowles et al., 1999).
Various criteria have been proposed for selec ting an appropriate benchm ark response rate for continuous data such as body wei ght, blood cell numbers, and leve ls of enzyme activity (U.S. EPA, 1995; Gaylor et al., 1998; Crump, 2002; Sand et al., 2003). One criterion is statistical confidence, e.g., criteria based on some multiple (1.0 - 3.0) of the standard deviation of the reported measurements, either above or below th e mean, particularly in controls or low-dose groups. A standard deviation of 2.33 from th e mean identifies values at the first and 99 th percentiles, extreme values even if not a dverse. If values greater than the 98 th to 99 th percentile are abnormal, then a concentration that change s the mean by one standard deviation yields roughly 10% excess risk in subjects in the abnorm al range (Crump, 1995). A second criterion is scientific judgment as to what constitutes a bi ologically relevant pert urbation in a measured parameter, such as one that exceeds the like ly range of physiologica l compensation. Some clinical guidelines are generally accepted as cutoff points although they are not necessarily thresholds. These might include:

Technical Support Document 43 June, 2008TSD for Noncancer RELs June 2008 (1) reduction in lung function (>20% of expect ed forced expiratory volume (FEV)) as clinically significant (2) a carboxyhemoglobin level of 1.1 to 1.3%, and (3) a pesticide worker’s b lood cholinesterase le vel less than 80% of th e individual’s baseline level.
The choice of an appropriate benchmark criterion for continuous data is currently based on the particular nature of those data, including suppor ting inform ation on severity of the effect and possible mechanisms of repair or compensati on, rather than on any overall policy-based guidance. In the development of the chroni c REL for carbon disulfide, OEHHA used as the benchmark response rate a five percent reduc tion in peroneal motor conduction velocity (BMC 05 ), a mild effect and definitely within th e range of normal variation. In some cases, population shifts in a conti nuous variable such as FEV 1 , blood pressure, birt h weight, thyroid hormone levels (Ting et al., 2006) or IQ ( e.g. effects of lead as re ported by Lanphear et al. (2005)) may result in pushing more individuals into a high-risk category, and thus small shifts can be considered adverse.

4.4.1.2.2 Selection of Confidence Lim its

The benchmark dose or concentration is select ed by fitting an assumed dose-response curve to the observed response data. Mathematical curv e fitting of this type necessarily involves recognition of uncertainty and variab ility in the input data. Fitted curves or interpolated values are generally described in terms of both maximum likelihood estimates (MLE) and confidence bounds on these estimates. Variation around the pred icted values is generally assumed to follow

a χ 2 (chi-squared) distribution, and the χ 2 statistic is used as a cr iterion of fit quality and in deriving “p” values and confidence limits on esti mates. The 95% lower confidence limit (LCL) of the concentration at the chosen benchmark re sponse rate or level is generally used as the BMC, rather than the MLE. This is preferred since it takes into account sources of uncertainty intrinsic to the source data, including the vari ability of the test population and the number of subjects in the study. This provides an incentiv e for the generation and use of higher quality data, unlike the NOAEL/LOAEL methodology, which makes no explicit quantitative allowance for uncertainty in the underlying data. Use of the 95% LCL in a benchmark calculation also takes into account the qualit y of fit for the dose-response curve. The Benchmark Dose Workshop (Barnes et al., 1995) recommende d using the 95% LCL in benchmark dose calculations. With robust data se ts the 90, 95, and 99% LCLs are cl ose to each other and to the MLE (Sand et al., 2002).

4.4.1.2.3 Selection of Models to fit the Dose-R esponse Curve
It is important to select an appropriate math e matical model for the type of data used for benchmark concentration calculati ons (Filipsson et al., 2003). The U.S. EPA’s Benchmark Dose Software (BMDS) contains a variet y of models (U.S. EPA, 2006a).

Technical Support Document 44 June, 2008TSD for Noncancer RELs June 2008 For dichotomous data, the models include the following:
(1) gamma distribution, (4) pr obit, (7) Weibull models.

N d), er for and a th

mo (2) logistic, (5) quantal linear,
(3) multistage, (6) quantal quadratic, and
The quantal linear and the quantal qu adratic are special cases of the Weibull model in which the exponents are one and two, respectively. The probit and logistic models can be run using either the dose or the logarithm of the dose. These mode ls are useful for data where the subjects at each level of exposure did or did not experience a specific adverse effect such as eye irritation, liver enlargement, or an impaired nervous system (based on passing or failing a specific test). For nested dichotomous data, such as found in animal developmental data in which individual offspring are nested in litters , the models available are:
1) Logistic (logistic neste (2) NCTR (National Cent Toxicolo gical Research), (3) Rai & Van Ryzin (after the

u ors who described the del).
For continuous data such as body weight, enzyme activity level, blood cell counts, IQ, and nerve conduction velocity, the models available are the:

• (1) linea r, • (3) power, and

• (2) polynom ial, • (4) Hill.
To date the models most used by OEHHA are thos e for dichotomous data. Usually each model is fit to a do se-response data se t of the most sensitive endpoint available, and both the MLE and the lower 95% confidence bound be nchmark confidence level (BMCL 05 ) of the effective dose (ED 05 ) are derived from each model. When the numb er of subjects is very large as in the case for some occupational epidemiological exposures su ch as respirable, crystalline silica, the MLE 01 and BMCL 01 (a one percent benchmark) can be determined (Collins et al., 2005). The models that give an acceptable fit (p ≥ 0.10 by χ 2 ) are further examined. Some models may fit the entire range of the data equally well by the χ 2 test, but one may be better th an another in describing the shape of the dose-response curve at the lower end of the dose range, which is critical in defining a benchmark such as BMCL 05 . If more than one model gives an acceptable fit to the data, then some judgment is used in balancing a model’ s goodness of fit (as possibly indicated by a much higher p value or as determined visually from the plotted curve) versus the level of health protection provided by the BMCL 05 derived using that model. From the perspective of protecting public health, the lowest value of the BMCL 05 from a model having an acceptable fit might be taken. However, with certain data se ts, some models (including the often used logprobit model) may indicate an MLE which is ve ry far from the BMCL value (Murrell et al., 1998). For well-fitting models, the BMCL is se ldom less than one third of the corresponding MLE, unless the overall precision of the data is poor. The analyst shou ld also beware of attempts to fit complex models to data sets w ith insufficient precision to specify all the model parameters accurately (U.S. EPA, 2006a). T hus there must be allowance for professional

Technical Support Document 45 June, 2008TSD for Noncancer RELs June 2008 judgment by toxicologists and statis ticians. These considerations are discussed in the summary for each REL derived by the benchmark method.

4.4.2 Extrapolation and Unc ertainties in the Database
A BMC or observed NOAEL may be a concentrat ion where adverse effects are observable rarely, or not at all, in a speci fic study, but this level m ay not be without effect among the general human population, which includes indi viduals who are more sensitive than average, or who may receive repeated or extended exposures. In de velopment of a REL, systematic extrapolation methods must be used to relate the dose-response charac teristics observed in the experimental (or epidemiological) data to those expected fo r the general human population in a community exposure situation. The REL must also address, and where possible quan tify, uncertainties in the available data and variability in the target population. These issues are accounted for by means of explicit extrapolation models where these ar e available and appropria te input data can be obtained. Where these explicit models are unavaila ble, UFs have been used extensively with human or animal toxicity data to estimate “s afe” or “acceptable” exposure levels for humans.
Extrapolation methods are used by OEHHA in de riving RELs to account for exposure duration adjustm ents and discontinuity, interspecies differences in expo sure and pharmacokinetics, and expected differences among members of the targ et human population (e.g., differences between adults and children). Extrapolat ion methods are based on identifica tion of measurable attributes that are judged to be relevant to addressing an area of concern, and incorporation of these data into, ideally, a mechanistic model, or (failing an established mechanistic model) an empirical mathematical model of the expos ure and toxicological response.

4.4.3 Types of Uncertainty an d Variability
Model-based extrapolation procedures or, where these are un available, UFs are used by OEHHA in deriving RELs to account for:
(1) the m agnitude of effect observed at a LOAEL compared with a NOAEL (Dourson and Stara, 1983; Mitchell et al., 1993); (2) for chronic RELs, the potentially greater effects from a continuous lifetime exposure compared to a subchronic exposure (Lehman and Fitzhugh, 1954; Bigwood, 1973; Dourson and Stara, 1983). (3) the poten tially greater sensitivity of humans relative to experimental animals not accounted for by differences in relative inhalation exposure (Vetto razzi, 1977; Dourson and Stara, 1983); (4) the poten tially increased susceptibility of se nsitive individuals, for example due to interindividual variability in res ponse (Vettorazzi, 1977; Hattis, 1996a; Ginsberg et al., 2002; Miller et al., 2002; Dorne and Renwick, 2005a) and (5) other deficiencies in the study desi gn (Lehm an and Fitzhugh, 1954; Bigwood, 1973; Dourson and Stara, 1983; NRC, 1993; U.S. EPA, 1993).

Technical Support Document 46 June, 2008TSD for Noncancer RELs June 2008 The use of UFs for determining “safe” or “acceptabl e” levels has been discussed extensively in the toxicological literature (Vettorazzi, 1977; NRC, 1977- 1987; Dourson and Stara, 1983; Alexeeff et al., 1989a; Alexeeff and Lewis, 1989b; U.S. EPA, 1994a; Dourson et al., 1996).
As noted above, UFs are used when insufficien t data are available to support the use of chem ical-specific and species-specific extrapolation factors. In this document, five UFs will be described (see Table 4.4.1 ):
(1) LOAEL unc ertainty factor – UF L ; (2) subchronic uncertainty f actor – UF S ; (3) interspecies uncertainty f actor – UF A ; (4) intraspecies uncertainty f actor – UF H , and (5) database deficiency factor - UF D . Historically, UFs have most ofte n been order-of-m agnitude factors, indicating the broad level of uncertainty in addressing the area of con cern (Dourson and Stara, 1983). More recently, OEHHA and the U.S. EPA have used intermediate UFs, usually having a value of 3 (the rounded square root of 10) in areas estimated to have less residual uncertainty (U.S. EPA, 1994a). In special cases, other UF values may be consid ered appropriate. While the actual value of √ 10 is 3.16, in practice, a single intermediate UF is calculated as 3 rather than 3.16, while two such intermediate UFs cumulate to 10. Thus, cumulative UFs could equal 1, 3, 10, 30, 100, 300, 1000, or 3000.

TABLE 4.4.1. POSSIBLE DEFAULT UNCE RTAI NTY FACTORS USED IN DERIVING ACUTE, 8-HO UR AND CHRONIC RELS
Method or Factor Values Used REL types

LOAEL uncertainty factor (UF L ) Values used: 1 NOAEL or benchmark used 6 LOAEL, mild effect 10 LOAEL, severe effect 10 LOAEL, any effect A, 8, C A A 8, C

Interspecies uncertainty factor (UF A ) Values used for a combined interspecies uncertainty factor (UF A ): 1 human observation √ 10 animal observation in nonhuman primates
10 where no data are available on toxicokinetic or toxicodynam ic differences between humans and a non-primate test species A, 8, C

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TABLE 4.4.1. POSSIBLE DEFAULT UNCE RTAINTY FACTORS USED IN DERIVING ACUTE, 8-HO UR AND CHRONIC RELS
Method or Factor Values Used REL types

Values used for the toxicokinetic component (UF A-k ) of the interspecies uncertainty factor: 1 where animal and human PBPK models are used to describe interspecies differences 2 for residual toxicokinetic differences in studies of non-prim ate species using the HEC approach or incomplete DAF model √ 10 non-primate studies with no chemical- or species-specific kinetic data A, 8, C

Values used for the toxicodynamic component (UF A-d ) of the interspecies uncertainty factor: 1 where animal and human mechanistic data fully describe interspecies differences. ( This is unlikely to be the case.) 2 for residual susceptibility differences where there are som e toxicodynamic data √ 10 non-primate studies with no data on toxicodynamic interspecies differences A, 8, C

Intraspecies uncertainty factor (UF H

) Values used for the toxicokinetic component of the intraspecies uncertainty factor, (UF H-k ) for systemic toxicants: 1 human study including sensitive subpopulations (e.g., inf ants and children) 1 where a PBPK model including measured inte r-individual variability is used √ 10 for residual susceptibility differences where there are some toxicokinetic data (e.g., PBPK models for adults only) 10 to allow for diversit y, including infants and children, with no hum an kinetic data A, 8, C

Values used for the toxicodynamic component of the intraspecies uncertainty factor, (UF H-d ): 1 Human study including sensitive subpopulations (e.g., inf ants and children) √ 10 Studies including human studies with normal adult subjects only, but no reason to suspect additional susceptibility of children 10 Suspect additional susceptibility of child ren (e.g., exacerbation of asthma, neurotoxicity) A, 8, C

Subchronic uncertainty factor (UF S )

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TABLE 4.4.1. POSSIBLE DEFAULT UNCE RTAINTY FACTORS USED IN DERIVING ACUTE, 8-HO UR AND CHRONIC RELS
Method or Factor Values Used REL types

Values used: 1 Study duration >12% of estimated lifetime √ 10 Study duration 8-12% of estimated lifetime 10 Study duration <8% of estimated lifetime C

Database deficiency factor ( UF D ) Values used: 1 No substantial data gaps √ 10 Substantial data gaps including, but not limited to, developmental toxicity A, 8, C

Notes for Table 4.4.1 : A = acute REL; 8 = eight-hour REL; C = chronic REL. “T oxicodynamic” refers to the processes involved in the toxic action at the system, tissue or cellular level. “Toxicokinetic” refers to processes involved in deposition, absorption, distribution, metabolis m and excretion of the toxicant. Individual UFs are rounded after multiplication, so two factors of √ 10 cumulate to 10, but one is rounded down to 3. Cumulative UF values are normally limi ted to between 1 and 3,000: if the la tter value is exceeded it is generally taken to indicate that the source data are in sufficient to support derivation of a REL. The table presents suggested default valu es in particular situations; these may be modified in either direction by more specific data relating to the test and target populations considered.

4.4.4 Application of Mechanistic Data in Inte rspecies and Intraspecies Extrapolation
It is necessary to determine what (if anything) is known of the mechanism of action of the toxic agent as a first step in evaluating which extra polation m ethodologies or UFs should be applied to the point of departure (BMC, NOAEL or LOAEL) for the extrapolation to estimate a safe level for human exposure. This will determine whether there are data to support a mechanistic model, or if a more generic model would be applicable . If the information ne cessary to construct a model is lacking, then the UF approach is nece ssary. The size of the UFs used is based on information about variability in response to broad classes of toxic agents, tests systems and target populations, and is necessarily a policy choice. It may neverthe less be possible to narrow the bounds of the uncertainty if specifi c features such as the site of action (either the respiratory system or other point of first contact, as used in the HEC approach, or a systemic target), and the general type of toxic response can be identified.
Extrapolation generally will be necessary to cove r two basic areas of difference between the test system (e.g., animals in a toxicological expe riment) and the target human population:
a) differences in absorption, distribution, m etabolism and excretion (dosimetric and toxicokinetic adjustments), and

Technical Support Document 49 June, 2008TSD for Noncancer RELs June 2008 b) differences between species or individuals in their sensitivity to the toxic material (either the original substance or a metabolite) at the site of its action (toxicodynamic adjustments).
As will be described in greater detail below, both these types of difference need to be considered either by means of a model, or by an UF, both for extrapolation from the test species (usually a rodent) to the human, and to allow for the lik ely range of inter-i ndividual variation among members of a human population wh ich is diverse in age, sex, genetic background, health status, diet, and lifestyle.
A general scheme for extrapolation between test and target species is shown Figure 4.2 below.

FIGURE 4-2. INTERSPECIES EXTRAPOLATION



## C A 

## D A Dosimetric and/or pharmacokinetic model (Animal parameters)



## D H 

## C H Dosimetric and/or pharmacokinetic model (Human parameters) Model of toxicodynamic differences b etween s p ecies Default: UF= 10 Applied Concentration Internal dose

Test Species

Human

C A = Applied concentration (e.g., BMC, LOAE L or NOAEL) in an animal experiment. D A = Dose of compound or active metabolite at site of action in animal. D H = Similarly effective dose of compound or activ e metabolite at site of action in a human. C H = Human equivalent applied concentration.

Technical Support Document 50 June, 2008TSD for Noncancer RELs June 2008 In this diagram and that which follows, the term “model” is used in the formal sense rather than implying that a detailed quantitat ive model of the transition is actually available. In practice such a quantitative model is usually not availabl e, or may be incomplete, in which case the uncertainty caused by this deficiency needs to be recognized by inclusion of an UF. As will be described in Sections 4.4.7.2.1 and 4.4.8.2.1 below, detailed models are sometimes available to describ e interspecies and intraspecies differen ces in pharmacokinetics. Unfortunately at this time there are few cases where quantitative pharm acodynamic models are available, so these extrapolations almost always utilize UFs to account for pharmacodynamic differences within humans and between species. Model parameters ma y be defined as single values appropriate to the test species and the default human, or as dist ributions representing uncer tainty in the values of these parameters. In principl e, variability in the values of key parameters in the animal models could also be represente d by distributions, although in pract ice such variation is usually small due to the standardi zed genotype and environmen t of laboratory animals.
A similar scheme ( Figure 4-3 ) may be applied in considering ex trapolation from the default adult specif ied in the interspecies extrapolation to other specific individuals, or (when a quantitative model is available, by replacing defined single para meter values with distri butions) to a range of such individuals encompassing the expected ex tent of variation in the target population (intraspecies extrapolation).

If C H is the human equivalent concentration of an effect threshold such as the NOAEL or BMCL 05 (adjusted for duration and for any other uncertainties), and a sufficient number of human cases ( i ), or an appropriate range of a distribution, is consider ed so that all but rare hypersensitive individuals are repr esented, then the REL is set at the level of the lowest individual equivalent concentr ation, or at an appropriate lo wer bound on the distribution of C H i values. In order to provide a REL, which is prot ective of children’s health, it is necessary that at least some of the cases considered, or distri bution values included in the models, represent children.
A selection of useful model type s and extrapolation procedures is given below. It should be noted that this selection is exem plary rather thanprescriptive, and that the models used in any particular case will be determined by the availabil ity of data and mechanistic information for that toxic agent and type of effect.

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FIGURE 4-3 INTRASPECIES EXTRAPOLATION



## C H 

## D Hd Dosimetric and/or pharmacokinetic model (Default human parameters)



## D H1 

## C H1 Dosimetric and/or pharmacokinetic model (Human #1 parameters) Model of toxicodynamic differences between individuals

Etc.



## D H2 

## C H2 Dosimetric and/or pharmacokinetic model (Human #2 parameters) Default: UF= 10 Internal dose

Test Species

Specific

subpopulations

or individuals Applied Concentration

C H = Human equivalent applied concentration (default human adult). D Hd = Dose of compound or active metabolite at site of action in a default human. D H1 = Similarly effective dose at site of action in human #1. D H2 = Similarly effective dose at site of action in human #2. C H1 = Equivalent applied concentration in human #1 C H2 = Equivalent applied concentration in human #2

4.4.5 Extrapolating from LOAELs to NOAELs
The use of the BMC methodology allows derivation of a point of departure suitable for REL determination even when an actual NOAEL has not been observed in the experiment. Since this approach uses an empirical model fit to the ac tual experimental data over the range of doses examined, it is the preferred way to address the un certainty inherent in deriving a REL from such an experiment. When this model-based extrapol ation is not possible due to limitations of data quality or reporting, an observed LOAEL may be used as the basis of the REL. The UF approach is then used to estimate a health-protectiv e level. This is a last resort, when data are entirely unsuitable for a benchmark dose analys is (e.g., all dose groups except control show 100% response rate). It should be recognized that use of the LOAEL methodology fails to reveal or quantify the actual uncertainty and variability cont ained in the source data, and can be influenced by the study design. A one-t o-ten-fold uncertainty factor (UF L ) has been proposed to

Technical Support Document 52 June, 2008TSD for Noncancer RELs June 2008 account for the higher health risk potentially associated with a LOAEL compared with use of a NOAEL (U.S. EPA, 1994a). Historically, a factor of 10 has been used in U.S. EPA and OEHHA assessments. This UF L is applied to estimate a threshol d level (NOAEL) from the LOAEL:

LOAEL/UF L = NOAEL
The relationship between LOAELs and NOAELs for acute, and some chronic, exposures has been exam ined by various authors. The effectiveness of a 10-fold LOAEL to NOAEL UF was confirmed for several data sets with inhalation exposure (Gift et al., 1993; Kadry et al., 1995; Alexeeff et al., 1997; Alexeeff et al., 2002) a nd oral exposure (Dourson and Stara, 1983). Mitchell et al. (1993) evaluated the LOAEL to NOAEL ra tio for 107 subchronic and chronic inhalation studies. They reported that 15 of the 107 studies had LOAEL to NOAEL ratios of 10 or greater. Alexeeff et al. (2002) evaluated 215 acute inhalati on studies for 36 chemicals and reported that the range of LOAEL to NOAEL ratios for mild effects had 90 th and 95 th percentiles of 5.0 and 6.3, respectively. In contrast, the ratio of the LOAEL for serious effects to the NOAEL for all effects had 90 th and 95 th percentiles of 12 and 40, re spectively (Alexeeff et al., 1997). Kadry et al. (1995) showed that among a small data set (four chemicals) LOAEL to NOAEL ratios were less than 5. However, where only a LOAEL has been observed, the magnitude of the difference between the observed LOAEL and the hypothetical NOAEL is uncertain.
On the basis of these data and following earlier precedents, OEHHA considers a 10-fold UF L for extrapolation from a LOAEL to a NOAEL to be pr otective when applied to all types of studies. However, OEHHA has also attempted to delineat e situations where UFs less than 10 could be used in the REL development proc ess. The use of an UF less th an 10 may be appropriate under certain circumstances, but application of UF s less than 10 has sometimes been somewhat subjective, and guidance as to when it is appr opriate is lacking. Consequently, OEHHA has developed criteria for use of an intermediate UF for acute RELs (see Section 5). These criteria are based primarily on data from acute exposures . When the effect is of low severity, the exposure is likely to be relati vely nearer to the NOAEL. Co nversely, more severe effects indicate the likelihood of a higher LOAEL to NOAEL ratio. Ho wever, extending this concept to evaluating chronic exposures or repeated 8-hour exposures is mo re complicated in this case because multiple effects are more likely to be se en, and serious and persistent effects such as developmental neurotoxicity may occur at low doses . Further, the 8 hour RELS are for repeated exposures, and chronic RELs are for continuous exposure – the exposure does not cease, so effects that are of no consequence for a short pe riod of time may indeed be adverse chronically.

Recommended default values of UF L for acute, eight-hour and chronic REL derivations are therefore as follows:
(1) Where the o bserved effect level used as th e basis of the REL is a NOAEL or equivalent benchmark, the value of UF L is 1. (2) When the acute REL is b ased on a LOAEL, wh ere the observed effect is mild for acute exposures (U.S. EPA grade 5 or below, Table 5.5.1), the value of UF L is 6. (3) When the acute REL is b ased on a LOAEL, wh ere the observed effect is moderate to severe, the value of UF L is 10.

Technical Support Document 53 June, 2008TSD for Noncancer RELs June 2008 (4) When the chronic REL is based on a LOAEL, the value of UF L is 10; except in chemicalspecific circumstances where there is an in dication that the LOAEL is closer to the NOAEL. One such indicator used in the prev ious guidance is when the percent of the population responding at the LOAEL is ≤ 30. (5) When the 8-hour REL for repeat exposures is based on a LOAEL, and the effect is essentially an acute resp onse, then the guidelines for the acute REL derivation are followed. When the 8-hour REL for repeat exposures is based on a study where the effect is essentially a chr onic response, the guidelines fo r chronic REL derivation are followed.
These default values may be replaced by more specific valu es where appropriate data are available (e.g.

, for specific toxicological endpoints or ch emical classes). However, the use of a LOAEL as the basis of a REL is to be avoided wh erever possible, by using data sets in which a NOAEL is also observed or, preferably, by a pplying the BMC methodology to a study where a range of response levels withincreasing dose is measured.

4.4.6 Extrapolating from Stu dy Duration to REL Reference Period
The target reference period for development of a REL is one hour (single or infrequent exposure) for acute RELs, eight hours with potential for repeat exposures for the eight-hour RE Ls, and lifetime/annual average for the chronic RELs. Acute RELs are typically based on data from short-term exposures of a few minutes to a few hours, and eight-hour or chronic RELs typically involve data from extended repeat-dosing studie s. However, the experimental duration, or exposure period in an animal or human study, is not generally the same as the REL reference period. Scaling procedures may therefore be requi red to extrapolate from the specific duration (and extent of repetition) of th e studies to the REL reference pe riod. Since these are specific to the type of REL being developed they are described in the subs equent sections dealing with procedures specific to th e individual REL types.

4.4.6.1 Eight-hour and Chronic RELs
The dose-response for most toxicological processes is assum ed to follow some form of dose-time integral over moderate periods of exposure. For medium-term adjustments in repeat-exposure animal studies such as six to ei ght hours to twenty-four, or five days a week to seven, a simple concentration multiplied by time (C x T) depende nce, often referred to as Haber’s Law, is assumed, so these results are adjusted by simple proportion, as described in Section 7.2.1

. The default approach to extrapolating from subchronic to chronic e xposures used by OEHHA (Section 7.2.2 ) for development of chronic RELs is to use a 1 to 10-fold subchronic uncertainty factor (UF S ) for subchronic exposures (Table 4.4.1). Chronic studies in st andard toxicological testing paradigms are those where the exposure dura tion is 12% or more of the expected lifetime of the test species, while subchr onic studies are repeat-dosing studi es shorter than this but longer than standard sub-acute protocols. The same adjustment is used for human studies where the average exposure duration is less than 12% of life time (70 years). For exposures less than 8% of expected lifetime a 10-fold UF S is applied, while for exposures from 8 to 12% of expected

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lifetime a 3-fold UF S is applied. Where exposures are longe r than 12% of expected lifetime there is no adjustment, i.e., UF S = 1.

4.4.6.2 Acute RELs
For shorter study periods such as those of a fe w minutes to hours that are considered in developm ent of acute RELs and some eight-hour RELs, the basic C x T dependence is modified by means of exponents. Most commonl y, an expression of the form C n x T is used to reflect acute toxic responses where concentra tion is a more important determ inant of response than duration over the time period of the observation. Application of this modi fied Haber’s Law procedure in development of acute RELs is described in Section 5.4.1

.
4.4.6.3 Exposure Duration REL Adjustments for Developmental Toxicants
Historically, duration adjustment of inhalation exposures for deve lopm ental toxicity studies has not been done (U.S. EPA, 2002a). Unlike subc hronic and chronic toxici ty studies, in which months or even years of exposure may be needed before tissue damage becomes evident, developmental toxicity is frequently the resu lt of exposure during a sm all window of time during gestation in which exposure may only be on th e order of hours during a critical stage of development. Because the timing and duration of the sensitive period of gestation is usually unknown, the standard experimental protocol is to expose pregnant animals for several hours per day over several days during gestation in order to increase the power of the study to detect an effect. As a result, time extrapolation to the REL must take into account two principal toxicokinetic issues to prevent, in particular, underestimation of developmental toxicity - peak tissue concentration and total tissue dose (e.g., ar ea under the concentration-time curve (AUC)). Instances of developmental toxicants that operate predominantly by one or the other toxicokinetic factors have been observed. For exam ple, prenatal exposure of mice to short, high exposures of ethylene oxide on day 7 of ge station was found to cause more adverse developmental effects than mice exposed to th e same C x T multiple but at longer, lower exposures (Weller et al., 1999). Alternatively, pregnant rats admi nistered all-trans-retinoic acid indicated that AUC, and not maximum plasma concentrations, was the most appropriate pharmacokinetic marker of developmental toxi city (Tzimas et al., 1997). The following procedures are designed to be health-protective ev en in the case where a developmental effect is the result of a possibly very brief sensitive period during a single day of exposure to the toxicant (U.S. EPA, 2004).

4.4.6.3.1 Developm ental REL Duration Adjustment from Shorter to Longer Exposures
When the principal toxicokinetic process invo lved in the developm ental toxicity of a nonaccumulating chemical is unknown, the U.S. EPA Technical Panel recommends that duration adjustment procedures from discontinuous to continuous exposures be based on equivalent multiples of concentration (C) and duration (T) for inhalation developmental toxicity studies as it is used for other health effects from inha lation exposure (U.S. EPA, 2002a). This C x T approach favors a health protective overestimati on of risk when adjusting the exposure duration from a shorter period to a longer period of exposur e, as has been shown experimentally in doserate studies of developmental toxicants (Weller et al., 1999). The pharmac okinetic basis for this duration adjustment assumes that the total tissu e dose during a single-day exposure period is the

Technical Support Document 55 June, 2008TSD for Noncancer RELs June 2008 critical quantity in determining the level of re sponse and ensures that the AUC, as well as the peak tissue level, will not be increased in the duration adjustment . Correspondingly, OEHHA will use this time adjustment procedure when estimating a chronic REL based on a developmental study. The default approach for dur ation adjustment of a developmental endpoint from discontinuous exposure to chronic continuous e xposure is the same as that used for a chronic toxicity duration adjust ment, and can be summarized as:

C AVG = (C OBS ) x (H hours / 24 hours) x (D days per 7 days);

where C AVG is the time-weighted average concentration, and C OBS is the observed concentration.
Time extrapolation to an eight-hour REL must also take into account pharm acokinetic processes affecting a developmental endpoint, from either a single eight-hour exposure or multiple daily eight-hour exposures during gestation. Thus, esti mation of the eight-hour REL will also use the daily average C x T time adjustment when extrap olating from a shorter exposure time to an eight-hour REL. The same daily average C x T ad justment should also be used when an acute REL is based on a developmental study involving exposure of animals for less than an hour for one or more days during gestation.

As more information becomes available on PB PK m odeling of developmental toxicants for interspecies extrapolation from the exposed an imal species to humans , modeling of blood and tissue levels may confirm the C x T adjustments on the REL exposure durations to ensure they do not exceed the peak tissue concentrati on or total tissue dose at the NOAEL.

4.4.6.3.2 Developm ental REL Duration Adjustment from Longer to Shorter Exposures
For acute REL development, time duration adju stm ent will often require extrapolation from multi-hour exposure to the 1-hour exposure durati on of the acute REL. Dose-rate exposure studies have shown that a C x T approach from a long exposure duration to a shorter exposure duration could underestimate the response of devel opmental toxicants (Welle r et al., 1999). To avoid underestimation of risk when the pharmacoki netic nature of the developmental toxicant is unknown, OEHHA recommends no duration adjustment on the exposure concentration when extrapolating from a longer exposure duration per day down to a one-hour exposure. This procedure primarily protects agains t higher peak tissue concentrati ons that would occur if a C x T time adjustment was applied. Preferably, the ac ute studies used as the basis of an acute REL would be those with exposure duration nearest one hour, in order to reduce the uncertainty of this approach. This approach would also apply to eight-hour RELs in which the primary study used daily exposures greater than eight hours (i.e ., no time extrapolati on would be applied).

4.4.6.3.3 Duration Ad justment for Bioaccumulating Developmental Toxicants
An additional pharmacokinetic issue to consider involves chem icals in which discontinuous daily exposures may take one to two weeks of gesta tional exposure before ti ssue saturation occurs. Many developmental studies begin exposures fo llowing conception. Conceivably, the critical point of gestation for developmental effects may have passed before maximal fetal/maternal blood levels were attained during the exposure period. For example, the aromatic hydrocarbon 1,2,4-trimethylbenzene shows a gra dual increase in prior-to-shift blood levels (and the AUC) in humans over a 5-day period with daily eight- hour exposures (Jarnberg and Johanson, 1999).

Technical Support Document 56 June, 2008TSD for Noncancer RELs June 2008 Ideally, in animal studies of a bioaccumulating to xicant, maternal exposures would occur prior to the beginning of gestation so tissue saturation at a given expo sure concentration is already present when development begins. Multi-genera tion studies often expose animals for at least several weeks prior to mating and could resolve th is concern. In lieu of multi-generation studies and studies that started exposure prior to gestat ion, a modifying UF may be considered for those chemicals that slowly accumulate to maximal tissue levels during gestational exposure, to account for the potential underestimation of dose during the window of developmental susceptibility. Alternatively, a fractional adjustment of the exposure level can be made if sufficient pharmacokinetic data are available to identify the time to tissue saturation and tissue saturation levels. This pharmacokinetic adjust ment would prevent exceedance of peak tissue levels or total tissue dose at critical time points in fetal development.
For major bioaccumulators such as dioxins and some metals, developmental exposure studies in which exposure occurred only during gestation is not sufficient for estab lishing eight-hour or chronic RELs based on developmen tal toxicity. These types of toxicants can accumulate in body tissues over extended periods of time prior to ge station, leading to very high maternal body burdens that may be detrimental to the fetus during gestation. Lack of sufficient chronic exposure and multi-generation studies and lack of adequate pharmacokinetic modeling information that can predict body tissue burdens ma y require application of a modifying UF for pharmacokinetic deficiencies in calculating the REL.

4.4.6.3.4 Effects of Exposure Continuity
Acute, eight-hour and chronic R ELs are intended to protect m emb ers of the general population from the types of exposures result ing from facility emissions or ambi ent levels of air pollutants. Such emissions may show variations diurnally, seasonally or over the long term. Modeling and interpretation of such exposure patterns are c overed in the Exposure Assessment section of the Hot Spots Technical Support Documents (OEHHA, 2000b). It may also be necessary to apply models or adjustments to the exposures receive d by the subjects (animal or human) of studies used as the basis for derivation of acute, eight- hour or chronic RELs, where animal experiments or human studies involve discon tinuous or repeated exposure patterns. Specific adjustment procedures are prescribed for derivation of RELs, which are different for the three types of REL. They are therefore describe d separately in Sections 5 , 6 and 7 , covering issues specific to each type of REL.

4.4.7 Accounting for Potentia lly Greater Human Susceptibility

4.4.7.1 Introduction
Greater sensitivity of humans compared to animal test species for a variety of toxicological endpoints have been shown Dourson and Stara (1983). A well-known example is teratogenesis by various agents including tha lidomide Brown and Fabro (1983). In general, interspecies UFs are applied to the animal study results to account for potentially greater hu man susceptibility (see Section 4.4.7.3 ). However, a preferred approach to interspecies extrapolation is to employ chem ical-specific kinetic models to assess species differences in relevant tissue dosimetry. If chemical specific models are not available, gene ric approaches such as the human equivalent concentration (HEC; the air concen tration of an agent that induces the same magnitude of toxic

Technical Support Document 57 June, 2008TSD for Noncancer RELs June 2008 effect in humans as that seen in experimental animals) and/or an animal to human uncertainty factor (UF A ) may be applied. As described above (Section 4.4.4 ), this factor may be regarded as consisting of toxicokinetic and toxicodynam ic factors, which ma y be considered separately where explicit models are available to describe some aspects of the ex trapolation, especially toxicokinetics. Differences in ac ute behavioral toxicity of toluen e in rats and humans are partly described by a toxicokinetic model: there are resi dual differences in sensitivity between species based on the tissue dose levels which might relate to actual sensitivity differences at the cellular level, or to differences in the sensitivity and co mparability of the tests used in the two species (Benignus et al., 1998; Bushnell et al., 2007).

4.4.7.2 Kinetic Modeling in Interspecies Extrapolation
As part of the scientific ba sis for this update of the risk assessm ent guidelines, OEHHA conducted a pilot investigation of the applic ation of physiologically based pharmacokinetic (PBPK) modeling to dosimetric adjustments innoncancer risk assessment. The aim was to derive alternate dosimetric adjustment factors ( DAFs) or human equivalent concentration (HEC) factors based on metrics of internal dosimetry su ch as peak concentrations (Cmaxs) and areas under the blood or tissue concentration x time curves (AUCs). The chemicals selected for this pilot study were: ethylbenzene, vinyl chlo ride, toluene, styr ene/styrene oxide, naphthalene/naphthalene oxides, and formaldehyde. All of these chemicals occur in outdoor and indoor air and have some prior PBPK model availa bility for rat or human. Initial comparisons were limited to rat/human conversions for adults and immature animals/children. In addition, since the overall objective is to improve the scien tific basis for predictive toxicological criteria for air pollutants the investigation also included a series of straight ch ain aliphatic aldehydes: CH 3 (CH 2 ) n CHO (n = 0 to 8). Several aliphatic alde hydes have been observed in outdoor (Uebori and Imamura, 2004) and indoor (Arcus et al., 1995) air sampling or are known to originate in building materials or furnishings.

4.4.7.2.1 PBPK Mode ls
The type of PBPK model used by OEHHA is de pendent on the physicochem ical characteristics and toxicokinetic properties of the agent in que stion (See Appendix E for more detail; see U.S. EPA (2006b) for a general descri ption of PBPK modeling). Broadly speaking, gaseous agents fall into one of three categories.

• Category 1 gases are reactive gase s that in teract mainly at th e site of contact; either the nasal or respiratory tracts (R T) as portals of entry.

o For agents in Category 1, OEHHA used eith er a 4- com partment RT model of the type described by Sarangapani et al. (2004) that is similar to a 3-compartment default model of the RT recommended by Hanna et al. (2001), with uptake defined by regional mass transfer coeffi cients. Depending on the agent being studied, for some Category 1 gases, OEHH A used nasal models as described by Frederick et al. (1998).

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• Category 2 gases tend to be less reactive and water soluble, a nd have effects both locally, on the RT, and systemically.

o For Category 2 gases, OEHHA used RT-PBP K models of the type described by Sarangapani et al. (2004). These m ode ls included both RT compartments and body compartments for remote distribution and metabolism as recommended by Hanna (2001).

• Category 3 gases are less wa ter so luble, less reactive, and therefore scrubbed less efficiently in the respiratory tract, and ma inly have remote systemic effects.

o For Category 3 gases, with m ainly remo te effects, OEHHA used either a onecompartment or, alternativ ely, a two-compartment lung model as described by Evelo et al. (1993), consisting of a high-pe rfusion alveolar exchange compartment and a low-perfusion bronchial compartment. In some instances flow-limited model components may be augmented or replaced with diffusion-limited components based on physicochemical/kinetic properties and improved model performance (e.g., dioxin).
Particle exposures are defined mainly by air concentration ( μ g/m 3 ), size distribution including mean mass aerodynamic diameter (MMAD, μ m) and geometric standard deviation ( σ g), breathing rate, nose versus mouth co ntributions, and particle solubi lity. The prototypical human model is the Human Respiratory Tract Model for Radiological Protection from the International Commission on Radiological Prot ection (ICRP, 1994). This model provides tables of deposition fractions by RT region, age, sex, br eathing rate and particle size. Computer models are available to predict RT clearance for a given exposure, and particle deposition and ICRP clearance parameters, e.g., Humorap 2 (Sanchez, 2002). A more complete deposition and clearance model for humans and rats is the multiple path par ticle deposition (MPPD) model of The Chemical Industry Institute of Toxicology (CIIT) and the Ne therlands National Institute for Public Health and the Environment (RIVM) (Anjilvel and Asgh arian, 1995; Brown et al., 2005; Jarabek et al., 2005). This model provides several particle number and mass-based dose metrics, although mass/surface area metrics need to be derived from graphic outputs of deposition and user supplied regional RT surface areas (Sarangapani et al., 2003). Another advantage of this model is a number of built in human child parameters for different ages. However, this model is very complex and longer-term simulations may not run successfully. Additional particle deposition and clearance models may be much simpler a nd adequate in many instances (Snipes, 1989a; Snipes et al., 1989b). The main dose metric of the Snipes model is mg/lung or lung burden. Also Yu and Xu (1987) provide a deposition mode l description for humans, rats, hamsters and guinea pigs that may be useful in many cases.

4.4.7.2.2 HEC Adjustm ent
The development of reference exposure concentr ations (RfCs ) by the U.S. EPA (1994a) requires the conversion by dosimetric adju stment of the NOAELs and L OAELs observed in laboratory animal experiments to human equivalent concen trations (HECs) for ambient exposure conditions (U.S. EPA, 1994a). The HEC procedure estimate s the concentration for human exposure, which would be equivalent to the animal exposure, by adjusting for differences in minute volume and

Technical Support Document 59 June, 2008TSD for Noncancer RELs June 2008 surface area of various regions of the respiratory tract between the experimental species and humans. The conversion of animal exposures to HECs is described in detail in Appendix F and involves the use of regional de posited dose ratios (RDDRs) for pa rticles or regional gas dose ratios (RGDRs) for gases. Category 1 gases are highly reactive and/or so luble, and they do not accumulate in the blood. For these compounds, the conversion factor usually reduces to a ratio of alveolar ventilation (AV A ) to regional surface area (RSA A ) for the animal test species, divided by the same ratio for the human (AV H / RSA H ). Adjustments for extrathoracic (ET), tracheobronchial (TB) and pulmona ry (PU) regions or the total lung can be calculated (U.S. EPA, 1994a). For pulmonary exposures to a cat egory 1 gas from rat data, adult and child specific dosimetric adjustment factors (DAFs) may be derived as follows:
DAF = (AV A / RSA A ) / (AV H / RSA H )
DAF (Adult) = (120 cm 3 /min/3400 cm 2 ) / (7000 cm 3 /min/633,000 cm 2 ) = 3.19
DAF (Child) = (120 cm 3 /min/3400 cm 2 ) / (914 cm 3 /min/21,500 cm 2 ) = 0.83

At the other extreme of reactivity an d solubility are Category 3 gases that have predominantly systemic effects. In the default methodology, th e average exposure concentration is adjusted with a RGDR that represents the ratio of the blood:air partition coefficient in experimental animals to that in humans [RGDR = (H b/g ) A /(H b/g ) H ] (see Appendix F.1.2). Category 2 gases fall somewhere between categories 1 and 3 on the conti nuums of reactivity and solubility. They are moderately soluble and/or reac tive and may have both local (res piratory tract) and systemic effects. In practice, in the absence of data sufficient to perform more sophisticated modeling, these compounds are treated as either Cate gory 1 or Category 3 gases depending on their physicochemical properties and the data availabl e for the specified toxicological endpoint.

Thus, a given rat NOAEL or LOAEL concentration would be m ultiplied by these factors to give human equivalent concentrations (HECs) for adults and childre n, respectively. The U.S. EPA derives RfCs by dividing the HECs by appropriate UFs. While this is a standard methodology, it is obvious that no chemical-specific informati on, other than a broad ch aracterization of gas category, is involved. The method essentially adjusts for a pote ntial difference in absorption based on physiological and anatomical differe nces between species. This methodology is described in greater detail and reviewed in Appendix F which also considers extensions necessary to allow for human intraspecies variability, including age differences.

4.4.7.3 Uncertainty Factor for Animal to Human Extrapolation (UF A )
Where data are insufficient to allow development of an extrapolation m odel, the default approach has been to apply a 10-fold uncertainty factor (UF A ) to animal data based on an assumption that an average human is likely to be at most 10-fold more susceptible to the effects of the substance than experimental animals Table 4.4.1 ). This is truly an “uncerta inty ” factor since we are unsure how humans would respond, in contrast to the animals tested, to the specific chemical. However, the UF is based on the potential for great er sensitivity of humans and the larger surface area of humans compared with experimental an imals (Rall, 1969; Weil, 1972; Krasovskii, 1976; Lewis and Alexeeff, 1989). This UF methodology is in contrast to the practice used in cancer

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risk assessment where an allometric surface area correction and a 95% confidence interval of the slope of the dose response are used. The UF approach was used by the U.S. EPA (1994a) and recommended by NRC (1977-1987) for drinking wate r standards. Dour son and Stara (1983) provided limited support for the co ncept of a ten-fold UF. Khodair et al. (1995) showed that among a small data set (six chemicals) animal NOAEL to human NOAEL ratios were less than four. Schmidt et al. (1997) evaluated inters pecies variation between human and five other animal species. Sixty compounds had human data th at could be matched to one or more animal species. The animal to human ratio of 10 represented approximately the 85 th percentile.

The U.S. EPA has used human e quivalent concentration (HE C) extrapolation and a 3-fold UF A for RfC derivation (U.S. EPA, 1994a). In the U.S. EPA method, this intermediate value is chosen since the HEC derivation is assumed to ha ve accounted for the toxicokinetic part of the difference between the species. However, this HEC extrapolation addresses only some of the differences; in particular, onl y respiratory regional exposure and deposition of the parent compound is considered; any differences in me tabolism and elimination are ignored. The remaining 3-fold UF is to account for pharmacodynamic or response differences between the species. This modified approach was also prev iously used by OEHHA fo r derivation of chronic RELs where sufficient data were availabl e. OEHHA continues to recommend the HEC methodology where data are insufficient to suppo rt a full PBPK model. However, it is recommended that the toxi cokinetic part of the UF A be reduced to 2, rather than 1 to reflect the presence of remaining uncertainties in toxicoki netics due to metabolism and excretion. In some instances, it may be appropria te to retain a larger UF A , for example if differences in deposition between the test species and hum ans are known to be large. OEHHA has also examined the effect of child-specific parameters on the HEC calculation.
Where both chemical- and species-s pecific data are unavailable, and therefore a HEC cannot be estimated, a 10-fold UF A is normally used. The 10-fold default UF A would only be applied after consideration of other f actors that potentially affect the valid ity of the default assumption. Such factors include differences betw een humans and the test species in absorption, distribution, and metabolism, which would serve as a basis for predic ting interspecies differences in susceptibility. In some cases, data may indicate that a larger UF A is appropriate. An exception is made for data from studies of non-human primates, where a default UF A of √ 10 is used because of their similarities to humans (See Table 4.4.1).

4.4.8 Increased S usceptibility of Sensitive Individuals

4.4.8.1 Introduction
RELs are intended to protect id entifiable sensitive individual s from harm due to chemical exposure. Susceptibility to harm from chemi cal exposure may vary among individuals due to genetic and epigenetic variabilitywithin the population, resulting in lower levels of protective biological mechanisms. Predisposition to incr eased metabolic activat ion or to decreased detoxification are just two examples of how genetic variability influences response to toxicants (Hattis et al., 1987; Eichelba um et al., 1992; Grandjean, 1992; U.S. EPA, 1994a; Autrup, 2000). Additionally, susceptibility to ch emical-related health effects ma y vary over time for the same individual due to changing factors such as age, health status, and activity level. It should be recognized that RELs may not necessarily protec t individuals who may de velop an idiosyncratic

Technical Support Document 61 June, 2008TSD for Noncancer RELs June 2008 response, such as allergic hypersensitivity, that ca nnot be predicted from sc ientific investigation of the chemical.
Thus, sensitive individuals may include infants, children, pregnant women and their fetuses, elderly persons, those w ith existi ng diseases such as lung, heart or liver disease, and persons engaging in physical activity (U.S. EPA, 1994a). Other factors, such as acute illness or immunosuppression, may cause short-term variati ons in individual susceptibility. Seasonal changes in absorption and toxicity have also been noted in labo ratory animals Barton and Huster (1987).
Healthy workers, the subject of most epidemiol ogical studies, are often f ound to have lower rates of m orbidity and mortality than the gene ral population (Wen et al., 1983; Monson, 1986) (Rothman and Greenland, 1998, p 119). In stud ies of experimental animals, highly homogeneous (inbred), healthy stra ins are generally used. Such strains are likely to have much less variability in response th an the heterogeneous human population. Chizhikov (1973) found that animals in poor health were more likely to experience adverse effects from chronic oral exposure to chemicals than were healthy animals.
Finally, OEHHA is required to protect infants and children in devel oping Reference Exposure Levels. There are a number of differences in re sponse to toxicant by age, which in som e cases, increase the susceptibility of in fants and children. These are described more fully elsewhere in Section 3.1.1 and Miller et al. (2002) and OEHHA (2001).

4.4.8.2 Pharmacokinetic Factors in Inter-individual Variability

4.4.8.2.1 Physiologically Based P harmacokinetic (PBPK) Models of Inter-individual Variability
PBPK models can give useful predictions of how the body handles a particular chem ical and its metabolites. The models address issues of in ternal body or tissue dosimetry, route-to-route extrapolation and, in some cases, interspecies extrapolation. To date, relatively few published models for various environmental pollutant s address infant and child exposure and pharmacokinetics in a systematic fashion. This is parallel to the bulk of toxicity testing in animals, which is usually in itiated in young adult animals.
However, this issue has received more attention in recent years than previously. Several authors have undertaken system atic modeling studies usi ng child-specific physiologi cal, biochemical and exposure parameters for various toxicants of inte rest (Pelekis et al., 2001; Pelekis et al., 2003; Price et al., 2003; Clewell et al ., 2004; Ginsberg et al., 2004b). These studies are summarized and evaluated in Appendix E. OEHHA has used these published results and also undertaken a series of original investigations (also described in detail in Appendix E) to explore both the feasibility of using child-specific PBPK mode ls when the necessary supporting data are available, and the appropriate values for UFs or other limited analyses where the data required for a full chemical-specific model are not available.

PBPK models are meant to incr ease the accuracy of risk asses sment and inform as to the adequacy of the traditional NOAEL/UF approach to deriving RELs. These models are used only where there are adequate data available. While in many cases the variability in a parameter can be adequately incorporated into the model where da ta exist to characterize the distribution of this

Technical Support Document 62 June, 2008TSD for Noncancer RELs June 2008 parameter, there is still residual uncertainty. Further, many parameters may have limited data available. Sensitivity analyses should be conducted in a chemical specific PBPK modeling exercise to ascertain the importance of specifi c variables to the model output, and to gain understanding of model uncertainty.
OEHHA’s approach to applying PBPK modeling to assess children’s environm ental health risks has been similar to that of Pelekis et al. (2001). We have used a case study approach using published PBPK models of selected environmen tal toxicants and adjusting anatomical and physiological parameters to simulate infant and ch ild ages from newborn to 18 years. Results are then compared to those using adult models. In these models, we have scaled metabolic parameters as a function of body weight. Wh ere possible we have focused on dose metrics involving toxicologically relevant metabolites. Initial findings by this approach were presented at the 2001 Children’s Environmental HealthSymposium (Brown, 2001). Of the seven chemicals studied with oral and inhalation expo sures (vinyl chloride, DCM, TCE, chloroform, arsenic, butadiene, and naphthalene), three chemi cals showed greater internal doses in children compared to adults: DCM, TCE, and but adiene, all via the inhalation route.
In follow up work we have attempted to stan dardize the m odeling approach for different chemicals as much as possible and focus on inha lation exposures only. For example, we have employed several of the age specif ic regressions for model parameters suggested by Price et al. (2003). Also in a few cases we have used more elaborate lung modeling, for example as proposed by Sarangapani et al. (2002) for styren e and styrene oxide, as opposed to the simpler lung modeling of Evelo et al. (1993) for butadiene. Two or three similar child models were used with differing fractional tissue flows more heav ily weighted towards rapidly perfused tissues than in adults. Details are provided in Appendix E.
The published studies and the OEHHA case studies of PBP K modeling show clearly that infants in the first year of life are likely to show increas ed internal dosages via the inhalation route for a variety of agents and their metabolites and longer clearance times (see Appendix E). It is also apparent that the current de fault intraspecies UF (UF A-k ) for kinetic effects of √ 10 is inadequate to protect neonates and young infants from some chemicals, as further discussed below.
It is worth noting that the large majority of studies and PBPK mode ling ex ercises involve relatively short-term exposures that represent environmental, occupational, or therapeutic scenarios. Extreme situations of short-term high exposures or very long-term low exposures were not simulated. Despite this limitation, the results are considered indicative of the unique toxicokinetics of infants and children for some e nvironmental pollutants. As such, a revised PK UF should be broadly applicab le to acute (one-hour), ei ght-hour, and chronic RELs.

4.4.8.2.2 Uncertainty Factor for Variability within the Human Population (UF H )
Where data are insufficient to permit developm ent of a reliab le model, an intraspecies uncertainty factor (UF H ) has traditionally been used to account for variability within the human population. This factor is intended to account for the greater susceptibility to chemical toxicity of various sensitive s ubpopulations, including infants and ch ildren. Previously, OEHHA has, like the U.S. EPA generally applied a 10-fold UF H to address variability in response among individual members of the general population (U.S. EPA, 1994a).

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4.4.8.2.2.1 Contribution of Kinetic Factors to UF H The variability in human response to toxicants m ay result from di fferences in toxicokinetics and toxicodynamics. The UF H typically used in OEHHA’s risk assessment methodology is thus considered to be composed of two sub-f actors to allow for bot h toxicokinetic (UF H-k ) and toxicodynamic (UF H-d ) differences ( Table 4.4.1 ).
Some studies suggested that the overall 10-fold factor was reasonable to account for intraspecies variab ility in humans. Gillis et al. (1997) sugge sted, based on modeled intraspecies variability, that for chronic exposures, a 10- fold factor will protect the 85 th percentile. Within this overall 10-fold UF H , the values of the two sub-factors UF H-k and UF H-dwere both assumed to be √ 10, which equals 3.16. However, more recent studies have indicated that a value higher than √ 10 should be considered for the pharmacokinetic com ponent of the intraspecies uncertainty factor (UF H-k ), especially for substances that are bioactivated, since th e enzymes involved in both Phase I (primarily CYP) and Phase II (numerous conjugating reactions) of xenobiotic metabolism have shown pronounced polymorphism in many cases (R enwick and Lazarus, 1998; Hattis et al., 1999).

4.4.8.2.2.2 Infants and Children

The difference in toxicokinetics is even more pressing when considering infants and children as part of the affected populati on. As discussed in Section 3.1 , it has been suggested that children

m ay be both more sensitive, and more diverse, than adults, as a result of both pharmacodynamic and pharmacokinetic factors affec ting toxicity. Several revisions in this version of OEHHA’s risk assessment methodology are designed to address this concern. An additional 10-fold UF (presumably to account for both toxicokinetic an d toxicodynamic factors) has been mandated by Congress to specifically protect ch ildren in assessments conducted for pesticides in accordance with the Federal Food Quality Protection Act (FQPA), assuming infants and children are more sensitive than adults, unless data to the cont rary exist. U.S. EPA (2002b) has developed guidelines for evaluating data to determine an a ppropriate value (generallybetween 1 and 10) for the FQPA-specified uncertainty factor. In the following discu ssion, the approach will be to determine an appropriate value to substitute for the default value for the two separate components of UF H , rather than to specify additional overall UFs.
In Appendix E we have summarized the more rele vant data and studies be aring on the size of the default UF to protect infants and children ade quately from the adverse effects of toxic air contaminants. Obviously, these studies and data are not ideal since th ey rely heavily on the pharmacology literature where most drugs are admi nistered orally and not by inhalation. In addition, drug literature frequently focuses on the parent compound rather than downstream metabolites, which are often of interest to envi ronmental toxicologists due to their frequent involvement in toxic modes of action. Modeli ng of environmental toxicants also presents difficulties, the foremost being a lack of releva nt metabolic parameters at various stages of human development. Infant and child metabolism of environmental agents is usually estimated by scaling from adult human or animal values, a limitation when there are qualitative as well as quantitative differences in infant vs . adult metabolism (e.g., theophylline). Table 4.4.2 summarizes the PK UF values indicated by the P BPK modeling of various test chemicals by OEHHA and others. Of the 25 chemicals a nd metabolites in this table, 13 have UF H-k greater

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than √ 10. This results primarily from the differen ces in toxicokinetics between infants and adults, resulting in high er internal dosages of the compounds and longer clearance half-lives. The details of these modeling exercises are given in Appendix E (text and tables; model parameters; and model equations).

4.4.8.2.2.3 Value of UF H-k to Account for Toxicokinetic Differences by Age
Based on the limited information presently available, OEHHA thinks it is appropriate to increase the def ault UF H-k from its previous value of √ 10 = 3.16 in order to protect neonates and young infants from potential adverse effects of airborne toxicants. OEHHA will apply a UF H-k value of 10 as a default for gases acting systemically, and for particles that involve systemic exposure via dissolution and absorption in the l ung or via the gastro-intestinal tract. Thus, in these cases, the overall default intraspecies UF would be 30. Gases that act solely at the por tal of entry (i.e., lung or upper respiratory tract for inhaled toxicants) without involvement of metabolic activation or other complex kinetic processes would use a UF H-k of √ 10. These are default values applicable to acute, eight-hour and chronic RELs derived from animal studies or epidemiological studies of healthy adult populations (e.g., workers). An exce ption to this procedure is when an exposure level is estimated from a study that includes the assessment of a sensitive human subpopulation, where a default UF H-k of 1 may be appropriate.
Because the true extent of variability is frequentlyunknown, there may be a portion of the population for whom the chronic RELs will not be protective. When information defining susceptible individuals is available, such data will be incorporated by means of pharmacokinetic models or adjustment of UFs as necessary to pr otect those individuals. Ideally, more chemicalspecific data in sens itive subgroups would obviate the n eed for the use of a default UF H. Unfortunately, such data are rarely available for children (or even immature animals) with environmentally relevant toxicants.

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TABLE 4.4.2. CHEMICALS ST UDIED BY OEHHA IN PB PK ANALYSES, GROUPED BY MODELED UF H-K FOR INFANTS AND CHILDREN (SEE APPENDIX E)

UF H-k ≤ √ 10 UF H-k > √ 10 to 9.9 UF H-k ≥ 10
Furan MTBE Perchloroethylene Styrene/Styrene oxide Butadiene/Butadiene monoxide/Diepoxybutane Naphthalene/Naphthalene oxides Ethyle ne/Ethylene oxide Dichloromethane Carbon tetrachloride Vinyl chloride TCE and metabolites Chloroform Toluene Benzo[a]pyrene Arsenic and metabolites† m-Xylene Ethylbenzene* Toluene/Xylene mixtures 1,1-Dichloroethylene‡ Isopropanol Benzene* Bromochloromethane* Methyl chloroform* Diethyl ether*

*Note that simulation results for these chemicals are notshown in the text but are based on parameters in Haddad et al. (2001) and Gargas et al. (1986) using th e same approach as for toluene and xylene. †Based on PBPK model of Yu (1999). ‡ Based on PB PK model of El-Masri et al. (1996a,b).

4.4.8.3 Contribution of Toxicodynamic Factors to UF H
A subfactor UF H-dto account for toxicodynamic differences between individuals has generally been assigned a default value of √ 10. This assumption is cons istent with the previous assumptions about likely human interindividual variability. However, although there are some specific data on individual susceptibility for pharmaceutical agents (for example, bumetanide: (Skowronski et al., 2001)), there is little basis other than this pr ecedent for setting a default value of UF H-dthat would be suitable for the kind of toxic chemicals of concern to the Air Toxics Hot Spots program. However, there are grounds for su specting that the differences between infants or children and adults may be greater for certain endpoints, as discussed in Section 3.2.2 . In these cases (such as chemicals causing neurotox icity, or suspected of causing or exacerbating asthm a) it may be appropriate to select a different, and larger, value for UF H-don a chemicalspecific basis. Such choices will be explained and justif ied in the desc ription of the individual RELs where they are applied.

4.4.9 Uncertainty Associated with Defi ciencies in the Overall Database

In som e cases, the database on an environmental chemical m ay be insufficient to be confident that the REL will be protective. Since this type of deficiency necessarily implies a lack of adequate data, it is accommodated by application of a database deficiency uncertainty factor (UF D ), usually a value of √ 10 ( Table 4.4.1 ). This is similar to the U.S. EPA modifying factor of 1 to 10 to account for data uncertainties in th eir procedures for calcu lating RfDs (U.S. EPA, 1993). As noted in U.S.EPA (2002a), “the database UF is intended to account for the potential for deriving an underprotective Rf D/RfC as a result of an incomplete characterization of the chemical’s toxicity. In additi on to identifying toxicity informa tion that is lacking, review of

Technical Support Document 66 June, 2008TSD for Noncancer RELs June 2008 existing data may also suggest that a lower refe rence value might result if additional data were available. Consequently, in deciding to apply this factor to account for deficiencies in the available data set and in identifying its magnit ude, the assessor should consider both the data lacking and the data available fo r particular organ systems as we ll as life stages.” Although this was not used in the previous version of the Hot Spots guidance, OEHHA now recommends an additional three-fold UF to apply in devel oping an REL for chemicals with substantial toxicological data gaps, including, but not limited to, developmental toxicity. In some cases, it may be appropriate to apply a database deficiency factor larger than three-fold. The need for the additional database deficiency UF will be evaluated on a chemical-by-chemical basis, and justified in the individual REL summaries. Examples of situations where this might be considered appropriate include where a structura lly related chemical indicates potentially more toxicity for the compound of concern than has be en evaluated experiment ally. Thus, structureactivity analysis may be brought to bear on use of the database deficiency factor. Another example is where there is a metabolite for which data indicate a concern for a type or severity of toxic response which has not been evaluated e xperimentally for the parent compound. Similarly, this factor might be applied where a preliminar y study was reported but the sample sizes used were too small or the number of doses used was in adequate to characterize an effect accurately.

4.4.9.1 Database Deficiency Factor for L ack of Developm ental Toxicity Data
Under SB 25, OEHHA is mandated to ensure that our health standards take into account the potential greater vulnerability of infants and ch ildren to chem ical exposure and toxicity. Some chemicals can affect the developi ng fetus or development in infant s and children. If studies in immature animals are lacking, it may be impossibl e to predict effects on developing organs and tissues. OEHHA will use a databa se deficiency factor (UF D ), with a default value of between √ 10 and 10, when animal developmental studies are notavailable for a chemical in order to help ensure that RELs protect infant s and children. The rationale for application of this uncertainty factor will be presented in th e individual toxicity summary.

4.4.9.2 Estimation of Inhalation Eff ects from Oral Exposure Data
Strong weight is given to inhala tion exposure-based health effect s data. If adequate inhalation data are not available, oral e xposure data are also considered. Both the U.S. EPA (1994a) and the NRC (1986b) support route-to-route extrapolat ion under certain circumstances. Route-toroute extrapolation m ay sometime s be inappropriate (e.g., where chemicals act at the portal of entry).
Use of oral exposure studies to develop RELs requires consideration of kinetic differences between routes, including differences in absorp tion across the lung versus the gastrointestinal tract. W herever possible, such extrapolations should be undertaken us ing PBPK models which allow for the route-specific features of uptak e and distribution of the specific chemical.

Where data are unavailable to support this approach it m ay be possible to use default assumptions or limited data to allow for route- to-route differences, at least in simple and straightforward cases. While rout e-specific differences in absorption and potency may occur, no additional UF is generally applied for non-inhalati on data. Instead, attempts should be made to adjust for absorption and other kinetic differe nces (e.g., first pass metabolism following oral

Technical Support Document 67 June, 2008TSD for Noncancer RELs June 2008 exposure) when possible. Owen (1990) found th at the median inhalation/oral absorption coefficient ratio was 1.0 for 34 substances. Fo r 32 of the substances (94%), inhalation absorption coefficients were at mo st 10-fold higher than oral abso rption coefficients for the same substance. The two exceptions (6%) with mu ch greater absorption by inhalation were metals with very low oral absorption (<1%): inhalation absorption of beryllium and elemental mercury was estimated to be 500-fold and 7,500-fold hi gher, respectively, than corresponding oral absorption. Fifteen substances (44%) were predicted to have greater inhalation than oral absorption, and 7 substances (21%) were predicted to have at leas t 2-fold greater inhalation than oral absorption. Pepelko (1987; 1991) provided additional evidence that differences between toxic effects following oral and inhalation exposures are generally within a 10-fold dose range. Inhalation and oral doses associated with a 25% additional risk of cancer (RRD(25)) were estimated for various chemicals. Carcinogens were more potent via oral exposure compared with inhalation exposure in 15 of 23 rodent data sets, and 20 oral exposure data sets (87%) predicted inhalation results within a 10-fold factor . Greater than 10-fold differences in potency were found in rats exposed to asbestos, hexavalent chromium (Cr VI ), hydrazine, or vinyl chloride.

4.4.10 Summary of Uncertainty Factors
A summary of UFs used for acu te, eight-hour and chronic R EL development is given in Table 4.4.1

.
4.5 Supporting Data
Summaries describing the development of the acute, eight-hour and chronic RELs for each chem ical are found in Appendix D. In addition, a list of acronyms is provided in Appendix A. All toxicity summaries for the newest RELs in clude a discussion of the information upon which the calculations are based. This discu ssion includes the following key elements:

1. Physical and chemical properties: Descripti ons include information on volatility, reactivity, stability, toxic secondary compounds, flammability, density, water solubility, color, odor, and some additional properties.

2. Occurrence and use: The typical m ajor uses of the chemical are described as well as where it is likely to be found. If available, meas ured ambient air levels are provided.

3. Routes of exposure: The routes of exposure th at m ay lead to toxic effects are mentioned for each substance. Since the intent of this document is to provide information on airborne toxicants, the data presented focuses on inhalation exposure studies and may be supplemented by relevant non-inhalation toxi cology studies. If i nhalation data are unavailable or are of poor qual ity for a particular chemical, other routes of exposure may be considered for the development of RELs. For extrapolation from oral to inhalation exposures, ideally a PBPK model dealing with both routes is used. Failing that, methodology presented by U.S. EPA (1994a) should be used.

4. Summ ary of toxic effects: Toxic effects are described for relevant endpoints. Where possible, all of the following attributes are men tioned: endpoints, test species, concentration

Technical Support Document 68 June, 2008TSD for Noncancer RELs June 2008 or dose, duration and frequency of exposure, type of effect level (such as benchmark dose or NOAEL), reversibility of findings, UFs applied, and RELs derived. Note: while an overview of the toxicity of the chemical is provided in the summary, only the papers deemed key to the REL are described in detail.

5. Pharm acokinetics and metabolism: A discu ssion of pharmacokinetics is included if information is available. This may in clude information on absorption, distribution, metabolism, and excretion. The inhalation rout e of exposure is examined preferentially. Metabolites of the parent compound are also identified when know n. Where data are available to support it, a pharmacokinetic model may be derived; if used in the derivation it is described in the summary.

6. Children ’s sensitivity to the chemical relative to adults: A discussion of the potential for infants’ and children’s differential sensitivity to the chemical is provided, and any adjustments to the REL to protect children ’s health are described. Effects on other potentially sensitive subpopulat ions are also considered.

7. Quality a ssurance measures: Weak or conflicting data are reviewed. Studies are evaluated for any recognized violations of sound laboratory or statis tical practices.

8. Sources of data: In the absence of well-doc um ented experimental dose-response studies in humans, reliance on toxicological data from an imal studies and human data from workplace and other exposures is appropria te. In addition, in vitro to xicity studies are sometimes reviewed, particularly for info rmation on mechanism of action.

9. Oral RELs: Substances em itted to the air may deposit on soil, water or plants with subsequent human exposure vi a non-inhalation routes. Si nce oral exposure is the predominant non-inhalation pathway, non-inhalati on RELs are referred to as oral RELs. Where appropriate, oral RELs ar e included to capture the cont ribution of this pathway, for example, for the nonvolatile compounds anticipate d to be present in the air adsorbed to particulate matter. In the absence of adequate inhalation data, oral REL data may be used in the development of inhalation RELs.

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## 5 Acute Reference Ex posure Levels

This section presents methods for deriving acu te (one-hour) inhalation Reference Exposure Levels (RELs) for toxic air contaminants (TACs). The acute REL is an exposure that is not likely to cause adverse effects in a human popul ation, including sensitive subgroups (such as infants and children), exposed to that concentration for one hour on an intermittent basis.
As with all health effects, certain individuals may be m ore susceptible to adverse health consequences following exposure above the acute REL. These sensitive individuals may suffer health effects at a lower level of exposure than the general popul ation. For example, individuals with asthma, who following exposure to sulfur dioxide are likely to exhibit bronchoconstriction at a lower concentration than the general population, may require greater protection from this substance than non-asthmatic persons. Acute RELs are designed to be protective for the range of susceptible persons in the general po pulation including infants and children.

5.1 Time Frame of Interest
In the Air Toxics Hot Spots Program, routine i ndustrial em issions are evaluated for potential public health impacts. Facility emissions ma y fluctuate considerably, with daily and hourly maximum and minimum concentrations. The comm only used air dispersion models can be used to model concentrations hour by hour throughout a year, giving an indication of the one-hour maximum exposure concentrations. The hourly fl uctuations are a reflection of the changing meteorological conditions that are included in the model. Section 5.4.1 provides more description of the underlying assumptions and applicability of the acute REL.
In general, the one-hour modeled maximum concen trations in the Air Toxics Hot Spots Program are used in a HI approach in order to evaluate “acute” expo sures and potential public health impacts from such exposures. The HI is th e ratio of the one-hour maximum modeled ground level concentration (GLC) to the acute referenc e exposure level (REL). If the ratio exceeds one, then the risk manager needs to c onsider whether risk reduction is appropriate. An exceedance of one does not mean adverse effects will occur. Rather, it is an indication of the erosion of the margin of safety for exposure to that chemical

5.2 .Exposure Duration and Patterns
As indicated in Section 5.1, the focus of acute RELs is on short-term exposures. A one-hour exposure is used as the timescale for which toxic ity is assessed, which is consistent with the hour-by-hour monitoring or modeling that is ge nerally conducted for f acilities under the Hot Spots Program. Sometimes it is necessary to extr apolate from other dura tions of experimental exposure or from reports of huma n exposure situations, to a 1-hour exposure duration. This is described in Section 5.4 , and is also discussed on a chemical -by-chem ical basis in the toxicity reviews for many compounds.

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5.2.1 Exposure Concentration Averaging Period

The acute REL is a concentration that is not lik ely to cause adverse noncancer effects in a hum an population, including sensitive subgroups, exposed on an intermittent basis to that concentration for one hour. Intermittent exposure is difficult to define. The U.S. EPA views intermittent exposure as that lasting less th an 24 hours and occurring no more fr equently than monthly. This is, in part, based on an assumption that an acute exposure concentration is at least 10-fold higher than the monthly average, and the presumption th at individual exposures are independent of one another. They point out that very few chemical s will have sufficient data to determine the safe “periodicity” of an acute exposure. Thus, U.S. EPA (1994b) has identifie d three issues to be addressed: length of acute expos ure, periodicity of exposures, and the relationship between the acute exposure and the chronic background (U.S. EPA, 1994b). These will be discussed below.
In acute toxicology experiments, the study design usually involves exposures of short duration to an otherwis e unexposed animal. However, real world “acute” exposures occur intermittently, rather than as rare events in a lifetime. T hus, the typical ambient exposure scenario is not reflected in the standard acute toxicology experimental design. The possibility of cumulative effects from intermittent ambient exposure canno t be addressed in acute REL development. Hence, acute environmental exposures are c onsidered by the U.S. EPA to occur no more frequently than monthly. The U.S. EPA also recommends that longer inter-exposure periods be established for chemicals with long clearance times or for those with evidence of cumulative or sensitizing effects.
A related exposure issue is the fact that peak exposures are superim posed on lower long-term exposures to the same compound. This is also not reflected in the standard acute toxicology design. For some compounds this will result in an in creased body burden rela tive to the typical toxicology experimental design a nd in a potential lowering of the acute exposure needed to produce an adverse effect. For sensitizers, peak exposures in occupational settings can increase the response to much lower levels . It is not clear whether sens itization occurs at environmental exposures, but it is an uncertainty. Chronic exposures to particulate matter pollution can result in elevated risk factors for heart disease such as atherosclerosis; peak exposures may trigger a cardiovascular event such as a myocardial infarcti on. The U.S. EPA’s approach is to assume that the peak exposures are at least 10 times the mont hly average so that the acute exposure can be considered to be relatively independent of the longer-term chronic exposure to the same substance (U.S. EPA, 1994b). This may be genera lly true for specific indu strial emissions (but not for regional air pollution).
Despite these limitations, it is im perative to examine whether s hort-term exposures to peak concentrations might result in adverse public health impacts. OEHHA’s RELs should be compared to the modeled one-hour maximum (or multi-hour as noted for specific reproductive/developmental toxicants) concentra tions used in the HI approach to risk assessment. OEHHA recommends that these acute RELs be used to evaluate exposures that occur no more frequently than every two weeks in a given year. The two-week interval was chosen because in most acute toxicology experi ments two weeks is the duration of time an animal is observed for signs of adverse outcomes following exposure.

Technical Support Document 71 June, 2008TSD for Noncancer RELs June 2008 An assumption in making this recommendation is that the REL is protective of adverse health effects that are not cumulative. Thus, the e ffects of each peak expos ure are independent of previous or subsequent peak exposures that occur as often as every two weeks. This recommendation is only valid for substances that do not bioaccumulate. Also, the assumption of independence of peak exposures is geared to typical ambient environmental exposures, and not occupational exposures or exposures to environm ental tobacco smoke indoors, for example. When bioaccumulation is known to occur and body bur den is associated with an adverse effect, or where cumulative tissue damage occurs with repeated exposures, longer inter-exposure periods should be specified.
The modeled one-hour peak concentrations ar e typically much great er than the m aximum average annualized concentrations used for determining chronic exposure and risk. Thus, it is assumed that acute exposures are independent of the long-term average exposure based on the modeled annualized maximum aver age concentration. However, under certain meteorological conditions (poor mixing, persistent calm winds), it is conceivable that there are many hours in a day or within a few days where exposures are cl ose to the peak one-hour in any given year. Concentrations close to the maximum one-hour exposure may occur many times during the year including on consecutive days. In addition, it is conceivable that exposure concentrations close to the maximum may occur in c onsecutive hours. Current ly, the local air districts, Air Board, and facilities do not ascertain how often exposur es close to the one-hour maximum occur in a given day, week, month or year. This contribute s to the uncertainty in evaluating the adverse health effects of peak one-hour exposures.
In evaluating chemicals with developmental toxi city, we found that the standard experim ental paradigm of repeated exposure over several days did not lend itself easily to extrapolation to a one-hour acute REL. Since developmental endpoi nts are frequently manifested in a small window of time during gestation, the standard protocol is to expos e pregnant animals for several hours per day over several days dur ing gestation in order to incr ease the power of the study to detect an effect. Issues that affect the extr apolation to one hour include not only when the sensitive gestational period is, but also toxicoki netic issues. Whether or not a single one-hour exposure could produce a reproductive or deve lopmental adverse outcome depends on the toxicokinetics governing the concentration of the chemical in ma ternal and fetal tissues, timing of exposure, mechanism of action, and other factors. These issu es are not easily taken into account in extrapolating to a one-hour acute REL. Thus, for those acute RELs addressing a developmental endpoint determined under our previous methodology, the REL was for the exposure duration chosen for a single day in th e experimental protocol . In this revised methodology, OEHHA proposes to use the exposure concentration in a developmental toxicity study as the basis of the one-hour REL, regardle ss of the daily exposure duration in the study. Given the seriousness of developmental endpoints and our mandate to ensure our risk assessment methods adequately protect infants and children, this is justified. It is rarely clear in a developmental toxicity study if the toxicity de pends on tissue concentrat ion during a discrete time interval or on total dose over the course of exposure. This may be pa rticularly important for developmental endpoints where short time periods of extreme vulnerability to toxicants may be accompanied by uncertainties in toxicological mechanisms. The duration of the period of vulnerability may itself be highly uncertain.

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5.3 Human Equivalent Concentration (H EC) Procedure for Acute RELs

When animal studies are used for acute R EL developm ent, the U.S. EPA HEC procedure (described in Appendix F) may be used as a pa rtial adjustment for inte rspecies toxicokinetic differences, in which case the 10-fold in terspecies UF is reduced to 6 (UF H-k = 2, UF H-d = √ 10). The modifications of the HEC procedure to a ccount for children may also be used. These procedures will be used where applicable as the acute RELs are update d to reflect additional available research and to fulfill the mandate s of SB 25 to account for potentially greater vulnerability of children when setting health standards.

5.4 Effects o f Exposure Duration – Special Considerations for Acute Effects

Studies of adverse health effect s associated with exposures in hum ans or experimental animals are generally conducted for time periods different from that which is of interest in the acute exposure scenario. Typical exposure scenarios involve several hours for human exposures and several daily exposures for two weeks in anim als. OEHHA acute RELs, on the other hand, are designed to be protective for one-hour exposures (with the ex ception of some developmental toxicants where the REL is fo r several hour exposures).
Acute inhalation toxicology studi es (exposure duration of 8 hour s or less) are preferred over other exposure routes. In their absence, stud ies using exposures of longer durations may be

em ployed if appropriate (e.g., symptoms noted after short period of time; developmental endpoints). If inhalation toxicity data are unavailable, studies on other exposure routes may be used. Studies that include an adequate follo w-up period (hours to days, depending on the chemical and endpoint) to account for delayed health effects are preferred to those that terminate observation immediately following exposure. In order to adjust e xperimental exposure durations to one-hour, OEHHA uses a method termed time extrapolation.

5.4.1 Concentration and Time Extrapolation using Haber’s Law
“Haber’s Law” states that the product of the c oncentration (C) and tim e of exposure (T) required to produce a specific physiologic effect is equal to a constant level or severity of response (K), or C * T = K (Rinehart and Hatch, 1964). When the dur ation of experimental exposure differs from the desired exposure duration for which an acute expos ure level is being calcul ated (in this case 1 hour), a modification of Haber’s Law is used to adjust the experimental exposure duration to the desired duration of the acute exposure level:

C n * T = K

where n is a chemical-specific parame ter greater than zero (ten Be rge et al., 1986). When n is equal to one ( n = 1), the toxicity of a chemical is equally depende nt on changes in concentration and duration of exposure; when n is less than one ( n < 1), the duration of exposure is a greater determinant of toxicity than the concentra tion; finally, when n is greater than one ( n > 1), the toxicity of a chemical is determined to a gr eater extent by exposure concentration than by duration.

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5.4.1.1 Value of the concentration exponent, n Ideally, the magnitude of n should be determined for all chemicals by evaluating the concentration versus response relationships for several different exposur e durations. However, this information is available for only a limited numb er of substances. Empirically-derived values of the exponent n range from 0.8-3.5 (ten Berge et al., 1986). The time-concentration-response relationship depends on the time-frame considered and the endpoint measured. There are usually multiple “n” values for a single chem ical that are applicable to di fferent response endpoints. For example, the “n” for irritation of ammonia is 4.6, while the “n” for lethality of ammonia is 2 (See Appendix G.). As concentration becomes the more important factor, the value of n will increase. Values of n greater than three suggest that concentration has a strong predominance over time.
The value for the exponent n used by OEHHA in acute toxicity summaries is chosen as follows. First, when an empirically derived value for th e exponent is available fr om the open literature, this is adopted for time extrapolation, using the modification of Haber’s Law as described above. Appendix G shows published or OEHHA derived values for n which were used in acute RELs previously devel oped by OEHHA (1999).

When a derived value is not available and there a re insufficient data from which to determine a value de novo , a default value for n must be used. The publishe d or OEHHA derived values for

n shown in Appendix G range from 0.8 to 4.6. The mean value in this range rounds to 2; the interquartile range (25%-75%) is from 1 to 2.2. Previously, the mean value of n = 2 was used by OEHHA (1999) when extrapolating from an exposure duration that is grea ter than one hour to a 1-hour level. However, when this issue was considered by NRC (2001) they concluded that it would be more appropriate to use the value n = 3, which approximates the 95 thpercentile of the range of values reported by ten Berge (1986). OEHHA now therefore recommends the use of n = 3 when extrapolating from experimental exposur es greater than one hour to the 1-hour period of concern for the acute RELs. Use of this exponent makes concentratio n much more important than time, and is thus health-protective when extrapolating from greater than one hour exposures to one-hour exposures.
When extrapolating from an experimental exposure duration of less than one hour to a 1-hour level, the va lue of n = 1 was used. Using a value of n = 1 is more health-protective than a value of

n = 3. A value of n = 1 results in a relatively rapid decrease in the derived REL when extrapolations are made from shorter to longe r exposures. For exampl e, when extrapolating from a 30 minute exposure at the published NOAEL of 60 ppm (Purser et al., 1984) to a 60 minute exposure for hydrogen cyanide, using n = 1 results in an extrap olated 1-hour NOAEL of 30 ppm; when using n = 3, the extrapolated NOAEL is 48 ppm.
In summary, the default exponent s used by OEHHA in the form ula C n T = K for extrapolation to 1-hour acute RELs are as follows:

• From less than 1 hour n = 1

• From greater than 1 hour n = 3

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5.4.1.2 Haber’s Law and Irritants
The applicability or otherwise of Haber’s Law to ir ritants has been the subj ect of various studies. The NAS ha s suggested that Ha ber’s Law does not apply for “some irritants” (NRC, 1986a; NRC, 1986b; NRC, 1993). This statement is appa rently based on the observation that for some substances, irritation appears to be solely concentration dependent. In fact, the time course of response to the small number of sensory irritant s for which data are available suggests that although the response follows a modified dose/tim e integral relationship (like most other toxicities) over very short time scales of a few seconds or minutes, this relationship has reached a plateau where the level of response is dependent only on concentration well within the one-hour time scale of concern for acute REL de rivation (Shusterman et al., 2006).
Response to mild sensory irritants is detected th rough binding to the trigem inal nerve receptors. In humans, this results in a complex response including a burning sensation of the eyes, nose, and throat. Other notable symptoms are c oughing, nasal congestion, rhinorrhea, sinus and Eustachian tube dysfunction, and worsening of lowe r airway function in some asthmatics (the socalled "naso-bronchial reflex") (W iddicombe, 1990; Raphael et al ., 1991). The response in the rodent is simpler, consisting primarily of a re flex depression of the breathing rate. When a mouse is exposed to an irrita nt, the decrease in respirator y rate is proportional to the concentration of the airborne chemical. Also, a minimum respiratory rate is reached and remains at a plateau, or fades in response during exposure. This has been used as the basis for a bioassay of sensory irritant properties (Alarie, 1966), in which irritant potency is expressed as the concentration producing a 50% depr ession in respiratory rate (RD 50 ).
Although the receptors have not been fully char acterized, receptor binding has been found to follow the classic M ichaelis-Menten receptor kine tics. There is evidence that many chemicals bind to a common receptor, sometimes referred to as the common “chemical sense” receptor (Cometto-Muniz et al., 1997; Brya nt and Silver, 2000). There is also evidence of multiple receptor types on the trigeminal nerve (Nielsen and Vinggaard, 1988). The irritant response can be described by the Michaelis-Men ten equation in an animal mode l (Kristiansen et al., 1986; Nielsen and Vinggaard, 1988) . Competitive agonism has beendemonstrated in the mouse RD 50 bioassay (Bos et al., 1991). This is additional evidence for a receptor mediated mechanism, with a common receptor for these two chemicals.
The degree of receptor binding is mediated by the tissu e concentration of the toxicant, not the duration of exposure once equilibrium is reached, which generally occurs relatively quickly. At equilibrium, at a constant exposur e concentration, a constant leve l of receptor binding would be expected presumably leading to a constant eff ect level, independent of the duration (the “T” factor in the Haber’s Law equa tion). Michaelis-Menten kinetics also predicts that receptors would be saturated at higher irri tant chemical concentrations a nd therefore additional trigeminal transmitted irritation response with increased expos ure concentration would not be expected in this situation.
Thus, irritation should be more a f unction of the air concentration of the irritant than of the total dose. Often these chem icals are non-reactive volatile organic compounds (VOCs), although in some cases they may be reactive. This simple picture is complicated by additional factors such

Technical Support Document 75 June, 2008TSD for Noncancer RELs June 2008 as desensitization of receptors that can cause a decline in perceived irr itation over time for some chemicals (Nielsen, 1991; Shusterman et al., 2006).
The trigeminal system is distinct from odor pe rception. Persons lacki ng a functional sense of

sm ell (anosmics) still perceive chemical irritant s in a similar fashion to people with a normal sense of smell. Odor perception occurs at a lower threshold than irritation, and in some cases at a much lower threshold. In both odor perception and trigeminal i rritation from a chemical, there can be wide variability in threshold air co ncentrations in the general population.

If the irritation reaction is a func tion of the concentration, then the fact that children have higher breathing rates than adults should not influence the health im pact of a particular concentration. There is no evidence that infants and children have different or more irritation receptors than adults. Therefore, OEHHA has not assumed that children are more sensitive than adults to the sensory effects of eye, nasal or respiratory irritants. However, it must be considered that many irritants, especially those that are chemically reactive, may have the potential to exacerbate or induce asthma, which is a special co ncern for children’s health.
OEHHA will consider trigeminally-transmitted sens ory irritation endpoints to be ind ependent of the duration of exposure over the one-hour timescale, unless data indicate such time dependence. Data establishing time dependency should be in a concentration range relevant for trigeminal nerve transmitted effects and not at considerably higher concentrations. Higher concentrations may cause irritation through tissue damage, a nd thus show time dependence because of accumulating tissue damage. The National Academy of Science Subcommittee on Acute Exposure Guideline Levels made the same dete rmination for their Acute Exposure Guideline Levels (AEGLs) (NRC, 2001). Sometimes trigeminally-transmitted irritation is difficult to distinguish (based on available data for a chem ical) from tissue damage mechanisms, or there may be mixed mechanisms. Empirical determinati on of an “n” value, indi cating that duration of exposure for a particular chemical influences toxicity, will be ac cepted as an adequate basis for Haber’s Law adjustments in these cases.

5.4.1.3 Strong Irritants Causing Tissue Damage and/or Hyperplasia
Some chemicals cause irritation through tissue damage that can re sult in hyperplasia or other nasal, eye or respiratory tissue dam age. The tissue damage resulting from exposure to these chemicals may be both time and concentration depe ndent and in some cases be dependent on the total cumulative dose or the c oncentration. For example, formaldehyde-induced hyperplasia appears to be more concentration dependent th an exposure duration dependent according to an analysis of several studies cited in the development of OEHHA’s chronic REL (OEHHA, 2000a). Trigeminally-transmitted irritation may occur at a lower concentration, while tissue damage or hyperplasia may occur at a higher co ncentration. Tissue damage or hyperplasia may also occur with longer exposur e to the same concentration (B arrow et al., 1986). This is particularly evident with highl y reactive chemicals such as ch lorine which have both sensory irritant and direct tissue-dama ging properties in the upper respir atory tract (Jiang et al., 1983; Bos et al., 1991). Chemicals which cause sensor y irritation in the upper respiratory tract as a result of lower short-term exposures may al so cause pathological changes in the lower respiratory tract, especially following more ex tended or more intense exposures (Shusterman, 1999). However, persistent histological changes may not always be seen with the isolated oneTechnical Support Document 76 June, 2008TSD for Noncancer RELs June 2008 hour exposures against which acute RELs are intende d to be protective. In such cases, the onehour REL would likely be diffe rent from a chronic REL.
If such tissue damage in the nose or other parts o f the respiratory tract accumulates over time, then the toxic effect would be dependent upon bot h time and concentration. Such damage could trigger pain receptors, and needs to be distinguish ed from trigeminally-transmitted irritation. In contrast to the case of pure sensory irritation, the use of Haber’s Law where tissue damage is a factor in the response is appropriate.
The higher breathing rates of children may need to be considered for chemicals caus ing cumulative damage at the point of entry, for which either total dose or AUC is the determinant of toxicity. An analysis of the mechanism of toxi city may help to determine whether children are more sensitive than adults to irritants that cause tissue damage or hyperplasia.

5.4.2 Time Extra polation for Acute RELs Based on Developmental Studies
In the previous guidelines, OEHHA (1999) cons idered that extrapolat ion to one hour using Haber’s law was not appropriate in the case of repeated dose studi es for developm ental endpoints. OEHHA chose a single day’s exposure for each chemi cal (ranged from 1 to 8 hours) as the exposure duration for which the REL is to be applied. Thus, no time extrapolation was used for developmental toxicants. Several of the acute RELs derived using these earlier guidelines based on developmenta l studies have averaging time s longer than one hour. These averaging times include six hours for benzene, carbon disulfide, EGEE, EGEEA, and EGME, and seven hours for carbon tetrachlo ride and chloroform (OEHHA, 1999).
OEHHA has developed a differe nt underlying m ethodology in th e present version of these guidelines, which has been described in Section 4.4.6.3 . As in the cases noted above, the time extrapo lation used when deriving acute RELs w ill most often be from a longer experimental duration to a shorter one-hour reference period for the REL. In these cases, the revised methodology treats the experimentally applied co ncentration as the basis for the acute REL, i.e. the concentration present during th e experiment is not to be exc eeded during any 1-hour period. The revised methodology will, in these cases, resu lt in an acute REL which is numerically the same as that obtained by the previous method, although the previous complication of having a non-standard averaging time is avoided.

5.5 LOAEL to NOAEL Ex trapolation
As noted in the general discussion of R EL methodology, there are som e cases where a benchmark concentration approach will not work b ecause of data constraints. The studies may not have identified a NOAEL, but only a LOAEL, and it may be necessary to extrapolate from the LOAEL to a NOAEL using a default UF L of 10. We have developed criteria for when the UF L can be less than the default of 10.
Following acute exposure, health effects of vary ing severity m ay be observed, depending on the extent of exposure, or dose, and the toxic pr operties of the compound. Although the relationship between exposure and health outcome is a co ntinuous one, effects may be categorized into discrete severity levels, part icularly for acute exposures (T able 5.7.1). The purpose of acute

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Mild effects are defined as those w ith severity of grade 5 or below, as described in Table 5.5.1.
Based on an analysis of LOAELs and NOAELs re ported in various acute toxicological studies, we found that when extrapolating from a LOAEL to a NOAEL for mild effects, UFs less than 10 are justified (Alexeeff et al., 1997; Alexeeff et al., 2002). In the case of the mild adverse effect, an analysis by Alexeeff et al. (1997) of LOAEL to NOAEL ratios for over 100 datasets indicated that the 95 th percentile of that ratio is 6.2. The dist ribution was skewed to the right; for some chemicals, a UF of 10 may not be adequate. OE HHA has chosen a UF of 6 to extrapolate from the LOAEL to the NOAEL where the effect is m ild, based on this analysis. Recommended default values of UF L for acute REL derivations are therefore as follows:

• Where the o bserved effect level used as the basis of the REL is a NOAEL or equivalent benchmark, the value of UF L is 1.

• For a LOAEL where the observed effect is m ild (for acute exposures, U.S. EPA grade 5 or below, Table 5.5.1), the value of UF L is 6.

• For a LOAEL where the observed effect is m oderate to severe, the value of UF L is 10.
These default values may be replaced by more specific valu es where appropriate data are available (e.g.

, for specific toxicological endpoints or ch emical classes). However, the use of a LOAEL as the basis of a REL is to be avoided wh erever possible, by using data sets in which a NOAEL is also observed or, preferably, by a pplying the BMC methodology to a study where a range of response levels withincreasing dose is measured.

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TABLE 5.5.1. RELATIONSHIP BETWEEN EFFECT CATEGORIES AND SEVERITY.

Severity Level Effect Category Effect

0 NOEL No observed effects.

1 NOAEL Enzyme induction or other biochemical change (excluding signal transduction effects), consistent with possible mechanism of action, with no pathologic changes, no change in organ weights, and no downstream adverse developmental effects. 2 NOAEL/LOAEL Enzyme induction and s ubcellular proliferation or other changes in organelles, consistent with possible mechanis m of action, but no ot her apparent effects. 3 NOAEL/LOAEL Hyperplasia, hypertr ophy, or atrophy, but without changes in organ weight. 4 NOAEL/LOAEL Hyperplasia, hypertroph y, or atrophy, with changes in organ weight. 5 LOAEL Reversible cellular ch anges including cloudy swelling, hydropic change, or fatty changes. 6 (LO)AEL Degenerative or necr otic tissue changes with no apparent decrement in organ function. 7 (LO)AEL/FEL Reversible slightchanges in organ function.

8 FEL Pathological changes with definite organ dysfunction which are unlikely to be fully reversible. 9 FEL Pronounced pathological ch ange with severe organ dysfunction and long-term sequelae; developm ental dysfunction including biochemical changes affecting signal transduction that result in developmental defects or dysfunction. 10 FEL Life-shortening or death.

(Adapted and expanded from U.S. EPA, 1994a) NOEL – no-observed-effect-level; NOAEL – no- observed-adverse-effect-level; LOAEL – lowest-observed-adverse-effect-l evel; AEL – adverse-effect-lev el; FEL – frank-effect-level.

5.6 Pre-Existing Acute Exposure Guidelines
Acute exposure standards have b een developed by several diff er ent organizations. However, there are no inhalation exposure valu es that were derived using a c onsistent basis to protect the public from planned industrial emissions. Values designed for protection of the general public exist, but they are intended to address accidental releases and use methodologies that are not well documented. Occupational exposure guidelines ar e available for hundreds of substances, but

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have an inconsistent basis, often have not in corporated recently available data, and are not designed to protect sensitive s ubpopulations. The ex isting exposure guidelines considered for possible relevance to OEHHA’s acute RELs are described below.

5.6.1 The Califor nia Ambient Air Quality Standards (CAAQS)
CAAQSs are promulgated by the Californi a Air Resources B oard (CARB) based on recommendations from OEHHA, and are specified concentrations and durations of exposure to air pollutants which reflect th e relationship between the inte nsity and composition of air pollution to undesirable effects. The CAAQS for a criteria air pollutant has in the past been adopted as the acute REL. If necessary, a one-hour value was derived using time extrapolation (described below). The CARB on April 28, 2005 reviewed the current one-hour ozone standard and left it unchanged, but promulgated a new ei ght-hour ozone standard. The two together are meant to provide adequate protection of sensitive populations including children.

5.6.1.1 Ambient Air Quality Standards as Acute RELs
Almost all acute RELs were developed de novo . However, the California Ambient Air Quality Standards for Criteria Air Polluta nts were reviewed. If they we re found to be appropriate, they were adopted as the relevant acute toxicity R ELs. For the six criteria air pollutants carbon monoxide, nitrogen dioxide, sulfates, ozone, hydr ogen sulfide, and sulfur dioxide, the CAAQS for short-term (one-hour) exposure is used as the REL, or one-hour values were derived by extrapolation from the 24-hour standard.

5.6.2 The Threshold Limit Value-Time Weighted Average (TLV-TWA) and Short-Term Exposure Limit (STEL)
The TLV-TWAs and STELs are developed by th e Am erican Conference of Governmental Industrial Hygienists (A CGIH) and updated annually (ACGIH, 2006); similarly, the National Institute for Occupational Safety and Health (N IOSH) recommended exposure limits also exist (NIOSH, 2005). The TLV-TWA is defined as th e time-weighted average concentration for a normal eight-hour workday and a 40-hour workw eek to which nearly all workers may be repeatedly exposed, day after day, without advers e effect. The STEL is defined as a 15-minute TWA exposure which should not be exceeded at any time during the workday.
Occupational exposure limits have sometimes been used to derive chem ical exposure guidelines for the general public (NATICH and McCull ough, 1991; Robinson and Paxman, 1992; U.S. EPA, 1994a). More than 600 ACGIH TLVs and NIOS H RELs are available. These values have been attractive because of the large number of accessible values and the concept that they are intended to protect a human population from inhala tion exposures. However, these values are not designed for or recommende d for protection of the general public, and in many cases may not prevent adverse health effects among workers (Roach and Rappaport, 1990). OEHHA has therefore not taken the TLV-TWAs and STELs dir ectly into account in developing acute RELs, but has taken advantage of the data identified and evaluations offered by ACGIH when relevant.

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5.6.3 Various Emergency Exposure Guidance Levels
A variety of guidance levels have b een developed to assist in dealing with accidental chemical releases. As such, these values focus on emer gency planning and response, not on the routine emissions and exposure which are the focus of th is document. Thus NRC (2001) described the objective of U.S. EPA’s AEGL program (see below) as “to develop guideline levels for once-ina-lifetime, short-term exposures to airborne co ncentrations of acutel y toxic, high-priority chemicals.” Emergency guidelines are typically defined as predic ted thresholds above which some level of adverse health effect is anticipated: standard margins of safety are not incorporated. Also, in many cases these guidelines are designed to identify tolerable conditions for emergency first responders such as firefighter s or military personnel, rather than to protect the general population. Such guida nce values are seldom comparable to the acute RELs, and are not suitable for protecting the he alth of the general public from routine emissions. However they may incorporate relevant information as to the type of effects to be expected and the dose response for exposure to compounds of interest.
Emergency Exposure Guidance Levels (EEGLs) ar e des igned to provide guidelines for military personnel operating under emergency conditions that are peculiar to military operations and for which regulatory agencies have not set standa rds, and are defined by the NAS as the ceiling concentrations of substances in air that may be judged by the Department of Defense to be acceptable for the performance of specific tasks during rare emergency conditions lasting for periods of 1 to 24 hours (NRC, 1986a). “Emerg ency” connotes an unexpected situation with potential for loss of life. The Short-term Pub lic Emergency Guidance Level (SPEGL) is defined by the NAS as a suitable concentration for unpr edicted, single, short-term, emergency exposure of the general public (NRC, 1986a). In contrast to the EEGL, the SPEGL takes into account the wide range of susceptibility of the general public , but it is not designed for repeated or multiple exposures. The American Industrial Hygiene Associati on (A IHA) has defined Emergency Response Planning Guidelines (ERPGs) as concentration ranges where adverse health effects could be observed (AIHA, 2006). ERPGs have a specific emphasis on responding to accidental releases.
The U.S. EPA has developed Acute Emerge ncy Guidance L evels (AEGLs) to provide information to incident commanders in an emergency. The NRC has published a methodology for developing AEGLs (NRC, 2001). As of April 2007, AEGLs for 31 chemicals have been finalized (U.S. EPA, 2007a).

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5.7 Areas for Further Research

5.7.1 Acute Toxic ity Data
Many chemicals lack adequate data on acute t oxicity. There are appr oximately 450 chem icals on the Air Toxics Hot Spots list of substances to be quantified (Appendix C). This is the list of substances, which facilities must report in their emissions invent ories. We have to date only developed acute RELs for 51 of these compounds, six of which have so far been revised according to these new guidelines. While not al l of the 450 chemicals have reported emissions in California, more work needs to be done in analyzing available litera ture for the remaining compounds and in revising existing RELs to take explicit account of children’s health issues.

5.7.2 LOAEL to NOAEL Uncerta inty Factor
The application of UFs to account for extr apolation fro m a LOAEL to a NOAEL warrants further analysis (see Section 4.4.5). When eval uating dose-response relati onships, the slope of the dose-response curve determines the dist ance between the LOAEL and the NOAEL from a particular study. Some endpoints tend to have steep dose-response slopes and may not warrant a 10-fold UF to extrapolate from a LOAEL to a NOAEL; other endpoint s have a shallow doseresponse slope and may warrant a 10-fold (or higher) UF for extr apolating from the LOAEL to the NOAEL. An analysis of the distribution of the LOAEL to NOAEL ratios for 112 datasets (Gift et al., 1993; Kadry et al., 1995; Alexeeff et al., 1997; Almstr up et al., 2002) suggested an intermediate UF of 6 to extrapolate from the LOAEL to a NOAEL for mild effects. Further analysis of 215 data sets for 36 pollutants yielded LOAEL to NOAEL ratios of 2.0, 5.0, 6.3, and 10.0 for the 50 th , 90th, 95 th , and 99 th percentile, respectively (Ale xeeff et al., 2002). The 90% confidence interval for the 95th percentile wa s 5.0-7.5. Thus, the LOAEL to NOAEL UF of 6 would be protective for 95% of the responses, and a value of 10 for 99%. However, the 99 th percentile value was considered un stable. For this reason the 95 th percentile value is chosen for extrapolation of the LOAEL to a NOAEL for mild effects.
Little variability was noted among species, particularly at the m edi an. This analysis is based on toxicity data from mild acute inhalation studies and may not be appli cable to other exposure routes, exposure durations, or more severe toxicity. (A value of 10 should be used by default for effects considered severe.) In addition, this an alysis did not focus specifically on children.

5.7.3 Interspec ies Uncertainty Factor
An interspecies UF of 10 is commonly used to ex trapolate from animal studies to the human response (UF A ) (Section 4.4.7.3). The available analys es supporting use of the 10-fold interspecies UF A were conducted on studies of toxicity by the oral route of administration (Dourson and Stara, 1983). Furthe r analysis of available data on chemicals for which there is both human and animal data for the same e ndpoints by the inhalation route of exposure is warranted.
In some cases, there may be a reason that a di fferent UF could be used. Som e part of the uncertainty encompassed by this factor may be replaced by species-specific models of

Technical Support Document 82 June, 2008TSD for Noncancer RELs June 2008 deposition, distribution or metabolis m where data exist to support th ese models. In certain cases there may be specific reasons for concluding that the toxicodynamic component of this variability may be smalle r or larger than the √ 10 assumed by default. For example, in lethality studies, the exposure to irrita nt chemicals producing lung edem a may have very similar doseresponse slopes because the basic loss of ce llular integrity at high doses may not be a phenomenon that would vary substantially from one species to another. However, in general data on the extent of toxicodynamic differen ces between species are limited, although the situation for acute exposures may be simpler than for the case of chronic exposures. The existing analyses are limited in terms of toxi cological endpoints examined. Interspecies variability may differ significantl y for different toxicological e ndpoints. This is another area where more research is warranted.

5.7.4 Uncertainty Factor for Database Deficiencies
An additional UF may be used in cases where th e re are identifiable deficiencies in the data (Section 4.4.8.3 ). For example, a database deficiency factor of √ 10 (UF D ) may be applied to protect developing infants and children if no developm ental data are available. Judgment is still needed when some developmental data are av ailable. The ideal dataset for evaluating developmental endpoints would include studies intwo species in which exposure occurs during gestation and a two-generation reproductive study in each of two species. In practice such a large database is unusual. Available mechanistic data will be considered when deciding when to apply the data base deficiencyfactor and what its value s hould be. The more robust the database, the less likely that the factor will be ne eded. Other types of data deficiency besides developmental toxicity may also be addressed with this factor.

5.7.5 Time Extra polation for Acute RELs
We have used time extrapolation with a modi fied Haber’s Law to extrapo late from the experimental duration in the acute study to an eq uivalent concentration for a one-hour exposure, for endpoints other than sensory ir ritation. There are empirical datafor the value of n in Haber’s equation for some chemicals. More data would be valuable for additional chemicals. Further analysis of the validity of the Haber’s Law a pplication for different toxicological endpoints would be useful.

5.7.6 Additiv ity of Adverse Effects
We currently use an additive approach to assess the impacts of multiple chemicals on a target organ (Sections 2.2; 5.3). Som e interactions may be synergistic and others antagonistic. Additivity has generally been accepted as health-pro tective at low environmental concentrations. However, there is a need for key studies on the additivity or synergism of chemicals at low concentrations that act on the same target orga n. Further literature ev aluation would also be helpful to elucidate whether the additive approach is the most valid approach for all scenarios (DeVito et al., 2000; Crofton et al., 2005; U.S. EPA, 2007b).

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## 6 Eight-Hour Reference Exposure Levels

This section presents additional informati on for deriving eight-hour inhalation Reference Exposure Levels (RELs) for toxic air contaminants (TACs). Eight-hour RELs are concentrations at or below which adverse health effects are not likely to occur in the general human population with intermittent exposures of eight hours per day, up to 7 days per week.

6.1 Populations at Risk
The Air Toxics Hot Spots Program Guidance Manual for Preparation of Health Risk Assessm ents (OEHHA, 2003) calls for evaluation of sensitive receptors such as daycare centers and schools as well as offsite workers. Onsite workers are under the jurisdiction of the California Occupational Safety and Health Admini stration. Current occupa tional standards such as threshold level values (TLVs) and permissi ble exposure levels (PELs ) are usually expressed as a time weighted average (TWA) over an eight -hour shift. Noncancer health impacts for children at schools have been eval uated using either the chronic or acute RELs. Acute RELs are only useful for evaluating impacts of estimated maximum one-hour air concentrations when such exposures occur infrequently. E xposure duration for children and offsite workers will vary, but an eight-hour exposure duration assumption would be reasonable, particularly if children and offsite workers are exposed to facility emissions at their school or place of work and not at their residential locations. It is not intended that appl ications of 8-hour RELs will be confined to five days per week. Many facilities operate seven da ys a week, and the exposed individuals include categories besides workers on a standard daily sh ift. This means that it cannot simply be assumed that cumulative impacts and bioconcentr ation issues are covered by the timing of exposures for a typical occupational exposure.
Chronic RELs are designed to be protective ag ainst long term 24-hour a day exposure and thus

m ay overestimate some noncancer chemical risks a ssociated with shorter, daily exposure (e.g., eight-hour exposures). Alterna tively, chronic RELs may underest imate the noncancer risk where facility operation and emissions occur only 8 hour s per day but coincide with the presence of nearby offsite workers and attendance at daycares and schools. Many faciliti es operate five days a week, eight hours per day. Such facilities have been modeled as if the total emissions were occurring twenty-four hours a day, seven days a week, three hundred sixty five days a year. The annual average ground level concentr ation (GLC) could then be comp ared to the chronic REL to determine noncancer chronic health risk. This a pproach has the advantage of simplicity but is a less accurate modeling a pproach because of diurnal meteor ological variation and non-continuous facility emissions. This approach assumes th at a higher eight-hour pollutant concentration followed by a sixteen-hour period of no exposure is toxicologically equivalent to the twenty-four hour average concentration (with two days of non-operation). De velopment of eight-hour RELs would allow more accurate evaluation of the im pacts of exposure to modeled eight-hour ground level concentrations by comparis on with noncancer health standard s specifically tailored to actual exposure duration.

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6.2 Characterization of 8-Hour Exposures
An eight-hour REL, designed to protect against pe riodic exposure that could occur as often as daily, m ay share characteristics of both acute and chronic exposure. Frequent eight-hour exposures to a chemical with a short half-life in the body that does not cause tissue damage or accumulate may resemble a series of acute exposure s. The previous exposures may have little or no impact on the current-day exposure. In these cases, acute exposure methodology would be employed for derivation of the ei ght-hour REL. Frequent eight- hour exposures to a chemical that accumulates in the body, or causes cumu lative tissue damage, a nd/or activating or deactivating enzyme induction is considered a chronic exposure, requiring chronic exposure methodology for derivation of the eight-hour REL. The REL for an eight-hour period would need to be adjusted in such cases to reflect cumulative dose from previous eight-hour exposures. Pharmacokinetic modeling may be appropriate to determine the cumulative dose from serial eight-hour exposures.

6.2.1 Eight-Hour Averaging Period based on Chronic Toxicity
In cases where the evidence shows that an eight -hour REL should be derived based on chronic exposure, a modification of the default approach adopted for the chronic RELs is used (see Section 7.2.1). The default approach to esti m ating an equivalent time-weighted average concentration (C AVG ) from the observed concentration (C OBS ) in non-occupational, continuous exposure studies may be summarized as:

C AVG = C OBS x (H hours per 8 hours) x (D days per week)
Based on the assumption that half of the 20 m 3 of air breathed in any 24 -hour period is breathed while active at work, the default approach to estimating an equivalent inhalation-weighted average concentration (C AVG ) for an eight-hour period of elevated activity (such as at work) from the observed concentration (C OBS ) for continuously exposed humans or experimental animals is:

C AVG = C OBS x (20 m 3 /day total exposure / 10 m 3 /day occupational exposure)
x (D days per week)
Commonly encountered exposure scenarios in both worker studies and experim ental animal toxicology studies involve exposur es of 6 to 8 hours per day for 5 days per week. Less time adjustment, and associated uncertainty, occurs applying an eight-hour REL under these exposure scenarios relative to applying a chronic REL.
For simplicity, it may be desirable in some cases to use th e chronic REL as a health guidance value for repeated eight-hour exposures. This might be appropriate for substances where the response is concentration rather than time depe ndent, and for substances that accumulate in the body and have long internal half-lives, such as dioxins and some metals, or substances that demonstrate cumulative toxicity, where large pharm acokinetic uncertainties exist. Thus, in these cases the chronic and eight-hour REL may be the same.

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6.2.2 Eight-Hour Averaging Period fo r Acute Recurrent Toxicity
There are some acute RELs that have used singl e health studies with si x- or eight-hour hum an exposures to derive NOAELs or LO AELs. It may be appropriate to use such studies to derive eight-hour RELs using acute REL methodology if the data show th at the chemical is quickly eliminated and does not cause cumulative tissu e damage. Similarly, intermittent exposure studies in experimental animals, often with da ily exposures at or near six hours, may exhibit toxicity that reflects a daily recu rrent acute effect rather than a chronic cumulative-type injury. In some cases, that daily recurrent acute effect may consist of sensory irritation, in which case no concentration adjustment is ap plied to extrapolate to an ei ght-hour REL (see Section 5.8.1). A cautious interpretation of such situations is n ecessary, however, since a nu mber of agents shown to cause sensory irritation during a single one-h our (acute) exposure have also been shown to cause persistent (and ther efore to some degree cumulative) hi stological damage in various parts of the respiratory tract followi ng repeated (chronic) exposures.
In cases where daily intermittent exposure shows a recurrent acute effect other than sensory irritation, acute REL m ethodology is applied for time extrapola tion to an eight-hour exposure employing a modification of Haber’s Law as follows:

C n * T = K,
In this equation, (C) is concentra tion, (T) is tim e of exposure, and n is a chemical-specific parameter greater than zero. When the value of n is unknown, default exponents are used by OEHHA for extrapolation to 8 hours. When extrapolating from an experimental exposure duration of less than 8 hours to an eight-hour leve l, the value of n=1 was used. A value of n = 1 results in a relatively rapid decrease in the de rived REL when extrapolations are made from shorter to longer exposures and is considered an appropriate hea lth-protective a pproach. Most human worker and experimental animal studies with daily intermittent exposures have time durations at or near 6-8 hours per day, which are well-suited for extrapolating to an eight-hour REL. Data on experimental or workplace exposu res longer than 8 hours are less likely to be encountered, but if this were the case a value of n = 3 would be used as for the acute RELs. Daily exposures considerably less than 6 hours are not as preferab le and may be more practical for acute REL derivation.

6.2.3 Eight-Hour REL Expos ure Duration Adju stments for Developmental Toxicants
Because the timing and duration of the sensitive period of gestation is usually unknown, time extrapo lation to an eight-hour REL must take in to account two principal toxicokinetic issues to prevent, in particular, underestimation of devel opmental toxicity - peak tissue concentration and total tissue dose (e.g., area under the concentratio n-time curve, or AUC). Additionally, for those developmental toxicants where there is a suspic ion that the chemical or its metabolites may accumulate with daily eight-hour exposures, a duration adjustment from discontinuous to continuous exposures based on equivalent multiple s of concentration (C ) and duration (T) is recommended (See Section 4.4.6.1). This C x T a pproach avoids possible underestimation of risk when adjusting the exposure duration from a s horter period to a longer period of exposure.

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As more information becomes available on PB PK modeling of developmental toxicants for interspecies extrapolation from the exposed an imal species to humans , modeling of blood and tissue levels may confirm the C x T adjustments on the REL exposure durations to ensure they do not exceed the peak tissue concentrati on or total tissue dose at the NOAEL.
For developmental studies in which the daily exposures are greater than eight -hours, a “not to be exceeded” h ealth guidance is recommended in wh ich no adjustment is applied to the duration with extrapolation down to 8 hours. This proced ure avoids underestimation of risk when the pharmacokinetic nature of the de velopmental toxicant is unknown.
For bioaccumulating toxicants such as dioxins and some metals, developmental exposure studies in which exposure occurred only du ring gestation is not sufficient for establishing an eight-hour REL based on developmental toxicity. These type s of toxicants can accumulate in body tissues over extended periods of time prior to gestation, leading to maternal body burdens that may bedetrimental to the fetus during gestation. Lack of sufficient chronic-exposure and multigeneration studies, and adequate pharmacokineti c modeling information that can predict body tissue burdens, may require app lication of a modifying UF for pharmacokinetic deficiencies in calculating the REL.

6.3 Human Equivalent Co ncentration (HEC) and Uncertainty Factor Applications
Application of HEC adjustments and UFs for eight -hour REL derivation uses the same formulae

as are us ed for the acute and chronic RELs. Fo r eight-hour RELs based on chronic effects, the UFs used for chronic exposure are applied; for eight-hour RELs based on acu te recurrent effects, the UFs used for acute exposures are applied.

6.4 Haz ard Index Calculation
In calculating the HI, the same standardized targ et organ categories are used for the eight-hour RELs as for acute and chronic RELs (see Section 4.3.4 ). Calculation of the HI is described in Section 2.2.

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## 7 Chronic Reference Exposure Levels

This section presents additional information fo r deriving chronic inhalation Reference Exposure Levels (RELs) for hazardous airborne substances . Chronic exposure is evaluated using ambient air concentrations of emitted chemicals aver aged over a year. The annualized average air concentration forms the basis for both chronic no ncancer and cancer risk evaluation. In reality, exposure over a 24-hour period does not occur at a continuous level. Chronic RELs are concentrations at or below whic h adverse health effects are not likely to occur in the general human population exposed continuously over a lifetime.

7.1 Priority for Evaluation of Chemicals
Chronic noncancer RELs have been developed f or 80 substances as of May, 2005; these are described in Appendix B of this Technical S upport Document and in OEHHA (OEHHA, 2000a). Substances were selected for chronic REL deve lopment primarily based on (1) the magnitude of current known emissions in California, (2) the av ailability of a strong scientific database on which to estimate a chronic REL, and (3) toxic ity. We include impacts on children’s health or other sensitive subpopulations in prioritizi ng chemicals for chronic REL development.
The amount of data and the quality of the info rm ation will ultimately determine whether a chronic REL can be derived for a specific chemical . Margins of safety or UFs can be used to address the common data gaps enco untered in risk assessment, but in some cases, chronic RELs cannot be developed because the data are not re levant to inhalation e xposure, or because too much uncertainty exists in the database and subsequent derivations. As more data become available over time, chronic RELs may be added or re-evaluated.
Exposure above a particular chr onic REL m ay or may not lead to the development of adverse health effects. Conversely, there may be i ndividuals exhibiting id iosyncratic responses (unpredictable health effects) at concentrations below the ch ronic RELs. Health effects associated with individual chemicals are pres ented in Appendix D individual summaries of acute, eight-hour, and chronic RELs.

7.2 Exposure Concentratio n Averaging Period
The exposure period of concern in the developm ent of chronic RELs is a full lifetime, which encompasses periods of potentially increased susceptibility to adverse health effects from chemical exposure, particularly during childhood and the later years of life. The chronic REL is intended to be protective for indi viduals exposed continuously over th eir lifetime. Sc ientific data available to assess these effects generally c onsist of discontinuous e xposures over a shorter interval. In such cases, default or chemical-s pecific assumptions are required to estimate concentrations causing comparable effects if e xposures were to be continued over the entire lifetime.

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7.2.1 Effects of Exposure Continuity and Duration

Studies of adverse health effects associated with long-term exposur es of humans or experimental animals generally involve discon tinuous exposures. Commonly encountered exposure scenarios involve exposures of six to eight hours per day for five days per week. OEHHA’s chronic RELs, however, are intended to protect the general public who could be exposed continuously. In practice, discontinuous facility emissions are gene rally adjusted to a continuous daily or annual average. The default approach adopted for the chronic RE Ls presented in this docum ent to account for differences in effects associated with discont inuous and continuous inhalation exposures to substances is an equivalent time-weighted average approach. This is the same approach used in the derivation of U.S. EPA RfCs (U.S. EPA, 199 4a). It is similar to modified Haber’s law approach used for acute and 8-hour RELs in the special case where n = 1. Values of n greater than 1 have not been shown to be applicab le in chronic exposure situations, although toxicokinetic effects such as extensive bio accumulation may require other types of special treatment.
For non-occupational studies, the de fault approach for estim ating an equivalent time-weighted average concentration (C AVG ) from the observed concentration (C OBS ) may be summarized as:

C AVG = C OBS x (H hours per 24 hours) x (D days per 7 days)
For studies of occupationally e xposed hum ans, based on the assu mption that half of the 20 m 3 of air breathed in any 24-hour peri od is breathed while active at wo rk, the default approach to estimating an equivalent inhalation- weighted average concentration (C AVG ) from the observed concentration (C OBS ) is:

C AVG = C OBS x (10 m 3 /day occupational exposure / 20 m 3 /day total exposure)
x (D days per 7 days)

7.2.2 Differences between Lifetime an d Less-than-L ifetime Exposures

Studies of adverse health effect s associated with exposures of hum ans or experimental animals generally involve less-than-lifetime exposures. The OE HHA chronic RELs, however, are intended to protect the general public who coul d be exposed over thei r entire lifetime. In traditional toxicity testing paradigms, studies th at expose experimental animals for at least 12% of the expected lifetime for the test species are considered chronic exposur e studies. RELs based on such chronic animal studies are not adjusted for less-than-lifetime exposures. Similarly using this convention, chronic exposure for humans is c onsidered to be greater than 12% of a lifetime of 70 years. Thus, human exposur es of greater than 8 years ar e considered chronic exposures and are not adjusted eith er in their calculation or application. Although a potential source of uncertainty, this approximation appears reas onable for the majority of chemicals.
There are certain situations, such as in cancer risk assessm ent, where dependence on cumulative dose over long periods up to and including a lifetime (subject to weighting during critical periods

Technical Support Document 89 June, 2008TSD for Noncancer RELs June 2008 early in life) may reasonably be assumed. Mode ls of dose-time cumulation over relatively short timescales have been explored for various acute toxicity endpoints, and are described elsewhere in this document. However, for most situati ons involving chronic noncancer toxicity an explicit description of the time/dose re lationship over longer interval s (including several weeks or months to a full lifetime) is not available. Toxicity studies tend to be conducted for specific periods representing subchronic, chronic and lifetime exposures, but these are seldom directly related to one another, and frequently report di fferent endpoints. Subchr onic exposures are those with duration less than 12% of expected lifetime fo r the test species, except in the case of mice and rats where the U.S. EPA has considered 13 weeks subchronic. Therefore, the default approach to extrapolating from subchronic to chronic exposures used by OEHHA and the U.S. EPA is to use a 1 to 10-fold uncertainty factor, UF S for subchronic exposures.

The UF S to extrapolate from subchronic to chr onic exposures is determined as follows: (1) exposures less than 8% of expect ed lifetim e were given a 10-fold UF (2) exposures f rom 8 to <12% of expected lifetime were given a 3-fold UF, and (3) exposures ≥ 12% of expected lifetim e we re given a 1-fold UF.
Average life spans assumed for humans a nd experim ental animals are presented in Table 7.2.1

.
TABLE 7.2.1. AVERAGE LIFE-SPAN FOR HUMANS VS. EXPERIMENTAL ANIMALS

Species Approximate average Life-span (years) 1 Subchronic exposure duration (weeks) 2 Human 70 ≤ 364 Baboon 55 ≤ 286 Cat 15 ≤ 78 Dog 15 ≤ 78 Guinea pig 6 ≤ 31 Hamster 2.5 ≤ 13 3 Mouse 2 ≤ 13 3 Rabbit 6 ≤ 31 Rat 2 ≤ 13 Rhesus monkey 35 ≤ 182

1 U.S. EPA (1988). 2 Subchronic exposures are usuall y defined as those over less th an 12% of average lifetime (U.S. EPA, 1994a). 3 Special rule adopted by U.S. EPA that exposures of 13 weeks or less are subchronic regardless of the species i nvolved (U.S. EPA, 1994a).
Unlike the extensive exposure concentration-dura tion-effect analyses th at have been conducted for acute lethality data in experim ental animal s, only limited work has been done to compare the differences between acute, s ub-chronic, chronic and lif etime exposure scenarios.

Technical Support Document 90 June, 2008TSD for Noncancer RELs June 2008 Kadry and associates (1995) showed that among a small data set (6 chlorinated chemicals) subchronic NOAEL to chronic NOAEL ratios were le ss than 10. Nessel et al. (1995) reported that for 9 inhalation studies the mean and median subchronic NOAEL to chronic NOAEL ratios were 4.5 and 4.0 respectively (range = 1 to 8) . However, in a study of published animal NOAELs for a larger group of pesticides, Nair and associates (1995) found that 19 of 148 (13%) of the subchronic to chronic NOAEL ratios di ffered by more than 10-fold. The U.S. EPA reported that, based on an analysis of responses to 100 substances, the subchronic to chronic ratios formed a distribution with a median value of 2 and an upper 95 th percentile of 15; the value of 10 represents the 90 th percentile (Swartout, 1997). This su pports the selection of a default maximum value of 10 for the UF S
.
7.3 Human Equivalent Co ncentration (H EC) Procedure for Chronic RELs
As previously noted for the acute and 8 hour RELs, the preferred m ethod of adjustment for interspecies toxicokinetic di fferences when animal studies are used for chronic REL development is the application of a compound- and species-specific toxicokinetic model. However, there will be many case where the data to support such a model ar e not available. If no model-based correction can be developed the default UF H-k = √ 10 would apply. Where suitable parameters are available for the test species ( e.g. for rats and mice), the U.S. EPA HEC procedure (described in Appendi x F) may be used as a partial adjustment for interspecies toxicokinetic differenc es, in which case UF H-k = 2 ( thus the 10-fold ove rall interspecies UF is reduced to 6 if UF H-dhas the default value of √ 10). The modifications of the HEC procedure to account for children may also be us ed to address concerns for human intraspecies variability and to fulfill the mandates of SB 25 to account for potentially greater vu lnerability of children when setting health standards.

7.4 LOAEL to NOAEL Ex trapolation

There are some instances where the data are not available to identify a NOAEL for a chronic exposure to a chemical, and are not suitable for a benchmark concentration approach. In these cases, we are left with a LOAEL upon which to base a chronic REL. It should be noted that use of a LOAEL is a last resort, as it is frequently not clear how close one is to the NOAEL for a particular effect. In developing chronic R ELs, OEHHA will use a default value for the LOAEL to NOAEL UF of 10. There may be cases where a smaller value can be used where the data indicate that the LOAEL is fairly close to an expected NOAEL. For acute effects, OEHHA has used the severity of effect concept developed by U.S. EPA as an indicator of proximity to a NOAEL (see Section 5.5 ). However, this does not work well for chronic effects, where there are disparate types of response, which are difficu lt to com pare. Many chronic effects could reasonably be considered “serious” even if they occurred rarely or to a low degree, and the concept of reversibility (an importa nt criterion of severity for acute effects) is ambiguous in the context of continuous exposures ov er extended periods up to and in cluding a complete lifetime. Therefore, for chronic effects, indicators of the proximity or otherwise of a LOAEL to the presumed NOAEL will be described on a case-by -case basis in the toxicity summary of a specified chemical. OEHHA may use an intermedia te uncertainty factor where an effect was observed in ≤ 30% of subjects, since for many endpoint s a low response rate suggests that the exposure is likely to be relatively nearer to the NOAEL. Similar arguments may be applied for

Technical Support Document 91 June, 2008TSD for Noncancer RELs June 2008 continuous endpoints, where low intensity of res ponse and/or low frequency of responses above control values suggest proximity to a NOAEL.

7.5 Hyperplas ia
The use of hyperplasia as a toxicological endpoi nt for setting chronic RELs should consider whether the hyperplasia m ay progress to dysplas ia and neoplasia. In a chronic study, if hyperplasia was the most sensitive endpoint for th at chemical, it was used as an endpoint for REL development. Hyperplasia can be seen as a normal response (e.g., to hormones), and is also seen in response to a number of sensory irri tants which are not carcinogens. When hyperplasia was used as the toxicological endpoint and as a mild effect, the histological grade was low (e.g., one on a scale of one to five) and there was no increase in organ weight noted.

7.6 Pre-Existin g Chronic Exposure Guidelines
Chronic exposure levels have been derived us ing several different approaches, but inhalation exposure values estim ated using a consistent basis to protect the general p ublic are only available for certain chemicals. The U.S. EPA RfCs, now published for 72 chemicals, are a notable example. Other values designed for the protectio n of the general public, such as the U.S. EPA reference doses (RfDs), are available for more ch emicals but are intended primarily to deal with non-inhalation exposures to chemicals and are us ually based on toxicity data obtained following oral exposure. It is likely th at the oral and dermal routes w ould underestimate the health effects of inhalation exposure, unless the he alth effect is an identifiable systemic effect and not affected by first-pass metabolism. If th e effect is systemic, then appropriate adjustments for absorption can be made.

7.6.1 U.S. EP A Reference Concentrations
The U.S. EPA developed an inhalation referen ce concentration (RfC) me thod (Jarabek et al., 1989; U.S. EPA, 1994a; 2002). The inhalation RfC considers toxic effects for both the respiratory system (portal-of-entry) and for eff ects peripheral to the resp iratory system (extrarespiratory effects). The RfC is comparable to earlier Acceptable Daily Intake (ADI) and RfD methods but addresses inhalation specific issues such as respiratory dynamics and delivered doses by inhalation. Dosimetry models are used to extrapolate the internal dose metric across species and to estimate the human equivalent conc entration (HEC), as de scribed in Appendix F.

7.6.2 U.S. EPA Reference Doses
The U.S. EPA developed an or al reference dose (RfD) concep t in 1987 (Barnes and Dourson, 1988). This provides a protocol for study selection, identifying NOAE Ls, applying UFs, and assessing the weight of evidence. As of Sept ember 2005, U.S. EPA RfDs were available for more than 350 substances (U.S. EPA, 2007a). The major limitation of these values for application to inhalation REL development is that they are al most entirely based on studies of exposures by routes other than inhalation. However, they have utility for substances treated as multi-pathway chemicals in the Air Toxics Hot Spots Program’s risk assessments. Additionally, route-to-route extrapolation is sometimes possible, depending on the compound’s toxicity and pharmacokinetics.

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7.6.3 Occupational Threshold Limit Values
Occupational exposure limits have been used to derive chem ical expos ure guidelines for the general public (NATICH and McCullough, 1991; Robinson and Paxman, 1992). As of May, 2005, more than 600 American Conference of G overnmental Industrial Hygienists (ACGIH) Threshold Limit Values (TLVs) (ACGIH, 2005) a nd National Institute for Occupational Safety and Health (NIOSH) Permissible Exposure Li mits (PELs) (NIOSH, 2005) were available. The California Occupational Safety and Health Administration also has approximately 600 occupational PELs. However, these values lack a consistent basis, are not designed for or recommended for protection of the general public , and in many cases may not prevent adverse health effects among workers (R oach and Rappaport, 1990). Occ upational exposure guidelines, which are available for hundreds of substances, have been used in many states to derive inhalation exposure guidelines for the general public. These values, however, have an inconsistent basis, which often included risk ma nagement and feasibility considerations specific to industrial facilities, in addi tion to health-based criteria, and have not always incorporated recently available data. Most importantly, oc cupational exposure guidelines are designed to protect healthy adult workers, and do not allo w for possibly more sensitive members of the general population such as chil dren and the elderly, or those with genetically predetermined sensitivities. Thus, OEHHA does not use occupa tional guidelines for chronic RELs, which are intended to protect the general public.

7.6.4 California Ambient Air Quality Standards
California Ambient Air Quality Standards (CAAQS ) are available for criteria air pollutants (CAPCOA, 1993). W here defined according to a basis appropriate to lifetime exposures, the CAAQS was adopted as the chronic inhalation REL.

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## References

ACGIH. (2005). Documentation of the Threshold Limit Values and Biological Exposure Indices Annual Reports of the C ommittees on TLVs ® and BEIs ® for Year 2005 Publication #0106A

. Cincinnati (OH): American Conference of Governmental Industrial Hygienists, Inc.
ACGIH. (2006). Documentation of the Threshold Limit Values and Biological Exposure Indices Annual Reports of the C ommittees on TLVs ® and BEIs ® for Year 2006 Publication #0106

. Cincinnati (OH): American Conference of Governmental Industrial Hygienists, Inc.
Agunod M, Yamaguchi N, Lopez R, Luhby AL and Glass GB (1969). Correlative study of hydrochloric acid, pepsin, and intrin sic factor secretion in newbor ns and infants. Am J Dig Dis 14(6): 400-414.
AIHA. (2006). Public Exposure Guidelines . American Industrial Hygiene Association. http://archive.orr.noaa.g ov/cam eo/locs/expguide.html

. Alarie Y (1966). Irritating prope rties of airborne m aterials to the upper respiratory tract. Arch Environ Health 13(4): 433-49.
Alcorn J and McNamara PJ (2003). Pharmac okinetics in the newborn. Adv Drug Deliv Rev 55(5): 667-686.
Aldridge JE, Seidler FJ and Slotkin TA (2004). Developm ental exposure to chlorpyrifos elicits sex-selective alterations of serotonergic synaptic functi on in adulthood: Critical periods and regional selectivity for e ffects on the serotonin transporter, receptor subtypes, and cell signaling. Environ Health Pers pect 112(2): 148-155.
Alexeeff GV, Broadwin R, Liaw J and Dawson SV (2002). Characterization of the L OAEL-toNOAEL uncertainty factor for mild adverse e ffects from acute inha lation exposures. Regul Toxicol Pharmacol 36(1): 96-105.
Alexeeff GV, Deng KK, Broadwin RL and Salm on AG (2006). Benchm ark dose evaluation for human irritation [Abstract # 901] . The Toxicologist 90(1): 183.
Alexeeff GV, Fowles JR, Hill M and Dodge D (1997) . Stoch astic evaluation of acute inhalation thresholds from reported LOAELs [Abstract #851]. The Toxico logist 36(1 Part 2): 167.
Alexeeff GV and Lewis DC. (1989b). Factors In fluencing Quantitative Risk Analysis of Noncancer Health Effects From Air Pollutants . Vol. 89-91.3: 1-14. Pi ttsburgh (PA): Air & Waste Management Association.
Alexeeff GV, Lewis DC and Lipsett MJ (1992). Use of toxicity inform ation in risk assessment for accidental release of toxic ga ses. J Hazard Mater 29(3): 387-403.
Alexeeff GV, Lewis DC and Ragle NL (1993). Estim ation of potential healtheffects from acute exposure to hydrogen fluoride using a "benchma rk dose" approach. Risk Anal 13(1): 63-69.

Technical Support Document 94 June, 2008TSD for Noncancer RELs June 2008 Alexeeff GV, Lipsett MJ and Kizer KW (1989a). Problems associated with the use of immediately dangerous to life a nd health (IDLH) values for estim ating the hazard of accidental chemical releases. Am Ind Hyg Assoc J 50(11): 598-605.
Almstrup K, Fernandez MF, Petersen JH, Olea N, Skakkebaek NE and Leffers H (2002). Dual effects of phytoestrogens result in u-shaped dose-response curves. Environ Health Perspect 110(8): 743-748.
Amateau SK and McCarthy MM (2004). Induc tion of PGE2 by estradiol m ediates developmental masculinization of sex behavior. Nat Neurosci 7(6): 643-650.
American Thoracic Society (ATS) (2000a). What c onstitutes an adverse h ealth effect of air pollution. Am J Respir Crit Ca re Med 161(2 Pt 1): 665-673.
Anglen DM. (1981). Sensory Response of Human S ubjects to Chlorine in Air. Dissertation. Ann Arbor (MI ): University of Michigan.
Anjilvel S and Asgharian B (1995). A multiple-path m odel of particle depos ition in the rat lung. Fundam Appl Toxicol 28(1): 41-50.
Arant Jr. BS (1978). Developmental patterns of renal functional m aturation compared in the human neonate. J Pediatr 92(5): 705-712.
Arcus A, Broadwin R, Lam R and Vork K. (1995). A Database of Indoor Air Volatile Organic Compounds and Selected Combustion Products: Construction and Development (draft). Report to Indoor Air Quality and Personal Exposure Assessment Section . Sacramento (CA): Air Resources Board, California Environmental Protection Agency.
Augustinsson KB and Barr M (1963). Age variation in plasma aryl esterase activity in children. Clin Chim Acta 8: 568-573.
Autrup H (2000). Genetic polymorphisms in human xenobiotica metabolizing enzymes as susceptibility factors in toxic response. Mutat Res 464(1): 65-76.
Avery GB, Randolph JG and Weaver T (1966). Gastric acidity in the first day of life. Pediatrics 37(6): 1005-1007.

Ballatori N and Clarkson TW (1982). Developmental changes in the biliary excretion of

m ethylmercury and glutathione. Science 216(4541): 61-63.
Barnes DG, Daston GP, Evans JS, Jarabek AM, Kavlock RJ, Ki mmel CA, Park C and Spitzer HL (1995). Benchmark Dose Work shop: Criteria for use of a benchmark dose to estimate a reference dose. Regul Toxicol Pharmacol 21(2): 296-306.
Barnes DG and Dourson M (1988). Reference dose (RfD): Description and use in health risk

assessm ents. Regul Toxicol Pharmacol 8(4): 471-486.

Technical Support Document 95 June, 2008TSD for Noncancer RELs June 2008 Barrow C, Buckley L, James R, Steinhagen W an d Chang J (1986). Sensory Irritation: Studies on correlation to pathology, structure-activity, tolerance-development, and prediction of species differences to nasal injury. Chapter 7. In: Toxicology of the Nasal Passages. Barrow C. Hemisphere. Washington (DC) & New York (NY): 101-122.
Barton JC and Huster WJ (1987). Seasonal changes in lead absorption in laboratory rats. Environ Health Perspect 73: 209-214.
Belay ED, Bresee JS, Holman RC, Khan AS, Sh ahriari A and Schonberger LB (1999). Reye' s syndrome in the United States from 1981 through 1997. N Engl J Med 340(18): 1377-1382.
Benignus VA, Boyes WK and Bushnell PJ (1998). A dosimetric analysis of behavioral effects of acute toluene exposure in rats and humans. Toxicol Sci 43(2): 186-95.
Besunder JB, Reed MD and Blumer JL (1988). Pr incip les of drug biodisposition in the neonate. A critical evaluation of the pharmacokine tic-pharmacodynamic interface (Part I). Clin Pharmacokinet 14(4): 189-216.
Bigwood EJ (1973). The acceptable daily intake of food addi tives. CRC Crit Rev Toxicol 2(1): 41-93.
Bos PM, Zwart A, Reuzel PG and Bragt PC (1991). Evaluation of the sensory irritation test for the assessment of occupational health risk. Crit Rev Toxicol 21(6): 423-450.
Bradford Hill AB (1971). Chapter XXIV: Statistical Eviden ce and Inference. In: Principles of Medical Statistics. Oxford Universi ty Press. Oxford (UK): 309-323.
Brodersen R, Friis-Hansen B and Stern L (1983). Drug-induced displacement of bilirubin from album in in the newborn. Dev Pharmacol Ther 6(4): 217-229.
Brown JP (2001). Physiological and Anatomical Param eters for Infants and Children's PBPK Modeling. Children's Environmental Health--De veloping a Risk Assessment Framework.Office of Environmental Health Hazar d Assessment, California Environmental Protection Agency. Monterey (CA), April.
Brown JP, Collins JF, Salmon AG, Marty MA a nd Alexeeff GV (2006). Use of benchm ark dose methodology on human non-cancer data to develop pr otective criteria for child exposures to arsenic [Abstract # 2185]. The Toxicologist 90(1): 448.
Brown JS, Wilson WE and Grant LD (2005). Dosime tric co mparisons of particle deposition and retention in rats and humans. Inhal Toxicol 17(7-8): 355-385.
Brown NA and Fabro S (1983). The value of animal teratogenicity testin g for predicting hum an risk. Clin Obstet Gynecol 26(2): 467-77.
Bryant B and Silver W (2000). Chemesthes is: T he common chemical sense. In: The Neurobiology of Taste and Smell (2nd Edition). Finger T., Silver W. and Restrepo D. WileyLiss. NY: 73-100.

Technical Support Document 96 June, 2008TSD for Noncancer RELs June 2008 Buehler BA, Rao V and Finnell RH (1994). Bioc hemical and molecular teratology of fetal hydantoin syndrome. Neurol Clin 12(4): 741-748.
Bushnell PJ, Boyes WK, Shafer TJ, Bale AS and Benignus VA (2007). Approaches to extrapolating anim al toxicity data on organic solvents to public healt h. Neurotoxicology 28(2): 221-6.
Calabrese EJ (1983). Principles of Animal Ex trapolation. Environm ent Science and Technology. New York: Wiley.
Canalle R, Burim RV, Tone LG and Takahashi CS (2004). Genetic polym orphisms and susceptibility to childhood acute lymphoblastic leukemia. Envir on Mol Mutagen 43(2): 100-109.
CAPCOA. (1993). The Air Toxics Hot Spots Program R evised 1992 Risk Assessment Guidelines

. Cam eron Park (CA): California Air Pollution Control Officers’ Association Toxics Committee
CARB. (1990). Proposed Identification of Vinyl Chlo ride as a Toxic Air Contaminant. Technical Support Document. Part C . California Air Resources Board.
Carlisle J and Dowling K (2006). Child-specifi c health guidance for lead. Abstract #2185, p 448. The Toxicologist.
Chen YC, Yu ML, Rogan WJ, Gladen BC and Hs u CC (1994). A 6-year follow-up of behavior and activity disorders in the Taiwan Yu-che ng children. Am J Public Health 84(3): 415-21.
Chhabra RS, Huff JE, Schwetz BS and Selkirk J (1990). An overview of prechronic and chronic toxicity/carcinogenicity experim e ntal study designs and criteria used by the National Toxicology Program. Environ Health Perspect 86: 313-321.
Chiron C, Raynaud C, Maziere B, Zilbovicius M, Laflamme L, Masure MC, Dulac O, Bourguignon M and Syrota A (1992). Changes in regional cerebral bl ood flow during brain

m aturation in children and adol escents. J Nucl Med 33(5): 696-703.
Chizhikov VA (1973). [Effect of harmful substan ces on anim als with weakened health under chronic feeding conditions][Russian]. Gig Sanit 38(7): 7-12.
Clewell HJ, Gentry PR, Covington TR, Sarangapani R and Teeguarden JG (2004). Evaluation of the potential im pact of age- and gender-specifi c pharmacokinetic differences on tissue dosimetry. Toxicol Sci 79(2): 381-393.
Cole TB, Jampsa RL, Walter BJ, Arndt TL, Richte r RJ, Shih DM, Tward A, Lusis AJ, Jack RM, Costa LG and Furlong CE (2003). Expre ssion of human paraoxonase (PON1) during development. Pharmacogenetics 13(6): 357-364.
Collins JF, Alexeeff GV, Lewis DC, Dodge DE, Marty M A, Parker TR, Budroe JD, Lam RH, Lipsett MJ, Fowles JR and Da s R (2004). Development of acute inhalation reference exposure levels (RELs) to protect the public from predictabl e excursions of airborne toxicants. J Appl Toxicol 24(2): 155-166.

Technical Support Document 97 June, 2008TSD for Noncancer RELs June 2008
Collins JF, Salmon AG, Brown JP, Lewis DC, Dodge DE, Marty MA and Alexeeff GV (2003). Use of benchmark concentration methodology in risk assessment for air toxics [Abstract]. The Toxicologist 72: 142.
Collins JF, Salmon AG, Brown JP, Marty MA and Alexeeff GV (2005). Developm ent of a chronic inhalation reference level for respirable crystalline silica. Regul Toxicol Pharmacol 43(3): 292-300.
Cometto-Muniz JE, Cain WS and Hudnell HK (1997) . Agonistic sensory e ffects of airborne chem icals in mixtures: Odor, nasal pungency, and eye irritati on. Percept Psychophys 59(5): 665- 674.
Conceicao GM, Miraglia SG, Kishi HS, Saldiv a PH and Singer JM (2001). Air pollution and child m ortality: A time-series study in Sao Paulo, Brazil. Environ Health Perspect 109 (Suppl 3): 347-350.
Costa LG, Richter RJ, Li WF, Cole T, Gui zzetti M and Furlo ng CE (2003). Paraoxonase (PON 1) as a biomarker of susceptibility for or ganophosphate toxicity. Biomarkers 8(1): 1-12.
Costa LG, Vitalone A, Cole TB and Furl ong CE (2005). Modulation of paraoxonase (PON1) activity. Biochem Pharmacol 69(4): 541-550.
Cresteil T (1998). Onset of xenobiot ic m etabolism in children: Toxi cological implications. Food Addit Contam 15 (Suppl): 45-51.
Crofton KM, Craft ES, Hedge JM, Gennings C, Si mmons J E, Carchman RA, Carter Jr. WH and DeVito MJ (2005). Thyroid-hormone-disrupti ng chemicals: Evidence for dose-dependent additivity or synergism. Envir on Health Perspect 113(11): 1549-1554.
Crump KS (1984). A new method for determining a llowable daily intakes. Funda m Appl Toxicol 4(5): 854-871.
Crump KS (1995). Calculation of benchmark dose s from continuous data. Risk Anal 15: 78-89.
Crump KS (2002). Critical issues in benchmar k calculations from continuous data. Crit Rev Toxicol 32(3): 133-153.
Csanady GA, Kessler W, Hoffmann HD and Filser JG (2003). A t oxicokinetic m odel for styrene and its metabolite styrene-7,8-oxide in mouse, rat and human with special emphasis on the lung. Toxicol Lett 138(1-2): 75-102.
Daniels MJ, Dominici F, Samet JM and Zeger SL (2000). Estim ating particulate matter-mortality dose-response curves and threshol d levels: an analysis of daily time-series for the 20 largest US cities. Am J Epidemiol 152(5): 397-406.
Darras VM (2008). Endocrine disrupting polyhalo genated organic pollutants interfere with thyroid hormone signalling in th e developing brain. Cerebellum

.

Technical Support Document 98 June, 2008TSD for Noncancer RELs June 2008
DeVito MJ, Menache MG, Diliberto JJ, Ross DG and Birnbaum LS (2000). Dose-response relationships for induction of CYP1A1 and CYP1A2 enzyme activity in liver, lung, and skin in female mice following subchronic exposure to polychlorinated biphenyls. Toxicol Appl Pharmacol 167(3): 157-172.
Dorne JL and Renwick AG (2005a). The refineme nt of unc ertainty/saf ety factors in risk assessment by the incorporation of data on toxi cokinetic variability in humans. Toxicol Sci 86(1): 20-26.
Dourson ML (1986). New approaches in the deri vation of acceptab le daily intake (ADI). Comm Toxicol 1: 35-48.
Dourson ML, Felter SP and Robinson D (1996). Evol ution of science-based uncertainty factors in noncancer risk assessment. Regul Toxicol Pharmacol 24(2 Pt 1): 108-120.
Dourson ML and Stara JF (1983) . Regulatory history and experi mental support of uncertainty (safety) factors. Regul T oxicol Pharmacol 3(3): 224-238.
Ecobichon DJ and Stephens DS (1973). Perinatal development of human blood esterases. Clin Pharm acol Ther 14(1): 41-47.
Eichelbaum M, Kroemer HK and Mikus G (1992). Genetically determ ined differences in drug metabolism as a risk factor in drug toxicity. Toxicol Lett 64-65 (Spec No): 115-122.
El-Masri HA, Constan AA, Ramsdell HS, and Yang RSH ( 1996a). Physiologically based pharmacodynamic modeling of an interaction th reshold between trichloroethylene and 1,1- dichloroethylene in Fischer 344 rats . Toxicol Appl Pharmacol 141: 124-132.
El-Masri HA, Tessari JD, and Yang RSH (1996b). E xploration of an inter action threshold for the joint toxicity of trichloroethyl ene and 1,1-dichloroethy lene:utilization of a PBPK model. Arch Toxicol 70: 527-539.
ElDesoky ES (2007). Pharmacokinetic-pharmacodynami c crisis in the elderly. Am J Ther 14(5): 488-98.
Eluma FO, Sucheston ME, Hayes TG and Paul son RB (1984). Teratogenic effects of dosage levels and tim e of administration of carbamazepin e, sodium valproate, and diphenylhydantoin on craniofacial development in the CD-1 mouse fetus. J Craniofac Genet Dev Biol 4(3): 191-210.
Evelo CT, Oostendorp JG, ten Berge WF and Borm PJ (1993). Physiologically based toxicokinetic modeling of 1,3-butadiene lung me tabolism in mice becomes more important at low doses. Environ Health Perspect 101(6): 496-502.
Fanucchi MV and Plopper CG (1997). Pulmonary Developmental Responses to Toxicants. In: Com prehensive Toxicology Roth R. Pergamon. New York: Vol. 8: 203-220.

Technical Support Document 99 June, 2008TSD for Noncancer RELs June 2008 Fanucchi MV, Plopper CG, Evans MJ, Hyde DM, Van Winkle LS, Gershwin LJ and Schelegle ES (2006). Cyclic exposure to ozone alters distal airway development in infant rhesus monkeys. Am J Physiol Lung Cell Mol Physiol 291(4): L644-L650.
Filipsson AF, Sand S, Nilsson J and Victorin K (2003). The benchm ark dose method--review of available models, and recommendations for appli cation in health risk assessment. Crit Rev Toxicol 33(5): 505-542.
Foradori AC, Bertinchamps A, Gulibon JM and Co tzias GC (1967). The discrim ination between magnesium and manganese by serum pr oteins. J Gen Physiol 50(9): 2255-2266.
Fowles JR, Alexeeff GV and Dodge D (1999). The use of benchmark dose methodology with acute inhalation lethality data. Re gul Toxicol Pharm acol 29(3): 262-278.
Frederick CB, Bush ML, Lomax LG, Black KA, Finch L, Kimbell JS, Morgan KT, Subram aniam RP, Morris JB and Ultman JS (1998) . Application of a hybrid computational fluid dynamics and physiologically based inhalation model for interspecies dosimetry extrapolation of acidic vapors in the upper airways. Toxicol Appl Pharmacol 152(1): 211-231.
Friis-Hansen B (1961). Body water compartments in children: Changes during grow th and related changes in body composition. Pediatrics 28: 169-181.
Friis-Hansen B (1971). Body composition during gr owth. In vivo measurements and biochemical data correlated to differential anatomical growth. Pediatrics 47(1 Suppl 2): 264-274.
Galizia A and Kinney PL (1999). Long-term residen ce in areas of high ozone: Associations with respiratory health in a nationw ide sample of nonsm oking young adu lts. Environ Health Perspect 107(8): 675-679.
Gauderman WJ, Avol E, Gilliland F, Vora H, T hom as D, Berhane K, McConnell R, Kuenzli N, Lurmann F, Rappaport E, Margolis H, Bates D a nd Peters J (2004). The effect of air pollution on lung development from 10 to 18 years of age. N Engl J Med 351(11): 1057-1067.
Gauderman WJ, Avol E, Lurmann F, Kuenzli N, Gilliland F, Peters J and McConnell R (2005). Childhood asthm a and exposure to traffic and nitrogen dioxide. Epidemiology 16(6): 737-743.
Gaylor D, Ryan L, Krewski D and Zhu Y (1998) . Procedures for calculating benchm ark doses for health risk assessment. Regul Toxicol Pharmacol 28(2): 150-164.
Gaylor DW (1988). Applicability of cancer risk assessm ent techni ques to other toxic effects. Toxicol Ind Health 4(4): 453-459.
Gaylor DW (1992). Incidence of developmental de fects at the no observed adverse effect level (NOAEL). Regul Toxicol Ph arm acol 15(2 Pt 1): 151-160.
Gebremichael A, Chang AM, Buckpitt AR, Plopper CG and Pinkerton KE (1995). Postnatal developm ent of cytochrome P4501A1 and 2B1 in ra t lung and liver: Effect of aged and diluted sidestream cigarette smoke. T oxicol Appl Pharmacol 135(2): 246-253.

Technical Support Document 100 June, 2008TSD for Noncancer RELs June 2008 Geller AM and Zenick H (2005). Aging and the environment: a research framework. Environ Health Perspect 113(9): 1257-62.
Gibbons RA, Dixon SN, Hallis K, Russell AM , S ansom BF and Symonds HW (1976). Manganese metabolism in cows and goa ts. Biochim Biophys Acta 444(1): 1-10.
Gift JS, Webb CK and Jarabek AM (1993). Suitability of LOAEL-to-NOAEL 10-fol d uncertainty factor for health assessments of inhaled toxicants [Abstract # 475]. The Toxicologist 13: 140.
Gillis CA, Keenan RE, Carlson-Lynch HL and Pr ice PS (1997 ). Characterization of the interindividual (UFH) factors: Alternative models and approaches [Abstract #1053]. The Toxicologist 36: 207.
Ginsberg G (2000). Xenobiotic Metabolism and Chemical Fate From Early Childhood Onward. Children' s Environmental Health Symposium.Office of Environmental Health Hazard Assessment, California Environmental Prot ection Agency. Oakland (CA), May 2, 2000.
Ginsberg G, Hattis D, Russ A and Sonawane B (2004b). Physiologically based pharm acokinetic (PBPK) modeling of caffeine and theophylline in neonates and adults: Imp lications for assessing children's risks from environmental agents. J Toxicol Environ Health A 67(4): 297-329.
Ginsberg G, Hattis D, Russ A and Sonawane B (2005). Pharm acokinetic and pharmacodynamic factors that can affect sensitivity to neurotoxic sequelae in elderly individuals. Environ Health Perspect 113(9): 1243-9.
Ginsberg G, Hattis D, Sonawane B, Russ A, Banati P, Kozlak M, Smolenski S and Goble R (2002). Evaluation of child/adult pharm acokinetic di fferences from a database derived from the therapeutic drug literature . Toxicol Sci 66(2): 185-200.
Ginsberg G, Slikker Jr. W, Bruckner J and S onawane B (2004c). Incorporating children' s toxicokinetics into a risk framework. Environ Health Perspect 112(2): 272-283.
Goldstein BD (1983). Toxic substances in the atmo spheric environm ent. A critical review. J Air Pollut Control Assoc 33(5): 454-467.
Grandjean P (1992). Individual susceptibility to toxicity. Toxicol Le tt 64-65 (Spec No): 43-51.
Guberman AH, Besag FM, Brodie MJ, Dooley JM, Duchowny MS, Pellock JM, R ichens A, Stern RS and Trevathan E (1999). Lamotrigine-associated rash: ri sk/benefit considerations in adults and children. Epilepsia 40(7): 985-991.
Guignard JP, Torrado A, Da Cunha O and Gautier E (1975). Glom erular filtra tion rate in the first three weeks of life. J Pediatr 87(2): 268-272.
Ha EH, Hong YC, Lee BE, Woo BH, Schwartz J a nd Christiani DC (2001). Is air pollution a risk factor for low birth weight inSeoul? Epidem iology 12(6): 643-648.

Technical Support Document 101 June, 2008TSD for Noncancer RELs June 2008 Hackney JD and Linn WS (1983). Controlled cl inical studies of ai r pollutant exposure: Evaluating scientific information in relation to ai r quality standards. Environ Health Perspect 52: 187-191.
Haddad S, Beliveau M, Tardif R and Krishnan K (2001). A PBPK modeling-based approach to account for interactions in the health risk asse ssment of chemical mixtures. Toxicol Sci 63(1): 125-131.
Hakkola J, Tanaka E and Pel konen O (1998). Developm ental e xpression of cytochrome P450 enzymes in human liver. Pharmacol Toxicol 82(5): 209-217.
Hanna LM, Lou SR, Su S and Jarabek AM (2001) . Mass transport analys is: Inhalation RfC

m ethods framework for interspecies dosimet ric adjustment. Inhal Toxicol 13(5): 437-463.
Harada M (1995). Minamata disease: Me thylm ercury poisoning in Japan caused by environmental pollution. Crit Rev Toxicol 25(1): 1-24.
Harding R, Pinkerton K and Plopper CG (2004). The Lung: De velopment, Aging and the Environm ent. London (UK); San Diego (CA): Elsevier Academic Press.
Hartung R (1987). Dose-Response Relationships. In: Toxic S ubstances and Human Risk. Tardiff R. G. and Rodricks J. V. Plenum Press. New York: 29-46.
Hattis D (1996a). Variability in susceptibility--how big, how often, for what responses to what agents? Environ Toxicol Pharmacol 2: 135-145.
Hattis D (1996b). Human interindividual variability in su sceptibility to toxic effects: From annoying detail to a central determin ant of risk. Toxicology 111(1-3): 5-14.
Hattis D, Banati P and Goble R (1999). Distributi ons of individual susceptibility among humans for toxic effects. How much protection does the traditional tenfold fact or provide for what fraction of which kinds of chemicals and effects? Ann N Y Acad Sci 895: 286-316.
Hattis D, Erdreich L and Ballew M (1987). Huma n variability in sus ceptibility to toxic chemicals--a preliminary analysis of pharmac okinetic data from normal volunteers. Risk Anal 7(4): 415-426.
Hattis D, Ginsberg G, Sonawane B, Smolenski S, Russ A, Kozlak M and Goble R (2003). Differences in pharm acokinetics between children and adults--II. Children's variability in drug elimination half-lives and in some parameters needed for physiologically-based pharmacokinetic modeling. Risk Anal 23(1): 117-142.
Heath LM, Soole KL, McLaughlin ML, McEwan GT and Edwards JW (2003). Toxicity of environm ental lead and the influence of intest inal absorption in children. Rev Environ Health 18(4): 231-250.

Technical Support Document 102 June, 2008TSD for Noncancer RELs June 2008 Herngren L, Ehrnebo M and Bore us LO (1983). Drug binding to plasma proteins during human pregnancy and in the perinatal period. Studies on cloxacillin and alprenolol. Dev Pharmacol Ther 6(2): 110-124.
Hines RN and McCarver DG (2002). The ontogeny of hum an drug-metabolizing enzymes: Phase I oxidative enzymes. J Pharmacol Exp Ther 300(2): 355-360.
Hnizdo E, Murray J, Sluis-Cremer GK and Thomas RG (1993). Correlati on between radiological and pathological diagnosis of silicosis: An autopsy population based study. Am J Ind Med 24(4): 427-445.
Hook JB and Hewitt WR (1977). Development of m echanisms for drug excretion. Am J Med 62(4): 497-506.
Horstman D, Roger LJ, Kehrl H and Hazucha M (1986). Airway sensitivity of asthmatics to sulfur dioxide. Toxicol I nd Health 2(3): 289-298.
Howdeshell KL, Furr J, Lambright CR, Rider CV, W ilson VS and Gray LE, Jr. (2007). Cumulative effects of dibutyl phtha late and diethylhexyl phthalat e on male rat reproductive tract development: altered fetal steroid horm ones and genes. Toxicol Sci 99(1): 190-202.
IARC. (2006). IARC Monographs on the Evaluation of Carcinogenic Risks to Humans

. Pream ble. International Agency for Research on Cancer http://monographs.iarc.fr/ENG/Preamble/index.php

. ICRP (1994). Human Respiratory Tract Model f or Radiological Prot ection. Inte rnational Commission on Radiological Prot ection. Publication 66 Annals of the ICRP. Tarrytown (NY): Elsevier Science Inc. 24(1-3).
Ikeda M (1988). Multiple exposure to chem icals. Regul Toxicol Pharm acol 8(4): 414-421. IRDC. (1985). Three Acute Inhalation Toxicity Studies of Arsine on Rats (Final Report) Report No. 533-001, 533-002, and 533-003. Mattawan (MI): International Research & Developm ent Corporation.
Islam MS and Schlipkoter HW (1989). Reversible fraction of airway resistance in healthy children of areas with different levels of at m ospheric pollutants. Exp Pathol 37(1-4): 23-26.
Jacobson JL, Jacobson SW and Humphrey HE (1990) . Effects of exposure to PCBs and related

com pounds on growth and activity in ch ildren. Neurotoxicol Teratol 12(4): 319-26.
Jarabek AM, Asgharian B and Miller FJ (2005) . Dosim etric adjustments for interspecies extrapolation of inhaled poorly soluble par ticles (PSP). Inhal Toxi col 17(7-8): 317-334.
Jarnberg J and Johanson G (1999). Physiologi cally based m odeling of 1,2,4-trimethylbenzene inhalation toxicokinetic s. Toxicol Appl Ph armacol 155(3): 203-214.

Technical Support Document 103 June, 2008TSD for Noncancer RELs June 2008 Jiang X, Buckley L and Morgan K (1983). Pathology of toxic responses to the RD50 concentration of chlorine gas in the nasal pass ages of rats and mice. Toxicol Appl Pharmacol 71(2): 225-236.
Jonker D, Woutersen RA, van Bladeren PJ, Til HP and Feron VJ (1990). 4-Week oral toxicity study of a com bination of eight ch emicals in rats: Comparison with the toxicity of the individual compounds. Food Chem Toxicol 28(9): 623-631.
Kadry AM, Khodair AJ, Skowronski GA and Ab del-Rahm an MS (1995). Evaluation of the current method for extrapolating subchronic and chronic test resu lts for estimation of lifetime exposure levels [Abstract #180] . The Toxicologist 15(1): 33.
Kearns GL, Abdel-Rahman SM, Alander SW, Blow ey DL, Leeder JS and Kauffma n RE (2003). Developmental pharmacology--Drug disposition, ac tion, and therapy in in fants and children. N Engl J Med 349(12): 1157-1167.
Khodair AJ, Kadry AM, Skowronski GA and Abde l-Rahm an MS (1995). Comparison of animal and human data to estimate the no adverse eff ect level (NOAEL) in hum ans [Abstract #179]. The Toxicologist 15(1): 33.
Klaassen CD (1972). Immaturity of the newborn rat' s hepatic excretory function for ouabain. J Pharmacol Exp Ther 183(3): 520-526.
Klaassen CD (1973). Comparison of the toxicity of che micals in newborn rats to bile ductligated and sham-operated rats and mice. Toxicol Appl Pharmacol 24(1): 37-44.
Krasovskii GN (1976). Extrapolation of experiment al data from animals to man. Environ Health Perspect 13: 51-58.
Kristiansen U, Hansen L, Nielsen GD and Ho lst E (1986). Sensory irritation and pulmonary irritation of cum ene and n-propa nol: Mechanisms of receptor activ ation and desensitization. Acta Pharmacol Toxicol (Copenh) 59(1): 60-72.
Kunzli N, Lurmann F, Segal M, Ngo L, Balmes J and Tager IB (1997). Association between lifetim e ambient ozone exposure and pulmonary f unction in college freshmen--results of a pilot study. Environ Res 72(1): 8-23.
Kuwabara Y, Alexeeff G, Broadwin R and Salmon A (2006). Evaluation of the RD 50 for determining acceptable levels of exposure to ai rborne sensory irritants. [Abstract #882]. The Toxicologist 90(1): 179.
Lanphear BP, Hornung R, Khoury J, Yolton K, Baghur st P, Bellinger DC, Canfield RL, Dietrich KN, Bornschein R, Greene T, Rothenberg SJ, Needlem an HL, Schnaas L, Wasserman G, Graziano J and Roberts R (2005) . Low-level environmental l ead exposure and children's intellectual function: an intern ational pooled analysis. Enviro n Health Perspect 113(7): 894-9.
Lehman AJ and Fitzhugh OG (1954). 100-Fold ma rgin of safety. Assoc Food Drug Off USQ Bull 18: 33-35.

Technical Support Document 104 June, 2008TSD for Noncancer RELs June 2008 Lehmann KP, Phillips S, Sar M, Foster PM and Ga ido KW (2004). Dose-dependent alterations in gene expression and testosterone sy nthesis in the fetal te stes of male rats exposed to di (n-butyl) phthalate. Toxicol Sci 81(1): 60-68.
Leisenring W and Ryan L (1992). St atistical properties of the NOAEL. Regul Toxicol Pharm acol 15(2 Pt 1): 161-171.
Levy G, Khanna NN, Soda DM, Tsuzuki O a nd Stern L (1975). Pharm acokinetics of acetaminophen in the human neonate: Formation of acetaminophen glucuronide and sulfate in relation to plasma bilirubin concentration and D-glucaric acid excre tion. Pediatrics 55(6): 818- 825.
Lewis DC and Alexeeff GV (1989). Quantitative RiskAssess ment of Noncancer Health Effects for Acute Exposure to Air Pollutants. 82nd Annua l Meeting of the Air and Waste Management Association.Air and Waste Managmen t Association. pp. 89-91. Anaheim (CA).
Lilienfeld AM and Lilienfeld DE (1980). Foundations of Epidemiology, 2nd Edition. New York: Oxford University Press.
Loomis D, Castillejos M, Gold DR, McDonnell W and Borja-Aburto VH (1999). Air pollution and infant mortality in Mexico City. Epidemiology 10(2): 118-123.
Mantel N, Bohidar NR, Brown CC, Ciminera JL and Tukey JW (1975). An improved MantelBryan procedure for "safety" testing of carcinogens. Cancer Res 35(4): 865-872.
Mantel N and Bryan WR (1961). "S afety" testing of carcinogenic agents. J Natl Cancer Inst 27: 455-470.
Maughan B, Taylor C, Taylor A, Butler N and Bynner J (2001). Pregnancy sm oking and childhood conduct problems: A causal associatio n? J Child Psychol Psychiatry 42(8): 1021- 1028.
McCarver DG and Hines RN (2002). The ontogeny of hum an drug-metabolizing enzymes: Phase II conjugation enzymes and regulatory mechan isms. J Pharmacol Exp Ther 300(2): 361-366.
McConnell R, Berhane K, Yao L, Jerrett M, Lurmann F, Gilliland F, Kunzli N, Gauderman J, Avol E, Thom as D and Peters J (2006). Traffi c, susceptibility, and childhood asthma. Environ Health Perspect 114(5): 766-772.
McFadden SW and Haddow JE (1969). Coma pr oduced by topical application of isopropanol. Pediatrics 43(4): 622-623.
Miles M (1983). Pediatric Pharmacokinetics. In: Applied Clinical Pharmacokinetics. Mungall D. McGraw-Hill. New York: 367-388.
Miller MD, Marty MA, Arcus A, Brown J, Mo rry D and Sandy M (2002). Differences between child ren and adults: Implications for risk assessmen t at California EPA. Int J Toxicol 21(5): 403- 418.

Technical Support Document 105 June, 2008TSD for Noncancer RELs June 2008 Miller RA (1941). Observations on the gastric aci dity during the first mo nth of life. Arch Dis Child 16: 22-30.
Milsap RL and Jusko WJ (1994). Pharmacokinetics in the infant. Environ Health Perspect 102 (Suppl 11): 107-110.
Mitchell WA, Gift JS and Jarabek AM (1993) . Suitability of LOAEL to NOAEL 10-fold uncertainty factor for health assessments of inhaled toxicants [Abstract #475]. The Toxicologist 13: 140.
Monson RR (1986). Observations on the healt hy worker effect. J Occup Med 28(6): 425-433.
Morselli PL (1976). Clincial ph arm acokinetics in neonates. Clin Pharmacokinet 1(2): 81-98.
Morselli PL (1989). Clinical ph arm acology of the perinatal pe riod and early infancy. Clin Pharmacokinet 17 (Suppl 1): 13-28.
Morselli PL, Franco-Morselli R and Bossi L (19 80). Clinical pharm acokinetics in newborns and infants. Age-related differences and therapeutic implications. Clin Pharmacokinet 5(6): 485-527.
Muller G, Spassovski M and Henschler D (1972). Trichloroethylene exposure and trichloroethylene m etabolites in urin e and blood. Arch Toxikol 29(4): 335-340.
Murrell JA, Portier CJ and Morris RW (1998). Characterizi ng dose-response I: Critical assessment of the benchmark dose concept. Risk Anal 18(1): 13-26.
Nair RS, Sherman JH, Stevens MW and Johanns en FR (1995). Selecting a More Realistic Uncertainty Factor: Reducing Com pounding Effects of Multiple Uncertainties. St. Louis (MO): Monsanto Company. Unpublished report.
NATICH and McCullough M. (1991). National Air Toxics Inform ation Clearinghouse Database Report on State, Local and EPA Ai r Toxics Activities: Final

. Research Triangle Park (NC): Office of Air Quality Planning and Standards, Un ited States Environmental Protection Agency, National Air Toxics Information Clearinghouse.
Needleman HL, Schell A, Bellinger D, Leviton A and Allred EN (1990). The long-term effects of exposure to low doses of lead in chil dhood. An 11-year follow-up report. N Engl J Med 322(2): 83-88.
Nielsen GD (1991). Mechanisms of activation of the sensory irritant receptor by airbo rne chemicals. Crit Rev Toxicol 21(3): 183-208.
Nielsen GD and Vinggaard AM (198 8). Sensory irritation and pulm onary irritation of C3-C7 nalkylamines: Mechanisms of receptor activation. Pharmacol Toxicol 63(4): 293-304.
NIOSH. (2005). NIOSH Pocket Guide to Chemical Hazards . Washington (DC) U.S. Department of Health and Human Services, National Inst itute for Occupational Safety and Health. http://www.cdc.gov/niosh/npg/

.

Technical Support Document 106 June, 2008TSD for Noncancer RELs June 2008 NRC. (1977-1987). Drinking Water and Health . 1-7. Washington (DC): National Research Council, National Academy Press. http://darwin.nap.edu/openbook.php?record_id=1780&page=905

. NRC. (1986a). Criteria and Methods for Preparing Emergency Exposure Guidance Level (EEGL) , Short Term Public Emergency Gu idance Level (SPEGL) and Continuous Exposure Guidance Level (CEGL) Documents . Washington (DC): Comm ittee on Toxicology, National Research Council, National Academy Press.
NRC (1986b). Dose-Route Extrapolations: Using Inhalat ion Toxicity Data to Set Drinking Water Limits . In: Drinking W ater and Health. Nationa l Research Council, National Academy Press. Washington (DC): Vol. 6: 457.
NRC. (1993). Guidelines for Develo ping Community Emergency Exposure Levels for Hazardous Substances . Washington (DC): Committee on Toxicol ogy, National Research Council, National Academy Press.
NRC. (1994). Science and Judgement in Risk Assessment . Washington (DC): Committee on Risk Assessm ent of Hazardous Air Pollutants, Nationa l Research Council, National Academy Press. http://www.nap.edu/books/030904894X/html/index.html

. NRC. (2001). Standing Operating P rocedures for Developi ng Acute Exposure Guideline Levels for Hazardous Chemicals . Washington (DC): Subcommitt ee on Acute Exposure Guideline Levels, National Research Council, National Academy Press.
NRC. (2007). Scientific Review of the Proposed Risk Assessment Bu lletin from the Office of Management and Budget . W ashington (DC): National Academy Press.
OEHHA. (1999). The Air Toxics Hot Spots Program Risk Assessment Guidelines. Part I: Technical S upport Document for Determinati on of Acute Reference Exposure Levels for Airborne Toxicants . Air Toxicology and Epidemiology Sect ion, Office of Environmental Health Hazard Assessment, California E nvironmental Protection Agency. http://www.oehha.ca.gov/air/acute_rels/acuterel.html#download

. OEHHA. (2000a). The Air Toxics H ot Spots Program Risk Assessment Guidelines Part III: Technical Support Document for the Determination of Noncancer Chronic Reference Exposure Levels . Air Toxicology and Epidemiology Section, Office of Environmental Health Hazard Assessment, California Envir onmental Protection Agency. http://www.oehha.ca.gov/air/ chronic_rels/pdf/relsP32k.pdf

. OEHHA. (2000b). The Air Toxics Hot Spots Program Risk Assessment Guidelines. Part IV: Technical Support Document for Expos ure Assessment and Stochastic A nalysis . Air Toxicology and Epidemiology Section, Office of Environmen tal Health Hazard Assessment, California Environmental Protection Agency. http://www.oehha.ca.gov/air/hot _spots/finalStoc.htm l#download

. OEHHA. (2001). Prioritization of Toxic Air Contaminant s Under the Children’s Environmental Health Protection Act . Air Toxicology and Epidem iology Section, Office of Environmental

Technical Support Document 107 June, 2008TSD for Noncancer RELs June 2008
Health Hazard Assessment, Californi a Environmental Protection Agency. http://www.oehha.ca.gov/air/toxic_contamin ants/pdf_zip/SB25%20T AC%20prioritization.pdf

. OEHHA. (2003). The Air Toxics Hot Spots Program Gu idance Manual for Preparation of Health Risk Assessments . August. Air Toxicology and Epidem iology Section; Office of Environmental Health Hazard Assessment, Ca lifornia Environmental Protection Agency. http://www.oehha.ca.gov/air/hot _spots/pdf/HRAguidefinal.pdf

. OEHHA. (2005a). The Air Toxics H ot Spots Program Risk Assessment Guidelines. Part II: Technical Support Document for Describi ng Available Cancer Potency Factors . Air Toxicology and Epidemiology Section, Office of Environmen tal Health Hazard Assessment, California Environmental Protection Agency. http://www.oehha.ca.gov/air/hot _spots/pdf/May2005Hotspots.pdf

. OEHHA. (2005b). Proposed Identification of Environmen tal Tobacco Smoke as a Toxic Air Contaminant . Part B: Health Effects. Air Toxico logy and Epidem iology Section, Office of Environmental Health Hazard Assessment, Ca lifornia Environmental Protection Agency. http://www.oehha.ca.gov/air/environmental_tobacco/2005etsfinal.html

. Orup Jr. HI, Holmes LB, Keith DA and Coull BA (2003). Craniofacial skeletal deviations following in utero exposure to the anticonvulsant phenytoin: Monotherapy and polytherapy. Orthod Craniofac Res 6(1): 2-19.
Owen BA (1990). Literature-derived absorption coefficients for 39 ch em icals via oral and inhalation routes of exposure. Re gul Toxicol Pharmacol 11(3): 237-252.
Pelekis M, Gephart LA and Lerman SE (2001). Physiological-model-based derivation of the adult and child pharm acokinetic intraspecies uncertain ty factors for volatile organic compounds. Regul Toxicol Pharmacol 33(1): 12-20.
Pelekis M, Nicolich MJ and Gaut hier JS (2003). Probabi listic fra mework for the estimation of the adult and child toxicokineti c intraspecies uncerta inty factors. Risk Anal 23(6): 1239-1255.
Pepelko WE (1987). Feasibility of route extrapol ation in risk assessm ent. Br J Ind Med 44(10): 649-651.
Pepelko WE (1991). Effect of exposure route on potency of carcinogens. Regul Toxicol Pharm acol 13(1): 3-17.
Perera FP, Jedrychowski W, Ra uh V and W hyatt RM (1999). Molecu lar epidemiologic research on the effects of environmental pollutants on the fetus. Environ Health Perspect 107 (Suppl 3): 451-460.
Phalen RF, Oldham MJ, Beaucage CB, Crocker TT and Mortensen JD (1985). Postnatal enlargem ent of human tracheobronchial airways and implications for particle deposition. Anat Rec 212(4): 368-380.

Pineiro-Carrero VM and Pine iro EO (2004). Liver. Pedi atrics 113(4 Suppl): 1097-1106.

Technical Support Document 108 June, 2008TSD for Noncancer RELs June 2008 Plopper CG and Fanucchi MV (2004). Developmen t of Airway Epithelium. In: The Lung: Development, Aging and The Environment Hardi ng R., Pinkerton K. and Plopper C. G. Elsevier Academic Press. San Diego (CA).
Plopper CG, Mariassy AT, Wilson DW, Alley JL, Nishio SJ and Nettesheim P (1983). Com parison of nonciliated tracheal epithelial cells in six mammalia n species: Ultrastructure and population densities. Exp Lung Res 5(4): 281-294.
Plunkett LM, Turnbull D and Rodericks JV (1992) . Differences Between Adults and Children Affecting E xposure Assessment. In: Similarities and Differences Between Children and Adults: Implications for Risk Assessment. Guzelian P. S ., Henry C. J. and Olin S. S. ILSI Press. Washington (DC): pp. 79-94.
Price K, Haddad S and Krishnan K (2003). Physiological modeling of age- specific changes in the pharm acokinetics of organic chemicals in ch ildren. J Toxicol Environ Health A 66(5): 417- 433.
Purser DA, Grimshaw P and Berrill KR (1984). In toxication by cyanide in fires: a study in monkeys using polyacrylonitrile. Ar ch Environ Health 39(6): 394-400.
Rall DP (1969). Difficulties in extra polating the results of to xicity studies in laboratory animals to man. Environ Res 2(5): 360-367.
Rane A and Wilson JT (1976). Clinical pharm ac okinetics in infants and children. Clin Pharmacokinet 1(1): 2-24.
Raphael G, Meredith S, Baraniuk J and Kaliner M (1991). Nasal reflexes. In: Rhinitis (2nd Edition ). Settipane G. OceanSide Pub lications. Providence (RI): 135-142.
Renwick AG, Dorne JL and Walton K (2000). An analysis of the need for an additional uncertainty f actor for infants and children. Regul Toxicol Pharmacol 31(3): 286-296.
Renwick AG and Lazarus NR (1998). Human vari ab ility and noncancer risk assessment--An analysis of the default uncertainty fa ctor. Regul Toxicol Pharmacol 27(1): 3-20.
Rice D and Barone Jr. S (2000). Critical period s of vulnerability for the d eveloping nervous system: Evidence from humans and animal mode ls. Environ Health Pers pect 108(Suppl 3): 511- 533.
Rice DC (1996). Evidence for delayed neurotoxicity produced by m ethylmercury. Neurotoxicology 17(3-4): 583-596.
Rinehart WE and Hatch T (1964). Concentration- tim e product (Ct) as an expression of dose in sublethal exposures to phosgene . Am Ind Hyg Assoc J 25: 545-553.
Ritz B and Yu F (1999). The effect of ambi ent carbon monoxide on lo w birth weight am ong children born in Southern Calif ornia between 1989 and 1993. Envi ron Health Perspect 107(1): 17-25.

Technical Support Document 109 June, 2008TSD for Noncancer RELs June 2008 Roach SA and Rappaport SM (1990). But they are not thresholds: A criti cal analysis of the documentation of Threshold Limit Values. Am J Ind Med 17(6): 727-753.
Robillard J, Guillery E and Petershack J (1999). Renal Function During Fetal Life. In: Pediatric Nephrology. Barratt T. M., Avner E. and Harmon W. Lippincott Williams & Wilkins. Baltimore (MD): 21-37.
Robinson JC and Paxman DG (1992). The role of threshold lim it values in U.S. air pollution policy. Am J Ind Med 21(3): 383-396.
Rothman KJ and Greenland S (1998). Modern Ep idem iology. Philadelphia (PA): Lippincott, Raven Publishers.
Roels H, Meiers G, Delos M, Ortega I, Lauwerys R, Buchet JP and Lison D (1997). Influence of the route of adm inistration and the chemical form (MnCl 2 , MnO 2 ) on the absorption and cerebral distribution of manganese in rats . Arch Toxicol 71(4): 223-230.
Rothman KJ and Greenland S (2005). Causation and causal inference in epidem iology. Am J Public Health 95 (Suppl 1): S144-S150.
Rozman KK and Klaassen CD (1996). Absorption, Distribution, and Excreti on of Toxicants. In: Casarett and Doull's Toxicology; The Basic Science of Poisons. Klaassen C. D. McGraw-Hill. New York: p 104.
Sagiv SK, Mendola P, Loomis D, Herring AH, Neas LM, Savitz DA and Poole C (2005). A tim e-series analysis of air pollution and pr eterm birth in Pennsyl vania, 1997-2001. Environ Health Perspect 113(5): 602-606.
Salmon A (2007). Standard risk assessment pr ocedures: Are they adequate to accoun t for cumulative risks? International J ournal of Toxicology in press.
Sanchez G. (2002). Humorap: A Mathemati ca package for solving the ICRP 66 and 78

com partmental models and more. http://web.usal.es/~guillerm/

. Sand S, Filipsson AF and Victorin K (2002). Evaluation of the benchm ark dose method for dichotomous data: Model dependence and model selection. Regul Toxicol Pharmacol 36(2): 184- 197.
Sand SJ, von Rosen D and Filipsson AF (2003). Benchm ark calculations in risk assessment using continuous dose-response information: The influe nce of variance and the determination of a cutoff value. Risk Anal 23(5): 1059-1068.
Sarangapani R, Gentry PR, Covington TR, T eeguarden JG and Clewell 3rd. HJ (2003). Evaluation of the potential im pact of age- and gender-specific lung morp hology and ventilation rate on the dosimetry of vapors. Inhal Toxicol 15(10): 987-1016.

Technical Support Document 110 June, 2008TSD for Noncancer RELs June 2008 Sarangapani R, Teeguarden JG, Cruzan G, Clewell 3rd. HJ and Andersen ME (2002). Physiologically based pharmacokinetic modeling of styrene and styrene oxi de respiratory-tract dosimetry in rodents and huma ns. Inhal Toxico l 14(8): 789-834.
Sarangapani R, Teeguarden JG, Gentry PR, Clewell 3rd. HJ, Barton HA and Bogdanffy MS (2004). Interspecies dose extrap olation for inhaled dim ethyl sulfate: A PBPK model-based analysis using nasal cavity N7-methylguani ne adducts. Inhal Toxi col 16(9): 593-605.
Schmidt CW, Gillis CA, Keenan RE and Pric e PS (1997). Characterizing inter-chemical variation in the interspecies un certainty factor (UFA) [Abstract #1057]. The Toxicologist 36(1 Pt 2): 208.
Schwartz J, Ballester F, Saez M, Perez-Hoyos S, Bellido J, C ambra K, Arribas F, Canada A, Perez-Boillos MJ and Sunyer J (2001). The concen tration-response relation between air pollution and daily deaths. Environ Health Perspect 109(10): 1001-6.
Schwela D (2000). Air pollution and health in ur ban areas. Rev Environ Health 15(1-2): 13-42.
Sherwin RP (1983). What is an adverse health effect? Environ Health Perspect 52: 177-182.
Shusterman D (1999). Upper and lower airway seque lae of irritant inhalations. Clin P ulm Med 6(1): 18-31.
Shusterman D, Matovinovic E and Salmon A (2006) . Does Haber' s Law apply to human sensory irritation? Inhal T oxicol 18(7): 457-471.
Siegel M, Lebenthal E and Krantz B (1984). Eff ect of caloric density on gastric em ptying in premature infants. J Pediatr 104(1): 118-122.
Signer E (1975). Gastric emptying in newborns and young infants. Measurem ent of the rate of emptying using indium-113m-microcollo id. Acta Paediatr Scand 64(3): 525-530.
Skowronski GA, Seide M and Abdel-Rahman MS (2001). Oral bioaccessibili ty of triv alent and hexavalent chromium in soil by simulated gastri c fluid. J Toxicol Envir on Health A 63(5): 351- 62.
Smiley-Jewell SM, Liu FJ, Weir AJ and Plopper CG (2000). Acute injury to differentiating Clara cells in neonatal rabbits results in age-related failure of bronc hiolar epithelial repair. T oxicol Pathol 28(2): 267-276.
Snipes MB (1989a). Long-term retention and clearance of particle s inhaled by m ammalian species. Crit Rev Toxicol 20(3): 175-211.
Snipes MB, McClellan RO, Mauderly JL and Wol ff RK (1989b). Retention patterns for inhaled particles in the lung: Comparisons between laboratory anim als and humans for chronic exposures. Health Phys 57 (Suppl 1): 69-77; discussion pp. 77-78.

Technical Support Document 111 June, 2008TSD for Noncancer RELs June 2008 Snodgrass WR (1992). Physiologica l and Biochemical Differences Between Children and Adults as Determinants of Toxic Response to Environmen tal Pollutants. In: Simila rities and Differences Between Children and Adults: Implications For Ri sk Assessment. Guzelian P. S., Henry C. J. and Olin S. S. ILSI Press. Washington (DC): 35-42.
Starr TB, Goodman JI and Hoel DG (2005). Uses of benchmark dose methodology in quantitative risk assessm ent. Regul Toxicol Pharmacol 42(1): 1-2.
Streissguth AP, Aase JM, Clarren SK, Randels SP, LaDue RA and Sm ith DF (1991). Fetal alcohol syndrome in adolescents and adults. JAMA 265(15): 1961-1967.
Stromland K, Nordin V, Miller M, Akerstro m B and Gillberg C (1994). Autism in thalidomide

em bryopathy: A population study. Dev Med Child Neurol 36(4): 351-356.
Swartout JC (1997). Exposure-duration uncertain ty factor for the Rf D [Abstract #1060]. The Toxicologist 36: 209.
ten Berge WF, Zwart A and Appelman LM (1986). Concentration-tim e mortality response relationship of irritant and systemically acting vapours and gases. J Hazard Mater 13: 301-309.
Ting D, Howd RA, Fan AM a nd Alexeeff GV (2006). Developm ent of a health-protective drinking water level for perchlorate. Environ Health Pers pect 114(6): 881-6.
Treluyer JM, Gueret G, Cheron G, Sonnier M and Cresteil T (1997). Developm ental expression of CYP2C and CYP2C-dependent activities in the human liver: In-vivo/in-vitro correlation and inducibility. Pharmacogenetics 7(6): 441-452.
Treluyer JM, Jacqz-Aigrain E, Alvarez F and Cr esteil T (1991). Expression of CYP2D6 in developing hum an liver. Eu r J Biochem 202(2): 583-588.
Tyrala EE, Hillman LS, Hillman RE and Dodson W E (1977). Clinical pharmacology of hexachlorophene in newborn infa nts. J Pediatr 91(3): 481-486.
Tzimas G, Thiel R, Chahoud I and Nau H (1997). Th e area under the concentr ation-tim e curve of all-trans-retinoic acid is the mo st suitable pharmacokinetic correlate to the embryotoxicity of this retinoid in the rat. Toxicol Appl Pharmacol 143(2): 436-444.
U.S. DHHS. (2004). The Health Consequences of Smoki ng; A Report of the Surgeon General

. Washington (D.C.) Office on Sm oking and Healt h, United States Department of Health and Human Services. http://www.cdc.gov/tobacco/sgr/sgr_2004

. U.S. EPA. (1988). Recommendations for and Documentation of Biological Values for Use in Risk Assessment . EPA/600/6-87-008. W ashington (DC): Unit ed States Environmental Protection Agency.
U.S. EPA. (1993). Reference Dose (RfD) : Description and Use in Health Risk Assessments. Background Document1A. March 15 . 2005. United States Environmental Protection Agency. http://www.epa.gov/iris/rfd.htm

.

Technical Support Document 112 June, 2008TSD for Noncancer RELs June 2008 U.S. EPA. (1994a). Methods for Derivation of Inhalati on Reference Concentrations and Application of Inhalation Dosimetry . EPA/600/8-90/066F. Washington (DC): Office of Research and Development, United States Environmental Protection Agency. http://www.epa.gov/iris/subst/0364.htm

. U.S. EPA. (1994b). Methods for Exposure-Response Analys is and Health Assessment for Acute Inhalation E xposure to Chemicals. Developm ent of the Acute Reference Exposure (Draft)

. Research Triangle Park (NC): Office of Health and Environmental Asse ssment, United States Environmental Protection Agency.
U.S. EPA. (1995). The Use of the B enchmark Dose Approach in Health Risk Assessment

. EPA/630/R-94/007. Washington (DC): Risk Assessm ent Forum, United States Environmental Protection Agency. http://cfpub.epa.gov/ ncea/raf/recordisplay.cfm ?deid=42601

. U.S. EPA. (2000). Strategy for Research on Environmental Risks to Children . EPA/600/R00/068. W ashington (DC): Office of Research and Development, United States Environmental Protection Agency. http://www.epa.gov/nceawww1/pdfs/stra4resrch.pdf

. U.S. EPA. (2002a). A Review of the Reference Dose and Reference Concentration P rocess

. EPA/630/P-02/002F. Washington (DC) : Risk Assessment Forum, United States Environmental Protection Agency. http://www.epa.gov/iris/RFD_FINAL%5B1%5D.pdf

. U.S. EPA (2002b). Determination of the Appropr iate FQPA Safety Factor(s) in Tolerance Assessm ent. February 28, 2002.
U.S. EPA. (2004). An Examination of EPA Risk Asse ssment Principles and Practices

. EPA/100/B-04/001. W ashington (DC): Office of the Science Advisor, United States Environmental Protection Agency. http://www.epa.gov/OSA/pdfs/ratf-final.pdf

. U.S. EPA (2006a). Benchmark Dose Software (B MDS) Tutorial. United S tates Environmental Protection Agency. http://www.epa.gov/ncea/bmds_ training/m ethodology/model.htm . June 29, 2006.
U.S. EPA. (2006b). Approaches for the Application of Ph ysio logically Base d Pharmacokinetic (PBPK) Models and Supporting Data in Risk Assessment . EPA/600/R-05/043F. National Center for Environmental Assessment, Office of Re search and Development, United States Environmental Protection Agency. http://oaspub.epa.gov/eims/xmlreport.disp lay? deid=157668&z_chk=33346&format=print

. U.S. EPA. (2006c). A Framework for Assessing Health Risks of Environ mental Exposures to Children . Washington (D.C.): Office of Resear ch and Development, United States Environmental Protection Agency. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=150263

. U.S. EPA (2007a). Integrated Risk Informa tion System (IRIS) Database. United States Environmental Protection Agency. http://www.epa.gov/IRIS/

.

Technical Support Document 113 June, 2008TSD for Noncancer RELs June 2008 U.S. EPA (2007b). Acute Exposure Guideline Leve ls. United States En vironmental Protection Agency. http://www.epa.gov/oppt/aegl/pubs/compiled.pdf . May 14, 2007.
U.S. FDA. (2006). Redbook 2000 Toxicological Principles for the Safety Assessment of Food Ingredients . Office of Food Additive Safety, U.S. Food and Drug Administration. http://www.cfsan.fda.gov/~redbook/red-toca.html

. Uebori M and Imamura K (2004). Analysis of al iphatic and arom atic carbonyl compounds in ambient air by LC/MS/MS. Anal Sci 20(10): 1459-1462.
Vedal S, Brauer M, White R and Petkau J (2003). Air pollution and daily m ort ality in a city with low levels of pollution. Environ Health Perspect 111(1): 45-52.
Vettorazzi G (1977). Safety Factor s and Their Application in th e Toxicological Evaluation. In: The Evaluation of Toxicological Data for the Pr otection of Public Hea lth: Proceedings of the Intern ational Colloquium, Luxembourg, D ecember 1976. Commission of the European Communities, Pergamon Press. Oxford, [Eng.]; New York: 207-223.
Watzka M, Bidlingmaier F, Schramm J, Kli ngmuller D and Stoffel- Wagner B (1999). Sex- and age-specific differences in human brain CYP11A1 mRNA expre ssion. J Neuroendocrinol 11(12): 901-905.
Weil CS (1972). Statistics vs safety factors and scientific judgm ent in the evaluation of safety for man. Toxicol Appl Pharmacol 21(4): 454-463.
Weller E, Long N, Smith A, Williams P, Ravi S, Gill J, Henessey R, Skornik W , Brain J, Kimmel C, Kimmel G, Holmes L and Ryan L (1999). Dose-rate eff ects of ethylene oxide exposure on developmental toxic ity. Toxicol Sci 50(2): 259-270.
Wen CP, Tsai SP and Gibson RL (1983). Anatomy of the healthy worker effect: A critical review. J Occup Med 25(4): 283-289.
Widdicombe JG (1990). Nasal pathophysiology. Re spir Med 84 Suppl A: 3-9; discussion 9-10.
Wilhelm M and Ritz B (2005). Local variations in CO and particulate air pollution and adverse birth outcom es in Los Angeles County, California, USA. Environ Health Perspect 113(9): 1212- 1221.
Williams GM, O'Callaghan M, Najman JM, Bor W , Andersen MJ, Richards D and U C (1998). Maternal cigarette smoking and child psychiat ric morbidity: A longit udinal study. Pediatrics 102(1): e11.
Woodruff TJ, Parker JD and Schoendorf KC (2 006). Fine particulate m atter (PM2.5) air pollution and selected causes of postneonatal in fant mortality in California. Environ Health Perspect 114(5): 786-790.

Technical Support Document 114 June, 2008TSD for Noncancer RELs June 2008 Yolton K, Dietrich K, Auinger P, Lanph ear BP and Hornung R (2005). Exposure to environmental tobacco smoke and cognitive abil ities among U.S. children and adolescents. Environ Health Pers pect 113(1): 98-103.
Yu CP and Xu GB (1987). Predictive models for de position of inhaled diesel exhaust particles in humans and laboratory species. Re s Rep Health Eff Inst(10): 3-22.
Yu D (1999). A physiologically based pharmacoki netic m odel of inorganic arsenic. Regul Toxicol Pharmacol 29: 128-141.
Zeltner TB and Burri PH (1987). The postnatal development and growth of the human lung. II. Morphology. Respir Physiol 67(3): 269-282.

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