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DRAFT                                                      EPA/600/6-88/005A
DO NOT QUOTE OR CITE                                             March 1988
                                                              External Review Draft
                   ESTIMATING EXPOSURES TO 2,3,7,8-TCDD
                                     NOTICE
THIS DOCUMENT IS AN EXTERNAL REVIEW DRAFT.  It has not been formally released
by the U.S. Environmental Protection Agency and should not at this stage be
construed to represent Agency policy.  It is being circulated  for comment on its
technical accuracy and policy implications.
                            Exposure Assessment Group
                   Office of Health and Environmental Assessment
                        Office of Research and Development
                              Washington, DC 20460

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                                            CONTENTS



                                                                                  Page

     Tables                                                                        viii

     Figures                                                                        xii

     Foreword                                                                      xiii

     Preface                                                                        xiv

     Document Development                                                         xv


     1.   EXECUTIVE SUMMARY                                                    1

         A.   Introduction                                                            2
         B.   Conclusions                                                             5
^-       C.   Recommendations                                                       8

^   PART ONE: AN UPDATE OF CURRENT KNOWLEDGE AND METHODS FOR
r                PERFORMING EXPOSURE ASSESSMENTS FOR 2,3,7,8-TCDD        10
00
r^   2.   PHYSICAL/CHEMICAL PROPERTIES AND GENERAL EXPOSURE
         PARAMETERS                                                             11

         A.   Physical/Chemical Properties                                            11
         B.   Body Weights and Pulmonary Ventilation Rates in Exposure
              Assessments                                                           18

              1.   Body Weights                                                     18
              2.   Pulmonary Ventilation Rates                                       20

     3.   FATE                                                                    24

         A.   Fate of 2,3,7,8-TCDD in Soil                                           25

              1.   Transient Behavior of TCDD Profile in Soil Layer                    25
              2.   Transient Profile in Soil Column                                   27
              3.   Degradation of 2,3,7,8-TCDD in Soil                               29
              4.   Biodegradation of 2,3,7,8-TCDD in Soil                            30

         B.   Fate of 2,3,7,8-TCDD in Sediments                                     34

              1.   Aquatic Sediments                                                34
              2.   Sediment-to-Water Transport Process                               35
              3.   Estimation of TCDD Concentration in Water Body                    36
              4.   Example Calculation                                              38
                                              in

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                               CONTENTS, continued

                                                                                Page

     C.   Bioaccumulation of 2,3,7,8-TCDD in Fish and Cattle                       39

          1.    Bioaccumulation in Fish                                             39
          2.    Bioaccumulation in Cattle                                            42

     D.   Plant Uptake                                                            43

4.    EXPOSURE                                                                  46

     A.   Inhalation — Indoor  Dust Levels Versus Outdoor Levels                     46
     B.   Inhalation — Vapors                                                     48

          1.    Emission Potential                                                   SO
          2.    Dilution of Emissions in Ambient Air                                 54
          3.    Exposure Estimation                                                 57
          4.    Effect of Photodegradation on Exposure Estimation                    59

     C.   Inhalation -- Particulates                                                 62

          1.    Vehicular Traffic                                                   63
          2.    Loading and Unloading Operations                                   64
          3.    Spreading Operations                                                65
          4.    Transportation in Trucks                                            65
          5.    Wind Erosion                                                       66

     D.   Dermal  — Soil Contact Rates and Dermal Absorption                       68

          1.    Contact Rates                                                      68
          2.    Absorption                                                         71
          3.    Summary                                                           73

     E.   Ingestion  — Soil                                                         73

          1.    Available Studies                                                   74
          2.    Evaluation                                                          78

     F.   Ingestion  ~ Beef and Dairy Products                                     80
     G.   Ingestion  — Fish Consumption Data                                       83

          1.    Available Studies                                                   83
          2.    Evaluation                                                          88
                                           IV

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                             CONTENTS, continued

                                                                            Page

5.    POST-EXPOSURE                                                         90

     A.  Absorption from Environmental Matrices (Unavailability)                  91
                ;
         1.   General Considerations                                            91
         2.   Review of Data on Unavailability                                  92
         3.   Summary                                                       120

     B.   Pharmacokinetics and Body Burden of Dioxins                           126

         1.   Body Burden: Estimate of Exposure                               128
         2.   Physiologically Based Pharmacokinetic Modeling                     130
         3.   Calculation of Daily Intake                          .              139

              a.  Data                                                        139
              b.  Data Use                                                    140
              c.  Findings                                                     140
              d.  Conclusions Regarding Body Burden Data                       141
              e.  Calculation, Assumptions, Uncertainties, and Actual
                  Parameter Values                                             142
              f.  Parameters Chosen                                            143
              g.  Daily Intakes Calculated                                       144
              h.  Impact of Daily Background on Risk                           144
              i.  Recommendations for Future Activities                          145

PART TWO:  APPLICATION OF EXPOSURE ASSESSMENT METHODS IN EVALUATING
          2,3,7,8-TCDD EXPOSURES FROM SELECTED SITUATIONS           149

6.    USE OF METHODOLOGIES TO ESTIMATE EXPOSURE TO 2,3,7,8-TCDD    150

     A.  Description of the Exposure Scenarios for Contaminated
         Soil and Landfills                                                    151
     B.   Exposure Pathways                                                   160

         1.   General                                                        160
         2.   Exposure Factors Common to More than  One Pathway                161

              a.  Degradation and Dilution                                      161
              b.  Sediment Dilution  Factor                                      171
              c.  Body Weight                                                 172
              d.  Lifetime                                                     172
              e.  Pharmacokinetics                                             172

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                          CONTENTS, continued
     3.    Specific Factors by Pathway                                         173

          a.  Dust Inhalation from Wind Erosion                                173
          b.  Dust Inhalation from Vehicular Traffic                            183
          c.  Vapor Inhalation                                                 184
          d.  Dermal Exposure                                                190
          e.  Soil Ingestion                                                    191
          f.  Ingestion of Beef and  Dairy Products                              193
          g.  Ingestion of Fish                                                194
          h.  Water Ingestion—Surface Water                                   197
          i.  Ground Water Contamination                                      199
          j., Fruit and Vegetable Ingestion                                     203

C.   Description of Exposure Scenarios for Incineration                         206

     1.    Summary of Incineration  Scenarios                                   208
     2.    General Calculations and  Factors Used                                212

          a.  Summary of Emissions Data and Vapor/Particulate
              Distribution                                                    212
          b.  Municipal Waste Incierator Capacities in the U. S.                  221
          c.  Air Dispersion Modeling                                         222
          d.  Surface Water Contamination                                     227
              (1)  Vapor Absorption                                           229
              (2)  Particulate Deposition                                       231
          e.  Land-Disposed Ash                                              234
          f.  Soil Contamination                                               237

D.   Incinerator Exposure Pathway Calculations                                 241

     1.    Inhalation of Ambient Air                                           241
     2.    Ingestion of Contaminated Soil                                       247
     3.    Dermal Contact with Contaminated Soil                               247
     4.    Ingestion of Contaminated Drinking Water                            248
     5.    Ingestion of Contaminated Fish                                      248
     6.    Ingestion of Contaminated Beef and Dairy Products                   249
     7.    Ingestion of Dairy Products Due to Particulate
          Deposition on Fodder                                               250

E.   Risks Associated with Total CDDs vs. 2,3,7,8-TCDD                       253
                                      VI

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                   CONTENTS, continued

7.    UNCERTAINTY EVALUATION                                            257

     A.   Contaminated Soil and Landfills                                         259

          1.   Summary of Uncertainties                                         259
          2.   Uncertainties in Specific Methods Applied                          262
              a.   Soil Dilution Factor                                          262
              b.   Sediment Dilution Factor                                     265
              c.   Degradation                                                 267
              d.   Dust Inhalation                                              271
              e.   Vapor Inhalation                                             275
              f.   Dermal Exposure                                            278
              g.   Soil Ingestion                                               280
              h.   Beef and Milk Fat Ingestion                                  283
              i.   Fish Ingestion                                               287
              j.   Water Ingestion - Surface Water                               291
              k.   Ground Water Contamination                                 296
              1.   Plant Uptake                                                297

     B.   Incineration Scenarios                                                 297

          1.   Emissions Data                                                   299
          2.   Selection of Model Incinerator and Exposure Scenario                300
          3.   Inhalation and Surface Deposition                                  300
          4.   Surface Water Contamination                                      304
          5.   Soil Contamination from Emissions                                 306
          6.   Dairy Product Exposure Following Deposition on Plants              309
          7.   Land-Disposed Ash                                               311


8.    REFERENCES                                                            315


APPENDIX. RISK ESTIMATES FOR CHAPTER 6 SCENARIOS                      333
                                          vn

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                                    TABLES

                                                                              Page

2-1       Properties of 2,3,7,8-TCDD                                             19

2-2       Estimated Minute Ventilation Associated with Activity Level
          for Average Male Adult                                                 23

4-1       Estimates of Soil Ingestion from Dermal Contact                           76

4-2       Rates of Ingestion of Beef and Dairy Products                             82

5-1       Guinea Pigs Receiving a Single Gavage Dose of Materials
          Containing 2,3,7,8-TCDD                                               93

5-2       Toxicity of TCDD Contaminated Soil                                     98

5-3       Comparison of Mortality in Guinea Pigs Following a Single
          Dose of Contaminated Soils                                             103

5-4       Guinea Pig Mortality and Weight Changes Following Treatment
          with Contaminated Soot or 2,3,7,8-TCDD                                106

5-5       Concentrations of PCDD and PCDF Isomer-Groups in Fly Ash
          Extracts (Diluted with Acetone) and Fly Ash                             110

5-6       Concentrations of PCDD and PCDF Isomer Groups in Livers
          of Rats Fed Fly Ash Materials                                          111

5-7       Percentage of Cumulative Dose of Dioxins and  Furans Present
          in Rat Liver Following 19 Days Exposure in Diet                         112

5-8       Percentage of Tritium-Labeled 2,3,7,8-TCDD in Rat Liver
          Following Administration of 14.7 mg Dose in Ethanol                     116

5-9       Percentage of Tritiated 2,3,7,8-TCDD Dose  in the Liver
          24 Hours After Oral Administration of 0.5 ml, of Various Media            117

5-10      Gut Absorption of 2,3,7,8-TCDD in Rabbits after 7-Day
          Treatment                                                            119

5-11      Summary of Data on the Bioavailability of 2,3,7,8-TCDD
          Following Ingestion of Environmental Matrices                            122

5-12      Animal vs Human Clearance and Half-Lives of TCDD                    138

5-13      Calculated Average Daily Intake                                         144

5-14      Risks Associated with Background Daily Intake of 2,3,7,8-TCDD
          Compared with Annual Cancer Incidence in U.S. Population               146
                                         Vlll

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                             TABLES, continued

6-1       Assumptions for Contaminated Soil Scenarios                              158

6-2       Assumptions for Landfill Scenarios                                       159

6-3       Erosion Parameters                                                      167

6-4       Dilution Factors                                                        170

6-5       Factors Used in Exposure Calculations                                    174

6-6       Exposure Levels Associated with Various  Exposure
          Pathways/Scenarios  - Contaminated Soil                           .       176

6-7       Simulated Concentrations at Wells                                        202

6-8       Parameter Values for Incinerator Facilities in Scenarios  16-19              209

6-9       Parameter Values for Populations in Scenarios 16-19                       210

6-10      Stack Emission of PCDD's from  Municipal Incinerators                     214

6-11      PCDD's in Fly Ash  of Combustion                                       216

6-12      Emissions of CDD's from Combustion Devices Other Than MWI            218

6-13      Air Dispersion Modeling of Particulate-Form 2,3,7,8-TCDD
          Emissions                                                              224

6-14      Summary of Ambient Air Concentration and Deposition Rate
          in the Vicinity of the Facilities in Scenarios 16-19      ,^                  228

6-15      Comparison  of Particle Size in Settling Velocity                            229

6-16      Exposures Associated with Incinerator Exposure Pathway/
          Scenarios A. Exposures Associated  with Stack Emissions
          and B. Exposures Associated with Fly Ash Disposal                        242

6-17      Parameter Values for Calculating Exposures Associated  with
          Incinerators                                                             244

6-18      Ambient Air Concentrations and Exposures at 0.8 km                      246

6-19      Inhalation Exposures at 200 m and 100 km                                246

6-20      Exposure from Ingestion of Contaminated Soil                             247

6-21      Exposure from Dermal Contact of  Contaminated Soil                       247

6-22      Exposure from Ingestion of Contaminated Drinking Water                  248
                                           IX

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                        TABLES, continued


6-23      Exposure from Ingestion of Contaminated Fish                           249

6-24      Exposure from Ingestion of Contaminated Beef and
          Dairy Products                                                         250

6-25      Parameter Values Needed in Equation 6-53                               252

6-26      Daily Exposure from Ingestion of Milk Resulting from
          Particulate Deposition on Fodder                                        253

6-27      Weight Percent Distribution of CDD Congener Equivalents in
          MWI Stack Emissions                                                   254

6-28      Weight Percent Distribution of CDD Congener Equivalents in
          MWI Fly Ash                                                          256

7-1       Landfill Assessment - Soil Dilution Factor                                266

7-2       Landfill Assessment - Sediment Dilution  Factor - Ponds                   268

7-3       Landfill Assessment - Sediment Dilution  Factor - Streams                 269

7-4       Landfill Assessment - Degradation                                       272

7-5       Landfill Assessment - Dust Inhalation                                    276
                                                      i
7-6       Landfill Assessment - Vapor Inhalation                                   279

7-7       Landfill Assessment - Dermal Contact                                    281

7-8       Landfill Assessment - Soil Ingestion                                     284

7-9       Landfill Assessment - Beef and Milk Ingestion                           288

7-10      Landfill Assessment - Fish Ingestion                                     292

7-11      Landfill Assessment - Surface Water Contamination                       295

7-12      Landfill Assessment - Ground Water Contamination                       298

7-13      Incinerator Assessment - Air Emissions Estimate                          302

7-14      Incinerator Assessment - Inhalation and Surface Deposition                303

7-15      Incinerator Assessment - Surface Water Contamination by
          Incinerator Stack Emissions                                             307

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                        TABLES, continued
7-16      Incinerator Assessment - Soil Contamination Levels
          Resulting from Incinerator Emissions                                     310

7-17      Land-Disposed Ash                                                    314
A-l       Upper-Bound Incremental Cancer Risks Associated
          With Various Exposure Pathways/Scenarios:  Contaminated
          Soil                                                                   336

A-2       Upper-Bound Incremental Cancer Risks Associated
          With Incinerator Exposure Pathways/Scenarios:  A. Risks
          Associated with Stack Emissions.  B. Risks Associated
          with Fly Ash Disposal                                                  339
                                          XI

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                                     FIGURES
6-1       Landfill Scenario                                                       157
6-2       Ambient Air Concentration and Exposure with Distance
          for 1 Acre Site                               .                          187

6-3       Ambient Air Concentration and Exposure with Distance
          for 10 Acre Site                                                        187

6-4       Incinerator Scenarios                                                    211
                                           XII

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                                    FOREWORD


     The Exposure Assessment Group (EAG) of EPA's Office of Health and Environmental

Assessment has three main functions:  (1) to conduct exposure assessments, (2) to review

assessments and related documents,  and (3) to  develop guidelines for Agency exposure

assessments.  The activities under each of these functions are supported  by and respond

to the needs of the various EPA program offices.  In relation to the third function, EAG

sponsors  projects  aimed  at  developing  or  refining  techniques   used  in  exposure

assessments.

     2,3,7,8-TCDD problems first surfaced in the United States in the early 1970s with

Agent Orange and the Missouri Horse Arenas.  Since  then, 2,3,7,8-TCDD contamination

has been found elsewhere in Missouri,  Arkansas,  Michigan,  New  York, and New Jersey.

The  EPA  has  become increasingly involved in the discovery, assessment, and cleanup of

these sites. A previous EAG document  (Schaum, 1984)  featured  the use of nomographs to

provide quick and appropriate estimates of risks  for five exposure pathways.   For each

pathway, factors such as contact rates,  absorption fractions, and exposure duration  were

developed, together  with  equations  to be  used  in calculating  exposure levels.   The

purpose of this document is to provide the most  recent exposure  and  risk  estimation

methodology for application to 2,3,7,8-TCDD-contaminated sites.  This methodology will

help us  set priorities and make decisions required to address this  important problem.
                                       Michael A. Callahan
                                       Director
                                       Exposure  Assessment Group
                                          Xlll

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                                    PREFACE






     The Exposure Assessment Group of the Office of Health and Environmental




Assessment has prepared this exposure assessment document at the request of the Office




of Solid Waste. This document presents an update of previous work and an analysis of




key issues related primarily to the assessment of exposure of 2,3,7,8-TCDD. Estimates of




exposure and risk for a  number of exposure pathways are presented.  Current thinking in




the area of bioavailability and pharinacokinetic modeling are presented.  The literature




search supporting this document is current to March 1988.
                                          xiv

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                         DOCUMENT DEVELOPMENT
                       Richard V. Moraski, Ph.D.
                       Document Manager
                       Exposure Assessment Group
                       U.S. Environmental Protection Agency
                       Washington, D.C. 20460
Chapter                         Titles and Authors

   1      EXECUTIVE SUMMARY - Michael A. Callahan; Richard V. Moraski, Ph.D.;
                            and Charles H. Nauman, Ph.D.

   2      PHYSICAL/CHEMICAL PROPERTIES AND GENERAL EXPOSURE PARAMETERS
                            Gregory Kew, Ph.D. and Richard Walentowicz

   3      FATE - Seong T. Hwang, Ph.D.; Charles H. Nauman, Ph.D.;
                            John L. Schaum, P.E.; and Gregory Kew, Ph.D.

   4      EXPOSURE - Seong T. Hwang, Ph.D.;  Gregory Kew, Ph.D.;
                            Richard Walentowicz; and  Paul White

   5      POST-EXPOSURE  - Jerry N. Blancato, Ph.D. and  Paul White

   6      USE OF METHODOLOGIES TO ESTIMATE EXPOSURE TO 2,3,7,8-TCDD
                            Michael A. Callahan; Seong T. Hwang, Ph.D.;
                            John J.  Segna, P.E.; Gregory Kew, Ph.D.; and
                            John L. Schaum, P.E.

   7      UNCERTAINTY EVALUATION - Paul White
                                  Reviewers
Donald Barnes
Office of Pesticides and Toxic Substances
U.S. Environmental Protection Agency
Washington, DC 20460

Judith S. Bellin
Risk Assessment Forum
U.S. Environmental Protection Agency
Washington, DC 20460
                                        xv

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Philip M. Cook
Hazardous Waste Branch
Environmental Research Laboratory
U.S. Environmental Protection Agency
Duluth, MN 55804

William Ellis
Science Applications International Corp.
8400 West Park Drive
McClean, VA 22102

James W. Falco
Director
Environmental Monitoring Systems Laboratory
Research Triangle Park, NC 27711

Michael Firestone
Exposure Assessment Branch
Hazard Evaluation Division
Office of Pesticide Programs
U.S. Environmental Protection Agency
Washington, DC 20460

George Fries
Pesticides Degradation Laboratory, Bldg. 050
U.S. Department of Agriculture
Beltsville, MD 20205

Michael Gallo
Department of Environmental and Community Medicine
UMDNJ-Robert Wood Johnson Medical School
675 Hoes Lane
Piscataway, NJ  08854-5635

Lester D. Grant
Director
Environmental Criteria and Assessment Office
U.S. Environmental Agency
Research Triangle Park, NC 27711

Karen Hammerstrom
Exposure Assessment Branch
Exposure Evaluation Division
Office of Toxics Substances
U. S. Environmental Protection Agency
Washington, DC 20460
                                         xvi

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Renata D. Kimbrough
Office of Regional Operations
Office of the Administrator
U.S. Environmental Protection Agency
Washington, DC 20460

Steven D.  Lutkenhoff
Environmental Criteria and Assessment Office
U.S. Environmental Protection Agency
Cincinnati, OH 45268

Debdas Mukerjee
Environmental Criteria and Assessment Office
U.S. Environmental Protection Agency
Cincinnati, OH 45268

Jerry Schroy
Monsanto  Company
800 N. Lindbergh Boulevard
St. Louis,  MO 63166

Marcia Williams
Director
Office of Solid Waste
U.S. Environmental Protection Agency
Washington, DC 20460

Howard Zar
Chairman, Dioxin Task Force
Region 5, U.S. Environmental Protection Agency
230 South Dearborn Street
Chicago, IL 60604
                                         xvn

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1.  EXECUTIVE SUMMARY




     This report was prepared by scientists and engineers from the Exposure Assessment




Group,  Office of Health and  Environmental Assessment.   The primary  purpose of the




report   is  to  provide  a review  and  update  of  information  related  to exposure  to




2,3,7,8-TCDD  that has  come to light  since 1984.  In addition,  this report provides  an




illustration of the application of this information  in performing exposure  assessments for




2,3,7,8-TCDD.   This  is accomplished by  using the information  to  construct  several




scenarios  where  contaminated material may result in  exposure  to 2,3,7,8-TCDD, and




estimating  what the  exposure (and  risk in the Appendix) would  be for various pathways




from  source  to  humans exposed.   Sources used  as examples  in this  report include




contaminated  soil, various land disposal situations,  and municipal waste incinerators.  It




must be emphasized  that these scenarios  are not to  be interpreted as an  exposure/risk




assessment for  all sources  of these  types.   The assumptions  used  to  construct the




scenarios may be quite different from  the situations encountered  in  a specific assessment




in an actual  case.  It should be emphasized that when assessing  actual sites, monitoring




data may be available, or measurements may be made, that would preclude the necessity



of  part or  all  of  the estimation  methods  described  here.    Good  monitoring  or




measurement  data will  add reliability to the appropriate parts  of the assessment.   In




many cases, however, where measured  data are unavailable and estimation techniques are




required,  the assumptions  used  in certain  scenarios  in this  report may be reasonable




approximations  of the actual  situations being  assessed.   For those cases,  the  scenarios




provided as examples here may provide valuable insight into the  general  magnitude of




exposures to be expected from  similar sources.   It  is  hoped that  this report will provide




a sound starting point for many exposure assessments of 2,3,7,8-TCDD contamination.




     The scope of this report is  outlined  in  the  Introduction,  followed by the  major




conclusions and recommendations.






                                           1

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A.  INTRODUCTION


     2,3,7,8-Tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD) is a substance that is of major


concern to public health because of its  extreme toxicity.   In the family of chemicals


known as  chlorinated dibenzo-p-dioxins (CDDs),  2,3,7,8-TCDD has been shown to be the


most toxic compound to animals that has been isolated and tested. Humans and animals


exposed   to  2,3,7,8-TCDD  have  shown  acute,  subchronic,   and  chronic   effects.


2,3,7,8-TCDD adversely affects the  skin, the  liver, the nervous system, and the  immune
                 r

system of humans  and animals. As evidenced by its high  cancer potency slope  factor


(Q!*),  2,3,7,8-TCDD  is  quite  potent  compared to  other  known carcinogens,  and  is


classified  a probable carcinogen in humans on the basis of  animal carcinogenicity studies


which were positive in multiple  species and organs.


     Although CDDs have never been intentionally produced  as an industrial product for


wide distribution, they are generated as  a by-product by  many  different sources  (U.S.


EPA, 1980a,  1986d), including:  processes for  production of chlorinated phenol; processes


for production of chemicals using chlorophenols; combustion processes in  industrial and


municipal  incinerators;  automobile  exhaust;   processes   resulting   in   wastes  from


pentachlorophenol wood  treating operations;  and  processes  involved  in  production of


bleached kraft paper products.


     Additionally, CDDs have been detected in human mothers' milk (Gross, 1982), and it


has been  suggested  that CDDs  may be formed  in forest  fires (Sheffield,  1985).   It is


beyond the scope of this paper  to address the ways in which all of these  various sources


contribute to human exposure.  Many of these sources of CDDs can result in air, water,


and soil contamination; some of the exposure  pathways that  might  be associated  with


some of the sources are addressed in detail in  Chapter 6.

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     It has been concluded by the Centers for Disease Control that 2,3,7,8-TCDD soji




concentrations  above  1  ppb  in residential areas  raise  concerns  about  health  risks




(Kimbrough et al., 1984).




     Human  exposure is likely to result from ingestion of contaminated fish, beef, dairy




products,  and other foods; ingestion  of contaminated soil, especially by children with pica




tendencies; from dermal contact with 2,3,7,8-TCDD-contaminated soil, dust, and sediment;




and from  inhalation of contaminated dust and 2,3,7,8-TCDD vapors.




     This report is  divided into two  parts.  Part One' (Chapters 2  to  5)  presents  an




update of previous work  and an  analysis of  key  issues related to exposure assessment for




CDDs, with emphasis on  2,3,7,8-TCDD.  The updated information builds upon exposure




assessment methods and general  concepts developed as part of the Dioxin Strategy (U.S.




EPA,  1983)  and published  by the  Exposure  Assessment Group  in  November of  1984




(Schaum,  1984).  The 1984 document includes standard factors, assumptions, computation




methods,  and  nomographs  for  estimating  exposure  under  various  exposure  scenarios




involving  2,3,7,8-TCDD-contaminated  soil.   Schaum  (1984)  addressed five pathways  of




exposure:  dust  inhalation,  fish  ingestion,  dermal  absorption  from  soil contact, soil




ingestion, and ingestion  of beef and  dairy products.   In the interim,  results of new




studies have  provided information and  an understanding of  scientific issues which now




enable us to  make more informed judgments regarding qualitative  and  quantitative inputs




to exposure assessments for 2,3,7,8-TCDD and related compounds,  including the ability to




make estimates of exposure through  a number of additional  exposure pathways.  This new




information  has  enabled  us to  construct   more realistic  scenarios,  narrow  ranges  of




estimates  for parameter  input values, broaden  the  scope  of  assessments by  including




municipal waste incinerators and disposal of fly  ash generated from the incinerators, and




thus to lessen the degree of uncertainty in resulting exposure assessments.

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     Several  of the items discussed in this update report were originally identified  in the



1984 document.  An expanded and updated analysis is provided relative to the  physical



and  chemical properties  of 2,3,7,8-TCDD,  the behavior of  2,3,7,8-TCDD in soil  and




sediment, the concentrations of 2,3,7,8-TCDD in indoor versus outdoor dust and soil, and




inclusion  of  additional pathways.  Also discussed are  biologically related issues such as




bioavailability from soil; body  weight and respiration rates; absorption rates of soil-sorbed




2,3,7,8-TCDD through human lung, gut, and skin; consumption rates for fish, beef, and




dairy products; soil ingestion rates; and bioaccumulation in fish, beef, and dairy products.




Methods  for considering exposure due  to  inhalation of vapor-phase  2,3,7,8-TCDD are




presented; exposures  due to inhalation of dust from vehicular  traffic,  and loading and




unloading of ash are  considered; food chain contamination by direct and  indirect routes is




incorporated;   and  the  analysis  of  pharmacokinetics  for estimating  exposure  to




2,3,7,8-TCDD is discussed.   Available information on the plant uptake of 2,3,7,8-TCDD is




incorporated in estimating human exposures to make the inclusion of pertinent exposure




pathways as complete as possible.




     Part Two (Chapters 6  and 7) of this report shows how the refinements discussed in




Part One can  be put  to use  in a new  set of calculated exposure  scenarios.   Twenty




scenarios  are calculated, each  one  considering many  different exposure  pathways, and




these exposures  are  converted  into risk estimates.    For scenarios  1-15, which  cover




contaminated soil,  open dumps, abandoned dumps, and a capped landfill, contamination




levels of  2,3,7,8-TCDD of  one part per trillion show relatively  low exposures in most




pathways of these scenarios.   Future developments in the areas of  bioavailability and




pharmacokinetic   modeling   may  substantially  improve  our confidence  in  exposure




assessment for 2,3,7,8-TCDD.




     As  part  of assessing  exposure  associated  with  releases  of  the emissions  from




combustion devices and the  disposal of fly  ash collected  in  control  equipment,  two

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municipal waste incinerators with different capacities and levels of control are considered


for evaluation.  The exposure assessment scenarios presented here (scenarios 16-20) differ


from the traditional approach in that exposure from multimedia pathways is evaluated in


addition to the direct inhalation pathway, and exposure associated  with disposal of fly


ash is considered.


     The  risk numbers calculated in the Appendix  relate  to the  individual  scenarios


chosen, and  the reader  is again cautioned that application of these numbers to specific


(actual) sites  is not appropriate  without a careful examination of  the  circumstances that


exist at the site relative to the scenario assumptions.


B.  CONCLUSIONS


     The  authors  are in consensus on the following  conclusions.  Where risk  is discussed,


it refers to the upper bound incremental lifetime cancer risk only.


     (1)  For the scenarios  considered in the report (contaminated soil, dumps, municipal


          waste   incinerators)   where  2,3,7,8-TCDD  was  openly  available  to  the


          environment  (i.e.,  not  capped in a  landfill),  the  highest  exposures and


          consequent  risks were associated with the food chain (e.g., plants, beef, fish,


          dairy products).   The  apparent  reasons for  this include  the tendency  of


          2,3,7,8-TCDD to partition and accumulate  in  organic  substances, the higher


          access  humans  have  to  contamination  through  these  pathways,  and  the


          activities of the  populations which may make it  more likely to  be exposed


          through these  pathways  than through other pathways  such as  soil ingestion,


          dust inhalation, and dermal contact with soil.


     (2)  Reasonable  worst case scenarios illustrate that in the  absence of any controls


          on disposal of 2,3,7,8-TCDD-contaminated material at the  1 ppb level, exposure

                                                          >j
          may result in increased cancer risks as high as  10"^ as shown in the Appendix.


          However, careful handling and  disposal  of contaminated  material  in  both the

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     landfill and incinerator ash scenarios (e.g., capping properly designed  landfills

     or  monofills,  proper  incinerator  design,  runoff  control,  etc.)  results  in

     predicted exposures correlated to substantially  reduced risks  (10~^ or below).

     Exposures calculated  for  contaminated materials of 1  ppt or below  in land-

     related scenarios were low  in all cases regardless of  controls,  except for the

     reasonable worst case  soil  contamination scenarios, where the pathway with the

     highest exposure was correlated with a risk in the range of  10"^.

(3)   For  the  two incinerator  capacities considered,  poor  operating  practice  and

     improper control of stack  emissions resulted  in higher exposures and risks with

     the  smaller  capacity  unit.    In all scenarios  dealing with  stack emissions,

     highest exposures and risks were associated  with indirect  routes of  exposure

     (e.g., dairy products,  beef)  in contrast to the direct inhalation pathway.   The

     apparent  reasons  for  this  would be similar to the ones  described in earlier

     conclusions coupled with the deposition of particulate and vapor 2,3,7,8-TCDD

     on land, water and fodder over the lifetime of incinerator operation.

(4)   Fly  ash  disposal  scenarios   illustrate  that  in  the  absence  of containment

     measures such as landfill cap, exposure  may be significant especially for the

     population that derives some  of  its  food from a  farm operation located  in the

     vicinity of the disposal site (see Appendix for risk estimates).
             ;
(5)   Recent  literature  is  divided  and  seemingly contradictory  on  the  issue of

     whether,  and  how  much,   2,3,7,8-TCDD  is  taken  up into  plants  from

     contaminated soil.   The authors  of  this report  conclude that  there  is evidence

     that 2,3,7,8-TCDD is  taken up by plants  growing in contaminated soils, but the

     amount taken up, or subsequent  transport within  the plant  itself (say,  to edible

     portions) is  very uncertain.   The  worst-case  calculations (using  the  highest

     plant-to-soil ratio  from the literature) result in  very  high exposures, at least

-------
     as high as all other pathways.  On the other hand, using other values from the




     literature would result in exposures of little concern.



(6)   The properties of 2,3,7,8-TCDD  make widespread ground water contamination




     from landfills unlikely, provided  uncontaminated water  filters  through  the




     capped landfill.  Preliminary calculations of the effects of codisposed solvents




     indicate a slight increase in solubility of 2,3,7,8-TCDD with one-phase solutions




     (i.e., saturated solutions or moderate mixtures of miscible solvents with water),




     but  the  effect of this solubility  increase on  mobility has  not  been fully




     investigated.  For  systems  where two distinct liquid phases exist (water and a




     relatively nonpolar  organic solvent), the authors believe much greater mobility




     of  2,3,7,8-TCDD  is  possible.  For these cases, and  in cases where  physical




     transport  of soil  particles  to  ground  water  can occur,  there  may  be  an




     associated threat to ground water.




(7)   The weight of evidence  indicates that 2,3,7,8-TCDD is often bioavailable from




     contaminated soils, although  certain soils may bind 2,3,7,8-TCDD very tightly,




     decreasing the bioavailability by an order of magnitude or more.  The reasons




     for this difference in bioavailability from  one  material to another  is not well




     understood at this  time.  The data base upon which this conclusion  is drawn is




     very slim.   The implications of this conclusion are that after additional data




     are collected, sufficient  to draw  more firm conclusions, bioavailability may be




     an important factor in site-specific  assessments.




(8)   Pharmacokinetics have been considered  in order to calculate, from body burden




     data, "background" daily intake levels in the U.S. population. " While the data




     do  not allow an estimation of  an average body  burden in the U.S. population




     from which  to calculate an average daily intake, an upper limit of  6.72 ppt in




     the adipose  tissue  has  been estimated.   From  this upper  bound  estimate of

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          body burden, the  upper bound daily  intake  ranges  from  0.04  pg/kg to 0.51




          pg/kg.   The  upper limit of risk which results from such  estimates is then




          compared with the annual cancer incidence in the U.S.   Further aims,  future




          research and application goals regarding physiologically  based pharmacokinetic




          models  are discussed.




     (9)   The authors believe that a significant amount of uncertainty in the exposure




          assessment could be reduced by a focused, limited research  program  addressing




          the areas where critical  information  is  needed.   These  areas are outlined in




          the section for recommendations, below.




C.  RECOMMENDATIONS




     The authors  believe  that,  should  additional work  be  necessary  to reduce the




uncertainty  in exposure estimates for  2,3,7,8-TCDD,  the following areas  are  important.




They are listed in priority order (highest first) in the ability to address major areas of




uncertainty  having an impact on the overall assessment.




     (1)   Because of the uncertainty of many orders of magnitude, and the possibility of




          the exposures  being significant, it is  the authors1 consensus  that the area of




          plant uptake  and  transport  of 2,3,7,8-TCDD within the  plant, especially to




          edible portions  for both  humans and  animals,  is a major area needing further




          work.




     (2)   In  addition  to  being  an  aid  for   the  calculation  of  background   levels,




          pharmacokinetics  may also  assist  in  determining  background levels in soils,




          target organ dose,  absorbed  dose, lactational/placental transfers,  and effects on




          offspring.    For this  reason, the  authors  feel that pharmacokinetics  is  an




          important area for  future work.




     (3)   The  bioavailability data base  is  very  slim,  yet for  site-specific  situations,




          bioavailability  may be  a  very  important issue.    The authors recommend






                                            8

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     additional  work to determine whether a  simple  test for bioavailability  can be




     developed, and if so, to develop guidance on  how the results of such  a  test




     could be interpreted for exposure assessments.




(4)   The potential effect  of solvents  on 2,3,7,8-TCDD  mobility in soils is another




     area where the authors feel that additional work  may  help  fill  a significant




     gap in the  assessment.




(5)   The authors  feel that  additional  work  in  the  areas  of  erosion  factors,




     distribution factors for fish, degradation  rates of 2,3,7,8-TCDD  in various



     media, and in understanding the vapor/particulate behavior of 2,3,7,8-TCDD in




     stack emissions  would  all  lead to significant  reductions of  uncertainty in




     important parts of the assessment.

-------
                            PART ONE




AN UPDATE OF CURRENT KNOWLEDGE AND METHODS FOR PERFORMING




              EXPOSURE ASSESSMENTS FOR 2,3,7,8-TCDD
                                 10

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2.  PHYSICAL/CHEMICAL PROPERTIES AND GENERAL EXPOSURE PARAMETERS




     In the past few years, there  have been several refinements in  what is known about




general exposure parameters (e.g.,  pulmonary ventilation rates and human body weights as




a function of age and sex) and also in what is known of the properties of 2,3,7,8-TCDD.




Most of these  refinements have little  effect on exposure  assessments, but they add to




our  confidence in  such assessments  by making  the  input  data more  precise.   Updated




input data include revised  Henry's law constant which would be a factor in  predicting the




volatilization potential  of 2,3,7,8-TCDD,  and  recent work on  increased  solubility  of




2,3,7,8-TCDD  when other organic materials are present.  In the past the volatilization




potential of high molecular weight organics such as 2,3,7,8-TCDD had been neglected by




many exposure assessors.   This  chapter will discuss the refinements to our knowledge in




the areas  of general  exposure parameters and physical and chemical properties including




solubility  enhancement.  Implications of  the increased importance of volatilization from




soil and water are developed more fully in Chapter  4.




A.  PHYSICAL/CHEMICAL PROPERTIES




     Knowledge of the  basic physical and chemical  properties of 2,3,7,8-TCDD is essential




to  understanding  or  modeling  its  environmental transport  and  fate  as well  as  its




pharmacokinetic  or  toxicologic  behavior.   The  most essential parameters  appear to  be




vapor pressure  (Pv), octanol/water partition coefficient (Kow),  and  water solubility (Sw).




Numerous other  important but  less  frequently  investigated parameters are available by



derivation  or  through published   correlations,   e.g.,  to  soil  or  sediment  partition



coefficients and bioconcentration  factors  (Lyman  et  al.,  1982,  Chapters  4  and  5




respectively).   The  ratio  of  Pv  to  Sw  (PV/SW)  yields  Henry's law  constant  (Hc)  for



low-solubility organic compounds, an index of partitioning  for a compound between the




atmosphere and the water phase  (Mackay et al., 1982).
                                           11

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     Brief summaries of recent scientific  articles on the physical-chemical properties of



2,3,7,8-TCDD  and some  related compounds  are provided in the following paragraphs.




These have been chosen based  on credibility of experimental methods and results.  No




discussion relative to earlier findings is included here, although such discussion usually  is




offered in the  original  papers and  in reviews such as Webster et al. (1985), Schroy et al.




(1985a),  and Mackay et al. (1985).  [The  most  recent comprehensive list of the  physical




properties of 2,3,7,8-TCDD is found in Schroy et al. (1985a).]




     Podoll et  al. (1986) recently  measured the vapor  pressure  of  2,3,7,8-TCDD using




l^C-labeled  2,3,7,8-TCDD and a gas saturation technique  followed  by  combustion to




^CO2-   The mean value and standard error of five determinations were 7.4 ± 0.4  x




10"'0 mm Hg  at 25°C. Henry's law constant was then calculated as 12 mm Hg  M~^ (or




1.6 x 10"5  atm m^  mol"1), using a water solubility reported  by Marple et al.  (1986a).




Based on this  Henry's  law constant, Lyman  et al.  (1982) offers guidelines, though not




specific  to  2,3,7,8-TCDD, to  compare organic  compounds that  may  or may  not  be




volatilized from water  at a significant amount, and provides the ranges of Henry's law




constant at which volatilization  represents  "significant transfer mechanisms" and at which




volatilization would  be insignificant.   The compound  listed as having the potential for




volatilization include polycyclic  aromatic  hydrocarbons and  other halogenated aromatics




such as  PCBs.  Further  discussion can be found  in Section B of Chapter 4.




     Marple  et   al.  (1986b)  reported  the  octanol/water  partition  coefficient  of




2,3,7,8-TCDD  as (4.24  ± 2.73)  x 106 at 22 ±  1°C.  Two similar experimental  techniques




were  used,  but the  more  expeditious and reliable one  involved equilibration  of octanol



presaturated  with  water and containing the 2,3,7,8-TCDD, with water, presaturated with




octanol,  over 6 to 31  days.




     Burkhard and  Kuehl (1986)  used  reverse-phase HPLC   and LRMS detection  to




determine  octanol/water partition  coefficients  for  2,3,7,8-TCDD and a series of seven






                                           12

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other  tetrachlorinated  planar  molecules,  including  three  more  TCDD  isomers  and




2,3,7,8-tetrachlorodibenzofuran  (TCDF).   Log Kow  = 7.02 ±   0.50 was reported for




2,3,7,8-TCDD.   These  authors also  reevaluated  data on 13  chlorinated dioxins  and




dibenzofurans previously obtained by  Sarna  et  al. (1984) by very  similar experimental




techniques.   In  the reevaluation, Burkhard  and Kuehl (1986) used experimental  rather



than estimated log Kow values in correlations with gas chromatographic retention  time.




This approach yielded log octanol-water partition coefficients ranging from about 4.0 for




the non-chlorinated parent molecules  to about 8.6 for the octa-chlorinated compounds,




much lower than  previously reported.  Coefficients in this range usually  mean  that the




substance tends to adsorb strongly to organic components in the soil.




     The water  solubility of 2,3,7,8-TCDD recently was reported as 19.3 ± 3.7 parts per




trillion  at 22°C  (or 5.99 ±  1.15 x  10'11  M)  by Marple et al. (1986a) after equilibrating




thin films of resublimed 2,3,7,8-TCDD  with a small volume of water  followed by gas



chromatography (GC) analysis  with  "•'Ni electron capture detection.   A corresponding




experiment using radiolabeled 2,3,7,8-TCDD and GC plus  scintillation counting was found




to  be  less  reliable due to  only  80% purity of  radio-labeled versus  98%  purity of




non-radiolabeled material, low  scintillation count rates (three to four times background)




and unexplained losses after equilibration.




     The very low solubility of 2,3,7,8-TCDD would imply a low likelihood of leaching to




ground water from the soil  surface if pure water were  the only  transporting  medium.




However, some  hazardous waste  landfill  leachates  may be viewed as  mixed solvent




systems, with an aqueous phase containing a  variety of man-made organic chemicals and




possibly a second, organic  phase which could dissolve and transport significant amounts




of  chemicals  like  2,3,7,8-TCDD having   very   low solubilities  in  pure  water  or




predominantly aqueous  mixed solvents (demonstrated below).  [Solubility of 2,3,7,8-TCDD




has been reported for benzene (570 mg/L), methanol  (10 mg/L), and acetone (110 mg/L)






                                           13

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(U.S.  EPA,  1980a)].    Naturally,   partition  coefficients   could  be  determined   for



2,3,7,8-TCDD between  water and any other solvent not miscible with water  (i.e.,  any




solvent which forms a second phase; one not soluble in all proportions).  More details on




mixed solvent effects on solvent solubility follow shortly.



     Recent work  by Kapila et al. (1987) focused on the role of a non-polar dispersing




medium on  the  future  fate  and transport of  2,3,7,8-TCDD  in  contact with soil.   The




medium involved in a pollution incident which occurred at Times Beach, MO (used motor




oil mixed with 2,4,5-T process still bottom materials) likely would exist as a second phase




if in contact with  ground water.  No contact with an experimental equivalent of ground




water  was involved in the work of Kapila et al. (1987),  although contact with an aqueous




phase  in an unsaturated zone  was introduced through  simulated rainfall.  Their  results




suggested  that 2,3,7,8-TCDD migration through soil and losses due to volatilization and




photolysis or due to surface photolysis  alone appear much lower  than previously reported




in the literature.




     In  addition,  the  effects  of dissolved  organic  matter  and very  finely divided




suspended  solids  on measurement  of partition  coefficients have  been  discussed  in




numerous publications reviewed by  Lyman and  Loreti (1987).   The dissolved  organic




matter of surface  waters and ground water  both  before and  after pollution shows wide




variability  in  sorption  capacity, especially  for  hydrophobic  chemicals,  although  the




potential effect of its presence must  be increased transport of sorbed  pollutants.  Details




and  examples of this and other factors  affecting sorption, such as pH  and ionic strength,




are available in Lyman and Loreti (1987).




     A "solids concentration  effect"  connected with the presence of very fine suspended




solids  is characterized by a decrease in sorption constant with increasing soil or sediment




oncentration and is believed  to  be due to  the  presence of microparticles not removed by




standard  filtration or centrifuging procedures.  Lyman and  Loreti (1987)  note  that this






                                            14

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phenomenon  often  was not acknowledged in studies published before 1980 and also cite




studies  demonstrating  that levels  of  microparticles  (or  "non-settleable  solids")  can




increase  as  a  result  of  chemical,  mechanical  or  thermal  modifications to  soils or




sediments which tend to break down the soil matrix in non-reproducible ways.  Examples




of techniques which can  yield test  materials much  different from  the  original soil or




sediment include pH adjustment, ionic-strength adjustments,  drying  and/or sterilization,




grinding,  sieving  and  extended  mixing  times.    In-depth  discussion  of  the  solids




concentration effect also is presented in Lyman and Loreti (1987).



     Because little  information currently  is available on the frequency of occurrence of a



second liquid phase in  contact with ground water, description of pollutant transport in a




second phase is viewed as a topic for future consideration.




     The potential  effect on solubility of organics  in mixed water/organic  solvent systems




is well  known.  A variety  of  thermodynamic  approaches  have  been  developed  for




estimating solute  solubility  in  mixed  solvent  systems  (reviewed in U.S.  EPA,  1985d).




More  recently,  Webster   et  al.  (1986)   reported  on  adsorption   and  transport of




1,3,6,8-TCDD  on dissolved and suspended organics (humic and fulvic acids) in natural




waters.  Investigators  also  have reported on the solubility and sorption properties  of a




number  of aromatic organic compounds in methanol/water  and acetone/water  systems




(Nkedi-Kizza et al., 1985;  U.S. EPA, 1985d; Fu and Luthy,  1986).  (Because methanol and




acetone are miscible with water no second phase would form.)




     Earlier  work by  Yalkowsky  et al. (1972) related solubility of organics in water and




binary solvents by showing a semi-logarithmic  increase  in  solubility  with  increasing




volume fraction of  organic solvent,








                                 In Sm = In Sw + of0                      (2-1)
                                           15

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where  Sm = solute solubility in mixed solvent (moles/L), Sw = solute solubility in water,




a = a system-specific empirical parameter related to surface area and surface free energy




of solute, and f° = volume fraction of organic cosolvent, 0 < f° < 1.




     Nkedi-Kizza et al. (1985)  noted an exponential decrease  in sorption coefficient with




increasing fraction of cosolvent  for both methanol/water and acetone/water systems,








                                 In (Km/Kw) - -aof0                       (2-2)








where  Km = sorption coefficient in mixed solvent  systems, Kw = sorption coefficient in




water,  and a = an empirical constant.  These investigators also found that a was unique




to each sorbate (organic solute)/mixed solvent combination and was independent of the




soil (sorbent) used  in  different experiments, suggesting  that  this might be an  unusual




site-independent phenomenon.




     A similar exponential or semi-logarithmic relationship between solubility and  fraction




of organic cosolvent was reported  in  U.S.  EPA (1985d), where  it was also  noted that




solubility increases  upon adding  a  fixed  amount of cosolvent  are most pronounced for




very hydrophobic compounds (such as 2,3,7,8-TCDD). It was also noted  that increases in




solubility with  increasing fraction  of  organic cosolvent did not  result  in  directly




proportional  decreases  in the sorption coefficient.   (This effect is attributed  to  solvent




swelling of  the soil organic carbon material and a  corresponding increase in accessibility




of the  latter for sorption.)




     Equation  2-1  may  be applied  to  the  question  of 2,3,7,8-TCDD  solubility  in




methanol/water mixed  solvents, since the Hildebrand solubility parameters (5) of methanol




(15.15  calories1/2 cm~3/2)  and  water (23.50  calories1/2 cm"3/2) are more than three units




larger  than  that  of 2,3,7,8-TCDD (approximately 10 calories1/2 cm~3/2) (Martin et al.,




1982).   A technique described  in U.S. EPA (1985d, p. 107) may be used to approximate






                                            16

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the solubility parameter, a, for 2,3,7,8-TCDD in a  mixed  solvent  system if the solute




solubility in  both pure solvents is known.  The solubility  parameter estimate is obtained




by taking the difference between  the  log of solute solubility in pure solvent and  the  log




of solute solubility in pure water.




     Substituting  into  Equation 2-1,  the calculated  solubility of 2,3,7,8-TCDD in  1%




methanol/water (by volume) is 14% greater than in  pure water  (22.0  ng/L  versus 19.3




ng/L, a  1.14-fold increase).  In 10% methanol/water, 2,3,7,8-TCDD solubility is predicted




to be 7.19 ng/L, or a 3.73-fold increase, while in the environmentally unrealistic  case of



50% methanol/water, solubility should increase to 13,800 ng/L (a  715-fold increase).  If




similar calculations are performed  for a saturated  solution of benzene in water (1.78 g/L),




2,3,7,8-TCDD solubility is  predicted to be  20.0 ng/L (1.036-fold, or less  than a  4%



increase).  The application  criteria  for the use of Equation 2-1, referred to earlier,  are




not  fully satisfied  for  2,3,7,8-TCDD in benzene/water,  but generally this only poses




problems at high-volume fractions.




     Increases in  solubility  due  to the presence of  cosolvents  thus  are predicted  as




relatively small for low  percentages of  cosolvent (typical  in landfills), as  a consequence




of  the  logarithmic variation  of solubility with  linear  variation  in  volume  fraction of




cosolvent.    Walters  et al.  (1987)  recently reported  measuring  sorption isotherms  for




2,3,7,8-TCDD in  soil/water and soil/water/methanol systems. Isotherms were  linear up to



0.5 of solubility  and logarithmic variation  of solubility and partition coefficients with




linear variation of fraction cosolvent was confirmed.  (Further details await publication.)




     In summary, prediction of increased solubility for hydrophobic solutes is feasible  for




binary systems of related  solvents, either  through UNIFAC  calculations  (from  activity




coefficients)  or   through existing  information  in  the  literature,  which might allow




calculation  of a  and/or o. for  the  desired  cosolvent/solute combination.    UNIFAC




calculations apparently have not yet  been published.






                                            17

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     For ease  of reference  and comparison,  the  results of at least  two  experimental

determinations  for Pv, Sw, and Kow have been included in Table 2-1.

     Changes  in  the vapor pressure,  pure  water solubility, and octanol/water  partition

coefficient of the properties of 2,3,7,8-TCDD between Schaum (1984) and the values cited

above  will  have  negligible effect  on exposures calculated  for any of  the five  routes

covered in Schaum (1984).  The major influence of changes in  vapor pressure and water

solubility (hence  Henry's  law  constant) concerns volatilization from water and soils.  The

effect  of  volatilization on potential exposure to 2,3,7,8-TCDD is discussed in  greater

detail in Section B  of Chapter 4.

B.  BODY  WEIGHTS AND PULMONARY VENTILATION RATES IN EXPOSURE
     ASSESSMENTS

1.  Body Weights

     The   performance  of  representative  exposure  assessments  requires   the  use  of

appropriate physiological  parameters.  Traditionally, the assumption was made that  human

body weight  was  equal  to   70 kg, which  represented  the typical  U.S.  male.  When

calculations are made  for large populations, this is  a valid and acceptable number. When

considering smaller numbers  of individuals or subpopulations of concern (e.g., children), a

different value might be more appropriate.

     In a   report  on risks   from  2,3,7,8-TCDD-contaminated soil  (Schaum,  1984),  a

procedure  was presented  which allowed average  body  weight to  be considered as   a

function of age,  in particular for individuals under  18 years old (those 18 years of age or

older were considered to  be  70 kg).  One of the  concerns in  that report  was to obtain

representative  values for  small  children  who  had a tendency to ingest soil,  so that more

appropriate exposure values could be calculated.

     A more  recent report,  entitled "Development  of Statistical Distributions or  Ranges

of Standard Factors Used in Exposure  Assessments" (U.S.  EPA, 1985a),  refines the
                                           18

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                    TABLE 2-1.  PROPERTIES OF 2,3,7,8-TCDD
Structure of 2,3,7,8-TCDD:


Molecular Weight:   322
                   Cl

                   Cl
                                                O
                                 O
                   Cl

                   Cl
Property
Value      Temp.(°C)     Method
              Reference
Vapor pressure
(x 10'9 mm Hg)
               3.49 ± 0.55    30.1
               1.52
Water solubility
(ppt = ng/L)
              19.3  ± 3.7
Octanol/water partition
coefficient (x  106)

               6.9 ± 1.6
              14.5 ± 1.6
              25
               0.74 ± 0.04    25
              22
               7.91 ± 2.7     25
              25
               4.24 ± 2.73    22


              10.5 ± 1.1
              25
Gas saturation,
GC/MS

Extrapolation
                            Gas saturation,
                            combustion
Schroy et al.
(1985a)

Schroy et al.
(1985a)

Podoll et al.
(1986)
Thin film          Marple et al.
equil., GC/LRMS   (1986a)

                   Adams and Elaine
                   (1986)
Fragment
     additivity

Diffusion,
     GC/LRMS

HPLC
Fragment
     additivity
U.S. EPA (1981a)
Marple et al.
(1986b)

Burkhard and Kuehl
(1986)

U.S. EPA (1984a)
                                          19

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treatment of body weight.   It provides  weight data  on  age-sex distributions  (with




percentiles)  for tailoring exposure assessments to whatever level of detail is necessary.




     The source of the data for the above report was the second  National  Health and




Nutrition Examination  Survey, conducted from 1976  to 1980 (National Center for Health




Statistics, as referenced in  U.S.  EPA, 1985a).  The survey  was a probability sampling of




approximately 28,000  people from  the  ages of 6 months  to 74 years.   Being concerned




with  nutrition,  the survey oversampled  subpopulations  thought to be  at  high  risk of




malnutrition.




2. Pulmonary Ventilation Rates




     One of the most  critical and variable  factors in considering the inhalation route in




exposure assessments is the pulmonary  ventilation rate.   Respiration is usually  presented




as a flow rate and denoted as  minute volume (L/min or  m^/d).  Minute volume is the




product  of the amount of air moved during  each cycle (tidal volume  = 0.5 L) and  the rate




of respiration.




     The resting  ventilation rate  is related to an individual's  basal metabolic rate for




oxygen consumption, and  is  reported as 7.5 L/min (0.5 L  x 15 breaths/minute).  As the




activity  of  individuals  increases,  so does  their  metabolism and,  hence, the ventilation




rate.   To obtain a representative description of exposure,  information  on the activity, its




duration, and the  associated ventilation rates must be integrated.   A  report  by the U.S.




EPA  (1985a) on standard  factors provides tables on  distributions of minute volumes and




activity  levels and patterns for  various age-sex groups.  These data are especially useful




in  situations when subpopulations  are being considered  for  their particular exposure




levels.




     Some  factors  to  consider  in addressing ventilation  rates relate  to individuals  in




compromised states, such  as emphysema, fibrosis, or those changes  that occur  with age.




The U.S. EPA  (1985a) report  contains a  table  listing  various formulae for calculating






                                            20

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minute volume (empirically) based on variables including surface area, weight, height, age,




and  sex.  It should be  noted that  little information is available for preschool children,




due mainly to the problems involved in clinically studying this age group.




     Activity levels can be categorized  as light, moderate, or heavy according  to criteria




developed by the Environmental Criteria and Assessment Office, RTF [Air Quality Criteria




for Ozone  and Other  Photochemical Oxidants, June  1984; as cited in U.S. EPA (1985)].




The  estimated  ventilation  rates for these  different activity levels, which were originally




presented  in Table  4-3  of  the  U.S. EPA (1985a)  report  on  standard  factors,  are



reproduced here for the convenience of the reader (Table 2-2).



     The activity patterns,  when  used  with  the  ventilation  data,  will  provide  a




time-weighted  average  ventilation  rate  for use  in  assessment.   The data on activity




patterns  indicate  the  time  which  individuals  might spend  at  various activities  or in




different microenvironments.  This  type of data is especially useful when focusing on the




specific  locations of  individuals' exposure.  These activity data  are  averaged for both




sexes and all age groups.   Appendix D in the above-referenced report contains detailed



information on activity patterns for 56 population subgroups.




     When  performing  assessments  for  general populations, the  ventilation  rates (U.S.




EPA, 1985a) and activity pattern data [93% light activity, 6% moderate,  and 1%  heavy




(U.S. EPA,  1985a)] can be combined as follows to  provide  an approximate overall daily



ventilation rate:








                      Ventilation rate = [(22.4 hr/d x  13.8 L/min)            (2-3)




                               + (1.4 hr/d x 40.9 L/min)




            + (0.2 hr/d  x 80 L/min)] / (1,000 L/m3 x hr/60 min) = 23 m3/d
                                            21

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This value is the same as that reported  in a previous EAG report (Schaum, 1984), and  is




similar to values used traditionally that range from  20 to  23 m3/d as  a daily ventilation




rate.
                                            22

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              TABLE 2-2. ESTIMATED MINUTE VENTILATION ASSOCIATED WITH
                          ACTIVITY LEVEL FOR AVERAGE MALE ADULT
Level
of
work
Light
Light
Light
Watts kg-m/mina
25 150
50 300
75 450
L/min
13
19
25
Representative activities
Level walking at 2 mph;
washing clothes
Level walking at 3 mph;
bowling; scrubbing floors
Dancing; pushing
Moderate
Severe
100
300
600
1,800
30
Moderate
Moderate
Heavy
Heavy
Very heavy
Very heavy
125
150
175
200
225
250
750
900
1,050
1,200
1,350
1,500
35
40
55
63
72
85
100+
wheelbarrow  with   15-kg
load;  simple  construction;
stacking firewood

Easy    cycling;    pushing
wheelbarrow  with   75-kg
load; using sledge hammer

Climbing  stairs;  playing
tennis; digging with spade

Cycling at 13 mph; walking
on snow; digging trenches

Cross-country skiing; rock
climbing; stair climbing
with  load;  playing squash
and handball

chopping with axe

Level running at 10 mph;
competitive cycling

Competitive   long  distance
running;    cross-country
skiing
akg-m/min = work performed each minute to move a mass of 1 kg through a vertical
distance of 1 m against the  force of gravity.

SOURCE: Adapted from U.S. EPA, 1985a.
                                         23

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3.  FATE



     Recent information on the fate of 2,3,7,8-TCDD in soil and sediments tends to




confirm previous findings on this subject.  Once 2,3,7,8-TCDD is in the soil.the chemical




and biological degradation  processes are very slow, with half-lives estimated in tens of




years or longer. Although 2,3,7,8-TCDD has a  low solubility and low vapor pressure, the




long-term (years-to-decades) soil-moisture-interstitial air partitioning system will lead to




slow movement of the chemical. In systems where the contamination is relatively near




the surface, it is likely that the  2,3,7,8-TCDD will migrate to the surface over time and




volatize rather  than leach into ground water. Except in unusual cases involving mobile,




organic-contaminants, large-scale leaching of 2,3,7,8-TCDD to ground water from soil is




thought to be unlikely (EPA,  1985g).  (Note, however, that some landfills may have these




very conditions.) There is little evidence to support the suggestion that photolysis at




the soil surface plays a significant role in reducing contaminant concentrations.   An




estimated biodegradation half-life of several decades would make some difference  to an




exposure assessment on a site  for a 70-year lifetime,  compared to the assumption that




the compound  does not degrade at all, perhaps lowering exposure in some scenarios by a




factor of two to four.




     Contaminated soil may also be ingested by grazing animals, potentially contaminating




foodstuffs such as meat  and dairy products.  Recent studies tend to support earlier




estimates of transfer  factors from soil to food.




     Recent  attempts to determine  the effect contaminated sediments may have on




aquatic biota have led to estimates that differ by several orders of magnitude for average




bulk water concentrations and those concentrations near the contaminated sediments.




       The following sections discuss these areas in more detail.
                                           24

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A.  FATE OF 2,3,7,8-TCDD IN SOIL




1.  Transient Behavior of TCDD Profile in Soil Layer




     In this section, a brief description will given of the manner in which concentrations




of 2,3,7,8-TCDD in the soil media can change over a period of time.  The method of




incorporating these changes into an exposure assessment will also be discussed.




     2,3,7,8-TCDD, like any other organic contaminant, can undergo transport and




transformation processes in soil. These processes may be chemical, biological or physical




in nature.  The chemical processes may include hydrolysis, photolysis (discussed in more




depth in Chapter 4), or breakdown of chemical bonds in the molecules, resulting in the




change of the contaminant to products that could be more harmful or  less harmful than




the original contaminant.  The  biological processes occur in the presence of soil microbes




to enhance the  breakdown of the contaminant to the other products.  Finally, the




physical processes can be thought  of as transport processes in which the contaminant



retains its chemical identity, but is transported from one location to another by diffusion




or advection mechanisms, and  may be transferred to different media.  Examples of




transport include diffusion of 2,3,7,8-TCDD vapor through soil pores  and ultimate




volatilization into the air, or the leaching of the contaminant into soil  by precipitation




or floods.  The severity of the  migration will be dependent on the mobility of




2,3,7,8-TCDD in the soil. As  a result, the initial concentration distribution  will change




as the contaminant is subjected to these transport and transformation processes over a




long period of time.




     As discussed above, a variety of  physical and chemical processes may affect the fate




of 2,3,7,8-TCDD in soil.  However, the most important process appears to be vapor phase




diffusion and photolysis at the surface (Freeman and Schroy, 1986). Diffusion is




discussed further in this chapter.  Photolysis  is discussed in Chapter 4.  Although
                                           25

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biodegradation appears to be a relatively unimportant process, it is also discussed in this




chapter.




     Freeman and Schroy (1986), EPA (1985b), and Tung et al. (1985) simulated the




concentration and thermal profile of 2,3,7,8-TCDD in soil with initially uniform




contamination. As time progressed, the simulated concentration profile tended to be bell




shaped, with a maximum concentration somewhere in the core of the soil column.  The




bell-shaped concentration profiles, calculated as a function of depth in soil, were




compared with the results of analyses for 2,3,7,8-TCDD in soil core samples taken at




various depths.  Samples were taken from plots at Times Beach, Missouri (EPA 1985c) and




Eglin Air Force  Base (Tung et al., 1986).  They showed good agreement between the




model simulation and the measured data in both cases.  EPA 1985c noted that "the floods




at Times Beach, Missouri, have not redistributed the TCDD over a large area," and




concluded that based on a simulation of the measured concentration profile at some time




periods, the volatilization process is a major mechanism by which 2,3,7,8-TCDD is




depleted from the soil.  EPA (1985g) used field soils to measure the soil/water partition  '




coefficients, which ranged from 3 x  104 L/kg to 1.3 x 107 L/kg, and evaluated the




teachability of 2,3,7,8-TCDD from the soils. Based on these  partition coefficients  and the




use of solute transport models, they concluded that the worst-case movement of




2,3,7,8-TCDD in leaching  from  soil media is so slow that leaching by water is




unimportant compared with other transport mechanisms, such as volatilization and




erosion.  Note that in other situations concentration profiles may differ due to




differences in mode of application and weather conditions.




      According  to EPA (1985g), EPA (1985b) and Freeman and Schroy (1986), the rate of




movement of 2,3,7,8-TCDD in soil during the leaching process is insignificant compared to




the depletion of 2,3,7,8-TCDD by volatilization.  Over a long period of time, this




depletion will create  a new profile of 2,3,7,8-TCDD concentration in soil.  This






                                           26

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redistribution should be an extremely slow process in view of the very low vapor




pressure of 2,3,7,8-TCDD.  The change of concentration profile in the soil column, along




with the effect of the soil concentration profile on the exposure evaluation, is discussed




below.




2. Transient Profile in Soil Column




     For assessment of exposures over extended periods, it is appropriate to obtain the




average concentration of 2,3,7,8-TCDD in soil over the  depth of concern and the




exposure duration.  For some pathways, this average concentration is important;  for other




pathways, surface concentrations are important. Although the surface concentration may




theoretically  appear to be relevant in some cases, the soil surface is not always



quiescent, and could be subject to disturbances due  to construction activities, erosion, or




digging.  These activities will expose the subsurface soil and make these soils available




for human exposure.




     Tung et al.  (1985) experimentally measured the variation of the soil temperature




profile as a function of depth and time of a day.  The temperature variation along the




soil column in a  typical day can affect the volatilization rate of 2,3,7,8-TCDD vapor




because certain properties of  2,3,7,8-TCDD vapor influencing the volatilization  rate is




temperature-dependent. These properties are particularly important when dealing with




low volatility organics in a soil matrix, and include  vapor pressure and diffusivity.  The




experimental data showed that the diurnal temperature variations are noticeable  at soil



depths 2 and 10  cm from the surface, and diverge to an essentially constant temperature




at a depth of 48  cm regardless of times of day.




     The significant diurnal temperature change on the  surface of soil would be an




important factor  in dealing  with volatilization  of 2,3,7,8-TCDD vapors from the shallow




surface of soil.  This phenomena would be significant during the initial stage of




contamination.  As time progresses,  the bulk concentration of contaminant will remain at






                                           27

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a depth of the soil column as demonstrated  by Freeman and Schroy (1986). Since the




2,3,7,8-TCDD vapor molecules in the soil pore in the bulk  of the soil column should




diffuse out to the air-soil interface, the bulk of the transport process occurs at the




depth where  the bulk of the contaminant is contained.  The transport process will be




affected by the vapor pressure and diffusivity corresponding to the temperature in the




bulk of the soil column. The bulk soil temperature deep inside the soil should remain




fairly constant without  being affected by the diurnal temperature variation.  In




considering landfills with depth of 10 feet or more, the bulk phenomena would be more




important that the surface phenomena when dealing with long-term exposure.




     The methods of estimating the average concentration along a soil depth are




available for  two cases  in which initially the contaminant is uniformly distributed to a




specific depth in soil.  In one case, it is assumed that contamination occurred from the




soil surface to a certain depth. In the other case, it is assumed  that the contaminated




surface is covered with a soil material of known thickness initially free of the




contaminant.  Methods  for estimating the average concentrations in these cases involve




Fourier series solutions to partial differential equations (U.S EPA,  1986a). Although it




may be a tedious process to correct for the  time- and depth-dependent concentration




variation, such a correction is particularly important for sites that were contaminated a




long time ago or are being evaluated for long-term exposures.  However, the use  of the




initial concentration in  uniformly contaminated soil will provide an upper-limit value. If




the site-specific concentration profile data are available, the maximum value for the




bell-shaped concentration profile can approximate the initial value.




     The use of cover soil initially free from  2,3,7,8-TCDD will retard exposure  for a




period of time.  The time required to contaminate a clean cover will depend on a number




of site-specific properties.  An estimate of  this time was made  assuming a 25-cm cover




thickness, 1% organic carbon content, and other typical soil properties. This estimate






                                            28

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also assumes that the 2,3,7,8-TCDD is infinitely available under the cover, no convective




transport occurs, no degradation occurs, however, equilibrium partitioning occurs between




the 2,3,7,8-TCDD adsorbed to soil and in the air space of the soil.  On this basis, it was




estimated that the 2,3,7,8-TCDD concentration adsorbed to  soil at the surface would




reach 1% of the concentration under the cover in  1,000 years and 90% of the




concentration under the cover in one million years.  The uncertainties in these estimates




could be significant, since the estimates are based on a mathematical model rather than




actual data. However, topsoils frequently contain more than 1% organic carbon and the




2,3,7,8-TCDD source will not be infinite, which suggests that the model estimates are




more likely to be low than high.




     Another site-specific property affecting volatilization rates from soil is the




temperature of the soil.  Freeman and Schroy (1986) noted that soil temperature



fluctuations were important considerations in the estimates of vapor flux rates.




     Vapor-phase diffusion can occur downward and  laterally as well as upwards.  For




near-surface contamination scenarios, the upward movement is more important, since the




chemical will probably reach the surface before it reaches the ground water. Thus,




although downward diffusion may occur at rates similar to upward diffusion, a much



longer time elapses before the chemical becomes avail able for exposure.



3.  Degradation of 2.3.7.8-TCDD in Soil




     If the concentration of  2,3,7,8-TCDD in soil changes significantly over a period of




time, the exposure evaluation should reflect this change in concentration.  Such changes




can be incrementally accounted for in the exposure computations requiring the summation




of all exposures over the  lifetime period, or, alternatively, a representative concentration




of 2,3,7,8-TCDD in soil averaged over the  exposure period can be used.




     In addition to volatilization, leaching,  and atmospheric  photolysis, which are




addressed in Chapter 4, another possible mechanism of reducing the concentration of






                                            29

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2,3,7,8-TCDD in soil is biodegradation by action of microorganisms.  Biodegradation in




soil is discussed in Section A.4 of this chapter, and biodegradation in sediment is




discussed in Section  B.I of this chapter.




     Many researchers claim that photodegradation is the primary means by which




degradation of  2,3,7,8-TCDD occurs at the soil surface.  Czuczwa and Hites (1986) studied




lake sediments  and concluded that little photolysis occurred during the long-range



transport of atmospheric 2,3,7,8-TCDD on particulates.  However, final conclusions cannot




be drawn, since the  sources of lake sediments are not known with certainty.




Additionally, this work focused on incinerator fly ash so it may not be applicable to




soils. Chemical degradation via hydrolysis and oxidation in soil is very unlikely in view




of the insignificant rate of these reactions in aquatic media (U.S. EPA, 1985b).  Recent




evidence indicates that photolytic reactivity on fly ash behaves differently from the soil




surface:  SRI found  experimentally that photolytic degradation of 2,3,7,8-TCDD on the




two types of fly ash tested is  negligible (Mill, 1987). Investigators have shown that




2,3,7,8-TCDD  on the soil surface photolyzes at a rate slower than observed in organic




solutions (Zepp et al. 1988).




     The concentration of 2,3,7,8-TCDD in environmental media may depend on the




degradation of  related congeners as well  as that of 2,3,7,8-TCDD itself.  The  process of




reductive dechlorination; more highly chlorinated congeners degrading to 2,3,7,8-TCDD,




may not occur  at a significant rate except in anaerobic microbes, where the rate would




be extremely slow.   In fact, the available data strongly suggests that more highly




chlorinated  PCDDs will not degrade to the 2,3,7,8-TCDD isomers (U.S. EPA, 1985d).




4.  Biodegradation of 2.3.7.8-TCDD in Soil




     The environmental persistence of 2,3,7,8-TCDD has created concern on  a national




level (EPA  1985g).  It is thought that one reason for this persistence is that soil




microorganisms cannot degrade 2,3,7,8-TCDD, or that they do so very slowly (Bumpus et






                                            30

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al., 1985).  However, very few studies have been done on the biodegradation of


2,3,7,8-TCDD in soil. A biodegradation rate constant and a half-life will be derived


below on the basis of the limited available information.


     Bacteria, while the most abundant of soil microorganisms, constitute less than half


of the total microbiological cell population (Alexander, 1977).  Fungi, because of their


extensive network of mycelium, usually account for a significant portion of the soil


biomass (Alexander, 1977). One of the major activities of fungi in the mycelial  state  is


the degradation  of complex molecules.  Fungi require aerobic conditions in order to

                                                                  •
degrade chemicals, and are affected by the availability of oxidizable organic substrates.


The actinomycetes become predominant in dry and cultivated areas (Alexander,  1977).


Algae, being phototrophic and having a lower population in soil than other


microorganisms, generally play an insignificant role in soil biodegradation.


     Young (1983) estimated the half-life of 2,3,7,8-TCDD on his test grid (grass field


located at Eglin Air Force Base in Florida) to be 10 to 12 years. He cited several


mechanisms to account for the disappearance of 2,3,7,8-TCDD in the herbicide applied


within the  area of his study.  Crosby and Wong (1977) had  observed that trace amounts


of 2,3,7,8-TCDD in Herbicide Orange exposed to sunlight on leaves, soil, or grass, were


apparently photodegraded during dissemination of the herbicide. On the basis of their


data, Young calculated that less than 1% of the original 2,3,7,8-TCDD that was sprayed


actually remained in  the ecosystem of the test site, and that the majority of the


remaining  1% was retained in the soil.  He reasoned that the processes of water and


wind transport of contaminated particles and biomass removal would be unimportant


mechanisms in removing the 2,3,7,8-TCDD  retained in the soil. Although he stated that


the role of volatilization and microbial degradation in removing 2,3,7,8-TCDD from soil is


not clear, he estimated the half-life as 10  to 12 years, based on observed changes in soil


concentrations.



                                           31

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     Ward and Matsumura (1978) summarized the conclusions of other investigators to the




effect that microbial degradation of 2,3,7,8-TCDD was found to be very low or




nonexistent.  Freeman and Schroy (1986) also concluded that biodegradation of 2,3,7,8-




TCDD does not occur on the basis of tests they conducted with soil from Eglin Air Force




Base. Bumpus et al. (1985) conducted experiments on the degradation of 2,3,7,8-TCDD




mixed in cultures containing the white rot fungus, and measured the rate of CC>2




evolution  as an indication of the progression of biodegradation.




     It is  difficult to analyze the Bumpus et al. (1985) data in a strict kinetics sense,




since the progress of the reaction was monitored by analyzing the reaction product (CC«2)




being evolved, and  exact stoichiometric relations between the reaction product and




2,3,7,8-TCDD are not known.  For example, the CC>2 may have evolved from oxidation of




compounds other than 2,3,7,8-TCDD.  Additionally, the applicability of experimental




conditions to actual soil conditions is rather speculative because the distribution of




microorganisms in actual versus experimental soil is different, and because fungus favors




aerobic  conditions for biodegradation.  If it is assumed that aerobic conditions are poorly




maintained in soil, except perhaps in surface layers, the biodegradation constant derived




from these data would tend to overestimate biodegradation.




     For  these reasons and  others, it is widely believed that the application of such




experiments, particularly those based on pure  cultures, to actual field conditions may be




inappropriate.  Accordingly, the results of this study  were not  applied anywhere in this




report.  However, for illustrative purposes only, a rate constant was derived from the




Bumpus et al. (1985) data.  Assuming first-order kinetics, the rate constant derived was




6.6 x 10"^ day~*. This  corresponds to a half-life of  about 29  years. It should  be noted




that these  data are applicable for one fungus type only. The effects of the presence of




other microorganisms, including bacteria, on the rate constant  cannot be evaluated at
                                            32

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present.  It appears reasonable to expect a longer half-life than that observed by Young

(1983), since his observation includes the effect of photolytic degradation.

     Once a half-life has been estimated, the exposure can be calculated under the

assumption that the concentration of 2,3,7,8-TCDD in soil varies according to first-order

kinetics.
                                       = Csoe-kt                          (3-1)
where Cs = the concentration of 2,3,7,8-TCDD in soil at any time (days) from initial

contamination at concentration Cso, and k = the rate constant (day~^).  The half-life,

tj/2,  can be given as



                               t1/2 = 0.693/k                           (3-2)



     The average concentration in soil under the influence of biodegradation 'can be

obtained by integrating Cs over the exposure time, and can be substituted for use in

exposure evaluation.  When the concentration is evaluated considering volatilization, and

based on the depth-averaging process, the initial concentration, Cso, should be replaced

by the time- and depth-averaged concentration in obtaining the concentration corrected

for biodegradation.  Alternately, exposure can  be estimated by solving for Cs at  frequent

intervals, computing exposure, and summing exposure values.  Such calculations  can be

conveniently done on a computer.  The effects of degradation on  exposure can be shown

as follows:

               (Degradation exposure)   =/Csdt/Csot = (l-e"kt)/kt          (3-3)
               (Non-degradation exposure)
                                            33

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     The non-degradation exposure is multiplied by this ratio to reflect the effects of



degradation.  The ratio of 1 assumes that biodegradation will not occur (i.e., half-life



equals infinity). The lower limit of this ratio will provide the maximum degradation.



     Microbial degradation reduces the concentration of 2,3,7,8-TCDD available for human



exposure.  Although the biodegradation rate for 2,3,7,8-TCDD has not been established, it



appears that its half-life in soil is in the range of several decades.  For purposes of



illustration, if we assume a 30-year half-life for biodegradation in soil,  approximately 80%



of the original 2,3,7,8-TCDD would have transformed to other products at the end of a



70-year (life-time)  period.  For a lifetime exposure evaluation, it is appropriate to take



into account the gradually decreasing 2,3,7,8-TCDD concentration in soil from which the



contaminant is released for human exposure. For a 70-year exposure period, Equation



3-3 indicates that at 30-year half-life causes a 50% reduction in exposure relative to an



infinite half-life (i.e., no degradation).



B.  FATE OF 2,3,7,8-TCDD IN SEDIMENTS



1. Aquatic Sediments



     Low concentrations of various CDDs have been reported to exist in sediments in the



Great Lakes and other water bodies (Czuczwa and Kites, 1986).  Czuczwa and Kites



attribute the existence of CDDs in aquatic sediments to  the long-range transport through



the atmosphere of dioxin-related material in emissions of combustion products.  Erosion



of contaminated soil may also result in accumulation of 2,3,7,8-TCDD in sediments.



Contaminated sediments will slowly release the  contaminant to the water body in



dissolved form or as suspended sediment.  The  impacts  of contaminated sediments must be



considered in  exposure estimation.



     Recent theoretical discussions (e.g., Thibodeaux e't al.,  1986) of the manner in which



2,3,7,8-TCDD may partition from sediments to water to fish and other  aquatic biota,



when compared to empirical observations (e.g., Kuehl et al, 1987b), allow some feeling for






                                           34

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the importance of the water-to-fish route for bioaccumulation as compared to the sum of




all routes (including ingestion of suspended sediment and other biota) as implied by




empirical data. The following paragraphs discuss the sediment-to-water partitioning of




2,3,7,8-TCDD, and the implications this partitioning may have for the water-to-biota




(alone) route,  as well as a way to calculate potential surface water-drinking water




concentrations due to contaminated sediments.  The section that follows (Section C)




discusses the use  of empirical data for estimating impacts of contaminated sediment on




fish.




2.  Sediment-to-Water Transport  Process




     In estimating the 2,3,7,8-TCDD concentration in a water body above a sediment of




known contamination level, it is useful to picture a system where, initially, the water is




free of 2,3,7,8-TCDD, and therefore  a concentration gradient is set up between sediment




and water, providing a driving force  for the contaminant to enter the water.  In the




process, dilution will occur as a result of mixing with the moving water and diffusion




through it.  If the 2,3,7,8-TCDD molecules reach the interface of the water body and




atmosphere, volatilization will occur.  In the process of transporting from bottom layer




to top surface, 2,3,7,8-TCDD in water may be subject to photolysis, biodegradation and




other inter-related reactions resulting in some disappearance of the contaminant.  It is a




complex process to  track the movement of 2,3,7,8-TCDD from the sediments to the




atmosphere across the  water body.




     Although the process of the transport may be inherently  transient, the average




concentration  in the water body may  approximate steady-state; that is, the concentration




in the bulk water remains  constant by assuming that the  amount of 2,3,7,8-TCDD leached



from the sediments into the water is equal to that lost to the atmosphere.  The




steady-state (non-equilibrium) process can be modeled using steady-state transport models




(Thibodeaux et al.,  1986).  The results of such  a model should represent an average value






                                           35

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of 2,3,7,8-TCDD concentration across the water body.  Impacts on the organisms




inhabiting near the sediments may be greater than the exposure estimated by this average



value.  For such organisms, the use of the equilibrium partitioning relationship will




provide an upper-bound limit of exposure (for the sediment-water-organism route alone).




The more appropriate parameter would be the sediment to organism transfer coefficient




obtained from field data.




3.  Estimation of TCDD Concentration In Water Body




     Transient aspects of diffusional processes through the sediments and water body




boundary layer will require applications of Fickian-type models.  Thibodeaux et al. (1986)




presented a simplified model based on the consideration of two-phase resistances in the




sediment and water sides, and pointed out important parameters controlling the  rate of




the contaminant transfer from sediment to water body. These parameters include the




effect of surface winds creating mixing and moving of lake water, thermal  stratification,




flow-through, and lake geometry.  The effects of these parameters are combined into




mass transfer coefficients based on experimental data (Thibodeaux and Becker, 1982).




     Although the model is based  on the widely applied two-phase resistance theory and




uses experimentally derived mass transfer coefficients, it has not been validated via field




measurement.




     The steady-state model relating the sediment and water concentrations in the




absence of chemical  reactions in the water body is given by Thibodeaux et  al. (1986) as:








                    Cw = ((kwke)/(kw+KLA)(kw+ke)-(kw)2Xl/Kd Ce)          (3-4)








where Ce = the concentration in sediment (mg/kg), Cw = the concentration in the bulk




water body (mg/L),  kw = the water-side mass transfer coefficient above sediment




(cm/hr), ke = the sediment-side mass transfer coefficient (cm/hr), KL& = the overall






                                           36

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water/air mass transfer coefficient based on water side for air-water interface (cm/hr),




and K(j = the partition coefficient between sediment and water (mg/kg sediment/mg/L




water).  It can be noted that the water body concentration, Cw, refers to the




concentration in the bulk of water, and should be distinguished from the concentration in




the vicinity  of sediments which may be close to  the equilibrium partitioning




concentration. This model is derived assuming that the sediment is the source of the




contaminant and volatilization losses to the atmosphere are the sinks, that resuspension




of sediments is negligible, and  that there is no significant inflow and outflow of water.




     Thibodeaux and Becker (1982) presented correlations for individual mass transfer




coefficients  for sediment and water sides. These correlations are as follows:



     o Water-side mass transfer coefficient







                   kw = (0.06(CDV2h5/4)/FMl/2)(pa/pw)                  (3_5)









where CD = the drag coefficient  (0.00166 for wind speed 1  to 7 m/s and 0.00237 for wind




speed 4 to 12 m/s), V =  the wind speed at 10 meters above the surface of the water




body (cm/min),  h = the average depth of the water body (cm), F = the average wind




fetch (cm),  M = the molecular  weight of 2,3,7,8-TCDD (322), pa = the air density (g/L),



and pw = the water density (g/L).




     o Sediment-side mass transfer coefficient








                       ke  = 3,600((DwE4/3)/r)                        (3-6)








where Dw = the diffusivity of  2,3,7,8-TCDD in water (cm2/s) [5.6 x 10"6  cm2/s)],  E =




the sediment porosity, and r =  the thickness of contaminated sediments  (cm).
                                           37

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     Equations 3-5 and 3-6 provide the coefficients necessary to calculate the average




2,3,7,8-TCDD concentration in the  water body using Equation 3-4. The concentration at



the water body interface above the  sediments should be closer to the equilibrium




partitioning concentration than the average water body concentration.




4. Example Calculation




     To facilitate the use of Equation 3-4 in estimating the concentration in the water




body contaminated by the presence  of 2,3,7,8-TCDD in the sediments, an example




calculation is provided below.  This example is tailored for a particular site.  For other




conditions, calculations should be performed with appropriate parameter  values and




conditions applicable to the sites.




     Suppose that a small pond is contaminated with 2,3,7,8-TCDD. For the water body,




it is assumed that the temperature is 15°C - 25°C, depth is 500 cm with  a surface  area




of 100 m x  100 m, and  the lake is unstratified.  For the sediment layer, it is assumed




that the temperature is also 15°C -  25°C, the thickness of contaminated sediments  is 10




cm,  the surface area of  contaminated sediments is also 100 m x 100 m, and the sediments




have a porosity of 50% and contain 1% organic matter.




     Other parameters assumed are  that the wind speed is 6 miles per hour, the




diffusivity of 2,3,7,8-TCDD  in water is Dw = 5.6 x 10~6 cm2/s, and the sediment/water




partition coefficient (at  1% organic  matter) at  the Koc value of 468,000 is Kj = 4,680




L/kg (Schroy et al., 1985b).  Using  these values, one can  calculate the value for kw from




Equation  3-5 as kw = 0.4 cm/hr, the value for ke from Equation 3-6 as  ke = 8 x 10~^*




cm/hr, and  the value for K-La from the two-resistance theory between the water body




and  air as KL& = 0.725  cm/hr (Thibodeaux, 1979).  Substituting these values into Equation




3-4, the  average water body concentration (Cw)  is 2.4 x 10"° ug/L when the




concentration in sediments is 10 ug/kg.  As an alternative value, an equilibrium




partitioning model  predicts the concentration to  be 2.1 x  10"^ ug/L when the






                                           38

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2,3,7,8-TCDD concentration in sediment is 10 ug/kg. For large water bodies, an




equilibrium approach for calculating average water body concentrations is unrealistic,




since equilibrium may never be attained.




     This example shows the method of using Equations 3-4, 3-5, and 3-6 to calculate




the concentration of 2,3,7,8-TCDD in the water underlain by the sediments using the




steady-state and equilibrium partitioning models.




C.  BIOACCUMULATION OF 2,3,7,8-TCDD IN  FISH AND CATTLE




1.  Bioaccumulation in Fish




     2,3,7,8-TCDD has been shown to  be bioavailable to fish from sediments and fly-ash.




Many aquatic organisms, including fish, selectively accumulate  polychlorinated




dibenzodioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs), which are substituted




at the 2, 3, 7, and 8 positions (Rappe et al.,  1981; Kuehl et al.,  1985, 1986a, b).




Furthermore, a marked preferential affinity is demonstrated by some fish for




2,3,7,8-TCDD over all other 2,3,7,8-substituted dioxin congeners in the tetra through octa




homologous groups (Kuehl et al., 1987b).  This is  believed to be due to more rapid




elimination of other TCDD isomers or,  for higher chlorinated PCDDs and  1,3,6,8-TCDD, it




may be due to a combination  of elimination  rate differences and kinetic effects involving




decreasing amounts of each isomer with respect to 2,3,7,8-TCDD in each  step along the




food chain, as well as decreased uptake rates across the gills with increasing degree of




chlorination (Cook,  1987).




     The exposure  assessment procedures detailed  in this document, as well as the



exposure assessment methods outlined in a previous document (Schaum, 1984), consider




bioaccumulation in fish as  a function of a fish/sediment distribution factor.  This




approach avoids difficulties inherent  in attempts to use  recently updated bioconcentration




factors (BCFs) for 2,3,7,8-TCDD [66,000 for carp, 97,000 and  159,000 for fathead minnows




at two exposure concentrations (Cook, 1987a)].  The  principal difficulty arises from the






                                           39

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inability to detect environmental water concentrations with the most sensitive techniques



now available.  This approach also avoids the difficulty of only using the water-to-fish




route to estimate bioconcentration, as one might do with the concentrations derived in




Section B.4 of this chapter.  By using empirical data, all routes are "lumped," making it




somewhat harder to understand and manipulate this information using theoretical models.




The fish/sediment distribution factor approach assumes that the fish and sediment are at




some "steady-state", rather than true thermodynamic equilibrium, over the exposure




period. This means that 2,3,7,8-TCDD levels in the sediment remain essentially constant




at a particular location and that fish have achieved a balance with the environment.  A




further assumption is made that the levels of 2,3,7,8-TCDD in fish from a particular




location will remain constant over time and with a constant relationship to the




2,3,7,8-TCDD level in the sediment.  Some fish species, such  as bottom feeders, will move




toward steady-state conditions faster than others.  Many species may never reach




equilibrium due to the fact that they do not spend enough time in one location, and




some species will bioaccumulate more 2,3,7,8-TCDD than others due  to greater lipid




content.




     As a first approximation, the ratio of 2,3,7,8-TCDD in fish to 2,3,7,8-TCDD in




sediment may be assumed to range from 1  to 10, as has been suggested in a variety of




studies.  For example, laboratory-derived fish/sediment ratios for 2,3,7,8-TCDD for the




catfish, Ictalurus (after only 6 days of exposure), ranged from 0.2 to 2.0, with  the higher




ratios corresponding to the less-contaminated sediment. Fish/sediment ratios for the




mosquito fish, Gambusia (after only 3 days of exposure),  ranged from 0.2 to 12.0, again




with higher ratios being calculated for the less-contaminated sediment (Isensee and Jones,




1975).  A fish/sediment ratio of 0.44 for 2,3,7,8-TCDD can be calculated for the northern




brook silverside, Laludesthes. from the laboratory data of Matsumura and  Benezet (1973);




exposure in this case was 4 to 7 days.  A field study cited by Kenaga and Morris (1983)






                                           40

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associates fish (species unspecified) 2,3,7,8-TCDD residues of 4 to 85 ppt with sediment




concentrations of 10 to 35 ppt; the means of these ranges (44.5/22.5) would indicate a




fish/sediment ratio of about 2.0.



     Newer data support the range of fish/sediment ratios presented above.  Kuehl et al.




(1987b) presented field data which indicate that carp (Cvorinus) fish (70  pg/g)/sediment




(30 to 200 pg/g) ratios are in the range of 0.4 to 2.3 for 2,3,7,8-TCDD.  Laboratory data




presented by the same authors for 2,3,7,8-TCDD yield a fish (7.5 pg/g)/sediment (39 pg/g)




ratio of 0.2 after 55 days of exposure; however, this ratio probably does not represent a




steady state. In some Missouri streams, bottom fish such as  sculpins appear to have




2,3,7,8-TCDD concentrations exceeding  10 times the sediment concentrations (Cook, 1986).




     Thus, fish/sediment ratios for 2,3,7,8-TCDD can be variable depending on a series of




interdependent factors, including species, lipid content, weight, ratio of surface area to




weight, organic carbon content of the sediment, food  intake rate, density of suspended




particulate matter,  and concentration of 2,3,7,8-TCDD in the sediment.  In addition, fish




in a stream may approach a steady-state with higher sediment concentrations upstream




due to food drift and/or suspended sediment with a higher 2,3,7,8-TCDD concentration




than the bottom sediment concentration.




     Some of the variability in the values derived for fish/sediment ratios could be




eliminated if they were derived based on 2,3,7,8-TCDD in the lipid of fish and organic




carbon of the sediment.  Lake et al. (1984) reported partitioning (preference) factors for




polychlorinated biphenyls (PCBs) in field studies with aquatic invertebrates of 0.1  to 0.5



(two-  to 10-fold greater concentration of PCB per gram of lipid than per gram of organic




carbon of the sediment). These authors also report 3.3- to 5.9-fold greater




concentrations of chlordane, DDD, and tetrachlorodiphenyl in the lipid of these organisms



than in organic carbon of sediments.  Kuehl et al. (1987b) also used this  approach in




order to facilitate comparison of data for laboratory (10-g carp) and field (1.5-kg carp)






                                           41

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experiments, and to determine the congener-dependent bioavailability of select




2,3,7,8-substituted PCDDs and PCDFs.  The Bioavailibility Indices derived for these




congeners show clearly that 2,3,7,8-TCDD is preferentially bioaccumulated, with other




2,3,7,8-substituted congeners being accumulated to a lesser degree and non-2,3,7,8-




substituted cogeners being accumulated to a  much lesser degree.



2. Bioaccumulation in Cattle




     Beef and dairy cattle have been shown  to accumulate significant levels of




2,3,7,8-TCDD and compounds with generally related structures such  as PCBs, DDT, and




PBBs following administration in the diet or ingestion of contaminated soil.  The




potential for human exposure through consumption of beef and dairy products is greatest




where the cattle have  contact with the soil; soil ingestion by cattle is  the major pathway




for the transmission of 2,3,7,8-TCDD residue from soil to these animals.  The amount of




soil ingested by grazing cattle can vary between 2% and 15% of dry matter intake,




depending on whether vegetation is lush or sparse (Healy, 1968).




     A number of studies have been conducted using compounds having structures




generally related to 2,3,7,8-TCDD, such as PCB, PBB,  and DDT, which relate the resulting




level in body fat or milk fat to the level of the contaminant in the  diet.  Fries (1982)




reported that under constant feeding these compounds reach an upper estimate,




steady-state milk fat/diet ratio of approximately 5, with body  fat levels being slightly




lower. Jensen et al. (1981) conducted similar studies using 2,3,7,8-TCDD, and found the




beef fat/diet ratio (after 28 days  of feeding) to be about 4, suggesting that 2,3,7,8-TCDD




behaves similarly to PCB, PBB, and DDT. Jensen and  Hummel (1982) developed data from




dairy cows given 2,3,7,8-TCDD in their feed which indicated  a cream/diet ratio of 1.6 to




2.2 (cream containing 18% to about 40% butterfat).




     Fries (1985) analyzed data from a study in which  cattle were kept in feed-lots on




four Michigan farms  where soils  in the confinement areas were the sole source of PBB.






                                           42

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Under these conditions, the beef fat/soil ratio was in the range of 0.27 to 0.39 for beef




cows, beef calves, and dairy heifers (never lactated), and the milk fat/soil ratio ranged




from 0.02 to 0.06 for multiparous and primiparous dairy cows. Assuming, again, that




2,3,7,8-TCDD behaves in a manner similar to PBB, and that the conditions  on the




Michigan farms represent the  typical situation on U.S. farms, a beef fat/soil




bioconcentration ratio of 0.3 to 0.4 and a milk fat/soil bioconcentration ratio of 0.04 are




suggested for use in the procedures described for exposure assessment in this document




and  in Schaum (1984).




     However, if more specific  information concerning the farm management system is




known, such information should be used to adjust these values.  It should be recognized




that  the significance of soil ingestion as a pathway for animal exposure, and ultimately




for human exposure, is greatly reduced under U.S. agricultural conditions (Fries, 1986).




Lactating dairy  cows are rarely pastured.  Beef cattle that may have been on pasture are




often fattened for as long as 150 days in feed lots before slaughter, thus giving




considerable opportunity for elimination and dilution of tissue residues.




D.  PLANT UPTAKE




     The degree to which 2,3,7,8-TCDD can be taken up into plants  has not been well




established. The available  literature on this issue is somewhat contradictory.




     In one study (Wipf et al., 1982; Wipf and Schmid, 1983), investigators  collected soil




and  vegetation samples in Seveso, Italy, over the period 1976 through  1979, following the




runaway reaction incident at the IMESCO plant.  They found 2,3,7,8-TCDD concentrations




on the order of 1 ppm in plant material in 1976.  However, the  levels dropped by several




orders of magnitude over the  following years. The authors suspect the contamination




was  due  to 2,3,7,8-TCDD absorption through leaves deposited from local dusts. They also




conducted greenhouse tests using carrots grown in highly contaminated soil  collected




from the Seveso area.  The 2,3,7,8-TCDD levels in the peeled edible  portions of the






                                           43

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carrots were approximately 3% of the levels in the soil.  On. this basis, the authors



concluded that plant uptake was minimal.



     Coc.ucci.et al. (1979)  conducted very similar tests using Seveso soils and various



types of vegetation, including carrots,, potatoes,, and onions.  In contrast to Wipf et al.



(1982),, they found significant uptake levels [2,3,7,8-TCDD levels (sources unspecified) in



inner parts of the vegetables were approximately equal to levels in the soil].



     Young-(1983) studied uptake in perennial grasses and small broadleaf plants located



at a. field in. Eglin Air Force Base, Florida.  The field was sprayed with 2,4,5-T during



1962-1970.  In 1978 and 1979 the levels of T.CDD (isomers unspecified) in roots (-700 ppt)



were found at levels similar to those in the soil (~500 ppt).  Young concluded that this



result suggested a "passive" uptake process, in. which soil particles are incorporated into



the epidermis of the root tissue.  The upper portions of the  plants were found to have



10 to 75 ppt of TCDD (unspecified  isomers).



     A study by Facchetti et. al. (1986) looked at the potential for maize and beans to



absorb, translocate, and accumulate  2,3,7,8-TCDD from contaminated soils.   Although the



study is somewhat difficult to interpret due to poor translation, the authors appear to



have concluded the following:



     (1)  Roots had higher levels of 2,3,7,8-TCDD than the surrounding soil.



     (2)  2,3,7,8-TCDD levels in above-ground parts of plants did not increase



          significantly over time or with, increasing levels of soil contamination (1 to 752




          PPt).



     (3)  2,3,7,8-TCDD contamination of above-ground parts of plants was due primarily



          to volatilization from soil.



     (4)  2,3,7,8-TCDD was: lost from the soils over time due to volatilization.



     (5)  High absorption of 2,3,7,8-TCDD  by the roots warrants precautions to be taken



          in the consumption of root vegetables such as carrots and potatoes.





                                            44

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     Isensee and Jones (1971) studied uptake of 2,3,7,8-TCDD into oats and soybeans




from treated soils.  They observed a time dependency in which uptake peaked soon after




planting and declined to very low levels by maturity.  They concluded that accumulation




of 2,3,7,8-TCDD in plants from soil uptake is highly unlikely.  Note, however, that these




are above-ground crops, as opposed to  the root crops discussed above.




     Sacchi et al. (1986) measured levels of 2,3,7,8-TCDD in bean and maize plants grown




inside green houses using soil which was dosed with various concentrations of




2,3,7,8-TCDD.  They found  that 2,3,7,8-TCDD accumulated in the aerial parts of the



plants.  The accumulation  levels generally increased with plant age and soil concentration




levels. The ratio between  levels in soil and in aerial parts ranged from about 0.3% - 30%




and varied inversely with soil level. At 1 ppb soil-plant ratio was 1% for beans and 3%




for maize. Substantially lower uptake levels were found when peat was added to the




soil.




     Because of the contradictory nature of the current literature, it is not possible at




this time  to establish an equilibrium partition ratio between the plant and soil, nor the




rate of plant uptake from  soil or other overlying media (air or dust on leaves).  If




uptakes such as those observed  by Cocucci actually occur in a situation where an




individual obtains a significant  portion of his root  vegetable diet from a contaminated




home garden, very high risks would result. The findings of Young (1983) and Sacchi et




al.  (1986) may indicate that ingestion of certain above-ground plant parts would pose a




smaller, but still potentially significant risk.
                                            45

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4. EXPOSURE



     This chapter looks at some of the assumptions made in the parameters used to




calculate exposure from various pathways.  Specifically, the parameters discussed in  this




chapter relate to exposure through inhalation of dust, inhalation of vapor, dermal



contact, ingestion  of soil, ingestion of beef and dairy products, and ingestion of fish.  As




discussed  in Chapter 2, some of the refinements of the past few years  (e.g., in treatment




of indoor dust levels, soil contact rates, and consumption rates for fish, meat, and dairy




products) have added to our confidence in the exposure estimates, without substantially




changing  the estimates themselves.  The refinements in the data on soil ingestion have




resulted in the reduction, by approximately a factor of five, in the estimate of the high




end of the range of the "normal" amount of soil ingested by children while playing.  It




should be noted that incidental ingestion of soil is common in children through mouthing




of hands with soil on them or through ingestion of airborne soil. The estimates in this




report are not for the so-called "pica child," who intentionally ingests non-food material




("eating mud pies," etc.).




     The exposure routes discussed in this chapter include inhalation of particulates, dust




and vapors, dermal contact, and ingestion of contaminated soil,  beef, dairy products, and




fish.  A recent evaluation of the significance of inhaling volatilized 2,3,7,8-TCDD in the




vicinity of a contaminated site indicates that this pathway cannot always be treated as




negligible.




A.  INHALATION — INDOOR DUST LEVELS VERSUS OUTDOOR LEVELS




     For  exposure assessments near 2,3,7,8-TCDD-contaminated areas, the level  of




suspended particulate matter,  and  its contaminant content, are major variables  in the




calculation of exposure or risk. Usually, when attempting to estimate  exposure through a




pathway involving dust intake or dermal contact, not all the factors have  been analyzed,






                                            46

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and measurements might only be available for 2,3,7,8-TCDD levels in the soil.  To gain




information on other variables, such as the suspended particulate matter or dust content,




assumptions are made in order to provide estimates.




     In a report on 2,3,7,8-TCDD transport from contaminated sites (U.S. EPA, 1985b), a




technique is presented for calculating conversion factors between soil, air, and sediment.




This report (U.S. EPA, 1985b) provides a methodology for using conversion factors in




calculating air concentrations of 2,3,7,8-TCDD:








                      cair Gig/m3) = 1(T7 kg/m3 (csoil 0*g/kg))              (4-1)
The authors cite a study by Fred C. Hart Associates, Inc. (EPA 1984b) which indicates




that 2,3,7,8-TCDD levels might increase by a factor of 2 to 12 on small particles as




compared to larger ones.  However, U.S. EPA (1985c)  report uses the assumption that the




concentration of 2,3,7,8-TCDD adsorbed on suspended particles will be the same as that




in the soil.




      Hawley (1985) assumed, based on several other studies in which measurements were




made, that the concentration of suspended particulate matter in indoor air is equal  to




75% of that outside.  Also, his report stated that most  household  dust is outdoor dust ,




that is transported into the house, and that only a small percentage is developed from




sources within.  He  then concluded that  80% of the indoor dust is identical in




contaminant content to outdoor soil.  Previous reports  (e.g., Schaum, 1984) have usually




assumed that 2,3,7,8-TCDD levels in the soil and dust  are equal.  This refinement (i.e.,




using Hawley's (1985) method rather than Schaum's (1984) method) should have a minor




effect on the overall exposure estimates.   The way this refinement enters  into the




exposure assessment is further elucidated in Section C.I. of this chapter.
                                           47

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B. INHALATION — VAPORS



     The compound  2,3,7,8-TCDD exerts a very low vapor pressure (Freeman and Schroy,



1985a, b; Schroy et al., 1985a; Podoll et al., 1986).  However, compounds with low vapor



pressure and low solubility exhibit some properties in the environment that are not



readily apparent from looking at pure-state properties individually.  Based on the vapor



pressure consideration, Paustenbach et al. (1986) discounted the importance of



2,3,7,8-TCDD uptake via vapor inhalation in risk assessment evaluation, and assumed that



the human intake via inhalation is related to the intake of airborne, respirable



particulates only.  On the other hand, Freeman and Schroy (1985a, b,) and EPA (1985c)



considered the vaporization process to be the most  important transport process for CDDs



present in soils, and  compared the results of their modeling with the concentration data



obtained at different depths of the soil column and at different times.  In addition to



concluding that 2,3,7,8-TCDD can be relatively volatile in an environmental setting, they



presented a set of conditions that will influence volatilization from contaminated spill



sites such as Times Beach, Missouri, and Eglin Air Force Base. Thibodeaux (1983)



compared estimated  environmental 2,3,7,8-TCDD exposures from vapor and dust inhalation,



and concluded that vapor inhalation is a significant exposure pathway. Eitzer and Hites



(1986), based on a limited experimental study, found that CDD in the ambient air was



present primarily in  the vapor phase (this study is  discussed in more detail below).



     Despite its low vapor pressure, 2,3,7,8-TCDD can volatilize from spill and disposal



sites, and can be emitted  into the air from a variety of other sources,  including



incineration and combustion  processes, facilities manufacturing PCBs, paper products and



pentachlorophenol, and pyrolysis  of PCBs and other chlorinated benzene  derivatives



(Radian Corp., 1983; Freeman and Schroy, I985a; Commoner et al.,  1985; Czuczwa and



Hites, 1986).  For example, Nash and Beall (1980)  found ambient air concentrations of



2,3,7,8-TCDD when silvex spiked with 2,3,7,8-TCDD  was  applied to  turf and field sites.






                                           48

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The data show that the ambient air concentrations decreased as a function of time after




the application.  Initially, concentrations of vaporized 2,3,7,8-TCDD as high as 7.98




x 10" H and 9 x 10"^ g/m^ were measured when the spray material spiked with




2,3,7,8-TCDD at concentrations of 7.5 and 15 ppm was applied  to turf in a microcosm




experiment and at the field site.  The measurements for the volatilized material were




made immediately after the application.  These ambient concentrations were due to




volatilization from the field, which the authors noted was a major pathway  of




2,3,7,8-TCDD dissipation.




     Czuczwa and Kites  (1986) showed that particulates collected from the ambient air in




Washington, D.C., and St. Louis, Missouri, were enriched in octachlorodibenzo-p-dioxin




compared with the congener profiles in the combustion source effluent, which were




reported to be the major source of dioxin constituents in the urban air particulates.




Similar enrichment was noted in congener profiles in surface sediments collected from the




Great Lakes.  The authors noted that particulates containing PCDD emitted from



combustion sources would travel through the atmosphere to ultimate environmental sinks,




such as lake sediments.




     This section of the  report, however, concentrates on risk analysis of contaminated




soils, and therefore does not address the procedure for estimating the amount of




2,3,7,8-TCDD emissions from combustion or pyrolysis sources.  Since exposure to




2,3,7,8-TCDD via vapor inhalation is directly proportional to the 2,3,7,8-TCDD




concentration in the ambient air that a person breathes and the air  respiration rate




(contact rate), the critical parameter in estimating exposure from vapor inhalation is the




2,3,7,8-TCDD concentration in  the ambient air.  Although the measured concentration




values can be used directly in exposure evaluation, the analytical difficulty  and the cost




associated with obtaining properly quality-controlled concentration  data from




measurements for low vapor pressure compounds are extremely disadvantageous.






                                           49

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     Because of the problems in measurement noted above, models are very convenient



tools for estimating the ambient air concentrations at the site where volatilization



occurs, or at a distance away from the site.  The more distant the exposure location is



from the area source where the emissions occur, the less concentrated the contaminant



will be in the ambient air.  The major cause for this dilution is the mixing of the



contaminant with the winds, dispersion in the air, and possibly some degradation in the



atmosphere by action of sunlight and free radicals. Since some models describing the



emission rate from soil and the dispersion of volatilized CDD are complex and lengthy,



the reader who is interested in details of the model derivation and different applications



is encouraged to consult the relevant  references (U.S. EPA, 1986a; U.S. EPA, 1981c; U.S.



EPA, 1979; Turner,  1970).  This part of the report will concentrate on presenting the



model results and pertinent applications.



1.  Emission Potential



     In estimating the on-site or off-site ambient air concentrations of volatilized



2,3,7,8-TCDD to which people would be exposed, the first task should be to estimate the



emission rate from the contaminated  area. As  a result of changing concentrations of



2,3,7,8-TCDD in the soil column as the emission proceeds (see Section A of Chapter 3),



no matter how small the vapor pressure is, the emission rate estimation involves



consideration of an nonsteady-state process.  Because of this,  the emission rate can be



presented either on an instantaneous  basis or on an average basis; in the latter case, the



emission rate should be averaged over the time period of interest.  For evaluation of



long-term exposure, it is most often appropriate to make  use of the average values.



     As can be seen in the model presented below, the data requirements for model



estimation of the transient emission rate include the concentration of 2,3,7,8-TCDD in



soil, Henry's law constant (which can also be calculated from  vapor pressure and aqueous



solubility), the effective porosity of the contaminated soil media, the diffusivity of






                                           50

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2,3,7,8-TCDD vapor in air, the area of contamination, and the depth of contamination.




The data that must be  determined on a site-specific basis are the concentration of




2,3,7,8-TCDD in soil,  and the  area and depth of contamination.  The other parameters




can be estimated from data on  physical properties, or can be found in the listing of




properties for 2,3,7,8-TCDD in Chapter 2.




     Other factors affecting the emission rate are the cover layer of contaminated soil,




2,3,7,8-TCDD concentration profile in soil, the moisture content of the soil, the




biodegradation rate in  the soil, and the existence of gases generated by decomposing




material.  While cover  material can reduce the emission rate, once the cover material  is




saturated it loses the capability for adsorption, and any enhancement in retardation is



due to the increased path length of vapor diffusion. (See discussion in Section A.2. of



Chapter 3). Vaporization of moisture and generation of other gases from decomposing




material will lead to convective transport as well as increased diffusion rate and thus



increase the emission rate.




     When it can be assumed that 2,3,7,8-TCDD initially contaminates soil from the  soil



surface down to a specified depth, with a uniform concentration distribution along the




soil column, the time-averaged emission rate, ND, in grams  per cm^ per second, can be




estimated from U.S. EPA (1986a) and Hwang and Falco (1986) as follows:








                    ND = 2Dj E4/3 Kas Cso/>/3.14aT                        (4-2)








The parameters in Equation 4-2 can be defined as follows:  D] = the molecular diffusivity




of dioxin vapor in air (= 4.7 x 10   cm~/s), E = the porosity of soil, T = the exposure




duration (seconds), Kas = the air/soil partition coefficient (mg/cm3 air/mg/g soil), Cso =




the initial 2,3,7,8-TCDD concentration in soil (g/g), and a (cm^/s) is
                                           51

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               o = Di E4/3/[E  + ps(l - E)/Kas]                             (4-3)
where ps = the true density of soil (g/cnP).



     For wet soils, 2,3,7,8-TCDD is partitioned between the soil, water, and air phases.



Henry's law constant and the soil/water partition coefficient can be used to describe



partitioning of 2,3,7,8-TCDD between the soil and air phases, or








                                   Kas  = 41 Hc/Kd                        (4-4)







where Hc = Henry's law constant (1.6 x 10~^  - 4.6 x 10^ atm m^/g mol) (Podoll et al.,



1986; Schroy,  1985a); K
-------
     It should be noted that the vapor emission rate changes over time due to changes



in the concentration profile of 2,3,7,8-TCDD along the soil column.  Equation 4-2 is used




to estimate the emission rate  averaged over the time period of exposure.  Freeman and




Schroy (1985a, b,) and EPA (1985c) showed, by modeling a heat balance around the soil




element, that the temperature at the soil surface fluctuates appreciably in a period of  1




day, while the fluctuation diminishes at greater depths.  They concluded that these




temperature fluctuations may cause important changes in the volatilization rate. They




also showed that the  concentration profile in the soil column changes with time.




Assuming that these changes in the soil concentration profile are due to volatilization




and diffusion, the initial concentration (Cso at t = 0, in Equation 4-2) can be represented




by the maximum value of the concentration profile derived from sampling done a long




time after contamination occurred. The total rate of emission, Q (g/s), over an area, A




(cm^), of contamination can  be obtained from








                              Q = A . Nd                                   (4-5)








It is preferable not to use the temperature at the soil surface in choosing physical




parameters, because the emission results from a diffusion process occurring below the




surface.  In reality, the 2,3,7,8-TCDD concentration at the soil surface will rapidly




approach zero following  initial deposition  (assuming that vaporization/photolysis losses



occur more rapidly than erosion), although the 2,3,7,8-TCDD in the bulk soil may have




volatilized very little.  The temperature to be used in choosing values  for physical



parameters to calculate the effect on  emission rate should be representative of the



contamination depth.
                                            53

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2. Dilution of Emissions in Ambient Air



     The 2,3,7,8-TCDD emanating from the soil surface in vapor or particulate form are



diluted by  winds at the site, and are transported through the atmosphere until they are



ultimately reduced in concentration, possibly destroyed through photolytic reactions, or



deposited on land or in water bodies.  The atmospheric phenomena which influence the



dilution, transport, and transformation of 2,3,7,8-TCDD emissions can change extensively



as a function of time and location.  Although model simulations may be sufficiently



representative, such variations in atmospheric phenomena can lead to uncertainties of



more concern than those associated with the models themselves.  These uncertainties will



arise from  assumptions of estimates regarding (1) mixing height, (2) meteorological



conditions  (wind speed and direction), (3) stability conditions, and (4) atmospheric



reactions.



     The maximum ground-level concentrations resulting from point-source stack



emissions occur some distance from the source. In contrast, ground-source emissions



occurring over a large area cause higher ground-level concentrations at the site of



emission, and become more diluted as they  are transported downwind of the source.



Because  of the higher concentration of the contaminant on-site than off-site, the



population residing on-site will normally have higher levels of exposure from  vapor



inhalation  than those  off-site.  If concerns relating to emission impacts arise for people



living on or having access to the site, it may then also be necessary  to conduct an



exposure evaluation for the population located downwind of the site.



     Gaussian dispersion modeling cannot be used in estimating the on-site concentrations



or the receptor concentrations within 100 meters of the center of the facility.  Despite



the importance of the contaminant dispersion phenomena at the short-range or on-site



locations, experimental data are lacking with which to calibrate the  dispersion



coefficients needed in the short-range dispersion equation derived by integrating  point






                                            54

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source modeling over the area of emission (Hwang, 1987). The on-site or short-range

concentrations along the center of an area source can be estimated from


                                                                     9
          C=  v/2/3.14 ((q)a//«rz)  EXP (-i(z/az)2) erf (b/2v/2ay)            (4-6)




where a, b = dimensions of the site  parallel and perpendicular to the wind direction,

respectively; q =  emission rate per unit area; u = average wind speed; Sy and Sz are the

horizontal and vertical dispersion  coefficients in air,  respectively; z = receptor height,

and it is assumed that the source is  at ground level.

      Under the assumption that a contaminant present at the site has traveled only a

short distance before it is inhaled by the population, the box-model approach considers

mixing of the emitted contaminant with the winds, ignoring the dispersion effects.  Based

on the use of an average value for wind  speeds that varies logarithmically with respect

to height, and for a mixing height,  this approach provides an estimate  of  the on-site

concentrations of 2,3,7,8-TCDD  in  ambient air,  as follows:


                    On-site Ca  =  Q/[(LS)V(MH)]                                 (4-7)




where Ca = the ambient air concentration of 2,3,7,8-TCDD at the exposure  location

(g/m^), Q = total emission rate (g/s), LS  = an equivalent side length of the site

perpendicular to  the direction of the winds (m), V = the average wind  speed at the

inhalation height (about 2.2 m/s for 10-mph winds), and MH = the mixing height before

being inhaled by an individual (m).

     Two approaches are possible for estimating the  ambient air concentrations of

2,3,7,8-TCDD at off-site locations.  In the current state of model development, both

approaches make use of virtual source approximations for area sources. The first
                             t
approach requires extensive site-specific  meteorological data, which are employed in using

                                            55

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refined computer models.  These data are used to sum the frequency distribution of wind

speed for each radial/concentric sector of exposure around the source, and to evaluate

the vertical standard deviation of the plume for each observed stability class on an

annual basis.  The details of the equation can be found elsewhere (U.S. EPA, 1986a).

     The second approach, which is applicable for estimating  concentrations at distances

of 100 meters or more from the source, uses an approximation of the model for a quick

assessment.  The simplified form of the equation is given in Turner (1970) as:



                         Off-site Ca =  2.03 (Q/LvazV)                           (4-8)



where Lv = the total virtual downwind distance to the receptor (m), obtained from Lv =

L + 2.5S; L  = the distance  from the  center of the facility to the  receptor; S  = the width

of the facility perpendicular to the wind direction, (m); Ca, Q, and V are as defined for

Equation 4-7, and oz = the vertical standard deviation (m).  The values for  sz can be

found in most standard air pollution textbooks in graphic or formula form (Turner,  1970;

U.S. EPA, 1986a).  In estimating the annual average values, the  concentration obtained by

Equation 4-8 is often  corrected by multiplying by a frequency factor with which the wind

blows toward a particular sector of interest.

      Introduction  of the dilution factor, essentially a conversion factor, makes the

estimation of on-site  ambient air concentrations very convenient.  The procedures

involved in  calculating the emission rate and the ambient air mixing can be combined

into a single step.  The dilution factor, D, can be defined as
                ambient air concentration at exposure location                 (4-9)
               air-phase concentration of TCDD at the soil surface
                          from which emissions originate
     The vapor-phase concentration, which is assumed to be in equilibrium with the


                                           56

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contaminated soil, will still reach the soil surface by the diffusion process along the soil

column.  Consequently, the vapor-phase 2,3,7,8-TCDD at the soil surface can be given as


                         C  =  KasCso                                     (4-10)


Once the dilution factor is evaluated, the ambient air concentration at the exposure point

can be obtained by multiplying it by the 2,3,7,8-TCDD concentration at the soil surface

corresponding to the initial 2,3,7,8-TCDD concentration in soil. In order to do this, one

can combine Equation 4-2 for emission rates  in the case  of surface contamination, and

Equation 4-8 for on-site mixing, to yield


                     n_ Xa_  _ 0,02 Dj.E4/3  A                   (4-11)
                          CsoKas   (LS)V(MHV3.14aT


where A is  the area of contamination (m2), and all other  units are as given before (i.e.,

Dj in cm2/s, LS in m, V in m/s, MH in m, a in cm2/s, and T in seconds; note mixed

units for the length).

      For example, suppose the average 2,3,7,8-TCDD concentration on a contaminated site

is initially 0.05 Mg/g-  At the  values for T = 2.2 x 109 s, A =  2,024 m2, LS = 45 m, Dj

= 4.7 x 10~2 cm2/s, V = 2.25 m/s, MH = 2 m, and Kas = 4  x 10'7 g soil/cm3 air, the

air-phase 2,3,7,8-TCDD concentration  at the soil-air interface, C, and the dilution factor,

D, are calculated to be 2 x 10~2 Mg/m3 and 5.4 x 10~4, respectively.   is 2 x 10~9 as

calculated from Equation 4-3. In this calculation, the values E =  0.35 and ps = 2.65 are

used.  From these two results, the 2,3,7,8-TCDD concentration in the ambient air at the

exposure point is found to be 1.1 x 10"^ g/m3.

3. Exposure Estimation

      The estimation of average  lifetime exposure via vapor inhalation requires

information on the contact rate, the duration of exposure, and the fraction of

2,3,7,8-TCDD vapor absorbed through  the lungs upon inhalation,  as well as the ambient

                                           57

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air concentrations being inhaled.  The contact rate is the air respiration rate for

children and adults, and should be consistent with the  air respiration rate discussed for

dust inhalation.  The exposure lifetime period is normally assumed to be 70 years, as

discussed in the section dealing with dust inhalation (Section A of Chapter 4).

     The rate of absorption of vapor-phase 2,3,7,8-TCDD through the membranes of

human lungs into  the bloodstream has not been adequately addressed in the literature.

Such a toxicokinetic analysis may require consideration of the diffusional process through

the cell membranes of the trace amount of 2,3,7,8-TCDD vapor that entered the alveoli.

The diffusion processes for lung  absorption include both passive and facilitated transport

as well  as active transport, while  the diffusion process through the gut (small intestine)

mostly involves osmosis.

     In view of the data showing that 2,3,7,8-TCDD tightly bound on the soil is absorbed

through the gastrointestinal (GI)  tract  at the rate of 20% to  26% (Poiger and Schlatter,

1980), the  vapor-phase 2,3,7,8-TCDD, which is not bound  on adsorptive solids,  should find

its way through the single-layer  membrane between the air space  and blood capillaries in

excess of the rate reported for the GI tract.  Until rigorous kinetic models or

experimental data are available, it appears reasonable to assume 50% to 100% absorption

of inhaled 2,3,7,8-TCDD vapor through the thin membrane layer, which at the alveoli and

blood capillaries contains both hydrophilic and hydrophobic components.

     The average lifetime exposure for the vapor  inhalation pathway can be estimated as

follows:

     Average     Ambient air concentration x respiration rate x exposure
     lifetime	duration x absorption fraction	            (4-12)
     exposure ~               Body weight x lifetime


The body weight and respiration rate  vary from childhood to adulthood.  An

approximation for these two variables is possible based on the assumption that changes in

the body weight and respiration  rate are proportional.   In this case, the body weight and

                                            58

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respiration rate for an average adult male can be used for lifetime exposure estimation.




4.  Effect of Photodegradation on Exposure Estimation




     Once emitted, 2,3,7,8-TCDD vapors or particulates can be destroyed in the



atmosphere through photodegradation. This may occur  by direct absorption of sunlight




energy, resulting in the breakdown of 2,3,7,8-TCDD by photolysis, or through




photo-induced oxidation by the  reaction of 2,3,7,8-TCDD with free radicals present in the




atmosphere.  Photolysis requires sunlight and is facilitated by availability of a hydrogen




donor (Crosby and Wong, 1977). Also, the presence of  a solvent on soil appears to make




adsorbed compounds  more available for photolysis.



     Podoll et al. (1986) compared the half-lives of 2,3,7,8-TCDD vapors under the




conditions of photolysis and hydroxyl (OH) radical oxidation in the atmosphere.  In




estimating the half-lives for photolysis of 2,3,7,8-TCDD vapor, the authors used the




quantum yield observed  in hexane and estimated an upper-bound photolysis rate of t^ =




58 minutes.  At an average concentration of OH radical of 3 x 10"^ M in the




atmosphere,  they also estimated the half-life for oxidation of 2,3,7,8-TCDD vapor by OH




radicals as t^ = 200 hours. The  authors presented these results  with  reservations,




suggesting the need for an accurate measurement of the vapor-phase quantum yield for




2,3,7,8-TCDD.




     Crosby and Wong (1977) conducted experimental photolysis studies for 2,3,7,8-TCDD




to evaluate its photolysis rates in different herbicide formulations and on different




surfaces.  The half-lives for loss of 2,3,7,8-TCDD from herbicide formulations on glass




surfaces ranged  from 2 to 6 hours.  Crosby and Wong (1977) reported that thin films of




2,3,7,8-TCDD on  glass plates were found to be  stable in sunlight for at least 14 days.




Note that this test did not use herbicide formulations.  They determined the half-lives




on leaves  as about 1 to 2 hours, and those  on soil as longer than 7 hours.  All




experiments were conducted under natural sunlight without using organic solvents.






                                            59

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Accounting for daily and annual fractions of sunlight, Thibodeaux and Lipsky (1985)



-adjusted the 6-hour half-life derived by Crosby and Wong to obtain an effective photo-



degradation half-life of 7.2 days.



     These findings appear to indicate that photolysis plays a role in the degradation of



2,3,7,8-TCDD only under certain conditions.  The use of solvents, such as olive oil or



hexane, can enhance  the photolysis of 2,3,7,8-TCDD on solid surfaces. The surface itself,



and perhaps the organic films present on  that surface,  are factors influencing the



photolysis rate; for example, 2,3,7,8-TCDD was stable on glass surfaces without being



affected by photolysis,  but underwent photolytic degradation when organic solvent film



was present on solid surfaces.  This suggests that in the environment, 2,3,7,8-TCDD on a



clean surface, such as glass,  may react quite differently from 2,3,7,8-TCDD on soil or



leaf surfaces with regard to photolysis.



     A preliminary photolysis experiment using 2,3,7,8-TCDD adsorbed on fly ash



particulates suspended in recirculating air indicated that the  photolysis of 2,3,7,8-TCDD



in particulate form underwent virtually no photolytic reactions after 30 hours of



illumination (Mill et al  1987).  Further experiments will be needed to compare the



relative magnitude of the photolysis rates for 2,3,7,8-TCDD vapors and particulates.



Eitzer and Kites (1986) reported that 2,3,7,8-TCDD in the atmosphere is all in vapor



form.  The vapor was captured by adsorption on polyurethane foam.  They collected



ambient air particulates using a high-volume sampler and 0.1-um pore size filters, and



could not detect 2,3,7,8-TCDD in the particulates. The study did not determine how



much 2,3,7,8-TCDD may have  been  present on the particles measuring less than 0.1 um.



However, if it is true that 2,3,7,8-TCDD is present primarily in the vapor  phase, then the



disappearance of 2,3,7,8-TCDD in the atmosphere would be controlled by the vapor-phase
                                            60

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photolysis. Further study is needed to confirm these rather unexpected results before




final conclusions can be drawn.




     Photolysis is generally assumed to decrease the ambient air concentrations that are




subject to human inhalation.  However, higher chlorinated CDDs could degrade to 2,3,7,8-




TCDD and the degradation products of 2,3,7,8-TCDD could still be toxic.  In the absence




of further experimental data under sunlight conditions, it appears that a reasonable value




for 2,3,7,8-TCDD vapor-phase half-life is in the range of 2 to 6 hours.  This range of




half-life is supported by recent experimental results (Mill et al 1987) on the vapor phase




photolysis of 2,3,7,8-TCDD under simulated sunlight conditions, where results show the



vapor-phase half-life being several hours rather than the fly ash particulate half-life of




several  hundred hours  as noted above.  Even with this relatively short vapor-phase  half-




life, the on-site ambient air concentrations, or nearby off-site ambient air concentrations




will not have degraded significantly before the population breathes the air.  This is




because the time required  for the 2,3,7,8-TCDD vapor emissions from the soil surface to



reach a human or structure is short compared with the half-life.




     For  ambient air concentrations at many off-site locations,  however, degradation  by




photolysis could be significant.  The distance at which the original 2,3,7,8-TCDD




emissions would have degraded will mostly depend on wind speed and direction, particle




size, and  the intensity  of light.  For example, with winds at 10  miles per hour, the



original amount of 2,3,7,8-TCDD vapor would have been degraded by one-half at a




distance of about 20 miles from the site, if it is assumed that the  half-life  is 2 hours.




     In estimating exposure to 2,3,7,8-TCDD vapor of the population residing at a




distance from the contaminated site, the ambient air concentration estimated by Equation
                                           61

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4-8 should be corrected by the amount of photodegradation.  For first-order




photodegradation kinetics, this correction is exponential with respect to the travel time:









                    ^corrected =  C*  ''*                                (4-'3>







The corrected concentration, as given by Equation 4-13, should be used in place  of




Equation 4-8 in subsequent exposure evaluations for the off-site population for which




photodegradation is significant.  In Equation 4-13, k is the first-order rate constant (=




0.12 hours"', based on a half-life of 6 hours), and t is the time-of-travel for




2,3,7,8-TCDD vapor to reach the  receptor by blowing winds.  The effect  of




photodegradation could be used in evaluating risk associated with the long-range




transport of 2,3,7,8-TCDD in particulate or vapor form in the atmosphere. For the




short-range transport of the contaminant in the atmosphere (e.g., within a S-mile radius




from  the site), the effect of photodegradation on the results of exposure evaluation can




be discounted.




C.  INHALATION —  PARTICULATES




     Dust emissions and the resulting TCDD emissions occur as a result of vehicular




traffic, loading and unloading operations,  spreading operations, transportation in  trucks,




and wind erosion.  Emissions from vehicular traffic is pertinent to the contaminated soil



scenarios where the possibility of traffic over the site can be considered.  The emissions




due to wind erosion are possible from contaminated soil or ash disposal sites where the




contaminant surface is exposed to the wind. Emissions from loading and unloading




operations, spreading operations, and during transportation in trucks would be more




appropriate in the scenarios dealing with fly ash disposal which typically  requires these




operations on a  frequent basis.  Such operations may also  occur at contaminated soil and




landfill sites.






                                            62

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     If dust emissions from all the operations and phenomena occur simultaneously, the




total emissions for each landfill scenario are  the sum of the vehicular traffic generated




emissions, the emissions resulting from unloading, the  emissions from spreading, and the




emissions from wind  erosion.  Emissions during transportation in trucks and loading




operations may affect populations far from the landfill site as well as those nearby.




Assumptions pertaining to each scenario are  further described later.




1. Vehicular Traffic



     The emissions from  a dump or landfill  site due to vehicular traffic can be estimated




from an  emission factor.  This factor can be found in  U.S. EPA (1985), and takes the




form of






          Ev =  K(1.7 (s/12)(s/48) (W/2.7)0-7 (w/4)°-5  (365-p/365)           (4-14)






where:    Ev =  emission  factor (kg/VKT)




           k = particle size multiplier (0.8 for particulates < 30 um)




           s = silt content of road surface material (%)




           S = mean vehicle speed,  km/hr



           W =  mean vehicle weight,  MG




           w =  mean number of wheels




           p = number of days with at least 0.254 mm




               (0.01  in) of precipitation per year




     This emission factor is provided in units of kilogram of particulate emitted per




vehicle kilometer traveled (kg/VKT).  Once  the emission factor is estimated, the vehicle




kilometers traveled in a day for each of the  scenarios  need to be estimated to get this




emission rate. VKT  equals the distance (km) traveled by all the vehicles which will  pass




through  the landfill or contaminated site.  Equation 4-14 can be used to solve for  the
                                            63

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quantity of particulate emitted if the VKT is known and the other parameter values can



be defined.  U.S. EPA (1985) provides 4.3 - 20% as the range of road silt content.



2.   Loading and Unloading Operations



     Emissions during loading and unloading of contaminated soil or fly ash can be



estimated using an equation given in U.S. EPA (1985).  The emission factor equation is








          E = k(0.0009)[(s/5)(u/2.2)(H/1.5)/(M/2)2 (y/4.6)0-33]                (4-15)








where:    E = emission factor (kg/Mg)



          k = particle size multiplier (dimensionless)



          s = material silt content (%)



          U = mean wind speed, m/s



          H = drop height, m



          M = material moisture content (%)



          Y = dumping device capacity, m3



Equation  (4-15) provides  an emission factor for kilograms of particulate emitted per



megagrams (Mg) of soil unloaded or loaded.  For fly ash disposal, the amount of soil that



is transported to  the landfill can be considered the same as the fly ash generation rates.



The particle size multiplier varies with aerodynamic particle size and is given numerical



values of 0.73 and 0.77 for batch drop and continuous drop operations for particle sizes



less than 30 um.  The  other parameters in Equation 4-15  can be defined as part of the



scenario.
                                           64

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3.    Spreading Operations
                    t


     It is assumed that spreading operations cause emissions on the same order as



agricultural tilling.   The emission factor derived from U.S. EPA (1985) is used to estimate



emissions:






          ES = k(5.38)(s)°-6                                                  (4-16)






where    Eg = emission factor (kg/ha)



            k = particle size multiplier



            s = silt  content



The particle size multiplier (k) varies with aerodynamic particle size, and is given as  1



for total particulate and 0.33 for particulates less than 30 um.



4.    Transportation in Trucks



      After  the ash is discharged from the storage bin to trucks, emissions can be



controlled by hauling  the fly ash in closed trucks or open trucks that use water or other



wetting agents for  dust control.  It is assumed that dry ash collection is used,  ash was



transported to landfills in open trucks, and the ash is wetted to control emissions prior



to being transported to the landfill.



      Currently, no emission factors are available for  estimating emissions from open



trucks.  It is assumed  that each truckload of ash can be treated as an individual



aggregate pile.  The emission factor for estimating emissions from open trucks is






          ET = 1.9 (s/1.5)[(365-p)/235](f/15)                                 (4-17)






where:      E = total suspended particulate emission factor (kg/d/ha)



            s = silt  content  of aggregate(%)





                                            65

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           p = number of days with > 0.25 mm (0.01  in) of precipitation



               per year



           f = percentage of time that the unobstructed wind speed exceeds



               5.4 m/s at the mean pile height



For wetted fly ash, the value for p can be assumed to be 364 days based on the



assumption that the surface of the ash is wetted prior  to hauling to the landfill.  Since



the truck is normally moving at a speed faster than 12 mph, the value for f is 100%.



     The emission rate from transporting soil or fly ash in trucks can be estimated using



the following steps:



     a.   Estimate the daily number of truckloads of ash transported by first



          converting the daily quantity of ash loaded  at each facility from kg to cubic



          meters. Next divide this quantity by the capacity of each truckload (typically



          12 m^).  This provides the daily number of truckloads of ash transported to



          the landfill.



     b.   Estimate the surface area of fly ash in each truckload capacity.



     c.   Estimate the quantity of ash emitted per minute of travel  time by multiplying



          the surface area of each truckload by the emission factor.



     d.   Estimate the emission rate of particulate matter by multiplying the quantity



          of particulate emitted per minute from each truck by the travel  time by the



          daily number of loads.



5.   Wind Erosion



     A method for estimating  dust emissions generated by wind is described below.  This



method assumes that  the uncrusted contaminated surface is exposed to the  wind and



consists of finely divided particles.  This  creates a condition defined by U.S. EPA (1985a)



as an "unlimited reservoir" and results in  maximum wind-caused dust emissions.  Surface
                                            66

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activities such as described above would increase the emissions, and these should be




computed separately if they occur.




     The flux of dust particles less than 10 um from surfaces with an "unlimited




reservoir" of erodible particles can be estimated as shown below (U.S. EPA, 1985a):








          E = 0.036 (1 -  V) (Um/Ut)3 F((x)                                   (4-18)








where:    E = total dust flux  rate of < 10 um particle (g/m^ . hr)




          V = fraction of vegetation cover



         Um =  mean annual wind speed  (m/s)




         Ut = threshold wind speed (m/s)



       F(x) = a function  specific to this model.








     Threshold  wind speed (Uj)  is the wind velocity at a height of 7  meters above the




ground needed to initiate soil erosion.  It depends on nature of surface crust,  moisture




content, size distribution  of particles, and presence of  non-erodible elements.  It can be




estimated on the basis of the  following procedure (U.S. EPA, 1985a):




     a.   Determine the  threshold friction velocity. This is the wind speed measured at




          the surface needed to  initiate soil erosion. For "unlimited reservoir" surfaces,




          U.S. EPA (1985a) suggests that this  velocity  is less than 75  cm/s.




     b.   Estimate the "roughness height." This is a measure of the roughness of the




          surface.




     c.   Estimate ratio  of threshold wind speed at 7  m to friction velocity, by using a




          chart provided by U.S. EPA (1985a).




     d.   Estimate threshold  wind speed by multiplying the friction velocity  by the ratios




          described in step (c.)






                                           67

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     Finally, F(x) is determined by first calculating the dimensionless ratio, x = 0.886



Ut/Um and finding F(x) from a chart of F(x) versus x, as provided in U.S. EPA (I985a).



     The dust flux is converted to an emission rate as follows (U.S. EPA, I985a):






          Q = CSEA (1 hr/3,600 s)                                          (4-19)






where:



           Q = TCDD emission rate (ng/s)



          Cs = TCDD concentration in soil (ng/g)
                             /


           A = site area (m2).



D.  DERMAL — SOIL CONTACT RATES AND DERMAL ABSORPTION



1. Contact  Rates



     Determining the amount of soil with which individuals might come in contact is a



critical first step  in obtaining estimates of dermal absorption or soil ingestion.  Among



the factors that must be considered for a relevant estimate of exposure by the dermal



route are type of soil (which determines the bioavailability of a compound), exposed skin



areas, soil contact period, soil and/or skin moisture, age of individuals (which influences



the permeability of the skin), temperature, and location on the body of  the soil contact.



     Surface area data can be readily obtained from  various  sources, for example, Snyder



(1975) or U.S. EPA (1985a).  The latter reference is an investigation and review of



literature to provide information on statistical distributions and ranges of standard



factors used to support EPA's Guidelines for Estimating Exposures.  It discusses



measurement techniques and contains formulae along with summary tables on body surface



areas on the basis of age, sex, and body parts or areas.



     Measurements of the amount of soil which adheres or accumulates on skin surfaces



have been conducted by Lepow et al. (1975) and Roels et al. (1980).  Lepow et al. (1975),




                                          68

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using an adhesive, found an average of 11 mg of dirt per 21.5 cm2 on the hands of




children.  Roels et al. (1980) obtained similar results from a study with older children




(11-year-olds) using a technique involving the lead content of the dirt.  In the above




studies, the amount of adhered soil was 0.5 mg/cm2 and 0.6  mg/cm2, respectively.




Hawley (1985) used the  results of Lepow et al. (1975) and Roels et al. (1980) in his




assessment of risk from  exposure to contaminated soil, and used a value of 0.51  mg/cm2.




This value was taken as the soil covering for estimating exposure to children playing




outdoors.  For adults, Hawley (1985) assumed a value of 3.5  mg/cm2 from doing yard




work.  Schaum (1984), after considering Snyder (1975), Lepow et al. (1975) and Roels et




al. (1980), assumed a contact range of 0.5 to  1.5 mg/cm2 and that this range also




represents an average for the entire exposed area of the human body for both adults and




children.




     The  duration (that is, contact time per  event [hr/d] times frequency of the event




[d/yr]) of the exposure to the contaminated soil is an important determination.  Schaum




(1984) adopted a  range of 247 to 365 d/yr as the exposure frequency. Paustenbach et al.



(1986),  in their examination of assumptions used for risk calculations, stated that it




appeared that the Centers for Disease Control (CDC) assumed exposure to soil for about




180 d/yr.  Hawley (1985) presented a reasonable description  and separation of the




exposure duration.  He assumed outdoor  exposure of 5 days/week for 6 months for young




children (2i years of age),  with a 12-hour contact time (since children often retain soil




on their skin after coming indoors).  This corresponds to about 130 d/yr.  For older




children, Hawley (1985) assumed an average outdoor playtime of 5 hr/d from May to




September, or 150 d/yr.  Adults were assumed to have about 43 d/yr of outdoor soil




exposure,  based on 8 hours of yard work 2 d/wk for 5 months.




     A similar issue is the length of time the soil is in contact with the skin surface.




This is  an important factor, since it will  help determine the  amounts absorbed.  The CDC






                                           69

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(Kimbrough et al., 1984) assumed that the contact period was sufficient to cause 1%




absorption.  This assumption was based on work by Poiger and Schlatter (1980), who




found 0.05 to  2.2% absorption in rats from a soil and water paste after 24 hours.



Schaum (1984) assumed 24 hours of contact for the days of exposure.  In contrast,




Hawley (1985) assumed 12 hr/d of contact for children and 8 hr/d for adults.




     Most of the above determinations and assumptions have recognized that contact




with soil is dependent on various factors, including weather, age, and activity patterns of




subgroups or individuals.




     The skin surface area which is exposed to soil may vary because of age, type of




activity, or outside conditions such as temperature.  Schaum (1984) used values  developed




by Sendroy and Cecchini (1954); that is, 2,940 cm2 for an adult  wearing a short-sleeved




shirt and no gloves, and 910 cm2 for an adult wearing  a long-sleeved shirt and  gloves.




For children, Schaum (1984) computed the exposed surface area  by multiplying the above




values by the  ratio of a child/adult total surface area.  Hawley (1985) derived surface




areas of various body parts from Diem and Lentner (1973) and Berkow (1924),  and then




made assumptions about the body parts which might be exposed. For young children, he




assumed that both hands and the legs and feet would come into contact with soil, giving




a surface area of 0.21 m2. For older children, he assumed soil contact over  both hands,




the forearms,  and  the legs from the knees down (0.16 m2). For adults, Hawley  (1985)




assumed contact on both hands and the forearms (0.17 m2), estimating 3.5 mg/cm2 of soil




on the skin for adults.




     Obviously, these surface area designations will change according to the attire  of the




individuals or assumptions made as to which body areas come in contact with soil.




     So far, only outdoor exposure has been considered in this section.  If the soil  in




the surrounding area  is contaminated, then it can be assumed that soil is carried into the




house, and that household dust is contaminated to significant levels approaching those






                                           70

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occurring outdoors.  Hawley (1985) assumed that about 80% of indoor dust is identical in




contaminant content to outdoor soil, and that the concentration of suspended particulate




matter indoors is three-quarters of that outdoors.  He also assumed that the dust




covering indoor  surfaces was 560 mg/m  , based on the assumption that the indoor




dustfall rate was 20% of that outdoors, or 80 mg/m^/d and that cleaning took place once



every 2 weeks.   Dermal contact, therefore, to children indoors, according to Hawley




(1985), was 560  mg/m^ on a surface area of 0.05 m^.  The exposed area was taken as




half that of the  feet, hands, and forearms. The contact area for older children was




assumed to cover both hands (0.04 m^) and to continue for 4 hours/day.  Adults were




assumed to be in contact with an area equivalent to the surface area of their hands (0.09




m2).



2.  Absorption




     The skin constitutes a major interface between humans and the environment, and




influences percutaneous absorption by physical, physiological, and biochemical means.




The factors that affect transfer across this membrane, and which can modify the




cutaneous  penetration rate, include the intrinsic properties of the skin itself (such as




age, location on the body, and any modifications from trauma or disease), in addition to




the environmental conditions of exposure (temperature, humidity, concentration gradient,




and duration of exposure).  All of these factors can influence  the permeability of the




skin to various contaminants.  In particular, an increase in any of these factors would




cause an increased  rate  of contaminant transfer.




     Suskind (1977) states that there are two major routes of penetration: the epidermis




itself, and the hair follicles and sebaceous glands.  According to Suskind, the latter are




particularly important in initial or transient exposures, and also in cases where



chlorinated hydrocarbons and dioxins seem to impact the  skin (for example, producing



chloracne at those sites).  Therefore, the skin may need to be considered as a target






                                           71

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organ. Tschirley (1986) reported that in an experiment with human volunteers where




2,3,7,8-TCDD was applied in a dose of 3 to 114 ng/kg to their skin, no chloracne




developed.  However, at a dose of 107,000 oig/kg, ,80% of the subjects developed




.chloracne.



     Many investigators believe  that the skin may be the most sensitive  index of




exposure to CDDs, especially in  cases of accidental or occupational exposure (Brodkin and



Schwartz, .1984;  Tschirley, 1986; Dunagin, 1984).  In fact, there are studies investigating




'the use of human epidermal cell cultures as indicators and models of toxicity to various




compounds (Greenlee et al., 1985; Osborne and Greenlee, 1985). Kao et al. (1985) studied



the metabolic processes in the skin itself, and the ways in which these processes may




influence percutaneous absorption.




     With regard to the absorption of 2,3,7,8-TCDD, Poiger and Schlatter (1980) looked




at the radiolabeled amounts of the compound in the liver of rats as an indication of its




uptake. When 2,3,7,8-TCDD was dermally applied as a pure compound (in methanol) for 24




hours, they found that the highest liver content was 14.8% of the dose applied to the




skin.  When 2,3,7,8-TCDD was  applied in a mixture of soil, Poiger and Schlatter (1980)




found the liver  content to be significantly less than half of that measured  in the




previous test. When 2,3,7,8-TCDD was applied in a soil-water paste, the  liver content




varied with dose from 0.05% to  2.2%. Schaum (1984), using the information reported by




Poiger and Schlatter (1980) to the effect that 70% of total body burden is  found in the




liver, modified  the range  for dermal absorption to 0.07% to 3%.




     Hawley (1985) first  considered studies by Bartek et al. (1972) and Feldman and




Maibach (1970)  on dermal uptake of various compounds in  humans when applied as pure




compounds or in acetone  for 24  hours. On the basis of these studies, he assumed the




percutaneous absorption rate to  be 11% in 24 hours for adults.  Therefore for a 12-hour




contact time, the rate  would be  about 6%.  For children, Hawley (1985) assumed the






                                           72

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absorption rate to be twice that of adults.  He then considered the results of Poiger and




Schlatter (1980) and modified this rate of 1.8% for children and 0.9% for adults on the




basis of a soil matrix effect (i.e., bioavailability) of 15% and a contact time of 12 hours.




3. Summary




     There are many variables and assumptions that need to be considered in addressing




dermal exposures.  For example, absorption is probably not a linear process, and the




assumption of a fractional contact time directly proportional to absorption in 24 hours




may not be completely valid.  However, there is little evidence to argue otherwise for




that assumption and others discussed here.  Most of the above-referenced studies  have




presented logical  approaches to  dealing with percutaneous absorption, and their



conclusions should  be  of considerable assistance.




     Absorption  from  soil contact can therefore be estimated as 0.9% for adults and 1.8%




for children; or as  a range of 0.07% to  3%, as given by Schaum (1984),  with no




distinction as to age.   The duration of contact, both in terms of physical contact and




yearly exposure,  can be estimated as 12 hr/d for children and 8 hr/d  for adults; and this




occurs for about  140 days for children  and about 45 days for adults.  These yearly values




can be modified  in the case of rural  populations.  The amount of soil which accumulates




or adheres on the skin can be considered as 0.5 to 0.6 mg/cm^ for children  and 1.8 to




3.5 mg/crcr  for adults doing yard work.




E.  INGESTION  — SOIL




     Until recently, only speculative information on the levels of soil ingestion by  young




children has  been available. During the past 2 years, studies have been conducted using a




new methodology,  that of measurement of trace elements present in soil and believed to




be poorly absorbed in  the gut.  While the initial trace element studies must still be




considered preliminary, a more quantitative basis is being developed for assessing soil




ingestion.






                                           73

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1.  Available Studies



     Binder et al. (1986) studied the ingestion of soil in children 1  to 3 years of age



wearing diapers.  The children studied were part of a larger study of residents  living



near a lead smelter  in East Helena, Montana. Soiled diapers were collected over a 3-day



period from 65 children (42 males and 23 females), and composited samples of soil were



obtained from the children's yards. Both excreta and soil were analyzed for  aluminum,



silicon, and titanium, elements thought to be poorly absorbed in the gut and  to have



been present in diet only in limited quantities, making them reasonable to use as tracers



in  a mass-balance calculation.  Both soil  and excreta measurements  were obtained for 59



children.  Using a standard assumed fecal dry weight of  15 g/d, soil ingestion by each



child  was estimated using each of the three tracer elements (assuming no absorption or



non-soil  source of these elements).  The  average quantity of soil ingested by  the children



was estimated at 121 mg/d [range 25 to 1,324] (aluminum tracer); 184 mg/d [range 31 to



799] (silicon tracer); and 1,830 mg/d [range 4 to 17,000] (titanium).  The overall soil



ingestion estimate based on the minimum of  the three individual element ingestion



estimates for each child was  108 mg/d [range 4 to 708].



     The authors were  not able to explain the difference between the results for



titanium and for the other two elements.  The frequency  distribution graph of  soil



ingestion estimates  based on titanium shows that a group  of 21 children had  particularly



high titanium values, > 1,000 mg/d; the  remainder of the children showed titanium



ingestion estimates  at lower levels, with a distribution more comparable to that for the



other elements.



     Clausing et al. (1986) conducted a soil ingestion study with Dutch children, using a



tracer element methodology similar to that of Binder et al. (1986).  Aluminum, titanium,



and acid-insoluble  residue (AIR) contents were  determined for fecal samples from



children, ages 2 to  4, attending a nursery school, and for samples of playground dirt at






                                           74

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that school.  Fecal samples were obtained daily over a 5-day period for the 18 children




examined.  Using the average soil concentrations present at the school, and assuming a




standard fecal dry weight of  10 g/d, the authors calculated mass-balance estimates of soil




ingestion for each material: aluminum, average 230 mg/d [range 21  to 878]; AIR, average




127 mg/d [range 48 to 362]; titanium, average 1,080 mg/d [range 53 to 9,588].  As in the




Binder et al. study, a fraction of the children (5/19) showed titanium  values of well




above 1,000 mg/d, with most of the remaining children showing substantially lower values.




Based on the minimum of the three chemical measurements for each child, an estimate of




100 mg/d, with a range of 21 to 362, was obtained.




     In a second  sample,  Clausing et al. (1986) collected fecal samples for six




hospitalized, bedridden children.  A mass-balance  calculation for these children, who




presumably  had very  limited  access to soil, yielded estimates of 46 mg/d based on



aluminum.   For titanium, two of the children had  estimates well in  excess of 1,000 mg/d,




with the remaining four  children in the range of 23 to 48 mg/d.  The data on




hospitalized children suggest  a major non-soil source of titanium for some children, and




may suggest a background non-soil source of aluminum. However, conditions specific to




hospitalization, e.g., medications, need to be considered. AIR measurements were not




reported for the hospitalized  children.  Speculation on  the source of titanium includes




diet, the white coloring in (disposable) diapers and several other items, but this has not




as yet been  resolved.




     Hawley (1985) developed scenarios for estimating exposure of young children, older




children, and adults to contaminated soil.  Hawley addressed  exposure by soil ingestion,




inhalation, and dermal contact.  His approach to estimating levels of ingestion is



presented here (see Table 4-1).  Each year was divided into two activity periods, May




through October, when individuals were assumed to spend much time outdoors, and
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       TABLE 4-1.  ESTIMATES OF SOIL INGESTION FROM DERMAL CONTACT
Scenarios
Young child (2.5 years old)
Outdoor activities (summer)
Indoor activities (summer)
Indoor activities (winter)

Older child (6 years old)
Outdoor activities (summer)
Indoor activities (year-round)

Adult
Work in attic (year-round)
Living space (year-round)
Outdoor work (summer)

Exposure
(mg/d)

250
50
100


50
3


110
0.56
480

Days/year
activity

130
182
182


152
365


12
365
43

Annual
average
(mg/d)

90
25
50
165

21
3
24

3.7
0.56
57
61
SOURCE: Hawley, 1985.
                                    76

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November through April, when weather conditions were assumed to eliminate outdoor




exposure to soil.  The following estimates were made by Hawley (1985).




     (1)  Young children (2.5 years old. 13.2 kg)




               Outdoor activity, May through October,  5 d/wk: 250 mg/d.  Estimate




               based on analysis of data from Lepow et al. (1974,  1975), who




               hypothesized 250 mg ingestion after experiments showed that dirt from a




               21.5  cm^ area of a child's hand typically had a mass of 11 mg.




               Additionally, Roels et al. (1980) measured contamination of children's




               hands by metal contaminants of soil while the children were active  on




               playgrounds.  These data led to an estimate  of 40 to 180 mg dirt being




               present on the dominant hand of an 11 -year-old (said to be equivalent in




               area  to both hands of a 2.5-year-old).




               Indoor activity, May through October: Child assumed to ingest 50 mg of




               household dust each day. Reference was made to the  previously cited




               experimental data.




               Indoor activity, November through April: 100 mg/d ingestion  assumed due




               to the longer period of indoor activity.




     (2)  Older Child (6 years old. 20.8 kg)




               Outdoor activity, May through October:  50 mg/d.  Using the surface dust




               value cited from Lepow et al. (1974) of  0.51 mg/cm^ on skin, a child is




               assumed to ingest dirt from an area equal to the area of the fingers on




               one hand.




               Indoor activity, year-round: 3 mg/d. Indoors, the child is assumed  to



               have dermal dirt present at the reduced  level of 0.056 mg/cm^, which is




               the quantity of dirt estimated by the authors to be present on surfaces
                                           77

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               within the home.  Dirt from inside surfaces of hands is assumed to be



               ingested.



     (3)  Adult (70 ke)



               Work in attics or other uncleaned areas of a house, 12 d/yr: 110 mg/d.



               Estimate based on ingestion of a 50-um-thick dust layer from the inside



               surfaces of the fingers and thumb of one hand while eating food or



               handling cigarettes.  Data from  Wolfe et al. (1974) are cited to support



               dust intake while smoking cigarettes.



               Living space activities: 0.56 mg/d.  Adults' hands are assumed to have



               dust contamination equal to that on indoor surfaces (0.056 mg/cm^), and



               dust is ingested from a lO-cm^  area of skin while eating or smoking.



               Outdoor activities, May  through October: 480 mg/active day.  The adult is



               assumed to be engaged in yard work or other outdoor physical activity



               for 8 hr/d, 2 d/wk.  The estimate is  based on ingesting a 50 um-thick



               layer of soil from the inside surfaces of the fingers and thumb of one



               hand twice daily.  These estimates  are summarized in Table 4-1.



2. Evaluation



     The data from the tracer element studies,  Binder et al. (1986) and Clausing et al.



(1986), provide support  for a preliminary estimate  of average soil ingestion by children



on the order of 100 to 200 mg/d, consistent with the "low" estimate used by Schaum



(1984).  These estimates are based on findings with silicon or AIR and aluminum.



Estimates based on a titanium tracer are higher by a factor of 5  to 10. This discrepancy



has not been explained,  but may be due to dietary and other sources.  Estimates based



on the minimum quantity  ingested as calculated using the three tracers are not utilized



here, because use of a minimum will tend to  bias the estimated ingestion downwards.



Hawley (1985), who estimated quantities of soil likely to be present on skin and






                                           78

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subsequently ingested, also arrived at an estimate in the above range.  It should be noted




that Hawley's approach would not address children who deliberately ingest dirt or mouth




soiled objects.




     Binder et al. (1986) and Clausing et al.  (1986) also provided some limited information




on the upper range of soil ingestion in children. With the exception of the titanium




data, the two studies provide evidence of an upper range of soil ingestion in children on




the order of  1,000 mg/d or more.  It should  be noted that both studies had limited




sample sizes and that neither specifically included (or excluded) children with pica (the



tendency to eat non-food materials). Again, estimates based on titanium would be



substantially  higher, on the order of 20 g/d.




     The Exposure Assessment Group is sponsoring a systematic study of soil ingestion




by children,  using the tracer element methodology.  Preliminary research has included a




study in miniature swine to assess the assumption that the tracer elements are poorly




absorbed, and to provide an experimental check on mass-balance calculations.




     The study in children includes a pre-pilot study to test field methods and to address




possible non-soil sources of titanium.  A randomly-selected sampling of  100 children will




provide an evaluation of soil ingestion in one location (Richland, Washington and




vicinity). Dietary contributions to tracer element intake will be measured in this study.




The results will be available in early 1988.




     Based on this review of the limited data now available, particularly the studies of




Binder et al. (1986)  and Clausing et al. (1986), the following values for soil ingestion  are




suggested:  Average soil ingestion in the population of young children (under the age of




7) is estimated at approximately 0.1 to 0.2 g/d. For calculation purposes, an estimate of




0.2 g/d is suggested as an average value.  An upper-range ingestion estimate among




children with a higher tendency to ingest soil materials  is  1  g/d.  These estimates are




based  on data using silicon and aluminum as trace elements.  The reason for the  higher






                                            79

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estimates for titanium are not understood, but the increase seems likely to be due to




non-soil factors.



F.  INGESTION — BEEF AND DAIRY PRODUCTS




     An indirect route of human exposure to 2,3,7,8-TCDD is that of soil contamination




and subsequent uptake in the food chain.  The foods subject to direct soil contamination




are those derived directly from plants and those derived from animals.




     While some general information is available on plant uptake of inorganic chemicals




and elements from soil, less appears to be known about uptake of large organic molecules




from soil.   The data on 2,3,7,8-TCDD uptake  is contradictory, as discussed in Section D




of Chapter 3.  The  few studies available on other halogenated hydrocarbons suggest low




absorption  by plants (Fries and Marrow, 1981; Jacobs et al.,  1976).  Further, most crops




consumed directly by humans are subjected to effective cleaning procedures that remove




most of the adherent soil or dust.  Consequently, the discussion that follows focuses on



foods derived from domestic cattle, grazing animals where commercial production often




involves potential direct contact, and ingestion of soil and deposited dust.




     Lengthy accounts of the factors involved in calculating human exposure to




2,3,7,8-TCDD from beef and dairy products are available (Schaum, 1984; U.S.  EPA, 1985b;




Fries,  1985, 1986).  Schaum (1984) and Fries  (1985, 1986) cited studies of soil




consumption by cattle and studies examining  ratios of contaminant levels in the diet to




resulting levels in body fat and milk fat for chemicals similar to 2,3,7,8-TCDD, such as




PCBs,  PBBs, and DDT (under various production scenarios) (see Section C of Chapter 3).




Exposure duration effects are also discussed in Schaum (1984).




     The potential  effects of "market dilution" of beef and dairy products on human




exposure are discussed briefly in Schaum (1984), at more length by Fries (1986), and at




much greater length in U.S. EPA (1985b) for the particular case of cattle production in




Missouri.   Aspects of the beef industry in this region specifically noted in U.S. EPA






                                           80

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(1985b) as important to estimating exposure were type of activity within the industry




[e.g. cow-calf production, "backgrounding" (preparing calves for feedlots), feeding (for




slaughter)], replacement rates as a function of activity, fractions of cattle fed to




maturity outside contaminated areas before slaughter, and slaughter categories and rates




relative to national figures.  Both Schaum (1984) and U.S. EPA (1985b) concluded that




dilution will vary widely between different marketing areas. Schaum (1984), U.S.  EPA




(1985b), and  Fries (1986) noted that the subpopulations most likely to receive high




exposures are beef producers, dairy farmers, and  their direct consumers and,  further,  that




exposure evaluations should be  very location-specific.




     Average consumption rates and fat content data for beef and dairy products are




presented in Table 4-2, which has been adapted from Schaum (1984) by addition  of




information from U.S. EPA (1984b, c) and Fries (1986).  Much greater "resolution"




actually is available in U.S.  EPA  (1984b, c) than is found in Table 4-2, since both (U.S.




EPA, 1984b,  c) are based on a U.S. Department of Agriculture (USDA) Nationwide Food




Consumption Survey (NFCS) conducted in 1977-1978.  The NFCS covered intake  of 3,735




possible food items by 30,770 individuals characterized by age, sex, geographic location,



and season of the year. Further description of the survey design is given in U.S.  EPA



(1984d).




     The average beef fat consumption noted in Table 4-2 ranges from 14.9 to 26.0 g per




70-kg  person/d, with a single high consumption estimate of 30.6 g per 70-kg person/day




that might be more appropriate for families of beef producers who home slaughter. Milk




fat consumption from all dairy  products ranges from 18.8 to 43 g per 70-kg person/d,




with the lower  end of this range  appearing best supported at present. Considering fresh




milk only,  milk fat consumption  is reported to average 8.9 to  10.7 g  per 70-kg person/d,




with a single high consumption estimate of 35 g per 70-kg person/d  perhaps appropriate
                                           81

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           TABLE 4-2.  RATES OF INGESTION OF BEEF AND DAIRY PRODUCTS
Total consumption
rate ± std. error
(g/70 kg person-d)
Percentage
of fat
Fat consumption
rate ± std. error
(g/70 kg person-d)
             Reference
124
110.7 ± 1.7
 87.6 ± l.la
 96.3
 66.8 (average)
137.1 (high)

Dairy products

550
308.6 ± 5.3
431.6 ± 5.6

Fresh milk (only)
     15
     23
    (23)
    (23)
     22
     22
      7.8
     (7.8)
     (4.4 implied)
     19
     26.0 ± 0.3
    (20.1 ± 0.3)b
    (22.1)
     14.9
     30.6
     43
    (24.1 ±
     18.8
0.4)c
              U.S. EPA (1981b)
              U.S. EPA (1984b)
              U.S. EPA (1984c)
              Berglund (1984)
              Fries (1986)c
              Fries (1986)
U.S. EPA (1981b)
U.S. EPA (1984c)
U.S. EPA (1984b)
253.5 ± 4.9
305 (average)
1000 (high)
(3.5)
3.5
3.5
(8.9)
10.7
35.0
U.S. EPA (1984c)
Fries (1986)
Fries (1986)
aThe categories established in U.S. EPA (1984c) exclude beef in meat mixtures
 (e.g., meat loaf), meat by-products (e.g., wieners), and organ meats.  The
 basic data set underlying both U.S. EPA (1984b) and U.S. EPA (I984c) was the
 USDA National Food Consumption Survey  1977-1978.  The basis for the difference
 in total dairy products consumption rates noted for U.S. EPA (1984b) and  U.S.
 EPA (1984c) has not yet been resolved.
bfleef fat consumption rates in parentheses are calculated using percentages of
 fat derived from U.S. EPA (1984b).
cThis and succeeding values from Fries (1986) reportedly derived from Breiden-
 stein (1984).
"Dairy fat consumption rates in parentheses  are calculated using percentages of
 fat derived from U.S. EPA (1981b).
                                           82

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for dairy farm families.  [Age range-specific information is available in both U.S. EPA




(1984b) and U.S. EPA (1984c).]




     Differences in beef and dairy fat consumption rates cited above from those used  by




Schaum (1984), and revised bioconcentration factors (Section C of Chapter 3), will result




in a reduction in estimated exposure.




G.  INGESTION — FISH CONSUMPTION DATA




1.  Available Studies



     A variety of definitions have been used for fish consumption.  Some studies examine




only commercially-caught fish while others do not distinguish between marine and




freshwater fish.  Others do not differentiate between fin and shellfish or fresh versus




processed fish.  Some data have been published which provide only nationwide averages




while others provide data for regions or states.  Consequently, drawing meaningful




comparisons between figures derived from different sources often is difficult.




     Different population bases have been used in the various surveys.  For example,




nonconsumers often are included in the population base for nationwide or regional




averages.  Reporting averages based only on consumers seems preferable on most




occasions, but so long as the basis for a given average  is reported unequivocally




modifications may be made as needed for later analyses.




     Several recent studies of fish consumption by the U.S. population are summarized




below.  These studies for the most part estimate consumption of certain population




subgroups and thus do not indicate an unequivocal need for changes in the average fish



consumption estimates presented by the Ambient Water Quality Criteria for 2,3,7,8-TCDD




(U.S. EPA,  1984), where an average daily consumption of 6.5 g/d per capita of  freshwater




and estuarine fish and shellfish  was derived from analysis of a survey of fish and




shellfish consumption in the United States  (U.S. EPA,  1980).  The variety of results  do
                                           83

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emphasize the need to base consumption assumed in a particular exposure assessment on




studies involving similar populations.



     Data from  the Nationwide Food Consumption Survey conducted by  the USDA in




1977-1978 were not available when the U.S. EPA derived the 6.5 g/d figure for




consumption of  freshwater and estuarine fish (Stephan, 1980).  The USDA survey obtained




information on both household and individual intake of food products.  Interviews were




conducted to determine food consumption in households during the previous week, and




included a 1-day recall plus a 2-day diary of individual food intake. A national




probability sample of households in the continental United States was obtained by means




of approximately 15,000 interviews covering over 36,000 individuals. Supplemental surveys




of households with elderly and low-income individuals were conducted.  Separate data




were gathered for Alaska, Hawaii, and Puerto Rico.




     Specific information was gathered, including use of specific fish species, as well as




the state of processing (fresh, frozen, etc.).  Analysis of the  data indicated an average




individual intake as 12 g/d fish and shellfish (edible weight) on a per capita basis




nationwide, although geographic regional averages ranged from 9 to 14 g/d, with highest




consumption in  the Northeast (U.S. Department of Agriculture, 1985).  Total population




figures, including non-consumers, were used in computing these averages.  This survey




also presents fish consumption by age group and season of the year. Other USDA




publications have provided average figures for fresh commercial fish — in 1983, an




average of 6.4 g/d was estimated to have been consumed per person.




     The most recent fish consumption data from the National Marine  Fisheries Service




(NMFS)  report total per-capita fish and shellfish consumption at 6.2 kg/yr (16.9 g/d)




(U.S. Department of Commerce, 1985).  This estimate is based on the commercially-landed




fish and shellfish catch only.
                                           84

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     An earlier report in the series (U.S. Department of Commerce, 1983) gave




consumption of edible weights of fresh and processed commercial marine fish  and




shellfish as 9.9 g/d per capita, based on yearly catches, imports, exports and existing




inventories.  The recreational catch  has been estimated to contribute an additional 3.7 to




5 g/d, based on  information from the National Oceanographic and Atmospheric




Administration (as cited in U.S. EPA, 1986a).




     U.S. Department of Commerce (1983) also reports 3.7  -  5.3 g/d (edible weight),




marine fish and  shellfish are consumed by recreational fishermen, fairly close  to an SRI




analysis showing consumption of 5.3 g/d of fish from recreational sources. Cordle (1981)




reported a 90th  percentile consumption of 15.7  g/d for Great Lakes region consumers




only and a 99th  percentile figure of 36.8 g/d.  No average  figures were presented.



     A National Seafood Consumption Survey was conducted by the NMFS in 1981 with a




panel of 7,500 households (NMFS, undated).  The households kept diaries on the amount




of fish and other seafoods purchased for household use, as  well as the amount actually




eaten both at home and away from home.  Purchase data are broken out by species,




nature of product (fresh, frozen, etc.), region, and a variety of demographic factors.




The Longwoods Research Group (1984) analyzed some of the 1981 NMFS data based upon




frequency of use rather than quantities consumed.  This revealed that 82% of  all




projected U.S. households eat seafood or fish.




     Still earlier (1969-1970), a Market Facts Survey conducted for NMFS revealed a per




capita total fish  consumption figure of 16.8 g/d of which 6.1 g/d consisted of fresh and




frozen fin fish.  This survey did not discuss explicitly whether portions were based on




edible weight or if recreational sources were considered.




     A National Purchase Diary (NPD) Fish Consumption Survey was performed for the




Tuna Research Institute in 1973-1974 with the results based only on  actual consumers of




fish rather than  total population (U.S. EPA, 1980).  The questionnaire was administered






                                           85

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to a total of 7,662 families (around 25,000 people) over one year, with 1/12 of the

families responding in a given month to eliminate seasonal effects.  Cordle et al. (1982)

later used data from this survey as the basis for their estimate of consumption totalling

18.7 g/d.  According to Conner (1984) the NPD Survey data show 6.5 g/d of estuarine

fish and shellfish and 2 g/d of freshwater fish are consumed.  SRI International later

reexamined the data tapes of the NPD Survey and found numerous discrepancies (U.S.

EPA, 1980).  A corrected version of the data base resulted in an average consumption

figure of 14.3 g/d total fish, with a 95th percentile value of 41.7 g/d.  SRI International

also presents  average and 95th percentile figures for each sex and different age groups

(U.S.  EPA, 1980).

     Race and religion, as well as regional factors and age, may have strong impacts on

fish consumption rates.  The Market Facts Survey reported seafood consumption by U.S.

blacks and people of Jewish faith to be approximately twice that of whites as a whole

(U.S.  EPA, 1980).  However, the NPD Research Survey for the  Tuna Research Institute

reported only a 13% higher consumption rate among blacks (U.S. EPA, 1980.  The NPD

survey also found that orientals consumed fish at a rate 47% above Caucasians.  The 95th

percentiles of fish and shellfish consumption typically were a factor of three above

averages for  the different population groups.

     According to the USDA publication  Foods  Commonly Eaten bv Individuals: Amounts
     per Dav and Per Eating Occasion, consumers of fin fish other than canned, dried or
     raw, consumed an average (mean) of 54  g/d/person.  It is  not apparent what
     percentage of fin fish is recreationally caught.  The following percentile distribution
     was given:   50th percentile - 38 g/d; 90th percentile  - 96 g/d; 95th percentile -
      132 g/d; 99th percentile - 221 g/d.

     The  difference between the mean and median (50th percentile) indicates that the
     amount of fish consumed is not distributed in a normal pattern among the consumer
     population.  It is also worthwhile to note the increase in average daily amount over
     those presented by the first series of surveys, which included  non-consumers as
     well.  [C.F.  Kleiman, "Fish Consumption  by Recreational Fishermen:  An  Example  of
     Lake Ontario/Niagara River Region" Environ Corporation, prepared for OECM, U.S.
     EPA, Washington, D.C., May 20,  1985, page 6.]
                                           86

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     Puffer et al. (1983) reported the results of a survey of fishing habits and fish

consumption rates among fishermen in the Los Angeles area.  Interviewers obtained

information from fishermen at 12 representative locations identified as frequently fished.

A total of 1,059 interviews were conducted from an estimated sport fishing population of

at least 31,000.  Approximately half of the  fishermen fished  one or more times per week,

with 14% of those interviewed fishing three to seven times per week.  The majority of

fishermen interviewed consumed the fish they caught.  The median amount of fish

consumed by the fishermen themselves was reported to be 37 g/d, with the 90th

percentile at 225 g/d. (The report estimated that at least 100,000 family members of

fishermen shared fish they caught.) These  consumption rates are substantially above

those for the general population.  These data do not take into account consumption of

fish purchased from stores.

     Individuals in other areas are known to have a high intake of sport fish. A study

by  the Michigan Department of Public Health (Humphrey et al., 1976) examined the health

status of individuals who consumed at least 30 g/d (annual average) of Great Lakes  fish.

The highest recorded fish consumption over the two-year study period was 224 g/d.

     The Puget Sound Estuary Program (U.S. EPA, 1986c) developed a guidance document

that included a useful framework for assessing quantities of fish consumed by local

populations; however, no data specific to Puget Sound were presented.

     The New York State Department of Environmental Conservation (NYSDEC) uses a
     figure of 32.4 g/d  in their health advisories, as the average fish consumption for
     recreational fishermen, based upon the 90th percentile of nationwide fish
     consumption figures (A. Newell, personal communication)...

     A survey of users of the 1983 Guide to Eating Ontario  Sport Fish (Ontario Ministry
     of the Environment, 1984) revealed that Ontario sports  fishermen eat locally-caught
     fish approximately once every 3 weeks, with an average meal size of 289 g (10.2
     oz), corresponding to  an average daily figure of 13.8 g/d.  A substantial percentage
     of respondents (26%) ate at least a pound of fish per meal.   However, as this survey
     is based on voluntary responses to a questionnaire, it may be subject to self-
     selection biases...
                                           87

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     Finally, a personal communication from R. Sonstegard, who is currently studying
     Lake Ontario sports fishermen, indicated that "intensive" fishermen (1 week trips in
     spring and fall, and weekends throughout the year) can consume 62 g of salmon and
     trout per day. An "average" figure of 31 g/d, with a range of 0-311 g/d, was also
     cited. [C.F. Kleiman, "Fish Consumption by Recreational Fisherman:  An Example of
     Lake Ontario/Niagara River Region" Environ Corporation, prepared for the Office of
     Compliance and Enforcement Monitoring.  U.S. Environmental Protection Agency,
     Washington, D.C., May 20, 1985,  pages 6-9].

2. Evaluation

     Substantial recent information on  fish consumption rates has become available

through the surveys conducted by USDA and NMFS.  While these surveys do not indicate

the need for  major revision of previous fish consumption estimates,  they can provide

more recent information and will allow examination of the fish  consumption habits of

particular population subgroups. The data from these surveys would also allow

recalculation  of the U.S. EPA's estimate of human consumption of freshwater and

estuarine fish and shellfish. Because current information indicates that some population

groups consume fish at rates much above the national average, this work could be of

significant value in determining the risks from 2,3,7,8-TCDD contamination that may be

encountered by specific population groups.

     Based on  this review, the 6.5 g/d  average consumption rate for freshwater and

estuarine fish and shellfish that has been used in previous U.S. EPA assessments is still

appropriate.  To account for individuals who habitually consume larger quantities  of fish,

a value of 30 g/d is suggested based on the Los Angeles and Great Lakes data.

     EPA (1987a) references the following values of average consumption rate that may

be assumed when site-specific data are unavailable:

     (a)  6.5 g/d represents an estimate  of average consumption of fish and shellfish

          from estuarine  and fresh waters by the U.S. population;

     (b)  20 g/d represents an estimate of the average consumption of fish and shellfish

          from marine, estuarine, and fresh waters by the U.S. population;
                                           88

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(c)   165 g/d represents average consumption of fish and shellfish from marine,




     estuarine, and fresh waters by the 99.9th percentile of the U.S. population; and



(d)   180 g/d represents a "reasonable worst case" based on the assumption that




     some  individuals would consume fish at a rate equal to the combined




     consumption of red meat, poultry, fish, and shellfish in the U.S.
                                      89

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5.  POST-EXPOSURE



     Within the last few years, two important areas have come increasingly under study



with regard to the fate of 2,3,7,8-TCDD once exposure has occurred; they are




bioavailability and pharmacokinetics. Unavailability, the first of these areas, refers to  an




organism's ability to remove 2,3,7,8-TCDD from an ingested or inhaled particle and then




to  absorb it. Strictly speaking, bioavailability is a property of both the material to which




an .organism is  exposed and the organism's capabilities and pharmacokinetic responses.




However, it is useful to assume for the present that the organism's extraction ability is




constant, and to look at bioavailability as a property of the material.  Recent research




has observed that 2,3,7,8-TCDD adsorbed on various substrates can differ in




bioavailability by approximately an order of magnitude. The current state of knowledge




about the causes of bioavailability differences is incomplete, but early hypotheses (based




on a very small data set) hold that the bioavailability of 2,3,7,8-TCDD from various




materials can be related to chemical availability measured by solvent extraction.  Most




contaminated soils tested so far (five) show bioavailability in animal tests of about 25%




to 50% that of 2,3,7,8-TCDD in corn oil  given by gavage.  Three soil samples spiked with




2,3,7,8-TCDD  had bioavailabilities in the 40% to 70% range compared  with corn oil. Based




on limited data, 2,3,7,8-TCDD in fly ash proved roughly 25% as bioavailable as 2,3,7,8-




TCDD from the solvent extract of the fly ash. (It should be noted that in this




experiment 2,3,7,8-TCDD from both fly ash and solvent extract were  recovered from the




rat liver in low quantities, making interpretation of the experiment difficult.) Studies




with soil from  one site, and with activated carbon with dioxin added, however, showed




gut bioavailabilities of < 10%, and <  1% compared with 2,3,7,8-TCDD in solvents,




respectively.




     The implications of this early work  are important, since estimated risk following




intake of an environmental matrix will  be proportion to bioavailability. At this point, it






                                           90

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is unclear what the long-term implications of bioavailability differences will be to risk




assessment.  Some soils have shown high 2,3,7,8-TCDD bioavailability, while bioavailability




in one tested soil is lower.  No data on the distribution of contaminated soils by




bioavailability currently exist  to allow this difference to be  systematically considered, nor




is there an accepted protocol for measuring bioavailability from soil on a site-by-site




basis.



     The second important post-exposure area of study is pharmacokinetics. Theoretically,




if one knows what happens to the 2,3,7,8-TCDD once it  is  absorbed,  one can look at




body burdens and back-calculate an average dose, or average exposure. In practical




terms, this procedure can lead to reduced uncertainty in a risk assessment by allowing




calculation of exposure from two independent methods. Currently, our ability to perform




these pharmacokinetics calculations is in its early stages of  development. There  are




significant difficulties in current approaches to using body  burden data to back-calculate



exposure, and at this point verification of certain not-easily-verified  assumptions needs




to be done before such calculations can become standard tools for exposure  assessment.




It is safe to say that, in the future, the role of pharmacokinetics in exposure assessment




will increase.




A.  ABSORPTION FROM  ENVIRONMENTAL MATRICES (BIOAVAILABILITY)




I.  General Considerations




      Following  ingestion of a material containing 2,3,7,8-TCDD or other toxic species,




the toxic effect of the material is modified by the degree of absorption, principally in




the small intestine.  In several experimental studies, investigators  administered 2,3,7,8-




TCDD-containing environmental matrices to experimental animals, and measured




parameters relating to bioavailability.  These studies included quantitation of 2,3,7,8-




TCDD in liver and other tissues following treatment; comparison  of toxicities of




contaminated environmental materials with pure 2,3,7,8-TCDD; and examination of enzyme






                                            91

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induction.  The results of these different approaches, their limitations, and needs for



further research are discussed below.



2. Review of Data on Bioavailabilitv



      Umbreit et al. (1985, 1986a,b) conducted experiments in guinea pigs, administering



2,3,7,8-TCDD in corn oil, 2,3,7,8-TCDD added to chemically decontaminated soil, or soil



from two industrial sites in Newark, New Jersey (a manufacturing site and a salvage site)



contaminated with CDDs.  2,3,7,8-TCDD was the principal lower chlorinated isomer



(dioxin or furan) present in the soil from the manufacturing site (for which a chemical



analysis was presented).  Soil from the manufacturing site was found to have  1,500 to



2,500 ppb 2,3,7,8-TCDD under soxhlet extraction; release under ambient temperature



manual solvent extraction was much lower, reported as ">2.5 ppb."  The soil from the



salvage site was reported as approximately  180 ppb 2,3,7,8-TCDD under soxhlet



extraction.



     Table 5-1 summarizes the findings of the study, in which groups of two or four



male and two or four female guinea pigs received single gavage doses of the test



materials and were observed until death or sacrifice at 60 days. 2,3,7,8-TCDD in corn oil



or in recontaminated soil (6 /ig/kg in both) proved highly toxic, without similar toxicity



being observed in animals treated with up to twice this dose of 2,3,7,8-TCDD in the soil



from the manufacturing site. The limited data on 2,3,7,8-TCDD levels in the liver showed



much higher levels following administration of recontaminated soil versus contaminated



soil from the manufacturing site.



     Umbreit et al. (1986a) thus demonstrated that gavaged 2,3,7,8-TCDD containing soil



from the manufacturing site was substantially less toxic than equivalent doses of 2,3,7,8-



TCDD in corn  oil.  However, quantitative comparison of the effective doses in this study



is difficult.  Approaches to a quantitative comparison are outlined below.
                                           92

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TABLE 5-1.  GUINEA PIGS RECEIVING A SINGLE GAVAGE DOSE
        OF MATERIALS CONTAINING 2,3,7,8-TCDD
Treatment
2,3,7,8-
TCDD
Early
deatha
2,3,7,8-TCDD
ppb in liver"
NEWARK MANUFACTURING
Decontamin-
ated soil6
Contaminated
soil6


Recontamin-
ated soil
Corn oil
TCDD in
corn oil

Decontamin-
ated soil
Contaminated
TCDD in
corn oil

0

3
6
12
6
0

6


0
0.32

6

0/7

0/8
0/7
0/7
6/7
0/7

5/8
NEWARK

0/4
0/4

3/4

NR

NR
NR
0.09 (0.07%)f
18.0 (14%)f
NR

NR
Effects
noted0
SITE

N

N
N
N
TS
N

TS
%weight
gain
0-4 weeks"


70

83
57
51
25
57

37
SALVAGE YARD SITE

NR
0.23 (5.8%)f

NR

N
N

TS

NR
NR

NR
                     93

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                               TABLE 5-1  (continued).

aGavage deaths excluded from counting; all treatment deaths occurred < 31 days
 after dosing.
^Results of analysis of single pooled liver tissue samples from subsets of the
 tested animals.
CTS = "Typical signs" of 2,3,7,8-TCDD toxicity including thymic atropy, absence of
 body fat,  and loss of approximately 40% of  body weight.  N = "Typical signs" not
 present.
^Data for survivors only.
eSoil type at  site reported to be medium dense, black, coarse to finegrained sand
 fill with some medium to fine gravel, and with traces of silt, organic material,
 and cinders.  Fill material at site included asphalt.  No chemical characteriza-
 tion of the soil sample was reported.
'Approximate percent of gavage dose found in liver, assuming liver is 4.7% of body
 weight. For the group receiving soil from the salvage site, no weight gain data
 were reported and a 100%  weight gain (0 to 8 weeks) was assumed, which is consis-
 tent with  other surviving groups. Liver weight data were not available to allow
 more precise calculation.
SSoil type at  site reported similar to  that at Newark  manufacturing site.
 Still bottoms were dumped on the site during salvage operations and were incor-
 porated into soil.  No other characterization of soil  sample was  reported.
NR = Not  reported.

SOURCE:  Umbreit  et al., 1985, 1986a,b.
                                           94

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(1)   Guinea pigs receiving 12 fig/kg 2,3,7,8-TCDD jn contaminated soil




     experienced no deaths, while five out of eight guinea pigs receiving




     6 Mg/kg 2,3,7,8-TCDD in corn oil died, with no groups tested having




     lower doses in corn oil. Other authors have provided data on the




     toxic effects of 2,3,7,8-TCDD in corn oil which could aid in the



     comparison.




          McConnell et al. (1984) observed one out of six animals dying at  1




     and six out of six animals dying at 3 Mg/kg.  Silkworth et al. (1982) observed




     three out of six animals dying at 2.5 /*g/kg and no deaths out of six at 0.5




     /ig/kg. Comparing these data directly with the Umbreit et al. results would




     suggest that the 2,3,7,8-TCDD in the Newark manufacturing site soil was less




     effective, by a factor of 10 or greater, in producing toxicity than  2,3,7,8-




     TCDD in corn oil.




(2)  Umbreit et al. reported a "slightly reduced" weight gain in guinea pigs




     receiving 6 Mg/kg of 2,3,7,8-TCDD in Newark manufacturing site soil, and a




     "greater reduction" at the  12 /ig/kg dose.  No  other signs  of toxicity were




     noted in these groups. The animals receiving 6 /*g/kg 2,3,7,8-TCDD  in corn




     oil, in contrast, exhibited a marked loss of body weight and showed toxicity



     and mortality.  Silkworth  et al. (1982) also provided data on weights of guinea




     pigs receiving 2,3,7,8-TCDD in corn oil.  Those receiving 2.5 ^g/kg exhibited a




     marked reduction in weight gain among three out  of six survivors, while those




     receiving 0.5 /ig/kg showed a weight gain comparable  to vehicle controls.




     Comparison of this weight data with that of Umbreit et al. suggests that the




     2,3,7,8-TCDD in corn oil was more than 5 times but less than 25  times as




     potent as 2,3,7,8-TCDD in the Newark soil.  This comparison assumes that the




     effect of the Newark manufacturing site soil on weight gain  was due to






                                       95

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          2,3,7,8-TCDD as opposed to other compounds in the soil.  Numerous other




          dioxin and furan compounds and other chemicals have been identified in this



          soil (Umbreit et al., 1987a).  It has not been established that 2,3,7,8-TCDD is




          the sole or prime source of toxicity in the soil.




     (3)   Umbreit et al. presented liver concentrations of 2,3,7,8-TCDD after death or




          sacrifice at 60 days following gavage (see Table 5-1).  Much lower




          concentrations of 2,3,7,8-TCDD were found in the livers of animals receiving




          soil from the manufacturing site compared with those receiving the dose in




          cordn oil.   There are, however, two factors that limit the conclusions  than can




          be drawn  from this comparison.




     First, the corn oil group experienced major toxicity and weight loss, particularly




complete loss of body fat.  These changes may have  affected the partitioning of 2,3,7,8-




TCDD within the body, leading to a higher concentration in the livers of the animals




experiencing toxicity.  Second, the animals gavaged with corn oil died early—half were




dead by 26 days, while all of the guinea pigs treated with soil survived to 60 days (with




the exception  of one gavage death).  The U.S. EPA (1985d) reported a half-life  for




2,3,7,8-TCDD elimination of 30 + 6 or 22 to 43 days from two studies in guinea pigs.




Additionally, the U.S. EPA (1985d) stated that elimination in the guinea pig may follow




zero-order kinetics.  Differences in elimination due to differences in periods of survival




are likely to have affected the relative quantities of 2,3,7,8-TCDD found  in the livers of




the test groups.




     Perhaps a more appropriate comparison can  be  made with the four   animals




receiving 0.32 /ig/kg of 2,3,7,8-TCDD in  contaminated soil from the Newark salvage site.




These animals experienced no reported toxic signs (weight data not presented) and




survived  the full 60-day experiment. Approximately 6% of the gavage dose was found in




the liver  of these animals (Table 5-1), while only about 0.06% of the gavage dose was






                                           96

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found in the livers of guinea pigs in the  12 pg/kg group receiving the Newark



manufacturing site soil. This would suggest that the 2,3,7,8-TCDD in the manufacturing




site soil was 100 times less bioavailable.  However, given the different doses used and




the fact that only a single pooled sample was analyzed for 2,3,7,8-TCDD in each group,




caution must be used in interpreting this comparison.




     The 2,3,7,8-TCDD in soil from the salvage site was substantially bioavailable, based




on the single liver tissue analysis.  Approximately 6% of the administered dose was




recovered from the livers  of these animals at 60 days. This can be compared with data




on hamsters given 2,3,7,8-TCDD in corn oil by McConnell et al. (1984), where




approximately 8% of the 2,3,7,8-TCDD could be recovered in the 1 Mg/kg dose group




among survivors at 30 days.




     McConnell et al. (1984) treated Hartley guinea pigs (2.5  weeks old) with single




gavage doses of either 2,3,7,8-TCDD or dioxin contaminated soil from two sites in




Missouri. The 2,3,7,8-TCDD concentrations from the two sites were reported at 700 and




880 ppb respectively; total tetrachlorodibenzofurans (TCDF) concentrations in the soil




were 40 to 80 ppb, and polychlorinated biphenyls (PCB) concentrations were 3 to 4 ppm.




Taking into account the relative toxicities, the authors concluded that toxicity from the




other compounds was likely to be small compared with that from 2,3,7,8-TCDD.  The




results of the study are shown in Table 5-2.  Livers were  analyzed for 2,3,7,8-TCDD at



death or sacrifice at 30 days following treatment. Treatment deaths occurred between



5 and 21 days post-gavage.




     Guinea pigs that died exhibited severe loss of body fat, markedly reduced  thymus




and testicle size, and adrenal hemorrhage.  No adverse affects were noted in animals




treated  with decontaminated soil.  For 2,3,7,8-TCDD in corn oil and for both




contaminated soils, there were clear dose-responses  in mortality.  The calculated LD5Q
                                           97

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                      TABLE 5-2. TOXICITY OF TCDD CONTAMINATED SOIL
                        2,3,7,8-
TCDD in liver (ppb)
f% Admin. dose)a»b
                                                                     Estimated LD50
TCDD dose
Group # Treatment /*g/kg
1 Corn oil 0
2,3,7,8-
2 TCDD in 1
corn oil
3 3

Times Beach
4 soil c»d 1.3
5 3.8

6 12.8

Minker Stout
7 soilc'd 1.1
8 3.3

9 11.0

Uncontamin-
10 ated soild 0
Uncontamin-
ated soil with
11 2,3,7,8-TCDD 10
added3
Dead/
treated
0/6

1/6

6/6


0/6
1/5

5/5


0/6
2/6

6/6


0/5


0/6

Alive at Animals
30 d dying
ND

1.6 +.02 4.1
(7.5%) (19%)
13.3 + 2.3
(26%)

(™&b)
1.0 + 0.1 3.2
(1.3%) (4.0%)
34.3+6.0
(13%)

*(<«%)
1.4 + 0.3 2.0 + 0.1
(2.0%) (2.8%)
25.7 + 5.2
(11%)

ND

\
45.3 + 8.4
(21%)


1.75
(95% CL
1.26-2.24)




7.15
(95% CL
4.90-9.40)



5.50
(95% CL
3.45-7.55)








Source: McConnell et al. (1984).
                                       98

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                                   TABLE 5-2 (continued).
aThe percentages of the administered doses found in the liver were calcu-
lated assuming a liver weight of 4.7% of body weight. For survivors,
the percentages are underestimated to some degree because data on
weight gain over  the study period were not available.

''Animals were observed for up to 30 d when survivors were sacrificed.

cSoil was sifted through a wire mesh to remove gravel particles.  No
details on soil type or composition presented.  The soil was contaminated
by waste oil containing 2,3,7,8-TCDD and other dioxins and furans.
The presence of residual waste oil in the soil was not specified.

^Soil was administered as a gavage dose in distilled water.
                                           99

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values for the two soil types were lower than the LD5Q for 2,3,7,8-TCDD in corn oil by




a factor of three- to four.



     There was  a dose-response between the liver concentration of 2,3,7,8-TCDD and the




gavage dose; the details  of this, relationship are  complex.  Animals dying  during the




experiment had  liver concentrations a factor, of 1.4  to 3.2 higher than animals in the




same  dose groups who survived. 30  days.   This observation makes  quantitation of the




dose-response relationships difficult (all or most of the animals  in the  low-dose groups




survived the experiment,  while all of the animals  in  the high-dose groups died).  When




the; liver concentrations of 2,3,7,8-TCDD in animals dying early at the middle and high-




dose  groups  are compared,  there appears to be a greater-than-linear increase  in liver




concentration with dose  for the  Times Beach and  Minker Stout soil  groups, with a 3.3-




fold increase in  dose producing a 10- to 13-fold increase in liver concentration.




     Liver concentrations of animals in the different dosing groups can best be compared




among groups that experienced similar mortality.




     (1)   Animals in dose groups in which all animals  died within 30 days:  2,3,7,8-TCDD




          in corn oil (group 3), approximately 20% of the  administered dose was  in the




          liver.   For the  soil-treated groups (groups 6 and 9), 13% and 11% of the doses,




          respectively, were in the liver.  Comparison of these data suggest  that 2,3,7,8-




          TCDD was approximately twice as available through corn oil as through soil.




     (2)   Animals surviving the 30-day experiment (in groups where at least 4  out of 6




          survived):  For 2,3,7,8-TCDD in corn oil (group 2), 7.5%  of  the  administered




          dose  was  in the liver.  For soil-treated  animals (groups 4, 5,  7, and 8) < 3.6,




          1.3, < 4.2, and 2.0% of the doses, respectively, were in the liver.  Comparison




          here would suggest that 2,3,7,8-TCDD was approximately four  times as  available




          through corn oil as through soil.
                                           100

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     The authors note that the  differences in liver concentrations observed in the study




may reflect varying partitioning of the 2,3,7,8-TCDD among internal organs, since dying




animals suffered major loss of body weight and fat content. In addition, surviving animals




would have had  greater opportunity to metabolize and excrete 2,3,7,8-TCDD  due to a




longer lifetime.




     Umbreit et al. (1986a) reported additional chemical analyses of the Times Beach soil.




Soxhlet extraction of  the Times Beach soil yielded a similar quantity of 2,3,7,8-TCDD to




the solvent extraction reported by McConnell et  al.  (1984).  This  is in contrast  to the




Newark manufacturing site soil  used  in  the Umbreit et  al. (1987a)  experiments,  where




only a small fraction  of soxhlet-extractable  2,3,7,8-TCDD was extractable by the solvent




extraction methodology used by McConnell et al. (1984).




     McConnell et al. (1984) also reported an experiment in which groups of six Sprague-




Dawley rats were given  single  gavage doses of  2,3,7,8-TCDD  in corn  oil  or dioxin-




contaminated  soil from the Minker  site.   Induction of  aryl hydrocarbon hydroxylase




(AHH) in  the rat livers  was measured at sacrifice 6 days  after dosing.   Experimental




doses ranged from 0.4 to 5.0 Mg/kg 2,3,7,8-TCDD.  Measured AHH induction  was similar




for groups receiving  2,3,7,8-TCDD in corn  oil or receiving  contaminated  soil containing




nearly equal doses of 2,3,7,8-TCDD.  For example (based on the  rate of formation of 3-




hydroxybenzo[a]pyrene), AHH  activity was measured  at 1,269 pmole min~^ mg~'  for the




group receiving 5 A*g/kg 2,3,7,8-TCDD in corn oil and at 1,230 pmole min~l mg~^  for the




group receiving 5.5 /Jg/kg 2,3,7,8-TCDD in  contaminated soil. For  the five dose  groups,



the AHH activity for the soil group ranged  from 50% to 110% of the activity  in the corn



oil group.




     The McConnell  et al. rat data indicate that the bioavailability of 2,3,7,8-TCDD from




the Minker site soil was at least 50% of that  of equivalent doses of 2,3,7,8-TCDD in corn



oil.






                                           101

-------
     JLucier  et  al. (1986) provided  additional information on  the  induction of hepatic




enzymes in rats  by the 2,3,7,8-TCDD contaminated soil  from the Minker site tested  by



McConnell et .al. (1984).  AHH induction was  similar for the groups  of rats receiving




,2,-3,7,8-T.CDD .in .corn oil .and,contaminated soil (within a factor  of two) over a broader




range of doses (0.015 /ig/kg to 5 Mg/kg) than reported by McConnell et al.  In a second




enzyme assay using the same animals, UDP glucuronyltransferase activity was found to be




slightly higher -in groups receiving 2,3,7,8-TCDD in corn oil  than groups receiving equal




.doses in contaminated soil.




     .Liver concentrations of 2,3,7,8-TCDD for the rats were  also  reported.  For the corn




oil vehicle the  liver  concentrations were  40.8 ± 6.5 ppb at  the 5 /ig/kg  dose  and 7.6 ±




2.5 ppb .at the  1 pg/k% dose.   Assuming that the  liver comprises 4.0% of body weight,




the retention rates for the 5 ;and 1 /ig/kg doses  were 33% and 30%, respectively.  In rats




receiving 2,3,7,8-TCDD in contaminated soil, the 5.5 jig/kg group  had liver concentrations




of  20.3 ±  12.9  ppb, and the  1.1  MgAg group  had concentrations  of 1.8 ± 0.3.   Thus,




retention  rates   for  the  5.5  and  1.1  /ig/kg  groups  are estimated  at   14%  and 7%,




respectively.   These  data  indicate  that liver retention  in  the  soil  group was 20% to 40%




of that  in the corn oil vehicle groups.




     Umbreit et al (1986b)  report additional  studies of mortality in  guinea pigs  treated




with soil containing 2,3,7,8-TCDD from Newark (manufacturing site) and Missouri (Times




Beach)  previously  tested  by  Umbreit  et  al   (1985,  1986a) and  McConnell  (1984),




respectively.   Guinea pigs received  a single gavage dose of  a soil suspension and  were




observed  for 60  days.   After autopsy, deaths  were  classified as  whether or  not they




appeared to  be  due to TCDD toxicity. Substantial mortality (25%  overall)  from conditions




not attributed to TCDD was  observed across all groups.  Table  5-3 contains the study




observations.
                                           102

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     The data  for  both  the  Newark and  Missouri  sites  are  similar in trend for the

previous data on these sites; and clearly indicate the greater toxicity of  the Newark soil

for given equal administered  doses of 2,3,7,8-TCDD.  With larger  groups of guinea pig

studied, a toxicity-related death was observed in both the 5  and 10 Mg/kg dose groups

for Newark soil while no deaths were observed in corresponding dose groups (6 and 12

A*8/kg) with fewer animals in  Umbreit et al (1986a).

          TABLE 5-3.  COMPARISON OF MORTALITY  IN GUINEA PIGS
            FOLLOWING A SINGLE DOSE OF CONTAMINATED SOILS
Treatment TCDD
(Mg/kg)
Decontaminated Soil
Newark Soil


Times Beach Soil


Recontaminated Soil
0
3
5
10
1
3
10
10
# Deaths
Attributed to
TCDD Toxicity
0
0
1
1
2
1
8
19
# Animals
Treated Minus
Deaths Not Due
to TCDD
13
12
14
10
16
13
11
19
Source:  Umbreit et al (1986b)
                                         103

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     Comparing groups  within this study, similar mortality (1  or 2 deaths in 10 to 16




animals) was seen  in  both the 5 and 10  /Jg/kg Newark groups and the 1 and 3 jig/kg




Missouri groups. These results suggest that the  toxicity of these materials, differs by an




order of magnitude or less.  As noted above the degree to which toxicity from thesesoils




can  be attributed  to  2,3,7,8-TCDD in  the presence of  numerous other related  toxic




compounds is not known..  2,3,7,8-TCDD tissue concentrations  were not reported in this




work..




     In  another comparative  study  Umbreit  et  al.  (1987b)  compared  the  Newark




manufacturing   site and  Times  Beach  soils  in  the  induction  of aryl  hydrocarbon




hydroxylase  (AHH)  in  rats.   While  the use  of  only  single  dose levels  prevents




detailedanalysis, the two soils  proved quite similar in their ability to induce AHH.  The




explanation for  the difference, in this finding from those observed in the toxicity studies




discussed above is  not clear,  but may relate to the presence of other toxic and/or AHH




inducing compounds.




     Umbreit et al.  (1987a)  report  a  reproductive toxicity  study with soils  from  the




Newark  manufacturing  site and  salvage  yard previously studied  by  Umbreit (1986a).




Female mice were treated thrice weekly  with soil  from  these sites, with  treatment




continuing through  fertilization to weaning of pups.  The total doses of 2,3,7,8-TCDD




received by the mice were 720 pg/kg in manufacturing site soil, and 86 /*g/kg  in salvage




yard soil.  A corn  oil vehichle group and are contaminated soil group received a total of




225 /jg/kg.




     Deaths  in  animals  showing "classic signs" of TCDD  toxicity were observed in the




corn  oil  and  recontaminated  soil  groups, and  indicate  appreciable  bioavailability  of




2,3,7,8-TCDD.  Deaths were also observed in animals receiving manufacturing site soil but




the authors did not observe "classic signs" of  TCDD toxicity. Fewer live  pups born and




fewer pups surviving  until weaning were observed in the manufacturing  site  soil group






                                           104

-------
compared  with  those  receiving  decontaminated  soil.    TCDD  completely  blocked




reproduction in the corn oil  and recontaminated soil groups.  The  results  of this study




demonstrate acute and  reproductive effects occurred in animals receiving manufacturing




site soil.  However, these  effects were of a lesser magnitude than those seen  in animals




treated  with 2,3,7,8-TCDD in corn oil at a dose three fold lower.  The authors note the




presence of substantial quantities of other toxic substances in the  manufacturing site soil




(chemical analyses presented).   No toxic  effects  were  noted  in animals treated with




salvage  site soil, who  received a  much smaller 2,3,7,8-TCDD  dose. The data does not




allow a  quantitative evaluation of the bioavailability of 2,3,7,8-TCDD.




     Kaminski et al. (1985) and Silkworth et al. (1982)  reported the results  of a series of




studies  on  the  toxicity of soot  containing  dioxin  and  furan  compounds from  a  fire




involving transformer fluid containing PCBs.  Hartley guinea pigs  (500 to 600 g) received




single oral doses of soot in an aqueous vehicle, a soxhlet extract of the soot in the same




vehicle, or 2,3,7,8-TCDD in either an aqueous vehicle or corn oil.




     The soot was  reported to contain 2.8 to 2.9 ppm 2,3,7,8-TCDD and 124 to 273 ppm




2,3,7,8-TCDF.   The total polychlorinated  dibenzofuran content was estimated at 5,000




ppm.   Animal  weights and  mortality were  recorded  for 42 days, at which point the




survivors were sacrificed and  LD5Q  values were  calculated.  Blood  chemistry  and  a




pathologic examination were  performed at sacrifice. Table 5-4 summarizes results from




these experiments.




     Silkworth et al. (1982) noted that the LD50's for contaminated soot and soot extract



were similar at 410 and 327 equivalent mg/kg, indicating that the matrix had only a small




effect on toxicity.  If expressed in terms of the content  of 2,3,7,8-TCDD, the LD5Q from




soot is  2.5  Mg/kg,  which is a factor of seven below  the LD5Q for 2,3,7,8-TCDD in an




aqueous vehicle, suggesting that other compounds contributed to the toxicity  of the soot



and soot extract.






                                           105

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  TABLE 5-4. GUINEA PIG MORTALITY AND WEIGHT CHANGES FOLLOWING
         TREATMENT WITH CONTAMINATED SOOT OR 2,3,7,8-TCDD

                   Contaminated soot in aqueous vehicle - Males

             Dose eq.     Dose,2,3,7,8-               % Weight gain    Estimated
Treatment  soot mg/kg   TCDD /*g/kg     Mortality      (0-42d)      LD5Q (95% C.I.)
Methyl
cellulose
vehicle
Active
carbon
Untreated
Contami-
nated soot
H
H
ti

Active
carbon
Contami-
nated soot
n
n
n
0
0
0
1
10
100
500
Contaminated
0
1
10
100
500
0
0
0
0.003
0.03
0.3
1.5
soot in aqueous
0
0.003
0.03
0.3
1.5
N2
N
N
N
N
N
N
vehicle - Females -
N
N
N
N
2/6
48
38
37
37
34
18
-1
1st Experiment
20
22
13
7
-5
                                        106

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                             TABLE 5-4 (continued).

          Contaminated soot in aqueous vehicle - Females - 2nd Experiment

              Dose eq.   Dose 2,3,7,8-                % Weight gain    Estimated
Treatment   soot mg/kg    TCDD jig/kg    Mortality      (0-42d)     LD5Q (95%C.I.)
Active
carbon
Contami-
nated soot
n
n
tt
ti

Control
(unspec)
Soot
extract
M
soot equiv.
II
it
ti
0
250
500
750
1000
1250
Soxhlet extract
0
4
20

100
500
1000
0
0.7
1.5
2.2
2.9
3.6
of contaminated
0
0.01
0.06

0.3
1.5

0/6
0/6
3/6
6/6
6/6
6/6
soot in aqueous
0/6
0/6
0/6

0/6
4/5
6/6
35
6
-10
_*
_*
_*
vehicle - Females
41
38
28

21
_*
_*


410 mg/kg
(281-604)





327 mg/kg

(183-583)


                                         107

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                             TABLE 5-4 (continued).

                        TCDD in aqueous vehicle - Females
Dose eq. Dose 2,3,7,8- % Weight gain
Treatment soot mg/kg TCDD /ig/kg Mortality (0-42d)
C.I.)
Untreated
Methyl
cellulose
2,3,7,8-TCDD
tl
tt
2,3,7,8-TCDD
n
n
n

Untreated
Corn oil
2,3,7,8-TCDD
2,3,7,8-TCDD -
n
H
ti
n
0
0

0.1
0.5

2.5
12.5
20.0
TCDD
0
0
0.1
0.5
2.5
12.5
20
0/6
0/6

0/6
0/6

0/6
0/6
4/6
in corn oil - Females
0/6
0/6
0/6
0/6
3/6
5/5
6/6
39
31

28
29

25
33
11

39
22
37
24
7
_*
_*
Estimated
LD50 (95%


19 Mg/kg


(15-23)






(1.2-5.4)




*Major weight loss seen before death.
Source:  Silkworth et al. (1982)
^Data on survivors only, data read from graph.
2N: No deaths mentioned by authors, group size 4-6
•'As quantities of chlorinated dibenzofurans were present, 2,3,7,8-TCDD, alone, may not
be responsible for toxicity.  The 2,3,7,8-TCDD dose is based on 2.9 ppm in soot.

                                         108

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     The  authors stated that they  adopted  an aqueous  vehicle  in these  experiments




because it was  nontoxic and  provided a stable suspension of soot;  they regarded this




vehicle  as more appropriate for modeling of  human exposure conditions  than  an oil




vehicle.   The data  from these experiments also demonstrate that  use of an oil vehicle




leads to substantially greater 2,3,7,8-TCDD toxicity than does an aqueous vehicle.




      Comparison of mortality and  weight loss in groups of female guinea pigs receiving




500  A*8/kg of  soot  or the equivalent amount of  soot extract  suggests that  the extract




may be somewhat more toxic; however, all  six animals died  in  the 1,000 /xg/kg soot




group, while  four out of  five died  in  the  500 /ig/kg  extract group.  Taken together,




these dataindicate that  the  soxhlet extract  of soot in an aqueous vehicle  was between




one  and  two  times as  toxic as the  soot itself.  It is likely  that  a  larger difference  in




toxicity would have  been observed if the  soot extract was in an oil vehicle.




     Van den  Berg et al.  (1983) fed small  groups of male  Wistar  rats fly ash from  a




municipal incinerator (pretreated  with  HC1) containing dioxins  and furans, a soxhlet




extract  of the  fly ash, or a purified extract of the ash that was  obtained using column




chromatography.  Table 5-5 lists the concentrations of dioxin and furan groups in these




materials.  2,3,7,8-TCDD was present as 3.3% of the  TCDD  isomer  group in the fly ash




extract.   (The  authors did not specify whether  this  reference  was to crude  or purified




extract.)   2,3,7,8-TCDF was  present as 17.9%  of the  tetra-CDF isomer group  in the




extract.   The  rats were  fed 2 g/d fly ash mixed with diet or the  residual from 2  mL/d




extract  after  the extract was  mixed with  diet  and the  solvent was evaporated. The




animals were  exposed to the treated  diet for  19 days, and then sacrificed,  and the liver




tissue was analyzed  for  the presence  of dioxins and furans.  Table  5-6 shows  the average




concentrations  of  isomer  groups found in  the livers.   (Results  were  not presented




separately for 2,3,7,8-TCDD or 2,3,7,8-TCDF.) Table 5-7 gives  the percentages of the
                                           109

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                                 TABLE 5-5
  CONCENTRATIONS OF PCDD AND PCDF ISOMER-GROUPS IN FLY-ASH EXTRACTS
                   (DILUTED WITH ACETONE) AND FLY-ASH

Extract (I)
(crude)
Extract (II)
(purified)
Fly-ash (III)
Tetra-
CDD
322
475
245
Tetra-
CDF
400
609
314
Penta-
CDD
493
580
422
Penta-
CDD
485
624
500
Hexa-
CDD
500
539
562
Hexa-
CDF
438
587
660
Units
ng/mL
ng/mL
ng/g
Source:  van den Berg et al. (1983)
                                       110

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                                TABLE 5-6

          CONCENTRATIONS OF PCDD AND PCDF ISOMER GROUPS
               IN LIVERS OF RATS FED FLY ASH MATERIALS

                                   (ng/g)1

             Tetra-CDD    Tetra-CDF   Penta-CDD Penta-CDF Hexa-CDD   Hexa-CDF
Fly ash 1.5
Fly ash
extract
(crude) 2.4
Fly ash
extract
(purified) 0.8
8.1 17.8 39.2 36.8 64.2


21 20.0 60.5 58.6 102.4


3.5 2.7 10.9 5.1 13.8
Source: van den Berg et at. (1983)
^Each Entry is the average for two rats.
                                       Ill

-------
                                        TABLE 5-7
            PERCENTAGE OF CUMULATIVE DOSE OF DIOXINS AND FURANS
           PRESENT IN RAT LIVER FOLLOWING 19 DAYS EXPOSURE IN DIET

              Terra-    2,3,7,8-    Tetra-   2,3,7,8-    Penta-   Penta-    Hexa-     Hexa-
               CDD     TCDD     CDF    TCDF     CDD    CDF      CDD     CDF

% cum. dose
in liver —
fly ash1        0.11      0.9        0.4      0.3        0.2      0.7       0.3       0.7

%cum. dose
in liver —
fly extracts2    0.16      3.7        0.9      1.0         1.2      2.9       3.0       5.3

Ratio of perct.
in liver
ash/extract)     0.7       0.2        0.4      0.3        0.2      0.2       0.1       0.1
Source:  van den Berg et al. (1983)

1 Average retention in two treated animals.

2Average of retention for extract and purified extract groups, total
 four animals.
                                              112

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cumulative administered doses found in the liver at sacrifice, and the ratios between the




percentages in liver for fly ash and fly ash extracts.




     Approximately 1% of the 2,3,7,8-TCDD dose from fly ash was retained in the liver,




and approximately 4% of the dose of  this isomer from  fly  ash  extract was so retained.




The corresponding percentages for 2,3,7,8-TCDF are 0.3 and  1.0.  Data on the retention of




isomer groups in adipose tissue were presented for the extract-treated groups but not for




the fly-ash-treated group.   The concentrations of the various isomers in adipose tissue




are comparable to, or less than, the concentrations in liver tissue.




     The U.S. EPA (1985d) reported a half-life for elimination of  2,3,7,8-TCDD in the rat




of 20 days  at  high dose.   If  a similar  half-life  is assumed  in  this experiment, the




quantities of 2,3,7,8-TCDD in the animals at the end of the 19-day feeding experimen



would be  significantly  less  than the  absorbed  dose,  but  still  of the  same order of




magnitude.  However, the recovery percentages in this study are  low for both  the fly ash




and fly ash extract groups in comparison with  other studies in which 2,3,7,8-TCDD was




administered to rats.  Fries  and Marrow (1975) fed rats diets containing 7 or 20 ppb of




2,3,7,8-TCDD for a period of up to 42 days.  After 14  days of feeding, the rat livers




contained an average of 32% of the cumulative administered dose; at 28 days,  21% of the




dose; and at  42 days,  18% of the dose.  Thus, in the van den Berg et al. study, the liver




retention of  2,3,7,8-TCDD for the fly ash extract group is a  factor of five to eight below




what could be anticipated for the Fries and Marrow data, and the liver retention in the




van  den Berg group fed soot is a factor of 20 to 30 lower than that seen by Fries and




Marrow.  Data from Kociba et al. (1976), Rose et al. (1976), and Kociba et al. (1978) lead




to similar  conclusions to those  from the Fries data regarding the fraction of  cumulative




2,3,7,8-TCDD dose retained in the rat liver.
                                           113

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     An explanation  of  the  low level of recovery for the animals receiving the soxhlet



extract  of soot is  not apparent.  It is possible that the presence of multiple compounds



affected absorption or metabolism in the rats fed soot and soot extract.



     A  second approach to the  van den Berg et al. data is to compare the ratios of liver



concentrations  for dioxins  in fly-ash-treated animals  to  the  concentrations in extract-



treated  animals.   These  ratios,  based  on  measurements  in small  numbers  of animals,



indicate a substantial bioavailability of dioxin and furan compounds from the  tested fly



ash.   This  availability varied  among the different  isomers with the value of 0.3 for



2,3,7,8-TCDD, indicating that  this isomer  was three times as  available from fly ash



extract as from fly ash.



     Van den Berg (1985) fed fly ash (pre-treated with HC1) to Wistar rats, guinea pigs,



and Syrian golden hamsters.  Fly ash was mixed with standard  laboratory diet at 2.5% by



weight,  and animals were allowed to eat ad libitum. The amount of fly ash consumed by



each group  of five rodents was  determined by the authors.  For each species there were



three groups of animals each fed fly ash for approximately 32 days (group I), 60 days



(group II), or 94 days (group III).  Concentrations of dioxin and furan isomer  groups  in



the food were presented,  and  include  1.4  ng/g  TCDD compounds and  2.1 ng/g  TCDF



compounds.



     The  authors  presented  calculated  recovery  percentages for  the cumulative dose  of



specific isomers in the rodent liver.  For 2,3,7,8-TCDD in guinea pigs,  3.7%,  0.9%, and



1.4%  of the  administered  dose was  recovered  in the liver  in groups  I, II, and III,



respectively. The 32-day (group I) recovery percentage is somewhat higher than seen  in



the lower  dose groups  receiving 2,3,7,8-TCDD contaminated  soil in McConnell et  al.



(1984).  The value in hamsters  was approximately 2% (only reported  for group II), and



analytical problems prevented  this determination in rats.  No other  TCDD compounds



were quantitated. Similarly, for 2,3,7,8-TCDF, guinea pigs showed retention of 4.7%, 2.2%,






                                           114

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2.5% of the administered dose in groups I,  II,  and III, respectively.  For  both 2,3,7,8-




TCDD and 2,3,7,8-TCDF the  recovery  percentages  in  guinea pigs at 32  days were




approximately a factor of 4  to  15 higher than that observed  in the van den  Berg et  al.




(1983) study in rats.



     Other TCDD compounds  that were  present showed  comparable or somewhat lower




retention, averaging  1% to 2% over the animals  groups.  No TCDD or TCDF  compounds




were detected in hamster liver  or analyzed for  in  rat liver.  Higher chlorinated isomers




most typically showed retention in the range of 2% to 5% in rat liver and 1% to 3% in




guinea pig liver, with the exception of 2,3,4,7,8-PnCDF (9.8%, 8.3%, and 11.3%  in the



hamster groups).  Few other compounds were found in hamster liver, but 2,3,4,7,8-PnCDF




was found with a recovery of 5% to  8% and 2,3,4,7,8-HxCDD was found at  3% to 7%.




     As  with other  experiments in which the retention of dioxins in the liver has been




determined, these percentages  place a lower  bound on the bioavailability  of  the dioxins



but, because not all dioxin is  localized  in the liver, do not  permit bioavailability to be




estimated without knowledge of the elimination of the administered dose  over time and




the quantity of dioxins in the remainder of the  organism.  No positive  control group




receiving 2,3,7,8-TCDD was  included for comparison.




     Poiger and  Schlatter  (1980) conducted  several experiments in Sprague-Dawley rats




(180 to 220  g) in which liver concentrations of tritium  label from 2,3,7,8-TCDD were




determined using various doses and  vehicles.   All  experiments  consisted  of a single




gastric intubation of 2,3,7,8-TCDD-containing  material, followed by  animal  sacrifice at




predetermined times. The doses used were well below the LD5Q in the rat (the  maximum




dose applied  was  5 /jg/kg), and no deaths or toxic effects were reported.




     In a  preliminary experiment, rats  were treated with  14.7 ng/rat 2,3,7,8-TCDD in




ethanol.  Table 5-8  shows  the percentage of  recovery of the administered dose  at various




times.






                                          115

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TABLE 5-8. PERCENTAGE OF TRITIUM-LABELED 2,3,7,8-TCDD IN RAT LIVER
        FOLLOWING ADMINISTRATION OF 14.7 ug DOSE IN ETHANOL
Number of
animals
2
7
6
2
2
2
Time after treatment
(hours)
8
24
48
72
96
120
Percentage of
dose in liver
33.2
36.7+ 1.2
30.8 ± 2
22.3
17.5
17.5
SOURCE: Poiger and Schlatter, 1980.
                                    116

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     These data indicate substantial localization of 2,3,7,8-TCDD in the rat liver, with a

decrease of a factor of two in the fraction of the dose in the liver between 1 and 4

days.   Poiger and Schlatter (1980) conducted all further studies with sacrifice at  24 hours

to maximize the recovery of 2,3,7,8-TCDD from the liver.

     In a second  experiment,  the authors  administered 2,3,7,8-TCDD doses  in ethanol

ranging from  15 to  1,070 ng/rat to groups  of six rats. They found a  graded  increase in

percentage retained in the liver from 37% +  1% at the 15  ng dose to 51% ± 4% at 280 ng.
              •
At the high-dose point, the percentage may have fallen (42% + 10% at  1,070 ng).

     In a further  experiment,  2,3,7,8-TCDD was administered at low dose in a series of

vehicles.  These results are shown in Table 5-9.  These data demonstrate that
  TABLE 5-9. PERCENTAGE OF TRITIATED 2,3,7,8-TCDD DOSE IN THE LIVER
   24 HOURS AFTER ORAL ADMINISTRATION OF 0.5 ml OF VARIOUS MEDIA
Formulation TCDD dose
(ng)
50% ethanol 14.7
Aqueous suspension
of soil after
TCDD contact for:
8-15 hr (room temp) 12.7, 22.4
8 d (30 °C - 40 °C) 21.2, 22.7
Aqueous suspension
of activated carbon 14.7
# Rats % Dose in
liver
7 36.7 + 1.2



17 24.1+4.8
10 16 ±2.2

6 < or = 0.07
Source: Poiger and Schlater (1980)




administration of 2,3,7,8-TCDD in soil  reduced the  retention  of the dose in the liver to

66%, or 44% of the retention seen with  2,3,7,8-TCDD in ethanol.  The lower value, 44%

was obtained for soil that was aged for  8 days at 30-40  °C following addition of 2,3,7,8-


                                           117

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TCDD.   This observation is consistent with the findings of other studies reported here

that 2,3,7,8-TCDD from environmental soil (naturally aged) was  generally less available

than 2,3,7,8-TCDD freshly added to clean samples of these soils. The aqueous suspension

of  2,3,7,8-TCDD in activated  carbon showed little  evidence of bioavailability; this  is

supported  by  the   authors'  measurements  showing   that  2,3,7,8-TCDD   was  only

slightlyextractable from the activated  carbon  matrix by various  solvents.   In contrast,

58% to 70% of  2,3,7,8-TCDD could be recovered  from soil samples by washing with

hexahe/acetone (4:1 v/v).
                                                                  •
     Poiger and Schlatter  (1980)  also presented  results from  several  skin  application

experiments with TCDD-containing materials using rats and rabbits (not reviewed here).

     Bonaccorsi et al (1984) reported the results of a study  of gut absorption of 2,3,7,8-

TCDD from  soil taken from the Seveso,  Italy  accident site.  Soil  containing 81 ± 8 ppb

2,3,7,8-TCDD from the "highly contaminated" area in Seveso was administered to albino

male rabbits  (2.6 ± 0.3 kg) in daily gavage  doses for seven days.  Additional samples of

clean soil  were  spiked  with 2,3,7,8-TCDD in  the  laboratory to yield  10  and 40  ppb

contamination levels and were administered to rabbits following the  same protocol.  For

comparison, rabbits were also treated with 2,3,7,8-TCDD in solution in acetone-vegetable

oil  (1:6) or  alcohol-water (1:1).   Rabbits  were sacrificed  on  the day after  treatment

stopped and liver concentrations of 2,3,7,8-TCDD were measured.   Table 5-10 contains the

results of these  experiments.  The authors did not remark on the  presence or  absence of

toxicity in the treated rabbits.   EPA (1985) reports values for the single dose LD$Q of

2,3,7,8-TCDD in rabbits of 115 and 275 /ig/kg.  The total  doses  received by  the rabbits

in this study were approximately 54, 107, and 215 us/kg over seven days. Based on this

comparison, there is a likelihood that toxic  effects occurred in the Bonaccorsi work, and

noted  above,  toxicity  has the  potential  to affect the tissue concentrations  of 2,3,7,8-

TCDD.  For this reason the most appropriate  comparisons among  these  data are between

                                    /

                                           118

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groups showing similar liver concentrations of 2,3,7,8-TCDD, which may then be inferred

to have experienced similar toxic effects.
  TABLE 5-10.  GUT ABSORPTION OF 2,3,7,8-TCDD IN RABBITS AFTER 7-DAY
                                  TREATMENT
Treatment
Vehicle
(/ig/dayb)
Acetone-Oil
Mixture
Alcohol or
Acetone-Oilc
Alcohol
Lab Con-
taminated
Soilb
ll it
n M
Seveso Soilb
It M
2,3,7,8-
TCDD Dose
20

40

80

20
40
80
80
160
Number of
Rabbits
5

16

5

7
13
10
7
7
Mean TCDD in
Liver ppb
0.26 ± 0.07

1.1 +0.3

2.7 ± 0.5

0.26 ± 0.08
0.81 ± .31
1.5 ± 0.2
0.88 + .28
2.2 ± 1.0
% Admin. Dose
in Livera
24.14

51.07

62.77

24.14
37.5
34.91
20.43
25.63
alne percentage or  the administered dose found in the liver was calculated
 assuming a liver weight of 5.0% of body weight; liver weights were not
 reported by authors.
bl-2g soil administered  by gavage in 10ml water.  Soil sifted through wire
 mesh.
cThe two vehicle groups are not broken out.
                                          119

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     That this  method  of comparison is desirable  can also be  seen  from the Bonaccorsi




data,  where both solvent vehicle groups and the spiked soil  groups  show an increase of




the fraction  of the dose  in  the  liver at  the  higher administered  doses.   However, it




should be mentioned that use of two different  solvent vehicles complicates  interpretation.




Similar liver concentrations of  2,3,7,8-TCDD  were seen in the 40  jtg/d solvent vehicle




and 80 ng/d  Seveso soil groups. Comparing the percentage of liver retention in these  two




groups indicates absorption from  Seveso soil was 40% of that  from the solvent vehicle.




Using the  same  approach, comparison  of the 80  A«g/d solvent vehicle and  160 A*g/d




Seveso soil  groups indicates  that absorption from  the  soil was  41%  of that  from  the




solvent.




     The same approach can be used to compare absorption from the solvent vehicle  and




from  the  spiked soil.   In this case  the  40  /ig/d  solvent vehicle group  had  the liver




concentrations closest to either the 40 or 80 pg/d spiked soil  groups.  Comparison of the




percentage of dose in the liver indicates  absorption from spiked soil  is 68-73% of  that




from  the  solvent  vehicle. Bonaccorsi et al (1984) work conducted  with either aged or




non-aged spiked soil but do not present data to allow a comparison of these  groups.




     Shu et al. (1987,  as cited by Leung and Paustenbach,  1987) study of  2,3,7,8-TCDD




from  the  Missouri  site tested by  McConnell et al. (1984).  Their paper "reports an  oral




bioavailability of approximately 43% in the rat dosed with  environmentally contaminated




soil from Times Beach, Missouri.  This figure did not change significantly over a 500-fold




dose  range of 2 to 1450 ng 2,3,7,8-TCDD per kg of body weight  for soil contaminated




with approximately 2,  30 or 60 ppb of 2,3,7,8-TCDD.  The data from  this study is not  now




available to the Exposure Assessment Group for review.




3. Summary




      Table 5-11 summarizes data that are pertinent to the bioavailability of 2,3,7,8-TCDD




from  environmental matrices.   Studies of bioavailability, which examined soil  samples,






                                          120

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soot, and fly ash,  have utilized three methodologies:  measuring acute toxicity, retention




of 2,3,7,8-TCDD in the liver, and induction of hepatic enzymes.




     Among the five samples of soil from contaminated sites that have been tested,  three




have shown substantial bioavailability, e.g., 25% to 50%, when compared with 2,3,7,8-TCDD




in corn oil gavage.  A  fourth soil sample was compared with 2,3,7,8-TCDD administered




in a solvent vehicle,  and fell  in this range.  The fifth  soil,  tested by Umbreit et al.




(1986a,b; 1987a,b) showed  bioavailability substantially  less  than  the  other soils tested.




While  difficult to  gauge  quantitatively,  dioxin  from this soil  may  be  an  order of




magnitude less available than from the other soils.




     Additionally,  three samples  of soil  spiked with 2,3,7,8-TCDD  have been tested for




bioavailability, including one sample in which the 2,3,7,8-TCDD was incubated with soil at




an  elevated  temperature.  The 2,3,7,8-TCDD  added  to these soil samples  proved to be




highly available (e.g., 40% to 70%).




     In  one study, soot from  a  transformer fire containing dioxins and furans proved




similarly toxic to a soxhlet  extract of the soot in an  aqueous vehicle. However, the soot




extract may  have proved more  toxic if delivered in  corn oil, as was  2,3,7,8-TCDD in the




soil  studies.   The availability  of 2,3,7,8-TCDD  and  other dioxins and furans  from




incinerator  fly  ash have been addressed  by  van  den  Berg et al.  in  extended  feeding




studies.  In these studies, liver retention of 2,3,7,8-TCDD from either fly ash or fly ash



extract proved low, with availability  from fly  ash being approximately 25% of that from



the extract.
                                            121

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                                        TABLE 5-11
            SUMMARY OF DATA ON THE BIOAVAILABILITY OF 2,3,7,8-TCDD
               FOLLOWING INGESTION OF ENVIRONMENTAL  MATRICIES
Author
Material
Species
              Dosing
                               Observation
Umbreit et al.
(1986a,b)
Soil
Newark
Manuf.
Site
Guinea
Pig
              Single
              Gavage
McConnell et al.
(1984)
                    Soil
                    Newark
                    Salvage
                    Site
                    Recontami-
                    nated Soil
Soil Times
Beach, MO
Guinea
Pig
Guinea
Pig
Guinea
Pig
                                Single
                                Gavage
                                Single
                                Gavage
              Single
              Gavage
McConnell et al.
(1984)
Soil
Minker
Site, MO
Guinea
Pig
              Single
              Gavage
                           2,3,7,8-TCDD in soil <10%
                           as toxic as in corn oil,
                           based on lethality and
                           weight loss.

                           2,3,7,8-TCDD in the manuf.
                           site soil had retention in
                           liver approx. 1% as great as
                           with salvage site soil.

                           Liver retention similar
                           to 2,3,7,8-TCDD in corn
                           oil from lower dose
                           McConnell et al. (1984)
                           data.

                           Toxicity similar to
                           equal dose of 2,3,7,8-TCDD
                           in corn oil.
                                 data indicate
                           2,3,7,8-TCDD in soil appox.
                           25% as toxic as in corn oil.

                           Comparing animals dying
                           early, liver retention of
                           2,3,7,8-TCDD in soil group
                           approx. 50% of that in corn
                           oil vehicle group.

                           Comparing animals
                           surviving experiment,
                           liver retention of 2,3,7,8-
                           TCDD in soil group approx.
                           20% of that in corn oil
                           vehicle group.

                           ^059 data indicate soil
                           approx. 30% as toxic
                           as 2,3,7,8-TCDD in corn
                           oil.
                                               122

-------
Author
Material
TABLE 5-11 (continued).

  Species        Dosing
                  Observation
McConnell et al.
(1984) and Lucier
Soil
Minker
Site, MO
   Rat
Poiger and
Schlatter
(1980)

Bonaccorsi
(cite in
McConnell et
al., 1984)

Kaminski et al.
(1985) and
Silkworth et
al. (1982)
van den Berg
et al.(1983)
Soil with
2,3,7,8-TCDD
Soil Seveso
Accident Site
Soot
from Fire
   Rabbit
   Guinea
   Pig
Incinerator
Fly Ash
   Rat
             Comparing animals dying
             early, liver retention
             approx. 50% of that in
             corn oil vehicle group.

             Comparing animals surviving
             experiment, liver retention
             approx. 25% of that of
             corn oil vehicle group.

Single        Introduction of AHH and
Gavage      UDP glucuronyltrans-
             ferase activity > 50%
             of that in groups receiving
             2,3,7,8-TCDD in corn oil.

             Liver retention 20-40%
             of that in rats receiving
             equal dose of 2,3,7,8-TCDD
             in corn oil.

             Liver retention approx.
             40-70% of that in ethanol
             vehicle  groups.

             2,3,7,8-TCDD 30%  as bio-
             available from soil as from
             solvent  vehicle.
Single        LD5Q data indicate soot
Gavage      containing dioxins and
             furans approx. equal in
             toxicity to soxhlet extract
             of soot in aqueous
             vehicle.

19 day       Liver retention of 2,3,7,8-
Feeding      TCDD from ash and ash
             extract 1% and 4%
             respect.,  indicating
             2,3,7,8-TCDD approx. 25%
             as avail from ash as from
             extract.  Both ash and
             and extract retentions
             are low compared with other
             feeding and gavage studies.
                                                123

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                                  TABLE 5-11 (continued).


Author              Material          Species         Dosing          Observation
van den Berg
et al. (1985)



Incinerator
Fly Ash



Guinea
Pig



Feeding 4%, 1% and 1% retention
of total dose in liver
following feeding for
32, 60, and 94 days,
respect.
Van den Berg       Incinerator       Hamster       Feeding     2% of total dose retained
(1984)              Fly Ash                         60 Day      in liver following feeding.

Poiger and          2,3,7,8-TCDD    Rat            Single       <0.1% retention in liver.
Schlater             on activated                     Gavage
(1980)              Carbon
                                               124

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     The  individual studies  reviewed have  a variety of  limitations, as discussed in the



preceding text.  A  notable limitation was that some experiments were conducted  at using




highly  toxic  doses of  2,3,7,8-TCDD,  so  that  determination  of bioavailability  was




complicated by wasting and  early death of the test animals.   It should also be  noted




that,  while  the  relative  retention  of 2,3,7,8-TCDD in  the  liver  can  serve as an




appropriate indication  of differences in bioavailability between samples, the  percentage of




dose  found in the  liver only  places a lower bound on absorption.  This is  particularly




relevant to experiments where animals have  been maintained for many  weeks after dosing




and an  undetermined quantity  of 2,3,7,8-TCDD has been excreted.




      Finally,  toxicity  data for mixtures for  which both toxicity  and  bioavailability of




individual compounds may vary  are  difficult to interpret quantitatively in  terms of




bioavailability.




      As presented  in  U.S. EPA  (1985c), Rose et al. (1976) determined gut  absorption of




2,3,7,8-TCDD in a 1:25 mixture of  acetone  to corn oil (by volume) in the rat.  In both




single dose and multiple dose experiments,  measured absorption was approximately 85%.




Assuming  that absorption  from  pure corn  oil is similar  to that from  this  mixture, and




assuming  that absorption in  other species for which data are not available is similar, the




85% factor can be  applied to the data presented here to obtain an  approximate range for




typical  2,3,7,8-TCDD absorption  from soil.   Using  this  factor,  the   estimated relative




bioavailability of 2,3,7,8-TCDD from soil is 25% to 50% and, when compared with corn oil,




provides an estimate of gut  absorption of 20% to 40%  of ingested 2,3,7,8-TCDD in  soil.




This  estimate is comparable  with the 20% to  26% absorption from 2,3,7,8-TCDD treated



soil from  the work  of  Poiger and Schlatter (1980).




      Recognizing these limitations, the weight of evidence indicates that 2,3,7,8-TCDD  is



often highly available  from environmental materials.  However,  in one  tested  soil sample




the compound  was  substantially less  bioavailable.  While the data are too sparse  to allow






                                           125

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 a prediction as  to  whether a particular environmental  sample will  prove more or less



 bioavailable, one important suggestion has emerged.  In the two samples that have proved




 least bioavailable (the Umbreit et al. (1986a) manufacturing site soil sample, and 2,3,7,8-




 TCDD on activated carbon tested by Poiger and Schlatter (1980)) the 2,3,7,8-TCDD was




 largely resistant to solvent extraction.   This  was  not  the  case for more bioavailable




 materials.



      Further research, using short-term experiments in which animals are handled under




 identical  conditions and are fed dioxins in different media, is needed  for  an improved




 comparison of absorption between different environmental samples.  Acutely toxic  doses




 should be  avoided  to  ensure that  tissue  concentrations are directly  interpretable.




 Experiments studying both tissue retention and enzyme induction should prove valuable




 for this  research.   Whole-body levels  of 2,3,7,8-TCDD  need  to  be  related to  liver




 concentrations,  and  the  effects of  metabolism need to be  addressed.   The  vehicle of




 administration has been shown to affect acute 2,3,7,8-TCDD toxicity, and vehicle effects




. need to be considered in designing experiments.




 B.  PHARMACOKINETICS AND BODY BURDEN OF DIOXINS




      The  pharmacokinetic profiles  of CDDs  and  other related  compounds, such as  the




 polychlorinated  dibenzofurans, are  quite complex.   However, a thorough  analysis and




 understanding  of these pharmacokinetic data could prove very  helpful in ensuring that




 exposure assessments  for CDDs are reliable.  In addition, such profiles may be useful in




 providing information to help understand and apply  the  data  from  animal studies to




 human exposure and risk assessments.




      Wroblewski and Olson  (1985)  reported  differing levels  of responses  to  CDDs by




 various species.  It  may be that some of these differences can be explained by examining




 and  quantifying the  species  differences in disposition  and metabolism (Wroblewski and




 Olson, 1985; King  et al., 1983).  The varying responses to various isomers may also be






                                           126

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explained by differences in the disposition and metabolism  (Burant and Hsia, 1984).   It




may be  well  to note that the definition  of "disposition" may  have to be  extended  to




include suborgan  or  even subcellular sites in order to more fully  describe  some of the




noted differences.  As will be discussed in greater detail  later in this section, CDDs have




been  implicated  to  bind  with  very specific  loci  within  cells.    The  structure  and




concentration  of  these  intracellular receptors appear to be  under  genetic  control,  and




thus may exhibit considerable inter- and intra-species variation.




     Pharmacokinetic analysis  may  also  allow  for  predicting  the time  required for




eliminating the body burden  after exposure ceases.   With sufficient data  and proper




understanding,  these  analyses  can  account   for various  exposure  and  physiologic




conditions.




     The redistribution  of a CDD among the various  tissues  and organs, which may occur




during elimination, can  be accounted for and tracked.  Effects on disposition, which may




result from altered physiology,  such as from sudden weight loss  or from lactation, can  be




incorporated and  thus adequately considered in  exposure and risk assessments.  Lactation




(Astrila, et al., 1981) and  pregnancy (Nau and Bass,  1981) are known to accelerate the




removal  of CDDs from the body.  This increased elimination may  be at the expense  of




accumulation by the embryo, fetus, or offspring.




     In  the future, as  more becomes known about  the mechanisms of action  of  these




compounds, it may become necessary to extend the traditional physiologic pharmacokinetic




analysis  to subcellular sites.  The risk assessor would be  greatly  aided by predictions and




descriptions of toxin disposition  at  sites  of toxicity. This  factor  becomes  particularly




significant if  concentrations at target sites deviate significantly  from linear  relationships




with ambient concentrations.




     One potentially powerful  and practical  application of pharmacokinetic analysis is  to



estimate  exposure levels from body burden data.  The goal here  would be to use as much






                                           127

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human data  as  are  available,  in  order  to  avoid uncertainties  that  arise when making



extrapolations from animal data.



     Some of the applications mentioned thus far are more easily applied than others for



these compounds.   Significant  data exist regarding these  compounds, and some attempts



have  been made  to apply  pharmacokinetic  analyses  to  exposure  assessments.   Other



applications  will require more research and data gathering.  It  is well  to note that



assumptions  are  made  when  making predictive statements  based  on  pharmacokinetic



analyses.  The rest of this chapter will discuss some present and future applications and



some of assumptions involved.



1. Body Burden: Estimate of Exposure



     "Commoner Approach":  Commoner et al. (1985, 1986) discussed ways to calculate the



intake of 2,3,7,8-TCDD per  day from human adipose tissue data. A major factor of the



data  base  for these  compounds is  that significant documentation  exists regarding the



amounts  that are found in human adipose  tissue. After making certain assumptions one



may  then  "back-calculate" what  the exposure  was to give such levels in  the adipose



tissue.



     A commonly used function to describe repeated dosing, as  would occur  with chronic



ingestion, would be:








                               D = (M)(ka)(l - e-kat)                      (5-1)



where D = dose, M =  mass  of material  taken in, ka = absorption rate constant, and t =



time after first dosing.








                            C =  D/V =(M)(ka)(l - e'kat)                   (5-2)



where C = concentration, and V = volume of body  (or compartment, etc.)  If one assumes



steady-state conditions  (material coming into  the body equals material  leaving the body)






                                          128

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for relatively long periods of time,




                                    Css   =  M/V                          (5-3)




where  Css = concentration at steady-state.  Commoner et al. defines I as  the intake per




day based on the steady-state concentration:




                                     I . Css (ke)a                          (5-4)




where  ke  = first-order  elimination rate constant,  and a  = fraction of body  which is




adipose tissue.



     Note that the Css  used here is the actual concentration  measured  in adipose tissue




samples.  The  adipose  tissue fraction is assumed  to be  0.14, and  ke is  determined from




the half-life of the compound in the body according to:




                                   ke = (In 2)/t1/2                          (5-5)



     Some of the assumptions that are inherent in this approach are as follows:




     (1)  After  a long  period  of  time, steady-state is reached within the adipose tissue.




          This  assumption  greatly simplifies  these calculations, because  the  absorption




          rate constant, ka, need not be independently determined.  This assumption only




          applies for exposure  under relatively stable conditions for  long periods.  If the




          half-life of this compound in the body  is 5  years, it would require 16 years for




          the  concentration  to reach  90% of  steady-state. This  further  assumes stable




          exposure conditions for  those 16 years.




     (2)  Whole-body  concentration and adipose  tissue concentration are linearly related,




          with the adipose tissue fraction being the constant of proportionality.




          Normally,  one  finds that the constant called "fraction  of the dose absorbed,"




          Fo,  is related to  several factors, including bioavailability,  gut  contents, other




          chemicals  in  the mixture, etc.  From studies  with similar compounds  (King et




          al., 1983) it appears that a multicompartment model analysis best describes the
                                            129

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          data.   Thus,  assuming  that  the  adipose tissue  fraction  is  the  constant  of



          proportionality may introduce  some error.



     (3)   Determining  ke  from the  biological  half-life (tj/2)  implies a  simple, one



          .compartment model.  Given the work on 2,3,7,8-TCDF and the tendency for



          CDDs  to  partition in lipid, it seems unlikely that  such  a one compartment



          analysis would be adequate. This  could  result in an overestimate of ke, which



          would in turn result in an overestimation of the daily input, I.



     (4)   The  parent compound is the toxin and thus the  species of  interest.  This



          assumption  is  reasonable  and appears  to  be supported  by  several  studies



          (Burant and Hsia, 1984;  Wroblewski and Olson,  1985).  Also, studies indicate



          that  only  the  parent  compounds have a tendency  to bioaccumulate (Weber et



          al., 1982).



     This  analysis cannot  account for  the  redistribution among  various body organs



resulting  from physiologic and biochemical  changes such as  weight loss,  nor for the



variation in ke which may exist among individuals. Further, this analysis cannot be used



to determine any individual organ, cellular, or sub-cellular dispositions.



     In  summary,   this  method   is  designed  to  calculate,   from   adipose  tissue



concentrations, the average daily intake.  Because of some simplifying  assumptions that



are inherent, such as assuming  a single  compartment and linear, first-order elimination,



this method may  miscalculate the actual input.



2. Physiologically Based Pharmacokinetic Modeling



     An alternate method  for describing and predicting disposition within the body is to



use  physiologically  based  pharmacokinetic  models.   These  models  take  into account



physiologic  and  biochemical processes such as  blood flows,  metabolism,  and  renal



clearance, and  describe the body according to its normal anatomy.  Physiologically based



pharmacokinetic models can, given  adequate  data, predict disposition from one exposure






                                           1.30

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scenario to another and even from species to species.  One such model was developed for

2,3,7,8-TCDF (King et  al.,  1983) and is described here with some modification for the

dioxins. First, the anatomic  regions of the  body are:  blood,  liver, fat, skin,  and muscle.

The  other organs are all  lumped together as the "carcass." Input may be by a variety of

routes,  but for the purposes  of this  discussion,  is considered to occur  through the

gastrointestinal system  by continuous or chronic dosing.  Only the  parent compound  is

tracked in each organ because  of its presumed toxicity.  The pertinent equations are:

Liver:

         VL(dCL/dt) = QLCB -(QLCL)/RL-(kmCL)/RL+ D                    (5~6)

where  V = Volume of liver, QL = blood  flow to liver, CL = concentration of TCDD  in

liver, Cg  = concentration of TCDD in  blood, RL = partitioning ratio of TCDD between

liver and blood, km = first-order elimination rate constant, D  = dosing function.

Fat:

                            vF(dCF/dt) = QF(CB -CF/RF)                 (5-7)
Terms are  analogous  to those  for  liver.    Skin,  carcass,  and  muscle  equations  are

analogous to that for fat.

Blood:

VB(dCB/dt) = QLCL/RL + QFCF/RF + QmCm/Rm + QSCS/RS + QCCC/RC  - QBCB(5-8)


     Equations are also written to account  for  metabolite formed and excreted through

the bile.

     Parameters:
     (V) Organ volumes:                                   Literature

     (Q) Blood flows:                                      Literature

     (R) Partition ratios:                                   Estimated from data
  (further discussed below)
                                          131

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     (km) Metabolic clearance rates:                        Estimated from data
                                                            (in vol/time)
     (ka) Absorption rate constant:                           Estimated from data


     Obviously, such an  approach  requires a great deal of data simply to  estimate  the

parameters.  Some parameters, such as the partitioning ratio, can be determined from  in-

vivo  or  in-vitro  animal  studies  or  from  mathematical  analysis  of  time  versus

concentration profiles (King et al., 1983).

     The partitioning ratios for humans would have their  initial estimates set at values

very close to other species.  For this compound it may  be  reasonable to assume  that  the

major difference among the species is metabolism and not partitioning  ratios.

     The clearance rate, km, can be determined in various animal species and then scaled

to humans  (King  et al., 1983).   A more acceptable  approach  would  be  to  set  the

elimination  rate  constant from human elimination  data.   The elimination  profile after

exposure ceases would be necessary in order to calculate this parameter.

     Some  assumptions  may be made to simplify  the model for use in  estimating intake

from fat (adipose) tissue concentrations determined in actual human samples:

     If one assumes  fat  tissue to  be in  steady-state (the  limitation  of this assumption

was discussed previously), then

                                    CF = CF,SS                            (5-9)

and
                                   VF = d£F - 0
                                        dt                                 (5-10)
and thus,

                                Qc  = (QF/RF)CF,SS                       (s-ii)

Solving for

                                 CB =(CF,SS)/RF                           (5- 12)
                                          132

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     If one assumes the other various organs to be in steady-state, then the equation for

liver becomes

0 = dCL/dt = -(kmCL)/VLRL -(QLCL)/VLRL + (QLCF>ss)/VLRL + (FoMka)/VL(5- 13)
Then

                            (F0Mka)/VL =(kmCL)/VLRL               (5-15)


and
                             F0Mka  =(kmCL)/RL                      (5-16)

and
                                      = CB                             (5-n)
and at steady-state

                             CB = (CF,ss)/RF                            (5-18)

Thus,

                          I = MkaF0  =(CF>sskm)/RF                      (5-19)

     With MkaFo defined as the  intake function, the last equation resembles the equation

used  by Commoner et al. (1985, 1986).   In  this equation  km  is the rate  constant for

metabolic clearance.  Rather than using the body fraction as  in  Commoner et al. (1985,

1986), the fat-to-blood partitioning ratio is  used. The  intake calculated  in  this manner

could be significantly different from that calculated by the Commoner Method.

     Thus, it can readily be seen  that three important factors that govern the

bioaccumulation of these  compounds are  bioavailability, lipid-to-blood partitioning, and

rate of elimination.

     To estimate  intake,  several pieces  of  information are needed.    Obviously, the

concentration of  dioxin in the fat tissue  is needed.   Such information may  be  available

from  various "adipose  tissue" banks.   However, some assumptions have to  be made when

using such data.   First, the  assumption of steady-state is  made.  The basis for  this  is

that  it is assumed that regular and repeated daily dosing occurs.   Another assumption  is

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that composite samples are representative for all persons at an exposure site.  Given  the




possible  differences  that  may  exist  regarding  absorption,  metabolism,  etc.,  between




individuals, the accuracy of such an assumption  may be questioned.  Another parameter




needed is the fat-to-blood partition ratio.  This  may be difficult to obtain for  humans,




but may be estimated from animal data.   There is evidence that for similar compounds



this parameter is nearly equal in all the species tested (King et al., 1983, Kahn, 1987).




     The most difficult  parameter  to  estimate for  humans  is  the  elimination  rate




constant.  One way to obtain this parameter would be to directly monitor humans for  the




disappearance of the chemical of concern from  the body after  exposure  was known to




have stopped.  An  alternate method would be to determine the parameter experimentally




in animals, and extrapolate to humans.  This  technique must be carefully evaluated before




application, however.   Given  the rather significant differences that  exist  among species,




care must  be taken to ensure that  the  animal parameter is determined in  species which




are representative of humans.  Further, extrapolation methods for this parameter are  not




uniformly accepted, and thus some uncertainty may arise.




     Animal studies need to be performed to simulate steady-state conditions and validate




such methodology for determining intake.   The animal experiments should be performed in




several  species, at  several doses,  and under different  conditions of bioavailability (see




Section A of Chapter 5) and non-steady-state conditions.




     The major advantage of global physiologically based pharmacokinetic  models is that




they may be modified to account for any number of circumstances. Obviously, at non-




steady-state conditions the mass  balances  for the model are considerably  more complex;




thus,  more  parameters need to be determined.   However,  there may  be  a number  of




circumstances where the global model is necessary.




     There  is  ample evidence,  for example, that during lactation  (Astrila et al.,  1981)




CDDs  are mobilized from  the fat stores and eliminated  through  the  milk.  Thus, it is of






                                           134

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interest to both  mother  and child to track the course  of  the chemical, for example




2,3,7,8-TCDD.  A reasonable assumption  would be that the 2,3,7,8-TCDD mobilizes from




the mother's  fat tissue, reaches the mammary glands, and  there enters the milk. Suitable




mass-balance  equations  are  written  and  added to  the model.    Given  the  proper




parameters, this model could also  be  modified and  used  to  describe the  2,3,7,8-TCDD




concentration in the milk  of exposed cows.




     Similarly, if one needed to follow 2,3,7,8-TCDD passage across the placenta, suitable




mass-balance equations would be added to  the  model.   All of these modifications would




require laboratory experimentation  to  estimate the necessary  parameters and  for ultimate




validation. However, when and if  it becomes obvious that information is needed in these




circumstances,  the necessary  parameters would be  estimated from appropriate  experiments




and the model  utilized.




     Ultimately, this model could be expanded to include  various subcellular  sites.  There




is a growing body of evidence which  indicates that the  possible  mechanisms  of action of




2,3,7,8-TCDD  involve  interaction  and/or binding of the  chemical  with subcellular sites




(Hannah et al., 1986; DiBartolomeis et al.,  1986). Thus,  as  more becomes known about




mechanisms  of action, exposure assessments will need  to be extended to these various




subcellular sites. A well formulated and validated physiologically based pharmacokinetic




model could  be an excellent method to accomplish such extended exposure  assessments.




     It also appears that CDDs may alter normal metabolic and physiologic processes such




as cholesterol metabolism  (DiBartolomeis et  al., 1986) vitamin  A bioavailability (Hakansson




and  Ahlborg,  1985), lipid metabolism (Swift et al., 1981;  Albro  et al., 1986),  biliary




excretion (Herman et al.,  1986), and thyroxine activity (McKinney et al., 1985).




     Thus,  in  the  future the model can  be modified to  account for such  alterations




induced by CDDs.  Such pharmacodynamic models ultimately relate disposition with effect,




and can be a great aid in  risk assessment.






                                           135

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     With the steady-state assumptions,  Equation 5-19 may be  used  to estimate the fat



concentration  at  steady-state  given  an average intake over time, for example  per  day.



Alternatively, given the concentration in the fat, an individual's  daily intake may be



estimated.  In doing so, total body  clearance is  substituted for metabolic clearance.  To



use  Equation  5-19  to estimate intake, several  pieces  of  information  are  needed.



Obviously, the concentration of the  CDD in the  fat is needed.  These data are generally



available for humans from various "adipose tissue" banks.  For animals, these data may be



determined when conducting experimental studies.  Another parameter needed is the fat-



blood partition ratio.   This may be difficult to obtain for humans, but may be estimated



from animal data.  There is evidence that for similar compounds  this  parameter  is nearly



equal in all tested species (King et al., 1983).  Total body clearance is the most  difficult



parameter  to  estimate  for  humans.   One  way  to obtain this  parameter would be  to



directly  monitor humans for the disappearance of  the  chemical from the body after



exposure was known to have stopped.  From these  data, the elimination rate constant can



be  determined and thus some  estimate  of clearance can be  made.   Elimination  rate



constants and clearance may be related according  to:




                                   CL = (ke Vd)                     (5-20)



where  CL  = clearance, ke = elimination rate constant, and Vj  = volume of distribution.



For a one-compartment model,



                                   ke =  In 2/t1/2                     (5-21)



where  tj/2 represents the half-life of the  chemical in the body.



     The volume of distribution may  be estimated as in King  et al.  (1983) by summing



the product of organ volume  times tissue-blood partition ratio for each of the individual



organs.



     From these equations and  laboratory data,  some approximation  of clearance in the



human may be made, as follows:






                                           136

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     (1)   From  animal   experiments,  determine  elimination  rate  constant  and



          partition  ratios.   If  data  in  humans exist, the elimination rate constant




          need not  be extrapolated from animals.  (In this section, human half-lives




          are extrapolated from animal data and compared to published  human data.




          The elimination constant used to calculate daily intake is  taken from the




          published data.  The extrapolation result is compared  merely  to assess the




          possible utility of such an extrapolation procedure.)




     (2)   From  known organ volumes  and partition ratios,  calculate the volume of




          distribution for 2,3,7,8-TCDD.




     (3)   From  the  volume of  distribution  and the  elimination  rate  constant,




          determine the clearance.



     (4)   Relate clearance in animal species to clearance in  the  human  according to




          body  weight,  to the 0.7  power, or determine clearance  using  available




          half-life  in the human  and estimating  the volume as described above.




          (Determining elimination rate constants directly from  human  data reduces




          the uncertainty associated with interspecies scaling.)




     Obviously,  careful  consideration must be made when extrapolating any parameter




from animals  to humans.   It may be  that both partition ratio  and clearance should be



extrapolated  from  several animal  species, if  possible.   As  another possibility,  the




extrapolations  can be made from available data in non-human primates.  Preliminary  data




from rhesus  monkeys are available  (Bowman, et  al., 1987)  and have been used here.




Human  half-lives for 2,3,7,8-TCDD were calculated using various values estimated from




the preliminary  data in monkeys.  The  calculations were based on a fat-to-blood partition




ratio of  100 based  on the monkey data (Bowman, et al., 1987) and human  data (Kahn,




1987) and a monkey volume of distribution was calculated, as described  above, to be 51.4
                                           137

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liters.  The human volume of distribution  was calculated to be  720 liters.  Table 5-12



summarizes the resulting half-lives:




  TABLE 5-12. ANIMAL VS. HUMAN CLEARANCE AND HALF-LIVES OF TCDD
Monkey
clearance
(L/yr)
28.47
21.9
16.43
1-3.14
Human
clearance
(L/yr)
182.0
137.6
104.0
82.5
Half-Life
in monkey
(yr)
1.24
1.65
2.19
2.74
Half-Life
in human
(yr)
2.76
3.63
4.79
6.07
     Commoner et al. (1985) reported  that a survey of the available literature revealed



an average human half-life for 2,3,7,8-TCDD of 4.95  years; Poiger and Schlatter (1986)



found it to be 5.8 years.  Thus, these clearance values  are appropriate for estimating the



average intake of 2,3,7,8-TCDD based on human adipose tissue data. A survey of human



adipose tissues from the human adipose tissue bank reveals a wide range of concentration



of 2,3,7,8-TCDD.  Data were gathered from a variety of geographical locations across the



United  States and categorized according to three age groups.   As an example, the data



used here were  reported for  persons over 45 years  of  age.  The 45-year-old age group



could be  approximated to be in steady-state if exposures over  that period were fairly



constant regardless of living  conditions and  geographical moves during the span.  The



time required to reach  steady-state can be determined  from the following equation for a



one-compartment model:



                          log [(Css - C) /Css] = - kt/2.303                 (5-22)

-------
     From this equation it may be determined that it would require  approximately four




half-lives,  or 20 years, to reach 90% of the steady-state concentration,  and seven half-




lives, or 35 years, to reach 99% of  the steady-state concentration.




3. Calculation of Daily Intake.




     As discussed, a growing  body  of  evidence may imply  that there exists an  overall




body burden of CDDs, including 2,3,7,8-TCDD  in the general population of the  United




States.  If  true, a number of important issues arise.  First, sources  of such a widespread




body burden need to be  identified.  Second, if such background exposures exist, then a




calculation of the  carcinogenic  risks  based on such  background  levels  need  to  be




performed.




     To  review,  some basic  questions  require  resolution  in order  to  determine daily




intake and subsequent  risk  estimates  from  such  background exposure.   First, is  it




reasonable to assume, after examining the available data that a body burden of 2,3,7,8-




TCDD exists  in  the general population of the  United States?  Second,  if such  a body




burden  exists, what  are  the average daily intake levels  that result in such background




levels?  The following sections address  these questions,  attempt to  identify and estimate




the uncertainties  associated with such assumptions and calculations, and try to estimate




ranges of  risk from such putative intake levels.




a. Data




     Because of their high  lipid  solubilities CDDs tend  to  preferentially  partition  into




adipose tissues  and reside there for long periods of time.  Depending  upon  the exact




elimination rates  they can then remain in human adipose  tissue for  well over  25 years.




Thus,  the  presence of CDDs  in adipose  tissue is  good evidence for  previous  exposure.




Further, if steady state conditions are assumed,  the adipose tissue levels  may be  used to




calculate  average daily  intake as  described earlier in the  chapter.   As a  result, most




investigators  have taken fat biopsies to  determine the body burden of dioxin in humans.






                                           139

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iBlood .concentration can 
-------
those individuals having  an exposure history  could  have been  low,  the  exposure could




have been sporadic, and could have occurred long before the monitoring.  Thus the levels




of 2,3,7,8-TCDD due to  phenoxy herbicide exposure, in those  persons, could have  had




little impact  on their  total  concentration observed at the time of monitoring.  In other




words,  the  concentrations  in  these  persons  might  have returned back  to background




levels.



     Ono (1986) reports 9  ppt  as an average  concentration in the adipose tissues of 13




Japanese people with  no known exposure to 2,3,7,8-TCDD containing  substances.  Persons




in rural areas of Georgia  and Utah with no known exposure had 7.1  ppt in their adipose




tissues (Patterson et al., 1986).   Grahm (1986) reported similar  levels for samples taken




at autopsy.




     Results  of the  National  Human Adipose  Tissue  Survey (NHATS)  (Stanley 1986)




showed 6.2  + 3.3 ppt  in the composited  adipose  tissue samples taken at random from




throughout the U.S. at surgery or autopsy.



d. Conclusions Regarding Body Burden Data




     Technical Resources, Inc.  in support of EPA, reviewed all  available  data regarding



body burden  in the  U. S.  Population (U.S. EPA, 1987).  The  open  literature was first




reviewed and, where  appropriate and  necessary, authors were contacted and asked  for the




original raw  data.  At this time, the Exposure  Assessment Group staff conclude that it




would be reasonable  to assume that  background levels  of 2,3,7,8-TCDD exist in some




persons in the U.S.   It is also  possible that background levels exist in the population at




large (i.e., virtually  all  persons in  the U.S.).   Review of  the limited  available data




indicate that an upper  bound background  level of 2,3,7,8-TCDD in the adipose tissue of




the U.S. population at  this  time is estimated to be about 6.7  ppt., but it  is not possible




at this time  to state  what an average body  burden  would be for the U.S. population at



large.






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e.  Calculation, Assumptions, Uncertainties, and Actual Parameter Values




     The method chosen to calculate daily intake  from adipose tissue  concentrations is




developed and described in detail earlier in the chapter.  Two major assumptions go into



the simplification  of  the  model  for purposes of  calculations  from  the  available data.




First steady state conditions are assumed.  Given that the elimination of the compound



from  the body is probably at  least five  years, it could take well over 15 years to reach




such steady state conditions. Thus,  the  assumption of steady  state could be considered




reasonable  only   if  background  environmental  concentrations  are  relatively  similar




throughout the nation.  Under those conditions even if people move from one geographic




area to another,  exposure concentrations would be relatively constant.   Also implicit in




the scenario of steady state  is an assumption  that the bioavailability of 2,3,7,8-TCDD is




virtually the same through the U.S.  As discussed in section  5-A, this does not appear to




be the case.  Therefore, even  if environmental concentrations  are  the same for a person




moving  from  one  area  of the country  to another the amount  absorbed into the body




could  vary  significantly.    Hence,  steady  state  conditions  may  not be  constantly




maintained.  The result of this is  that the adipose tissue  concentrations measured at  any




one time may not  reflect actual steady  state  concentrations.   Alternately, concentrations




measured at  one time, although  at  steady  state,  may  not reflect  concentrations of  a




steady state reached with a previous exposure to a form of 2,3,7,8-TCDD with different




bioavailabilty.    Errors resulting  from this assumption  could  either  overpredict or




underpredict daily intake.  Without knowing the bioavailability of the 2,3,7,8-TCDD at the




various locations  to which an individual  has been exposed and  the length of time that he




or she  may  have  been  exposed  at  these locations  it  is  not  possible  to  measure  the




amount of uncertainty associated with this assumption.




     The second  major assumption is that  2,3,7,8-TCDD is eliminated from the body by




monophasic kinetics.   Data gathered within  only a few years of  exposure  might  not






                                           142

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reveal  any second or even  third elimination phases that might exist.  (It should be noted




that  compounds with  large fat-to-blood partition  ratios frequently behave according to




two  compartment kinetics  with the fat acting as a "deep" second compartment).   The




result  from  an error  in  this  assumption  is  that the half-life  would  be  erroneously




underestimated.  As a result, the daily intake levels required to reach the steady state




levels  in  the adipose  tissues  would  be overestimated.  The impact of  this can be  more




easily minimized. Intake values can be calculated using a range of half-lives.  Choosing a




range  with sufficiently long half-lives assures that possible slower  phase  elimination




kinetic constants would also be  included.



     Also, the elimination  kinetics are  assumed to be constant over the entire life of the




individual.   This may  not  be  accurate  in many  cases.   Variation in  renal  function,




metabolic capabilities  caused  by disease and exposure to other compounds would alter the




kinetics of elimination over  the lifetime.  For the purposes of these  calculations, due to




the  lack  of  relevant data, it is assumed that the elimination rate constant is relatively




stable  with time.   Again, by choosing half lives far greater than those estimated in the




literature one is assured of including those individuals with reduced elimination rates.




f. Parameters Chosen




     The total  fat  volume for  a  70 kg  adult person  was assumed  to range  between 5




liters and  14  liters.   A  common assumption is 10 liters.  Based on the discussion above




an upper bound concentration  of 2,3,7,8-TCDD in adipose tissue at  steady state  of 6.72




ppt  was  chosen. Based on several  reports (Commoner et  al.,  1985; Poiger and Schlatter,




1980) and from extrapolation from elimination data in non human primates, a half-life of




approximately  5 to  8  years is assumed.  Because of the possible underestimation of this




value  as  discussed  earlier, however, a wider  range of 5  to  30 years  was  chosen.   As




discussed  previously, the value  of the partition coefficient between adipose and lean body




tissues was set at 100.






                                           143

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ig.  Daily Intakes Calculated




     The smallest  fat volume (5 liters), an adipose tissue  concentration of 6.72 ppt and




±he  longest  half-life in  the range  (30  years)  were  used for  calculating the  lowest




•reasonable daily intake.   The largest fat-.volume (-10 liters), the same concentration in the




adipose  tissue  (6.72 ppt) and  the shortest  half-life in the  range (5 years) were used for




calculating  the highest  reasonable  daily  intake.   A  fat volume  of  7  liters, the  same



adipose  tissue concentration of 6.72  ppt  and  a half-life of  10  years were arbitrarily




chosen :as a .reasonable expectation between extremes of the range.  Table 5-13 shows ithe




.results.




              TABLE 5-13. CALCULATED AVERAGE DAILY INTAKE
tl/2
(yrs)
5
5
10
20
30
30
Fat Vol
(L)
10
7
7
7
7
5
Vol of Dist
(L x 100)
14
10
10
10
10
7
,Conc in fat
(pg/gm)
6.72
6.72
6.72
6.72
6.72
6.72
Daily Intake
(pg/kg)
0.51
0.36
0.18
0.09
0.06
0.04
     .In summary these calculations resulted in estimates of daily intake of 2,3,7,8-TCDD



 between 0.04 picograms per  kilogram  body weight per day (pg/kg) and 0.51 pg/kg.  The



 "reasonable expectation" value is 0.18 pg/kg.  This latter value is in reasonable agreement



 with those reported by others (Geyer et al., 1986; Graham et al., 1985).  Also, the values



 calculated above are  similar to  those calculated  using  formulas discussed in  a recent



 paper  by Leung and Paustenbach (1987).



 h.  Impact of Daily Background On Risk



     Calculations are then performed as follows to  estimate the upper bound risk that



 could  result  from the background intake levels calculated in the preceding section:
                                            144

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     A  potency based on animal studies of 1.5  x 10   is multiplied  by the average daily




intake  (adjusted  for  fraction absorbed) to calculate  the  estimated  upper limit  of  risk.




The  value of the potency is discussed in Chapter 6. Because the average daily intake  was




determined  from  steady  state conditions  as  described above  the  exposure duration  is




assumed to  be  over the entire life time.   For illustrative  purposes the  highest calculated




daily intake was used for estimation.



     These  upper limit risks are then compared  with incidence of specific tumors and all




tumors  for  the  general  population.   Table   5-14   summarizes the  results  of these




calculations and comparisons.  As may be observed from  examining Table 14 if 2,3,7,8-




TCDD  were assumed to  cause  only  human soft tissue sarcomas, the  background intake




levels presently  calculated  would  account for, at most,  about  10%  of the soft  tissue




sarcomas  observed in  the  general population.    Similarly the background  levels would




account, at most,  for  1% of all non-Hodgkins lymphomas,  and less  than  0.1% of all




cancers  in the general population.




i.  Recommendations for Future Activities




     TCDDs have interesting and important pharmacokinetic characteristics. There appear




to be significant differences between species in  several  pharmacokinetic properties  and




parameters.  For example, rodents and primates show  very different elimination  kinetics.




The  impact that this and even  the effect of the larger fat compartment of  primates on




risk  estimates could be elucidated by the use of physiologically  based  pharmacokinetics.




The  role of the lymphatic system on absorption and transport of dioxin within the body




remains an unexplained process.  A well formulated and validated physiologically based




pharmacokinetic  model will accurately assess  the dose  received by infants from lactating



mothers with a body burden of TCDDs.
                                           145

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                                        TABLE 5-14
        RISKS ASSOCIATED WITH BACKGROUND DAILY INTAKE OF 2,3,7,8-TCDD
          COMPARED WITH ANNUAL CANCER INCIDENCE IN U.S. POPULATION
Upper Limit
of animal
  Potency      Daily Dose3
(pg/kg-day)'1   (pg/kg)
              Life Time
              Incremental
              Cancer Risk
              Resulting from
              Daily Intake
                   Upper Limit
                   Annual Cancers
                   Resulting from
                   Daily Intakeb
                 Background
                 Probability      Annual
                  Cancer in    Background
                 U.S.          Cancerb
1.5 x 1(T4       0.96
       -4
1.5 x  10
1.5 x  10~4
0.96
0.96
              1..47 x 10'4
1.47 x 10~4
1.47 x 10~4
                      504
504
504
1.9 x  10 '3      6500
(Soft Tissue
 Sarcoma)


9.2 x  10'3       32000
(Non-Hodgkins
Lymphoma)
(All Cancers)   965000
aDaily intake (absorbed) converted to applied dose to be consistent with animal derived potency
which is based on applied dose.
bBased on a U.S. population of 240,000,000.


     EPA's Exposure Assessment Group (EAG) is developing a physiologically based

pharmacokinetic model for TCDDs that, with properly gathered data for formulation and

validation, will:

     o    more accurately account for simultaneous exposure by more than one route and which

          does not depend on the implicit assumption that absorption fractions are the same over

          all concentrations, times, and for all  species;

     o   not be restricted to steady state conditions;

     o    account for elimination by other than monophasic kinetics and assess the potential impact

          of the change in elimination kinetics which may occur throughout life with changing

          exposure and physiologic conditions;

                                              146

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     o    account for elimination by more than on simultaneous process including lactational




          shedding;




     o    realistically represent the role that absorption of TCDD by lacteals and its transport by




          lymphatics may have;



     o    with proper data, be extended to food producing animals and thus be  used to more fully




          evaluate human exposure by this route; and




     o    help explain and account for obvious pharmacokinetic differences (metabolism, lipid




          sequestering, etc.) between species.  This is especially important regarding the differences




          between rodents and humans.




     With regard to risk assessments, there are several potential ways in which pharmacokinetics




may be applied in exposure assessments.  In a conventional risk assessment for carcinogens, some




dose-response function is generated, and from that function human risk is calculated at various




exposure concentrations. Usually such a process involves extrapolation from  animal high-dose



experiments to calculated risk for animals at low doses,  and  then further extrapolation  from animals




to humans.  First, the pharmacokinetic model enables the risk assessor to utilize some internal body



concentration of the parent compound of the metabolite (depending upon the mechanism of action)




as the dose for the dose-response curve.  The dose-response function is then calculated from the




model-generated  target concentrations.  To do this, something needs to be known about the




mechanism of action. At  the very least, it needs to be known whether the parent compound or the




metabolite is the  carcinogen.  An example of such a process was performed  for tetrachloroethylene



(Chen and Blancato, 1987), where the




     physiological pharmacokinetic model described total metabolite formation.  The amount of




     metabolite was  then used  as the dose in  the  two-stage cancer model  to  define the




     incremental cancer risk for  mice and the  compound's potency factor.   The next  step




     involves  adjusting the parameters  so  that the pharmacokinetic model  describes the target




     concentration  of  the  carcinogenic  species  in  human  tissues after  exposure.    This






                                                147

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calculated dose is then used with the potency factor to estimate the incremental risk for



humans (Chen and Blancato, 1987).  As more detail becomes known about the mechanism



of action, the pharmacokinetic model is further refined to give detailed  concentrations of



the toxin at very specific target sites.
                                           148

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                           PART TWO




APPLICATION OF EXPOSURE ASSESSMENT METHODS IN EVALUATING




      2,3,7,8-TCDD EXPOSURES FROM SELECTED SITUATIONS
                                149

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6.  USE OF METHODOLOGIES TO ESTIMATE EXPOSURE TO 2,3,7,8-TCDD




     In .this chapter, the methods and parameter refinements discussed in the previous




chapters will be used to calculate exposures and risks associated with several




hypothetical situations. The set of starting assumptions for these hypothetical situations




(both in terms of parameters and in terms of how sources are related to exposure) are




referred to as "exposure scenarios." Two sets of scenarios are presented in this chapter.




The  first set deals with 2,3,7,8-TCDD-contaminated land representing a range of site




types, i.e., contaminated soil situations, controlled-access landfills, and uncontrolled




access landfills (open dump).  The  second set deals with 2,3,7,8-TCDD-contaminated




emissions  from combustion devices (i.e., incinerators) and the disposal of




2,3,7,8-TCDD-contaminated fly ash collected in control equipment.  It should be noted




that  these scenarios are not meant to represent every possible event that could lead to




high risk.  The scenarios were selected to represent  a range of plausible conditions, but




they cannot be considered "representative" of the U.S. or region of the U.S. In many




cases, the parameter values were selected on the basis of best judgment rather than data.




Thus, this chapter applies  exposure assessment methods to a set of defined scenarios for




purposes of illustrating how they can be applied in site-specific  situations. Application




of these techniques to non-site-specific problems, may require collection of extensive




survey data to ensure  that the input parameters are  truly representative of  the area of



concern.  Further discussion of related issues is presented, along with details of the




scenarios, later in this chapter.




     Although this document is focused toward 2,3,7,8-TCDD, the other dioxin congeners




may also be of concern.  Accordingly, the other congeners are discussed briefly with




regard to  exposures associated with incinerators. This was feasible since some data was




available on the distribution of dioxin congeners in  fly ash.  However, no such data was




available for contaminated soil and thus they were not addressed for these scenarios.






                                           150

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     Exposure is often expressed as a daily contact rate averaged over an individual's




lifetime and body weight.  Estimates of exposure, including assessments of uncertainty,




are used  for conducting risk assessments.  The general equation used to estimate




2,3,7,8-TCDD exposure is  as follows:




             Exposure = (2,3,7,8-TCDD media  concentration x contact rate




                 x exposure duration x dilution and degradation factor




                    x distribution factor)  / (body weight x lifetime)           (6-1)




The above procedure will be used to calculate exposure levels in  this document.  The




procedure for converting these exposures to doses by consideration of absorption of the




contaminant into the body and estimating  risk is discussed in the Appendix.




A. DESCRIPTION OF THE EXPOSURE  SCENARIOS FOR CONTAMINATED SOIL AND




     LANDFILLS




     The first seven scenarios described below deal with situations where soil




surrounding a home or a farm has been contaminated with varying concentrations of




2,3,7,8-TCDD.  In scenario 1,  a family lives on a 1-acre site with 50% grass cover. This




is the only scenario where  farming and fishing are not conducted.  It is intended to




represent the more common residential setting.  However, it is still considered




"reasonable worst case" in terms of the behavior patterns affecting duration and




frequency of contact.  Scenarios 2-4 represent "reasonable worst-case" scenarios where




the soil has 50%  vegetative cover and the family living in the area gets much of their




food from their own farm. Scenarios 5-7  represent a more typical situation  where the




contaminated soil is  largely covered with grass and the family's habits are somewhat




more typical of  the population at large.




     Scenarios 8-15  deal with a farm situated near an inactive landfill.  In scenarios




8-11, the farm is located 100 feet from an inactive, uncontrolled access landfill



containing contaminated soil  with no vegetative cover. These factors, along  with the






                                           151

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behavior of the farm family are meant to represent a reasonable worst case. In



scenarios 12-14, the inactive uncontrolled access landfill has a grass cover,  the farm has




been moved to 500 feet from the landfill, and the farm family's habits are  considered



more typical of the population at large.  Scenario 15 is a capped controlled  access




landfill containing 2,3,7,8-TCDD contaminated material  (soil  or equivalent; no organic




solvents) in the same "reasonable worst-case" configuration as scenario 9.




     For each scenario, human exposure may occur by several pathways. It is a




relatively simple exercise to hypothesize situations for each exposure pathway that would




lead to unacceptably high risks. On the other hand, most such situations are relatively




rare, and would affect a relatively small number of people. In exposure assessment in




general, occurrence of a true "worst case,"  in which many variables approach their




maximum potential for exposure simultaneously, is exceedingly rare, approaching zero




probability of happening in a real-life case.  Moreover, the population affected would




also approach zero.  For that reason, the concept of "reasonable worst case" is used.




     Describing a "reasonable worst case" involves specifying situations where there is




judged to be a reasonable probability of individual events occurring, rather than looking




at a situation which would  maximize all exposure pathway risks simultaneously.  While




risks for all scenarios and pathways considered in this chapter are summarized later in a




single  table (see Appendix), it is very unlikely that people would experience the highest




risk for all exposure pathways simultaneously.  It would be reasonable to assume that an




individual could experience the calculated  risk of one to several of the pathways




simultaneously.




     Tables 6-1 and 6-2 summarize the assumptions concerning the fifteen scenarios for




which  exposure and risk estimates have been made.  For each scenario, estimates  were




made for the following pathways:




     o   dermal contact with contaminated soil;






                                           152

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     o    inhalation of 2,3,7,8-TCDD vapors;




     o    inhalation of dust from contaminated soil, both from wind erosion and




          vehicular traffic;




     o    ingestion of contaminated soil;



     o    ingestion of drinking  water contaminated by runoff (stream only);




     o    ingestion of fish contaminated by runoff;




     o    ingestion of beef contaminated via grazing on or near the site;




     o    ingestion of contaminated dairy products from cattle contaminated via grazing




          on or near the site; and



     o    ingestion of contaminated vegetables.




     The  following additional pathways were considered, but were not included in the




scenario calculations for the stated reasons:



     o    Ingestion of ground water contaminated from leachate from the landfill.




          Contaminant levels proved to be so low under all of the scenarios, even after




          hundreds of years, as to be of negligible risk. However, none of these




          scenarios considered leaching under  conditions where non-polar organics or




          other solvents were present as co-contaminants.  These situations could




          apparently make 2,3,7,8-TCDD more mobile, but  to what extent is uncertain




          (see section A of Chapter 2).  Physical transport of 2,3,7,8-TCDD-containing




          particles through a porous  subsurface zone can also have an appreciable effect



          on  mobility of 2,3,7,8-TCDD in soil. In any case, these situations should be




          evaluated on a case-by-case basis.




     o    Dermal contact with contaminated surface water and sediments.  These




          pathways would result in very small exposure relative  to the other pathways in




          any but the most extreme cases.  In  a case where relatively heavy
                                           153

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     contamination exists in a body of water where frequent swimming or




     wading/fishing occurs, this would  need to be evaluated on a




     case-specific basis.




The seven scenarios summarized in Table 6-1 represent the  following situations:




     Scenario 1:  A 1-acre area of contaminated soil (at 1 ppb  of 2,3,7,8-TCDD)




     where a family lives long enough for a child to spend  a 70-year lifetime.




     About 80% of the lifetime of this individual is spent in the vicinity of home.




     This is meant to represent a "reasonable worst-case" scenario for a non-




     farming residential  situation.



     Scenario 2:  A 10-acre area of contaminated soil (at 1  ppb of 2,3,7,8-TCDD),




     upon which is a small stocked pond, some area where cattle graze, and a




     garden to grow vegetables.  Fish are regularly caught and eaten by a family




     living on this farm.  The family lives there long enough for a child to spend




     his/her  70-year  lifetime there. About 80% of the lifetime of this individual is




     spent in the vicinity of home. Of the  individuals' lifetime food intake, about




     40% of the dairy products, 44% of the  beef  products, and 10% of the




     freshwater fish come from the immediate vicinity (i.e., from the pond and




     grazing  animals). This is meant to  represent a "reasonable worst-case" scenario.




     The exposure and risks, however, are not added for each  exposure pathway,




     since it  is unlikely that an individual would suffer worst-case exposures in all




     pathways simultaneously.  It is reasonable to expect, however, that given this




     situation, individuals would have a reasonable chance to experience exposures




     such as  those estimated in one or more pathways (i.e.,  several, but not all




     simultaneously).




     Scenario 3:  As above for scenario 2, but a one part-per-trillion starting




     concentration in the soil.






                                      154

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Scenario 4:  As above for scenario 2, but a one part-per-quadrillion




concentration in the soil.




Scenario 5:  The exposure area is the same as in scenarios 2 through 4, but




the pond is replaced by a stream located immediately adjacent to the exposure




area.  This is meant to represent a more "average" case than those above, in




that the exposed individual's actions are closer to the typical case.  The




individual  obtains 10% of his freshwater fish from the immediate vicinity.  The




individual  spends only about 40 years in the area.  About 50% of the lifetime




of this individual is spent in the vicinity of home.  The soil is contaminated at




1 ppb.



Scenario 6:  As above in scenario 5,  but contamination level is 1 part per




trillion.




Scenario 7:  As above in scenario 5,  but contamination level is 1 part per



quadrillion.The eight scenarios summarized  in Table 6-2 represent the following




situations:




Scenario 8:  A  1-acre uncapped landfill with no vegetation.  The open landfill




(see Figure 6-1) is  located 100 feet away from the exposure area. The




exposure area is a 10-acre farm including a residence, stocked pond, and




pasture.  Fish are caught regularly and  eaten by a family living on this farm.




The family lives there long enough for a child to spend his/her 70-year




lifetime near the site.  About 80% of the lifetime of this  individual is spent in




the vicinity of home.  Cattle graze in the pasture, which is contaminated by



runoff from the landfill.  Of the individual's lifetime food intake, about 44% of




the beef, 40% of the dairy products and 10% of the fish come from the




immediate vicinity (i.e., from the pond and grazing animals).




Scenario 9:  As above for scenario 8, but a  10-acre landfill site.






                                 155

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          Scenario 10:  As above for scenario 9, but a starting concentration of 1  part



          per trillion in the landfill.



          .Scenario 11:  As above for .scenario 9, but a concentration of 1 part per



          quadrillion in the landfill.



          .Scenario 12:  The exposure area is the same as in scenarios 9 through  11, but



          the pond is replaced by a stream located immediately  adjacent to the  exposure



          area.  This is meant to represent a more average case than in 9-11, though,



          since  the individual's actions are closer to the typical case.  The uncapped



          landfill in this scenario has been abandoned and grassed over (90% vegetation),



          but the soil is contaminated at the surface.  The exposure area (farm) is 500



          feet from the inactive landfill.  The exposed individual fishes  from the



          adjacent stream, is an average fish-eater, and gets  10% of his freshwater fish



          from  the stream. The individual only spends 40 years in the area.  About 50%



          of the lifetime of this individual is spent in the vicinity of home.  The



          inactive landfill itself is a  10-acre site with a contamination level of 1 ppb.



          Scenario 13.  As above in scenario 12, but the contamination level is  1 part



          per trillion.



          Scenario 14.  As above in scenario 12, but the contamination level is  1 part



          per quadrillion.



          Scenario 15.  This scenario is meant to be a reasonable worst case  treatment



          of a closed landfill. The size of the landfill is 10 acres, with 1 ppb



          contamination under a 25 cm clean cap, with grass over the cap (90%



          vegetation).  In other aspects this scenario is the same as scenario 9.



Scenarios 1-15 are diagrammed in Figure 6-1.

-------
                  Figure 6-1.  Landfill Scenarios
ON-SITE; Reasonable Worst Case
Scenario 1:
1 c
/\


ere
Scenarios 2-4:
ON-SITE; Typical Case
Scenarios 5-7:
                            Pasture
                         10 acres
OFF-SITE; Reasonable  Worst  Case
Scenarios  8-11,15:
Bare
Landfill
1-10 acres
100 feet ^

rponcT^
10 acres
OFF-SITE; Typical  Case
Scenarios  12-14:
Grass
Covered
Landfill
10 acres
500 feet

Pasture
a
10 acres
                                                             ^\
                           157

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      TABLE 6-1. ASSUMPTIONS FOR CONTAMINATED SOIL SCENARIOS
Scenario
Area (acres) contaminated
Soil concentration
Water body type
Vegetation on-site?
Family
Yrs. at residence
% time at residence
% freshwater fish
diet from contami-
nated water body
% beef from vicinity*
% dairy from vicinity*
Ages for soil
ingestion
1
1
Ippb
none
50%

70
80
NA


NA
NA
2-6

2
10
Ippb
pond
50%

70
80
10


44
40
2-6

3
10
Ippt
pond
50%

70
80
10


44
40
2-6

4
10
1 ppq
pond
50%

70
80
10


44
40
2-6

5
10
1 ppb
stream
90%

40
50
10


44
40
2-6

6 7
10 10
Ippt 1 ppq
stream stream
90% 90%

40 40
SO 50
10 10


44 40
40 40
2-6 2-6

aAverage percent of annual consumption which is home-grown by 900 rural farm households
 U. S. Department of Agriculture, 1966).

NA = not applicable.

-------
                  TABLE 6-2.  ASSUMPTIONS FOR LANDFILL SCENARIOS
    Scenario
                                                    Scenario

                                              9        10       11
                                                                            12        13       14     15
    Access
Cap?
Size (acres)
Waste concentration
Water body type
Vegetation on-site?
Distance (ft) from
site to exposure area

Family
Yrs. at residence
% time at residence
% freshwater fish
diet from contami-
nated water body
% beef diet from
contaminated sourcea
% dairy diet from
contaminated sourcea
Ages for soil
ingestion
uncontrol
   no
   1
   Ippb
   pond
   0%

   100
   70
   80
   10
   44

   40

   2-6
                                           uncontrol uncontrol uncontrol uncontrol
no
10
Ippb
pond
0%

100
 70
 80
 10
 44

 40

2-6
no
10
Ippt
pond
0%

100
70
80
10
44

40

2-6
no
10
Ippq
pond
                                    100
70
80
10
44

40

2-6
no
10
Ippb
stream
90%

 500
 40
 50
 10
                     44
uncontrol uncontrol cont
  no       no     yes
  10       10     10
  Ippt     Ippq   Ippb
  stream   stream pond
                                                        500
  40
  50
  10
                              44
                                                                 500
40
50
10
                                                                        100
70
80
10
                    44     40
 40       40        40     40

 2-6      2-6       2-6    2-6
aAverage percent of annual consumption which is home-grown by 900 rural farm households
 (U. S. Department of Agriculture, 1966).
                                                       159

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B. EXPOSURE PATHWAYS




1. General



     The parameters shown in Equation 6-1 must be defined for each of the pathways of



concern  in  a given scenario.  In the case of a landfill, inhalation of  vapors and dust,



ingestion of soil,  contaminated foodstuffs (fish, cattle) and drinking  water (from either




surface water or ground water sources), as well as dermal exposure to soil and sediments




are  plausible exposure  routes.   Chapter 4  of  this  report  presented techniques  for




estimating inhalation of  vapors, indoor levels of contaminated dust, and quantities of  soil




ingested.  Updated data on fish, beef, and dairy products consumption also are found




there.




     The effects  of  the  physicochemical properties  of  2,3,7,8-TCDD  on transport,




transformation, and bioavailability should be examined soon after undertaking an exposure




assessment.    Table 2-1  in this  report  presents  values for  the vapor pressure, water




solubility, and octanol/water partition coefficient.   These values were used to  estimate




intermedia distribution processes such as volatilization, sorption, and partitioning  between




aquatic sediments and  water (Section B of Chapter 3).




     Although the water solubility of 2,3,7,8-TCDD is extremely low, the presence of oil




or solvents  would  affect the movement  and environmental behavior  of the contaminant




(Section A of Chapter 2).  Although the  presence of oil or solvents would contribute to  a




worst-case scenario, the  methodology for predicting the effects is not  well defined, so oil




or solvents are assumed to be absent in the scenarios presented here.




     Exposure from inhaling  2,3,7,8-TCDD vapor  released from contaminated soil can be




estimated by calculating potential emissions, dilution  in the  atmosphere,  and effects of




photodegradation using methods explained in Section B of Chapter 4.




     An issue common  to  all exposure routes associated with soil contamination  is  how




the  concentration  profile over depth  affect human  exposure.   Work  by  Freeman  and






                                           1.60

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Schroy  (1986)  suggests  that contaminated soils develop  a profile  in  which  the  TCDD




levels at the surface  are essentially zero and increase  with depth.   This profile develops




because  photodegradation is  assumed  to deplete  the  surface  more quickly than vapor




diffusion moves TCDD upward.  Freeman and Schroy suggest that since the upper layer is




clean, exposure levels will be much lower than implied by the average soil concentration.




However,  the  clean  layer  is  very thin (<1 cm) and deeper levels  may contribute  to




exposure if  human activities  disturb the surface (i.e., digging, playing, working, etc.).




For  this reason,  the concentration  levels  used  in  this  report  are averages which  are




assumed to represent the levels of concern for purposes of human exposure.




2. Exposure Factors  Common  to More than  One Pathway




a. Degradation and Dilution




     Exposure  calculations  for several pathways may  be influenced  by  mobility  of




2,3,7,8-TCDD in soil.   Apparent  mobility in soil is  probably  the  result of volatilization




and  erosion (discussed  in  later sections) rather than  leaching.  Other factors  possibly




affecting  2,3,7,8-TCDD soil  concentration  include  photolysis  at  the soil  surface  and




microbial degradation in soil.




     The approach used in  calculating  risk associated with the  scenarios of this chapter




was  to  obtain  the  average soil concentration over the depth of concern and duration of




exposure.  The combined effect of the processes noted above should  be 2,3,7,8-TCDD  soil




concentration profiles which  change only slowly with time  and depth.   The  available




literature on these  topics was reviewed in depth in Section A of Chapter 3.




     Young  (1983) studied  a  surface  contamination  site  where losses were  attributed




primarily  to volatilization and photolysis.   An overall  loss half-life  for  2,3,7,8-TCDD




under  those  conditions  was reported to be  10-12  years.  However,  this study involved




shallow contamination depths.   Since photolysis is a surface phenomenon, the  results may



apply  only to scenarios which involve similar  depths,  such as  those  where  transport






                                           161

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occurs by. surface erosion.  Consequently, the effects of photolysis on estimated exposure



have  been incorporated  into the procedures used to model erosion in Section 6-B-2b




which follows, specifically, through an overall loss rate constant in Equation 6-4.




     In. Section  3-A, data  of  Bumpus  et  al.  (1985) were analyzed further, based  on




apparent first-order kinetics, to derive a biodegradation half-life for 2,3,7,8-TCDD equal




to 29- years.   This value was  specific, to one  fungus type  and soil  condition.   Other




investigators report  that microbial  degradation  of. 2,3,7,8-TCDD is  very  low.  or  not




detected..  A  29 year half-life, would translate  to a 35% reduction in exposure  over a




period of  40  years, relative to a  situation, where  no degradation  occurs.   Given  the




shortage  of data on biodegradation and disagreement  among existing data, rather than




consider  this phenomenon separately, it is assumed that any losses due to biodegradation




are reflected in the overall loss rate  constant of Equation 6-6.




     The ratio of the 2,3,7,8-TCDD concentration in the soil at the  exposure site  to that.




of the soil or sediment  at  the source referred  to in this  report as the dilution  factor.




This factor is common to all exposure pathways except those for inhalation.




     Soil, is  transported  from  a contaminated  site primarily  via  windblown dust and




suspended  sediment in  overland  runoff.   As  shown below, the contributions from




windblown dust to downgradient areas are estimated to be  negligible  compared  to the




sediment in runoff.




     Using the assumptions and procedure  described  below for the particulate emission




calculation, 0.44 mg/year of 2,3,7,8-TCDD is estimated to be  released from the  site  on




dust (for scenario  9;  1 ppb and bare soil).  Using  the  Universal Soil Loss  Equation, it




was  estimated that approximately  56 mg/year  of 2,3,7,8-TCDD could be  released  via




runoff.  Shifting wind directions will further reduce the amount of dust deposited at any




one  location around  the  site.  Lacking site-specific data,  a wind direction  frequency of




0.15 is commonly assumed.  This factor  reduces the potential dust deposits in one  of  the






                                           162

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standard 16  wind directions  from  the  site to 0.066  mg/year of  2,3,7,8-TCDD.  This



emission rate is approximately 0.1%  of the total runoff releases.




     In situations where the exposure area is  upgradient from the  contamination source,




soil transport will occur entirely via windblown dust.  Although  these scenarios  were  not




explicitly considered in this report,  the risk can be estimated by  simply dividing the risk



estimated for the downgradient areas by  1,000. This procedure should be applied to only




the landfill scenarios (8-15) for dairy ingestion, beef  ingestion, soil ingestion, and dermal




contact with  soil.




     The 2,3,7,8-TCDD in a field  downgradient  of  the site was computed by  assuming




that the 2,3,7,8-TCDD carried  to the field becomes mixed with  the soil in the field to a




certain depth.  The  mixing depth depends on  activities which disturb the surface, such as




construction, plowing,  vehicle  traffic, movement of cattle or other animals, burrowing




action of animals, and other biological activity.  Mixing depths for fallout plutonium have




been  found to be 20 cm on cultivated land and 5 cm on uncultivated  forest and rangeland




(Foster and Hakonson,  1987).  An intermediate value of 10 cm was assumed  here, for all




scenarios.  Using this  depth  and the area of  the field (10 acres), the  mass of soil into




which the  eroded 2,3,7,8-TCDD is mixed can  be calculated as:








       M = (10 acres) (4,047  m2/acre) (0.10 m) (1,700 kg/m3) = 6.88 x 106 kg      (6-2)








     The delivery rate of 2,3,7,8-TCDD to the field must also  be estimated.   The first




step in deriving  this value is  to use the Universal Soil Loss Equation (USLE) (U.S.  EPA,



1976)  to estimate the total amount of soil eroded from  the site:








                         A = (R)(K)(LS)(C)(P)                                  (6-3)
                                           163

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where A  = average annual  soil loss (tons/acre-year), R =  rainfall  and runoff erosivity



index, K  = soil erodibility factor, LS = topographical factor representing slope length and



steepness, C =  cover and management practice, and P = supporting practices factor.



     Average values of these factors  were obtained from a survey of over 70  sanitary



landfills in the U.S. (Science Applications International Corp. (SAIC), 1986):



     R =  155 -The rainfall  and runoff factor represents the influence of precipitation on



               erosion.   It  is  derived  from  data on  the frequency and intensity  of



               storms.  A  value of 155  is typical of rainfall  patterns seen  in much  of



               the midwestern United  States.



    K = 0.23 - The soil erodibility factor reflects the influence  of soil  properties on



               erosion.  A value of 0.23 is typical of sandy loam  with 2% organic  matter.



    LS =  1.5 - The topographic factor reflects  the  influence  of slope  steepness and



               length  on erosion.   A  value of 1.5 can  correspond  to a  variety  of



               combinations,  such  as  a  10% slope over a 100-foot  length  or a 5% slope



               over a 1,000-foot length.



     P =  1.0 - The supporting  practices factor reflects the use  of  surface conditioning,



               dikes,  or other methods to  control 'runoff/erosion. A value  of 1.0 reflects



               a compacted surface without control structures.



     The  final term in the  USLE is the cover and management practice factor (C), which



primarily  reflects how vegetative cover influences erosion.  The values assumed  for this



term  were  based on  the scenario  descriptions rather than the  survey discussed above.



Since the  site  is  bare  in scenarios 8 through 11, C is assumed  to be 1.0; since the site  is



grass-covered in scenarios 12 through 15, C is assumed to be 0.1 (U.S.  EPA, 1976).



     The  survey data could be used in two  ways.  The  average values for each factor



could be  multiplied together,  which yields R K LS P =  56 tons/acre-year.  Alternatively,



the factors for each landfill in the SAIC survey  could be multiplied together and then






                                           164

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averaged, which yields  (R)(K)(LS)(P) =  62 tons/acre-year.   Since there may be  some




dependency among the factors, the latter method is probably more statistically  valid and




was adopted here.  Combining this value  with  the assumptions for C yields the  following




erosion estimates:



     Scenarios 8-11:   A = 62 tons/acre-year




     Scenarios 12-15:  A = 6.2 tons/acre-year




     More sophisticated models are available for estimating erosion rates (i.e., CREAMS),




and should be considered in  actual site-specific assessments.




     The fraction  of  eroded soil  which  enters the field  must now be  computed.  This




quantity is very site-specific, depending  largely  on local gradients and runoff channeling




patterns.  If the field is located immediately downgradient of the site, a large fraction of




the eroded  soil may enter the field.  In scenarios 9-15, it  is assumed that the  field is




downgradient  from the  site,  but  100-500  feet  away.   Channeling  patterns  over this




distance could divert much  of the runoff away from the field.  For the reasonable  worst




case (scenarios 8 through  11 and scenario 15),  this factor was assumed to be 0.5,  and for




the more typical cases (scenarios  12 through 14) it was assumed to be  0.1.  This factor is




very similar to the sediment delivery ratio  used  by soil scientists to describe the  fraction




of eroded soil which  reaches a water body.  Wade and  Heady (1978) studied 105 major




U.S. river basins  and found sediment delivery ratios which  ranged from 0.001 to  0.378




with an  average of 0.042.  The delivery  factor used in this report refers to  the fraction




of soil reaching a  nearby  field,  which  should  be greater than  the  fraction  ultimately




reaching  a  water  body.  Thus,  it  is  reasonable  that  the worst-case factor is  slightly




greater than the upper end  of reported sediment delivery ratios and the typical factor is




slightly greater than the average reported sediment delivery ratio.  The wider range of




reported sediment delivery ratios reveals the site-specific  nature of erosion phenomena
                                            165

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and  the  potential uncertainty  regarding  how  the  values assumed here  would apply  to  a




particular, situation-.




     Mow the soil delivery rate, to the field can be-computed:  Scenarios 9 through 11:








      D.I; - (62- tons/acre.-year) (10 acres) (0:5) (907 kg/ton)




         = (-280,000 kg/year)                                                (6-4),








For.  the: other, scenarios,  a similar, procedure is  used,  yielding Dj  = 28,000 kg/  year for




scenario, 8 and. 15 and^D,], = 5*600 kg/year for  scenarios 12  through  14.




     In: addition, to. the contaminated, soil, delivered to  the  field a certain amount  of clean




soil:  will- also be delivered. (D-2). Assuming that the mass of soil in the field mixing  zone




remains constant a soil mass balance, can  be; written as  follows:








                    Dj + D2 =-R                                           (6-5)








where R. = removal rate of soil from  the field  mixing  zone.  No assumption  is made




regarding: whether the soil is  removed from the. mixing, zone  by accumulation under the




mixing zone or by runoff.  The value of D2 was. estimated using the same procedure^ as




illustrated  in  Equation 6-4  except that  the area  term represented the area between the




site  and. field.  This approach assumes that.clean  soil  enters the-field  only from the area




between, the site, and  field and  that the. same erosion  rates-apply to this area as the site.




The" values of D], D-2, and R are summarized in Table 6-3.
                                            166

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                       TABLE 6-3.  EROSION PARAMETERS
Scenario
8
9
10
11
12
13
14
15
D!
(kg/yr)
28,000
280,000
280,000
280,000
5,600
5,600
5,600
28,000
E>2
(kg/yr)
42,000
42,000
42,000
42,000
4,200
4,200
4,200
4,200
R
(kg/yr)
70,000
320,000
320,000
320,000
9,800
9,800
9,800
32,000
     Dj  = Delivery rate of contaminated soil to field

     D2  = Delivery rate of clean soil to field

      R  = Removal rate of contaminated soil from field


     Assuming that the eroded soil is perfectly mixed with the field soil to a depth of 10

cm,  the  resulting concentration  of  2,3,7,8-TCDD in the field can  be computed on the

basis of the following mass balance:
                         dC = DjCo - RC - kC                             (6-6)
                         dt   M      M
where  C  =  concentration  of  2,3,7,8-TCDD  in  field  soil  (kg/kg),  C0  =  original

concentration  of 2,3,7,8-TCDD in site soil (kg/kg), Dj  = delivery rate of contaminated

soil to field (kg/kg), M = mass of soil in field down to mixing depth (kg), k =
                                           167

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degradation rate constant (year-1), R = soil removal rate from field (kg/yr), and t = time

(year).

     The last term in Equation 6-6 represents  the  rate at  which 2,3,7,8-TCDD degrades

by any combination of  vaporization, photolysis, or biological degradation.  As discussed

previously,  this rate constant has not  been well  established,  but appears  to  be slow,

particularly  when  the  soil is not  exposed  to sunlight.    For  all the  scenarios,  no

degradation  was  assumed to occur at the  landfill  site,  largely because  much of  it is

buried and therefore  not subject to  photolysis.  Eroded soil  transport,  however,  is a

surface  phenomenon  that  increases  the  opportunity  for  photolysis  and   increases

vaporization rates.   This  situation  most  closely  matches the  experimental conditions

studied by  Young  (1983),  who derived  a rate constant of  0.069  year"', which  is also

assumed to apply to eroded soil.

     Assuming that the  2,3,7,8-TCDD concentration in the exposure  site  field  soil is

initially zero, Equation 6-6 can be solved to yield:
                    C =  DjSo.  [1 - e-(R/M + k)t]                         (6-7)
                         R + kM
     Equation 6-7 computes C as a function of  time (t).  The average  value  over a

70-year exposure period can be computed by integrating C with respect to t and dividing

by  the exposed period.  An alternative approach is to assume  that contamination at the

site has existed for a long period of time,  so that the 2,3,7,8-TCDD concentration in the

field has reached steady state, in which case:
                    C= DjCo.                                             (6-8)
                        R + kM
                                           1.6.8

-------
     This  latter approach was  assumed  to apply  for  the  exposure  site  worst-case

scenarios  8 through 11 and scenario  15.   Using the parameter  values  discussed earlier,

the dilution factor (C/CO) can now be computed (for scenarios 9-11):
               £_ = _D\_ -	280.000	    = 0.35              (6-9)
               C0   R+kM   320,000 + (.069) (6.88x106)
     The average value approach  was assumed to be more appropriate  for  the  off-site

typical case (scenarios  12 through  14).  The  average  value of C over a 40-year exposure

period was calculated as 0.008 C0, which implies a  dilution factor of 0.008.  Since the

soil  concentrations  are  defined for all  contaminated  soil scenarios  (1-7),  the  dilution

factor becomes 1.0.  All soil dilution factors are summarized in Table 6-4.

     It   should  be  noted  that  field  studies  of fallout  plutonium  have  observed  an

enrichment of plutonium  levels in stream sediment  over  that  found in upland  areas of

water sheds (Foster and Hakonson, 1987). This  phenomena is explained by the fact that

as overland runoff enters  a deposition area, dense  and  large  particles  (i.e.,  sand,  large

aggregates) deposit first and small/less  dense  particles  (i.e., clay,  silt) deposit  further

downgradient. This causes stream  sediment  to be richer in fine particulates than upland

soils.  Since  plutonium  preferentially associates  with smaller  particulates  the levels in

sediment are  higher than  levels in upland soils.   A  similar  phenomenon may occur with

CDDs due to their affinity  for  organics which are found in  the  smaller  or lighter

particulates.   This particle size enrichment was  not  accounted  for in  the dilution model

described above.  However, we believe that this enrichment effect  will be small compared

to the dilution  effects.  The plutonium  scenario involves fallout over  the  entire water

shed  whereas  the TCDD scenarios involve contamination  areas which are small compared

to the whole  water shed.   Thus, the contributions of eroded soil from the contamination

areas would be  small  compared  to the  contributions  from clean areas.  The resulting

                                            169

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dilution  is  further enhanced by  mixing with clean  soil originally  found  at  the site.

Ultimately,  field tests are needed to validate this model.




                         TABLE 6-4.  DILUTION FACTORS
     Scenarios
          Soil
     dilution factor
      Sediment
   dilution factor
Soil, reasonable
worst case (pond)
scenarios !• - 4
Soil, typical
case (stream)
scenarios 5 - 7
Landfill rea-
sonable worst
case (pond)
scenarios 8-11
and 15
Landfill, typical
case (stream)
scenarios 12-14
Soil concentration is
defined.
DF soil = 1.0
Soil concentration is
defined.
DFsoil = 1.0
Use steady state mixing
model to calculate soil
concentrations.
DF soil = 0.051 (Scenario 8)
DF soil=0.35 (Scenario 9-11)
DF soil=0.055 (Scenario 15)

Use non-steady state
mixing model to calcu-
late soil concentration.
DF soil = 0.008
Assume sediment
levels equal
soil levels.
DF sed = 1.0

Use erosion model to
calculate sediment
concentration.
DF sed = 0.001

Assume sediment
levels equal
soil levels.
DF sed = 0.051 (Scenario 8)
DF sed = 0.35 (Scenarios 9-11)
DF sed = 0.055(Scenario 15)

Use erosion model to
calculate sediment
concentrations.
DF sed = 0.001
     Finally, a methodology has been presented above which can  be used to estimate soil

concentrations  resulting from runoff  from an upgradient soil contamination  source.  Site-

specific  values were used  to illustrate application of  the  methodology at a hypothetical

but plausible range of sites.  We believe  that the range of selected  values are reasonable,
                                            170

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but insufficient data are available to interpret  these as representative of  the country  or




region of the country.  Rather, the methodology is best applied on a site-specific basis.




b.  Sediment Dilution Factor




     The worst-case scenarios involve a pond surrounded by contaminated soil.  Since the




pond  sediment is derived from locally eroded soils, the concentrations of 2,3,7,8-TCDD in




the sediment are assumed to  equal the  levels in the  soil;  i.e., the  dilution factor for




sediment is the same as that for soil.



     In  the typical  scenarios, the stream is  located 500 feet from  the contaminated site.




In this situation, not all of the soil eroded  from the site will  reach  the stream,  and the




portion  that does will  be diluted by clean  sediment  derived from other  portions of the




watershed.   If a uniform erosion rate  occurs throughout the watershed,  this dilution is




equal  to the area of  the site divided by  the area  of  the upgradient  portion of the




watershed.   This assumption should be valid in the  typical scenarios, since the site is




grass-covered, as can be expected in the remainder  of the watershed.   The site in all of




these scenarios (5-7, 12-14) is 10 acres, and the watershed is assumed to be 10,000 acres




(this  represents the median value found in  a survey of 70 landfills  [Science Application




international Corp., 1986]).  Thus, the dilution factor can be calculated as 0.001.




Alternatively, the dilution  can be calculated as follows.  The average runoff rate for the




midwestern  U.S.  is  about  15 inches/year  (Linsley  et  al.,  1982).    For a  10,000-acre




watershed, this yields a stream flow  of  18 cfs. The sediment yield can be estimated from




the stream flow as follows (Linsley et al., 1982):








                         Qs = aQn                                           (6-10)



where Qs = sediment flow rate (T/year); Q = stream flow rate (cfs);  a  and n =
                                            171

-------
empirical constants,  reflecting the vegetation cover  in  the watershed.   Linsley et al.




(1982) recommend using:








      a = 3,500 and n = 0.82 for coniferous forest and tall grass




      a = 19,000 and n = 0.65 for scrub and short grass








     Substituting into Equation 6-10 yields a  sediment flow of  37,000 to  124,000  T/year.




Using the  earlier estimate of 6.2 T/acre-year for the 10-acre site, the sediment dilution




is calculated  to be  1.7  x 10"-*  to  0.5  x  10"^.  These  estimates  agree  closely with  the



1,000-fold dilution indicated by the ratio of the site  area to the  watershed area.




     The soil and sediment dilution factors are summarized  in Table 6-4.




c. Body Weight




     Throughout all of the pathways  considered  in this  chapter,  except  that  of soil




ingestion, adult human  body weight is  taken  to  be  70 kg.   This factor was  discussed in




more detail in Section B of Chapter 2.  The specific assumptions and parameters  used in




the soil ingestion pathway will be discussed in detail in a following section.




d. Lifetime




     Following widespread  practice in  exposure and risk  assessment, the average  adult




lifetime  assumed throughout this chapter is 70 years.  Even  though actuarial data indicate




that  the U.S. average lifetime now exceeds  70 years, this  convention was continued in




order to simplify comparisons of risk with  those calculated in other analyses.




e. Pharmacokinetics




     While  not employed in this study,  physiologically based pharmacokinetic models can




be of great utility  in  describing the  disposition of compounds  within  the body  after




exposure.   As such, they  are an extension  of  the exposure  assessment into the body.




These higher-resolution exposure  assessments  provide  target  doses or  concentrations






                                           172

-------
which  risk assessors may eventually use in various types of dose-response functions to




better  characterize  risk.  Little is known about the exact mechanism of toxic action of




2,3,7,8-TCDD.  However, the model developed in Section B of Chapter 5 has great utility




in describing  previous  intake  from  adipose tissue  concentrations,  provided one assumes




the achievement of steady-state  conditions.   As more information  is gained  about the




mechanisms  of  action,  pharmacokinetic  models  may  be  used  as  the  basis   for




pharmacodynamic models which will further aid in the quantification of risk.  The latter




might  also be modified to describe and predict other important facets of the behavior of




this compound, such as placental and lactational transfer.




3. Specific Factors bv Pathway




     The specific input parameters used in calculating exposure and risk associated  with




various pathways are summarized in Table 6-5.  The exposure  estimates for each scenario




are presented  in Table 6-6.




a. Dust Inhalation from Wind  Erosion




     Dust emissions may occur as  a result of wind erosion only;  i.e., no  disturbance of




the surface due  to vehicle traffic  or other activity.  Emissions caused  by surface




disturbance are  discussed later in this  section.  The surface was assumed  to be exposed




to the wind, uncrusted,  and  to consist  of  finely  divided  particles.   This creates a




condition defined by U.S. EPA (1985a) as an "unlimited reservoir" and results in maximum




dust emissions due to wind  only.
                                           173

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TABLE; 6-5. FACTORS USED IN EXPOSURE CALCULATIONS



                     Scenario
Pathway
Soil ingestion
Contact rate (g/day)
Absorption, fraction
Exposure, duration (days)
Body-weight, (kg)
On-site dilution factora
Off -site dilutions factor*3
Dermal exposure- to soil .
Contact rate, (g/day)
Absorption fraction
Exposure duration (days)
Body weight (kg)
On-site dilution factora
Off-site dilution factorb
Vapor inhalation
n
Contact rate (m /day)
Absorption fraction
Exposure duration (days)
Body-weight (kg)
Fat, ingestion
Beef ingestion (g/day)
Dairy ingestion (g/day)
Absorption
Beef exposure duratation (days)
Dairy 'exposure duration .(days)
Body weight (kg)
On-site dilution-factor*
Off-site dilution factor*1
Beef fat/soil dist:
Dairy fat /soil dist.

1/8

1
0:3
1,600
17-
1.0
0.051

1.
0.006
20,000
70
1.0-
0.051

23
0.76.
20,000
70

26
43
0:68
11,000
10,000
70
1.0
0.051
0.4
0.04

2/9

1
0.3
1,500
17-
1.0
0.35.

1
0.005
20,000
70
1.0
0.35

23
0.76:
20,000
70

26
43
0.68
11,000
10,000
70
1.0
0.35
0.4
0.04

3/10

1
0.3
1,500
17-
1.0
0.35

'l
0.005
20,000
70
1.0
0.35

23
0.76
20,000
70

26
43
0.68
11,000
10,000
70
1.0
0.36
0.4
0.04

4/11

1
0:3
1,500
17
1.0
0.35

1.
0.005
20,000
70
1.0
0.35

23
0.75
20,000
70

26
43
0.68
11,000
10,000
70
1.0
0.35
0.4
0.04

6/12

0.2
0.3
910
17
1.0
0.008

1
0.005
7,300
70
1.0
0.008

23
0.75.
7,300
70

14.9
18.8
0.68
6,400
5,800
70
1.0
0.008
0.3
0.04
fContin
6/13

0.2
0.3
910
17
1.0
0.008

1
0.005
7300
70
1.0
0.008

23
0.75
7,300
70

14.9
18.8
0.68
6,400
6,800
70
1.0
0.008
0.3
0.04
ued 	
7 714

0.2
0.3*
910
17
1.0
0.008

1
0.005
7,300
70
1.0
0.008

23
0.75
7,300
70.

14.9
18.8
0.68
6,400
5,800
70
1.0
0.008
0.3
0.04
	 }
7/15

1
0.3
1,500
17
-
0.055

1
0.005
20,000
70
_
0.056

23
0.75
20,000
70

26
43
0.68
11,000
10,000
70
_
55
0.4
0.04

                          174

-------
                                       TABLE  6-5.  (CONTINUED)
Pathway
Dust inhalation
o
Respiration rate (m /day)
Absorption fraction
Exposure duration (days)
Body weight (kg)
Fish Ingeation
Ingestion (g/day)
Absorption
Exposure duration (days)
Body weight (kg)
On-site dilution factor3
Off-site dilution factorb
Distribution factor
Surface Water Ingestion
Ingeetion (L/day)
Absorption
Exposure duration (days)
Body weight (kg)
On-site dilution factora
Off -site dilution factor15
1/8

23
0.27
20,000
70

30
0.68
2,600
70
1.0
0.061
5

2
0.5
20,000
70
1.0
0.051
2/9

23
0.27
20,000
70

30
0.68
2,600
70
1.0
0.35
5

2
0.5
20,000
70
1.0
0.35
3/10

23
0.27
20,000
70

30
0.68
2,600
70
1.0
0.35
5

2
0.5
20,000
70
1.0
0.35
4/11

23
0.27
20,000
70

30
0.068
2,600
70
1.0
0.35
5

2
0.5
20,000
70
1.0
0.35
5/12

23
0.27
7,300
70

6.5
0.68
1,500
70
0.001
0.001
6

2
0.5
7,300
70
1.0
0.001
6/13

23
0.27
7,300
70

6.5
0.68
1,500
70
0.001
0.001
5

2
0.5
7,300
70
1.0
0.001
7/14

23
0.27
7,300
70

6.5
0.68
1,500
70
0.001
0.001
5

2
0.5
7,300
70
1.0
0.001
7/15

23
0.27
20,000
70

SO
0.68
2.600
70
-
0.055
5

2
0.5
20,000
70
_
0.055
aRefers to contaminated soil scenarios 1-7.





 Refers to scenarios 8-15.
                                                      176

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               TABLE 6-6.  EXPOSURE LEVELS ASSOCIATED WITH VARIOUS
                EXPOSURE  PATHWAYS/SCENARIOS - CONTAMINATED SOIL
                                               (ng/kg-d)
Scenario.
Dairy    Beef     Fish     Soil
inges-    inges-    inges-    inges -
tion      tion      tion      tion
                                    Vapor    Dust
                                    inhala-   inhala-
                                    tion      tion
        Drink-
Soil     ing-
dermal  water
Vegeta-
ble
inges-
tion
1)1 ppb
1 acre
reasonable
worst-case
NA      NA-      NA.
                           3.4xlO."S  9.8X10'6 4.2xlO'6   l.lxlO"2  NA
                                                                         See
                                                                         text
2)1 ppb
10 acres
reasonable
worst-case
9.6xlO"3  6.4xlO"2  2.2X10"1  S.4xlO"3  1.4xlO'6  3.4xlO'6 l.lxlO'2 6xlO~5
                                                                        See
                                                                        text
3)lppt
10 acres'
reasonable
worst-case
9.6xlO~6  6.4xlO'5  2.2xlOr4  3.4xlO"6  1.4xlO'8 3.4xlO'9 l.lxlO'5 6xlO'8
                                                                         See
                                                                         text
4)1 ppq
10 acres
reasonable
worst-case
9.6xlO"9  6.4xlO"8  2.2xlO"7  3.4xlO"
                                             3.4xlO"12 l.lxlO"8  CxlO"11
                                                                         See
                                                                         text
5)1 ppb
10 acres
typical
2.4xlO"3 1.6xlO"2 2.7xlO'6 4.2xlO"4 8.7xlO'6 1.2xlO'6 4.1xlO"3  2.2xlO"8
                                                                         See
                                                                         text
6)1 ppt
10 acres
typical
2.4xlO"6 1.6xlO"B 2.7xlO"8 4.2xlor7 8.7xlO"9  1.2xlO"9  4.1xlO"6' 2.2X10"11 See
                                                                         text
7)1 ppq
10 acres
typical
2.4xlO'9 1.6xlO'8 2.7X10"11 4.2x10"10 8.7x10'12 1.2x10'12 4.1xlO"9  2.2xlO'14
                                                                         See
                                                                         text
NA = Not applicable.
                                                                             (Continued	)
                                                      176

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TABLE 6-6.  (CONTINUED)
Scenario
8)1 ppb
1 acre
reasonable
worst -case
9)1 ppb
10 acres
reasonable
worst-case
10)1 ppt
10 acres
reasonable
worst-case
11)1 ppq
10 acres
reasonable
worst-case
12)1 ppb
10 acres
inactive
site
typical
13)1 ppt
10 acres
inactive
site
typical
Dairy Beef Fish Soil Vapor Dust Drink- Vegeta-
inges- inges- inges- inges- inhala- inhala- Soil ing ble
tion tion tion tion tion tion dermal water in gee -
tion

4.9xlO'4 S.SxlO'3 l.lxlO"2 l.SxlO'4 l.lxlO"6 4.6xlO"7 5.7xlO'4 S.lxlO"6
See
text

3.4xlO"3 2.2xlO"2 7.6xlO'2 1.2xlO"3 S.lxlO"6 S.SxlO"7 3.9xlO'3 2.1xlO'5
See
text

3.4xlO"6 2.2xlO"5 7.6xlO"6 1.2xlO"6 S.lxlO'9 S.SxlO"10 3.9xlO"6 2.1xlO"8
See
text

3.4xlO'9 2.2xlO"8 7.6xlO"8 1.2xlO'9 S.lxlO'12 S.SxlO'18 3.9xlO'9 2-lxlO"11
See
text

1.9xlO'5 l.SxlO'4 2.7xlO"5 S.SxlO"6 8.9xlO"7 5.3xlO"8 S.SxlO"5 2.2xlO"8
See
text


1.9xlO'8 l.SxlO'7 2.7xlO'8 S.SxlO'9 8.9x10' 10 5-SxlO'11 S.SxlO'8 2.2X10'11
See
text
/
                                (Continued	)
              177

-------
                                        TABLE 6-6.   (CONTINUED)
Dairy Beef Fish Soil Vapor Dust
Scenario inges- inges- inges- inges- inhala- inhala- Soil
tion tion tion tion tion tion dermal

14)1 ppq
10 acres l.OxlO'11 l.SxlO'10 2.7xlO~U S.SxlO'12 8.9xlO~ 1S 6.3xlO~14 S.SxlO"11
typical

15)1 ppb
10 acres neg. neg. neg. neg. 4x10 neg. neg.
capped land fill
reasonable worst-case
Drink- Vegeta-
ing ble
water inges-
tion

2.2xlO"14
See
text

neg. neg.


       scenarios assume  that the exposure area is downgradient of the contaminated source.  If the exposure -area was

located upgradient and all transport was via windblown dust, these exposures would be reduced by a factor of 1,000.


    \\                              fi
     neg. = negligible exposure (<10"e)
                                                       178

-------
     The  flux  of dust  particles  less than  10 um in diameter  from  surfaces  with an




"unlimited  reservoir"  of  credible particles can be  estimated as shown below  (U.S. EPA,




1985a):








                    E = 0.036 (1 - V) (Um/Ut)3 F(x)                        (6-11)








where E = total dust flux of <10 um particle (g/m2 .  hr), V = fraction  of vegetation




cover, Um = mean annual wind speed (m/s), Ut =  threshold wind speed (m/s), and F(x) =




a function specific to this model.




     The value assumptions for each  parameter are explained below:




     o    Fraction of vegetation cover (V)—For contaminated  soil scenarios 1-4, the site




          is assumed to be 50% vegetated (V = 0.5)  and for contaminated soil  scenarios




          5-7, the site  is assumed to be 90% vegetated (V =  0.9).   Under  scenarios 8




          through 11 the site is bare; therefore, V =  0.  Under inactive landfill  scenarios




           12 through 15,  the site is  assumed  to be largely  covered with  grass; therefore,




          V = 0.9.




     o    Mean annual  wind speed (Um)—U.S.  EPA (1985c) lists the mean annual wind




          speeds  at 10 meter height for the 60 major cities in the U. S.  These  values




          range from 2.8 to 6.3 m/s, with an  average  of approximately  4  m/s.   This




          average value  was assumed to apply  in all of the  scenarios.




     o    Threshold wind speed (Ut)—This is  the  wind velocity at a height of 7  m above




          the ground needed to  initiate soil  erosion.  It  depends on nature of surface



          crust,   moisture  content,  size  distribution of  particles,  and  presence of




          non-erodible  elements.  It can be estimated on the basis of  the  following




          procedure (U.S. EPA, 1985a):
                                           179

-------
     (1)   Determine  the  threshold  friction  velocity.    This is  the  wind speed




          measured at  the  surface needed to initiate  soil erosion.   For "unlimited




          reservoir"  surfaces, U.S. EPA  (1985a)  suggests  that this velocity  is less




          than  75 cm/s.    Thus,  a value of  50  cm/s  was  assumed  to  be




          representative of  these types of surfaces.




     (2)   Estimate the "roughness height." This is a measure of the roughness of




          the surface.   The  surface  of  the site  in  scenarios 1  through 4  and 8



          through  11  was assumed  to  resemble  a  plowed  field, which  has a




          roughness height  of 1 cm, and the site in scenarios 5 through 7 and




          12 through 15 is grass-covered, giving a roughness height of 2  cm.




     (3)   Estimate ratio of threshold wind speed  at 7 m to friction velocity.  Using




          a chart provided by U.S. EPA (1985a), this ratio is seen to be 16.5 for a




          roughness height  of 1 cm and 15  for a roughness height of 2 cm.




     (4)   Estimate threshold  wind speed.  Multiplying the friction velocity  by  the




          ratios described in  step  (3), the  threshold wind speed  is estimated as  8.2




          m/second for scenarios  1  through 4 and  8 through 11  and 7.5 m/s  for




          scenarios 5 through 7 and 12 through 15.




o    Finally,  F(x) is  determined  by first  calculating  the dimensionless ratio  (x)




     where  x = 0.886 Ut/Um (where Uf is the erosion threshold wind  speed (m/s)




     and Um is the mean wind speed (m/s)) and finding F(x) from a chart of F(x)




     versus  x, as  provided  in  U.S. EPA  (1985a).   For scenarios  1  through 4 and 8




     through  11,  x is 1.85 and  F(x) is  0.45; for  scenarios 5  through 7  and 12




     through  15, x is 1.7 and F(x) is 0.65.




The dust flux is converted to an emission rate as follows (U.S. EPA 1985a):








                    Q = CSEA (1 hr/3,600 s)                           (6-12)






                                      180

-------
where Q = TCDD emission rate (ng/s), Cs = TCDD concentration in soil (ng/g), and A =




site area (m2).




     The value assumptions for each of these parameters are explained below:




     o    TCDD concentration in soil  (Cs)—This value depends on the scenario




          assumptions, as specified in  Table 6-1.




     o    Site  area (A)—This  value  also  depends  on the  scenario assumptions.   For




          scenarios  1 and 8, the site  is assumed to be 1 acre (4,000 m2),  and for all



          other scenarios the site is assumed to be 10 acres (40,000 m2).




     For all  off-site scenarios (8-15), the  dispersion was calculated  on the basis of the



virtual  point  source dispersion  model, which  was  derived from  the  Industrial Source




Complex Model (Turner 1970).  This model is described in Chapter 4 (Equation 4-7).




     The value  assumptions for each of the  parameters  used in  Equation  4-7  are




explained below:




     o    Wind direction frequency ((j))--Lacking site-specific data, a default value of 0.15




          is  recommended for this  parameter (Turner 1970), which was assumed for all




          scenarios.




     o    Virtual downwind distance to receptor (Lv)—As explained in Chapter 4,




          this  parameter is computed  from Lv = L + 2.55 S, where L = distance to




          the  receptor  from  the  facility center and S =  facility width perpendicular  to




          the wind.  Assuming that the site  is a square, the  10-acre site  will have sides




          equal  to  200  m, and the  1-acre site  will have sides equal to 63  m.  Using




          these distances  and the 100-foot (30 m)  distance from  site edge  to receptor,




          Lv for scenario 8 is  223 m, for  scenarios 9 through 11 is 640  m,  and for




          scenarios 12 through 14 is 762 m.
                                           181

-------
     o    The  vertical dispersion coefficient (<7Z)—This parameter is a function of the air



          stability  and  distance from the source.   Lacking  site-specific data,  Turner



          1970 recommends assuming Air Stability Class D.  Using this assumption and  a



          chart of  L versus az from Turner 1970, crz for scenario & is 5 m, for scenarios



          9 through 11 and  15 is 6 m, and for scenarios 12 through 14 is 10 m.



     o    Annual average wind speed (Um)—As discussed earlier, this value was assumed



          to equal 4 m/second, based on national data, and was applied in; all scenarios.



     For  the contaminated soil  scenarios,   both  a  simple mixing box  model-  and  a



near-field dispersion modek were evaluated1 in Chapter 4.  The approach used' for vapor



emissions (described previously in Chapter 4-B) was also applied to dust emissions.



     The  final  step; is  to'  calculate' the  actual  exposure  resulting  from  inhalation' of



2,3,.7,8-TCDD-contaminated dust.  This is accomplished by application of  Equation* 6"-L



The values assumed for each parameter used in the equation are described below:



     o    Contact Rate--For  this pathway,, this parameter is  the respiration  rate.  The



          recommended rate is 21 m?/d  for. an. average adult who spends  22.4  hours/day



          engaged,  in light activity, 1.4 hr/d  engaged  in moderate  activity^ and 0.2



          hours/day engaged in; heavy activity (see Section B of Chapter 2).  This value



          was. assumed to apply to all scenarios..



     o    Exposure duration - For the reasonable worst case scenarios (1-4, 8-ll,:



          IS)'- as shown in Tables 6-1 and. 6-2,. the exposed population is. assumed:



          to live 70 years at the exposure  area and to actually spend 80% of their



          time, at this location. Thus, the exposure- duration is  calculated as:








                    ED- = (70 yr)(365 d/yr)(0.8) = 20,000, d                  (6> 13')

-------
          For typical case scenarios  (5-7,  12-14),  the  exposed population  is




          assumed  to live 40 years at the exposure location and to  spend 50%




          of    their time there.  Thus, the exposure duration is calculated as:








                    ED = (40 yr)(365 d/yr)(0.50) = 7,300 d                  (6-14)








     In  converting exposure (equation  6-1) to  risk  (equation  A-l),  the following




assumption is made:




     o    Absorption fraction—Schaum (1984), using animal data and information




          on fate of particles in the respiratory system, estimated that the




          fraction  of 2,3,7,8-TCDD absorbed  into the body ranges from 0.25 to 0.29.  An




          average of 0.27 was assumed to apply to all scenarios.




b. Dust Inhalation from Vehicular Traffic




     In addition to dust  emissions caused by  wind erosion, as discussed above, dust  can




also  be generated by vehicles entering the contaminated site.  This was assumed  to take




place for the  landfill scenarios [the incinerator scenarios are treated separately, since fly




ash is  being landfilled  (see  Section 4.C.e)], although it  is assumed  that no other activity




occurs that would generate dust, such as unloading.




     Several assumptions are  made to estimate emission rates  of particulate matter  and



hence  2,3,7,8-TCDD bound on the  particulates.  The  methodology for  estimating the




particulate  emission  rate is described in  section C of  Chapter  4.   The assumptions




include:   silt  content of soil = 20%;  vehicle speed  on the site  =  16  km/hr (10 mph);




weight of a vehicle = 12.3 Mg; number of wheels =  10;  days of precipitation =110 days.




Since the emission  rate is given in terms of kg dust/vehicle kilometers  traveled (VKT), it




is necessary to  estimate  the  approximate distances  vehicles  traveled  on the site.   The




dimension of a site would provide  the approximate distance that a vehicle would normally






                                           183

-------
travel.  This distance  multiplied by an  estimated number of vehicles that may travel  on



the site in a day would provide the VKT per day.   The estimated dust emission rate is



converted  to  an   equivalent  2,3,7,8-TCDD  emission  rate   based  on   contaminant



concentration in soil for each scenario.  The emission rate used for dust emissions in the



scenario exposure and risk  calculations is  the  sum  of the  wind  erosion  and vehicular



traffic contributions.



     Dispersion models are used  to  estimate  the  ambient air concentrations from the



emission rates.   Exposure  estimates  were then based  on the  degradation  factor,  body



weight, and  lifetime assumptions discussed  previously.   The exposure and risk estimates



are presented in Table 6-6  and the appendix, respectively.   The  calculations show that



for the scenarios used, the contribution  to ambient  air concentrations  by vehicular traffic



is about 1-2  orders of magnitude higher than that of wind erosion alone.



c. Vapor Inhalation



     The  exposure  assessment considered inhalation of 2,3,7,8-TCDD  vapor  as a pathway



for human exposure.  Despite the chemical's extremely low vapor  pressure, volatilization



can occur, with effects on the downwind population possible.  Example exposure and risk



evaluations will be shown for the eight assumed landfill scenarios.   Calculations will also



be shown wherever appropriate.



     In all of the  scenarios, the  first task  in  risk  assessment is to compute  the rate  of



volatilization.  The  emission rate thus calculated will be used in dispersion modeling to



estimate ambient air concentrations at various  distances from the source. The Industrial



Source  Complex (ISC) model approximating the area source as a virtual  point source can



be used for  dispersion modeling for receptors located  at distances greater than  100 m



from the  center of  the source.  For receptors  located at distances less  than 100  m  from



the  source,  short-range  dispersion  models  are  appropriate  to  estimate   ambient  air



concentrations.






                                           184

-------
     First, to  calculate the 2,3,7,8-TCDD vapor volatilization rate, pertinent data can be




listed as follows:




     Water/soil partition coefficient, Kj = 4,680 L/kg (Schroy et al., 1985b)




     Henry's Law Constant, Hc = 1.6 x 10~5 atm m3/mol (Podoll et al., 1986)




     Diffusivity of dioxin in air, Dj = 0.05 cm2/s (Thibodeaux, 1985)




     Soil porosity, E = 0.35




     Soil density, Ps = 2.65  g/cm3




     Soil/air partition  coefficient, Kas = 41Hc/K(j




                                         = 1.4 x  10"7 g soil/cm3 air




In order to estimate the average emission rate, the value  for the intermediate parameter,




G is calculated as follows, using Equation 4-3:








                 G = Di(E)4/3/[E + Ps(l-E)/Kas]




                    = 1 x 10~9 cm2/s.                                       (6-15)








     An  example  calculation  will  be provided  for a case where  the initial level  of




contamination, C0, is  1 ppb and the size of the  landfill is 1 acre.  The exposure factor




values listed in Table  6-5 will be used.  In addition, for lifetime exposure  evaluation the




emission rate  can be  averaged over the exposure duration, T, of 70 years (2.2  x  10^  s).




Then the average emission flux, Nj, is








               Nd = 2KasC0Di(E)4/3/[(3.14)GT]1/2




                  = 1.3 x 10~18 g/cm2-s = 1.3 x 10'8 ug/m2-s.               (6-16)








     The  above emission flux assumes that the site is contaminated  from  the  surface of




the soil downward and that  no clean cover material is applied initially.  When soil is






                                           185

-------
contaminated  at the surface,  the emission rate is initially high, and gradually  decreases.



The  instantaneous  emission rates  at  various  time  intervals can  be summed up by  an



integration technique averaging over the period during which the emission continues.



     For a 1-acre site, the dimensions of the  site can be  approximated by 63.6 m x 63.6



m.  For a  receptor 500 feet (152 m)  away from the downwind edge of the site, the ISC



model can be applied by  noting that the actual distance from the center of the facility



to the receptor is 152 m + 63.6 m/2 = 183.8 m.  This is the distance needed in obtaining



the values  for  the  standard  deviation.   The  ambient  air  concentration, Ca, can  be



calculated  (Equation  4-8) as 9.7  x 10~^ /jg/m  , where  the default stability  class =  D,



wind  speed  = 4  m/s,  when  the  winds are  blowing  toward the receptor (100% wind



frequency), and other  symbols  are  identical to  earlier definitions.  The ambient  air



concentrations thus calculated are  shown in Figures 6-2  and  6-3  for 1 acre and 10 acre



sites,  respectively, as a function of distance.



     The  exposure  associated with breathing ambient air was  computed assuming the



concentration was reduced by the frequency  that  wind blows toward the receptor (15%)



and  substituting Ca  into  Equation  6-1.   By  multiplying  the  resulting exposure  by



absorption fraction  and by the cancer  potency  factor,  risk  estimates can be  obtained.



These risk estimates  are given in  the Appendix.  The  changes in exposures  encountered



prior  to absorption into the blood stream over  distance are shown in Figures 6-2 and



6-3.



     For  an  uncovered landfill with the  contaminant initially  present at the  surface,



ambient air  concentration,  and  therefore  exposure,  is  directly  proportional  to  the



contaminant  concentration  in  soil.  This relationship persists up  to  the  point  where the



air is  saturated  with 2,3,7,8-TCDD vapor  (186  ppb).   The concentrations calculated for



the scenarios in  this chapter are well below the saturation  level.
                                           186

-------
               Figure 6-2.   Ambient Air  Concentration
                            and Exposure with distance for
                            I  Acre Site.
                                                          Figure fj-3.  Ambient Air  Concentration
                                                                       and Exposure with distance  for
                                                                       10 Acre Site.
oo
 TO

 O>

 1—
 01


CM

T
      Ol
      .'O
      ex
      X
           1.2
           1.0
           0.8
           0.6
           Q.4
0.2
                                   oo

                                    O
                                    60
                                    9
                                              V
                                              c
                                              C
                                              D
                                              B
                                                               .
                                                               ro
                                                   C\J
                                                   i—i
                                                   I I
                                                              9
                                                              r
Ol
i-
^
to
O
O.
X
              0
        50   100   150   200  250
                                          0
                                      oo
                                      i
                                      o
                                                                                                      00
                                                                                                      3
                                       u
                                       c
                                       o
                                       u

                                       (-1
                                       •H
                                                                                           C
                                                                                           
-------
     The change in exposure  with distance from a 10-acre site  is illustrated  in  Figure




6-3. These calculations assume 1  ppb 2,3,7,8-TCDD in the soil, wind direction frequency




of 15%,  and that exposure  occurs over 80% of a 70-year lifetime.  For scenarios  10 and




11, concerned with concentrations of 2,3,7,8-TCDD in soil  at  1 ppt and 1  ppq, ambient




air concentrations and the corresponding exposure levels at  the appropriate locations will




decline linearly with declining  concentration in soil.




      The ISC model cannot be used for estimating the on-site ambient air concentration




of 2,3,7,8-TCDD at the site with contaminated  soil, because the model is not applicable




at distances close to the source. The on-site dispersion model given by Equation 4-6 was




used to estimate the concentration for scenarios  1-7.  Wind rose data should be used for




site-specific evaluation of annual  ambient concentrations.  For  the most common stability




class D, the standard deviations (a) can be estimated in units of meters as shown below:








                    ay = 0.1414 x°-894                                      (6-17)
and
                    
-------
4-7.  The on-site ambient air concentration for a 1-acre area of contamination, obtained



by substituting into the box  model equation, equals 1.9 x 10"^ pg/m*.  For a  10-acre site



at the initial contaminant concentration of 1  ppb, the on-site ambient air concentration,



calculated in the same fashion, equals 6 x  10"' /ig/m^.



     In reality,  as volatilization proceeds,  a non-uniform concentration will be established



along  the depth of the  contaminated soil.   The non-uniformity of the  concentration



profile can  be reduced still  further if the soil surface  is disturbed.  Disturbance reduces



the  effectiveness of  the surface layer  in  acting  as a  diffusion  barrier  to pollutant



transport, increasing the  emission rate.   Thus, removal of  surface soil  some time after



the  initial contamination  will increase emissions,  and hence exposure.   However, it  is



very  difficult  to quantify  the  magnitude  of this phenomenon and  the corresponding



increase in exposure to downwind populations.



     Controlled or closed landfills typically are capped.  The major purpose of capping is



to minimize the generation of leachate by preventing the infiltration of precipitation into



the  waste.  However, a  cap initially  free of contaminant will  also reduce volatilization



rate, thus reducing exposure.



     Rigorous mathematical  formulae are  available to  predict the emission rate at various



thicknesses  of  cover material (U.S.  EPA,  1986a).   Because  the calculations involved



require a  computer  for solution, as an approximation one may use a retardation factor, as



suggested in Chapter 4.  The vapor emission rate through a cover will  not  reach steady



state for hundreds  of years.   The  emission rate,  which initially  is  zero,  gradually



increases, and  finally reaches a  steady  state  when  all  adsorption  sites are saturated.



Taking into account this  time-dependent emission rate, a 25-cm cover  initially  free of



contaminant will reduce the  exposure and  risk over a 70-year period by a  factor of 5.
                                           189

-------
d. Dermal Exposure



     The exposures resulting from this pathway were computed using Equations 6-1.  All



parameters used in these equations are discussed below.



     Dust  from contaminated  soil  can. be carried indoors,  potentially  causing exposure



resulting, from cleaning and  other indoor activities.  For this  analysis it is  assumed that



the 2,3,7,8-TCDD levels in  the; soil surrounding  a home are  equal to  the  levels in the



dust inside, a home.



     Very  few data  are available on the amounts  of soil  that accumulate on human skin.



Obviously, such amounts will vary considerably  depending on behavior characteristics,



skin condition, soil type, exposed skin area, contact time, etc.   Schaum  (1984) concluded



that the limited data suggest  a daily contact rate of 0.5  to  1.5 mg/cm .   Using this



factor  in  conjunction with  estimates of the  exposed skin areas and  number of  days



exposed, the total soil contacted can  be computed:








      Soil contact rate (mg/d) =



           contact rate (mg/cm^-d)  x exposed skin area (cm^)                (6-19)








     For the purposes of this  analysis, the  contact rate  is assumed to be 1  mg/cm^-day



for all scenarios.  The exposed skin area, depends on the type of clothing worn and the



age of the exposed individual.  Schaum (1984) used a range of 910  to 2,940 cm^  for an



adult,  based on typical clothing, and adjusted this number for children proportional to



their body  surface  area.    This   age adjustment is  small  compared to  the  overall



uncertainty involved in  40- to 70-year exposure periods.   Thus,  for  this  analysis, the



exposed skin area was assumed to  be  1,000  cm^ for all scenarios.  Applying Equation



4-18, the soil contact rate is computed as 1 g/d, which was assumed for all scenarios.
                                           1;90

-------
     The  exposure duration was  derived  from the scenario assumptions given in Table



6-1.  For scenarios 1 through 4, scenarios 8  through 11, and scenario 15,  the exposure




durations were calculated as follows:




      Exposure duration = (70 yr)(365/d/yr)(0.8) = 20,000 d                  (6-20)




     For  scenarios  5  through  7,  and  12 through  14,  the exposure durations were




calculated as follows:








   Exposure duration = (40 yr)(365 d/yr)(0.50) = 7,300 d                     (6-21)








     Schaum  (1984)  was able to  find  only one relevant  animal  experiment dealing  with




dermal  absorption of  2,3,7,8-TCDD.   This  experiment  suggested  that  the absorption




fraction  varies from 0.07% to 3%.   Differences  in skin  properties between humans and




rats and differences between experimental conditions and the human exposure scenario




make it  very uncertain how well this absorption estimate applies in this analysis.  The




geometric average of this range, or 0.5%, was assumed to apply in all  scenarios.




     The remaining  parameters  used to calculate  exposures and risks, i.e.,  body weight,




lifetime,  potency  factor, degradation  factor, and  dilution  factor   were  all discussed




previously in  Section B.2 of this Chapter.




e.  Soil Ingestion




     Soil  ingestion exposure  estimates  were based largely  on the  procedures  provided  by




Schaum (1984).  The exposures were calculated using Equation 6-1.   All  parameters and




value assumptions  used in these  equations are discussed  below.   While estimates  of soil




ingestion  rates  are still  uncertain,  new  studies  have allowed some refinement  of the



procedures  presented in the original  report.   As discussed in  Chapter  4, the current




literature  suggests  that ingestion  rates average from 0.2  to 1.0  g/d  for young children.




The low end of this range,  0.2  g/d,  was assumed  to apply in  typical case scenarios  5






                                           191

-------
through 7, and 12 through 14.  The upper end, 1 g/d, was assumed to apply in reasonable



worst case scenarios 1 through 4, scenarios 8 through 11, and scenario  15.



     Inadvertent soil ingestion occurs among adults as well as children.  As indicated in



Chapter 4, actual measurements of adult soil ingestion have not  been  made.  However,



Hawley (1985) estimated  soil ingestion could be 61 mg/d, based largely on  unsupported



assumptions  regarding  activity  patterns and corresponding  ingestion  amounts.   This



ingestion   rate  is  much  less  than  the 200  to   1,000  mg/d  assumed  for  children.



However,the longer exposure periods for adults suggest that adult soil ingestion could be



of the same magnitude as that for children.



     The  gut absorption of 2,3,7,8-TCDD adsorbed to soil is discussed in detail in Section



A of Chapter 5.  The available data suggest that the absorption fraction is  20% to 40%.



The mid-value of this range (30%) was assumed to  apply to all scenarios.



     Soil  ingestion  can  occur at any age,  but is  most prevalent among children.   The



best available data  apply to children ages  2 through  6.   On this basis, Schaum  (1984)



concluded that  this age  represents  the time  when mouthing  tendencies  and  lack of



understanding of personal  hygiene will cause the most  significant soil ingestion.   This



5-year time  interval was  adopted in this analysis as the basis for computing  the exposure



duration.   Combining this  interval with the scenario assumptions summarized in Tables



6-1  and 6-2, the  following estimates were  made:   Scenarios  1 through 4,  and 8 through



11, and 15:








     Exposure duration = (5 yrX365 d/yr)(0.8) = 1,500 d                     (6-22)








Scenarios  5 through 7 and 12 through 14:








      Exposure  duration = (5 yr)(365 d/yr)(0.5)  - 910 d                     (6-23)






                                           192

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The factors 0.5 and 0.8 in the above calculations reflect estimates of the fraction of time




an individual is likely to spend in the exposure area.



     The body weight for a child aged 2 to 6 is an average of 17 kg, which was assumed




in all scenarios.



     The remaining factors used  to compute exposures and risks  (2,3,7,8-TCDD dilution




factor and  degradation factor) were discussed previously in Section B.2. of this chapter.




f. Ingestion of Beef and Dairy Products




     Grazing  animals ingest soil as they forage,  in amounts ranging from  2% to 15% of




total  dry  matter intake, as noted  in  Section  C  of  Chapter  3.   Some  fraction of  the



contaminated  soil deposited on neighboring land by  runoff thus  is likely to be ingested




by animals pastured there.   Dust evolution and redeposition from a contaminated  site




onto  forage generally is a less  important  source for bioaccumulation  through  cattle, as




shown in Section B.2.a. of this chapter, and adds a negligible amount to the intake of




cattle in these scenarios.




      The  contributions of  beef and dairy  products to 2,3,7,8-TCDD in the human diet




were calculated by substituting input values from Table 6-5 into Equation 6-1. Rationales




for  the  dilution factors  used  are provided  in  Section  B.2.a.   and  the  results  are




summarized in Table 6-4.




      For  the  reasonable  worst  case  scenarios the  exposure  duration  was  estimated




assuming   that the exposed  individuals  received 44%  of  their  beef diet from  the




contaminated  area.   This  value  represents the  average  percent  of annual consumption




which is home-grown  by 900  rural farm  households (U.S.   Department of  Agriculture,




1966). Accordingly 11,000 days is estimated:








               (70 yr)(365  d/yr)(.44) = 11,000 d                             (6-24)
                                           193

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The 44%  diet assumption was. also  applied to. the 40 year typical case  scenario resulting



in  an  exposure  duration of 6400. daySv   Similarly,  for the  dairy products  ingestion



scenarios;, a; 40% (U.S.D.A., 1966) diet assumption; was used yielding a 10,000 day exposure



duration? for the reasonable worst-case; scenario: and 5800 day exposure duration for. the



typical! case scenarios.  Nate that the  percent diet assumption could have been applied to



either;  tfie exposure; duration estimate or- the  consumption rate estimate.   When the



exposure  factors;  are' multiplied together,  either approach  yields  the  same-  exposure



estimate.



     Bioaccumulation of. 2,3,7,8-TCDD. in cattle  is well documented. (Section C of Chapter



3).   Equation. 6-1, used to. calculate, exposure, takes this into account in  the distribution1.



factor  term..  The ratio of 2,3,7,8.-TCDD; in beef fat to that in soil where the animals



were pastured  was  also  discussed in Section  C of Chapter  3, as  was  the  ratio- of



2,3y7,8-TCDD in milk fat. to that in soil.  Use-of a beef  fat/soil bioaccumulation factor of



0.3' to  0.4 and a milk fat/soil bioaccumulation factor of 0.04 were  recommended  in the



absence, of site-specific data.



     Fries: and Marrow (1975) estimated that 50%. to 60% of 2,3,7,8-TCDD was absorbed



by  rats from feed. Rose  et al. (1976)  estimated that 86% of 2,3,7,8-TCDD in a. mixture of



acetone and corn oil fed by gavage to rats was absorbed. The  average of this  range, or



68%, was assumed to apply to beef and dairy products.



     Exposures  calculated under the  various scenarios  are presented in<  Table.  6-6, and



risks, are- presented in the Appendix.



g.  Ingestion of  Fish.



     Potential  exposure  through ingestion  of   freshwater  fish was  calculated  using



Equation- 6-1.  While significant new information on  fish  consumption  is. described, in



Section F of Chapter 4;  the national average intake of  freshwater fish still appears well



represented  by  the value 6.5  g/d  used  by Schaum (1984).  The reasonable worst-case






                                           1,94,

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scenarios (2-4, 8-11,  15) use a somewhat higher intake value,  30 g/d,  which attempts  to




represent  a small  subpopulation  fishing from nearby water bodies and consuming fish




caught.




     Two fish consumption behavior patterns are assumed in this report.   In the typical




case, the exposed individual consumes an average of 6.5 g/d of freshwater fish of which




10% is derived  from  the contaminated  source (a  relatively  small  stream).   In the




reasonable worst case,  the exposed individual  consumes  30 g/d of  freshwater  fish  of




which  10% is derived from the contaminated source (a relatively small pond).




     The   reasonableness   of  these assumptions  can  be  analyzed  as  follows.    The




consumption rate  for the  typical case represents an average  U.S.  value.   A  one meal



serving of fish weighs about  100 g.  Thus  in the typical case  a little over two meals of




contaminated fish would be consumed per year:








                (6.5 g/d)(365 d/yr)(0.1)/100 g/meal  - 2.4 meals/yr           (6-25)








Assuming  that the weight of the fillet is  half  that of the whole fish, this would imply




that two  200  g (about a half pound) fish are caught from the stream per year.   This




catch rate and fish size appear reasonable for a small stream and an average consumer.




     In the reasonable  worst  case, a consumption rate is used which  represents a person




actively involved  in  sport fishing  and consuming relatively large amounts of fish.  For




this situation, about 11  meals of contaminated fish would be consumed per year:








                (30 g/d)(365 d/yr)(0.1)/100 g/meal -  11 meals/yr            (6-26)








This number of meals implies that eleven 200 g fish are caught from  the pond per year.




This catch rate and fish size appear reasonable for a small pond and  an  active fisherman.






                                           195

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     For  the  reasonable  worst-case  scenarios,  the exposure duration  was estimated as



2600 days:



               (365 days/yr)(70 yr)(0.1) - 2600  d.                           (6-27)



For the typical scenarios,  the exposure duration  was estimated as 1500 days:








               (365 d/yr)(40 yr)(0.1.) = 1500 d                              (6-28)








Note  that the  10%  of diet assumption could have been  applied  to  either the exposure



duration  estimate or  the consumption rate  estimate.   When  the exposure  factors are



multiplied together either approach yields the same exposure estimate.



     Calculating  the concentration of 2,3,7,8-TCDD in water as a result of contaminant



leaching from  sediment provides  interesting information on bioaccumulation in fish and



other aquatic  organisms.   The methodology is  shown  in  Section B of Chapter 3.  This



calculation  represents  the "water-to-fish"  portion of  fish  body  burden.   In  addition,



aquatic organisms will pick  up contamination from contact with sediments, ingestion of



suspended and bottom sediments, and ingestion of other contaminated organisms.   The



latter  contribution  practically  always  predominates,  but  the influence  of both are



accounted for  by measuring  "fish/sediment distribution factors." Based on the discussions



in Section C of Chapter 3, fish/sediment distribution factors are in the range of 1 to 10,



but a  single value of 5  was used in calculating  exposures associated with this pathway



for scenarios 2 through 15.  The results are presented in Table 6-6.  Fries and Marrow



(1975) found that 50% to 60% of  2,3,7,8-TCDD was absorbed by rats from feed.   Rose  et



al. (1976) found  that 86% of 2,3,7,8-TCDD in  a  mixture  of acetone  and corn oil  fed by



gavage to rats  was absorbed.  The average of  this range, or 68%, was assumed to  apply



to human gut absorption of 2,3,7,8-TCDD from fish.
                                           196

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h. Water Ingestion-- Surf ace Water




     Overland runoff could result in contamination of surface waters near the site.  The




transport model described in Chapter 3 will be used to estimate  the extent of release of




2,3,7,8-TCDD from sediment to water body.  It  is straight-forward to use the transport




model once all the mass transfer coefficients are evaluated.  These transfer coefficients




include the sediment side coefficient, the water-side coefficient,  and the overall  mass




transfer  coefficient  for  the  air-water  interface.    Basically   the  sediment-side  and




water-side coefficients  can be estimated from Equations 3-5 and 3-6.  Examples of the




worst  case and  a typical case will  be separately considered in  evaluating  the  effect of




sediment on the water quality.




     In the worst case,  the water body will be assumed to  be a  1-acre lake (64 m x 64




m) surrounded by soil with 1  ppb 2,3,7,8-TCDD.  As described previously,  the sediments




at the  bottom  of the  lake  are assumed to reach  an equilibrium level  at  the  same




concentration  as  the soil (1  ppb).   To estimate  the sediment-  and water-side  mass




transfer  coefficients, the following assumptions are  made:  The  water and  sediment




temperature is ambient  (15° - 25°C); the depth of the water body is 5 m; the lake water




has no significant inflow or outflow; the  thickness of sediment is 1 cm;  and the bottom




of the lake is covered by sediment  with a porosity of 50% and with 1%  organic matter.




These  assumptions provide  the water-side coefficient  of  kw  =  0.63  cm/hr and the




sediment-side coefficient of ke = 8 x 10"^ cm/hr.




     As  presented in  Section  B of Chapter  3,  the overall mass transfer  coefficient



between  the  water  and  air  phases  is  KLa  = 0.725  cm/hr.    At  the  contaminant



concentration  in  sediment of 1.0 ppb, the concentration of the contaminant  in the lake




body can be calculated from Equation 3-4, and is 2.3 x 10"^ ug/L.  This  concentration




compares  with an equilibrium concentration that would exist in  water if an equilibrium




between  the sediment and water were established; or  1.0 ug/kg/4,680 kg/L = 2.1 x 10"^






                                           197

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Mg/L.   The transport  model therefore indicates a concentration in water of about two



orders of magnitude lower than the equilibrium concentration.



     The  risk  from drinking surface water  contaminated at 2.3 x  10"^ /*g/L can be



computed using the procedure presented in the Appendix.  Assuming:



     o    the absorption fraction is 0.5 (Fries and Marrow, 1975);



     o    the exposure duration is 2Q,000 days;



     o    the water consumption rate is 2 L/d (U.S. EPA, 1984a);



     o    a 70-year lifetime; and



     o    an average body weight of 70 kg;



the  risk is estimated to  be 9 x 10  .   This should  be considered as a  worst-case



estimate, since it assumes a high  level  of sediment concentration and a long  exposure



duration.   Also, it is  rare  for people  to  use  untreated water  from small ponds  as  a



drinking-water source.  It is much more likely that wells would be used, which would



have substantially reduced 2,3,7,8-TCDD levels.



      In a typical case, .the analysis deals with the sediment contaminating the bottom of



the river stream.  As  previously shown, the concentration of 2,3,7,8-TCDD in  the river



sediment  is diluted  by  a  factor  of  1000  from  the original  concentration  to  a



concentration  of 0.001 ppb.   It  is assumed that the  size  of  the contaminated area  is



similar  to .the size  of  the lake.  Also, the depth of the  flowing river is assumed to  be 5



m with the bottom sediment at a thickness of  1  cm.  The average water flow  rate is 1



m/s.



     Calculations similar to that  just shown for the  pond water  body  will yield  the



concentration in  the river as 3 x  10"^ A*g/L. with an obviously negligible risk (3 x  10"^



at the potency slope of 0.156 (ng/kg d)"1).
                                           198

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i.  Ground Water Contamination




     Improper disposal of toxic contaminants will result in  releases of such contaminants




into  the environmental media,  including  ground water.  Although  the concentration  of




2,3,7,8-TCDD in many wastes  is very small, it is possible  that leachate being generated




from the 2,3,7,8-TCDD-containing landfill site can contain  the contaminant and enter the




ground water.   The  amount of leachate generation  and  the extent  of  ground  water




contamination  will  be dependent on  many site-specific characteristics, such as  the nature




of the  waste,  the  magnitude of precipitation, and  the transport characteristics  of the




ground water media.



      As precipitation  falls on the ground, the water will penetrate the  surface  of the soil




to form leachate.   Precipitation includes all  forms  of water deposited on  the  earth's




surface, including  mist,  rain,  hail,  sleet, and snow.   Precipitation will become  either




infiltration or surface runoff,  or will return  to the  atmosphere by evapotranspiration.




That portion of the precipitation that infiltrates will affect leachate formation and reach




ground water.  The  amount of infiltration is  affected by  many factors.  These include




thickness of the saturated layer,  moisture content of the soil, magnitude of compaction,




macrostructure of  soil,  vegetative  cover, temperature,  freezing of soil  moisture,  and




entrapped  air.




      When the infiltrated water reaches ground water, the  contaminant will be impacted




by flowing ground water to migrate  downgradient by advection, and will be dispersed by




diffusive and  dispersive  actions,  and  will  be retarded in the  ground water medium,




depending on the adsorptive capacity of the medium.



      Depending on landfill  design,  leachate  may directly enter ground water or may be




subject to retardation by the unsaturated zone before entering ground water.  In order




to assess the extent of migration of 2,3,7,8-TCDD-containing leachate in ground water, a




ground water  fate and  transport model (Hwang,   1986)  is  used.   There  are several






                                           199

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parameters that need to be assumed in using the model.  These parameters, necessary to



estimate the  retardation coefficient, include  ground water velocity,  the concentration  of



the contaminant in leachate,  the  precipitation infiltration rate,  the aquifer depth,  the



porosity of the aquifer, and the organic carbon content of the  ground water medium.



     According  to  Darcy's  law,  ground water  velocity is  a  function  of  hydraulic



conductivity, hydraulic gradient, and effective porosity.  Todd (1980) lists representative



hydraulic conductivities for a variety of geologic materials. Gravel material has hydraulic



conductivities  ranging from  150  to  450  m/d.    Representative   values  of  hydraulic



conductivity  for sandy material are shown  to be between  3 and  45 m/d.   Hydraulic



conductivities for sandstone range from 0.2 to 3 m/d.  The ground water velocity used  in



the model should  be  site specific.   For a  productive alluvial  aquifer with  hydraulic



conductivity  of  100 m/d, a  hydraulic gradient  of  10"^ (which  is within  the  values



commonly observed  in field  conditions  [Freeze  and Cherry, 1979]), and an effective



porosity of 0.2,  the ground  water velocity is calculated to be 5.5 x 10~^ cm/s, which is



used  in the  fate and  transport model.   The  hydraulic conductivity  used  is  within  the



range for sand and gravel.



     The mean  annual precipitation in the  United States ranges from 5 to  100  inches



(Wisler and  Brater, 1959).  The highest  precipitation occurs along the northern Pacific



coast,  where rainfall in excess of  100 inches is not unusual.   A belt of very low  annual



rainfall lies  just east  of the coastal  mountains, where  the rainfall  ranges  from .5  to  10



inches.  Data compiled by Todd (1983) show that a considerable amount of precipitation



is lost  to the atmosphere by the  process of evapotranspiration,  and becomes  surface



runoff.   The portion  of  precipitation  that becomes ground  water  recharge  is generally



less than 10%, and at times is less than 1%.   The infiltration rate is relatively high in



the Lake Tahoe basin  region, amounting to nearly 25% of the precipitation.   However,



this high percentage is an isolated case. As  a typical  worst-case infiltration rate, 15% of






                                           200

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the worst-case precipitation is  assumed  to  become  infiltration in the model  simulation.




This corresponds to an infiltration rate of 1.2 x 10~6 cm/s, averaged on an annual basis.




     The organic carbon  content of the  ground  water aquifer material is  needed  in




estimating  the pollutant  retardation factor.   Typical  values of the organic carbon content




are reported to be from  0.4% to 10.0% (U.S. EPA, 1985f). The report also notes that low




carbon  contents  of  less  than 1% are typical  of those  found  in  deep aquifer materials.




Bedient  et al. (1984), in their  study of ground  water  quality, attributed high  levels  of




organics at a well some  distance from the studied waste pits to the extremely low levels




of organic carbon  in the  aquifer (less  than 0.02%).  Although such an  organic carbon




level  is  considered extremely  low, the use  of this value will  reflect  a conservative




estimate for contamination concentration  because  estimated  retardation factors would




predict  migration farther away from the pit.




      At the  soil organic  carbon-water partition coefficient  of  486,000 cm^/g organic



carbon (Schroy et al.,  1985b), and organic carbon content (OC) = 0.0002 for ground  water




media,  the retardation factor becomes  Rj  =  973,  calculated from R
-------
     The concentrations  in  ground  water  at several  distances  from  the  place  of

contamination are calculated at the  release period of  100 years using the semi-analytical

three:-dimensional area source model (Hwang,  1985, 1986; Codell, 1982).

     The results of these simulations are. tabulated below (Table 6-7).

             TABLE 6-1.  SIMULATED CONCENTRATIONS AT WELLS
               Distance of receptor from.         Concentration in
                 the downgradient edge          ground water (mg/L)
                   of the  source (m)               after 100 years
                        15.2                        2.8 x 10'17
                        50                          2.3 x 10~17
                       152                          8.8 x 10-18
     The results show that the concentrations at the.  locations  of 15.2 m and 152 m

correspond to the exposure levels of 8 x 10"^ and 3 x 10"'^, ng/kg-d (risks of

2  x 10~13  and  9 x  10"14  at  the potency slope of  0.156  (ng/kg d)~J,  respectively.

Although the ground water has traveled, about  1.7 x  10^ m of distance over a 100-year

period,  the  plume concentrations at all  locations  are  relatively  small,  according to the

simulation.   This  is principally due to the  high retardation  factor for the contaminant,

which of course is related to the hydrophobia nature of 2,3,7,8-TCDD.

     This simulation indicates that because of very high retardation of  2,3,7,8-TCDD by

the ground  water media, the concentration in ground  water  will  be small, and ground

water is not  a  significant  exposure pathway for 2,3,7,8-TCDD  migrating from landfill

sites.    However,  as  noted  earlier,  if  cosolvents  are  present  in the  landfill or  if

channeling occurs, the mobility of 2,3,7,8-TCDD may be significantly increased.  This, is

an  especially important caution when applying the  methods  of this  report  to landfill

situations at actual sites.  Although the  solubility of 2,3,7,8-TCDD would probably not

increase enough  in a  one-phase system  (i.e., dissolving  in benzene-saturated water) to


                                           202

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make it extremely mobile, where two separate phases  are present (e.g., organic  solvents

present at  well over  saturation levels), the 2,3,7,8-TCDD may behave quite differently.

Evaluating the potential  for ground  water contamination at any  site must  include an

analysis of the cosolvent status.

j.  Fruit and Vegetable Ingestion

     The literature reviewed in Section 3.D. showed plant-to-soil ratios varying from

< 0.1% to  > 100%.   The most recent data (Sacchi et al., 1986) show  an uptake ratio of

about  2% for above-ground  plants (beans and maize).  Cocucci et al. (1979) found ratios

of  about  100%  in below-ground vegetables.   However,  these tests  were  conducted on

plants exposed to 2,3,7,8-TCDD during the Seveso  incident, which may not reflect normal

exposure conditions.   Greenhouse tests briefly reported by Wipf et al. (1982)  indicate a

ratio of between 1% and  1.5% for  underground vegetables (carrots).  For purposes of a

preliminary estimate, a 2% ratio was assumed to apply to all vegetables  and fruit.

     The  average daily ingestion  rate of  fruits  and  vegetables  is  280 g/d (U.S. EPA,

1984c).  The U.S. Department of Agriculture (1986) reported that  approximately 50% of

vegetables  eaten  in rural  farming  areas are home-grown.   This value was assumed to

represent  the portion  of a person's  vegetable diet  derived from the contaminated source.

Fries and Marrow (1975) found that about 50% of the 2,3,7,8-TCDD was absorbed by rats

from feed.  This value was assumed to represent the absorption occurring in humans from

vegetables.  Finally,  assuming 1 ppb 2,3,7,8-TCDD in the garden soil and 55% absorption,

the 70-year risk can be calculated as:

                            (plant             (soil
               (ingestion  uptake  (fraction    concen-   (cancer
    Risk =         rate)   ratiol home-grown) tration)   potency)          (6-29)
                                     (body weight)

                    « (280 e/d) (0.02) (0.5) (1 ng/g) (0.156 kg-d/ne)
                                             70 kg
                      6 x 10
                            -3
                                           203

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Such  risk estimates are linearly proportional to the soil concentration.  If th& soil level

were  1 ppt, the risk estimate would be reduced, to 6 x 10"^.

     Several points should be considered in evaluating, the above calculation:

     o    2% uptake  is much  less than, uptake levels  measured  by several investigators

          (as noted  above these  were  rejected  because  they  were  based on either
                                                            s
          non-edible   portions  of the  plant  or  derived  from studies   conducted  in

          connection with the;Seveso incident).

     o    Only one  study  (Wipf  et al.,  1982)  was   found  which  actually  measured

          2,3,7,8-TCDD levels in fruit itself (fruit is used here in the technical

          sense to refer to  plant  parts  consisting  of  the  seed  and  surrounding, pulpy

          tissue, which would include corn, tomatoes, grain, etc.) Wipf et  al., report that

          the  levels  of TCDD (unspecified isomers) in the edible  portions of apples,

          pears, peaches,  corn and  other  fruit were  less  than the  detection  limit  of

          about 1  ppt compared to about 10,000 ppt in the soil.  The Wipf study would

          suggest  that the  2% uptake  assumption  over-estimates  the   risk,  of fruit

          ingestion.

     o    Two  studies (Young, 1983 and Sacchi, 1986) did find substantial  uptake

          levels in the aerial portions of plants.   It is  unclear  whether this contradicts

          the  findings of Wipf  et  al.,  1982, or  whether it is  reasonable to  expect

          different levels in the fruit, than the other aerial, portions of the. plant.

     o    The  literature does  generally suggest  that   higher  uptake  levels have been

          observed  in underground  plant  parts  than   above-ground,  plant parts-   The

          logical conclusion that this implies, is, if data, were available, risks should  be

          calculated, in a way  which distinguishes between underground and above ground

          vegetables,  rather than using an across-the.-board  uptake value such as. 2%.  As

          an example  of the influence which this  consideration  could make, an  estimate



                                           204

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          of the  possible risk associated  with potato ingestion was  made.   Only one



          study  (Cocucci et  al.,  1979)  examined  uptake  in  potatoes  where  it  was




          estimated as about 40%.  As noted earlier, it is  unclear if Coccuci  results are




          applicable to normal gardening scenarios, but for  purposes of this example it is




          assumed to  be applicable.  The  average ingestion rate of potatoes is about 13




          g/d - excluding french fries and potato chips (Pennington, 1983).  Using these




          parameter values and the same values for the other parameters as were  used in




          the above  calculation,  the  risk  associated with  potato ingestion is  6 x  10"^.




          Coincidentally, this risk  level  is equal to the risk calculated earlier  (using the




          2% value)  for all   fruits and vegetables.   This  suggests  that   using  this




          approach (i.e.,  the uptake  values  from  the  Coccuci   paper applied  to




          underground portions of plants) would lead to much higher estimates  of  risk.




     Due to the high degree of uncertainty associated with this pathway, the exposures




were not presented in Table 6-6  or in the Appendix.  However, if they were computed




using a 2% uptake as shown above and  not making any distinction between typical and




worst  case  behavior  patterns,  the upper  bound incremental risks associated with the




various scenarios would be as follow.  For scenarios 1, 2,  5, 8, 9 and  12  where  the soil




level is 1 ppb the  risk is 6  x  lO"-'.  For scenarios 3, 6, 10 and  13  where  the  soils levels




is  1  ppt the risk is 6  x 10"^.  For scenarios  4,  7,  11 and 14  where the  soil level is 1



ppq  the risk is  6  x 10"9.  For  scenarios  8,9,10, and 11, the  risks for  the  population




living  100 feet  away  from  the site would  be  further reduced  by  a  factor of 0.35, the




dilution  factor.   For  scenarios 12, 13, and 14, the 2,3,7,8-TCDD  concentration at the




population area 500 feet away from the combination  site  is diluted by 0.008 from the




original  concentration.  Hence, the risks would also be reduced by 0.008.  Finally, for




scenario 15 the risk would be negligible since this involves  a capped landfill which would
                                           205

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prevent 2,3,7,8-TCDD exposure to the plants (assuming the cap is  thicker than the root



depth and remains clean).



C.  DESCRIPTION OF EXPOSURE SCENARIOS FOR INCINERATION



     A broad spectrum of combustion devices have been tested to determine the presence



of  polychlorinated dibenzo-p-dioxins (PCDD)  in  flue  gas and ash.  2,3,7,8-TCDD is



suspected of being formed as a low-level by-product  in  the  process of burning many



types of waste  or fuel  material.   The  combustion devices where  literature  test results



showed presence of 2,3,7,8-TCDD or PCDD  in flue gas or ash include  municipal waste



incinerators,  coal-fired utility boilers, wood stoves and fireplaces, hazardous and chemical



waste incinerators, and the internal combustion  engine.  Recent reports compiled by U.S.



EPA  (1986)  also list  other combustion devices  such  as  smelters,   sewage  sludge



incinerators,  wire reclamation incinerators, and drum and  barrel furnaces.  In  addition,



Sheffield (1985) mentions  forest fires and several types of chemical production facilities



as sources.  Des Rosier  and Lee (1986) cite PCB transformer fires as a potential source



of 2,3,7,8-TCDD formation.   Buser (1979) notes formation of dioxins from the laboratory



pyrolysis of chlorobenzenes.   It should be noted that the main  focus of this section is to



address the potential of health risk associated with the emissions of 2,3,7,8-TCDD and fly



ash generated from the incineration of municipal waste.  Municipal incinerators were used



in  the  example  scenarios since there are emissions data  available and these  types of



incinerators are  currently of interest.



     The available  literature  information  on  emission tests  shows  that 2,3,7,8-TCDD



emissions released into  the atmosphere consist of  vapors and particulate  matter, and that



fly  ash  collected  in   air  pollution  control  equipment  contains  some  amount  of



2,3,7,8-TCDD.  Although the exact ratio of vapor to particulate 2,3,7,8-TCDD  emissions



has  not been  systematically  studied,  the mere presence  of the  two-phase releases



complicates the  multimedia exposure analysis.  There is an indication that the long-range






                                          206

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transport of 2,3,7,8-TCDD favors the presence of 2,3,7,8-TCDD in the vapor phase (Eitzer




and Hites,  1986).




     The vapor-form stack emissions  will disperse  in the air as will the  particulate-form




stack  emissions.  Exposure to humans  results from inhalation of 2,3,7,8-TCDD vapors and




particulates,  ingestion of contaminated water, fish,  soil,  homegrown food, and  dermal




contact.




     Ash is produced from  non-combustible material as bottom ash,  which is also referred




to as  residue, and  from the remains  of the refuse or fuel after burning as  airborne fly




ash which  is collected in paniculate control equipment.  The bottom ash produced from a




high temperature oxidation  process is commonly referred to as slag.  Some incinerators




operate at  sufficiently  high temperatures  to  produce slag.   Not all incinerators produce




slag.  Many  newer hazardous  waste incinerators operate at slagging temperatures.  Most




existing  hazardous  waste   incinerators  do  not.    Very  few,  if any, municipal  waste




incinerators  operate  at slagging  temperatures.  One  paper  reports  the  bottom  residue




produced  from  a municipal mass burning  incinerator  as slag (Nottrodt,  1986).  Nottrodt




(1986) and Hay et  al. (1986) indicate  that the total CDD in  bottom  ash slag is  negligible.




However,  MRI (1985) reports levels  of 2,3,7,8-TCDD in bottom  as high as  1.5 ng/g.




Actually,  bottom ash as used  in  the  MRI  report refer to a combination  of  both  bottom




and fly ash, so  it  is not clear how much 2,3,7,8-TCDD  is  actually  present in the  real




bottom ash.   Due to  this  uncertainty and  the fact  that  fly ash  is clearly  of  greater




concern, the risk from slag is not addressed  further in this  report.  Land disposal of the




collected fly ash in a landfill is covered in the incinerator scenarios discussed later.




     There are  basically three types of incinerators used to  incinerate municipal  wastes:




mass  burn,  modular,  and  refuse  derived fuel (RDF) incinerators.   The  mass  burn




incinerators  predominate.    Mass  burn incinerators  are field-erected and  can  process




municipal waste without major preprocessing steps except removing  large items  which will






                                           207

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not .go  through the feed system.  These incinerators can  range in  size from  50 to  3000




tons per day (TPD) of waste input (Radian Corporation, 1986).  Modular  incinerators are




package units  and  can  range in size from 5 to  100 TPD.   The 'refuse-derived fuel




incinerators process wastes to produce  refuse derived fuel and  combust the RDF in a




waterwell boiler.




1.  Summary of Incineration Scenarios




     Four scenarios for  municipal waste incinerators are described  here and apply to the




calculations in the  remainder  of the chapter.  Two of the  scenarios  (16 and  17) deal with




population habits which involve cultivation of some farm products  with a stagnant pond




in the  area which  may  be used for stocking fish or for  other  purposes.  This scenario




•may represent  a reasonable-worst  case for some population.  The other two scenarios (18




and 19) use habits which also involve obtaining some farm products  from the impact "area,




but  have a flowing stream in the  area so  that  flowing  water may have  an affect  of




diluting soil and water  contamination in the stream.   This scenario may represent more




typical  for some population at large.  Of the four scenarios,  two (16 and  18) deal with a




large (3000 TPD capacity) incinerator, while the  other  two (17  and 19) deal with  a




smaller  120  TPD  facility.   The major assumptions  for the  incinerator  facilities  are




summarized  in Table 6-8, while the  major assumptions  about  population  habits  are




summarized in Table 6-9.




     The scenarios themselves describe  a  hypothetical family  living near a municipal



waste incinerator.   The incinerators used in this analysis are  modeled after  an existing




facility in Hampton Roads, Virginia and planned facility in Tampa, Florida. Buildings at




the Hampton Roads incinerator cause downwash effects  which cause  the modeled maximum




concentrations   from  emission  to  occur at  200  m  from the  incinerator.   Since  the




hypothetical family is assumed to live on a  small farm it is  unreasonable to expect them




to be located in the urban area where the ground level concentrations are maximum.






                                           208

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      TABLE 6-8.  PARAMETER VALUES FOR INCINERATOR FACILITIES
                      IN FACILITIES IN SCENARIOS 16-19

Capacity (TPD)
Heat Value of Waste (BTU/lb.)
Height of Buildings (m)
Controlled Emission Factor
for 2,3,7,8-TCDD (jig/kg)
Emission Rate for 2,3,7,8-TCDD
(g/s)
Vapor Form Emission Rate(g/s)
Particulate Form Emission Rate
(g/s)
Stack Parameters:
No. of Stacks
Height (m)
Diameter (m)
Gas Temperaturerature (°K)
Gas Velocity (m/s)
16
3000
4815
42
0.001
3xlO~8
1.9xlO~8
l.lxlO"8

4
46a
4.lb
470
11.3
Scenarios
17
120
4815
27.3
0.289
1.8xlQ-7a
l.lxlO-7a
0.7xlQ-7a

2
27.4a
1.2a
543
12
18
3000
4815
42
0.001
3xlO-8
1.9X10'8
l.lxlO'8

4
46a
4.1b
470
11.3
19
120
4815
27.3
0.289
1.8xlO-7a
l.lxlQ-7a
0.7xlO-7a

2
27.4a
1.2a
543
12
aEach stack.

''Note that a heat balance calculation indicates that the amount of combustion gas generated
requires four stacks each with a 4.1 m diameter to maintain the assumed stack gas velocity.
                                        209

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                    TABLE 6-9.  PARAMETER VALUES FOR
                      POPULATIONS IN SCENARIOS 16-19
   Parameter              Scenarios 16 & 17         Scenarios 18 & 19


Distance to Exposure              .8                           .8
Area (km)

Years at residence                 70                           40

% time at residence                80                           50

% freshwater fish
from contaminated
source                           10                           10

% beef diet from
contaminated source a              44                           44

% dairy diet from
contaminated source a              40                           40

Ages for soil ingestion             2-6                         2-6


a Average percent of annual consumption which is home grown by
  900 rural farm households (U. S. Department of Agriculture, 1966).
                                        210

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                              Figure 6-4. Incinerator Scenarios
 Scenarios: 16,17 (Reasonable Worst Case)
O
     Incinerator
0.8 Km
                      Exposure
                        Area
 Scenarios: 18,19 (Typical Case)
    Incinerator
                                        0.8 Km
                                                              /\   / f  Stream
                       Exposure
                       Area
                                          211

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The  nearest distance where a small farm  could  be located  was assumed  to be about 0.5



miles from  the  incinerator; for this  reason, the hypothetical  family  is located 0.5  miles



(0.8 km) from the incinerator.  Figure 6-4  is a schematic of  the scenarios.



2. General Calculations and Factors Used



     Since stack emissions are  not covered in  the  methods  discussed in Chapters  2-5,



which deal  essentially with  land-based   material,  some  background  information on



municipal incinerators  and emission  transport are  briefly described below.  This section



discusses  the selected  values (see Table  6-8) for  size  and  emission  factor for  the



incinerator facilities  in scenarios 16-19 from the  perspective of what is  known about



existing facilities in  general.  In addition, the methods used to  calculate concentrations



a. Summary of  Emissions  Data and Vapor/Particulate Distribution



     In 1977 researchers in the  Netherlands reported that CDDs are found in fly ash and



flue  gas  of municipal incinerators (Olie et al., 1977 ).  These  findings led Dow Chemical



Company to issue a  report suggesting the widespread presence  of CDDs in emissions  from



various combustion  devices  (Bumb et al., 1980).    The  sources listed by Dow  include



hazardous  waste  incinerators,  municipal waste   incinerators,  industrial  boilers,  and



fireplaces.   Since  the  issuance  of  this  report,  many  researchers  have  begun  to



characterize the nature  and amount of CDD compounds which can be  present in flue gas,



fly ash, and slag.  The  results of these studies are briefly summarized in Tables



6-10   through 6-12.  Since the  major emphasis of this  report is to assess the exposure to



2,3,7,8-TCDD, the summary presented is not inclusive of all literature  information dealing



with  the analysis of other types of CDDs.   Many  references  which  do not  contain



specific analyses for 2,3,7,8-TCDD are omitted from the summary table.
                                           212

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     In attempting to quantify the presence of CDD  emissions in flue gas, researchers




primarily  analyzed fly ash emissions.  Although some papers measured the  vapor phase




CDDs  in flue gas as  well as in the particulate phase, most literature does not distinguish




between the two.




     In several emission tests, the levels of 2,3,7,8-TCDD in the  gas  phase  were higher




than those measured  on  captured  particulate matter (Hagenmaier et al., 1986; Nielsen, et




al., 1986;  Scheidle et  al., 1985; EPA 1987b).  In one study testing a municipal incinerator,




virtually all CDD emissions in the stack were in the gas phase (EPA 1987b).




     More recently,  Midwest  Research  Institute under contract to EPA  summarized  an




emission data base for stack test results conducted  in U.S.A. and Canada (EPA  1987c).




The results show analyses of various congeners of dioxins in stack emissions, but there is




no  indication as  to what proportion is  particulate vs.  vapor form.   Knowledge of the




relative amounts  of particulates  and  vapors in stack  emissions is  important because




vapors will behave differently from particulates in the environment.




     Table 6-10 lists a collection of data showing emissions of 2,3,7,8-TCDD in the stack




gas of municipal  waste  incinerators.  For emissions  other than those  for 2,3,7,8-TCDD,




there is a more complete data base compiled for U.S.  EPA (Radian Corp.,  1983; U.S.



EPA,  1986;  U.S.  EPA,  1987).   Many  data  in the  literature are given  in  terms  of



concentration in stack gas, commonly in nanograms per normal cubic meter (ng/Nm^).  To




provide the  data  in  consistent units, these data are converted to  emission  factors given




in ug of contaminant emission  per kg of refuse burned.




     This conversion is difficult because many papers do not provide process data, and %




CC«2 in the  stack emissions  necessary for such  a  conversion.  For  example,  the  stack




flow rate  data corrected to  12% CC>2 is  presented in units of dry standard cubic feet per




minute, or dscfm, and the concentration of 2,3,7,8-TCDD in stack emissions  is given in
                                           213

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TABLE 6-10. STACK EMISSIONS OF PCDDS
    FROM MUNICIPAL INCINERATORS

              Emissions Factor( jig/kg)
2.3,7,8-TCDD Total TCDD PCDD H6CDD H7CDD OCDD Total
Dioxins
0.001-0.0034 0.055-0.24 0.005-0.024 0.016-0.085 0.03-0.14 NR
Av = 0.002 Av = 0.11 Av = 0.013 Av = 0.04 0.07
0.015-0.038* 0.27-0.36* 0.3-5.2* 0.46-2.5* 0.59-2.7* 1.3-2.7*
Av=0.0265
NR 72.8* 107.1* 132.8* 98.6* 17.1* 428.
0.0007-0.01 0.01-0.07 0.25-0.29 0.21-0.37 0.14-0.8 0.48
Av = 0.005

0.0003-0.004 0.022-0.14 NRS NRS NRS 0.022-0.27
Av = 0.002
0.0006-0.003 0.012-0.028 0.002-0.005 0.008-0.02 NR 0.022-0.08
Av = 0.002
NR 0.031-0.3 NR NR NR NR
NR 0.22 0.33 0.72 0.91 1.76
0.015 0.043 NR NR NR NR
0.021 0.045 NR NR NR NR
	 0.38 1.6 2.9 2.3 3
NR 0.14-0.94 0.28-0.72 0.77-2.1 1.05-2.5 0.9-2.04
0.002 0.032 ND 0.082 0.038 0.013 0.167

Remark
Participate 37%
Vapor 63%
ESP Control
Starved Air
No control
Before Control
20-30% parti-
culate 70-80%
vapor
Literature
Survey
ESP & Wet
Scrubber
ESP Control
Particulate 37%
Vapor 63%
Av of 4 samples
Av of 3 samples

Sample Before
Control
Found in gas
None in ash
fContinued 	
Reference
Hagenmaier, et
al., 1986, EQV
DeFre'. 1986,
EQV
Hay et al.,
1986
Nielsen et
al., 1986.EQV

Nottrodt,
1986
Nottrodt, 1986,
EQV
Rappe, 1986
Scheidl et
al., 1985
EPA 1987b
EPA 1987b
EPA 1987b
Kilgroe et al
1986
EPA 1987b
EQV
)
                     214

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                                              TABLE 6-10.  (CONTINUED)
2,3,7,8-TCDD Total TCDD   PCDD    H6CDD    H7CDD      OCDD    Total Dioxins       Remark       Reference
0.0021*       0.0316*
         0.0824*    0.0383*       0.0128*
                                                                                           ESP Control   MRI, 1987
                                                                                           Chicago
              3.02
3.84*      6.05*      7.32*         1.93*     22.1*
                                                                                           ESP Control   MRI, 1987
                                                                                           Hampton (1981)
0.289*         1.13*
                                                              ESP Control   MRI, 1987
                                                              Hampton (1982)
0.145
               1.04
                             5.44*     2.32*      0.726*        0.186*    9.68*
                                                              ESP Control   MRI, 1987
                                                              Hampton (1983)EQV
0.089*        2.93*          6.86*     8.09*      7.31*         1.87*     27*
                                                              ESP Control   MRI, 1987
                                                              Hampton (1984)EQV
0.00117*      0.0118*        0.0117*   0.016*     0.023*        0.037*    0.966*
                                                              ESP Control   MRI, 1987
                                                              Peekskill      EQV
0.000397*     0.00634*       0.0117*   0.02*      0.0174*       0.0189*   0.0745*
                                                              ESP Control   MRI, 1987
                                                              Tulsa (Units   EQV
                                                              1&2)
0.000371*     0.000893*      0.000243* 0.000504*  0.000842*    0.0027*   0.00517*
                                                              Fabric Filter   MRI, 1987
                                                              Marion County EQV
0.000056*     0.000621*      0.00827*  0.0104*    0.0141*       0.0339*   0.0727*
                                                              Fabric Filter   MRI, 1987
                                                              Wurzburg     EQV
0.069
               1.9
                             5.3       13.8       4.53
                                                              1.8       26.85
                                                              ESP          MRI, 1987
                                                              Philadelphia   EQV
                                                              (NWI)
0.062
               1.8
                             5.2       4.6        2
                                                              0.83      14.05
                                                              ESP          MRI, 1987
                                                              Philadelphia   EQV
                                                              (NW2)
0.0206
                                                                                           Cyclone
                                                                                           Mayport
NR           AV=0.013*    0.038*    0.0663*   0.1085*       0.167*    0.393*
                                                              Before Control  MRI, 1987
                                                              Prince Edward EQV
                                                              Island
NR = Not Reported, NRS = Not Reported Separately, ND = Not Detected
EQV = Data used in calculating weight percent adjusted to equivalent 2.3.7.8-TCDD.
                            9                             O                                          +
All Data Converted from ng/m to ug/kg by assuming 6000 Nm /T of refuse burned unless otherwise noted by .
                                                              215

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           TABLE 6-11.
PCDDS IN FLY ASH OF COMBUSTION

Source 2,3,7,8-
Categpry TCDD
MWI 0.07-0.1
MWI
MWI
MWI
MWI
MWI
Ontario
Oslo
Paris
Kyoto
Hiroshima.
Manchida
WBS
WBS
MWI 2.3
MWI 0.29
MWI
MWI

Concentration (ng/g)
Total
TCDD PCDD H6CDD H7CDD OCDD
0.9-1.6 0.3-0.5 3.2-9 42-215
<20ppt
0.15 for all dioxin homelogue
No dioxin in bottom ash
47 145 417 781 1861
436 504 668
27 77 149
18 50 142
8 17 38
29 95 149
0.2 0.8 4
ND ND-0.5 ND-1.7 0.1-0.5 0.2-0.4
ND-0.8 ND-4.2 ND-10 0.3-11 0.1-10
67.5 NR 350 1040 650
6.1 NR NR NR 160
+ + + + +
ND-1.5 ND-2.7 ND-26 2-87 6.5-330


Remark Reference
ESP control Nottrodt, 1986,
wet Scrubber EQV
Slag Nottrodt, 1986
No control Hay, 1986
Starved Air
Hay, 1986
Scheidl et al., 1985
Tong & Karasek, 1986





Chimney Ash Clement et al., 1985
Bottom Ash Clement et al., 1985
Lamparski, 1980 EQV
Cavallaro, 1980
Olie et al., 1977
* Tosine et al., 1985
fContinued 	 }
                216

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                                       TABLE 6-11.   (CONTINUED)

                              DIOXINS  IN  FLY ASH OF COMBUSTION DEVICES
Concentration (ng/g)
Source
Category
HWI
MWI
MWI
MWI
MWI
2,3,7,8-
TCDD
ND-110
0.4
0.065
0.14
100
Total
TCDD PCDD
3300-12000 NR
7.7 NR
1.12 NR
2.74 NR
NR NR
H6CDD
1300-5600
14
NR
NR
NR
H7CDD OCDD Remark Reference
2000-37000 3000-59000 Rotary Kiln ADL 1981, Bumb,
1980, Crummett, 1982
28 30 "
NR 35.5 Cavallaro, 198
NR 0.6
NR NR Single Test Ahling, 1982
                                                                              Pyrolysis
HWI
MWI
MWI
MWI
MWI
1.2-2.5      2-2
NR
NR
NR
NR
 Dioxin Work
Group, 1981
              5.2       273.8      555
                                              608.8      169.4
              1.4        91.5       346.7        334
                                                        192.6
   0.74       23.6
              0.1
                         2.9
                                   46.3
                                     8.3
            27.8       11.7
                                                9.3        5.9
                       37.3      NW Unite      MRI, 1985
                                Fly Ash

                      174       EC Units      MRI, 1985
                                Fly Ash

                       10.7      NW Units      MRI, 1985
                                Bottom Ash

                        8       EC Units      MRI, 1985
                                Bottom Ash
MWI: Municipal Waste Incinerator
WBS: Wood Burning Stove
HWI: Hazardous Waste Incinerator
+  :   Present
ND : Not Detected
FA : Fly Ash
* : This is an analysis of municipal waste, not fly ash
NR:  Not Reported
EQV: Data used in calculating the weight percent adjusted to equivalent 2,3,7,8-TCDD
    Bottom Ash:  Operationally combined fly ash and bottom ash from MWI.
                                                      217

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                  TABLE 6-12.  EMISSIONS OF CDDS FROM COMBUSTION
                                 DEVICES OTHER THAN MWI
Emission Factor (/ig/kg)
Source 2,3,7,8- Total
Category TCDD TCDD
Boiler NR 0.1
Boiler NR 0.13
245T NR <100-3000
IWI <0.0006
IB (coal) 0.2 0.69
IB(RDF) 0.11 0.36
IB(coal) 2 5.8
IB(RDF) 1.3 3.7
HWI 1.
UB(coal) NR ND
PCDD HgCDD H7CDD OCDD Remark Reference
0.69 0.37 0.5 0.07 RDF -only Hahn, et al., 1986
1.28 1.28 1.06 0.13 RDF-NG Hahn, et al., 1986
<300-1200 <200-2000 <200-300 <200-1400 * Ahling, 1977
<0.0006 <0.0008 <0.0006 <0.0006 Brenner et al., 1986
NR NR NR NR U.S. EPA, 1987b
NR NR NR NR U.S. EPA, 1987b
NR NR NR NR U.S. EPA, 1987b
NR NR NR NR U.S. EPA, 1987b

ND ND ND ND U.S.EPA, 1986
RDF: Refuse-Derived Fuel, 245T:  Combustion of 2,4,5-T Formulation
NG: Natural Gas
NR: Not Reported
   * :   emission factor in /ig/kg of 2,4,5-T formulation combusted
IWI:  Industrial Waste Incineration,
HWI: Hazardous Waste Incinerator
IB:  Industrial Boiler
UB:  Utility Boiler
ND:  Not detected
                                                 218

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grains/dscf, then the conversion of the concentration data to an emission factor, EF, in

/ig/kg can be done as follows:

                                   (% of CO2VStack gas flow rate in dscfm)
   EF(/ig/kg) = (gr/dscf)  1.43xlO~9 Refuse process rate ton/hr                (6-30)
      The concentration and emission  factors can be expressed in many different units.

In this  case, appropriate conversions were necessary  to present the data on a consistent

basis.

     In the absence of information on the relation between the flue gas generation rate

and  process weight rate, an average value of  5000 Nm^ flue gas per ton of  refuse burned

was  used, since existing data from European and American test results show that the gas

generation rate ranges from 4000 Nm^  to 6000  Nm^ per ton of  refuse  burned.   The

emission factor for 2,3,7,8-TCDD ranges from 0.002 - 0.289 /*g/kg.  Emission factors for

other CDD compounds, as  well as  available information on  use of particulate control

devices are shown in Table 6-10.

     Data concerning  the analysis of 2,3,7,8-TCDD and other CDD compounds in fly ash

collected  by air pollution  control devices are tabulated  in  Table 6-11.   Fly  ash  from

municipal incinerators and other combustion devices is also included in the table.

     For  municipal waste incinerators, the levels of  2,3,7,8-TCDD in fly  ash  emissions

collected in control equipment range from 0.065  - 5.2 ng/g with an average value of 1.3

ng/g.  The  Swedish experiment (Ahling  and  Lindskog, 1982) showing the 2,3,7,8-TCDD

level of 100  ng/g  was excluded in the averaging  process, since it is an unexplained

outlier.

     Table 6-12 summarizes emission factors  for combustion devices other than municipal

waste incinerators.   Very few data  are available  for 2,3,7,8-TCDD emissions from  other

combustion  devices.   Since test results  are  presented  in  the  literature on a weight or

volume basis,  it is difficult to convert the literature information to an emission factor.

                                           219

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Additional data are available for CDD emissions from modular starved-air and RDF-fired



municipal waste facilities (MRI, 1987) and from incineration devices other than municipal



waste combustors (U.S. EPA, 1986).



     There  are  virtually no  data  concerning the division of 2,3,7,8-TCDD emissions



between  the vapor and  particulate phases for stack emissions in the U.S.A.   There are



three European studies  analyzing  the  vapor and  particulate phase  emissions  from  a



municipal waste incinerator (Hagenmaier, et al., 1985; Nielsen, et al., 1986; Scheidl, et al.,



1985).  Nielsen et al.,  (1986) states that  the reported  distribution of  CDDs and CDFs



between  particulate and vapor phases in flue gases  varies  widely,  but it  is generally



recognized that an  average of 20-30% is in the particulate  phase, while 70-80% is in the



gas phase.   For our scenarios we assumed 63% to be  in the vapor phase and  37%



particulate,  since these  values  are reported in two studies  (Hagenmaier et al., 1985 and



Scheidl et al., 1985).



     In scenarios 16 and 18 the refuse rate of 3000 TPD corresponds to 2.7  x 106 kg/d.



Since downtime  will  be  required  for maintenance  and  repair, the  incineration rate



represents an average value over the time period of consideration.   At this  average rate



of refuse combustion, the emission rate of 2,3,7,8-TCDD is  0.001 ug/kg (2.7 x 10^ kg/d) =



2700  A*g/d, or 3 x 10~° g/s [see Table 6-8].  This emission  is assumed to consist of about



37% particulate  form and 63% vapor form (Hagenmaier et al., 1985; Scheidl et al., 1985;



Nielsen et al., 1986). Vapor emissions of 2,3,7,8-TCDD are  then 1.9 x 10~8 g/s and the



particulate emissions are 1.1 x  10~°  g/s.  Similar calculations can be performed for the



120 TPD plant in scenarios 17 and  19.  Since emissions are assumed to be discharged into



the atmosphere  from two stacks, each stack  emits a total  amount of 2,3,7,8-TCDD at a



rate of  1.8 x 10~7 g/s  as  shown  previously [see Table 6-8].   The emission  from each



stack will consist  of 1.1 x 10~7 g/s  of  2,3,7,8-TCDD as vapor and  0.7 x  10~7 g/s of



2,3,7,8-TCDD as particulate.






                                           220

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b.  Municipal Waste Incinerator Capacities in the U. S.




     There are currently a total of 45 mass burn  facilities, 56 modular incinerators, and




10 RDF incinerators in  the U.S., with a combined incineration capacity of about 49,000




tons  per day (TPD).  The mass  burn facilities make up  about 68 percent of  the  total




incineration capacity at  present, with modular incinerators making up about nine percent




and RDF facilities 23 percent.  There are a few  existing mass burn  incinerators with a




capacity as high as  3000 TPD.  Typical air emissions control  is electrostatic precipitation




which removes primarily particulate matter (Radian Corporation, 1986).




     There are 210  proposed, planned, or partly constructed municipal waste incinerators




with a  total combined capacity of about 193,000  TPD (Radian Corporation,  1986).  Of




these,  118 are  mass  burn  facilities,  24  are  modular  incinerators,  and  31 are  RDF



facilities.  The planned mass burn facilities range in capacity from 100 TPD to several




large incinerators  with capacities in the neighborhood of 3000 TPD.   Most plan either




ESPs or baghouses to control particulate emissions  (Radian Corporation,  1986), with many




of the  planned  facilities including dry scrubbers to reduce emissions  of  acid  gases



according to state and local air pollution regulations.




     Mass burn  incinerators are  being designed  and built  with and without energy




recovery.  Energy  recovery involves producing steam which  in turn  is used  to  produce




energy.   Steam  production at  a controled  rate is  an important consideration  for system




operation in planned facilities.  Modular units are starved-air, two-stage  systems where




waste is first  in contact  with lean air followed by completion of combustion.  Although




the capacity of a single  modular unit may  be limited to less than  100  TPD, a facility can




process  waste  in excess  100 TPD by operating two or more of these units simultaneously.




Energy  recovery steam plants require cooling towers, where steam plumes formed by large




amounts of water vapor  evaporated from these towers may interfere with the dispersion
                                           221

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characteristics of the incinerator plumes.  It would be worthwhile to consider  this effect

on dispersion characteristics of incineration emission.

     The scenarios in this chapter use two mass burn  facilities, one large one (3000 TPD)

and a smaller one  (120 TPD).

c. Air Dispersion Modeling

     The estimation of  ambient air concentrations  resulting from the  2,3,7,8-TCDD

emissions requires dispersion modeling.  Dispersion modeling involves the elevation of the

virtual origin obtained by adding the plume rise  (Ah) to the actual  stack height (hs).

The  effective stack height (H) is then H =  Ah + hs.  There are numerous methods for

calculating   Ah.   It is not unusual  to  get  the  spread in the answers  for  Ah using

different equations.  The Holland  and Briggs equations take the forms  of (Wark  and

Warner,  1981):




          h = (Vsd/u)[1.5 + 0.0096 (Qh/Vsd)J (Holland)                      (6-31)

               JJUKQQ1/3
          h  =    u               (Briggs)                                 (6-32)


where Vs = stack gas speed, d = stack diameter, Qj, =  heat emission rate associated with

stack gas, u = wind speed,




      K =  1.58 - 41.4 (dtf/dz)                                              (6-33)




where dd/dz is  the potential temperature gradient,




      F  = g Vs d2(Ts - Ta)/4 Ta                                          (6-34)
                                           222

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where  Ts,  Ta =  stack and ambient air temperatures,  respectively.   To apply the Briggs




equation for Ah, the stability class must  be known.   For neutral stability or d0/dz = 0,




the Briggs  equation  provides the plume  rise  Ah =  242 m for the 3000 TPD  facility




scenarios.   Hence the effective  stack  height can  be H = 46 +  242 =  288 m.  Such an




effective height is applicable to  a flat terrain with no precipitation assumed.  For all the




scenarios  under  consideration, however,  the heights of  the buildings are as tall as the




stack heights,  which triggers the building downwash effects in the  application of the




Industrial Source Complex (ISC)  Model.  An option  available  in an advanced dispersion




model  is the capability to simulate precipitation along with building downwash caused by




a short stack height (EPA, 1986e).  This feature is not available in  the  current ISC.  The




results of sample dispersion modeling  for the scenarios considered  can  be found  in U.S.




EPA (1986e).  The deposition rate of particulate matter and  the ambient air concentration




of various pollutants emitted at  a given rate are given as a function of distance and the




sector  of the area.




     The particle distribution is  needed  to estimate the deposition rate of particulate




matter, because  the  settling velocity  is  a  function  of  particle size and density.   The




particle size distribution  assumed for air  dispersion modeling which incorporates  the dry




and  wet  deposition  is 6.7% for  particles  greater than  10 urn in  diameter,  26.7% for




particles between 2 and  10 /*m  in diameter, and  66.6% for particles  less than 2 nm in



diameter.




     Table  6-13 is an  output of air  dispersion  modeling  for  particulate emissions of



2,3,7,8-TCDD  from the 120 TPD municipal waste incinerator.  The total emission rate of




2,3,7,8-TCDD  (from the  two stacks combined) used  in  the model estimation [see Table




6-8] is  1.3 x 10~7 g/s.   Several case studies were  made to compare  the  results of  the ISC




model  having the option of precipitation and building downwash, with the short-term ISC
                                           223

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                  TABLE 6-13. AIR DISPERSION MODELING OF
                 PARTICULATE-FORM 2,3,7,8-TCDD EMISSIONS
Case No.
1
2
3
4
5
Maximum
deposition rate
Oig/m2.yr)
0.048
0.136
0.168
0.154
0.13
Distance of
maximum
deposition
(m)
200
200
200
200
200
Angle of
maximum case no.
Deposition
225°
360°
280°
180°
180°
(ISCST) model without  the  options (U.S. EPA, 1986e).   The  model  output  results  are

shown for the deposition rate averaged over the days when precipitation occurs (Case 1);

for  the  dry  settling  case  in  which  the yearly deposition  calculated  with  the wet

deposition available in  the  program  removed (Case 2); for  the  deposition  rate with

precipitation and dry  settling occurring according to  the local  meteorological conditions

[assumed  to be southeastern  Virginia] (Case 3); for the deposition rate  obtained from the

short-term ISC model  averaged on an annual basis in which no  precipitation is accounted

for (Case  4); and for the dry deposition rate with wet deposition removed  using the stack

tipdown wash option,  but at the same location where the ISC model calculates in Case 4

(Case 5).  This  analysis  shows that the maximum deposition occurs when both wet and

dry  deposition  are  considered  according to local  meteorological  conditions  (Case  3).

Thus, Case  3 was  used  to estimate dispersion for  both the 120  TPD and  3000  TPD

incinerators.  The actual dispersion modeling utilized site-specific  meteorological data to

estimate the deposition rate and  the ambient air concentrations (U.S. EPA,  1986e).  The
                                          224

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details of the methodology used in treating the wet and dry deposition phenomena can be



found in the literature.



     The deposition  rates  for  particulate-form  2,3,7,8-TCDD  and  the  ambient  air



concentrations of vapor-form and particulate form 2,3,7,8-TCDD in the surrounding area



were  estimated  from  the air dispersion modeling for the distance  where the maximum



deposition and  concentration are likely to  occur, for 0.8 km where the  populations in the



scenarios  are assumed  to be, and for 100 km which is considered relatively removed from



the facility.  The results of computation  corresponding to conditions  with  precipitation



and dry deposition  affected by the local meteorological  conditions are shown in Table



6-14.  No photodegradation or desorption from  fly ash are assumed for the  emissions in



traveling  from  the  stack  exit  to  the  receptor  location.   This assumption  is consistent



with recent experimental observations  by SRI (Mill et al. 1987) under contract to EPA.



The proportion of vapor-form and particulate-form 2,3,7,8-TCDD available for dispersion



in the  ambient  air is  assumed  to  be the  same as  reported for the stack emissions.



2,3,7,8-TCDD  vapor may condense or adsorb onto particulates  as it cools during transport



through the air,  increasing the fraction in the particulate phase.   This  is not expected to



happen, however, since experimental data by Eitzer and  Kites (1986) showed that  all of



2,3,7,8-TCDD  in the ambient air as being present in the vapor-phase fraction collected in



polyurethane foam installed in the back end of the collection train.



     The collection  train used by Eitzer and Hites consisted of high volume filter  paper



with  a pore size of  0.1  /«n, followed  by polyurethane  foam.    Some  speculate  that



2,3,7,8-TCDD  collected on the filter paper  may have been desorbed from particulates by



the high  volume of air passing through and subsequently  absorbed  in the  polyurethane



adsorbent as  vapor.   Others  argue  that,  if  this  is  possible,  desorption  would  have



occurred  in  the ambient air where a large  volume of air surrounds the particulates.  Still



others argue that, since equilibrium is already established  between particulate and vapor





                                           225

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form 2,3,7,8-TCDD in the  ambient air, further .desorption by the same  flowing  air in



.equilibrium would be minimal, and hence most of .2,3,7,8-TCDD is in the vapor phase.



     Tjhe .apparently high fraction of vapor-phase 2,3,7,8-TCDD in the ambient air could



•be  due to .the large volume  of air compared to available paniculate surface area.  As an



example, an ambient  air concentration  of  particulate  matter  at 100 A*8/m^  represents a



paniculate to air volume  ratio of .approximately 1/10  .  An assumption of monolayer



.adsorption of 2,3,7,8-TCDD vapors on  the particulate will further  increase this volume



ratio.  At a partition coefficient of 10^  for distribution between particulates  and air, the



amount of 2,3,7,8-TCDD present in the  vapor phase is larger by a factor of 104. Hence,



this calculation shows  that the percentage of 2,3,7,8-TCDD on particulates at equilibrium



with a volume of ambient air will be negligible.



     The ratio of particulate phase to vapor phase 2,3,7,8-TCDD may also  be affected toy



losses  during transport from the incinerator stack.  For example,  particulate will be lost



from the plume due to deposition, which  would cause changes in  the  particulate/vapor



ratio.



     Due to the uncertainty surrounding this  issue, it was  decided to ;assume  that  the



vapor/particulate ratio remains the same during transport from  the stack and highlight



.this issue for future analysis.



     The effect of photolysis on the amount of 2,3,7,8-TCDD vapor photodegraded in



traveling from contaminated site to receptor population would be minimal:  For Scenarios



12  through 15 where  it is assumed that the receptor population is located 500 feet away



from the .site, the travel  time of volatilized  vapor is about  0.011  hours  at  an average



wind speed of 10 mph. The amount of 2,3,7,8-TCDD vapor degraded in the traveling this



distance is about 0.1% of  the original amount at a half-life of 6  hours.  For scenarios  8



through 11 with the population assumed  to be 100 feet away, the fraction of 2,3,7,8-
                                           226

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TCDD photolyzed  would  be smaller.   For these scenarios,  the  effect of  vapor-phase



photolysis on the result of exposure estimation may be neglected in  a practical sense.



d. Surface Water Contamination



     Two cases were evaluated for  the  extent of contamination of surface water by the



emissions from the  incinerator.   In the  first  case, used in  scenarios  16 and  17,  a



one-acre pond seven  meters  deep was considered with a negligible amount of inflow and



outflow water  compared to the amount  of water in  the pond.  In the second case, used



in scenarios 18 and 19, the impact on a  300 meter wide, five meter deep river flowing at



the rate  of  0.5 m/s,  was considered.  Both water bodies are located at 0.8 km  from the



incinerator.  This river is much larger than the one assumed in the land-related  scenarios



described in Sections A and B  of  this  chapter.   This is because incinerators  are  more



likely to be  located in urban  areas where large rivers are common.



     The 2,3,7,8-TCDD emissions  that  reach the water bodies upon dispersion in the



atmosphere  will  be partly particulates  and partly vapors.   The characteristics of  stack



emissions are  assumed to remain unchanged when the emissions reach the water body, so



the ambient air  concentrations above the  surface of the water bodies are  as shown in



Table 6-14.  These concentrations assume  no photodegradation in the atmosphere in the



process of pollutant transport from the stack(s) to the surface of water bodies.



     A photolysis  half-life  of 6 hours (Mill  et al,  1987) (k = 0.12  hr'1),  has  been



estimated for the vapor phase 2,3,7,8-TCDD and  experimentally supported under  simulated



sunlight conditions (Mill et al,  1987).  Assuming an average wind speed of  10  miles per



hour, the travel  time to the water  body is 0.05 hr,  very short compared to the 6 hour



half-life. The half-life  for 2,3,7,8-TCDD  in particulate form  is much longer, (Mill  et al,



1987).  Hence, no correction for degradation will be  applied to either the  vapor-form or



particulate-form  2,3,7,8-TCDD affecting the water body.
                                           227

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          TABLE 6-14. SUMMARY OF AMBIENT AIR CONCENTRATION
                AND DEPOSITION RATE IN THE VICINITY OF THE
                          FACILITIES IN SCENARIOS 16-19

Max. Cone.
at 200 m
(*/m3

Max. Deposition
Rate
(ug/m2.yr)

Cone, at
0.8 Km
(*/m3)

Deposition Cone, at
Rate at 0.8 Km 100 Km
(ug/m2.yr) (g/m3)
Deposition
Rate at
100 Km
(ug/m2.yr)
Vapor Form   2.1xlO'16
2,3,7,8-TCDD
(3000 TPD)

Participate-   1.2x10"16     3.7xlO"3
Form 2,3,7,8-
(3000 TPD)

Vapor Form   l.SxlO"13
2,3,7,8-TCDD
(120 TPD)

Particulate-   l.lxlO'13     0.168
Form 2,3,7,8-
TCDD
(120 TPD)
                                     1x10
                                        -15
7.1x10
                                                                 -18
                                    6.5xlO'16    6.3xlO~4     4.1xlO"18   2.2xlO'7
                                     8.3x10
                                         ,-14
9.1x10
                                                                 -16
                                     4.9x10'14    0.028
6.2xlO'16    2.7xlO"B
     The processes responsible for transferring  2,3,7,8-TCDD  in  the atmosphere into

the water body are dry deposition,  wet deposition  and vapor absorption.  The  first  two

processes are   responsible  for  the  removal  of  particulates,  and  the  last  process

removes the  vapor-form 2,3,7,8-TCDD from the atmosphere.  U.S. EPA, 198la) provides
the  ranges   of dry  deposition  rates  for  different  particle  sizes  which  will  allow
estimation of the concentration of 2,3,7,8-TCDD in  the water body caused by the  dry

deposition.    The  two-resistance   mass  transfer  theory  was   used  to   estimate  the
concentration of 2,3,7,8-TCDD in the water  body caused by  the  absorption  of vapors
into water.

     The deposition  rate  of  particulate-form  2,3,7,8-TCDD  will  depend  upon  the

characteristics   of   the  particles,   the  particle  size  distribution,  and   the   rate  of
precipitation.  For  particles with  a true density  of 1.5  g/cm^,  the settling velocities in
                                           228

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the air for the size fractions  comparable to the particulate emissions being considered is




given in Table 6-15.








   TABLE 6-15.  COMPARISON OF PARTICLE SIZE AND SETTLING VELOCITY






                    Particle Size (um)         Settling Velocity (cm/s)




                           0.8                         0.025




                           6                           0.25




                          16                           0.7




Source:  Wark and Warner, 1981.




      The dry deposition velocities rates are given by Turner 1970.  Deposition velocities




are minimal for particles with radii in the range 0.1 - 1.0 /zm and increase  for  both




larger and smaller particles.  For  particles having radii in the range  of 2  -  10 /«n,  the




deposition velocities  are 1-5 cm/s;  for particles  having  radii less than 0.1  pm,  the



velocities  are  0.02 -  0.8  cm/s; for particles in the range of 0.1  - 1.0 /mi, the velocities



are 0.1-1  cm/s.  The wet deposition  velocity cited  by  the  authors is 70  -  100 cm/yr.




Particle size distribution is needed to apply these deposition velocities  for various size




ranges.  Holton  (1985)  used a  deposition velocity of 0.005 m/s in his risk calculations for




PCB  emissions  from   hazardous  waste  incinerators.    The   deposition  velocity  of




particulate-form 2,3,7,8-TCDD is also estimated as 0.025 cm/s from  the results of the ISC



modeling  incorporating deposition due to dry settling and wet  deposition.



     (1)   Vapor Absorption




     The  absorption  of vapor phase 2,3,7,8-TCDD will  be caused  by  the concentration




driving  force between air  and water phases.   For the pond scenarios  (16 and 17) an




approach  to equilibrium is possible between the air and water phases after a long contact




time.  From Henry's law constant for 2,3,7,8-TCDD, which is  1.6 x 10~5 atm-m^/mol, the




equivalent water-phase concentration in equilibrium with the air phase, Cw*,  is  1.0 x




                                           229

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10~15 g/m3)/(1.6 x 10'5 x 41) = 1.5 x 10'12 g/m3,. or 1.5 x 10~18 g/cm3 in the 3000 TPD



case,, and.  1.3  x  10"^ g/cm3 in  the  120 TPD  case.   Shifting  winds  and unsteady



incinerator feed  conditions will cause the 2,3,7,8-TCDD concentration  in  air over the



pond to be variable which, may prevent the achievement of equilibrium. The site-specific



wind rose  frequency used in the dispersion modeling  available in  ISC will reflect  this



phenomenon- to some extent.  Hence, the maximum water-phase concentrations achievable



in. the pond, resulting from absorption from the vapor-phase 2,3,7,8-TCDD would be 1.5 x



1.0"I8 g/cm3 and 1.3 x  10~16  g/cm3 in the  3000 and 120 TPD cases,  respectively.  The



rigorous  evaluation of the concentration in the pond water will require consideration of



simultaneous absorption of vapors into water and disappearance from the water phase by



adsorption  on sediments occurring  under changing meteorological conditions.



     For the river scenario,  the vapor emissions coming  in contact  with  the river water



(scenarios  18 and 19) will be  absorbed into the water  to the  extent that mass transfer



rates allow.  This absorption, rate,  Q (in g/s) into the   water body can  be calculated



from the two-resistance mass transfer theory which takes the form:
                             (Cw* - Gw) A                                (6-35)
where Cw = concentration in water, (g/cm3), Cw  = water equivalent concentration of air



phase  concentration,  (g/cm3),  KOL = overall mass  transfer coefficient expressed  in  the



liquid phase unit,  (cm/s), and A = surface area where absorption occurs, (cm2).  The



mass  transfer coefficient is assumed to be KOL = 2 x 10~4 cm/s (Thibodeaux, 1979).  The



conservative assumption  was  made that Cw is negligible relative to  Cw* due  to  the



dilution provided by the river flow.  The Cw* values were identical to those calculated



above for the pond scenarios.



     At the plume location where the maximum concentration occurs, the diameter of the






                                          230

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plume is  about  120 m at the  surface  of the river.   Hence,  the water  surface  area



available for absorption is  120 m x 300 m = 3.6 x 10** m .  Hence



     Q = (2 x 10'4 cm/s)(1.5  x 10"18 g/cm3)(3.6 x 108  cm2)                 (6-36)



       = 1.1 x 10~13 g/s for the 3000 TPD case



     Q = 9.4 x 10~12 g/s for  the 120 TPD case                              (6-37)








     The  water flow rate in the river is  5 m x 300 m x 0.5 m/s = 750 m3/s.  The vapor



absorption  rate  and the  water flow rate can  be  used  to  calculate  the contaminant



concentration as  1.5 x 10~13 /ig/L for the 3000 TPD  facility and as 1.3 x  10"11  A»g/L for



the 120 TPD facility.



     (2)  Particulate Deposition



     Particulates that entered the  water  body will slowly  settle to its bottom,  and will



remain as  sediment.  The  change in the particle settling velocity as the particles enter



the  water  from  the air depends  upon   the  buoyancy  effect and the viscosity  of the



medium.  For the pond scenarios (16 and 17), while  particles are in suspension  in water,



the  amount  of 2,3,7,8-TCDD on  the particles should  be  accounted  for  as part  of the



contaminant concentration in  water.  For the deposition  velocity of 0.00025 m/s in the



air, the settling velocity in the water will be changed to








      0.00025 m/s[(2.5 g/cm3 - 1 g/cm3)/0.95 cp/(2.5 g/cm3 - 0 g/cm3)/0.018 cp]



   =  2.84 x 10"6 m/s                                                      (6-38)








where the densities of particles,  water and air are assumed to  be 2.5 g/cm3,  1  g/cm3,



and  negligible (0) relative to particle density, and the  viscosities of water and air  media
                                           231

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are 0.95 and 0.018 cp, respectively.  Particles will remain suspended in the water for an-



average of 28 days:



               7m/(2.8.4 x 10'6 m/s x 3600 s/hr x 24 hr/d) = 28.5 d         (6-39)



      In the case  of the 3000 TPD incinerator the concentration  of 2,3,7,8-TCDD  in the



pond due to dry and wet deposition of particulate matter can be estimated as








     (6.5 x 10T16  g/m3) (0.00025 m/s)(28.5 d x 24 hr/d x 3600 s/hr)/7m      (6-40)



   = 5.7 x. 10-14 g/m3








At 0.8  km distance, the lateral standard  deviation is  approximately  ay  = 60 m.  Hence.



the  diameter of  the  plume where deposition  occurs  is  approximately two standard



deviations and is  120  m with an  area of 1.1 x 104  m2.   This area is larger than the



surface area of the pond (4047 m2).  Hence no  correction for further dilution due to a



smaller mass  transfer  area than the pond surface is required.  A similar calculation can



be made  for particulate form of 2,3,7,8-TCDD emissions from the  120 TPD MWI  which



results in a calculated concentration in the pond due to the particulate-form emissions of



4.3 x 10'12 g/m3.



     For the  river scenarios (18 and 19), the settling of particulate-form 2,3,7,8-TCDD



will again occur at the rate of 0.025  cm/s  at the concentrations  of 6.5 x lO"1** g/m3



[3000 TPD]  and 4.9 x 10~14  g/m3  [120 TPD].   The settling velocity  is a function of



particle  size  and  density   which should be  determined  experimentally.    Since  this



information  is site-specific, a representative  settling  velocity  back-calculated from the



output  of the ISC model incorporating the  dry  and wet deposition is used.   Settling on



an area of 3.6 x 104 m2 is equivalent to a particle deposition rate  of








      0.00025 m/s (6.5 x  10'16 g/m3) (3.6 x 104 m2) = 5.9 x 10'15 g/s      (6-41)






                                           232

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in the 3000 TPD case, and 4.4  x 10~13 g/s in the  120  TPD case.   This  results  in  the




contaminant concentration in water as 7.9 x 10"^ A»g/L for the 3000 TPD case:








      5.9 x 10-15 g/s x 103 Oig/L/g/m3)/750 m3/s <•  7.9 x 10'15 pg/L       (6-42)








Similarly, the  concentration in water  for the 120 TPD case can be estimated  as 5.9 x




10"13 /ig/L.




      The total concentrations  of 2,3,7,8-TCDD in the river  water due to absorption of




vapor-phase emissions and deposition of particulate emissions  into the water body become




(for the 3000  TPD case):




           1.5 x ID'13/ig/L +  7.9x 10'15/ig/L = 1.6 x ID'13 Mg/L           (6-43)



Similarly, the river water concentration for the 120 TPD case becomes 1.4 x 10"" Mg/L.




Similarly,  the total  concentration of 2,3,7,8-TCDD  in pond  water due to absorption of




vapor phase emissions and deposition of particulates is 1.6 x 10"' /ig/L and 1.3 x 10"'




fjtg/L for  the  120 TPD and 3000  TPD facilities,  respectively.




      The above discussion indicates that the vapor emissions contribute considerably more




to  the contamination  levels in  water than do  the particulate  emissions.   The result is




surprising because intuitively (and as supported by our calculation) the rate at  which the




2,3,7,8-TCDD enters the water  is greater via the  particulate  route than the vapor route.




However, the particulates settle out relatively quickly and the vapor is assumed to remain




dissolved  in the water.  Under these assumptions,  the vapors contribute more to the total




amount either dissolved  or  suspended in  the water than do the  particulates.  Calculations



show that  the  percentage  of  2,3,7,8-TCDD   concentrations  in  water  attributable  to




particulates is about 3 to 5%.   In reality  much of  the initially dissolved 2,3,7,8-TCDD




derived from  vapors in  the  air  could  be absorbed into the sediment.  These losses were






                                           233

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not accounted  for and could  substantially reduce  estimates of  water concentration and



resulting risks  from either fish ingestion or water consumption.   However,  a  preliminary



calculation  for transport of the contaminant  from  water to sediment shows that this



transport  rate  is  rather  slow due  to the diffusional  resistance in the sediment layer,



thereby favoring  an  equilibrium situation between vapor and water  phases.   Future



analysis should attempt to address this issue more quantitatively.



e. Land-Disposed Ash



     The  incinerator  generates  both bottom  ash and  fly  ash which can  be ultimately



land-disposed.   The bottom  ash, as noted earlier, will not be considered  further, since no



data are available indicating PCDD content.  One affect of the  mixing is  to  reduce the



average concentration of 2,3,7,8-TCDD initially present in fly ash.  In actual  incinerator



facilities,  the fly ash and bottom ash are  often  mixed before disposal. If bottom ash has



negligible  amounts of  2,3,7,8-TCDD  in it,  this  would  result in a  dilution  of  the



concentration of 2,3,7,8-TCDD, with fairly straightforward effects on the predicted risks.



This  effect  can be noted  in the incinerator fly ash  and bottom ash  reported  for the



incinerator  in  Philadelphia (MRI, 1985).  The bottom ash reported in Table 6-11  for this



incinerator  is actually a mixture of fly ash and bottom ash being mixed operationally at



the facility.  Although  the  analysis of fly ash is given as reported in Table 6-11, the



analysis of  2,3,7,8-TCDD in bottom ash  (not the mixture) is  not separately given.   It is



also assumed that the  fly ash produced  from the incinerator contains the same amount of



2,3,7,8-TCDD at  the time it is disposed of in a landfill as  that being collected in control



equipment



     The uncontrolled  emission  factor  for emissions  of  particulate  matter  from  a
       v


municipal  waste incinerator is  30  Ib/T as given in U.S.  EPA,  1985.   At a particulate



emission control efficiency  of 99%, the emission factor  after  control is  0.3 Ib/T.  For a



3000  TPD capacity incinerator,  the daily  amount of fly ash collected for disposal is  3000






                                           234

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TPD x (30 - 0.3) Ib/T = 89,100 Ib per day. For the 120 TPD capacity the amount of fly

ash collected is 3,564 pounds per day.

     The concentration of 2,3,7,8-TCDD in fly ash reported in the literature varies from

0.07 - 100  ng/g as reported previously [see Table 6-11].  These  data  were mostly taken

from municipal incinerators in European countries.   The  cause of the variation can not

be  identified based on the data in the literature.  Except for a Swedish study (Ahling

and Lindskog, 1982), the literature suggests that the concentration range of 2,3,7,8-TCDD

in fly ash is 0.07 to 5.2 ng/g.  An average value of 1.3 ng/g excluding the Swedish study

was used for this.  Only fly ash is used in the averaging process.

     As  can be  noted  in  Table 6-11, data on the amount  of CDD  isomers  in ash  are

limited.   Also, it  is difficult to  compare the effects of analytical  efficiencies  on the

results regarding the amount of 2,3,7,8-TCDD in fly  ash.  Since  the  CDD components

including 2,3,7,8-TCDD are not easily extractable, MRI used a 16  hour benzene extraction

to remove the CDDs from the fly ash (MRI, 1985).  One  plausible explanation for lower

values of 2,3,7,8-TCDD in fly ash reported in European Studies may  be lower extraction

efficiencies resulting from  different extraction procedures including a shorter extraction

time.   Since  all  literature do  not  report  the exact procedure  investigators  used  in
                                                                   v
extracting CDDs, it is difficult to make a generalized conclusion.

     The exposure scenarios associated  with  the  land disposal  of 2,3,7,8-TCDD were

discussed in Sections A and B of this chapter.  Where reasonable the same procedures

were applied to incinerator ash; however, some modifications were required.  Since ash is

produced on  a continuous basis,  the  quantity disposed in  a  landfill  will increase over

time.  As  a  result,  the  exposure levels  associated with  ash  disposal  will also increase

over  time.  In actual incinerator facilities, the fly ash and bottom ash are often mixed

before disposal.  If bottom ash has negligible amounts of 2,3,7,8-TCDD in it,  this would

result in a  dilution of the concentration of  2,3,7,8-TCDD, with   fairly straightforward


                                           235

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effects  on the predicted risks.  Ideally,  the  releases and  associated exposures would be



computed, on a daily basis and summed over  the exposure  period to account for unsteady



exposure, rates.  In order to simplify the calculations,  it  was assumed that  the  ash was



generated at  a constant  rate over  70 years,  so  as  an average  ash amount,  it would be



half of that  generated in 70 years, or the amount generated, in 35 years4  Assuming that



the ash is landfilled at. a depth of  10 feet with a bulk  density  of 0.7 g/cm^, landfills of



2.6 acres and  66  acres would  be created from the  120  TPD and  3000 TPD incinerators



respectively.   Accordingly, the landfill  scenarios 9, 12,  and  15  were adopted for ash



disposal with sizes changed  to  2.6 and 66 acres (for the  35 year volume for the 120 TPD



and 3000 TPD incinerators  respectively) and  contamination level changed  to  1.3 ppb.  In



all other respects the ash  disposal  scenarios are  identical to scenarios  9,  12, and 15



described in Sections  A  and  B of  this chapter.   These  three  scenarios were  selected



because they represent a range of conditions from an uncontrolled access landfill with



reasonable worst-case  population characteristics  (scenario  9)  to an  uncontrolled  access



landfill with more  typical  population characteristics (scenario  12), to a controlled  access



landfill with cap  (scenarios  15).  This approach resulted in five fly ash disposal scenarios



defined as follows:



     (1)  Scenario  16  is  an uncontrolled access landfill receiving ash  from the 3000 TPD



          incinerator.    The  site  conditions and  population  habits  are  considered



          reasonable worst case as defined earlier for scenario 9.



     (2)  Scenario  17  is an uncontrolled access  landfill  receiving  ash from the 120 TPD



          incinerator.    The  site  conditions  and  population  habits  are  considered



          reasonable worst case as defined earlier for scenario 9.



     (3)  Scenario  18  is an uncontrolled access landfill receiving ash  from the 3000 TPD



          incinerator.  The site conditions and population habits are considered  typical



          as defined earlier for scenario 12.






                                            236

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     (4)   Scenario 19 is an  uncontrolled access landfill  receiving ash from the 120 TPD



          incinerator.  The  site conditions and population habits are considered typical




          as defined  earlier for scenario 12.



     (5)   Scenario 20 is a controlled access, capped landfill receiving ash from the 3000




          TPD  incinerator.   The site conditions and population habits  are  considered




          reasonable  worst case as defined earlier for scenario 15.




Using  the procedures described  in  Sections A and  B  of this  chapter  the ash disposal




exposures  were calculated  (see Table 6-16).   Exposures in  Table  6-16  are  based on




contact rather than absorbed doses.



     The particulate  emissions included those  generated during unloading of fly  ash at




the disposal site, the  spreading of the material unloaded, and transportation of fly ash in




trucks, and  particulates  airborne due  to  winds at  the  disposal  area.   The materials




handling  of ash (unloading, transporting  by trucks,  spreading,  etc.) will cause  greater




emissions than would be caused by  wind alone.  Air  dispersion modeling  along with the




methods  described  in Section C of Chapter  6 is  used to  estimate  the ambient  air




concentrations   from  each  activity and  wind  dust.     The  total  particulate  phase




concentrations are used to estimate the exposures shown in Table 6-16.




     Incinerator ash  could  also lead to  human exposure  when it is blown from trucks




transporting ash from the incinerator to  the landfill.   Such fugitive emissions would be




diluted over  a  long distance which  would  reduce potential  exposures  considerably




(compared to a  stationary point source).   Future analysis should attempt to estimate such



emissions and resulting exposure more definitely.




f.  Soil Contamination




     Soil   can  be contaminated   by the  fallout  of particulate  phase  emissions  and




adsorption of the vapor phase  2,3,7,8-TCDD on soil.  This adsorption will occur when the




vapor  phase plume reaches the  ground  level  and  comes in  contact with  soil.   For a






                                           237

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conservative  estimate,  the  soil  phase concentration  associated  with the  maximum air



phase concentration was evaluated.   The deposition rates are previously shown  in Table



6-14.  In all scenarios  involving the 3000 and 120 TPD MWIs, the maximum deposition



rate occurs at  a distance (200 m) very close  to the incinerator  because of the building



washdown effects coupled with precipitation washdown.  The maximum deposition location



can  be  possibly  closer than 200  m  in reality.  The distance  of 200 m is a calculated



distance constrained  by the limitation of the computational algorithm  built in  the  ISC.



Since soil ingestion by children, and  farming with  a pond or stream in an area very close



to the  incinerator  or at proximity  of buildings  within  200  m  is considered  unlikely,



exposure  from soil ingestion is evaluated at the site of the hypothetical family 0.8 km



from the  stack.  The difference  in deposition rate between the maximum deposition rate



and the rate at 0.8 km from the stack is approximately a factor  of 6.



     It  should be recalled  that the  particle settling velocity is dependent  upon particle



size and density.  The particle size distribution is  needed for  the spatial distribution of



the fallout. Over the period of paniculate fallout, the amount of 2,3,7,8-TCDD will build



up  from  zero  to the amount  accumulated up  to  the fallout time.   For 70  year  fallout



time, the total amount of the  contaminant fallen out per unit  area is 4.4 x 10~^2 g/cm2



in the 3000 TPD case,  and  2 x 10~10 g/cm2 in the  120 TPD case.  Hence, for situations



starting with zero and ending  with these values, the average amounts of fallout  over the



70-year period would be half, or 2.2 x 10~12 g/cm2 and 1 x  lO"1^, respectively.  For a



soil  bulk  density of  1.7 g/cm3,  a soil surface  density of at 1.7  g/cm2  will be used.  In



essence, this procedure assumes  that the particulate is mixed uniformly to a depth  of



1 cm.  The 2,3,7,8-TCDD concentration on the  soil surface for the  average  exposure



period is



     2.2 x 10-12/1.7  = 1.3 x 10~12 g/g, or 1.3 x 10'9 mg/g                  (6-44)



in the 3000 TPD case, and 5.9 x  10"8 mg/g in the  120 TPD case.






                                           238

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     This  concentration  will  be  decreased  under  the  influence  of  desorption  by



precipitation water, biodegradation, volatilization, and photolysis.  It  is possible  that the



action of  microorganisms  is  minimal  on the  soil surface,  while the  exact  extent of



photodegradation  on the  soil surface  is difficult  to  predict  at this  point.   In  these



scenarios, the disappearance rate  constant provided  by  Young (1983)  was used.  Young's



rate  constant,  0.069  yr~l,  is  derived  from  actual  field  conditions  which  include



photodegradation, biodegradation  and sediment loss, and runoff.  When  the disappearance



follows  the  first  order  kinetics,  the  total  amount  of  deposition  per unit area,  M,



remaining on soil  at any time t can be expressed by:








                         M - F [l-e"kt]/k                                  (6-45)








where F = constant deposition rate, and k =  first order disappearance constant.



      Hence, the concentrations in soil  resulting from the deposition  of particulate-form



2,3,7,8-TCDD given above should be  corrected  to account  for gradual  disappearance



using Equation 6-45. For the case of the 3000 TPD:








          M = (6.3 x 10'14 g/cm2 . yr/0.069 yr'1 [1-e  -0.069(70)]



            = 9.1  x I-'13 g/cm2                                             (6-46)








      Similarly, the mean deposition remaining in soil over the exposure period is 4 x



10" H g/cm2 in the 120 TPD case.   As discussed at  the beginning of  this subsection,



incorporation of the deposited particles into soil to a depth of 1 cm will yield an average



concentration of 5.4 x  10" 1^ mg/g for the  3000 TPD site, and 2.4 x 10~& mg/g for the



120 TPD site.
                                           239

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     The vapor-phase 2,3,7,8-TCDD in contact with the soil will affect the contaminant



concentration  on the soil surface.  Under the assumption of an equilibrium between the



soil-air interface,   the  soil-air  partition  coefficient  can  be  used  to  estimate  the



contaminant concentration  on soil  in  contact with  the vapors.   The soil-air partition



coefficient is:








               Kas  » 41H/Kd - 1.4 x 10~7 mg/cm3 air/mg/g soil            (6-47)








     Hence, for the 3000 TPD MWI case, the concentration of 2,3,7,8-TCDD on soil due



to the  vapor-phase TCDD is:








     Csm - 1  x 10~15.g/m3 x (103 mg/g)/ (1.4 x  10'7 g/cm3 x 106 cm3/m3)



         = 7.1 x 10~12 mg/g                                                (6-48)








     It is  likely  that  disappearance  of the adsorbed  contaminant will occur  by the



process of photodegradation, biodegradation  and erosion.   The  extent of  disappearance



will be dependent upon the elapsed time after the vapor impacts the soil,  and upon the



kinetic rate  of the process.    Hence,  this  concentration  represents  the  maximum soil



concentration  attainable  under equilibrium  with vapors.   Similarly,  the  maximum soil



concentration  in equilibrium with vapors for the 120 TPD site is 5.9 x lO"1^ mg/g.



     In these  scenarios, particulate deposition  provides a  concentration in soil larger



than or comparable  to the concentration caused by vapor adsorption.  As particulates fall



down  and  are mixed into soil,  additional adsorption is  possible from vapors approaching



the concentrations attainable by vapor adsorption on a short-term period.  This would be



particularly true at  the initial period of the incinerator  operation, because the amount of



particulate fallout is not significant compared to contribution from vapors.  If, on the






                                          240

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other hand, the particulate fallout contributes to a higher contaminant concentration than




vapor adsorption,  no further  adsorption of vapors is possible.  Hence, the resulting soil




concentration  will correspond initially to the  values determined  by  particulate fallout.




Particulate deposition contributes to soil contamination more than vapor adsorption over




a longer period of particulate  deposition or the lifetime of an incinerator.




D.  INCINERATOR EXPOSURE PATHWAY CALCULATIONS




     Table  6-16  is  a summary of  the calculated exposures for the  various incinerator




scenarios,  broken out  by exposure pathway.   The assumptions  used to obtain  these




exposure estimates are discussed below and the parameter values are listed in Table 6-17.




1. Inhalation  of Ambient Air



     The downwind concentrations  provided  in  Table  6-14  can be used to estimate




lifetime exposures associated with inhaling ambient air containing 2,3,7,8-TCDD in vapor




and  particulate forms.  The total exposures are based on the combined effects of vapors




and  particulates.




     Using the air concentration listed in Table 6-18 and parameter values listed in Table




6-17, the inhalation exposures at 0.8  km for scenarios 9-12 were calculated.  These are




also  included  in Table 6-18.




     For example, the exposure to the particulate-phase 2,3,7,8-TCDD  for Scenario 16 can




be calculated  from the given ambient air concentration and the  exposure parameter values



in Table 6-17:








  6.5 x KT10 (103)(23)(20,000/25,550)(1/70) - 1.7 x 1(T7 ng/kg-d             (6-49)








     For purposes of comparison  with the  inhalation exposures at  0.8 km ( as shown in




Table 6-18) the  inhalation exposures  at point of maximum ground  level concentration




(200m) and at 100 km are shown in Table 6-19.






                                          241

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                          TABLE 6-16. EXPOSURES ASSOCIATED
                 WITH INCINERATOR EXPOSURE PATHWAYS/SCENARIOS
            A.  EXPOSURES (ng/kg-day) ASSOCIATED WITH STACK EMISSIONS
             Dairy   Beef    fish    Soil    Vapor    Participate   Soil    Drinking   Vegetable
Scenario   Ingestion Ingeation Ingeation Ingeation Inhalation' Inhalation  Dermal   Water   Ingeation


16)3000TPD  JxlO'6  4xlO~B  7 x 10'7  2 x 10"6  6 x 1(T7  3 x 10~7  6 x 10*8 4 x 10"8
reasonable                                                                       See text
worst case

17)120TPD  6xlO"4  2xlO~S  6xlO"5  8 x NT6  5 x 1
-------
                                     TABLE  6-16.  (CONTINUED)
                  B.   EXPOSURES  (ng/kg-day)  ASSOCIATED WITH  FLY ASH DISPOSAL
               Dairy     Beef      Fish      Soil      Vapor     Participate  Soil       Drinking   Vegetable
Scenario*     Ingestion  Ingestion Ingestion Ingestion     Inhalation Inhalation    Dermal    Water     Ingestion


16)3000TPD IxlO"2   6xlO"2   2 x 10~5  3 x 10~3     5 x 10"6   3 x 10~7     1 x 10"2   2 x 10~6
reasonable                                                                                       See text
worst case

17) 120 TPD  2 x NT3   1 x 10"2   4 x 10"6  6 x 10~4     3 x 10"6   2 x 10"7     2 x NT3  3 x 10~6
reasonable                                                                                       See text
worst case

18) 3000 TPD 1 x 10~3  1 x 10"2    4 x 10'9  2 x 10'4     2 x 10'6   9 x 10'8     5 x 10'6   neg.b
abandoned                                                                                       See text
typical

19) 120 TPD  7 x 10"5   6 x 10"4   4 x 10"9  1 x 10"6     6 x 10"7   2 x 10-8     6 x 10"6   neg.
abandoned                                                                       .                See text
typical

20) 3000 TPD   neg.    neg.    neg.     neg.    neg.     neg.     neg.    neg.
reasonable                                                                                       neg.
worst case
monofill
w/capc
a All scenarios assmume O.Sppb 2,3,7,8-TCDD in flyash.
b Negligible exposure (<10~8).
c Stack emissions part of this scenario is the same as scenario 16.
                                                     243

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            TABLE 6-17
PARAMETER VALUES FOR CALCULATING EXPOSURES
     ASSOCIATED WITH INCINERATION

Inhalation
Respiration Rate (m-'/d)
Vapor Absorption Fraction
Participate Absorption Fraction
Exposure Duration (d)
Body Weight (kg)
Soil Ingestion
Ingestion Rate (g/d)
Absorption Fraction
Exposure Duration (d)
Body Weight (kg)
Dermal Contact
Contact Rate (g/d)
Absorption Fraction
Exposure Duration (d)
Body Weight (kg)
Drinking Water
Ingestion Rate (L/d)
Absorption Fraction
Exposure Duration (d)
Body Weight (kg)
Fish Ineestion
Ingestion Rate (g/d)
Absorption Fraction
Exposure Duration (d)
Body Weight (kg)

RWC
Scenarios
16,17,20

23
0.75
0.27
20,000
70

1
0.3
1,500
17

1
0.005
20,000
70

2
0.68
20,000
70

30
0.68
2,600
70

TYPICAL
Scenarios
18,19

23
0.75
0.27
7,300
70

0.2
0.3
910
17

1
0.005
7,300
70

2
0.68
7,300
70

6.5
0.68
1,500
70
(Continued 	 )
                244

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                          TABLE 6-17.  (CONTINUED)
Beef/Dairy  Products  Ingestion

Beef fat ingestion (g/d)                    26          14.9
Dairy products fat ingestion (g/d)          43          18.8
Absorption  fraction                       0.68          0.68
Beef exposure duration (d)              11,000         6,400
Dairy exposure duration  (d)        10,000         5,800
Beef fat/soil distribution factor             0.4           0.3
Dairy fat/soil distribution factor            0.04          0.04
Effective Grazing Area (m2/d)              22             22
Weathering  Rate Constant (1/d)           0.05          0.05
Transfer Coefficient  (d/L)               0.009         0.009
                                      245

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           TABLE 6-18. AMBIENT AIR CONCENTRATIONS
                    AND EXPOSURES AT 0.8 KM
Paniculate Concen- Vapor Concentration
tration (ftg/m^) (/ig/m^)
Scenario 16 6.5 x 1CT10 1 x 1(T9
Scenario 17 4.9 x 1(T8 8.3 x 1(T8
Scenario 18 6.5 x KT10 1 x IO'9
Scenario 19 4.9 x 10'8 8.3 x 10~8
Exposure (ng/kg-d)
Particulate Vapor
1.7 x 1(T7 2.5 x 10'7
1.3 x 10'5 2.1 x 10'5
6.1 x 10'8 9.4 x 1(T8
4.6 x ID'6 7.8 x 10'6
    TABLE 6-19. INHALATION EXPOSURES AT 200 m AND 100 km
                        EXPOSURES (ng/kg.d)


Scenarios                16            17           18                 19

Maximum Particulates    3.1  x 10"7     2.8 x 10~5     1.1  x 10~7        1 x 10~5

(200m)   Vapors        5.5  x 10'7     4.7 x 10"5      2 x 10~7      1.7 x 10~5



100 km   Particulates    1.1  x 10"9     1.3 x 10'7     3.7  x 10~10     4.8 x 10'8

         Vapors        1.9 x 10'9     2.4 x 10~7     6.7  x lO'10     8.5 x 10'8
                                  246

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2.  Ineestion of Contaminated Soil




     The procedures for calculating exposure and risk by soil ingestion were discussed in




Section  B.S.d. of this  chapter.  Using these  same procedures,  soil concentration listed




below and parameter values  listed  in  Table 6-17,  the exposures (see Table 6-20) were




calculated.  The corresponding risk values are provided in the appendix.




     TABLE 6-20. EXPOSURE FROM INGESTION OF CONTAMINATED SOIL






                        Soil Concentration (mg/g)     Exposure (ng/kg.d)






          Scenario 16         5.4 x 10"10                   1.9 x  10'6




          Scenario 17         2.4 x 10'8                    8.2 x  10'5




          Scenario 18         5.4 x 10'10                   2.3 x  10'7




          Scenario 19         2.4 x 10"8                      1 x 10"5








3.  Dermal Contact .with Contaminated  Soil




     The procedures for calculating exposure  and risk by dermal contact were discussed




in detail in Section B.3.  Using  the same procedures, the soil concentrations listed below



and  the parameter values listed in Table  6-17 the exposures (see Table  6-21) were




calculated.  The corresponding risk values are shown in the Appendix.




 TABLE 6-21.  EXPOSURE FROM DERMAL CONTACT OF CONTAMINATED SOIL

Scenario 16
Scenario 17
Scenario 18
Scenario 19
Soil Concentration (mg/g)
5.4 x 10-10
2.4 x 10'8
5.4 x 10~10
2.4 x 10"8
Exposures (ng/kg.d)
6 x 10-6
2.7 x 10"4
2.2 x 10~6
9.8 x 10~5
                                          247

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  4. Ingestion of Contaminated Drinking Water



       The total concentration in water was derived from  vapor absorption and particulate



  deposition.  Thus it  is composed of both a dissolved and suspended -component.  The



  contamination level was assmumed to remain constant from  the  source  to point where



  •water  consmumption  occurs.  Municipal or  home  treatment may substantially  reduce



  'exposure  levels.   The  procedures  for  discussing  exposure   from  drinking   water



  consmumption were discussed in detail in Section B.3.   Using the same  procedures, the



  water concentrations listed below and the parameter values smummarized in Table 6-17,



  •the exposures (see Table  6-22) were calculated.  The risk values for each scenario are



  shown in the Appendix.








TABLE 6-22.  EXPOSURE FROM INGESTION OF CONTAMINATED DRINKING  WATER





                           Water Concentration (0g/L)    Exposures (ng/kg.d)






            Scenario 16         1.6 x 10~9                    3.5 x 10~8



            Scenario 17         1.3 x 10'7                    2.9 x 10'6



            Scenario 18         1.6 x 10'13                   1.3 x 10~12



            Scenario 19         1.4 x KT11                    1.1 x 10'10








  5. Ingestion of Contaminated Fish



       The procedures for calculating exposure and risk by fish ingestion were discussed in



  Section B.3.  of  this chapter.  The same procedures were adopted  here  except that the



  concentration  of 2,3,7,8-TCDD in fish was  calculated on the basis of a bioconcentration



  factor between the fish and water of 10,000 L/kg (Schaffer, 1985) rather than fish and



  sediment.  Although the fish-sediment approach is generally considered better supported



  in the case of 2,3,7,8-TCDD (see discussion Chapter 5) it was more convenient to  use the






                                            248

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fish-water approach  here  since  estimates of the 2,3,7,8-TCDD concentration  in  water




were  available and the concentrations  in  sediment  were not.  Additionally, the bottom




sediments do not become immediately contaminated after the incinerator emissions begin.




Thus, it  may  take some time before the sediment-fish approach would be valid.  Using




the water  concentration listed below (dissolved  phase  only) and  the  parameter values




listed in  Table 6-17,  the  exposures  (see Table 6-23) were calculated.  The risk  estimates




for each  scenario are  presented in the Appendix.








      TABLE  6-23.  EXPOSURE FROM INGESTION OF CONTAMINATED FISH






                         Water Concentration (mg/g)   Exposures  (ng/kg.d)






          Scenario 16         1.6 x 10'9                    6.9 x  10"7



          Scenario 17         1.3 x 1
-------
        TABLE 6-24. EXPOSURE FROM INGESTION OF CONTAMINATED
                          BEEF AND DAIRY PRODUCTS
Soil Concen- Beef Exposure
tration (mg/g) (ng/kg/d)
Scenario 16 5.4 x 10~10 3.5 x 1(T5
Scenario 17 2.4 x 10'8 1.6 x 1(T3
Scenario 18 5.4 x 1(T10 8.6 x 1(T6
Scenario 19 2.4 x 10~8 3.8 x 1(T4
Dairy Exposure
(ng/kg.d)
5.2 x 10'6
2.4 x 1(T6
1.3 x 10'6
5.9 x 1(T5
7.  Ingestion of Dairy Products due to Particulate Deposition on Fodder

     The particulate matter carrying the dioxin compounds emitted from the incinerator

stack can be deposited on the farm fodder, which will become feed material for the cows

grazing in  the field.  The fodder contamination can  also occur through uptake by  plant

roots or  absorption  from  ambient  air.    The  2,3,7,8-TCDD  ingested  through  the

particulate-contaminated fodder will be  partially distributed into the  cow's system, will

accmumulate in body fat, and is excreted in the  fat portion of milk.  This  situation  is

different from the situation considered in Section 6 (where the 2,3,7,8-TCDD  ingested by

cows is from the soil rather than the fodder).

     Connett and Webster (1987) presented a comparison of exposures to 2,3,7,8-TCDD

emissions from an incinerator via inhalation and ingestion of cow's milk.  Their analysis

showed that exposure from ingesting milk of cows grazing  on  fodder  contaminated from

deposited incinerator emissions is about 200 times greater than exposure from  ambient air

inhalation of particulate matter.  Since many variables affect  the result of the analysis,

they presented the  variations of  the parameters used by different investigators, and the

resulting comparison between the inhalation and milk ingestion.


                                          250

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     The human intake rate of 2,3,7,8-TCDD from cow's milk can be presented as








                    Im = Cm Xm Am                                      (6-50)








where Im = intake rate from cow's milk (mg/d); Cm = concentration of 2,3,7,8-TCDD in




cow's milk (mg/L);  Xm = milk ingestion rate (L/d); and Am = absorption factor.  The




transfer factor (Fm) is defined as  the  ratio of the  concentration in milk divided by the




cow's contaminant intake rate  (I).  From this definition, the concentration in milk (Cm)




can be expressed as



                    Cm = Fm I                                            (6-51)




where  the  transfer factor Fm  has  the  units of d/L, and I is the intake rate  of 2,3,7,8-




TCDD, by the cow from ingestion of particulate deposited fodder (mg/d).




     Connett  and  Webster (1987) provided  an analysis regarding the  deposition rate  of




particulates on fodder and   a  series  of  first  order  processes  including  photolysis,




volatilization and weathering of the  deposited contaminant.  After neglecting  the  effect




of photolysis  and volatilization for  particulate-phase  2,3,7,8-TCDD,  they  presented  an




equation  relating the ingestion  rate  by a cow with other pertinent parameters:








                    I  = G d/KL                                            (6-52)








where  G  =   effective grazing area, (m^/d),  d = particulate  dioxin  deposition  rate,




(mg/m^-d), and KL =  weathering rate constant, (1/d).




     Combining Equations 6-50, 6-51,  and 6-52, one can get an expression for estimating



the  human intake of 2,3,7,8-TCDD  from  drinking  cow's milk  contaminated by  the




particulate deposited fodder:
                                           251

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                    Im = Fm G d Xm ATO/KL                              (6-53)
The parameter values used to estimate the exposure from cow's milk using Equation 6-53

are shown in Table 6-25.


              TABLE 6-25.  PARAMETER VALUES NEEDED IN EQUATION 6-53


                                                Average       Ranee
          Transfer Coefficient (d/L)          :     0.009     0.0015-0.013

          Effective Grazing Area (m2/d)     :      22           5.8-60

          Weathering Rate Constant (1/d)     :     0.05       0.046 - 0.05

          Milk Ingestion Rate                :     0.36        0.36 - 1.5



Source:  Connett and Webster (1987)



     The  values in Table 6-25 shown in the colmumn under "Average" represents values

recommended by Connett and Webster (1987) and an average value  for the milk ingestion

rate as given by  them, and those under "Range" represent the  ranges of different values

used by several investigators as reported by Connett and Webster (1987).

     As an  example,  the dose from ingestion of cow's milk contaminated by particulate-

deposited  fodder will  be  calculated for scenario 16.  The deposition rate of 6.3 x  10"4

ng/m^-yr at 0.8 km exposure distance is equal to 1.7 x 10~" mg/m2  • d.  Equation 6-53 in

conjunction  with the values in Tables 6-17  and 6-25 can  be  used  to  calculate the

exposure (ng/kg • d).

     Exposure =  (0.009)(22)(1.7 x 10-9)(0.36)/(0.05)(1/70)

                (10,000/25,550))x 106 = 1.4 x 10'5 ng/kg • d.               (6-54)



The exposures have beem calculated and are shown in Table 6-26.


                                          252

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   TABLE 6-26. DAILY EXPOSURE FROM INGESTION OF MILK RESULTING
                FROM PARTICULATE DEPOSITION ON FODDER
                                      Daily Exposure
                                        ng/kg.d


                   Scenario 16           1.4 x 10~5

                   Scenario 17           6.2 x 1(T4

                   Scenario 18           7.9 x 10"6

                   Scenario 19           3.5 x 1(T4



The exposures calculated in  Section 6, and Section 7  above  are compared, and the higher

exposure values for  each  scenario  are  reported  in Table 6-16.   The  doses can  be

computed by applying the absorption factor.   At an absorption factor  of 68%,  the dose

(absorbed dose) becomes  9.5  x 10~^  ng/kg  • d.   The corresponding risk values  are

presented in the Appendix.

E. RISKS ASSOCIATED WITH TOTAL CDDs VERSUS 2,3,7,8-TCDD

     Stack emissions and fly ash contain  many types of CDD congeners.  Each  congener

can exhibit different  toxic effects.  In an effort to  deal with the problem of  different

levels of toxicity for different congeners, the equivalency factors for other dioxins in

relation to the most potent 2,3,7,8-TCDD  have been developed (U.S. EPA, 1986).

     The term "TCDD-Equivalents", as applied to a CDD mixture, is  used to refer to the

amount of 2,3,7,8-TCDD which would have the same toxicity as the mixture. If the mass

fractions of each congener in stack emissions or  fly ash containing  a  mixture  of CDDs

are known, these emissions  or ash can be converted to the mass of  2,3,7,8-TCDD with

equivalent potency.  Hence, the weight  fraction  adjusted  according to the equivalency

factor  (EF)  will be different  from that  based on mass  weight  only.  The equivalency

factors used in this report were based on U. S. EPA (1986).


                                         253

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     In this effort, all available literature data with  information on  the concentration of

2,3,7,8-TCDD in the samples  taken were analyzed to obtain the adjusted weight percent

for the total dioxin components.   Appropriate data on emissions  were found from 13

different incinerators and appropriate data on fly  ash were found from  six  different

incinerators.

     The data denoted by "EQV" in Tables 6-10 and 6-11 were smummed to obtain the

averaged mass  fraction  of each component in stack emissions and fly  ash.  Table 6-27

shows  the results of the  emissions  analysis.  The  weight fraction of each congener was

averaged from the  available  data  points.   The weight  fractions  thus calculated were

multiplied by the EF as shown on the table to obtain  the adjusted weight percent.

     This table shows  that,  for stack emissions  the total CDD  constituents are more

toxic than  2,3,7,8-TCDD by  a factor of 100/2.7  = 37.  This indicates that if the risk

associated with the releases of 2,3,7,8-TCDD only is  10~*> for example, the risk from
             TABLE 6-27.  WEIGHT PERCENT DISTRIBUTION OF CDD
              CONGENER EQUIVALENTS IN MWI STACK EMISSIONS
Sum of Emission
Factors (/ig/kg) % EFa
2,3,7,8
Other tetras
Pentas
Hexas
Heptas
Octas
TOTAL
0.404
7.79
25.87
30.76
16.85
7.32
89
0.45 1
8.7 0.01
29.07 0.5
34.56 0.04
18.93 0.001
8.22 0
99.98
% x EF
0.45
0.087
14.5
1.38
0.019
0
16.44
Adjusted
%
2.7
0.53
88.2
8.40
0.12

99.95
  EF = toxic equivalency factor, based on U.S. EPA, 1986.


                                          254

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exposure to the total dioxin constituents  in  the release are higher by  a  factor of about




37. A value of about 50 has also been suggested assmuming that 2,3,7,8-TCDD comprises




about 2% on the  TCDD-equivalents basis (EPA 1987d)




     These ratios represent averages derived from  nmumerous incinerators.  However, the




ratio applicable to any  one  incinerator appears to vary widely.   For example, a MWI in




Marion County, Oklahoma was found to have an adjusted weight percent of 2,3,7,8-TCDD




of 85-92% (Ogden  Projects,  1986).   This percent would suggest that  the total CDD




constituents are more toxic than 2,3,7,8-TCDD only by a factor of about 1.13.



     A similar analysis was  conducted on the fly ash data (Table 6-28).  This analysis



indicates that the adjusted  weight percent of 2,3,7,8-TCDD in  fly ash  is 6.5%  which




suggested that the total CDD constituents are more toxic  than 2,3,7,8-TCDD only by a




factor  of about 15.




     The above procedure, using TCDD equivalents to estimate total CDD risks  involves




considerable uncertainty.  The  procedure  assmumes that the fate  and transport properties




of  the  CDD  congeners  are  identical  with those  of  2,3,7,8-TCDD.    Since  the




chemical/physical properties are not identical, the  environmental partitioning, degradation




rates, and human absorption are likely to be different.
                                          255

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             TABLE 6-28. WEIGHT PERCENT DISTRIBUTION OF
              CDD CONGENER EQUIVALENT IN MWI FLY ASH

2,3,7,8
Other tetras
Pentas
Hexas
Heptas
Octas
TOTAL
Sum of Emission
Factors (/igAg)
3.23
92.02
55
393.2
1057.6
797.2
2398.25
%
0.13
3.84
2.29
16.4
44.1
33.24
100
EFa
1
0.01
0.5
0.04
0.001
0
% xEF
0.13
0.038
1.145
0.656
0.044
0
2.013
Adjusted
%
6.46
1.89
56.88
32.59
2.19
0
100.01
a EF = toxic equivalency factor, based on U.S. EPA, 1986.
                                    256

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7.  UNCERTAINTY EVALUATION



     The estimates of 2,3,7,8-TCDD exposure presented in Chapter 6 are organized around



scenarios developed to reflect some of the varied sources of environmental exposure to



this compound.  In developing these scenarios, the Exposure Assessment Group tried to



construct examples that are relevant to exposure assessment needs faced by the Agency.



Accordingly, the major focus is on contaminated soil and on landfills containing dioxins



and on incinerators emitting dioxins.  The calculations for land related scenarios (1-15)



are of relevance to other land contamination issues and the incinerator scenarios (16-20)



are relevant to other sources of air emissions.



     The land-related scenarios address several simplified situations.  These scenarios



vary by the degree to which the contaminated material is maintained and controlled, the



distance  to human residences, and the presence of water bodies or agriculture. These



physical  scenarios are intended to represent either reasonable worst-case situations or



situations believed to be more typical, i.e., to more closely resemble occurrences that will



be commonly encountered in the field. In these scenarios a constant concentration of



2,3,7,8-TCDD is assumed across the contaminated site.  In the absence of detailed site-



specific information, use of an average site concentration to calculate exposures  is



deemed a useful procedure.



     The incinerator scenarios address two model incinerators:  an incinerator of



moderate size assumed to have a high dioxin emission factor and  a large incinerator



assumed  to have a low emission factor. The second incinerator model  is intended to



represent technology that may be utilized in the future. The incineration scenarios assess



multimedia exposure from incinerator stack emissions and landfilled (monofilled) fly ash.



     These scenarios are intended to illustrate a range of circumstances that may be



encountered, rather than predict exposures that will occur at specific sites.  It may be



expected that some factors affecting emissions will vary markedly between sites.  As





                                           257

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such, it is not meaningful to discuss the uncertainty present in the simplified physical



scenarios; rather, the test of their construction will be whether they prove useful to the



Agency as examples of how to evaluate sites encountered in practice.  Most importantly,



the methods used in assessing these scenarios can be applied to a variety of other



physical situations that may be encountered.



     Human behavior  patterns can strongly affect exposure to toxic materials. For



example, the number of years spent at a site and the quantity of locally caught fish



consumed will proportionally affect  exposure through a contaminated fish pathway.



Typically such factors  vary markedly among individuals and may also exhibit variation



between different population groups. Accordingly,  variations among behavioral parameters



are factored into the exposure scenarios presented.  Because the scenarios do not



represent  any specific  individuals or population, these behavioral parameters are regarded



as part of the scenario formulation.  That is, they are presented as illustrative values



rather than estimates.  However, survey data often provide a baseline with which the



reasonableness of behavior parameters may be compared.  For example, fish consumption



estimates must make sense when compared with the data available on fish consumption in



various  U.S. population groups.  In the  specific pathway discussions in this chapter, the



basis for selection of behavior parameters is addressed.



     After the physical site arrangement and human activities are specified, the degree



to which physical and  biological processes  transport the contaminant to the human



receptors  must be evaluated. Determining exposure requires use of  measurement data and



mathematical models.  Uncertainty can  be present in measured values that may not be



accurate or representative, in mathematical models that do not correctly reflect the



processes  actually occurring, and in  parameters used in models which are also subject to



measurement error.
                                           258

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     For the parameters used for transport of 2,3,7,8-TCDD via the various pathways, the



estimates made for the exposure scenarios are intended to be best estimates, given the




limitations of our knowledge of the mechanisms in exposure pathways.  In the small




number of instances where upper bound exposure assumptions are made, this fact is




explicitly  noted.  For each pathway assessed, this chapter presents a discussion of the




strengths and weaknesses of the methodologies utilized to generate the exposure




estimates.  This analysis attempts to provide a qualitative weight-of-evidence evaluation




as well as an evaluation of how far numerical results may be wrong.




A.  CONTAMINATED SOIL AND LANDFILLS




1. Summary of Uncertainties




     The  assessed exposure pathways can be conveniently divided into those that depend




on direct  human or animal contact with contaminated soil (including sediment containing




contaminated soil) and those  pathways that do not involve such contact.




     The  first group includes beef, vegetable and dairy products  ingestion, fish  ingestion,




soil ingestion, and soil dermal contact.  The second group, not involving direct soil




contact, includes vapor inhalation, dust inhalation, drinking water (surface) and  drinking




water (ground). A  review of the exposure and risk estimates




presented in Tables 6-6,  6-16,  and in the appendix shows that the pathways involving




direct soil contact generally have higher estimated risks than those that do not.   (The




ground water pathway is not included in these tables, as discussed in Chapter 6 estimated



ground water concentrations of 2,3,7,8-TCDD are very low).




     The  weight of available data indicates that,  however, major  uncertainty exists  in the




quantity of uptake.   Using a moderate amount of uptake as  an assumption, the plant




pathway can show exposures of the same order of those of the other food-chain related




pathways.  However, due  to the quantitative uncertainties plant uptake exposures have



not been estimated in the  scenarios.






                                           259

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     Exposures estimated under the "soil contact" pathways all depend on the estimated



soil or sediment concentrations of 2,3,7,8-TCDD. These estimated concentrations are all



dependent on assumptions about the degradation rate, and in some cases  also the  erosion



and deposition rates of contaminated soils. The assessment, which is premised upon a



thick layer of contaminated soil being present, assumes that no degradation occurs.



Because 2,3,7,8-TCDD is known to disappear slowly from surface soil it is likely that



concentrations in thick layers of soil will decrease even more slowly.  Therefore,  in the



absence of directly relevant data, making the assumption that no degradation occurs



below surface is a reasonable procedure which errs towards higher estimates of



concentration.



     The off-site soil concentration depends on the landfill erosion rate and the fraction



of eroded soil placed on an adjacent field.  The assessment presented  is appropriate for



situations where a landfill with a fairly high erosion rate places a significant quantity of



soil on an adjacent field.  The erosion  estimates used are judged appropriate as they are



taken from a survey of erosion conditions  at landfills.  Erosion rate and placement of



soil will  depend highly on site specific conditions.  In a low erosion situation, the



predicted concentration of 2,3,7,8-TCDD in the off-site field could be a factor of  100



lower. On the other  hand, soil concentration in the reasonable worst case situation



could not plausibly exceed three times the estimated levels.  Off-site  pond sediment



concentrations are assumed equal to the estimated off-site soil concentrations and will



exhibit corresponding site- specific variability.



      Predicted risks from beef, fish or dairy product consumption depend principally on



three factors:  estimated soil concentration, the estimated fish/sediment,  beef/soil or milk



fat/soil distribution ratios for 2,3,7,8-TCDD, and the rate of individual consumption of



these foods from the local source. The substantial expected variation in off-site soil or



sediment concentrations of 2,3,7,8-TCDD is discussed above.  The fish tissue/sediment






                                           260

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distribution ratio has exhibited substantial variation in laboratory and field measurements.



The value of five used in these analyses is towards the high end of measured values, and



a value one order of magnitude lower cannot be ruled out, with substantial fish species-



specific effects being likely.  Distribution ratios for beef and dairy products were



estimated using results obtained for polybrominated biphenyls for cattle in contaminated



feed lots. Comparison with laboratory data on cattle  fed 2,3,7,8-TCDD are supportive of



the beef/fat distribution ratio used but suggest the milk/fat distribution ratio may be



somewhat low (which would  lead to a low human  exposure estimate).  Dietary



consumption of beef and dairy products was estimated using survey data; survey data



were also available for the proportion of these products  that farm families  raise for



themselves. Thus the consumption estimates used have a reliable basis.  It should be



observed that these estimates apply only to individuals who regularly consume locally



raised  beef and dairy products.  In summary it is  unlikely that on-site exposure estimates



have large,  but off-site exposures can be expected to show substantial site  specific



variation depending on soil concentration.



     Two pathways involve direct human contact with contaminated soil:  soil ingestion



by children and dermal contact with  soil.  The exposures estimated for these pathways



are generally below those estimated for consumption  of  the animal products discussed



above, but are higher than the "indirect" pathways. Two circumstances could lead to



higher soil ingestion estimates. First, the values used do not specifically account  for



children with pica; data are not available for soil ingestion in children identified as



having pica. Second, adult inadvertent ingestion of soil  is not assessed,  although  it



might be argued  that exposure at much reduced levels from ages 7-70 would lead to



comparable exposures to those in ages 2-6 for which ingestion is assessed.  Gut



absorption of 2,3,7,8-TCDD  was estimated using measured absorption in animals  fed



contaminated soil.  The majority of the small number of tested soil samples showed






                                           261

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substantial absorption comparable to the 25% value used the pathway assessment; however



results with one tested soil sample indicate that absorption can be one to two orders of



magnitude lower for some soils.  This bioavailability uncertainty may be important for



site-specific risk assessments.



2. Uncertainties in Specific Methods Applied



a. Soil Dilution Factor



     The risks estimated for several off-site exposure  pathways depend on the



concentrations of 2,3,7,8-TCDD in surrounding soil due to erosion from the soil or



landfill.  It can be anticipated that the quantity of material eroded from the soil or



landfill will depend primarily on site-specific climatic, topographic, and soil



characteristics.  These factors are reflected in the parameters of the Universal Soil Loss



Equation (USLE) [Equation 6-3].  The USLE is a widely used model in agricultural



situations; the accuracy and precision of USLE estimates have  not been separately



reviewed for this report.



     The erosion estimates were obtained by using the USLE to calculate soil erosion in



a survey of 70 landfills conducted for EPA (Science Applications International Corp.,



1986). The survey, which was based on interviews with site managers  and local officials



and review of USGS topographic maps, ascertained estimates of the parameters related to



rainfall,  soil properties, and topography and site management practices.  The landfill



survey data can be used to estimate the quantity of material which would have been



eroded from each of these landfills under the scenario assumptions. In scenarios 8-11,



no vegetation was present to reduce erosion  (that is, the factor C  is equal to 1 in the



USLE).  For the 70  landfills, estimated erosion rates ranged from 0.6 to 306 tons/acre-



year, with a mean calculated value of 62 tons/acre-year.  The 10th to 90th percentile



range  was 2 to 163 tons/acre-year.  It is noteworthy that landfills with low erosion



potential may have two orders of magnitude less erosion than 62 tons/acre -year. Changes






                                           262

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in the erosion rate directly affect calculations of risk through all food-related pathways.



     For the scenarios where grass cover was assumed (12-14), the parameter C = 0.1



was used.  In this situation, the Chapter 6 estimates of erosion were reduced by a factor



of 10 to 6.2 tons/acre-year, and all estimates taken from the landfill study are similarly



reduced.  Thus, the conclusions about certainty remain the same.  It should be noted that



the depth of the contaminated soil will place a limit on the period at erosion, at a



specified rate,  may occur. This limit should be considered before applying the long-term



erosion model used here to fields where the contamination by 2,3,7,8-TCDD is not deep.



     The next  parameter estimated in calculating the dilution factor is F, the fraction of



the soil eroded from  the landfill that is assumed to be deposited on the adjacent  10-acre



field present in the scenarios.  Two values of F were selected for the  reasonable worst



case and typical case: 0.5 and 0.1, respectively.  These parameters were selected on the



basis of judgment concerning the fraction of eroded soil that could plausibly be deposited



on an adjacent field.  No data for  estimating F were available.  Much  variation in F



would be expected between sites, depending on the gradient of the landfill with respect



to the  field and the degree to which runoff is channelized. The estimates of F = 0.5 and



0.1 both reflect direct placement of eroded material on the off-site field; however, this



need not be the case—if the field were not directly down-gradient from the  landfill, a



much smaller quantity of material  might be deposited.



     A simplified mathematical model was developed  to address the fate of 2,3,7,8-TCDD



on eroded soil  after deposition in the field.  Two factors were considered:  1) mixing of



eroded soil with  the upper zone of soil present in the  field, and 2) degradation of



2,3,7,8-TCDD  in field soil due to  combined biological,  chemical, or physical processes.



     The mixing depth was selected as 10 cm, which was judged to be intermediate to



what might occur under different  agricultural practices.  A half-life of approximately 10



years was selected on the basis  of experimental data from one study of 2,3,7,8-TCDD in






                                           263

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surface soils.  The mathematical model applied assumed even mixing of 2,3,7,8-TCDD into



the soil to a depth .of 10 cm, it is recognized that this is a simplification of actual



processes in a field.  Such processes are likely to differ substantially between fields.



     The model results, however, show only modest sensitivity to these parameters as the



following observations for the reasonable worst case scenario (62 tons/acre-year, C = 1,



F - .5) show. Changing the assumed mixing depth to 1 cm increased the 70-year average



field soil concentration by a factor of 2.3, while increasing mixing depth to 20 cm, a



value which might be expected in a plowed field, reduces the average soil concentration



by  a factor of 1.6. Similarly, increasing the assumed half-life of 2,3,7,8-TCDD from 10



years to 35 years increases average levels by a factor of 1.8, while decreasing the



assumed half-life to  4 years decreased the estimated field concentration  by a factor of



2.0. Thus,  rather broad variation in these model parameters produces only limited



variation in model  estimates.



     BAG regards the soil concentration model as a plausible simplified approximation to



field conditions, however no field data are available to  assess  model predictions.



     Based on the preceding discussion, the largest uncertainties in site soil



concentration estimates are probably .due to the erosion rate used for the landfill and the



fraction of eroded  material assumed to reach the adjacent field. The values used reflect



relatively high erosion and relatively direct placement of eroded material on the field.  If



these conditions are not met, the  calculations here are not appropriate. For example, in



a low-.erosion situation (2 kg/acre-year), the soil mixing model  would lead  to an



estimated soil concentration (dilution factor) a factor of 20 below the value calculated in



Chapter 6.  If, additionally, only  5% of the total eroded material was deposited on the



field, the predicted 2,3,7,8-TCDD concentration would be a factor of 200 lower than the



reasonable worst case value and a factor of 40 below the typical case value. On the



other hand, since the field concentration could not reasonably reach a concentration in






                                           264

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excess of the landfill concentration, the soil concentration cannot exceed 2.7 times the



value (dilution factor 0.37) calculated in the reasonable worst-case bare site scenarios



(8-11) in Chapter 6.  A summary of the uncertainties associated with soil dilution factor



is in Table 7-1.



b.  Sediment Dilution Factor



     The sediment concentration for a pond near the waste site (scenarios  1-4, 8-11) is



assumed to have  the same concentration (dilution factor of  1) as the soil in the field in



which the pond is located.  In the absence of site-specific measurements, this is a



plausible assumption.  However if substantial quantities of sediment from uncontaminated



sites also reached the pond sediment concentrations would be diluted.  Additionally,



biological/photolytic/chemical degradation of 2,3,7,8-TCDD in pond sediments would



reduce this value to an extent depending on the rate  of transport of contaminated



sediment to the pond, although  the rate  of degradation is likely to be slow.



     For a stream off-site (scenarios 5-7, 12-14), both the  land (assumed to be grass-



covered  in these  scenarios) and  the surrounding watershed are assumed to suffer the



same degree of erosion.  Then,  the sediment in the stream is assumed to be a



proportional mix of sediment from the 10-acre site and a 10,000-acre area of watershed.



These assumptions lead to a dilution factor of 0.001.  This estimate utilized judgment of



the amount of mixing that might reasonably be taking  place, while recognizing that



variation between sites and  between watersheds would  lead  to much variation in actual



stream sediment  concentrations. Chapter 6 also presents a calculation, leading to a very



similar dilution factor, based  on expected run-off from a 10,000 acre watershed and the



estimated sediment burden of a stream carrying this amount of water, and the estimated



sediment eroded  annually from  a 10 acre landfill. This calculation reinforces the



plausibility of the 0.001  dilution factor used.  It  is also noted that  the stream flow
                                           265

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                                 TABLE 7.1.  LANDFILL ASSESSMENT
                                         SOIL DILUTION FACTOR
 Assumption/
   Method.
   Approach-
    Rationale
                                                                      Uncertainty
      Comments
Quantity of
erosion.from
contaminated
area.
Quantity, of
eroded soil
deposited on
adjacent field.
Mathematical
model.to assess.
rate of 2,3,7,8-
TCDD in soil
placed on field.
Used mean of ero-
sion) estimates
obtained from
applying, universal-soil
loss equation in a
survey of 70 land-
fills.
Mean: 65 Tons/acre--
      year.

Values of 50% and
10% used for reason-
able wont case,
more typical-case,
respectively.

Model assumed a
mixing: depth of 10
cm 2,3,7,8-TCDD
well  mixed in field
soil, above this,
not below.  Half-
life of 10 years for
2,3,7,8-TCDD in
fielf soil assumed.
Universal soil Ion
equation widely used
model for erosion.
Data.for landfills
appropriate for this
assessment.
Judgment on how
much, eroded soil.
could be placed on
adjoining field-
                                          Model judged to be a
                                          physically appro-
                                          priate idealised
                                          description.  Mixing,
                                          depth consistent with
                                          agricultural prac-
                                           tices, data on 2,3,7,
                                          8-TCDD profiles! on
                                          soils.  Degradation
                                          rate taken from field
                                          data.
                                                                  Landfill erosion
                                                                  estimates- ranged from
                                                                  0.6 to 306 tons/acre-
                                                                  year.
10th-90th percentiles
from erosion survey 2 to
163 tons acre-year.
Erosion rate will be
highly site-specific.
                                                                  Could be close to
                                                                  zero but not much
                                                                  higher than 50%.
                       Model not tested in
                       practice; parameter
                       estimates are not
                       precise;  However,
                       model estimates are
                       not very sensitive to
                        assumptions on mixing
                       depth or degradation
                       rate.
Highly site-specific, based
on-gradient of landfill,
adjoining fields.
Evaluation: Analysis is reasonable for a situation where a contaminated area with a fairly high erosion rate deposits
soil on an~ ad joining field. Largest sources of uncertainty in comparing the scenarios described here with an actual.
field site will be in the assumptions about quantity of soil eroded and placed on the adjacent field. In a low-erosion
situation, the.predicted concentration of.2,3,7,8-TCDD in the field could be a factor of 100 or more lower. The
concentrations on the field could not plausibly exceed about 3 times the estimated levels even in very high erosion
situations:  Risk numbers for food-related pathways are sensitive to these values.
                                                          266-

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calculated for the  10,000 acre watershed (17 ft3/sec) is of a size that could plausibly




support local fishing.




     Science Applications (1986) reports watershed areas for most of the 70 landfills for




which erosion rates were calculated.  These watershed sizes vary considerably with  10 of




51 watersheds being smaller than 1,000 acres and  16 of the 51 being 100,000 acres or




above (median 11,000 acres; mean 29,000 acres).  Thus the assumed value of 10,000 acres




falls in  the middle of the observed values.  If the landfill were in a smaller watershed,




less dilution of contaminated sediment by stream sediment would be expected. However, if




a much smaller watershed were assumed with a correspondingly lower stream flow, the



stream size may be inadequate to support substantial local fishing.  Additionally, however,




if local  hydrologic factors allowed significant accumulation of landfill sediment near its




input to the stream, larger values of the dilution factor would be expected.




     It  should be  noted that only the "more typical" and  not "reasonable worst case"




scenarios included a stream.  If a stream sediment dilution calculation were made using




the reasonable worst case assumption of a bare  landfill with a 62 ton/acre-year erosion




rate, the increased erosion would lead to a dilution factor of 0.01 rather than 0.001. A




summary of the uncertainties associated with sediment dilution factors is shown in  Tables



7-2 and 7-3.




c. Degradation




     As discussed under the soil dilution factor, measured values of near-surface




degradation or removal rates of 2,3,7,8-TCDD  were used in calculating off-site soil levels.




It was noted that in the soil mixing model applied, degradation rate had only a modest




effect on predicted soil concentration.  No degradation was assumed to  occur in the soil




buried in the  landfill.  No data were available to support estimates of degradation




inside the landfill; however, any such degradation should be less than the estimated half-




life for surface degradation/disappearance of 2,3,7,8-TCDD (estimated  at approximately 10






                                           267

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                                TABLE 7.2.  LANDFILL ASSESSMENT
                              SEDIMENT DILUTION FACTOR - PONDS
  Assumption/
   Method

Contamination
levels in
sediment.
    Approach

Level in soil
surrounding pond
assumed to equal level
in sediment.
   Rationale

Pond sediment is de-
rived from local soils
and has less turnover
than streams - so
should reflect local
soils.
   Uncertainty

Sediment transport to
some ponds may .come
from outside con-
taminated area
causing greater
dilution.
     Comments
Worst-case assumption.
Degradation of
2,3,7,8-TCDD in
sediment.
Assumed no
degradation.
Degradation in pond
expected to be less
than for land surface
as some paths of
degradation will be
reduced under water
(e.g., photolysis).
Degradation slow on
land surface.  Addi-
tional contaminated
soil will be mixed
with pond sediments
on continuing basis.
Young (1983) observ-
ed degradation rates
on land with roughly
a 10 year half-life.
If these apply to both
sediments in the
pond and to new
sediments reaching
the pond, the average
concentration over 70
years would be re-
duced by 80%.
Worst-case assump-
tion, since it is unknown
how the water
environment will change
the land-based half-life
observed by Young
(1983).
Evaluation:  This approach uses worst-ease assumptions in the absence of data. The scenarios in which the pond are
used are the "reasonable-worst-ease" assumptions, so these assumptions do not appear in the other scenarios.  Given
the pond itself in the scenarios where it is used in either on the contaminated site or directly downhill adjacent to the
landfill, these are not unreasonable assumptions.  Fish consumption risks are directly affected by sediment dilution
    factor estimates.
                                                        268

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                                TABLE 7.3.  LANDFILL  ASSESSMENT
                            SEDIMENT DILUTION FACTOR - STREAMS
  Assumption/
    Method
    Approach
    Rationale
   Uncertainty
                                                  Comments
Contamination
levels in
sediment.
Dilution assumed to
be proportional to
landfill area divided
by water shed area.
Assumed a landfill
area of 10  acres and
watershed area of
10,000 acres - yield-
ing a dilution of 1000
fold.
Taking proportions of
source areas is an
accepted method for
calculating sediment
dilution. A 10,000
acre watershed is
near the median size
seen in a survey of
70 landfills. The
runoff from 10,000
acres would support a
stream of fishable
size in many cli-
mates.
Watershed could be
much larger with
greater dilution.
Watershed could be
smaller with less
dilution, but might
not support fishable
stream. Mixing of
sediment in stream
may not be uniform
and higher concen-
trations of 2,3,7,8-
TCDD may be found
near landfill.
A second approach to
calculating dilution
yielded similar results:
Runoff from a 10,000
acre watershed was
calculated and standard
equations were applied  to
estimate the quantity of
sediment carried by a
stream of this size.
Sediment dilution was
then calculated by
comparing estimated
landfill erosion rate with
calculated stream
sediment load.
Relative erosion
at landfill site
vs. rest of
stream.
This method assumes
a uniform erosion rate
through the
watershed.
Site-specific infor-
mation would be
needed to evaluate
variable erosion rates.
Landfill survey found
erosion rates to vary
from 2 tons/acre-
year (10th percen-
tile) to 163 tons/
acre-year (90th per-
centile).
See Above.
                                                        269

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                                        TABLE 7.3.  (CONTINUED)
  Assumption/
    Method

Degradation of
2,3,7,8-TCDD
in sediment.
   Approach

Assumed no degrada-
tion.
   Rationale

Degradation expected
to be lower than slow
rate observed on land
surface (less photo-
lysis). Additional
contaminated soil will
be added to sediment
continually.
   Uncertainty

No sediment degrada-
tion data are avail-
able.  Young (1983)
observed degradation
rates on land at 10
year half-life.
Average  concentra-
tion over 70 years
would be reduced by
80% if both landfill
and stream sediment
2,3,7,8-TCDD were
degraded at this rate.
    Comments

Worst-ease assumption
used. It is unclear what
effect the stream
environment would have
on degradation relative
to Young's observations,
but it may be slow
degradation.
Evaluation: The estimate of stream sediment dilution factor is very site-specific, and therefore applying the stream
scenarios to an actual site should be done with caution. The key 'Uncertainty is .the evaluation of erosion rate from
the landfill vs. sediment load of the stream.  The sue of the watershed assumed [i.e., sediment load] is moderate for
landfills, but large enough to have a stream  which can support a reasonable fish population.  In this sense, the size of
the watershed is small relative to those in actual sites which will support fishing, but there are likely to be many
•streams like this in actual situations. The mixing of the stream sediment load with the erosion loading is not well
understood hi terms of concentrations of resulting downstream sediment, so therefore the uncertainty of the 1000
dilution factor is high (at least one to two orders of magnitude uncertainty). Obviously, uncertainties in the dilution
factor directly translate to uncertainties in the risk estimates for fish consumption.
                                                          2.70

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years). If a 29-year half-life were assumed inside the landfill (a value which was



calculated in this report for persistence in the presence of a particular kind of mold)



only a modest reduction (less than a factor of 2) in estimated risks averaged over a 40-



or 70-year time period would be predicted.



     Because of degradation processes at the surface, it is possible that surface



concentrations of 2,3,7,8-TCDD may be lower than the internal landfill concentrations.



Surface concentrations would depend on a balance between degradation rate and erosion



rate.  Some of the data presented in Young (1983) suggest the presence of such an



effect.  Recent data also indicate that photolysis occurs on the immediate surface of soil.



It is unclear what lower surface concentrations would mean in terms of risk, since there



are no data indicating how, especially if only on the immediate surface, much of an



effect this might have on 2,3,7,8-TCDD concentrations in materials such as windblown



dust.  If surface degradation has a substantial impact on the concentration of 2,3,7,8-



TCDD in surface soil and windblown dust, many of the risk numbers for pathways related



to surface soil (e.g., soil ingestion, dermal contact, dust inhalation, etc.) could  also



change substantially downward. At present the assumption of no degradation  is



essentially the only alternative,  having a moderate, but unquantifiable uncertainty.  A



summary of the uncertainties related to degradation is  in Table  7-4.



d.  Dust Inhalation



     Dust emissions from the soil and/or landfill were  calculated using an empirically



derived relationship which assumed  that the surface was uncrusted and composed of



finely divided particulates, a situation where dust emissions will be maximized for an



undisturbed site.  The emission  rate was based on the proportion of surface assumed to



be unvegetated. One parameter in the model is the  threshold wind speed for erosion,
                                           271

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                                 TABLE 7.4.  LANDFILL  ASSESSMENT
                                               DEGRADATION
  Assumption/
    Method

Degradation in
landfill.
   Approach

Assumed none.
Degradation on
contaminated
soil.
Assumed none.
   Rationale

Hydrolysis and oxida-
tion are very slow in
water, and hence ex-
pected to be very
slow in soil (U.S.
EPA,  1985b). While
most soil organisms
appear not  to degrade
2,3,7,8-TCDD, one
species of fungus may,
with an apparent
half-life of 29 years
(Bumpus et al., 1985).
Two mechanisms may
serve to renew sur-
face 2,3,7,8-TCDD
levels.  Erosion of
surface soil will
expose buried soil.
Movement through
volatilization and
reabsorption may
occur.  Need to
balance several fac-
tors makes surface
concentration diffi-
cult to estimate.
   Uncertainty

No data exist on
degradation of buried
2,3,7,8-TCDD, how-
ever, degradation
should be less than
slow rate observed for
surface contami-
nation. If buried
2,3,7,8-TCDD degrad-
ed with 29 year half-
life, less than a
factor of 2 change in
70 year average con-
centration would be
predicted.

Some loss of soil
surface 2,3,7,8-TCDD
would be expected
based on observa-
tions of Young (1983),
who noted overall
losses from known
effects like photolysis,
volatili-cation, soil
movement and possibly
biode-
gradation. Young
provided an estimate
of a half-life of
approximately 10
years for 2,3,7,8-
TCDD in the upper
layers of soil, based
on field data.
     Comments
Photolysis of 2,3,7,8-
TCDD on soil in presence'
of hydrogen donors (and
light) reported by Crosby
and Wongs (1977). By
extrapolation and
multiple corrections from
2,3,7,8-TCDD photolysis
on plant leaves,
estimated half-life on the
soil surface of 7.2 days
(Thibodeaux and Lipsky,
1985).
Evaluation: 2,3,7,8-TCDD is known to degrade slowly in contaminated surface soil and it is likely that concentrations
in thick layers^ of landfilled soil will decrease even more slowly.  In the absence of data, assuming no degradation is a
reasonable procedure that errs towards higher estimates of concentration.  However, 2,3,7,8-TCDD at the soil surface
itself may degrade at a rapid rate (see comment above). What effect this surface rate  would have on overall
concentration is questionable, and hence the source of significant uncertainty.  Uncertainties in degradation rate
directly affect the soil dermal, dust inhalation, and soil ingestion pathways.
                                                         172-

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estimated in a manner recommended by the model's developers. Since the procedure for



estimating threshold wind speed is complicated, it has not been evaluated here for




empirical agreement, and since the estimated erosion rate depends on the inverse of the




cube of this parameter, uncertainties in the predicted dust  emission rates may be of




consequence.  Dust emission also depends on the cube of mean annual wind speed.  The




mean annual wind speed for 60 U.S. cities varies from 2.8  to 6.3 m/s, a  mean of 4 m/s




was used to calculate emissions in Chapter 6.  Use of a 2.8 m/s wind speed would have




led to a dust emission estimate a factor of three lower,  while use of a 6.3 m/s wind




speed would have led to an estimate a factor of four higher.




     Since the empirical validation of the dust emission model has not been reviewed,




uncertainties cannot fully be assessed; however, the  assumptions on the character of site




soil tend to maximize emission estimates.  In some of the scenarios (1-4, 8-11) it was




assumed that most of the surface remained  bare and unvegetated.  Such  an assumption is




not plausible in many climates and alternate assumptions may be warranted in site




specific assessments.




     Dust emissions due to vehicular traffic on an unpaved road was calculated using the




methodology described in the section on land disposal ash from incinerators in this




chapter.   Note that the assumption that heavy trucks are present may not be appropriate




for many inactive sites.  On the other hand, the calculations assume that only the site



itself contributes contaminated airborne dust.   Over time, as erosion and previous



windblown dust contaminate areas adjoining the site, these areas will also release




contaminated, airborne dust, increasing exposures over  those calculated here.




     Following the generation of emissions estimates, transport models were used to




estimate  concentrations of dust reaching individuals in the vicinity. Different models were




used to assess on-site and off-site dust concentrations.  For off-site exposures with the




receptor  more than 100 m from the site, the ISC model was used,  with a virtual






                                           273

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downwind distance parameter incorporated to reflect the fact that the site is not a point



source.  The ISC model is widely accepted and used throughout EPA as a standard model.



The default model parameters utilized for this analysis are intended to represent typical



meteorologic conditions.  Thus, while the quantitative uncertainties of model predictions



are not assessed in this report, there is a strong basis for relying on the ISC model.



     On-site exposures, that is, exposures due to living in a contaminated area, are more



difficult to assess, since there is no standard model accepted for  modeling on-site air



concentrations.  In this analysis, a near-field dispersion model was applied (this model



was also  used for off-site exposures within 100 m of the site boundary).  The near-field



model is based on theoretical principles, and no empirical validation data are available.



There are however, two supporting analyses that buttress the general predictions of this



dispersion model. First, as  shown in Figures 6-2 and 6-3 in Chapter 6, the ISC model



and the near-field dispersion model are in satisfactory agreement (the near-field model



predicts concentrations 40% lower than the ISC model) at the boundary of the site where



both models can be applied. Second, the near-field model is in general agreement with,



but somewhat lower than the simple box  mixing model which  assumes sideways  transport,



without vertical mixing, of contaminants from the site.



     Three additional factors, the inhalation rate, exposure duration, and  absorption



fraction, enter into the inhalation risk calculation.  The inhalation rate utilized, 23



m-Yday, is within the range of standard values commonly utilized for this parameter, and



reasonable variations should not have a marked effect on risks.  Exposure duration set at



40 or 70 years is considered as a defined part of the exposure scenario, with other



durations being easily evaluated if desired. Little data exist on absorption of 2,3,7,8-



TCDD following inhalation. However, since much inhaled particulate will eventually enter



the gut, the gut absorption  data, discussed below, provide some support for the  27% value



utilized in this assessment.






                                           274

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     In summary, dust exposure calculations in some "reasonable worst-case" scenarios



assumed site conditions that would tend to maximize dust release from winds,  and include



dust emissions due to solid disturbance by vehicles.  Table 7-5 includes a discussion of



the uncertainties  involved with dust inhalation.



e.  Vapor Inhalation



     The  rate of air emission of 2,3,7,8-TCDD through volatilization was calculated using



a release model previously developed and peer reviewed in connection with an assessment



of PCBs [Equation 4-3]. The model is based on theoretical mass-balance calculations,



utilizing equations for fundamental physical/chemical transport processes.  No empirical



data are available to validate the model. Variables upon which the model release



estimates depend are Dj, the diffusivity of dioxin in air; E, soil porosity; Ps, soil density;



and Kas, the soil/air partition coefficient. The parameter Dj is calculable based on



physical laws, while E and Ps depend  on site soil characteristics; however, these



parameters would not be expected to vary over a great enough range to strongly affect



emission estimates.



     The  major source  of uncertainty in the predicted emissions pertains to K^, which is



equated to the ratio of Hc (Henry's Constant) to Kj (soil/water partition coefficient).



Chapter 3 reports a range of values for Hc of  1.6 x  1"^ to 4.6 x 10"^ from studies by



two authors.  The lower of these values is used in the emissions calculations; if the



higher value were used, the release estimate  would be a factor of three higher.



     The  parameter K^ is calculated using the following empirically supported



relationship:




                                   " 
-------
                                 TABLE 7.5.   LANDFILL ASSESSMENT
                                            DUST INHALATION
  Assumption/
    Method
    Approach
   Rationale
   Uncertainty
Comments
2.3,7.8-TCDD
was assumed to
be transported
from the site via
wind blown dust.
Dust generation.
Dust emissions were
modeled via the "un-
limited reservoir
method."  Soil sur-
face was assumed to
be finely divided,
uncrusted particu-
late.
Dust generated by
wind and vehicle
traffic.
This is a published
method developed
from field data.
Thought to be the
two principal sources
of dust emissions.
Calculation provides
high estimates of dust
generation rates
because many surfaces
may be crusted, re-
ducing potential for
dust emissions. Model
parameters, e.g.,
widespread, will
exhibit substan-tial
variation.

Vehicle generated dust
calculated assuming
presence of heavy
trucks; if only light
vehicles are present.
Vehicle emissions
reduced by factor of
five.
Vegetation cover.
Vegetation cover was
assumed to vary from
none to complete in
different scenario
calculations.
Inhalation rate.     Used 23 mS/d.
Vegetation cover re-
duces dust emission; a
range of values was
used to show impact
on dust emissions.
                       In range of standard
                       values used for this
                       parameter.
Full range of this
variable was utilized
among the several
scenarios, resulting in
a difference of about
two orders of
magnitude.

Not a major source of
variation.
Evaluation: Reasonable approach that tends toward making high estimates of dust generation for an untrafficked site,
but site disturbance could lead to much higher estimates. The ground cover assumptions here are highly site-specific
with a resulting range of about two orders of magnitude in risk.
                                                         276

-------
and 4% among different soils. Koc has not been measured for 2,3,7,8-TCDD, and must




itself be calculated using an empirical relationship relating Koc to Kow, the




octanol/water partition coefficient.  A careful review of this last relationship was




conducted by Lyman and Loreti (1986), who  empirically compared Koc and Kow for 57




organic compounds selected as having the most reliable experimental data.  Using the




three regression equations derived by Lyman  and Loreti, and the experimental value  of




4.24 x  10*> for Kow (presented in Chapter 2)  leads to estimates of Koc in the range 4 x




10^ to  7 x 10^. However, in the data analyzed by Lyman  and Loreti, the only compound




having a Kow above 10^ showed a Koc more than an order of magnitude below the




regression line estimate, reducing confidence  in the relationship for compounds such  as




2,3,7,8-TCDD with very high Kow values.




     U.S. EPA (1985g) reported laboratory measurements of the soil/water  partition




coefficients for 10 soil samples from sites in Missouri and  New Jersey (the eight Missouri




samples were from  soils contaminated by dioxin containing waste oil, the two New Jersey




samples were from  industrial sites). The measured partition coefficients (mean of "SWLP-




R" data) ranged from 4  x 104 to 4 x 106 with a geometric  mean of 5 x 105.  The total




organic content of these soil samples ranged from 1.5 8%.  Since these data show




substantially higher partition coefficients than the soil/water partition coefficient used in




the exposure calculations (Kj =  4,680 for a soil with 1.0% organic carbon content).




     In light of the points raised above, the use of the selected value of K.
-------
     As with dust emissions, respiration rate and residence time at the site would



influence  risk; however, both parameters are within standard ranges used for these



values, and reasonable variation (pertaining to long-term exposure) would have limited



impact on predicted risk.



     The  absorption fraction for vapor inhalation is estimated at 0.75.  Little data exist



to support a specific value for this absorption fraction; however, in consideration of the



high gut absorption of pure 2,3,7,8-TCDD, substantial inhalation absorption is plausible.



Table 7-6 is a summary of uncertainties for vapor inhalation.



f. Dermal Exposure



     Estimates of dermal exposure relied on the analysis by Schaum (1984) of the limited



data available on this pathway. The quantity of soil on exposed body surface areas was



estimated. Using two studies of the quantity of soil on children's hands using two



different  measurement  methods (Lepow et al., 1975 and Roels et al., 1980).  Data from



these studies were analyzed to obtain estimates of 0.5  and 1.5 mg/cm2 for the soil levels



on children's hands.  A  value of 1 mg/cm2 was used in scenario calculations.  It is  then



assumed that the soil levels on hands are reflective of soil levels on all exposed skin



areas of the body,  and  that adults have levels of soil on skin surfaces similar to those of



children.  No data were available to assess either assumption.  It may be  argued that



these assumptions are likely to overestimate exposure  if other unclothed body areas have



less dirt exposure than  hands and if adults have lower dermal soil levels than children.



Depending on the type of clothing worn, exposed adult skin area ranges from 900 to



2,500 cm2.  A value of  1,000 cm2 was used in scenario calculations.  Exposure durations



were taken as specified  in the separate scenarios.



     Experimental data on skin absorption  for soil containing added 2,3,7,8-TCDD are



available  for the rat.  Poiger and Schlatter (1980) reported the percentage of applied



radiolabel dose in the liver following placement of a water/soil paste on the skin.  Three






                                           278

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                                  TABLE 7.6.  LANDFILL ASSESSMENT
                                            VAPOR INHALATION
  Assumption/
    Method
    Approach
   Rationale
   Uncertainty
     Comments
Air emissions
release rate.
On-site air
concentration.
Used air emission
release rate model
based on physical
calculations of
2,3,7,8-TCDD
partitioning and
transfer, Used factor
previously desired in
a PCB assessment to
account for effect of
a clean cover, if
present.
Short-range disper-
ion modeling used.
Measurement data on
air release are not
available. Models are
commonly used for
estimation of emis-
sion rates.  The model
applied has been peer
reviewed and
published by BAG.
Gaussian dispersion
modeling not applic-
able for short-range
dispersion.
Models for air re-
lease rates are not
validated on a field
scale.  Models de-
scribe physical setting
fairly accurately.
Substan-tial
uncertainties are
associated with input
parameters in-
cluding Henry's  law
constant, partition
coefficients.

Model not validated
on a field scale.
Wind speed and dis-
persion coefficients
are the most uncer-
tain input parame-
ters.
The value for water-soil
partition coefficient most
uncertain.  Emis-  sion
rate can change by
2 orders of magnitude
depending upon the value
of the partition coeffi-
cient. Wicking effects
have the potential to
increase air emissions
under some circum-
stances; not quantita-
tively evaluated.

Site-specific meteoro-
logic conditions will
influence estimate.
Off-site air
concentration.
Industrial Source
Complex Model used
with modifications
applicable to area
source emissions.
This air dispersion
model is widely
accepted by the
Agency.
Meteorological input
data are site-specific.
Default values used
for risk estimation.
Input data can be site-
specific.
Inhalation rate: See Dust Inhalation, Table 7-5.

Evaluation: Substantial uncertainty is present in air emissions estimates; transport modeling is a smaller source of
uncertainty.
                                                           279

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doses were utilized:  26 ng, 350 ng, and 1,300 ng; the percentages of the applied dose



found in the liver were "circa 0.05," 1.7 + 0.5, and 2.2 + 0.5.  However, only the two



higher dose measurements were in  the range for which the authors reported that



"reproducible quantities of radioactivity in the liver were measured." The absorption



estimate in this report utilizes the geometric mean of the extreme values (0.07 and 3.0%)



for an estimate of 0.5% (an absorption  fraction  of .005).  Since this value is a factor of



four below the more reliably established higher dose values, absorption (and thus



exposure) may be underestimated by this factor. However, as the contaminated dirt was



in contact with rat skin for 24 hours, the experiment may over-represent absorption



compared with the case where skin would be washed periodically.



     The levels of 2,3,7,8-TCDD in dirt on skin are assumed to be equal to the 2,3,7,8-



TCDD in soil; thus, for the off-site scenarios, these estimates rely on the soil



concentration estimates for which the substantial uncertainties have been discussed above.



In summary, dermal exposure estimations rely on a number of parameters whose values



are not well established; principally:  skin levels of dirt, dermal absorption, and off-site



soil concentration estimates are subject to substantial uncertainty or site-to-site



variation. Therefore, the estimates for this pathway can be improved substantially if the



underlying data base is strengthened.  Table 7-7 is a summary of the uncertainties



related to dermal contact.



g. Soil Ingestion



     Estimated soil ingestion is based on field measurements, using trace elements, of



quantities of soil ingested by relatively small groups of children over brief



periods.Methodological issues in these studies remain to be addressed, particularly



ingestion estimates may have been  lower if dietary intake of the trace elements  was



taken into account and BAG is conducting research to refine soil ingestion estimates



obtained through trace element measurements.  Given the available data, 0.2 g/day is






                                            280

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                                TABLE 7.7.  LANDFILL ASSESSMENT
                                           DERMAL CONTACT
  Assumption/
    Method

Absorption
fraction.
    Approach

0.5%.
   Rationale

Based on Poiger &
Schlatter (1980).
   Uncertainty

May be low since data
supporting upper end
of range (396) more
reliable.
     Comments

Percutaneous absorption
is influenced by various
factors, including in-
trinsic skin properties
and environmental con-
ditions.
Exposure
duration.
7,300 - 20,000 days.
Contact rate.       1 mg/cm  -day.
Based on typical and
reasonable worst
case scenarios
assumptions.

Studies by Lepow et
at. (197S); Reels
et al. (1980) and
Hawley (1985).
Can vary for popula-
tions in rural
settings (especially
for adults).

Range reported in
literature is .5 to
1.5 mg/cm day.
Actual range is
probably much wider.
Time spent outdoors will
be function of geogra-
phic and climatic condi-
tions.

This approach does not
distinguish between
adults and children or
outdoor and indoor
exposures.
Evaluation:  The lack of supporting data and large influence of personal habits make this pathway very uncertain, by
    at least two orders of magnitude.
                                                         281

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used as a typical value for soil ingestion in young children.  Due to the behavior known



as pica, some children are known to be high ingesters of various non-food materials;



although no. quantitative data on soil ingestion are available for children known to



exhibit pica, the use of the high-end estimate of 1.0 g/day may better reflect such



behavior.



     Because of remaining methodological research  needs, no quantitative estimate of the



uncertainties in these estimates is made here.



     The gut absorption fraction for 2,3,7,8-TCDD from soil is a second major



determinant of exposure.  Data from experiments with rodents, reviewed in Chapter 5,



are consistent with, the 30% absorption fraction utilized for the pathway assessments.



Four of the five tested soils are in agreement with an absorption fraction of this



magnitude.   One soil sample showed absorption one or two orders of magnitude lower,



based  on limited data. Therefore, sites may be encountered where 2,3,7,8-TCDD in soil is



substantially less available than assumed in the scenario calculations.



     Soil ingestion exposure estimates also depend on the duration of the period over



which children  are assumed to ingest soil.  Data on soil ingestion by age are not



available, and the estimate that significant ingestion occurs between ages 2 and 6, is



broadly supportable on behavioral grounds.



     No measurement data are available on soil ingestion in infants (0-2 yrs. old) or in



older children or adults, and no ingestion is assumed for these groups.  While some  soil



ingestion will occur in these groups, e.g., through contact of soiled hands with food, it is



plausible that such ingestion is of a lesser degree than occurs in early childhood. If



Hawley's (1985) estimate that an adult ingests  an average 0.060 g/d of soil is used, after



accounting for differences in exposure duration (70 yr vs. 5, yr) and body weight (70 kg



vs. 17 kg), the adult soil ingestion risk is close to the estimated risk for children (at 0.2



g/d).





                                            282

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     Considering these uncertainties, the soil ingestion exposure estimates presented for




contaminated soil are plausible.  In the landfill scenarios, the estimated soil




concentrations are influenced by uncertainties, previously discussed, in the soil dilution




factor.  Table 7-8 is a summary of the uncertainties related to soil ingestion.




h. Beef and Milk Fat Ingestion



     Major determinants of 2,3,7,8-TCDD exposure through the intake of bovine products




are the  relative concentrations of dioxin present in milk or meat fat and the soil



concentrations in the cattle's pasture or pen.  No field data for these 2,3,7,8-TCDD




distribution ratios are available.  Jensen et al. (1981) determined 2,3,7,8-TCDD




concentrations in the fat of cattle fed a diet containing 2,3,7,8-TCDD present as a




contaminant of the herbicide 2,4,5-T. The 2,4,5-T was placed in a silica gel before




incorporation into a feed mixture.  After 28 days of feeding, the ratio of beef fat to




dietary 2,3,7,8-TCDD concentrations was about 4.  However, there was  no indication that




a steady state had been reached, and a kinetic model developed by the authors suggests




that 2,3,7,8-TCDD concentrations in fat at 28 days  would still be increasing rapidly at




this  time.  Additionally, there are no data on the absorption of 2,3,7,8-TCDD from the




herbicide-gel diet mix as compared with soil.  Based on comparisons in rodents,




absorption from diet may be  substantially higher than from soil.




     Jensen and Hummel (1982) similarly fed cattle 2,3,7,8-TCDD in 2,4,5-T added to




silica gel mixed into  the diet  for up to 21 days.  These limited data suggest a milk fat




to diet distribution ratio of 2,3,7,8-TCDD of as high as 6 (assuming that 2,3,7,8-TCDD in




milk cream is in the  fat component, where the cream is assumed to contain 30%  fat).




The authors'- data  are suggestive of a relatively rapid approach to a steady-state




concentration of 2,3,7,8-TCDD in milk.  Thus, while this ratio is unlikely to be at steady




state, it may be approaching it.  As noted above, the relative absorption of 2,3,7,8-TCDD




from the prepared diet and from soil has not been established.






                                           283

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                                 TABLE 7.8.   LANDFILL ASSESSMENT
                                              SOIL INGESTION
  Assumption/
    Method.
    Approach
   Rationale
   Uncertainty
     Comments
Soil contamination level:  see'Soil Dilution Factor (Table 7-1)
Child's inges-
tion rate- (2-6'
yeamold)..
Ingestion rate assum-
ed to vary from 0.2-
1.0 g/d.
The range selected
was primarily baaed
on the results of  two
field studies of soil
ingestion in children.
Field study method-
ology not fully
validated. Data from
several sources
indicate this range of
values for small
children.
Pica.children have been
estimated to. ingest
higher quantities (5 g/d).
Ingestion rate
for other, ages.
Absorption
fraction..
Ingestion assumed
to occur only, during
ages 2-6.
Absorption estimated
at 30%.
Mouthing tendencies
strongest and under-
standing of personal
hygiene low during'
ages 2-6.
Based on results of
2,3,7,8-TCDD absorp-
tion for several soil
samples in experimen-
tal animals.
Hawley estimates in-
advertent ingestion
may be 60 ug/d for
adults, which would
lead to an estimated
soil ingestion risk
over 64 years com-
parable to childhood
risk before age 7.

Four of five tested
soil samples showed
absorption of this
magnitude.  The fifth
sample indicated much
less absorption.  Thus,
estimate may not be
accurate for all soils
encountered.
Differences may  exist
in human and rodent
gut absorption.
Adults may inadvertently
ingest soil during
gardening and yard work.
Evaluation: The assumption of inadvertent soil ingestion for 2-6 year1 old children as. 0.2. g/d is a reasonable one based
on current data. This value does not account for children.with pica tendencies.  Future studies may revise this
estimate, since the methods used to derive the 0.2 g/d value are still being developed and evaluated. Adult: inadvertent
soil ingestion was not specifically included, although it might be argued that exposure at much reduced levels from
ages 7-10 would lead-to comparable'exposures to those during ages 2-6.
                                                         284

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     These studies are reviewed for comparison with the results of the Fries (1986) study




of beef fat/soil and milk fat/soil ratios for polybrominated biphenyls (PBBs) for cattle on




largely bare dirt lots in Michigan.  Fries reported beef fat/soil ratios of 0.3 to 0.4 for




beef cattle and milk fat/soil ratios of 0.02 to 0.06 for dairy cows.




     In Chapter 3, the data for PBBs from Fries (1986)  were used as surrogates to




estimate the distribution ratio for 2,3,7,8-TCDD.  Given the results of Jensen et al.




(1981) and Jensen and Hummel (1982), the difference between  the milk fat and dairy fat



ratios in Fries (1986) may not agree well with the situation for  2,3,7,8-TCDD.  (The




absolute difference between the 2,3,7,8-TCDD ratios and the PBB ratios probably also




reflects differences in absorption.)




     A variety of other  studies with chlorinated hydrocarbon compounds (reviewed in




Fries,  1982), while not allowing comparisons between beef fat and milk concentrations in




the same animals, do not suggest that the milk fat distribution ratios should be lower




than the beef fat distribution ratios.




     A second approach to distribution factors can be made using the data of Jensen et




al. (1981) and Jensen and Hummel (1982).  As noted above, absorption of 2,3,7,8-TCDD




from soil may be less than that from diet.  When rodent data are used 'for comparison,




results from Fries and Marrow (1975) indicate gut absorption of 2,3,7,8-TCDD in rats as




50% to 60% of the administered dose. On the other hand,  typical 2,3,7,8-TCDD




absorption from soil in rodents, as  discussed in Chapter 5,  is on the  order of 20% to 40%.




Very roughly, absorption from soil appears to be  half of that from diet.  If this same




difference applies to  cattle the results of  the Jensen studies can be used to estimate




fat/soil distribution ratios. If absorption  from soil is a factor of two lower than from




diet, and if 8% of dry diet is  soil, fat/soil ratios will also be a factor of 2/.08 = 25




lower than fat/diet ratios.  Accordingly, the data of Jensen et al. (1981) suggest a beef




fat/soil ratio of 0.16; actually, a higher value would be anticipated because the 2,3,7,8-






                                           285

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TCDD concentrations in Jensen et al. (1981) were probably not close to equilibrium.



Using the same approach, the Jensen and Hummel (1982) study suggests milk fat/diet



ratios on the order of 0.25, or somewhat higher if the milk fat TCDD concentrations



were not in equilibrium.



     Thus, using this second approach to the distribution ratios suggests a beef fat/soil



ratio similar to the 0.3 to 0.4 used in pathway calculations, but indicates that the milk



fat/soil ratio may be an order of magnitude higher than estimated.



     Methodologies exist to gather more reliable  data in this area, and would aid



substantially in reducing uncertainties.



     Several other factors enter into the calculation of exposures through milk and beef



contamination. Data on rates of milk and beef consumption were taken from surveys,



and form an adequate  basis for evaluating typical and reasonable worst-case product



intakes.



     The fraction of meat or milk intake coming from a local contaminated source was



selected on the basis of a survey of 900 rural farm households (U.S. Dept. of Agriculture,



1966).  The values selected are intended to apply to the situation of a farm family that



slaughters its own beef and maintains its own dairy cows.   In such a situation, the



fraction of intake from the farm can be expected to be substantial.  Additionally,  if



other families in the vicinity obtain beef and milk directly from a nearby contaminated



farm, similar percentages may reasonably apply.  The above analysis is not applicable to



individuals living near a contaminated site who obtain  their beef and dairy products from



regular commercial sources.  Such a situation can be expected to occur frequently.  If



beef and dairy products raised on a contaminated site are  sold commercially, population



risk from these activities should be addressed;  such an analysis was not part of the



scenario assessments here.



     Beef and dairy 2,3,7,8-TCDD concentrations will vary with the soil contamination






                                           286

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level.  In the off-site scenarios the uncertainty in estimating soil concentrations




influences estimated risks.



     Finally, data on human absorption of 2,3,7,8-TCDD from dietary sources are not




available, data on rodents' absorption from diet are used to estimate human absorption.




While this provides a basis for making  a plausible estimate, no quantitative evaluation of




uncertainty  is made.  Table 7-9 summarizes the  uncertainties associated with beef and




milk ingestion.




i.  Fish Ingestion



     The 2,3,7,8-TCDD concentration  in  fish tissue is estimated using  a distribution ratio




between fish tissue and sediment on the basis of information that  sediment levels are a




driving influence on fish tissue levels.   As discussed in Chapter 3, many factors  influence




2,3,7,8-TCDD levels in fish,  these include whether the fish is a bottom or surface feeder




and the position of the fish on the food chain.   A variety of site specific factors may




influence 2,3,7,8-TCDD concentrations in fish tissue that occur in different settings.




Therefore the use of a single fish/sediment distribution ratio, as done in the fish




pathway assessment,  must be recognized as a broad approximation.




     Chapter 3 suggests that  typical fish/sediment distribution ratios are in the range




1-10; some  reports cited indicate that the range  may be somewhat broader. Thus, given




the distribution factor of 5 issued in the pathway assessment, plausible concentrations of




2,3,7,8-TCDD in fish must include values from  1/5 to 2 times the calculated levels.  If




information on fish contamination is available for a specific site,  then adequate




measurement data should supercede values calculated using distribution factors.




     Two estimates of human fish consumption  were utilized, 6.5  g/d and 30 g/d. The 6.5




g/d is  a national average figure for fresh  water and estuarine  fish and shellfish.  Thus,




this figure represents a typical and relatively low (approximately 15-25 fish meals in a



year) consumption rate. The 6.5  g/d figure is based on data now  over a decade old,  and






                                            287

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              TABLE 7.9.   LANDFILL ASSESSMENT BEEF AND MILK INGESTION
  Assumption/
    Method
    Approach
   Rationale
Soil Contamination Levels: .See Soil Dilution Factor (Table 7-1)

Distribution Factors
   Uncertaintuv
                                                                                             Comments
   Beef
Used empirical data
for PBBs in feedlot
soils, giving beef
fat/soil ratio of
0.3 - 0.4 (Fries,
1985) as surrogate
for 2,3,7,8-TCDD
beef fat/soil data.
No 2,3,7,8-TCDD fat/
soil .field data
available.  PBBs
thought to be a
reasonable surrogate
compound (high lipid
partitioning; slow
removal from body).
Analogy with PBBs
may be in error.
However, alternate
calculation of factor
using laboratory data
on 2,3,7,8-TCDD in
feed and assumptions
on absorption from
soil support this
result.
                                                                                        As discussed in Section
                                                                                        C-2 of Chapter 3, details
                                                                                        of farm management are
                                                                                        very important
                                                                                        (e.g., duration of feed -
                                                                                        lot stay).
   Dairy
Empirical data for
PBBs in feed lot soils
gives milk fat/soil
ratios of 0.06 for
primiparous to 0.02
for multi-
parous cows. Used an
average of these, 0.04.
No 2,3,7,8-TCDD fat/
soil field data
available.  Beef fat
comparisons suggested
PBBs were reasonable
surrogate.
Analogy with PBBs
may be in error. An
alternate calculation
with laboratory data
on absorption on
2,3,7,8-TCDD from
feed, led to a higher
estimate of distri-
bution ratio.
Same as above (e.g.,
lactating dairy cows
pastured?)
Ingestion Rates

   Beef
   Dairy
Recommended 14.9 •
26.0 g/d based on
literature.
Recommended 18.8
43 g/d based on
literature.  Alter-
natively, 8.9 - 10.7
g/d for fresh milk
only.
Range provided en-
compasses averages
from five studies
based on three
surveys.

Range provided en-
compasses averages
from three studies
based on two sur-
veys.
Shape of distribution
of consumption not
well defined,
particularly the
extremes.

Study and survey
yielding 43 g/d (U.S.
EPA, 1981b) less well
documented than
remaining two studies
and survey. Ignoring
U.S. EPA (1981b),
range would be 18.8 -
 24.1 g/d. Again,
distribution not well
defined.
                                                         288

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                                       TABLE 7.9.  (CONTINUED)
  Assumption/
    Method
   Approach
   Rationale
   Uncertainty
                                                                           Comments
Absorption
fraction.
Adopted single value,
0.68.
Average of 2,3,7,8-
TCDD absorption from
commercial rodent
feed by rate (O.S) and
absorption from
gavage mixture with
corn oil and acetone
by rate (0.86).
No data on absorption
after ingestion of
animal products
available. Human and
rodent absorption may
differ.
Fraction of food
from local source
   Beef
   Dairy
                   44% of beef diet from
                   contaminated source.
40% of dairy products
from contaminated
source.
 Data available for %
of annual consumption
homegrown by rural
farm households (44%)
(U.S.  Dept.
Agriculture, 1966).

Same data source as
for "beef above.
 Likely to be sub-
stantial difference
between individuals.
Some from families
will get no beef from
local source.

Same concern as
noted for "beef"
above.
Evaluation: Analysis based on survey and experimental data on distribution ratio, absorption, and consumption. The
beef estimate is judged more reliable than milk estimate which may be low due to uncertainty in the distribution ratio.
Substantial uncertainty in soil concentration of 2,3,7,8-TCDD in off-site scenarios affects estimates. These estimates
apply only to individuals who raise their own beef or dairy cattle.
                                                         289

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fish consumption may have risen somewhat .in the .intervening period, however .this value



still appears Jo :be .a reasonably .typical value. This average value includes non-consumers



.of fish .in -the denominators; rates for consumers .of fresh water wish may be substantially



higher.  The .value of .3.0 g/d is based on more limited data on fish consumption by



'fishermen :or high consumers of locally caught fish  (see Chapter 4). These data



.demonstrate that the .intake for high consumers can exceed 30 g/d, with consumption



-rates/reported .by rsome .individuals being .on the order of .20.0 g/d.  Thus 30 g/d is a



^reasonable value for .regular .consumers of locally caught fish.



     •Kor.the reasonable worst, case analysis 1.0% of  the 3.0 g/d fish consumption was



assumed to be from the local, contaminated .source. For the  more  typical case a value of



10%.of'.6.5..g/d was adopted.  These figures .were chosen using the joint Judgment of "EAG



staff • as .survey .data were .not .available.  The figures .selected were regarded as



.appropriate for individuals who made .use of .locally caught fish.  Neither figure is



intended as an average .for the rural population. These estimates also assume that  the



.contaminated water bodies have adequate .biological capacity to support regular fishing.



Clearly, both fishing habits and biological .capacity  .of particular ponds and streams will



-vary-between .localities.   Thus, the.appropriateness of exposure estimates .from the fish



consumption pathwa.y is  best evaluated on .a .site specific basis where local data may aid



in 'the development of appropriate estimates. The reasonable worst case assumptions,



particularly that only 10% of .fish .eaten comes from the contaminated source may be



substantially low for an individual who engages in fishing to obtain .an important dietary



component.



      Rodent data on absorption .of 2,3,7,8-TCDD from the diet were used to estimate



human ;gut absorption for food products.  This .approach .provides  the basis for generating



plausible estimates of absorption but does not allow a quantitative Table 7-10 evaluation



of uncertainty.   For off-site scenarios there is .considerable uncertainty  in the estimated






                                           290

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stream sediment concentrations as is discussed separately above.  Table 7-10 is a



summary of uncertainties related to fish ingestion.



j.  Water Ingestion - Surface Water



     The surface water concentration of dioxin in  the pond scenarios is estimated using



a mass transfer calculation based in the level of 2,3,7,8 TCDD level in pond sediments.



Two resistance mass transfer calculations were used to estimate the movement from



sediment into the  water and from water into the air. The assumption is then made that



the loss of 2,3,7,8 TCDD from sediment to water equals the loss from water to air.  That



is, the water concentration  is assumed to be relatively constant, and the only significant



loss mechanism is assumed  to be volatilization.  Other potential losses, including



chemical, photolytic or biological degradation in the water column, are assumed to be



negligible. If other loss mechanisms are substantial the  estimated water concentration of



2,3,7,8-TCDD would decrease.



     The two resistance calculations lead to Equation 3-4  in Chapter 3. This relationship



depends on several parameters subject to uncertainty. The factor Kw, the water-side



mass transfer coefficient above the sediment, was estimated from using a  relationship



(3-5) empirically tested in a laboratory tank.  Among other factors, Kw is estimated to



be proportional to the 5/4th power of water depth to and  to be inversely  proportional to



fetch,  the length of the water body crossed by the  moving air.  A limitation in the



application of this relationship is that the experiments (Thibodeaux and Becker, 1982)



utilized a tank much smaller than the pond assessed here.  The fetch of the tank  was no



more  than 2.4 m vs. 64 m for the pond.  Furthermore, the  test data presented  by



Thibodeaux and Becker do  not clearly indicate that Kw increases with fetch beyond 2 m,



therefore the possibility exists that Kw is under-estimated by an order of magnitude due



to the extrapolation to the larger pond.  Similarly the lab data measured depth effects
                                           291

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                                TABLE 7.10.  LANDFILL  ASSESSMENT
                                             FISH INGESTION
  Assumption/
    Method
    Approach
   Rationale
   Uncertainty
                            Comments
Sediment Concentration: See Sediment Dilution Factor (Table 7-1)
Distribution
ratio.
Fish/sediment ratio
chosen. (Single value,
5).
Sediment concentra-
tion judged principal
determinant of fish
tissue concentration.
Ratio chosen also
encompasses fish/
water partitioning as
sediment concen-
tration tends to
determine water
concentrations.
Substantial range in
field and laboratory
measurements (<1-10);
equilibrium not
reached in most lab
experiments; species
specific; factors in
migration, feeding
habits, lipid content
etc., will affect
distribution. Dis-
tribution factor may
depend on sediment
level.
Judgment imposed in
choice of approximate
mid-point of range 1-10.
A less conservative
single value of 2 might
be justifiable as repre-
resenting preponderance
of higher values from
several studies.
Consumption
rates.
Used "customary* 6.6
g/d  for typical
scenarios and 30 g/d
 for reasonable worst -
case scenarios.
6.5 g/d  is most
commonly cited single
figure in EPA studies,
while 30 g/d
derived from sizable
study of fish
consumption by recre-
ational fishermen.
Differences in fish
consumption between
population groups has
been shown.  Much
individual variation in
consumption has been
shown.  Many rural
families will make no
use of locally caught
fish.
In actuality, the popu-
lation is likely to be
divided into those who
eat no freshwater/
estuarine fish and those
who eat more than the
6.6 g/d.
Fraction of fish
consumption
from local
sources.
     chosen.
Values chosen by
judgment in the
absence of data,  based
on how often fish
were thought to be
caught from the
scenario water bodies.
                                              Productivity in fish
                                              consumption between
                                              population groups has
                                              been shown. Much
                                              individual variation in
                                              consumption has been
                                              shown.  Many rural
                                              families will make no
                                              use of locally caught
                                              fish.
                        Large uncertainty; in
                       site-specific situations
                        local data must be used.
Evaluation:  Overall, the analysis represents a reasonable compromise between values for various inputs.  However,
substantial overall uncertainty exists in the estimates resulting from uncertainties in sediment levels, distribution ratios
and fish consumption habits of local populations.
                                                         292

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only up to 0.8 m and the assessed pond is assumed to have a depth of 5 m, and the

extrapolation of the  depth effects is uncertain.

     The factor K.La, the overall mass transfer coefficient for the air-water interface

was calculated using two resistance theory, requiring the use of the Henry's law

coefficient and assumptions about wind speed and other parameters.  These methods for

estimating volatilization  from the  water surface have been tested using comparisons of

predictions with measured emissions from liquid in waste disposal facilities (summarized in

Hwang,  1985).  The predicted volatilization based on two resistance theory calculations

were generally  within a  factor of  two of the measured values, with deviations reaching

an order of magnitude in some comparisons.  It should be noted that these empirical

tests were conducted with compounds much  more volatile than 2,3,7,8-TCDD.

     The parameter Ke, the sediment-side mass transfer coefficient, was estimated using

a relationship depending on the diffusivity of 2,3,7,8-TCDD and the sediment depth and

porosity.  The empirical support for this relationship is not reviewed in this report.

     Finally, the estimated water  concentration depends on Kj, the soil/water partition

coefficient for  2,3,7,8-TCDD. There is considerable uncertainty in this parameter as

discussed in the section  of this chapter discussing air emissions of 2,3,7,8-TCDD from

soil.

     If,  as calculated in Chapter 6, Kw is substantially higher than both Ke and

then Equation 3-4 for the water concentration,  Cw, of 2,3,7,8 TCDD is closely

approximated by the simplified relationship:
                               Fe_Ce
                          Cw = KLaLd                                     (7-2)
      Thus, when Kw is large it does not affect estimated water concentration which is

then directly or inversely proportional to the other factors discussed here. The water

                                           293

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concentration, Cw, is also proportional to the sediment concentration, Ce, of 2,3,7,8-



TCDD, which will .also involve substantial uncertainty for off-site calculations.



     In summary, the simplified model used to calculate the levels of 2,3,7,8-TCDD in



water was developed theoretically and has not been validated.  Several of the  parameters



entering into the model are themselves subject to substantial uncertainty. Table 7-11



-summarizes these uncertainties.



     The analysis for the scenarios with a stream are analogous to the pond calculations.



It is assumed that a one acre area of stream bed is contaminated with 2,3,7,8-TCDD at



the concentration of .01 times  the concentration in the landfill (see discussion of



sediment dilution factor).  For comparison this area would be equivalent to a  length of



0.8 km for a stream 5 m  wide.



     If 2,3,7,8-TCDD is  present in sediment to  an average depth  of  1 cm, 1 acre  of



contaminated sediment has a mass (at  1.7 g/cm^) of 6.9 x  104 kg. Noting the .001



dilution factor, 69 kg of  contaminated soil from the landfill  must have reached the



stream to produce this level of contamination.  For comparison the estimated eroded



material from the landfill (10 acre/grass covered) from Chapter 6 is 5600 kg/yr.   Thus



the estimate that only one acre of stream bottom is contaminated  is modest.  A much



larger area of contamination would be consistent with the  landfill erosion estimates



leading to higher estimates of 2,3,7,8-TCDD release.  On the other hand, the  assumption



used to calculate the sediment dilution factor are uncertain in regard to a stream of the



substantial size being assessed  here.  Additionally, the assumed stream depth (5 m) maybe



higher for the average depth of the stream envisioned in the scenario, and stream depth



has an inverse relationship to the estimated water concentration of 2,3,7,8-TCDD.



     The use of Equation 3-4 to calculate the water  concentration of 2,3,7,8-TCDD relies



on steady state assumptions that can be less strongly  defended in  the case of .a stream



flowing over sediment than in a pond situation. In consideration  of the issues mentioned






                                           294

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                                TABLE 7.11.  LANDFILL ASSESSMENT
                                SURFACE WATER CONTAMINATION
  Assumption/
    Method
    Approach
   Rationale
   Uncertainty
     Comments
Pond sediment
concentration.
Water concen-
tration - pond
See Sediment Dilution
Factor - Pond. (Table
7.2)

Used mass transfer
calculation to esti-
mate water concen-
tration as a function
of sediment concen-
tration. Model
depends on assumption
that water  concentra-
tion is steady state
reflecting balance
between sediment to
water and water to
air transfers.
Model calculations
address physical
processes involved in
determining transfer
to dioxin to the water
column. Moni-
toring data to esti-
mate water concen-
tration vs. sediment
concentration were
not present.
Model has not been
field tested, al-
though field data
exist to support the
water to air transfer
estimates at least for
more volatile
compounds. Some
model parameters e.g.,
soil water partition
coefficient have
substantial
uncertainty.
In these scenarios es-
timates of risks from
drinking pond water are
not presented because
this practice is con-
sidered unlikely to occur
commonly.
River sediment
concentration:
Water concentra-
tion - river.
See Sediment Dilution
Factor - stream.
(Table 7.2)

Used mass transfer
calculation similar to
stream approach but
adapted to a river
flowing at 1  m/s.
Contaminated sediment
assumed to cover 1
acre area of  stream
bed.
See above.
See above. The
assumption that
sediment covers only
1 acre area of stream
bed may be low given
the assumed landfill
erosion rates and
sediment dilution
factor sediment could
be contaminated over
much larger area.
Evaluation:  Applied a simplified theoretical model that has not been field validated, several model parameters are
subject to substantial uncertainty.  For river calculations the model assumptions assumed area of contamination is also
uncertain, however in the river scenarios calculated water concentrations are so low that uncertainties may not have
practical importance.
                                                         295

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above, the stream 2,3,7,8-TCDD concentrations have substantial added uncertainty beyond



the uncertainty present in the pond water calculations [see Table 7-11].



k. Ground Water Contamination



     Contamination of ground water through 2,3,7,8-TCDD leaching from a landfill into a



shallow underlying aquifer was assessed.  This assessment made several assumptions that



may lead to high estimates of ground water contamination.  Contaminated leachate was



assumed to directly enter ground water under the entire contaminated area.  Ground



water was assumed to move with a high speed of approximately 1 mile/year.  The



leachate reaching ground water was assumed  to be saturated with 2,3,7,8-TCDD at 8



ng/L.  Because of the high soil/water partition coefficient for this compound, in the



absence of cosolvent effects, a leachate concentration below the solubility level may be



anticipated for a landfill containing 1 ppb 2,3,7,8-TCDD or less.



     To calculate the retardation factor for 2,3,7,8-TCDD movement in ground water, the



estimated  organic carbon/water partition  coefficient of 486,000 was proportioned down by



the assumed fraction, 0.0002,  of organic carbon in the aquifer matrix.  Given the low



organic carbon content assumed, the procedure of estimating the media/water partition



coefficient by the fraction of organic carbon present is speculative. Other constituents



of the aquifer matrix may also retain 2,3,7,8-TCDD, leading to a higher matrix/water



partition coefficient.  This would lead to a lower estimate of the concentration  in ground



water. The value for the organic carbon/water partition coefficient is itself subject to



uncertainty of at least an order of magnitude.



     The  standard ground water transport model applied under these assumptions



predicted  very low levels of 2,3,7,8-TCDD in the water after a period of 100 years.  It



should be remembered that the analysis predicting even these low values used higher



range assumptions, however, co-solvent effects were assumed to be absent.  A



quantitative analysis of co-solvent effects which could increase transport of 2,3,7,8-






                                           296

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TCDD is not included here.  For a discussion of these effects see Chapter 3.  Table 7-12




summarizes uncertainties related to ground water contamination.




1.  Plant Uptake




     Estimates of exposure through human or animal consumption of plants growing in




contaminated soil are very uncertain.  As discussed in Chapter 3 and Chapter  4 (under




Description of Exposure Scenarios for Landfills) the limited available data indicate that




plants are capable of uptake  of 2,3,7,8-TCDD from soil.  However, because of the sparsity




of data only a speculative quantitative estimate of uptake was made.  The estimate




assumed plant concentrations on average, are on the order of 2% of soil levels.



However, the  substantial uncertainty in such a choice should be recognized as some data




indicate that plant roots may have levels exceeding soil levels.  See the  discussion in



Chapters 3 and 4 for more background on the variability of existing data on plant




uptake.




B.  INCINERATION SCENARIOS




     All exposures and risks resulting from incinerator stack emissions  are closely




proportional to the quantity of 2,3,7,8-TCDD in these emissions.  This  quantity is the




product of the emission rate per unit waste combusted and the plant size.  Wide




variation of the emission rate of 2,3,7,8-TCDD per unit waste combusted have been




reported with this assessment using a high and low emission rate differing by a factor of




300. Some data suggest that emission rates an order of magnitude either above or below




the range used in this assessment occur. Incinerator capacities also exhibit  much



variation with the smaller plant used  in this assessment having a capacity of 120  tons




per day and the large plant having a  capacity of 3000 tons per day; the latter being




selected to represent  planned facilities.




     Inhalation exposures were estimated using a modified Industrial Source Complex




model.  Both building wake effects and precipitation may increase ground level pollutant






                                           297

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       TABLE 7.12.   LANDFILL  ASSESSMENT -  GROUNDWATER CONTAMINATION
  Assumption/
    Method
    Approach
   Rationale
   Uncertainty
     Comments
Concentration of.
2,3,7,8-TCDD in
leachate.
Groundweter.
flow model.
Assumed.leachate
concentration equal to
the solubility of.
2,3,7,8-TCDD in
water. Solubility/of 8
ng/L assumed.
Standard, groundwater
transport model
applied, using a re-
tention factor for
2,3,7,8-TCDD based
on calculated
groundwater media/
water partition
coefficient, an
assumed  groundwater
flow rate, etc.
Presented, worst case
for 2,3,7,8-TCDD in
clean, water, noting
that the concentra-
tion, could be higher
for leachate with
substantial  organic
content.
Standard modeling
approach used by EPA
to calculate ground -
water concentrations.
In the absence of
cosolvent effects, the
concentration in
leachate is expected
to be lower than 8
ng/L for the soil
concentrations in
range shown in this
document (< 1 ppb).

Some of the
assumptions in the
model were selected
to maximize estimated
transport (e.g.,
groundwater flow
rate). Thus, model
predictions represent
worst case situation
in absence of co-
solvent  effects. Some
model parameters e.g.,
partition co-
efficients subject to
substantial uncer-
tainty.
See Chapter III for
discussion of importance
of cosolvent effects; no
quantitative analysis of
these effects has been
developed.
Evaluation:: This-analysis, using groundwater modeling-approach generally used-by EPA, indicated that minimal
transport of 2,3,7,8-TCDD in groundwater occurred. This was true even though the analysis incorporated some
assumptions that would .tend to maximize transport. Co-solvent effects would modify this analysis and increase
groundwater transport, however no quantitative analysis of this effect is yet available. Consequently, one should be
very cautious'of applying the conclusions reached here to an actual site, unless a great deal is known about the nature
    of the' landfill and leachate.
                                                          298

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concentrations and their effects on air concentrations and particulate deposition rates




were evaluated.  The uncertainties in air transport modeling are likely to be smaller than




uncertainties in the stack emission rates of 2,3,7,8-TCDD. Inhalation exposures are




assessed for an individual living 1/2 mile from the incinerator stack.  Maximum exposure




occurred very close to the facility and were estimated to be five times higher.  Exposure




levels were reduced  by two to three orders of magnitude at a distance of 60 miles.




     Exposure to 2,3,7,8-TCDD through beef ingestion, dairy products  ingestion, soil




ingestion by  children, and soil dermal contact (listed in decreasing order of estimated




exposure) were evaluated using similar assumptions  as in the land-related scenarios.




1.  Emissions Data




Data on 2,3,7,8-TCDD stack emissions from municipal waste incinerators (MWI) exhibit




wide variation, with the extremes of the range of data reported in Chapter 6 being 5.6 x




10~5 to .289  Mg/kg (ug 2,3,7,8-TCDD/kg waste combusted).  Data for one incinerator




operated without emission controls under starved air conditions showed  a total TCDD




release of 72.8 A»g/kg, with  no value reported for 2,3,7,8-TCDD for  this incinerator. In




comparison  1.1 /ig/ng total  TCDD emissions were reported for the incinerator that




showed 0.289 A
-------
incinerator showed 436 ng/g total TCDD;. this suggests a 2,3,7,8-TCDD content of fly ash




of approximately 20 ng/g (based on a rough ratio 20 ng total TCDD/ng 2,3,7,8-TCDD




obtained using the results in Table 6-11).



2.. Selection of Model Incinerator and Exposure Scenario




     Incinerators of sizes 120 TPD and 3000 TPD were selected for the scenarios. These




represent a common smaller size and one- of the largest size incinerators. These sizes are




appropriate considering both the existing stock of incinerators and incinerators now being




constructed or planned.




     The analysis assumed that  the large incinerator had a 2,3,7,8-TCDD emission rate




(0.001 Mg/kg) at the lower end of the range of measured values.  If an incinerator of




this size exhibited a high end value  of emission, 2,3,7,8-TCDD release would be a factor




of 300 higher. The analysis  for the small incinerator scenario used the highest measured




stack emissions of 0.289 /*g/kg.  Thus, while even higher  release  rates might be seen




from uncontrolled incinerators operating under certain conditions, this 2,3,7,8-TCDD




release is a reasonable worst case estimate for an incinerator of this size.




     The two incinerator models selected should be regarded as illustrative examples with




the variability of measured emission rates of 2,3,7,8-TCDD kept in mind.  No review was




conducted to determine the degree the engineering parameters  (e.g., stack  height) vary




between incinerators.  Table 7-13 summarizes the uncertainties related to plant sizes and



emission rates.




3. Inhalation and Surface Deposition




     Using the model incinerators and emissions estimates discussed above, pollutant




dispersion models were used to  predict  air concentrations and surface deposition rates for




2,3,7,8-TCDD.




     The transport model utilized was a modified industrial source complex (ISC) model




which took into account two features that may increase ground level pollutant






                                           300

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concentrations.



     a)   Buildings near the incinerator produce a wake effect leading to higher ground




          level concentrations.




     b)   The modified ISC model incorporated a "tipdown wash" effect through which




          precipitation increased surface pollutant concentrations.




     The ISC models are standard tools utilized by EPA to estimate pollutant




concentrations from air emission source.  A proprietary version of the model was used to




incorporate tipdown wash and EAG has not reviewed the procedure through which this




effect was calculated,  although the effects of tipdown wash on the concentration in the




scenario was small.




     An assumed particulate size distribution is required to calculate surface deposition




of the particulate emissions. The size distribution assumed is one used by the Office of




Air Quality Planning and Standards in  the modeling  of incinerator emissions; EAG has not




reviewed the variability of particulate size distributions for incinerators.




     Comparison between predicted surface deposition rates using different model




assumptions (with or without effect of precipitation, over different averaging periods)




produced similar results; the estimated  quantities of particulate from wet deposition are



smaller than those from dry deposition.




     Predicted air concentrations and deposition rates at 1/2 mile (0.8  km) from the site




are used for risk calculation.  These concentrations reflect annually averaged




concentrations utilizing local meteorologic data for the two model incinerators (in Florida




and Virginia). It should be noted that the highest 2,3,7,8-TCDD concentrations were



predicted to occur at 200m from the incinerator stack and  that these levels were




approximately a factor of five higher than  those predicted at 0.8  km.  For comparison




estimated concentrations at 100 Km from the site are also calculated and were generally




two to three orders of magnitude lower than levels at 0.8 km. Table 7-14 summarizes






                                           301

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                              TABLE  7.13.  INCINERATOR ASSESSMENT
                                        AIR EMISSIONS ESTIMATE
  Assumption/
    Method
    Approach
   Rationale
   Uncertainty
                                                    Comments
Incinerator
capacity.
Two plant sizes 120
tons/d, and 3000
tons/d were assessed;
these plants represent
an existing facility in
Virginia and a planned
facility in Florida,
respec- tively.
Smaller plant size is
typical of current
facilities. Larger
plant represents a
large, planned facility.
Existing and planned
plants vary widely in
sice. Many existing
plants are less than
120 tons/d.  3000
tons/d is near upper
limit of  planned plant
sizes.
Methodology can be
applied to plants of all
sizes.
Emission rate.
2,3,7,8-TCDD
concentration in
fly ash.
2,3,7,8-TCDD emission
rate for smaller plant
taken as 0.289 ug/kg
waste, based on
measurements at the
Virginia facility. For
larger plant, the
emission rate used is
0.001 ug/kg.
The emission rate for
VA facility repre-
sents the high end of
measured incinerator
emissions. The
emission rate of 0.001
ug/kg repre- sents
the lower end of
measured incinerator
emissions and is
thought to reflect
what can be expected
with new technology.
A single value of 0.55    0.55 ng/g is the
ng/g was used for
this concen- tration
in calcu- lations with
both incinerators.
average of measured
values presented in
Chapter 6, exclud-
ing one high end
point.
Measured incinerator
emission rates cover a
very broad range from
less than 0.001 ug/kg
up to 0.289 ug/kg,
with some data
suggesting that even
higher emissions may
be seen under some
incinerator operating
conditions.
A range of 0.07-2.3
ng/g has been ob-
served with the
exception of the one
high point, 100 ng/g
seen in a pyrolysis
test. Some addi-
tional data on total
TCDD measurements
suggest values well
above 2.3 ng/g may
occur.
Exposure estimates may
be scaled with estimated
emission rate. It should
be noted that if an
incinerator a high end of
the size range were to
have a high end emission
rate, exposures would
substantially exceed
those in either of the
scenarios pre- sented
here.
Evaluation: The scenarios chosen are appropriate for both incinerator size and 2,3,7,8-TDD release. However, the
large variability in both plant size and release rate should be noted.  If a large facility had a high emission rate
pathway exposures much higher than those calculated here would be anticipated.  Conversely, for a small plant with
    low emissions, much  lower concentrations would be expected.
                                                          302

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                             TABLE 7.14.  INCINERATION ASSESSMENT
                             INHALATION AND SURFACE DEPOSITION
  Assumption/
    Method
    Approach
   Rationale
   Uncertainty
                                                                           Comments
Estimate
transport of
stack emissions.
Applied industrial
source complex model,
the program-version
used evaluated "tip
down wash" effect of
precipitation and
assumed that a
building of height
equal to the incin-
erator stack was near
by.
This air dispersion
model is widely
accepted by Agency.
Both "tip down wash"
and presence of a
building as tall as the
stack may in- crease
ground level pollutant
concentra- tions.
Input data are site-
specific for meteor-
ologic conditions.
The presence of a tall
 building near the
incinerator stack may
not be typical.
Predicted surface
deposition rates with
or without the effects
of precipi- tation
were similar.
P articulate
distribution.
Point where
deposition and
inhalation are
evaluated.
Adopted sice distri-
bution used in OAQPS
modeling for incin-
erators.
Inhalation exposures
and surface deposi-
tion evaluated at
distance 1/2 mile (0.8
km) from in-
cinerator stack.
Data was specific to
incinerators.
Exposures at this
distance represent
rather direct ex-
posure to stack
emissions, but not the
maximum estimat- ed
pollutant concen-
trations.
Variability of sioe
distribution has not
been assessed. Size
distribution will have
strong influence on
deposition rates.

Exposures at 200m
from stack were cal-
culated to be five
times greater than at
0.8 km.  For compari-
son, concentrations at
100 km from stack
were also calculated
and are 2 to S orders
of magnitude lower
than at 0.8 km.
Inhalation rate.
See landfill dust
emissions chart.
Evaluation:  The analysis is appropriate for determining air concentrations and surface deposition rates on a family
relatively near incinerator stack emissions. The assumption that a building of height equal to the incinerator stack is
present leads to higher estimated concentrations near facility.  Concentrations 1/2 mile from stack are used in exposure
    calculations.  At longer distances exposures will  be substantially lower.
                                                         303

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the uncertainties related to inhalation and surface deposition.



4. Surface Water Contamination



     In different scenarios either a small pond or a large river are assumed to be located



at a distance of 1/2 mile (0.8 km) from the incinerator stack.  The sizes and  locations of



these water bodies should be seen as examples that can be modified in site-specific



assessments.  2,3,7,8-TCDD transfer to the water bodies through vapor absorption and



through wet and dry particulate deposition were estimated.



     Vapor absorption into river water was estimated using two-resistance theory for



mass transfer from the  air to the water body which was briefly discussed under the



surface water section of the landfill scenarios.  As noted there, calculations of this type



have been  shown to provide results correct to an order of magnitude or better for



compounds more volatile than 2,3,7,8-TCDD, for which data is  available.  The calculation



assumes that dissolved phase losses to sediment or biodegradation do not occur; in reality



some such  loss  is possible.



     The mass  transfer calculation made the  simplifying assumption that water levels of



2,3,7,8-TCDD  are assumed to be low in comparison with equilibrium concentrations. That



this assumption is appropriate can be seen by comparing estimated river water 2,3,7,8-



TCDD concentrations to the concentrations calculated for the pond water.



     Average river water concentrations are obtained by dividing the vapor absorption



rate by the quantity of water flow. This  same  methodology can be applied to rivers or



streams of differing size.



     Vapor absorption into lake water was estimated using Henry's Law and assuming an



equilibrium relationship between 2,3,7,8-TCDD in the air and water.  The equilibrium



water concentration was calculated using the estimated average vapor concentration of



2,3,7,8-TCDD  obtained by applying the wind frequency factor to the  modeled vapor



concentration.  This approach, while judged  reasonable may not fully  account for the






                                           304

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time varying nature of vapor concentration.  This calculations does not take into account



any loss of 2,3,7,8-TCDD to sediments; such loss would lead to lower estimated water



concentrations.



     Pond water levels of 2,3,7,8-TCDD due to  deposition of contaminated particulates



are calculated based on the  deposition rates from the ISC model discussed above.



Concentrations of  contaminated particulate in the water depend on the effective period



for which the particulate material remains in the water column.  As data are not



available to estimate this lifetime, a simplified theoretical model is used.  The deposition



rates from the ISC model allow calculation of an effective settling velocity of the



particles in the air.  Then physical principles allow calculation of the  settling rate  of the



same particles in the water  column. The particles are assumed to remain in the water



until sufficient time has passed for them to  settle to  the bottom.



     As noted, this is a  simplified model and data do not exist to establish that direct



settling is the principal loss mechanism for particulate in water.  Particle agglomeration,



effects of biota or photolysis  in water could alter the model predictions. Furthermore,



the model does not take into account mixing of  particulate within the water column or



resuspension of particulate  from the sediment.  Levels of 2,3,7,8-TCDD in  pond sediment



may accumulate and may then influence  water concentrations of 2,3,7,8-TCDD.



     Particulate deposition  rates  into rivers  are the same as used in the pond scenario,



but with the plume from the  incinerator  (as in the vapor case) covering only a calculated



area of the river surface. Water concentrations are obtained from the deposition rate



and water flow rate.



     A water/fish bioconcentration factor (BCF) of  10,000 was used to estimate



concentration of 2,3,7,8-TCDD in fish living in  the pond and river.  The uncertainties in



water concentrations translate directly to uncertainties in fish concentrations.  The BCF



of 10,000 represents a median value from a  wide range of reported values (Schaffer,






                                           305

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1985). In 1984, EPA proposed a BCF of 5,000 for use in the Water Quality Criteria (U.S.



EPA, 1984a).  More recently, laboratory studies have measured BCFs of 66,000 for carp



and 97,000-159,000 for fathead minnows (Cook, 1987). The more recent data suggest that



the BCF could be much higher than assumed, and the overall range suggests that this



factor is a major source of uncertainty. Table 7-15  is a summary of the uncertainties



related to surface water concentration.



5. Soil  Contamination from Emissions



     Both particulate deposition and vapor absorption of 2,3,7,8-TCDD to soil are assumed



to occur at sites 0.8 km from the model incinerators, the same locations evaluated for



the inhalation pathway.  Particulate deposition rates  are evaluated using results of the



ISC type model discussed above. Disappearance of 2,3,7,8-TCDD from the surface soil



through all loss mechanisms is accounted for by the  0.06 yr"1 rate constant that was



discussed above. Given the values for the deposition rate and the loss rate, the quantity



of 2,3,7,8-TCDD in the soil  as a function of time is calculated.   It is assumed that the



2,3,7,8-TCDD will remain in the top 1  cm depth of soil.  Data to evaluate this assumption



for nontilled soils have not been evaluated.



     A  partitioning calculation is used to estimate 2,3,7,8-TCDD levels in soil due to



vapor absorption. Here the assumption is made that the soil and air 2,3,7,8-TCDD



calculations will be in equilibrium.  This assumption leads to  maximum soil concentrations



attainable through vapor absorption for a fixed value of the air/soil partition  coefficient.



The time required to approach equilibrium was not estimated, and if this time proves



substantial compared to the estimated half-life of about 10  years for loss of 2,3,7,8-TCDD



from soil, soil levels will be overestimated.  Estimated soil concentrations are



proportional to the soil/air partitions coefficient which was estimated from the soil/water



partition coefficient for 2,3,7,8-TCDD  which is subject to substantial uncertainty as



discussed earlier.  The uncertainty in the assumed rate of soil ingestion, dermal contact,






                                           306

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     TABLE 7.15.   INCINERATOR ASSESSMENT SURFACE WATER CONTAMINATION
                               BY INCINERATOR STACK EMISSIONS
  Assumption/
    Method
    Approach
   Rationale
   Uncertainty
                                                                                           Comments
Location of
water body.
Either a small pond
or a large river are
assumed to be present
at 0.8 km from the
incinerator stack.
Addresses potential
exposure pathway.
Site-specific situation.
Distance of 0.8 km
reflect* direct
exposure to stack
emissions but not
maximum ground level
concentrations.
2,3,7,8-TCDD
vapor concen-
tration and
particulate de-
position rate.
See:  Inhalation and
Surface Deposition.
(Table 7.14)
Pond water con-

centration due to
vapor absorp-
tion.
Estimated by Henry's
Law calculation which
assumes equilibrium
has been reached.
Model reflects
physical processes
affecting water
concentration.
Absorption to
sediment not
accounted for.
Equilibrium may not
be achieved in
practice. These would
lead to lower
estimates of water
concentration.
Pond water
concentration
due to par-
ticulate
deposition.
Assumed that partic-
ulate deposited onto
water surface will
remain suspended for
a period equal to
calculated direct
settling time for
particulate through
the water column.
Idealized physical
model which accounts
for the phenomenon
that small particu-
lates will remain in
water column for
longer period.
Movement of water
and loss mechanisms
for five particulate
sices may alter
estimates. Model is
not field validated.
                                                        307

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                                       TABLE 7.15.  (CONTINUED)
  Assumption/
    Method
    Approach
   Rationale
   Uncertainty
                                                                            Comments
River water con-
centration due to
vapor.
Applied mass transfer
calculation account-
ing for water move-
ment.  No steady
state assumption is
made; instead calcu-
lation relies on water
concentration being
low (relative to
potential steady state)
to estimate transfer.
Model reflects phy-
sical process that will
affect water
concentration.
Measurement data are
not available.
Partition coeffi-
cients and other
model parameters
subject to uncer-
tainty. Model is  not
field validated.
River water
concentration
due to par-
ticulate
deposition.
Used particulate
deposition rate and
water flow rate to
calculate concen-
tration.
Physically appro-
priate.
Appropriate calcula-
tion for average river
water concen-
tration given esti-
mated deposition rate.
Bioconcentra-
tion factor.
10,000.
Median of reported
values.
Range of reported
values very wide.
Recent data suggest it
could be as high as
159,000.
Evaluation: Calculations of water concentration due to vapor absorption are uncertain due to uncertain parameters in
model, and the fact that the models have not been field validated.  Particulate concentration in pond also uncertain as
settling rate calculation is not known to be appropriate.  River water particulate concentration better established as
this estimate does not rely on unproven models.  Bioconcentration factor is a major source of uncertainty, possibly
causing an underestimate of risk by as much as a factor of 16.
                                                           308

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beef exposure and dairy exposure are discussed under the landfill scenarios. Table 7-16



is a summary of the uncertainties related to soil contamination levels due to incinerator



emissions.



6.  Dairy Product Exposure Following Deposition on Plants



     The calculation of exposure through milk produced by cows grazing in the vicinity



of an incinerator utilizes the model developed by Connett and Webster (1987).  These



authors have adapted  a model previously developed for radionuclides to address 2,3,7,8-



TCDD. The major components of the model are:



     (a)  The deposition rate of 2,3,7,8-TCDD for which this report utilizes the air



          transport model estimates discussed above.



     (b)  The concentration in fodder, which depends on an assumed half-life of 14 days



          for 2,3,7,8-TCDD following deposition.  This  value was based on weathering



          considerations by analogy with radionuclide modeling. Experimental data on



          2,3,7,8-TCDD were not available for evaluation of this half-life.



     (c)  The effective grazing area of a cow (surface area of vegetation consumed in a



          day, which was  estimated using the productivity of a field  for hay production



          (kg/m^ d) and the food consumption rate of a milk producing, pastured cow.



          The authors note that effective grazing area will vary regionally and upper



          New York  State values were used.



     (d)  A pharmacokinetic model, based on the experimental data of Jensen et al.



          (1981) for lactating cows fed 2,3,7,8-TCDD was used to estimate the transfer



          coefficient between fodder and milk assuming 33% bioavailability of the dioxin



          from fodder on  which particulate was deposited.  EAG regards the  formulation



          of this model as "appropriate" for estimating 2,3,7,8-TCDD exposure via this



          pathway. Further, the assumptions made by the authors concerning  individual



          model  parameters are felt to be  reasonable; the data for selecting parameter






                                           309

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              TABLE 7.16.  INCINERATOR ASSESSMENT SOIL CONTAMINATION
                     LEVELS RESULTING FROM INCINERATOR EMISSIONS
  Assumption/
    Method
                      Approach
                          Rationale
                          Uncertainty
                                                                          Comments
12,3,7,8-TCDD
deposition rate
to soil (particu-
late)

Soil Concentra-
tion from
participate
deposition.
See Inhalation and Surface Deposition
Constant deposition
over a 70 year period
assessed. 'First order
decay constant 0.06/y
assumed for 2,3,7,8-
TCDD in soil.
2,3,7,8-TCDD assumed
to remain in top 1 cm
of-soil.
70 years selected to
represent long-term
operation. The decay
constant, taken from
Young (1983), was
based on field obser-
vation of disappear-
ance of 2,3,7,8-TCDD
•through all pathways.
A 1 cm mixing depth
represents case where
no agricultural prac-
tices are present.
Field data demon-
strate that environ-
mental half-life of
2,3,7,8-TCDD is a
substantial period of
years but do not
allow precise esti-
mation of decay rate.
Data on mixing depth
of 2,3,7,8-TCDD
applied to soil sur-
face though particu-
late deposition are
not available.
Vapor absorp-
tion by soil.
Soil concentrations
estimated parti-
tioning calculation
using calculated vapor
concentrations (see
Inhalation and Surface
Deposition).  The
parti-
tioning calculation
yields maximum soil
levels consistent with
vapor concen-
trations.
A upper bound on
soil concentration
was desired in the
absence of a more
refined model.
Soil concentrations
may be less than cal-
culated by partition-
ing depending on the
time required to
approach equilibrium.
Soil/air partition
coefficient was
derived from soil/
water coefficient
which is subject to
substantial uncer-
tainty.
Soil, beef and dairy
ingestion rate
Duration of ingestion    - See Landfill Scenarios.
Gut absorption from soil
Dermal contact rate with soil
Dermal absorption       - See Dermal Contact for Landfill Scenarios.

Evaluation: The estimated soil concentration is proportional to 2,3,7,8-TCDD emission rate and depends on air
transport modeling, which are discussed in Tables 7.13 and 14. For the air concentrations assessed, soil concentrations
    and associated pathway exposures are likely to be less than those  calculated in the case of vapor absorption.
                                                         310

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          estimates, particularly for persistence on vegetation may be weak.  Further, as




          the model has not been validated with field data, an overall quantitative



          evaluation of uncertainty is not possible.




7.  Land-Disposed Ash




     The quantity of fly ash produced by the modeled incinerators is calculated using a




standard particulate emission factor and factors for control equipment efficiency.  The




quantity of landfilled ash generated from 35 years of  incineration operation is used as an




average accumulation period to  estimate landfill size for this analysis.




     The landfill area estimates were derived from the generation quantity and an




assumed disposal depth of 10 ft. Changes in depth or generation time  would change the




area estimate proportionally.




     The contamination level in the ash (assumed to be 0.5 ng/g) was derived as a mean




from a number of incinerators.  The  range was 0.07 to 100 ng/g.




     Exposures to ash disposal were evaluated for the same pathways as done for




landfills.  The same procedures  were  assumed to apply after changing only the size of




the landfill and contamination level.  This assumption could cause uncertainty in several




ways.  The physical properties of ash may differ from regular soils causing differences in




transport via surface runoff or windblown dust.  The  materials  handling associated with




ash could cause greater emissions than the soil scenarios where dust generation was




assumed to occur as a  result of wind  only. The transport of ash in trucks could cause




fugitive emissions leading to exposure.  The  bioconcentration of fly ash to fish may




differ from that of normal sediments. In general, these differences suggest that the




similar treatment of soil and ash leads to underestimates of risk. The bioconcentration




issue is  an  exception in that it is unknown if this causes under-  or over-estimates of




risk. In the calculation of ingestion exposures, the same bioavailability factor is used for




ash as for soil. There is much less data on availability of  2,3,7,8-TCDD  from ash than






                                           311

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from soil and as discussed in Chapter 5, the interpretation of the existing ash



bioavailability data presents difficulties.  Significant uncertainty exists in this area.



     Dust emission from disturbance of ash during the process of landfilling have been



estimated. These  estimates take into account the following activities.  These activities



are in effect. A scenario for landfilling activities and the extent of these activities  was



calculated to reflect the quantity of ash being disposed.



     (a)  Vehicle traffic:  Truck traffic over a unpaved road containing fly ash



          particulate generates dust.  A standard dust emission factor for traffic  on an



          unpaved road  was obtained from EPA (1985).  The authors of EPA (1985)



          assigned the road dust model a rating of "A" indicating that it was based  on



          substantial field  data obtained using appropriate methodologies.  The



          calculations here were based on the passage of 10 heavy trucks per day over



          an on-site unpaved road at a 16 kph speed. Ash content of the road was



          assumed to be 20%,  which  would be dependent on the specific character  of the



          road  being utilized.  As fly ash may be finer than road dust in general, these



          particulates may become airborne to a greater extent than calculated in this



          model.



     (b)  Unloading of ash at the landfill was assessed using particulate emission factor



          for handling of silt containing aggregate from EPA (1985).  This emission



          factor was assigned a rating of "C" by EPA (1985) indicating that extensive,



          appropriate field data were not available for the factor.  This calculation



          requires values for mean wind, drop height and several other parameters.



          Values  for these parameters were selected to be consistent with the



          calculations for wind generated dust and to corresponding to dumping  of fly



          ash from dump trucks.  Parameters used should reflect local conditions in any



          site-specific applications.






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     (c)   Spreading operations. An emission factor developed for agricultural tilling



          (EPA, 1985) was judged the available factor that most closely resembled the



          process of spreading fly ash.  The emission factor was given a rating of "A" or



          "B"  by EPA (1985) indicating that substantial appropriate data was available to



          estimate the emission factor.  However, the use  of this factor for spreading of



          fly  ash has not been validated.



     (d)   Emissions due to windblown emissions from trucks transporting fly ash on site



          (i.e., release from the truck's load) was calculated using an emission factor



          approach.  However, as it is thought that fly ash is normally wetted before



          transportation, an adjustment for this was made. Emissions were  calculated by



          assuming that a moving truck could be considered as comparable to a pile of



          material subjected to wind moving at the speed  of the truck (physically



          appropriate).  However, the adjustment for wetting was based on assumption



          that emissions could be calculated, by analogy, with a material pile under the



          circumstance where  rain fell 364 days/year. Data to evaluate the



          appropriateness of this  assumption are not available.



     Table 7-17 is a summary  of  the uncertainties  related  to land disposed ash resulting



from incinerator use.
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                                  TABLE 7.17.  LAND-DISPOSED ASH
  Assumption/
    Method
                      Approach
                          Rationale
                          Uncertainty
                                                                                            Comments
Quantity of ash
generated .by
incinerator and
landfilled.
Contamination
level.

Treatment of ash
vs. soil.
Used uncontrolled
emission factor to
estimate fly ash
production, assumed
captured for dis-
posal.  Quantity of
ash generated in 35
years calculated.

0.5 ng/g.
Assumed ash behaves
same as soil.
Based on standard
emission factor.
Landfill assumed to
receive long-term ash
generation.
Mean of available
data.

Lacked data to
.account for .differ-
ences.
Ash generation/ton
combusted material
may vary between
incinerators.
Assumption that ash
is placed in one
landfill may not be
typical.

Range is 0.07 to 100
ng/g.

Dust generation
during disposal and
transport likely to be
higher.
Evaluation:  Range of contamination levels spans three orders of magnitude, so this is a major source of uncertainty.
    Treatment of  ash  like soil may cause slight underestimates of risk.
                                                        314

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Office, Cincinnati, OH. EPA-600/8-84-014F.  NTIS PB86-122546.

U.S. EPA. (1985e)  Pollutant sorption to soils and sediments in organic/ aqueous solvent
systems. Office of Environmental Processes and Effects Research, Athens, GA.
EPA-600/3-85-050.  NTIS PB85-242535.
                                         329

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U.S. EPA (1985f) Modeling remedial actions at uncontrolled hazardous waste sites. Office
of Solid Waste and Emergency Response, Washington, D.C. EPA-540/2-85-001.

U.S. EPA (1985g) Proceeding of the eleventh annual research symposium, Leaching
potential of 2,3,7,8-TCDD in contaminated soils. U.S. EPA Hazardous Waste Engineering
Research Laboratory, Cinn, OH. EPA-600/9-85-013.

U.S. EPA.  (1986a)  Development of advisory levels for polychlorinated biphenyls (PCBs)
cleanup.  Office of Health and Environmental Assessment, Washington,  DC. EPA-600/6-86-
002. NTIS PB86-232774/AS.

U.S. EPA.  (1986b)  Development of risk assessment methodology for ocean disposal of
municipal sludge. Office of Health and Environmental Assessment, Environmental Criteria
and Assessment Office, Cincinnati, OH. (ECAO-CIN-492).

U.S. EPA.  (1986c)  Guidance manual for health risk assessment of chemically
contaminated seafood.  Puget Sound Estuary Program,  U.S. EPA Region X, Seattle, WA.,
Tetra Tech, TC-3991-07, June 1986.

U.S. EPA.  (1986d)  National dioxin study, tier 4: combustion sources.  Office of Air
Quality Planning and Standards, Research Triangle Park, NC. EPA-450/4-84-014g.

U.S. EPA.  (1986e) Air quality modeling analysis of municipal waste combustors. Internal
report dated November, 1986, prepared by  PEI Associates, Inc. and H.E. Cramer Company
Inc. for the Office of Air Quality Planning and  Standards, Research Triangle  Park, NC.

U.S. EPA (1987) Report on 2,3,7,8-TCDD Body  Burdens. Submitted  by Technical Resources,
Inc. to the Exposure Assessment Group, Office of Health and Environmental Assessment,
Washington, DC., under EPA Contract No.  68-02-4199.

U.S. EPA (1987a) Guidance manual for assessing human health risks  from chemically
contaminated fish and shellfish. Draft report C737-01, dated December 1987, submitted to
the Office of Water, Washington, DC, by PTI Environmental Services Inc. under EPA
contract No. 68-03-3319.

U.S. EPA (1987b) National dioxin study, tier 4:  combustion sources - engineering analysis
report, Office of Air Quality Planning and  Standards, Research Triangle Park, EPA-450/4-
84-014h, September 1987.

U.S. EPA (1987c) Municipal waste combustion study - emission data base for municipal
easte combustors, Office of Solid Waste and Emergency Response, EPA/530-SW-87-021b,
June 1987.

U.S. EPA (1987d) Memorandum and attachments titled "Preliminary  risk calculations for
polychlorinated dibenzo-p-dioxins using the ECAO-Cin risk assessment methodology for
municipal waste combustors", from Larry Fradkin, Acting Branch Chief, Systemic
Toxicants Assessment Branch, Environmental Criteria and Assessment Office, to Michael
Callahan, Office of Health and Environmental Assessment, February 9, 1987.

van den Berg, M.; Olie, K.; Hutzinger, O.  (1983)  Uptake and selective retention in rats
of orally administered chlorinated dioxins and dibenzofurans from fly-ash  and fly-ash
extract.   Chemosphere  12:537-544.

                                         330

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van den Berg, M.; Vroom, A.; van Greevenbroek, M.; Olie, K.; Hutzinger, O. (1985)
Bioavailability of PCDDs and PCDFs adsorbed on fly ash in the rat, guinea pig, and
Syrian golden hamster. Chemosphere  14:865-869.

Vick, R.D.; Junk, G.A.; Avery, M.J.; Richard, J.J.; Svec, H.J.  (1978)  Organic emissions
from  combustion of combination coal/refuse to produce electricity.  Chemosphere
7:893-902.

Wade, J.C.; Heady, E.O. (1978) Measurement of sediment control impacts on agriculture.
Water Resources Research:  14:1-8.

Walters, R.W.; Guiseppi-Elie, A.;  Yousefi, Z.; Means, J.C. (1987) Sorption of Dioxin to
Soils. Chemosphere (in press).

Ward, C.T.; Matsumura, F. (1978)  Fate of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in
a model aquatic environment.  Arch. Environ.  Contam. Toxicol. 7:349-357.

Wark, K.; Warner, C. (1981)  Air pollution--its origin and control.  New York, NY:
Harper and Row Publishing Co.

Weber, H.; Poiger, H.; Schlatter, C. (1982) Fate of 2,3,7,8-tetrachloro-dibenzo-p-dioxin
metabolites from dogs in rats. Xenobiotica 12(6):353.

Webster, G.R.B.; Friesen, K.J.; Sarna, L.P.; Muir, D.C.G.  (1985)  Environmental fate
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14(6/7):609-622.

Webster, G.R.B.; Muldrew, D.H.;  Graham, J.J.; Sarna, L.P.; Muir, D.C.G.  (1986) Dissolved
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Wipf, H.K.; Schmid, J. (1983) Seveso - an environmental assessment, In: Tucker, R.E.;
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Wipf, H.K.; Homberger, E.; Neuner, N.; Ranalder, U.B.; Vetter,  W.; Vuilleumier, J.P.  (1982)
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Wroblewski, V.J.; Olson, J.R.  (1985)  Hepatic  metabolism of 2,3,7,8-tetrachlorodibenzo-p-
dioxin in the rat and guinea pig.  Toxicol. Appl. Pharmacol. 81:(2)231.

Yalkowsky, S.H.; Flynn, G.L.; Amidon, G.L. (1972)  Solubility of nonelectrolytes in polar
solvents. J. Pharm. Sci. 61(6):983-984.
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Yaitsowsky, S.H.; Valvani, S.C.; Amidon, G.L.  (1976) Solubility of nonelectrolytes in
polar, solvents IV: nonpolar drugs in. mixed'solvents.  J. Pharm. Sci. 65(10): 1488-1494.

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national! ecosystem.  In: Tucker, A. eds.  Human and. environmental risks of chlorinated
dibxihs and related  compounds. New York, NY: Plenum Publishing Corp.

Zeppi R.G.; Miller, G.C.; Herbert, V.R.; Mille, NO.; Mitzel, R. (1988)  Photolysis of
octaehlorodibenzo-p-dioxin on soils;  production of 2,3,7,8-TCDD. Chemosphere (in press).
                                          332

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APPENDIX.  RISK ESTIMATES FOR CHAPTER 6 SCENARIOS
                          333

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           APPENDIX.  RISK ESTIMATES FOR CHAPTER 6 SCENARIOS








     The procedure used to calculate an upper-limit incremental cancer risk at low doses



is as follows:








               Upper-limit incremental cancer risk = 1  - e"****



                        = qi*d,  when qd <  10~3                               (A-l)








where  q is the cancer potency factor and d is the dose (discussed further below).  The



95% upper confidence limit of the linear slope, factor (qj ) of Dose-Response Function for



2,3,7,8-TCDD is 0.156 kg-d/ng).  The derivation of this factor is described in U.S. EPA



(1984a) and further background is provided in U.S. EPA, 1981b.  The Agency is currently



reevaluating this potency factor and may change it in the near future.



     EPA's Carcinogen Assessment Group (Farland,  1987a)  is also currently considering



adjusting  the potency factor for exposures  that occur to  children  only  (such as soil



ingestion).   This is  due to the fact that  1)  children may have greater sensitivity  than



adults  and 2) the scaling  procedure  used  in  deriving a potency factor uses the surface



area of adults  (not  children).   Currently, no final decision has been made on  how to



make this adjustment and no adjustment was made in this document.



     Dose  as used in Equation A-l  is the rate at which a chemical  is absorbed into the



body and is typically expressed in units of mg/kg-d.  The exposure estimates presented in



Chapter 6  reflect the rate at which chemicals contact  the  body and  do  not account for



absorption  into the  body.  Typically,  such  exposures can  be converted  to  doses by



multiplying the exposure  by the absorption fraction (fraction of chemical contacting the



body which enters the body).  However, in using Equation A-l, additional consideration



must be given to the differences  between   the absorption occurring  during the  human






                                          334

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exposure  event of  interest and the  absorption  which  occurred  during  the  animal




experiment  used  to  derive the  potency factor.   These  differences  may be  due  to




differences between animals and humans and/or differences between the vehicle  carrying




the contaminant used in the animal  study versus that  of the human exposure event.  The




absorption which  occurred  during the animal experiments, which  EPA  used to derive the




potency factor for 2,3,7,8-TCDD, was estimated to be 55% (Farland,  1987b).   Thus, if




55%  absorption also  occurs during  the human  exposure event of  interest then  no




adjustment to the exposure estimate is needed  when  calculating risk.  However,  if the




human exposure is different from 55%, the exposure  level must be adjusted accordingly.




This is accomplished via the following equation.








 Risk = (potency  factor) (exposure) (human absorption fraction)/0.55     (A-2)










     The  risk  estimates presented here were calculated using Equation  A-2, a  potency




factor of  0.156 kg-d/ng, an exposure corresponding to the  appropriate level listed  in




Table 6-5,  and a human  absorption  fraction corresponding to  the  appropriate  value




listed in  Table 6-4.




     The  risk  estimates for  all  land  scenarios  are  presented  in Table A-l  and



incinerator/ash scenarios in Table A-2.
                                         335

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                        TABLE  A-l.   UPPER-BOUND INCREMENTAL CANCER RISKS
                      ASSOCIATED WITH VARIOUS EXPOSURE PATHWAYS/SCENARIOS:
                                         CONTAMINATED SOILa
Scenario
Dairy    Beef
inges-    inges-
tion     tion
Fish     Soil
inges-    ingea-
tion      tion
Vapor    Dust
inhala-   inhala-
tion      tion
         Drink-  Veget-
Soil      ing      able
dermal  water  inges-
                 tion
l)l;ppb
1 acre
reasonable
worst-case
  NA     NA      NA     SxlO'4   2xlO"6   SxlO"7    2xlO"5   NA
                                                                        See
                                                                        text
2)1 ppb
10 acres
reasonable
worst-case
,2xlO"3   IxlO"2   4xlO"2   SxlO"4   SxlO"6   SxlO'7   2xlO"5   9x10"
                                                                       See
                                                                       text
3)1 ppt
10 acres
reasonable
worst-case
:2xlO"6   1x10"5   4x10"5  .SxlO"7   SxlO"9   SxlO"10  2x10"8   9xlO"9
                                                                       See
                                                                       text
4)1 .ppq
10.acres
reasonable
worst-case
2xlO"9   IxlO"8   4xlO"8   SxlO"10  SxlO"12  SxlO"13  2xlO"n  9xlO"12
                                                                       See
                                                                       text
5)1 ppb
10 acres
typical
5xlO~4   SxlO"3   5xlO"6   4xlO"6   2xlO"6   IxlO"7   6xlO"6   SxlO"9
                                                                       See
                                                                       text
6)1 ppt
10 acres
typical
BxlO"7   SxlO"6   5xlO"9   4xlO"8   .2xlO"9   IxlO"10  6xlO"9   SxlO"12  See
                                                                       text
7)1 ppq
10 acres
typical
 SxlO"10  .SxlO"9   BxlO"12  4X10"11  .J2xlO"12   IxlO"13  6xlO"12  SxlO"15
                                                                       See
                                                                       text
                                                                                (Continued	)
                                                    336

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                                         TABLE  A-l.  (CONTINUED)
Scenario
Dairy    Beef      Fish     Soil      Vapor    Dust                Drink-  Vegeta-
inges-    inges-    inges-    inges-     inhala-   inhala-   Soil      ing       ble
tion      tion      tion      tion      tion      tion      dermal    water    i n g e s t i o n
8)1 ppb
1 acre
reasonable
worst case
9xlO"5   6xlO"4   2xlO"3   IxlO"5    2xlO~7   4xlO"8   SxlO"7    4xlO"7
                                                                           See
                                                                           text
9)1 ppb
10 acres
reasonable
worst case
6xlO~4   4xlO~3    IxlO"2   IxlQ"4    7xlO"7   SxlO'8   6xlO"6    SxlO"6
                                                                           See
                                                                           text
10)1 ppt
10 acres
reasonable
worst case
6xlO"7   4xlO"6   IxlO"6   IxlO"7    7xlO"10  SxlO"11  6xlO"9    SxlO"9
                                                                           See
                                                                           text
11)1 ppq
10 acres
reasonable
worst case
6xlO'10   4xlO'9   IxlO"8   IxlO"10   7xlO"13  SxlO"14  6xlO"12   SxlO"12
                                                                           See
                                                                           text
12)1 ppb
10 acres
typical

13)1 ppt
10 acres
typical
4xlO"6    2xlO"5   5xlO"6   SxlO"7    2xlO"7   4xlO"9   5xlO"8    SxlO"9
4xlO"9    2xlO"8   5xlO"9   SxlO"10   2xlO"10  4xlO"12  SxlO"11   SxlO"12
                                                                           See
                                                                           text
                                                                           See
                                                                           text
                                                                                         (Continued	)
                                                       337

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                                        TABLE A-l.  (CONTINUED)

Scenario

14)1 ppq
10 acres
typical

15)1 ppb
10 acres
capped land fill
reasonable worst -case
Dairy Beef FUh Soil Vapor Dust Drink- Vegeta-
inges- inges- inges- inges- inhala- inhala- Soil ing ble
tion tion tion tion tion tion dermal water ingestion

4x10" 12 2x10" U 5x10' 12 3x10' 1S 2x10" 1S 4x10" 15 5x10" 14 3x10" 15
See
text

neg.c neg. neg. neg. 4x10" neg. neg. neg. neg.


alf the 'cancer potency factor recognized by the Agency is revised, the risk associated with any scenario and pathway may be
obtained by multiplying the corresponding entry from Table A-l by the factor (revised potency factor/0.156 kg-d/ng).

 These scenarios assume that the exposure area is downgradient of the contaminated source.  If the  exposure  area was
located upgradient and all transport was via windblown dust, these risks would be reduced by a factor of 1,000.

cneg. = negligible risk (<10~8)
                                                       338

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                 TABLE A-2.  UPPER-BOUND INCREMENTAL  CANCER RISKS ASSOCIATED
                          WITH INCINERATOR EXPOSURE PATHWAYS/SCENARIOS3
                            A.  RISKS ASSOCIATED WITH STACK EMISSIONS
               Dairy       Beef     Fish     Soil       Vapor     Participate   Soil     Drinking      Vegetable
Scenario    Ingestion     Ingestion    Ingestion Ingeation Inhalation  Inhalation  Dermal       Water      Ingestion


16) 3000 TPD  3 x 10"6    8 x 10'6    2 x 10~7  2 x 10"7  1 x 10"7   3 x 10~8     1 x 10~8   8 x 10"9     See text
reasonable
worst case

17) 120 TPD   1 x 10~4    4 x 10"4    1 x 10"5  9 x 10"6  1 x 10"6   2 x 10'6     B x 10~7   6 x 10"7      See text
reasonable
worst case

18) 3000 TPD  2 x 10"6    2 x 10"6    2 x 10"12 2 x 10~8  5 x 10'8   1 x 10~8     4 x 10~9  3 x 10"13      See text
typical
case

19) 120 TPD   8xlO'5    9xlO"B    2 x 10"10 1 x 10"8  4 x 10'6   9 x 10"7     2 x 10'7  2 x 10'11      See text
typical
case
a If the cancer potency factor recognized by the Agency is revised, the risk associated with any scenario and
  pathway may be obtained by multiplying the corresponding entry from Table A-2 by the ratio (revised potency
  factor/0.156 kg-d/ng).

    b at 200 m from stack.
                                                    339

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                                         TABLE A-2.   (CONTINUED)
                              B.  RISKS ASSOCIATED WITH FLY  ASH DISPOSAL
                Dairy       Beef      FUh      Soil       Vapor    Participate    Soil     Drinking      Vegetable
Scenario     Ingestion     Ingestion     Ingestion  Ingestion Inhalation  Inhalation  Dermal       Water        Ingestion


16) 3000 TPD  2 x 10'3    1 x 10'2   4 x 10"6   3 x 10"4    1 x 10'6    2 x 10"8   2 x 10~5    4 x 10~6    See text
reasonable       ,
worst case

17) 120 TPD   3 x 10'4    2 x 10'3   7 x 10"7   6 x 10'6    6 x 10'7    8 x 10"9   3 x 10'6    6 x 10"7    See text
reasonable
worst case

18) 3000 TPD  2xlO"4    2 x 10"3   7xlO"10  2 x 10"B    6 x 10"7    4 x 10"9   8 x 10"9    2 x 10"9    See text
typical

19) 120 TPD   1 x 10~6    1 x 10'4   7 x 10'10  1 x 10"6    1 x 10'7    1 x 10"9   8 x 10'9    2 x 10'9    See text
typical

20) 3000 TPD  neg.c      neg.       neg.     neg.        neg.         neg.       neg.       neg.        neg.
reasonable
worst case
capped


a If the cancer potency factor recognized by the Agency is revised, the risk associated with any scenario and
  pathway may be obtained by multiplying the corresponding entry from Table A-2 by the ratio (revised potency /factor/
  0.156 kg-d/ng).
  All scenarios assume 1.3 ppb 2,3,7,8-TCDD in fly ash.
c Negligible risk (<10~8).
  Stack emissions part of this scenario is the same as scenario 16.
                                                       340
                                                                                  r U.SaOVERNUtNTmNTMOOFFICE: IBM. 548-OIO/81TOS

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