SEPA
         United States
         Environmental Protection
         Agency
           Environmental Research
           Laboratory
           Athens GA 30613
EPA-600/6-82-004a
September 1982
         Research and Development
Water Quality
Assessment:

A Screening
Procedure for Toxic
and  Conventional
Pollutants—Part 1

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                                                       EPA-60Q/6-82-004a
                                                       September 1982
                     WATER QUALITY ASSESSMENT:
                  A Screening Procedure for Toxic
                    and Conventional Pollutants

                              Part 1
                                by

W.B. Mills, J.D. Dean, D.B. Porcella, S.A.  Gherini, R.J.M.  Hudson,
               W.E. Frick, G.L. Rupp, and G.L.  Bowie

                     Tetra Tech, Incorporated
                   Lafayette, California  94549
                      Contract No.  68-03-2673
              Prepared in Cooperation with U.S.  EPA's

                 Center for Water Quality Modeling
                 Environmental Research Laboratory
                         Athens, Georgia

                Monitoring and Data Support Division
              Office of Water Regulations and Standards
                          Office of Water
                          Washington, D.C.

                        Technology Transfer
          Center for Environmental Research Information
                        Cincinnati, Ohio
                 ENVIRONMENTAL RESEARCH LABORATORY
                 OFFICE OF RESEARCH AND DEVELOPMENT
                U.S.  ENVIRONMENTAL PROTECTION AGENCY
                        ATHENS, GEORGIA  30613

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                                 DISCLAIMER

      Mention of trade names or commercial  products does not constitute
endorsement or recommendation for use by the U.S.  Environmental  Protection
Agency.

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                                  FOREWORD

      As environmental controls become more costly to Implement and the
penalties of judgment errors become more severe, environmental  quality
management requires more efficient analytical  tools based on greater know-
ledge of the environmental phenomena to be managed.  As part of this Lab-
oratory's research on the occurrence, movement, transformation, impact,
and control of environmental contaminants, the Technology Development and
Application Branch develops management or engineering tools to  help pollu-
tion control officials achieve water quality goals through watershed manage-
ment.

      Basin planning requires a set of analysis procedures that can provide
an assessment of the current state of the environment as a means of predict-
ing the effectiveness of alternate pollution control  strategies.  This manual
contains a description of a set of consistent analysis procedures that can
help to accomplish these tasks.  It is directed toward local and state gov-
ernment planners who must interpret technical  information from  many sources
and recommend the most prudent course of action that will maximize the en-
vironmental benefits to the community and minimize the cost of  implementation.

      The manual was prepared in cooperation with the Office of Water and the
Center for Environmental Research Information.  The Office of Water is re-
viewing the manual for its potential use as a screening guide for the Waste-
load Allocation-Total Maximum Daily Load program.  User comments on the
methodologies in the manual are encouraged and should be directed to the
Center for Water Quality Modeling at the Athens Environmental Research Lab-
oratory.

                                      David W. Duttweiler
                                      Director
                                      Environmental Research Laboratory
                                      Athens, Georgia

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                                 ABSTRACT

      New technical  developments  in  the field  of  water  quality  assessment
and a reordering of  water quality priorities  prompted a revision  of  Water
QuaIJty Assessment:   A Screening  Methodology  for  Nondesignated  208 Areas
(EPA-600/9-77-023)!   The utility  of  the revised manual  is  enhanced by  the
inclusion of information on the accumulation,  transport, and  fate of toxic
chemicals in the environment.   The new subtitle—A Screening  Procedure for
Toxic and Conventional Pollutants — reflects  the added information.

      Applying  the manual's simple techniques, the user is now capable of
assessing the loading and fate of conventional pollutants  (temperature,
biochemical oxygen demand-dissolved oxygen, nutrients,  and sediments) and
toxic pollutants (from  the U.S. EPA list of priority pollutants) in  streams,
impoundments, and estuaries.  The techniques are readily programmed  on hand-
held calculators.  Most of the data required for using  these procedures are
contained in the manual.

      Because of its size, the manual  has been divided  into three parts.   Part
1  contains the  introduction and chapters on the  aquatic fate of toxic organic
substances, waste load calculations, and the assessment of water quality para-
meters in rivers and streams.   Part 2 continues  with chapters on the assessment
of impoundments and estuaries and appendices A,  B, C,  E, F, G and H.  Appendix
D is provided in the third part (on microfiche in the EPA-printed manual).

      This report is submitted in fulfillment of Contract  No. 68-03-2673 by
Tetra Tech, Inc., under the sponsorship of the U.S. Environmental Protection
Agency.  Work was completed as of February 1982.

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                              TABLE OF CONTENTS

                                   PART 1
FOREWORD                                                                  i i I

ABSTRACT                                                                   -j v

LIST OF FIGURES (PART 1)                                                  vi ^

LIST OF TABLES (PART 1)                                                   xi1

ACKNOWLEDGMENTS                                                           xix

CHAPTER

  1     INTRODUCTION                                                         I

       1.1   Background                                                      1
       1.2   Purpose and Scope                                               2
       1.3   Methodology Application                                         4
       1.4   Limitations                                                     6
       References for Chapter 1                                              7

  2     AQUATIC FATE OF TOXIC ORGANIC  SUBSTANCES                              8

       2.1   Introduction                                                    8
       2.2   Screening Methods for Toxic Organic  Compounds                   27
       2.3   Speciation Processes                                           54
       2.4   Transport Processes                                             76
       2.5   Transformation Processes                                       101
       References for Chapter 2

  3     WASTE LOAD CALCULATIONS                                            168

       3.1   Introduction                                                  168
       3.2   Nonurban Nonpoint Source  Loads                                 170
       3.3   Urban Nonpoint Source Loads                                   253
       3.4   Point Source Waste Loads                                       297
       References for Chapter 3                                            315

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                                                                         Page

   4     RIVERS  AND  STREAMS                                                 321

        4.1   Introduction                                                  321
        4.2   Carbonaceous and  Nitrogenous  Oxygen  Demand                    362
        4.3   Dissolved  Oxygen                                              380
        4.4   Temperature                                                   423
        4.5   Nutrients  and  Eutrophication  Potential                        469
        4.6   Total  Coliform Bacteria                                       480
        4.7   Conservative Constituents                                     486
        4.8   Sedimentation                                                 488
        4.9   Toxic  Substances                                              509
        References  for  Chapter 4


                                   PART  2

   5     IMPOUNDMENTS                                                        1

        5.1   Introduction                                                    1
        5.2   Impoundment Stratification                                      3
        5.3   Sediment Accumulation                                         24
        5.4   Eutrophication and Control                                     65
        5.5   Impoundment Dissolved Oxygen                                   92
        5.6   Toxic  Chemical Substances                                     128
        5.7   Application of Methods and  Example Problem                    140
        References  for Chapter 5                                           185
        Glossary of Terms                                                  187

   6     ESTUARIES                                                         191

        6.1   Introduction                                                  191
        6.2   Estuarine Classification                                     207
        6.3   Flushing Time  Calculations                                    222
        6.4   Far Field Approach to Pollutant Distribution in Estuaries    251
        6.5   Pollutant Distribution Following Discharge  from a Marine
             Outfall                                                      314
        6.6   Thermal Pollution                                            367
        6.7   Turbidity                                                    390
        6.8  Sedimentation                                                 408
        References  for Chapter 6

APPENDICES

   A    Monthly Distribution of Rainfall Erosivity Factor R               A-l
   B    Methods for Predicting Soil Erodibility Index K                   B-l
   C    Stream and River Data                                             C-l
   D    Impoundment Thermal Profiles                                      D-l
   E    Modeling Thermal  Stratification  in Impoundments                    E-l
   F    Reservoir Sediment Deposition Surveys                             F-l
   G    Initial Dilution Tables                                           G-l
   H    Equivalents of Commonly Used Units of Measurement                 H-l
                                     vi

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                              LIST OF FIGURES

                                   PART 1

Figure                                                                  Page

II-l    Environmental Fate of a Toxic Pollutant                            9

II-2    Speciation, Transport and Transformation Processes  in the         28
        Aquatic Environment

11-3    Flow System Representations                                       32

II-4    Isotherms for Adsorption of a Hydrophobic Pollutant on Sediments  64

II-5    Relationships Between Koc and Octanol-Water Partition Coeffi-      69
        cient (Kow) of Energy-Related Organic Pollutants

II-6    Correlation of Aqueous Solubility  with Octanol-Water Partition    70
        Coefficient

11-7    Relationship Between KQC and Kowfor Coarse Silt                   71

II-8    Schematic Representation of Volatilization form Solution  Phase    84
        to Liquid Phase

II-9    Microbial Transformations of Phenoxy Herbicides                  104

11-10   Ultraviolet Absorption Spectrum of Naphthacene                   128

11-11   Spectral  Distribution of Solar Energy                            129

11-12   Solar Radiation in the United States                             132

11-13   Photochemical Pathways of an Excited Molecule                    138

11-14   Direct Photochemical Reactions of  a 2,4-D Ester                  140

11-15   Comparison of Solar Irradiance with the Absorption  Spectra        143

11-16   pH Dependence of Hydrolysis Rate Constants                       157

III-l   Flow Diagram for Calculating Sediment Loading from  Surface        172
        Erosion

III-2   Average Annual  Values of the Rainfall-Erosivity Factor, R        174

                                    vii

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n_cju_re                                                                 Page

III-3   Mean Annual  Values of Erosion Index for Hawaii                   175

III-4   Soil Moisture-Soil Temperature Regimes of the Western U.S.       177

III-5   Relationships between Annual  Average Rainfall Erosivity Index   179
        and the 2--year, 6-hour Rainfall  Depth for 3 Rainfall Types
        in Western U.S.

III-6   Storm Distribution Regions in Western U.S.                      180

III-7   Slope Effect Chart Applicable to  Areas A-l in Washington,       184
        Oregon, and Idaho and All of A-3

III-8   Slope Effect Chart for Areas Where Figure III-7 is Not Appli-   185
        cable

111-9   Sediment Delivery Ratio for Relatively Homogeneous Basins       196

111-10  Percentage Nitrogen in Surface Foot of Soil                      213

III-ll  Soil Nitrogen vs. Humidity Factor and Temperature               215

111-12  Nomograph for Humidity Factor, H                                 216

111-13  Phosphorus Content in the Top 1 foot of Soil                    218

111-14  Nitrogen (NH4-N and N03-N) in Precipitation                     231

111-15  Climate Zone for  the Cities from which Data Are Available       270
        and Used in the URS Study

111-16  Correlation between Population Density and Curb Length Density  273

111-17  Street Surface Contaminant Removal as a Function of Runoff      276

111-18  Correlation of  Influent Total Metals Concentration to Percent   310
        Industrial Flow

IV-1    Illustration of River Segmentation Procedure on the James River 340

IV-2    Hypothetical River Having a Variety of Pollutant Sources and    342
        Sinks

IV-3    River Segmentation for BOD Distribution                         343

IV-4    Pollutant Discharge Where Initial Mixing  Occurs a Fractional    346
        Distance Across the River

IV-5    Illustration of Water Balance                                   353
                                    vm

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IV-6    Sketch of Snake River from Heise to Neeley,  Idaho                355

IV-7    Example of Flow Rate Information Tabulated in U.S.  Geological     357
        Survey's Water Data Report

IV-8    Example Set of User's Instructions for Hand-Held Calculator      361
        Programs

IV-9    The BOD Curve, (a) Curve for Oxidation of Carbonaceous  Matter.    364
        (b) Curve Showing Influence of Nitrification

IV-10   Mechanisms of BOD Removal from Rivers                            366

IV-11   Deoxygenation Coefficient as a Function of Depth                 367

IV-12   Example of Computation of KL from Stream Data                    369

IV-13   Hypothetical  BOD Waste Loadings in a River                       375

IV-14   Variability of Dissolved Oxygen by Season for 22 Major  Water-     381
        ways, 1968-72

IV-15   Reaeration Coefficient as a Function of Depth                    385

IV-16   Reaeration Coefficient for Shallow Streams                       386

IV-17   Reaeration Rate vs.  Depth and Velocity                           387

IV-18   Characteristic Dissolved Oxygen Profile Downstream  from a  Point   398
        Source of Pollution

IV-19   Flow Process  of Solution to Dissolved Oxygen Problem  in Rivers    399

IV-20   Daily Dissolved Oxygen Variation in Two Rivers                    408

IV-21   Flow Process  in Reach by Reach Solution to Critical Dissolved     415
        Oxygen Values

IV-22   Hypothetical  River Used in Example IV-9                          420

IV-23   Mechanisms of Heat Transfer Across a Water Surface                426

IV-24   Schematic of  Site No.  3 Cooling Lake                             427

IV-25   Observed Temperatures,  Site No. 3, July 18-July  24, 1965          428

IV-26   Comparison of Computed Equilibrium and Ambient Temperatures       429
        with Observed Mean Diurnal  Temperature Variations for Site
        No.  3, July 18-July 24,  1966
                                     IX

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Figure                                                                  Page

IV-27    Mean Daily Solar Radiation  throughout the  U.S.  for  July  and      431
         August

IV-28    Mean Dewpoint Temperature (Deg.  F)  throughout the U.S. for      441
         July and August

IV-29    Mean Daily Wind Speeds (mph)  throughtout the  U.S. for July      442
         and August

IV-30    Idealization of a Run-of-the-River  Power Plant                  447

IV-31    Downstream Temperature Profile for  Completely Mixed Stream,      460
         (T-E)/(Tm-E) vs. r

IV-32    Measured Air and Water Temperatures for the Santa Ana River      463
         near Mentone, California, in June 1979

IV-33    Measured Dissolved Oxygen Concentration and Predicted Satura-   464
         tion Concentration for the Santa Ana River near Mentone,
         California, in June 1979

IV-34    Flow Duration Curve, Hatchie River  at Bolivar, Tennessee        466

IV-35    Frequency of Lowest Mean Discharges of Indicated Duration,      467
         Hatchie River at Bolivar, Tennessee

IV-36    Three River Temperature Profiles                                468

IV-37    Total Coliform Profiles for the Willamette River                481

IV-38    Salinity Distribution in a Hypothetical River                   488

IV-39    Division between Wash Load and Bed Material Load                491

IV-40    y and TC for DuBoys Relationship as Functions of Median Size    494
         of  Bed Sediment

IV-41    Hydraulic Radii for Different Channel Shapes                    497

IV-42    User  Instructions for Yang's Sediment Transport Equation        502

IV-43    Program Listing and Sample Input/Output for Yang's Sediment     503
         Transport Equation

IV-44    Sediment Discharge as a  Function of Water Discharge  for the     507
         Colorado River at Taylor's Ferry

IV-45    Sediment Discharge as a  Function of Water Discharge  for the     508
         Niobrara River at Cody,  Nebraska

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Figure

IV-46    Toxicant Concentrations Following Initiation and Cessation       513
         of Point Source

IV-47    Vertical Equilibrium Distribution of Suspended Solids in a       516
         River

IV-48    Vertical Distribution of Relative Solute Concentration,           517
         KPSA = 10

IV-49    Vertical Distribution of Relative Solute Concentration,           518
         KPSA = 100

IV-50    Instreatn Transformation Processes Analyzed for Toxicants         527

IV-51    Location Map of Hudson River, New York                           537

IV-52    Hypothetical Concentration Distributions of Finitely Soluble     542
         and Infinitely Soluble Toxicants

IV-53    Hypothetical Distribution of Toxicant at Various Locations       546
         Following a Spill

IV-54    Illustration of Hypothetical Spill  Incident                      552

IV-55a   Chloroform Concentration in Water Column for First 60 Hours      560
         Following a Spill  16.3 Miles Upstream

IV-55b   Chloroform Concentration in the Mississippi River at a Loca-     561
         tion 16.3 Miles Below the August 29, 1973, Spill

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                               LIST OF TABLES

                                   PART 1

Table                                                                  Page

II-l   Brief Comparison of Conventional and Toxic Pollutants              10

II-2   Proposed Criteria for Toxic Substances  Designed to Protect        13
       Aquatic Life

II-3   EPA List of 129 Priority Pollutants and the Relative Frequency    16
       of These Materials in Industrial Wastewaters

II-4   Most Commonly Discharged Priority Pollutants                      17

II-5   Selected Characteristics of Various Aliphatic Hydrocarbons        20

II-6   Various Characteristics of Selected Pesticides                    21

II-7   Selected Characteristics of Polychlorinated Biphenyls  and Rela-   22
       ted Compounds

II-8   Selected Characteristics of Monocyclic  Aromatic Hydrocarbons      23

II-9   Selected Characteristics of Various Polycyclic Aromatic Hydro-    24
       carbons

11-10  Expressions for Toxic Pollutant Levels  in Various Water Bodies    35

11-11  Relative Importance of Processes Influencing Aquatic Fate of      39
       Organic Priority Pollutants

11-12  Occurrence of Acids and Bases in Neutral and Charged Forms as     57
       as a Function of p^1, pKa > anc! PKb

11-13  pKa and pK^  Values for Selected Toxic Organic Acids and Bases    58
       and Values of p ^ for Water

11-14  Relationship of Dissolved and Sorbed Phase Pollutant Cone         73
       trations to Partition Coefficient and Sediment Concentration

11-15  Henry's Law Constant for Selected Hydrocarbons                    81

11-16  Henry's Law Constants for Selected Compounds                      89


                                    xii

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Table                                                                    Pac]§

11-17   Typical  Values of Pollutant Volatilization  Rates  in  Surface         89
        Waters

11-18   Comparison of Tabulated and Predicted Values  of Diffusion  Coeffi-   91
        cients for Selected Pollutants

11-19   Results  of a Study to Directly Determine Volatilization  Rates       94
        of Several Priority Pollutants in Rivers

11-20   Relative Volatilization Mass Fluxes of Several  Chemicals in         99
        Saturated Solutions

11-21   Size of Typical  Bacterial  Populations in Natural  Waters            109

11-22   Summary  of the Characteristics of the Two General  Types  of Bio-    110
        degradation:  Metabolism and Cometabolism

11-23   Potential Biodegradability of Organic Pollutants  in  an Aerobic     113
        Environment

11-24   Biodegradation Rate Constants under Aerobic Conditions             116

11-25   Calculated Solar Radiant Energy Flux to a Horizontal  Surface       130
        under a  Clear Sky

11-26   Calculated Solar Irradiance in a Water Body Just  Beneath the       133
        Surface, Annual  Mean at 40 N

11-27   Contributions to Light Attenuation Coefficient                     136

11-28   Disappearance Quantum Yields, ^d, for Direct  Photolysis            142

11-29   Near-Surface Direct Photolysis Rate Constants                   ,  148

11-30   Generalized Hydrolytic Reactions of Organic Compounds             156

11-31   Hydrolysis Rate Parameters and Estimated Environmental Hydro-      160
        lysis Rates

III-l   Applicability of Rr and RS Factors in the Areas West of  the        178
        the Rocky Mountains

III-2   Generalized Values of the  Cover and Management  Factor, C,  in       187
        the 37 States East of the  Rocky Mountains

III-3   "C" Values for Permanent Pasture, Rangeland,  and  Idle Land        189

III-4   "C" Values for Woodland                                           191

III-5   "C" Values for Construction Sites                                 192

                                    xi i i

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Table                                                                   Page

III-6   Practice Factors (P) Used in Sediment Loading Equation            194

III-7   Typical Values of Drainage Density                               198

III-8   Erosion Equation Factor Precision Error                          201

III-9   Runoff Curve Numbers for Hydrologic Soil-Cover Complexes         206
        (For Antecedent Rainfall Condition II)

111-10  Antecedent Rainfall Conditions and Curve Numbers  (for  Ia = 0.25)208

111-12  Enrichment Ratios for Nitrogen                                   212

111-13  Enrichment Ratios for Phosphorus                                 221

111-14  Enrichment Ratios for Organic Matter in Surface Runoff            224

111-15  Calculated Sediment, Nitrogen, Phosphorus and Organic Matter     226
        Loads for Parke County, Indiana, Watershed

II1-16  Variation in Constituent Accounted for by Regression on Suspend- 229
        ed Solids (Linear Models Only)

111-17  Atmospheric Contributions of Nitrogen and Phosphorus in Rain-    232
        fall

111-18  Nutrient Budgets for Various Terrestrial Ecosystems of  the       233
        World

111-19  Salt Yields from Irrigation in Green River Subbasin              234

111-20  Salt Yields from Irrigation in Upper Colorado Main Subbasin      235

111-21  Salt Yields from Irrigation in San Juan River Subbasin            236

111-22  Salt Yields from Irrigation in Lower Colorado River Basin        237

111-23  Salt Yields from Irrigation for Selected Areas in California     237

111-24  Values of k  for Dissipation of Pesticides from Soil Surfaces    243

111-25  Degradation Rate Coefficients for Selected Pesticides            247

111-26  Octanol-Water Partition Coefficients for Selected Pesticides     249

111-27  General Land Consumption Rates fir Various Land Uses             256

111-28  Pollutant Loading  Factors                                        256

111-29  Comparison  of Quality of Storm Sewer Discharges for Cities       258

                                    xiv

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Tab!e                                                                    Pacj^

111-30  Comparison of Quality of Combined Sewers for Various  Cities        259

111-31  Summary of Stormwater Pollutant Concentrations                    260

111-32  Summary of Street Cleaning Methods                                263

111-33  Removal Rates for Selected Contaminants by Size                   264

111-34  Solid Loading Rates and Composition—Nationwide Means and         266
        Substitutions of the Nationwide Means at 80% Confidence  Level

111-35  Values of Runoff Coefficient,  k                                   274

111-36  Relationships between Total Suspended Solids and Other Pollutants 277

111-37  Field-Measured Dry Deposition  Velocities                          282

111-38  Washout Ratios for Selected Trace Organics                        288

111-39  PCBs, DDTs, and Phthalate Esters in the Gulf of Mexico Atmos-      289
        phere

111-40  1975 Monthly Average Concentrations of Three Organic  Compounds     290
        at Three New York City Locations

111-41  Seasonal Fluctuations in the Geometric Mean PAH Concentrations     291
        in Air Samples Collected at 13 Stations in the Los Angeles,
        California, Area

111-42  Average Monthly Atmospheric Levels of Four Pesticides at Stone-    292
        ville, Mississippi

111-43  Flow Weighted Mean Concentrations of Trace Metals and Chlorina-    294
        ted Hydrocarbons in the Los Angeles River

111-44  Concentrations of PAH in Municipal Wastewater Effluents  in  the     295
        GFR

111-45  Water Withdrawals for Public Supplies by States and by Selected    300
        Municipal Systems, 1970

111-46  Typical Municipal Waste Concentrations                            301

111-47  Municipal Wastewater Treatment System Performance                 302

111-48  Point Source Loadings of Six Major Wastewater Treatment  Facili-    303
        ties in One North Carolina 208 Area

111-49  Typical Industrial Discharge Pollutant Concentrations             305
                                     xv

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Table                                                                    Page

II1-50  Summary of Current and Projected Waste Loads  in  One Region        306
        208 Area (by SIC Code)

111-51  Predicted Priority Pollutants in Household Wastewater             308

111-52  Occurrence of Priority Pollutants in POTW Influent Samples        309

111-53  Industrial Categories and Frequently Detected Priority Pollu-      311
        tants by Category

111-54  Reduction of Conventional and Priority Pollutants by POTW         313
        Treatment Processes

111-55  Concentrations (Mean + Standard Error) of EPA Priority Pollu-      314
        tants in the Los Angeles County JWPCP Effluents

IV-1    Reference Level  Values of Selected Water Quality Indicators for   323
        U.S. Waterways

IV-2    Condition of Eight Major Waterways                                324

IV-3    Water Quality Problem Areas Reported by States                    327

IV-4    Example River Water Quality Standards                             328

IV-5    Water Quality Parameters Commonly Monitored by States             329

IV-6    Annual Phosphorus and Nitrogen Load for Selected Iowa River       332
        Basins

IV-7    Major Waterways:  Seasonal  Flow Analysis, 1968-72                 336

IV-8    Water Quality Analyses for River Screening Methodology            337

IV-9    Experimental Measurements of Transverse Mixing in Open Channels   348
        with Curves and Irregular Sides

IV-10   Suggested Configuration for Water and Nutrient Balance Table      351

IV-11   Solution to Snake River Water and Phosphorus Balance Problem      358

IV-12   Municipal Waste Characteristics before Treatment                  363

IV-13   Comparison of Predicted and Observed Reaeration Rates on Small    389
        Streams in Wisconsin

IV-14   Typical Hydraulic Properties in Patuxent River (September 1969)   390

IV-15   Solubility of Oxygen in Water                                     394
                                    xvi

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Table                                                                    p_a_g_e

IV-16  Dissolved Oxygen Saturation vs.  Temperature and Altitude           396

IV-17  DC/L0 Values vs. D0/L0 and ka/KL                                   402

IV-18  kat vs. D0/L0 and ka/kL                                            403

IV-19  Some Average Values of Gross Photosynthetic Production of Dissol-   407
       ved Oxygen

IV-20  Average Values of Oxygen Uptake Rates of River Bottoms             412

IV-21  Compilation of Information in Example IV-8                         417

IV-22  Critical Time Results                                              419

IV-23  Net Long Wa e Atmospheric Radiation, Han                           433

IV-24  Water Vapor Pressure vs. Air Temperature,  Ta,  and Relative         434
       Humidity

IV-25  B and C(B) as Functions of Temperature                             435

IV-26  Summary of Solar-Radiation Data for Mineola, Brookhaven, and the   437
       Connetquot River Sites

IV-27  Data Needed for Thermal Discharge Screening                        449

IV-28  Eutrophication Potential as a Function of Nutrient Concentrations   472

IV-29  Regional Stream Nutrient Concentration Predictive Models           476

IV-30  Total Nitrogen Distribution in a River in Response to Point and    479
       and Non-Point Source Loading

IV-31  Total Coliform Analysis                                            482

IV-32  Salinity Distribution in a Hypothetical  River                       489

IV-33  Relationship of Total Suspended Sediment Concentration to Problem   492
       Potential

IV-34  Sediment Grade Scale                                               495

IV-35  Computing D/T for Determining the Hydraulic Radius of a Parabolic   496
       Section

IV-36  Relationship between Width to Depth Ratio of a Graded Stream and   498
       the Suspended and Bed Load Discharge
                                     xvi

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Table                                                                   Pag_e_

IV-37  Characteristics of the Colorado and Niobrara Rivers               505

IV-38  Methods of Introduction of Toxic Organic Compounds into Rivers    510
       and Fate in Terms of Volatilization and Sorption

IV-39  Mass of Contaminated Sediments and Equivalent Water Depth as a    536
       Function of Depth of Contamination

IV-40  Water-Soluble, High Density, Immiscible Chemicals                 549
                                   xvm

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                              ACKNOWLEDGEMENTS
     This publication is the result of the labors of a number of individuals
who contributed to both this document and the previous edition.   Two of  the
authors  of  the  previous  document,  Stanley Zison and Kendall Haven, were
instrumental in producing this work because many  of  their  original  ideas
have  been  retained.   In addition, all of the individuals in the U.S. EPA,
especially Dr. James Falco, Mr. Orville Macomber,  Mr. Robert  Ambrose,  and
Mr. Tom  Barnwell,  who supported this work must be thanked for their input,
consideration, and patience.

     Because of the size of this document a phenomenal amount of typing  and
graphic   art  work  was  done.   The  authors  would  like  to  acknowledge
Susan I. Madson, Pencie Shrewsbury, Barbara Koch and Trudy Rokas  for  their
tireless  efforts  in these areas.  Finally, the authors would like to thank
Ms. Carrie Campbell who tabulated much of the data on toxic substances found
in Chapter 2.
                                    xix

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                              CHAPTER 1
                             INTRODUCTION

1.1   BACKGROUND
      In 1977, the United States Environmental Protection Agency published
Hater Quality Assessment:     A Screening Method for Nondeslgnated 208 Areas
(Zison et a]_., 1977).    This document was intended as a simplified
methodology that water quality planners in nondesignated 208 areas could
use to perform preliminary assessments of surface water quality.  The
method covered primarily the identification of problem areas for sediment,
nutrients, dissolved oxygen, and some urban pollutants in streams, lakes
and estuaries.

     The original methodology was used by its developers, Tetra Tech, Inc.,
as instructive materials in EPA workshops on water quality assessment.  It was
also used in an EPA project designed to test the methodology.   In that project,
elements of the procedures were applied to the Sandusky River in northern
Ohio and to the Ware, Patuxent, Occoquan, and Chester Rivers in Virginia
and Maryland.  Testing results were favorable for phosphorus and reasonable
for nitrogen  (nitrate loading was a problem) and were reported in two
publications  (Dean et al_., in press; Dean ejt al_., 1981).

     As feedback was acquired from individual users and workship partici-
pants, there arose a need to reassess the methods available in light of
new technical developments and new priorities in water pollution assess-
ment and control.  To this end, the original screening method (Zison e_t al_.,
1977) has been revised and updated to include the assessment of toxic
chemicals in the environment.  The title has been changed to reflect the
new content of the screening procedure.

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1.2  PURPOSE AND SCOPE

     This report contains a simplified methodology which can be used by
planners or engineers to perform preliminary assessment of toxic and
conventional pollutants in surface waters.   Conventional pollutants include
suspended sediments, nitrogen, phosphorus,  coliform bacteria, BOD and
dissolved oxygen deficits.  The 129 EPA priority pollutants are included in
the sections on toxic chemicals.  The analyses require little external
input, since much data are supplied by figures and tables in the text or
appendices.  Additional data can be found in Zison et_ al_., 1978.  All the
algorithms are intended to be used on a desk-top calculator.

     Where instructive, introductory material has preceded the actual
presentation of water quality assessment methodologies.  This was done to
orient the planner toward pertinent background material, as well as to
clearly state limitations of the methodologies due to assumptions and
simplifications.  Further, example calculations of the major emphases within
each chapter are included to illustrate the ideas being presented.  These
examples are designed to unify the theory that has preceded  it, as well as
in some cases to introduce new but related ideas.

     The units most commonly used  in this report are those that historically
appear in the literature.  Often, the units are not metric.  Consequently an
english-metric-conversion appendix is included at the end of this report.
Many equations are presented with both English and metric constants.

     The report is divided into five major chapters (two through six).  A
brief description of the content of each chapter is presented  in the
following paragraphs.

     •   Chapter 2 deals with the environmental chemistry of toxic
         chemicals.  Processes considered include photolysis,
         hydrolysis, volatilization, biodegradation and adsorption.
         The purpose of the chapter is to provide an understanding  of
         the processes and to provide procedures for estimating
         associated rate  and equilibrium constants.

-------
•   Chapter 3 deals with the estimation of pollutant loads from
    nonpoint and point sources for both toxic and conventional
    pollutants.  Procedures include load estimation for single
    event and annual loads from agricultural, forested, and urban
    areas.

0   In Chapter 4, impacts of point and nonpoint sources of
    conventional and toxic pollutants in rivers are addressed.
    Conventional pollutant interactions presented include BOD-DO,
    temperature, coliform bacteria, nutrients, and sediment
    transport.  Fate of toxic chemicals is assessed using
    volatilization, sorption and first order degradation.  Methods
    are also presented to handle large spills of toxic chemicals
    having density the same as or different from the receiving
    waters.

•   Chapter 5 contains methods for assessing water quality in
    impoundments.  The topics covered are sediment accumulation,
    thermal stratification, BOD-DO interactions, eutrophication,
    and fate of  toxic materials.  The physical/chemical processes
    governing the fate of toxicants as well as biological uptake
    and bioconcentration are considered.

•   In Chapter 6, methods are presented for estuary
    classification, flushing time prediction, and transport of
    conservative and non-conservative pollutants and dissolved
    oxygen in well-mixed extuaries.  For stratified estuaries,
    Pritchard's box model is used to determine the distribution of
    conservative materials.  Additionally, methods are presented
    to calculate initial dilution from a waste water discharge and
    pollution distribution at the completion of and subsequent to
    initial dilution.

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1.3  METHODOLOGY APPLICATION

     For each category in the methodology,  the six conceptual  steps shown
below should be followed to screen a river  basin:

     t   obtain necessary tools and data to make calculations  and
         utilize nomographs, etc.;

     •   identify problems that are obvious from inspection of the data
         base;

     •   determine the state variables which will  be screened;

     t   apply procedures and compare where possible to observed data;

     t   consider consequences of errors;  and

     •   reevaluate and make recommendations.

The techniques in the screening procedure are designed to interact which
makes them ideal for use as an analytical tool for river basin surface
waters which may include rivers, lakes, and/or estuaries.  Although the
procedures may interact, they can be applied individually and  with
identified data sets for specific case studies.


1.3.1  Base Maps

     The first step in the screening process can be to obtain  large scale
topographic maps of the study area.  These can be used to determine which
water bodies are to be examined and to establish an order of study.  Once
this has been done, selected small scale (7 1/2-minute or 15-minute series)
topographic sheets can be obtained.  On these, the planner can locate and
mark point source discharges, regions of specific kinds of land use,
population centers, and industrial complexes.  Use of overlays or push pins
may be helpful in preparing these displays.

-------

-------
     The maps are also very important in showing the relationships among
water bodies and the flow patterns for stormwater runoff.   Mnally,  control
strategies may be displayed for examination on the maps.
1.3.2  Data Collection

     Once the base maps are prepared, the kinds of data needed should be
fairly clear in most cases.  In general terms, the only data that will not
be provided in this methodology are climatic and hydrologic data.

     Hydrologic data includes such items as:

     0   Runoff quantity

     •   Stream flows (low flows, statistical flows such as 7Q10,
         critical flows to be protected as decreed by law)

     «   Inflows and outflows, stagnant regions, stratification,
         internal flow patterns

     e   Estuarine tidal prism

     Much of the necessary hydrologic data will be available from the USGS,
state geological surveys, state environmental protection agencies, and other
governmental organizations.  In addition, data may be available from the
private sector, from universities, local citizens groups, and private firms.

     Hydrologic data must usually be analyzed  to serve as a basis for
subsequent water quality analyses.  Statistical methods may be applied to
determine the annual runoff, monthly runoff,  and critical flow for a
stipulated return frequency, on a selected time basis.

     To select critical flow, for example, one must have some base knowledge
of the seasonal distribution of stream flow  and quantity-quality
relationships.  In general,  the summer low flow is considered as the
critical condition for stream and estuarine  analyses.  Average annual runoff

-------
is to be used for lake analyses,  even though wet  years  are  generally more
critical from the standpoint of lake water quality.

     Climatic data may also be needed.   Generally these are available from
the National Climatic Center in Ashville,  North Carolina.   This  agency can
provide data summaries of various kinds for a large  number  of weather
stations.  Data include precipitation,  cloud cover,  humidity, and other
important parameters.  Computer tapes can  often be provided.

     In collecting data for the area to be screened, the Reach File data
base (EPA, In Press) may also be useful.  This data base contains
information for over 68,000 river reaches  in the  48 contiguous states.  The
Reach File provides a unique index for each of these river  reaches and a
systematic way of retrieving the hydrologic or water quality information
which is available.
1.4  LIMITATIONS

     The processes which govern the fate of pollutants in the environment
are complex.  A methodology such as this, designed for hand calculation,
cannot be inclusive of all of these processes nor in all cases are the
methods state-of-the-art.  An attempt has been made in each chapter to cover
the assumptions under which the algorithms are developed.  Users should be
aware of the assumptions, potential errors, and limitations of the tools
presented.  When deficiencies are noted or the methods deemed inappropriate,
the user should be prepared to use a higher level analytical tool.

-------
                                 REFERENCES
Dean, J.D., W.B.  Mills and D.B.  Porcella.   1981.    A  Screening   Methodology
     for  Basin  Wide  Water Quality Management.   Symposium on Unified  River-
     Basin Management.  R.M. North,  L.B.  Dworsky   and   D.J.  Allee  (editors)
     May 4-7, 1980, Gatlinburg,  Tennessee.

Dean, J.D., B. Hudson and W.B.  Mills.  (In  Press)  River Basin Validation   of
     the   MRI  Nonpoint  Calculator  and   Tetra   Tech's  Nondesignated  208
     Screening Methodologies, Volume II.   Chesapeake-Sandusky  Nondesiqnated
     208 Screening Methodology Demonstration.   U.S.  Environmental Protection
     Agency, Athens, Georgia.

U.S. Environmental Protection Agency (In  Press).    An   Introduction  to  the
     Reach  File  and  Reach  File  Directory.    MonHoring Branch (WH-553).
     U.S. Environmental Protection Agency,  Washington,  D.C.  20460.

Zison, S.W., K. Haven, and W.B.  Mills,  1977.   Water Quality Assessment:    A
     Screening  Methodology  for Nondesignated  208 Areas.   F.PA-600/9-77-023,
     U.S. Environmental Protection Agency,  Athens, Georgia.

Zison, S.W., W.B. Mills, D. Deimer,  and C.  Chen,   1978.   Rates,   Constants,
     and   Kinetics  Formulations  in  Surface  Water    Quality     Modeling.
     EPA-600/3-78-105,  U.S. Environmental    Protection   Agency,    Athens,
     Georgia.

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                                 CHAPTER 2
                  AQUATIC FATE OF TOXIC ORGANIC SUBSTANCES
2.1  INTRODUCTION

2.1.1  Background

     Today's technological society generates enormous quantities of
chemicals both as products for consumption and as waste.  As the volume and
number of chemicals has increased, numerous unintended adverse effects of
these chemicals have been observed in the environment.  Because of the
potential hazard that exposure to these compounds poses to biota, the levels
of toxic and carcinogenic substances in the environment have become
important criteria for evaluating environmental quality.

     The level, or concentration, of a toxic compound in the environment
depends on the quantity added to the environment and  the processes which
influence its fate.  "Transport" processes tend to distribute chemicals
between the atmospheric, aquatic, and soil environments depending on the
affinity of the compound for each phase.  "Transformation" processes within
each phase chemically alter pollutants to forms of lesser, equivalent, or
sometimes greater toxicity.  These processes occur at rates which are
specific to each chemical and to each environmental compartment.  The sum of
these processes and their interactions, as Figure II-l  illustrates,
determines the environmental fate and consequent exposure of biota to a
toxic pollutant.  The fate of toxic substances in the aquatic environment  is
the  concern of this chapter.
2.1.2 Comparison of Conventional arLd_Toxic__Pql_]_L[tants

     Toxic  substances frequently exhibit properties which  are quite
different from the properties of conventional  aquatic pollutants.   It  is
worthwhile  to compare these differences  in order  to better  appreciate  the

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             SOURCE
                            TRANSPORT AND
                           TRANSf ORMATION
CHEMICAL
EXPOSURE
       FIGURE  II-l    ENVIRONMENTAL FATE  OF A  Toxic
                        POLLUTANT  (AFTER  HAGUE,  1980)
problems of analyzing  impacts of toxicants in surface water  systems.  Table
II-l shows  some  of  the more  important differences.
     Typically,  one  to  two dozen pollutants and water quality  parameters are
classified as  "conventional".  Until the past several years, these
parameters (e.g.   BOD,  nutrients) have received most of the attention  of
water quality  planners.   In  contrast to the small number of conventional
pollutants there are thousands of toxicants and many more synthetic
chemicals are  continually being developed.  Potentially, any of  these
toxicants could  enter the environment.

-------
                                 TABLE  II-l

           BRIEF COMPARISON OF CONVENTIONAL  AND TOXIC POLLUTANTS
          Conventional
          Toxic
One to two dozen pollutants fall  into
this category

Often large quantities required to
produce impact (e.g. thousands
Ibs/day)

Concentrations often expressed as
ppm (mg/1)

Often travel in dissolved form
Mean residence time within water
bodies often equal to or less
than the mean residence time of
moving waters

Many biodegrade into harmless
substances
Thousands fall into this category;
many more being synthesized

Small quantities can produce
impact (e.g. few Ibs/days)
Concentrations often expressed as
ppb (yg/1), or in smaller units

May be highly sorbed to suspended
and bedded sediments

Can reside in bedded sediments
for years
Many are transformed to chemicals
which are also toxic; others are
resistant to degradation and
bioconcentrate
                                      10

-------
     Even though there are relatively few types of conventional pollutants,
numerous sources combine to routinely discharge large quantities.  However,
because many surface water bodies have a capacity to assimilate conventional
pollutants (e.g. BOD) without apparent adverse effects, this practice is,
within limits, both acceptable and pragmatic.  Toxic substances, on the
other hand, can cause adverse effects even at low discharge rates.

     Concentrations of conventional pollutants are most often expressed in
units of ppm (or mg/1).  Because of the small quantities of toxicants which
are typically released, concentrations are often expressed in the ppb (or
yg/1) range, or in even smaller units.  This represents at least a thousand
fold difference relative to concentrations of conventional pollutants.
However, because toxic substances present in small amounts can adversely
impact the environment, these small concentrations can not always be
ignored.

     Many conventional pollutants are transported in dissolved form.  The
mean residence times of dissolved, conservative pollutants in a system is
equivalent to the mean residence time of water in the system, which is:

     •   the hydraulic detention time for freshwater lakes

     •   the travel  time for freshwater rivers;  and

     •   the flushing  time for estuaries.

Many toxic chemicals strongly sorb to suspended and bedded sediments and
consequently can become a part of the immobile sediments in the bed.  The
residence time of such chemicals can be on the order of years.  Therefore,
depending on the properties of the toxicant the period of impact can greatly
exceed the period of discharge (e.g. a PCB spill may occur in a few minutes,
but quantities of the PCB may remain in immobile, bedded, sediments for
years).  Consequently the recovery period of a system can be years.
                                     11

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2.1.3 Water Quality Criteria

     As previously indicated, toxicants are present in the environment in
quantities which are often measured in the ppb range.   Such small
concentrations are often foreign to many workers in the field.   When data or
model predictions contain concentrations in the ppb range, the significance
of the toxicant level is not always obvious (i.e.  there is no "feel" as to
whether the concentration is large or small).  Proposed criteria for toxic
substances can serve as a basis to gauge the significance of observed or
predicted levels.  Table II-2 shows proposed criteria for numerous
toxicants.  Since proposed criteria evolve over time the criteria shown in
the table are not necessarily the most current.  Nevertheless, their
function remains:  to provide a comparison with levels observed or predicted
in real systems.  The data in these tables come from the "Red Book"
(U.S. EPA, 1976) and the Federal Register, March 15, 1979;  July 25, 1979;
October 1, 1979;  and November 28, 1980.  Criteria, designed to protect
human health, for levels of toxicants in domestic water supplies, are
available from these same sources as well.
2.1.4  F reguencyJ3f.J31scharge of Toxic_S_ubstances__frqrn_I_ndustr|es

     Numerous organizations, including the U.S.  Department, of
Transportation and the U.S.  Environmental Protection Agency, continually
collect and analyze data on the discharge of toxic substances.  Table II-3
summarizes the results of  a study reported by Keith and Telliard  (1979)
which  shows the frequency  of detection of the 129 priority pollutants in
industrial wastewaters.  A total of 32 industrial categories were analyzed
for organics  and 28 for metals.  The number of samples ranged from 2532 to
2988.  Table  11-4 summarizes the most  commonly discharged priority
pollutants.   Table 111-53, shown in the next chapter, provides a  breakdown
by  industry of the occurrence of priority pollutants  in industrial effluent.

     It  is common in this  country for  numerous industrial plants  to release
their  effluent into a single water body.  Because of  this situation a
question that naturally arises  is:  Based on the number and type  of
industries located on the  water body,  what kinds of toxic chemicals are
likely to be  discharged there ?  If the industrial categories of  each plant
                                     12

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                    TABLE 11-2
PROPOSED CRITERIA FOR TOXIC  SUBSTANCES DESIGNATE)
              TO PROTECT AQUATIC LIFE
                                                  Sa i i
COMPOUND
Acenaphthene
Acrolein
Acrylonl trlle
Aldrin/Dieldrin
Antimony
Arsenic
Asbestos
Benzene
Benzidine
Beryllium
Cadmium

Carbon Tetrachlorlde
Chlordane <•
Chlorinated benzenes
Chlorobenzene
1,2,4 - Trichlorobenzene
1,2,3,5 - Tetrachlorobenzene
1,2,4,5 - Tetrachlorobenzene
Pentachlorobenzene
Chlorinated Ethanes
1,2 - Dichloroethane

1,1,1 - Trichloroethane
1,1,2 - Trichloroethane
1.1,1.2 - Tetrachloroethane
1,1,2,2 - Tetrachloroethane
Pen tac hi oroe thane
Hexachloroethane
Chlorinated Naphthalenes
Chlorinated Phenols
4 - Chlorophenol
2,4,6 - Trichlorophenol
CMoroalkyl Ethers
Chloroform
2 - Chlorophenol
Cftroriun (Hcxavalent)
Ccpper
C,;r,,de
DDT
24 Hour
Average
M9/1
LDa
21C
2600°
0.0019
1600
40C
LD
LD
LD
5.3°
d

620
0.0043

150Qh
210h
170h
97h
16h

3900h
h
5300h
310h
420h
170h
440h
62h
29

45
52
LD
500
60
0.29
5.6
3.5
0.00023
Maximum
ug/l
1700b
68b
7550b
2.5
9000
440b
LD
5300b
2500
130b
e

1400
2.4

3500h
470h
390h
220h
36h

8000h
i.
12000"
710h
960h
380h
ioooh
140h
67

180
150
LD
1200
180
21
1
52
0.41
.. .. 24 Hour
"Red Book" Average
710C
LO
LD
0.003 0.0019
LD
LD
LD
700°
LD
11. -1100 LD
0.4-l.Zf 4.5
4. 0-12. O9
2000
0.01 0.0040

120h
3.4h
2.6h
9.6
1.3h

880h
t.
240h
LD
LD
70h
38
7.0h
2.B

LD
LD
LD
620h
LD
100 18
j 4.0
5.0 LD
.001 O.C067h
Maximum "Red Book"
pg/1 yg/l
970b
55b
ID
0.71 0.003
LD
508b
LD
5100b
LD
LD
59 5.0

4000
D.09 0.004

280h
7.8h
5.9h
26
2.9h

2000h
h
54 Oh
LD
LD
160h
87
16h
6.4

LD
LO
LO
HQOh
LD
1?60
23 J
LD 5.0
0.021h .001
L i c f "!(jrc,L(_r,2eriei

    1,2 - DicMor&t t r,7tne



    1 • ^ - C-')cMt,rcI;r.7ene
              44
             310
                         59
                                13

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TABLE 11-2 (Continued)

COMPOUND
3,3' - Dichlorobenzidine
Dichloroethylenes
1,1 - Dichloroethylene
1,2 - Dichloroethylene
2,4 - Dichlorophenol
Olchloropropanes and
Dlchloropropenes
1,1 - Dichloropropane
1,2 - Dichloropropane
1,3 - Dichloropropane
1,3 - Dichloropropene
2,4 - Dimethyl phenol
Dim trotoluenes
2,3 - Dim trotoluene
2,4 - Dim trotoluene
1,2 - Diphenylhydrdzine
Cndosul fan
Endrui
Enthylbenzene
Fluordnthene
Haloetherb
4 - bi oniopheny 1 pht^nyl ether
Ha lunie thdnes
Chloromethane
Broinomethdrie
DiUiloromethdrie
Tr i bi onioiiietharie
Heptdchlor
Hexdchlorobutadiene
Hexd^h) orOLyclohexdne
L i nddtie
Other isomers
Huxav.nl or ucyclopen tad leiie
1 ^optior une
tedd
Mercury (tutdl)
Naphthalene
nickel
M trobenzene
24 Hour
Average
ug/1
LD



0.4

410
920
4800
18
38

12
620
17
0.042
0.0023
LD
250h

6.2

7000
140
4000h
840h
0.0038
LD

0.080
LD
0.39
2100
k
0.2
LD
n
480
Freshwater

Maximum "Red Book"
M9/1 pg/1
LD

11600
11600
110

930
2100
11000
250
86

27
1400
38
0.49 0.003
0 18 0.004
LD
560h

14

16000
320
9000h
1900h
0.52 0.001
LD

2.0
LD
7.0
4700
1 m
4 1 0.05
LD
0 p
1100
24 Hour
Average
M9/I
LD

224000
224000
LD

LD
400h
79
5.5h
LD

4.4h
LD
ID
LD
0.0023
LD
0.30

LO

3700h
170h
1900h
180
0.0036
LD

LD
LD
LD
97
25b
0.10
LD
7 1
53
Saline Watei

Maximum "Red Book"
M9/1 ug/I
LD



LD

LD
910h
180
14h
ID

10"
ID
LD
LD 0 OU1
0 037 0.004
LD
0.69

Lll

8400h
380h
440Uh
420
0 053 0.001
LD

0.16
LD
LO
220
668b
3.7 U.10
LD
140 p
120
        14

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                                      TABLE  11-2   (Continued)


COMPOUND
Nitrophenols
2 - Nitrophenol
4 - Nitrophenol
2,4 - Oinitrophenol
2,4 - Dinitro-6-methylphenol
2,4,6 - Trinitrophenol
N-Nitrosodiphenylamine
Pentachlorophenol
Phenol
Phthalate esters
Polychlorinated biphenyls
Polynuclear aromatic hydrocarbons
Selenium
Silver
2,3,7,8 - Tetrachlorodibenzo-
p-dioxin
Tetrachloroethene
Tha 1 1 i urn
Toluene
Toxaphene
Trichloroethene
Vinyl chloride
Zinc
dLO denotes IJCK of data
SA^ute toxicit, ievel


he vjlue in .g/1 should not excee exp [1
"The value in ug/1 should not exceed exp [1


'the value in ug/1 should not exceed exp [0
For freshwater and marine aquatic life, 0.1
The value in ug/1 should not exceed exp [2
The value in ug/l should not exceed exp [1

24 Hour
Average
ug/1

2700h
240h
79h
57h
1500h
LD
6.2
600
LD
0.014
LD
35
0.0090
LD

310
LD
2300h
0.013
1500
LD
47




03 n (hardness,
05 In (hardness)


94 In (hardness
Freshwater

Maximum "Red Book"
P9/1 ug/1

6200h
550h
180h
140h
3400h
LD
14
3400
LD 3.0
2.0b 0.001
LD
260 p
1.9 p
LD

700
LD
5200h
1.6 0.005
3400
LD
q P




-u DJJ w ere hardness is expressed in .nq;
-3 73] where hardness is expressed in nq,


-1 23)] .where hardness is expressed in rtg
times a 96 hr LCcn ds determined through nonaerated tnoss
15 In , hardness)
22 In (nardness)
-9 48] where hardness is expressed in mq/
-0 47] where hardness is expressed in rug.
0.01 times the 96 hour LC,~ value, using the receiving ar comparable water as the diluent and soluble
nlhe value in ug/1 should not exceed exp [0
°7he value in ^g/1 should not exceed exp [0
°For marine and/or fresh water aquatic life.
resident species
The value in t.g/1 should not exceed fxp [0
76 In ' hardness)
76 In (nardness)
0 01 of the %

;;j In (hardness)
*•! 06] where hardness is expressed in mg/1
+4 02] where haraness is expressed it\ mg/1
hour LCcn as determined through bioassay j

* 1 95] where hardness is expressed in "ig
Saline Hater
24 Hour
Average Maximum
ug/1 ug/1

LD LD
S3 120
37h B4h
LD LD
150h 340h
LD LD
3.7 8.5
LD LD
LD LD
0.030 10b
LD LD
54 410
0.26 2.3


79 180
LD LD
100 230
LD 0.07
LD LD
LD LD
58 170



1 is CaC03
1 as CaCOj


/I as CaC03
ay using a sensitive
i is CaCOj
: as CaC03
lead measurements
as CaC03
as CaC03
sing a sensitive

, 1 as CaCOj.

"Red Book"
ug/1










0.001

P
P





0.005




















"Red Book" (U 5.EPA 1976)
Federal Register nn these dates.
March 15, 1979 - July 25, 1979 - October 1, 1979 - November 29, 198C
                                           15

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                                           TABLE 11-3
         EPA  LIST OF 129  PRIORITY POLLUTANTS  AND THE  RELATIVE  FREQUENCY  OF
                        THESE  MATERIALS  IN  INDUSTRIAL WASTEWATERS
                               (After Keith anH  Telliard,  1979)
Percent
Of »
Sables'
Number of Percent . Number of
Industrial. of Industrial
Categories Samples Categories
b
Purgeable Organic*
1.2
2.7
29.)
29.3
16.7
7.7
5.0
6.5
10.2
1.4
7.7
1.9
4.2
0.4
1.5
40.2
5
10
25
28
24
14
10
16
25
8
17
12
13
2
1
28
Acroleln
Acrylonitrlle
Benzene
Toluene
Ethylbenzene
Carbon tetrachloride
Chloroaer.zer.e
1,2-Dichlorcethane
1,1 . 1-Trichloroe thane
1.1-Dichloroethane
1,1-Dichloroethylene
1,1.2-Tnchloroetnane
1,1 ,2,2-Tetrachloroetnjne
Chloroethane
2-Chloroethyl vinyl ether
Chloroform
2.1
1.0
34.2
1.9
0.1
1.9
4.3
6.8 x
0.3
2.5
10.2
10.5
0.2
7.7
0.1

5
5
25
6
1
12
17
11
4
15
19
21
2
18
2

1,2-Dichloropropane
1,3-Dtchloropropene
Hethylene chloride
Methyl chloride
Methyl bromide
Brornofonn
01 chlorobroT^oe thane
Trichlorofluorcme thane
Dtchlorodl fluorome thane
Chlorodi bronoTie thane
Tetrachloroethylene
Trlchloroethylene
Vinyl chloride
1,2- trans -DicMoroe thy lene
b1s(Chloronethyl)ether

B as e/Heutral Extract able Organic Compounds

6.0

0.5
0.2
1.1
1.0
0.4
10.6
0.9
1.5
1.8
1.1
1.5
0.04
41.9
6.4
5.6
7.6
18.9
4.5
4.2
8.5
26.1
2.3
2.2
1.6
t.l
fc.&

0.3
0.4
0.2
0.6
0.8
0.2
0.5
0.5
0.1
0.04
0.1
0.2
0.2
0.2

18.2
19.9
14.1
30.7
53.7
55.5
43.8

33.4


9

5
1
7
8
3
18
9
13
9
3
9
1
29
12
15
20
23
12
14
13
25
11
9
6
6
18

3
4
2
4
6
4
3
5
3
1
2
2
3
2

20
19
18
25
28
28
27

19

!l,2-D1chlorobenzene
1,3-Dtchlorobenzene
1,4-Dichlorobenzene
Hexachloroethane
Hexachlorob'jtadiene
Hexach) orotenzene
1,2,4-Trichlorobenzene
bi s ( 2-Chlo roe tnoxy)rr,e thane
Naphthalene
2-Chloronaphthalene
Isophorone
Nitrobenzene
2.4-Dimtrotoluene
2,6-Dim trotoluene
4-Bromopnenyl phenyl ether
bts(2-Ethylhexyl)phthalate
Bl-n-octyl phtnalate
Dimethyl phthalate
Diethyl phthalate
Di-n-butyl phthalate
Acenaphthylene
Acenaphthene
Butyl benzyl phthalate
Acid Extractable Organic
Phenol
2-NHrophenol
4-N1 trophenol
2,4-Dinitrophenol
4,6-Dfni tro-o-cresol
Pentachloropnenol
Pesticides/PCB1
a-Endosulfan
B-Endosulfan
Endosulfan sulfate
o-BHC
B-BHC
4-BHC
f-BHC
Aldrin
Dieldrln
4,4'-DOE
4.4I-DDO
4.4--DOT
Endrin
Endrin aldehyde
Ketals
Ant ir.ony
Arsenic
Beryllium
Cadniun
Chromium
Copper
Lead
Miscellaneous
Total cyanides

5.7
7.2
5.1
7.8

10.6
2.3
1.6
1.8
3.2
0.8
0.2
0.6
0.1
0
0.2
1.1
0.8
0.1
1.2
0.1
0.1
1.4
Compounds
1.9
2.3
3.3
4.6
5.2

s
0.3
0.1
0.2
0.2
0.6
0.5
0.9
0.8
0.6
0.6
0.5
-



16.5
34.7
18.9
22.9
19.2
54.6


Not available
Not available
11
12
9
14
• r
lo
6
6
6
a
4
4
7
2
0
4
4
7
1
5
1
2
6
8
10
12
12
15


3
1
4
2
2
1
2
3
2
3
1
-



20
27
21
25
19
28




Fluorene
Fluoranthene
Chrysene
Pyrene
{Phenanthrene
Anthracene
Benzo(a)anthracene
Benzojbjfluoranthene
Benzofkjfluoranthene
Benzo(a)pyrene
Indenot 1 ,2 ,3-c ,d)pyrene
D1 benzol a, h) anthracene
Benzo(g,h,1 jperylene
4-CMorophenyl phenyl ether
3,3'-Dichlorobenz1dine
Benzldine
bis(2-Chloroethyl)ether
1,2-Diphenylhyarazine
Hexachlorocylcl open tad iene
N-Hi trosodl phenyl am) ne
N-Ni trosodi methyl ami ne
K-Nitrosodi-n-propylamlne
b1s(2-Chlorouopropyl Jether
p-Chloro-m-cresol
2-Chlorophenol
2,4-Dichlorophenol
2,4,6-Tnchloropnenol
2,4-DiMthylphenol


Heptachlor
Heptachlor epoxide
Chlordane
Toxaphene
Aroclor 1016
Aroclor 1221
Aroclor 1232
Aroclor 1242
Aroclor 1248
Aroclor 1254
Aroclor 1260
2,3,7,8-Tetrachlorodibenzo-p-d!oxin (TCD



Mercury
Nickel
Selenium
Silver
Thallium
Zinc


Asbestor (fiborous)
Total phenols

"The percent of sarples represents the Purler of tir^s this co-sound fcjs found In all Si-pies In wllch it was analyzed for divided
 the total as of 31 August 1978.  Nu-^ers of Si-jles ran5ed fror, 2532 to 2958 with the average being 2617.

^A tctal  of 32 IrdjStrul categaries ft 5-tcategcries were analyzed for orgjnics and 28  for ratals as of 31 August 1978.


                                                 16

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                 TABLE 11-4



MOST COMMONLY DISCHARGED PRIORITY POLLUTANTS
Non-Metals
Pollutant
Bis (2-Ethylhexyl) Phthalate
Chloroform
Methyl ene Chloride
Total Cyanides
Toluene
Benzene
Phenol
Di-.n-Butyl Phthalate
Ethyl benzene
Naphthalene
Phenanthrene and Anthracene
Metal
Pollutant
Copper
Zinc
Chromium
Lead
Nickel
Percent of
Samples
41.9
40.2
34.2
33.4
29.3
29.1
29.1
18.9
16.7
10.6
10.6
s
Percent of
Samples
55.5
54.6
53.7
43.8
34.7
Percent of
Industries
91
88
78
59
88
78
78
72
75
56
50
Percent of
Industries
100
100
100
96
96
                       17

-------
are known,  the probability that a particular  pollutant  is  discharged from at
least one of the plants is:
                               n  /     f. .  \
                     pj ~~l  ~   n  I1" roo  )   j = lj M               •TI~P

where

     f  _ = relative frequency of discharge of pollutant type j from
           plant type  i, expressed as a percent

     P.  = probability that pollutant type j is discharged from at
            least one of the n plants  located on the water body.

     M  = number of toxic substances  being analyzed

     If the  industrial categories of  the plants are not known, then the
probability  that a particular pollutant is discharged can be estimated using
Table  11-3  together with  the following formula:

                                              j = 1,M                 (H-2)
                        J         1     J-UW I

where

     g  = percent of samples containing pollutant j
       j
     P  - probability  that  pollutant  j is  detected in at  least one  of
          the n discharges.

Equation  II-l is obviously  the  more  accurate of the two formulae, because  it
 is  based on  a knowledge of  the  types  of  industries which  discharge.
Although the above equations provide  information on the  likelihood  that
different chemicals  are discharged  into  the environment,  and  thus can be
used to prioritize investigative efforts,  they do not predict  quantities of
pollutants  which are discharged.  Chapter  III can be used to  generate that
type of information.
                                     18

-------
2.1.5  Physical _and Chemi_caT_ Characteristics of Tqxi_c Organic Compound-:;

     The most  intensively investigated toxic pollutants, as a qroup, are the
priority pollutants.   Because  of  the  greater  availability  of  data  on
priority  pollutants  from  such  sources as Cal lahan et _a_1_. (1979), Billing
_et al_. (1975), and Mackay  and  Leinonen  (1975),  data  are  presented  for
organic priority pollutants in the following categories:

     •   Halogenated Aliphatic Hydrocarbons (Table II-5)
     t   Pesticides (Table II-6)
     »   Polychlorinated Biphenyls (Table II-7)
     «   Monocyclic Aromatic Hydrocarbons (Table 11-8)
     •   Polycyclic Aromatic Hydrocarbons (Table II-9)

The  properties of the pollutants tabulated in Tables II-5 through II-9 are:

     •   Vapor pressure, Torr (1 Torr - 1 mrn-Hg)
     9   Solubility
     t   Octanol-water partition coefficient (K  )
                                               ow
     »   Volatilization half-life
     •   Qualitative statement of the importance of sorption.

     Specific  information is included in the tables for  volatilization  and
sorption  because  of  the  demonstrated  importance  of  these processes  in
governing the  fate of many pollutants.   In  particular,  for  the  approxi-
mately 103 organic priority pollutants:

     •   Sorption processes are important for 60
     •   Sorption is not important for 28
     •   It  is not certain if sorption is important for the remaining 15
     0   Volatilization is important for 52
     •   Volatilization is not important for 44
     •   It  is uncertain if volatilization is important for the remaining 7.

     The volatilization half-lives presented in the  tables  were  typically
measured under a specific set of laboratory conditions, and consequently are
shorter  than  in  most  natural  systems.   Other useful properties such as
                                      19

-------
                                    SELECTED  CHARACTERISTICS
TABLE  11-5

OF VARIOUS ALIPHATIC HYDROCARBONS
ro
o
Halogcnated Al iphatic
Hydrocarbons
Chloromethane
Oichloromethane
Trichloromethane (chloroform)
Tetrachlorome thane
(carbon tetrachtorlde)
Chloroethane
1 ,1-Oichloroe thane
1 ,2-Dicnloroethane
1, 1, 1-Tric hi oroe thane
1,1 ,2-Trichloroethane
1 , 1,2,2 -Tetrac hi oroe thane
Hexachloroethane
Chloroetnene
(vinyl chloride)
1 ,1-Dichloroethene
1 ,2-trans-Dichloroethene
Trichloroethene
Tetrachloroethene
1,2-Dichloropropane
1,3-Dichloropropene
Hexachlorobutadiene
Hexdchlorocyclopentadiene
Rromo methane
Onmudi Chloromethane
Di bromochl orpmrthanp
Trihromome thane
Dichlorodi fluorome thane
Trichlorof luoromo thane
Vapor Pressure (Torr)
at 20"C
3700
362
150
90
1000
180
61
96
19
5
0.4
2660
591
200
57.9
14
42
25
0.15
0.081 at 25"C
1420
50
15
10
4306
667
Soluhil ity
6450-7250 mg/1
at 20"C
13000-20000 mg/1
at 25°C
8200 mg/1 at 20'C
785 mg/1 at 20°C
5740 mg/1 at 20"C
5500 mg/1 at 20°C
8690 mg/1 at 20'C
440-4400 mg/1 at 20"C
4500 mg/1 at 20°C
2900 mg/1 at 20"C
50 mg/1 at 22"C
60 rog/1 at 10°C
400 mg/1 at 20°C
600 mg/1 at 20" C
1100 mg/1 at 20°C
150-200 mg/1
2700 mg/1
2700 mg/1
2
0.8 mg/1
900 mg/1
-
-
3000 mg/1
280 mg/1
1100 mg/1
^ow
8
20
93
400
35
60
30
150
150
360
2200
4
30
30
200
760
190
95
5500
10"
10
75
120
200
145
3400
Volati 1 iza tion
Half-Life
27 minutes3
21 m1nutesa
21 minutes3
29 minutes3
21 minutes3
22 minutes3
29 minutes3
20 minutes3
21 minutes
56 minutes3
45 minutes3
26 minutes3
22 minutes3
22 minutes3
21 minutes3
26 minutes3
<50 minutes3
31 minutes3
-
-
%30 minutes
-
-
-
few minutes
few minutes
'orption
Important?
HO
Probably Not
Probably Not
Uncertain
Probably Not
Probably Not
Probably Not
Probably Not
Uncertain
Uncertain
Uncertain
Probably Not
Probably Not
Probably Not
Probably Not
Probably Not
Probably
Uncertain
Probably
Probably
Probably Not
Uncertain
Uncertain
Uncertain
Probably
Uncertain
                        Stirring in an open container of depth 65 mm at 200  'PM filling e^aj.

-------
ro
                                                              TABLE 11-6



                                          VARIOUS CHARACTERISTICS OF SELECTED PESTICIDES
Pesticide
Acroleln
Aldri'n
Chlordane
ODD
DDE
DDT
Dieldrin
Endosulfan
Endrln
Heptachlor
Heptachlor Epoxide
He xachlo recycle he xane
Lindane
Isophorone
TCDD
Toxaphene
Vapor Pressure (Torn)
220 at 20°C
330 at 30°C
2.3xlO's at 20°C
6xlO'6 at 25°C
IxltT5 at 25°C
10.2-18.9xlO'7 at 30°C
6.2-6.5x10"' at 20°C
l.SxlO'7 at 20°C
1.9X10'7 at 25°C
1.8xlO"7 to
2.9xlO"7 at 20°C
IxlO'5 at 25°C
ZxlO'7
3xlO'"
-
lO'Mo-'
io-"-io~6
0.38
-
0.2-0.4
Solubility
20.8% at 20°C
17-180 ppb at 25°C
0.056-1.85 ppm
20-100 ppb at 25°C
1.2-140 ppb at 20°C
2-85 ppb
186-200 ppb at 25°C
100-260 ppb at 20°C
220 ppb at 25°C
56-180 ppb at 25°C
200-350 ppb at 25°C
0.70-21.3 ppm at 25°C
5-12 ppm at 25°C
12000 ppm
0.2 ppb
0.7-3. ppm
Kow
0.8
"410
600
106
5x10*
10--10*
-
4x10'
4xl05
-
-
10"
5xl03
50
-
2000
Volatil ization
Hal f-Life
Uncertain
Few hours to
few days
Several weeks
1 day to 1 month
1 to 10 hours
4 hours-1 week
Few hours to
few days
11 days-1 year
-
-
-
-
100-200 days
Probably great
-
-
Sorption
Important?
No
Yes
Probably
Yes
Yes
Yes
Probably
Yes
Uncertain
Probably
Probably
Probably
Probably
No
Yes
Yes
                    Conditions described  in ".allahan et al .  (1979)

-------
                                                                  TABLE II-7


                               SELECTED CHARACTERISTICS OF  POLYCHLORINATED BIPHENYLS AND RELATED COMPOUNDS
ro
ro
PCBs and Related
Compounds
Aroclor 1016
Aroclor 1221
Aroclor 1232
Aroclor 1242
Aroclor 1248
Aroclor 1254
Aroclor 1260
2-chloronaphthalene
Percent
Chlorine
41
21
32
42
48
54
60
-
Density
(gm/cmf)
1.33
1.15
1.24
1.35
1.41
1.50
1.58
-
Vapor Pressure
at 25 C°(Torr)
4x10'"
6.7x10"'
4xlO's
4x10"*
4.9x10'*
7.7xlO's
4xlO's
0.017
Solubility
mg/1
0.42
15.
1.45
0.1-0.3
0.054
0.01-0.06
0.0027
6.47
KOW
2xlO*-3xlOs
600-10*
1.5xlO'-3xlO*
10*-4xl05
MO1
MO*
>10'
10*
Volatil ization
Half-Lives
In
laboratory
(hrs)»
9.9
-
-
12.1
9.5
10.3
10.2
-
Loss in b
Natural Systems
3.6X after 24 hours
4.2% after 24 hours
-
-
-
-
34X-67X after 12 weeks

              aAt  25°C 1n 1 m' of water, 1 m deep (MacKay and Lelnonen,  1975).


              bConditions described in Callahan et aj_.  (1979)

-------
                                                                        TABLE  11-8

                                           SELECTED  CHARACTERISTICS OF MONOCYCLIC  AROMATIC HYDROCARBONS
CO
Monocycl ic Aromatics
Benzene
Chlorobenzene
1 ,2-Dichlorobenzene
Hexachlorobenzene
Ethyl benzene
Toluene
2,4-Oinitrotoluene
2,6-Dinltrotoluene
Pentachlorophenol
2-Nitrophenol
4-Ni trophenol
2,4-Dinitrophenol
4,6-Dinitro-o-cresol
Vapor Pressure (Torr)
95. at 25°C
MO at 20°C
1.5 at 25°C
ID"5 at 20°C
7
29 at 25°C
0.001 at 59°C
low
0.0001
1.0 at 49°C
2.2 at 146°C
-
-
Solubil i ty
1800 mg/1 at 25°C
^500 mg/1
145 mg/1
^20 ug/1
152 mg/1
535 mg/1
270 mg/1 at 22°C
^300 mg/1
14 mg/1
2100 mg/1 at 20°C
16000 mg/1 at 25°C
5600 mg/1
-
KOW
100
700
2400
MO6
1400
500
100
100
10s
60
80
34
700
Volatil ization
Half-Life
4.8 hrs at 25°Ca
0.5-9 hrs
8-9 hours3
8 hours3
5-6 hours3
5 hoursa
MOO days
MOO days
>100 days
-
-
-
-
Sorption
Important?
Uncertain
Probably
Probably
Yes
Probably
Probably
Yes
Yes
Yes
Yes
Yes
Yes
Yes
                      °Mackay and Leinonen (1975).   Calculated b^sed on water depth of 1 m, and  using ii'ass transfer
                       coefficients of 20 cm/hr  and 3000 cm/hr  for the liquid and gas transfer phases, respectively.

-------
                            TABLE 11-9



SELECTED CHARACTERISTICS  OF VARIOUS  POLYCYCLIC AROMATIC HYDROCARBONS
Polycyclic Aromatics
Acenaphthene
Acenaphthylene
Flourene
Naphthalene
Anthracene
Fluoranthrene
Phenanthrene
Ben2o[a]anthracene
Benzo[b]fluoranthrene
Benzo[k]fluoranthrene
Chrysene
Pyrene
Benzo[ghi]perylene
Benzo[a]pyrene
Dibenzo [a] anthracene
lndeno[l,2,3-cd]pyrene
Vapor Pressure (Torr)
lO'Mo-2 at 20°C
lO-'-lO"2 at 20°C
IQ-'-lO'2 at 20°C
.0492
2x10-* at 20°C
10- 6 to 10-* at 20°C
6.8x10-* at 20°C
5xlO'9 at 20°C
II"11 to 10"6 at 20°C
9.6x10-" at 20°C
10'11 to 10'6 at 20°C
6.9x O'7 at 20°C
MO-"
5xlO-9
MO-10
MO'10
Solubility
3.4 mg/1 at 25°C
3.93 mg/1
1.9 mg/1
32. mg/1
0.05-0.07 mg/1 at 25°C
0.26 mg/1 at 25°C
1.0-1.3 mg/1 at 25°C
0.01 mg/1 at 25°C
-
-
0.002 mg/1 at 25°C
0.14 mg/1 at 25°C
0.00026 mg/1 at 25°C
0.0038 mg/1 at 25°C
0.0005 mg/1 at 25°C
-
KQW
21,000
12,000
15,000
2.300
28,000
340,000
29,000
4xl05
4x10'
7xl06
4xl05
2xl05
10'
106
106
5x10'
Volatilization
Important?
Less than sorption
Less than sorption
Less than sorption
Less than sorption
Probably
Probably Not
Probably Not
No
Probably Not
Probably Not
Probably Not
Probably Not
Probably Not
Probably Not
Probably Not
Probably Not
Sorption
Important?
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes
Yes

-------
molecular weight and specific gravity are available in  standard  references
such as Perry and Chilton (1973).
2.1.6  Scope and Organization of Chapter

     The complexity of the  transport  and  transformation  processes  wlvch
influence  the  fate of toxicants require additional analytical tools beyond
those required for conventional pollutants.   This  chapter  develops  these
analytical  tools  in a general way that is applicable to rivers, lakes, and
estuaries.  Individual chapters on the various surface  water  types  refine
these  tools further and provide a framework within which to use them.  When
used together, the various chapters in this document should  help  the  user
both  understand  and quantitatively represent the processes influencing the
aquatic fate of a pollutant.

     This chapter presents both a general overview of the screening approach
for toxicants and a detailed description of the processes  included  in  the
screening methodology.  The various topics are organized as follows:

     •   Screening Methods for Toxic Organic Substances
     •   Speciation Processes
         1)  Acid-base Effects
         2)  Sorption
     t   Transport Processes
         1)  Solubility Limits
         2)  Volatilization
     •   Transformation Processes
         1)  Biodegradation
         2)  Photolysis
         3)  Hydrolysis

     These methods apply primarily to the fate of toxic organic  substances.
Some  processes  act  on  metals  as well, but considerable expansion of the
material would be necessary to incorporate them in these screening  methods.
Generally,  the  complexity  of  the environmental chemistry of metals makes
them more difficult to handle with simple methods.   The  utility  of  these
                                    25

-------
methods  remain  high even without metals since the overwhelming majority of
toxic substances and over 100 of the 129 EPA Priority Pollutants are organic
compounds.  In lieu of procedures designed specifically for metals, the user
may apply the screening methods for conservative substances.  The advantages
and limitations of this approach are discussed in Section 2.2.2.2.
                                     26

-------
2.2  SCREENING METHODS FOR TOXIC ORGANIC COMPOUNDS

2.2.1  Modeling the Fate of Toxic Organics

     The goal of this screening methodology for toxic pollutants is to help
the user identify surface water bodies where toxicants could reach hazardous
levels.  Multiple approaches for identifying pollution problems are
possible, e.g. extensive field measurements, statistical correlations of
discharges and pollutants detected in rivers, computer simulation models,
etc.  The approach taken here is to present simple methods for assessing the
fate of toxicants.

     The application of any method necessitates the use of judgment on the
part of those applying it.  In almost every case, the user must estimate
many of the methods' input parameters on the basis of limited data.
Consequently, even the projections of detailed computer models such as RAMS
(Burns, et _al_., 1981) and PEST (Park,  et aj_., 1980) are only as good as the
accuracy of the assumptions made by their developers and users.  Thus, the
goal of the materials presented herein is twofold:  to present simple
methods and to provide the background necessary to make knowledgeable
judgments.

     Predicting aquatic fate of pollutants  involves several steps.  Tho
steps described in the remainder of this section  include:

     *   Determination of Fate-Influencing Processes
     t   Delineation of Environmental Compartments
     •   Representation of Hydrologic Flow
     •   Mathematical Representation of Speciation Processes
     •   Mathematical Representation of Transport and Transformation
         Processes
     •   Determination of Pollutant Load and Mode of Entry into the
         Aquatic Environment

     Prediction of the fate of toxic pollutants requires the user to know
which processes act on the toxicant.  Figure II-2 illustrates the transport
arid transformation processes which are of potential importance  in a lake or
                                     27

-------
po
oo
      INFLOW
                                                                                                           OUTFLOW
   volatilization


           V
                            HA:? H++A-
                            Acid-Base Equilibria
                                                                                   Precipitation-Dissolution
 H-0--

   H
Hydrolysis
                                       Biodegradation
                                                                      Bioconcentration
                                                   Reduction-Oxidation
              FIGURE  11-2   SPECIATION,  TRANSPORT  AND TRANSFORMATION PROCESSES IN  THE AQUATIC

                              ENVIRONMENT

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other surface water body.  The processes fall into four categories as
follows:

     •   Loading Processes
         The rates at which waste discharges, atmospheric deposition,
         and land runoff introduce toxicants into natural waters
         influence resulting pollutant levels.

     »   Speciation Processes
         Acid-Base Equilibria - The pH of a natural water determines
         the fraction of an organic acid or base in neutral or ionic
         states, and therefore influences volatility.

         Sorption - Hydrophobic organic compounds sorb to suspended
         matter;  their  subsequent fate is influenced by the fate of
         the suspended matter.

     t   Transport Processes
         Precipitation-Dij_sgJution - Solubility limits of both organic
         and inorganic pollutants can cause a pure pollutant phase to
         form restricting its availability to transport and
         transformation  processes or substantially changing the
         transport route.

         Advection - Hydraulic flows transport pollutants which are
         dissolved or sorbed on suspended sediments into and out of
         particular aquatic habitats.
         Volatilization - Organic pollutants may enter the atmosphere
         from a water body, thereby reducing aquatic concentrations.

         Sedimentation - Deposition of suspended sediments containing
         sorbed pollutants, as well as direct sorption onto or
         desorption from bottom sediments can alter pollutant
         concentrations.
                                     29

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     •   Transformation Processes
         Biodegradation - Microbial organisms metabolize pollutants,
         altering their toxicity in the process.

         Photolysis - The absorption of sunlight by pollutants causes
         chemical reactions which affect their toxicity.

         Hydrolysis - The reaction of a compound with water frequently
         produces smaller, simpler organic products.

         R e d u c t i o n - 0 x i d at ion - Reactions of organic pollutants and
         metals which involve the subtraction or addition of electrons
         strongly influence their environmental properties.  For
         orga.nics, nearly all significant redox reactions are
         microbially mediated.

     •   Bioaccumulation
         Bio coneen tration - Uptake of toxic pollutants into biota via
         passive means, e.g. absorption through fish  gills.

         B jomagji i f i c at "[on - Uptake of toxicants into  biota via
         consumption of contaminated food.

     Once the pertinent processes have been identified, the physical
compartments of the environment between which the transport processes act
must be delineated.  For most water bodies, compartments representing the
atmosphere, bottom sediments, and one or more water elements are sufficient.
These methods are capable of representing transport of pollutants between
the atmosphere and a water body.  But rather than calculating atmospheric
concentrations of a pollutant, these methods generally assume them to be
close to zero unless available data indicate otherwise.  Bottom sediments,
however, frequently accumulate high levels of organic pollutants.  Because
of the difficulty of modeling the behavior of toxicants in sediments,
usually assumptions which approximate only the removal or addition of a
pollutant to the water column are made.  These approximations are presented
in the individual chapters on each water body.
                                     30

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     The next step in assessing the aquatic fate of toxic pollutants is to
represent the advection or flow of water.   Figure 11-3 illustrates a
representation of rivers as a segregated flow system and lake layers as
completely mixed flow systems.  Although these models are simple,  they serve
as adequate first-approximations of real systems.  Refinements and
limitations of these flow system models are considered in the individual
chapters on rivers, lakes, and estuaries.

     The transport and transformation processes responsible for the removal
of a pollutant from the water column are considered next.  First-order rate
expressions adequately represent all of the processes considered here.  The
first-order decay of a pollutant by a process is represented as follows:

                Rate of Pollutant Removal  = k  • C                  (H-^
                                             i    T                 (     '
where
     k. = first-order rate constant for process i
     C  = total concentration of pollutant

The rate constant for a process is specific to both the chemical it acts
upon and the local environment in which it acts.

     When all the first-order processes act independently, the total rate of
pollutant removal is:

                  Total Rate of Removal = k  • C                    (H-4)

where
                        k  = k   +k+k+k+k                 (II-5)
                         T    vm    S    B    P    H                     ;

     k   = specific mixed-body volatilization rate constant
      vm

     k   = specific rate constant for removal to bottom sediment
      O
                                       31

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 COMPLETELY MIXED  FLOW
      NATURAL SYSTEM:
                                               LAKE
       IDEALIZATION:
  SEGREGATED FLOW
                                 L
                                  MIXED FLOW
       NATURAL SYSTEM:
       IDEALIZATIONS:
                                               RIVER
                                               Pi UG  Fi ow

                                               FLOW  WITH
                                               AXIAL DISPERSION
FIGURE 11-3  FLOW SYSTEM REPRESENTATIONS
                             32

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     k   = specific rate constant for biodegradation
      B


     k   = specific rate constant for photolysis
      P


     k   = specific rate constant for hydrolysis
      H


The additivity of processes which are first-order with respect to pollutant

concentration is particularly convenient for analysis.



     Many of the decay processes are influenced by the chemical state of the

toxicant.  For example, sorbed pollutants cannot volatilize.  Mathematical

representations of equilibria between two species of a chemical can be

reduced to the following type of equation.  This type of equation serves

well at the low solute concentrations encountered in waste waters and

natural waters:



                              C  = K   C                            (H-6)
                               i    ij  J


where
     C   = concentration of form i
      i


     K   = equilibrium constant
     C   = concentration of form j
      j


     It is also convenient to know the fraction of the total pollutant

concentration which is in a given state:
                                      C,
                                a  =
                                 i    C,
1                              (II-7)
where
     C  = concentration in state i
      i
                                     33

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     c  = c + c
      T        S

     C  = total dissolved phase pollutant concentration

     C  = total sorbed phase pollutant concentration
      o

     To complete the assessment of the aquatic fate of a pollutant the mode
of entry into the aquatic environment must be considered.  Many pollutants
enter in dissolved or sorbed form from a point source.  In this case, a
simple mixing computation is sufficient to determine the initial
concentration of a pollutant in the water body.  Other cases include spills,
non-point sources, and desorption from sediments.  Chapter 4 presents
methods for dealing with these cases.

     The user may now reckon the concentration of a pollutant in a given
water body.  The equations which yield the desired results are specific to
each surface water type and are developed in the individual chapters on
lakes, rivers, and estuaries.  An equation representative of those in each
chapter is presented in Table 11-10.  The individual chapters go into
greater detail about factors influencing rate processes and interactions
with other important phenomena in each water body (See Sections 4.9, 5.6,
6.4.3, and 6.4.5).
2.2.2  Use of Assessment Techni ques as Screening_Tqol_s

2.2.2.1  Making Conservative Assumptions

     With the computational methods presented in this document, the user
could produce a relatively complete analysis of the aquatic fate of a
pollutant.  The goal of this screening method, however, is to
determine—with a minimum of effort—whether toxicants are likely to reach
problem levels in surface water bodies for either existing or projected
loading rates.  The user can minimize the effort expended in screening a
pollutant by starting with a simple approach which incorporates conservative
assumptions about the fate of a pollutant.  Conservative assumptions are
designed to yield higher calculated environmental concentrations than
                                     34

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                               TABLE 11-10


                 EXPRESSIONS FOR TOXIC POLLUTANT LEVELS
                         IN VARIOUS WATER BODIES
Water Body
Expression for Steady-State
Pollutant Concentration

Rivers
(Chapter IV)
[-k1 -^r*K
. ..Y— . .^"^. »
1 + K S U
P J
(IV-115)
Impoundments
(Chapter V)
Estuaries
where  x = distance downstream
       U = river velocity
       C = total dissolved phase concentration

C = Cin/(l + Tw x k)     (V-47)

where T  = hydraulic residence time
       W
      C  = total dissolved and sediment phase
           concentration
                              f.
                      (VI-33)
                                           (VI-34)
where C.
      f.
      r.
      t  =
                              concentration in segment i
                              fraction of fresh water in  segment i
                              segment i exchange ratio
                              time expressed in tidal cycles
                                     35

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probably exists in the real system.   If these higher concentrations are
below the water quality criterion under consideration,  a violation of the
standard is unlikely.  If the initial  predictions are higher than the
standard, the user may successively refine the approach until  it becomes
apparent that either the standard will  be met or that a more detailed study
is necessary.

     Three levels of refinement in assessing the aquatic fate of a pollutant
are considered here.  In order of increasing complexity, they are:

     1)  Treating the pollutant as a conservative substance

     2)  Considering transport and speciation processes

     3)  Considering transformation, transport, and speciation
         processes.

Each approach has advantages and limitations which the user should consider.
By following this sequence of refinements, the user should be able to
eliminate cases where water quality problems are unlikely with a minimum of
time and effort.
2.2.2.2  Treating the Pollutant as a Conservative Substance

     The simplest approach to estimating the concentration of a toxic
pollutant is to assume it behaves conservatively (i.e.  does not undergo
reaction):

                                 k  = 0

Unless an internal source of the pollutant exists, this approach will yield
the highest possible pollutant levels since pollutant decay and removal
processes are neglected.  The obvious advantage of this approach is that it
requires no chemical or environmental data to evaluate rate and equilibrium
constants.  The only data needed are pollutant loads and hydrological
parameters.  Its major drawback is that it neglects the possibility of a
                                    36

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compound accumulating in another environmental  compartment,  especially
bedded sediments.  This could result in the underestimation  of the duration
of the exposure of an aquatic habitat to a chemical.  Although the duration
of exposure may be underestimated, water column concentrations would not
exceed the upper limits predicted by this approach at any time during the
exposure period.  The fate of conservative pollutants in rivers,
impoundments, and esturaries is discussed in Sections 4.1.9, 5.6.1, and
6.4.
2.2.2.3  Considering Transport and Speciat ion Processes

     This refinement incorporates those processes which influence pollutant
transport out of the aquatic environment but neglects those processes which
chemically alter the compound.  Transport processes strongly depend upon
chemical speciation, which therefore must be included.  The rate constant
for first-order pollutant attenuation in this approach is:

                         k  = k  + k                                (II-8)
                          T    S    vm
where
     k   = specific rate constant for removal to bottom sediment

     k   = specific mixed body volatilization rate constant.
      vm

This approach requires more information on the properties of the toxicant
and the environment than when the pollutant is assumed to behave
conservatively, but the necessary data are much more readily available than
that required to characterize transformation processes.  Nearly all the
chemical data necessary to characterize acid-base equilibria, sediment
sorption, solubility limitations, and volatilization for the organitza
priority pollutants are presented in tables in Sections 2.1.5, 2.3.1, and
2.4.2.  The necessary environmental data can usually be obtained or
estimated with a minimal amount of effort.  Because of the demonstrated
importance of transport processes and the relative simplicity of assessing
them, this is a good intermediate step between the simplest and most
complicated approaches.
                                   37

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     Transport and speciation processes are applied specifically to
 rivers,  impoundments, and estuaries in Sections 4.9, 5.6, 6.4.3, and 6.4.5.
2.2.2.4  Considering Transformation, Transport,  and Speciatipn Processes

     The most complex model which the user can employ using these screening
methods includes consideration of transformation,  transport, and speciation
processes.  With this approach, the rate constant  for first-order
attenuation of a pollutant is:

            k=k+k   +k+k+k                             (II-9)
             T    S    vm    B    P    H

where

     k  = specific rate constant for biodegradation
      B
     k  = specific rate constant for photolysis
      P
     k  = specific rate constant for hydrolysis
      H
     The  inclusion of the degradative processes (i.e. biodegradation,
photolysis, and hydrolysis), considerably increases the chemical and
environmental data required to model a compound's fate.  Rather than
accurately determining all the constants for speciation, transport, and
transformation, the user should first ascertain which processes are the most
significant for a compound.  As a first step the user should obtain data on
the properties of the chemical which influence its aquatic fate from this
document  or other sources.  From compound specific data, it is usually
possible  to eliminate some processes from consideration.  For organic
priority  pollutants, consulting the ratings of the relative importance of
aquatic processes for the fate of each compound, Table  11-11, may aid the
user in eliminating unimportant processes.  Once the most significant
processes have been identified, the user should collect the environmental
data necessary to determine site specific constants.  These site specific
constants are then applied  in  the appropriate equation  for  each water body
type to obtain the best estimate of the actual pollutant concentrations  in
                                    38

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                                     TABLE 11-11


                     RELATIVE IMPORTANCE OF PROCESSES INFLUENCING
     AQUATIC  FATE OF ORGANIC  PRIORITY POLLUTANTS  (After Callahan et al_., 1979)
              Compound
Process
PESTICIDES
Acrolein
Aldrin
Chlordane
ODD
DDE
DDT
Dieldrin
Endosulfan and Endosulfan Sulfate
Endrin and Endrin Aldehyde
Heptachlor
Heptachlor Epoxide
Hexachlorocyclohexane (a,3,6 isomers)
 -Hexachlorocyclohexane (Lindane)
Isophorone
TCDD
Toxaphene

PCBs and RELATED COMPOUNDS
Polychlorinated Biphenyls
2-Chloronaphthalene

HAL06ENATED ALIPHATIC HYDROCARBONS
Chloromethane (methyl" chloride)
Dichloromethane (methylene chloride)
Trichloromethane (chloroform)
Tetrachloromethane (carbon tetrachloride)
Chloroethane (ethyl chloride)
1,1-Dichloroethane (ethylidene chloride)
1,2-Dichloroethane (ethylene dichloride)
1,1,1-Trichloroethane (methyl chloroform)
1,1,2-Trichloroethane
1,1,2,2-Tetrachloroethane
                                   Key to Symbols:
++ Predominant fate determining process       - Not likely to be an important process
 + Could be an important fate process         ? Importance of process uncertain or not
                                                known
                                         39

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                               TABLE 11-11 (continued)
             Compound
Process
Hexachloroethane
Chloroethene (vinyl chloride)
1,1-Dichloroethene (vinylidene chloride)
1,2-j,rajns-Di chloroethene
Trichloroethene
Tetrachloroethene (perchloroethylene)
1,2-Dichloropropane
1,3-Dichloropropene
Hexachlorobutadiene
Hexach1orocyclopentad i ene
Bromomethane (methyl bromide)
Bromodichloromethane
Dibromochloromethane
Tribromomethane (bromoform)
Dichlorodifluoromethane
Trichlorofluoromethane

HALOGENATED ETHERS
Bis(choromethyl) ether
Bis(Z-chloroethyl) ether
Bis(2-chloroisopropyl) ether
2-Chloroethyl vinyl ether
4-Chlorophenyl phenyl ether
4-Bromophenyl phenyl ether
Bis(2-chloroethoxy) methane

MONOCYCLIC  AROMATICS
Benzene
Chlorobenzene
1,2-Dichlorobenzene (^-dichlorobenzene)
1,3-DiChlorobenzene (m-dichlorobenzene)
1,4-Dichlorobenzene (£-diChlorobenzene)
1,2,4-TriChlorobenzene
Hexachlorobenzene
7
+
-f
+
4-
+
+
+
                     +
                     +
                                   Key to Symbols:
++ Predominant fate determining process       - Not likely to be an  important process
 + Could be an important fate process         ? Importance of process uncertain or  nol
                                                known
                                         40

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                               TABLE 11-11 (continued)
             Compound
Process
Ethylbenzene                                    ?+?___
Nitrobenzene                                    +__+__
Toluene                                         ++?___
2,4-Dinitrotoluene                              +      -      -      +      -      ?
2,6-Dinitrotoluene                              +_-+??
Phenol                                          -      +      +      +      __
2-Chlorophenol                                  --?+__
2,4-Dichlorophenol                              -             ++
2,4,6-Trichlorophenol                           ?      -      ?      ?
Pentachlorophenol                               +      -      +      +      _      +
2-Nitrophenol                                   -                    ++b
4-Nitrophenol                                   +                    ++
2,4-Dinitrophenol                               +                    ++b
2,4-Dimethyl phenol  (2,4-xylenol)               -_?+__
jD-chloro-m-cresol                               -      -      ?      ++
4,6-Dinitro-o-cresol                            +      -             ++     ?      ?

PHTHALATE ESTERS
Dimethyl phthalate                              +_+__+
Diethyl phthalate                               +.+__+
Di-n-butyl phthalate                            +_+__+
Di-n-octyl phthalate                            +_+__+
Bis(2-ethylhexyl) phthalate                     +_+__+
Butyl benzyl phthalate                          +_+__+

POLYCYCLIC AROMATIC HYDROCARBONS
Acenaphthene0+-++__
Acenaphthylene0                                 +-++__
Fluorenec                                       +-++__
Naphthalene                                     +-++__
Anthracene                                      ++++__
Fluoranthene0                                   ++++__
Phenanthrene0                                   ++++__
Benzo(a)anthracene                              ++++__
Benzo(b)fluoranthene0                           +-++__
Benzo(k)fluoranthene                            +-++__
Chrysene                                        +-++__

                                   Key to Symbols:
++ Predominant fate determining process       - Not likely to be an important process
 + Could be an important fate process         ? Importance of process uncertain or not
                                                known
                                          41

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                               TABLE  11-11  (continued)
             Compound
Process
Pyrene
Benzo(ghi)perylenec
Benzo(a)pyrene
Dibenzo(a,h)anthracene
Indeno(l,2,3-cd)pyrene

NITROSAMINES AND MISC. COMPOUNDS
Dimethylnitrosamine
Diphenylnitrosamine
Di-n-propyl nitrosamine
Benzidine
3,3'-Dichlorobenzidine
1,2-Diphenylhydrazine (Hydrazobenzene)
Aery Ionitrile
                                   Key to Symbols:
++ Predominate fate determining process       - Not likely to be an important process
 + Could be an important fate process         ? Importance of process uncertain or not
                                                known


Notes

a Biodegradation is the only process known to transform polychlorinated biphenyls
  under environmental conditions, and only the lighter compounds are measurably
  biodegraded.  There is experimental evidence that the heavier polychlorinated
  biphenyls (five chlorine atoms or more per molecule) can be photolyzed by
  ultraviolet light, but there are no data to indicate that this process is operative
  in the environment.

  based on information for 4-nitrophenol

c Based on information for PAH's as a group.  Little or no information for these
  compounds exists.
                                           42

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the environment that these methods are capable of making.  (See Sections
4.9, 5.6, 6.4.3, and 6.4.5).

     Frequently, kinetic and equilibrium constants will depend on the values
of parameters which the user must estimate (e.g. pH).  In such cases,
assuming conservative values is the best policy.  However, calculations
using a range of values may identify processes for which a more careful
determination of the key environmental and chemical parameters is warranted.

     Example II-l is an overall example for this chapter.  It demonstrates
the initial steps a user would take in applying these methods to assess the
fate of a particular organic pollutant.  The example follows the three level
analysis described above and also draws upon some of the procedures for
specific environmental processes which are developed later in this chapter.
This example can serve as a guide to evaluating the importance of the
various fate influencing processes for a particular pollutant.
                                EXAMPLE II-l
               Pentachlorophenol  in the Aurum Mirth Watershed

     Pentachlorophenol enters the Aurum Mirth River from a continuous point
 source.  The river  is the sole tributary to Lake Castile.  After mixing at
 the point of entry, the concentration of pentachlorophenol in the river is
 20yg/l.  The travel time from the point of contamination with
 pentachlorophenol to Lake Castile is about 6 days.  The mean hydraulic
 residence time in Lake Castile is 10 days.

     Use the screening methods to determine which chemical and environmental
 parameters are of the greatest importance for predicting the fate of
 pentachlorophenol in the watershed's surface waters.
                                     43

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1)  TREATING PENTACHLOROPHENOL AS A CONSERVATIVE SUBSTANCE

     The first step in the screening method is to assess the fate of
pentachlorophenol treating it as a conservative substance.   Sections 4.1.9,
5.6.1, and 6.4 discuss the fate of conservative pollutants  in rivers,  lakes,
and estuaries.  In this case, we assume no further dilution of the
pentachlorophenol occurs in either the lake or the river.   Consequently,  the
conservative pollutant approach predicts a mean concentration in the river
and lake of 20 yg/1.

     Table 11-2 lists a proposed water quality standard for
pentachlorophenol.  The 24 hour mean concentration must be  less than
6.2 yg/1.  Since 20 yg/1, exceeds this standard, a second level assessment
is in order.

     Prior to applying the next two levels of analysis it is worthwhile to
check Table 11-11 for the relative importance of the different
transformation and transport processes.  Table 11-11 summarizes the
influence of the aquatic processes on pentachlorophenol as  follows:

     •   Sorption - Important process

     •   Volatilization - Not an important process

     •   Biodegradation - Important process

     t   Direct Photolysis - Important process

     •   Hydrolysis - Not an important process

     •   Bioaccumulation - Important process

It will be instructive to compare these statements to the results of the
screening methodology.
                                    44

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2)  CONSIDERING TRANSPORT AND SPECIATION PROCESSES

     To analyze transport and speciation processes, first examine each
process for its potential influence on the fate of pentachlorophenol.
Speciation Processes

     Acid-Base Effects (Section 2.3.1)

     The chemical and environmental parameter governing acid-base effects
are:

     Chemical Parameters:

     •   pK  or pK  - acid or base equilibrium constants
           a      b

     Environmental Parameters:

     •   pH - hydrogen ion concentrations

     The pK  of pentachlorophenol  is 4.74, as shown in Table 11-13.
           a
According to Table 11-12, at  least 90 percent of the pentachlorophenol will
be  in the anionic state  at pH's greater than 5.74.  As long as the pH in the
Aurum Mirth River and Lake Castile remain above 5.74, the properties of
pentachlorophenol as measured for  neutral waters will remain unaffected.
But, because pH's below  5.74  could significantly alter the behavior of the
compound, it is important to  determine actual surface water pH values.


Sorption (Section 2.3.2)

     The key environmental and chemical parameters which influence sorption
are:
                                     45

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     Chemical parameters:

     •   K     octanol-water coefficient
          ow

     •   S   - solubility in water
          w

     Environmental Properties:

     •   Suspended sediment concentration

     •   organic carbon content of the suspended sediment

     Table II-8 lists the solubility and octanol-water coefficient of
pentachlorophenol as:
                                S = 14 mg/1
                              K   = 105
                               ow

Assuming an organic carbon content of 2 percent for the suspended sediments,
calculate K  using Equations 11-18 and 11-16:
           P
                                        5
                   K  - (.02) (.63)  (10 ) - 1300
                    P
According to Table 11-14, greater than 10 percent of the pentachlorophenol
will be in the sorbed state at suspended sediment concentrations exceeding
100 mg/1.  The relatively strong sorption of pentachlorophenol  dictates that
the suspended sediment concentration in the Aurum Mirth River and the
sediment trapping efficiency of Lake Castile be investigated further.
Sorption of pentachlorophenol potentially affects both its speciation and
its transport rates.
                                     46

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Transport Processes

     Solubi1 ity Limitations (Section 2.4.1)

     The most important chemical and environmental  factors which influence
solubility of a compound are:

     Chemical Parameters:

     •   S  - Aqueous equilibrium solubility
          w

     Environmental Parameters:

     •   T - Temperature

     •   Salinity

     Table II-8 lists the solubility limit for pentachlorophenol as 14 mg/1
(14000 ug/1).  At no point in the Aurum Mirth watershed should the
solubility of pentachlorophenol restrict the ability of the aqueous phase to
transport it.


     Volatilization (Section 2.4.2)

     The most significant chemical and environmental properties which
influence volatilization are:

     Chemical Parameters:
     •   K  - Henry's Law Contant
          H
     Environmental Parameters:
         k  - reaeration constant
          a
                                    47

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     •   V  - wind speed

     t   Z  - mixed depth of water body

     It is possible to estimate the Henry's law constant for
pentachlorophenol from its vapor pressure and aqueous solubility using
Equation 11-32.  However, it is simpler to rule out volatilization as a
significant transport process on the basis of the volatilization half-life
of 100 days given in Table II-8.  Because laboratory volatilization
half-lives are shorter than the true environmental values, it is safe to
assume the environmental half-life will be much greater than 100 days.
Given a total system mean hydraulic residence time of only 16 days (6+10),
volatilization can be safely neglected.
Summary.  Acid-base equilibria and sorption significantly influence the
transport and speciation of pentachlorophenol in the aquatic environment.
Acid-base effects do not influence the near-neutral volatilization and
photolysis rate constants presented in this document as long as pH's remain
above 5.7.  Sorption is a potentially important speciation process.
Consequently, the pH values and suspended sediment concentrations should be
determined in order to accurately evaluate these processes.

     The strong tendency of pentachlorophenol to sorb on sediments may
result  in sedimentation serving as a significant removal process in Lake
Castile.  The absence of net sediment deposition in the river implies that
transport processes do not reduce pentachlorophenol concentrations in the
Aurum Mirth.  Thus, the second level analysis predicts a total concentration
of 20 yg/1 of pentachlorophenol in the Aurum Mirth River with lower levels
possible in the lake.  Because the predicted river concentrations exceed the
standard, the third level model is necessary.
                                      48

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3)  CONSIDERING TRANSFORMATION, TRANSPORT,  AND SPECIATION PROCESSES

     To consider transformation, transport, and speciation processes,  the
transformation processes which were neglected in the level two analysis  must
be examined for their potential importance  in influencing the rate of
pentachlorophenol degradation.
Transformation Processes

     Biodegradation (Section 2.5.1)

     The key chemical and environmental variables which influence
biodegradation are:

     Chemical Parameters:

     •   Metabolic Pathway (growth or co-metabolism)

     •   k  - Biodegradation rate constant
          B

     Environmental Parameters:

     e   Bacterial population size

     t   State of adaptation

     •   Inorganic nutrient concentrations - Phosphorus

     •   Dissolved oxygen

     t   Temperature

     •   Pollutant concentration
                                   49

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     According to Table 11-23,  pentachlorophenol  is  potentially
biodegradable, although adaptation may be slow.   The reported  specific rate
constant values, 0.1 to 1.0 per day,  in Table 11-24  are in  the same range as
the 0.05 to 0.5 per day values  suggested in Table 11-23.  Although both rate
constants were determined under laboratory rather than  environmental
conditions, they do indicate that pentachlorophenol  can degrade very
rapidly.

     Table 11-24 also indicates that pentachlorophenol  is used by bacteria
as a growth substrate.  Thus, the time required  for  adaptation is of primary
concern.  The most important environmental factors for  determining whether
microorganisms in the Aurum Mirth watershed will  adapt  to degrade
pentachlorophenol are previous  exposure, time, and the  actual  concentrations
of pentachlorophenol in the surface waters (too  low--no enzyme induction;
too high—may have toxic effect on microbiota).
     Photolysis (Section 2.5.2)

     The key chemical and environmental characteristics influencing the rate
of photolysis are:

     Chemical Properties

     •   k      Near-surface rate constant
          do
or   •   eU) - Light absorption coefficient of pollutant, and

     •         Quantum yield


     Environmental Properties;

     •   I  - Solar radiant flux
                                     50

-------
     t   Z - Mixed depth of water body



     •   K - Diffuse light attenuation coefficient



         a)  Z    - Secchi disc depth
              sd


         b)  C    - Suspended sediment concentration
              ss


             C    - Dissolved organic carbon concentration
              DOC


             C    - Chlorophyll pigment concentration
              a


     According to Table 11-29, the near-surface photolysis rate constant for

pentachlorophenol is .46/day.  The size of the rate constant implies that

photolysis would be an important factor if the water bodies are not too deep

or too turbid.  Thus, it is important to gather information on the water

depths, and to estimate the light attenuation coefficients, and the solar

radiant flux in the Aurum Mirth watershed.
     Hydrolysis (Section 2.5.3)



     The important parameters influencing the rate of hydrolysis are:





     Chemical Parameters:
     •   k , k ,  k  - Acid, neutral, and base catalyzed hydrolysis rate
          a   n   b
         constants
     Environmental  Properties:



     t   pH - concentration of  hydrogen ion in the water bodies.
                                     51

-------
     Table 11-31 gives acid and base hydrolysis rate constants  for
                             4                   -1    -1
pentachlorophenol of 1.1 x 10  and 3.3 liter mole   day  .   The neutral  rate
constant is 5.8 x 10   per day.  The same table lists a half life of
100 days at pH = 7.  Because the acid catalyzed rate constant is large,
significantly higher rates could occur at lower pH's.  Using Equation 11-85,
the rate constant for pH = 5 is:

    k  = 1.1 x 104 (10~5) + 5.8 x 10"3 + 3.3 (10~9)
     H
       = .23 day"1
At this lower pH, degradation by abiotic hydrolysis would be very rapid.
Thus, determining the pH in the Aurum Mirth River and Lake  Castile is
very important.
Summary

     The consideration given to transformation, transport, and speciation
processes indicates the following processes are of potential importance to
the fate of pentachlorophenol in the Aurum Mirth watershed:

     •   Acid-Base Effects

     t   Sorption

     •   Biodegradation

     •   Photolysis

     •   Hydrolysis

Since the three transformation processes are potentially  important, there is
a good possibility that the  initial pentachlorophenol concentration of
20 yg/1 will be reduced below the 6.2 yg/1 standard.  Therefore further
analysis as presented  in the specific water body sections  is warranted.
                                     52

-------
     The results of this example agree with the summary of rate processes
given in Table 11-11 except for the case of hydrolysis.  This demonstrates
that the process summary table can serve as a useful  guide but should be
supplemented with actual data whenever possible.
                            END OF EXAMPLE II-l
                                   53

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2.3  SPECIATION PROCESSES

2.3.1  Acid-Base Effects

     The fate of toxic organics  which  are  either acids or bases can be
strongly affected by the concentration of  hydrogen  ions  in a water body.  It
is therefore necessary to have a means for estimating this influence.  This
section will first present a brief review  of  acid-base equilibria and then
will give a technique for quantifying  the  influence of hydrogen ion
concentration on the behavior of toxicants.
2.3.1.1  Acid-Base Equilibria
                                                +
     Acids by definition donate hydrogen ions,  H ,  to  solution.   Bases,  by
definition, accept hydrogen ions from solution.   2-Nitrophenol,  one  of the
129 priority pollutants, is an acid and donates hydrogen  ions  as shown by
the following reaction:
            OH
      2-nitrophenol          2-nitrophenolate          +   hydrogen ion

          (HP)                    (P-)                      (H+)

      Acid-base  reactions  are extremely fast and can be represented by
 equilibrium  expressions.  For the above reaction the expression would be:
                               [HP]
 where
                                     54

-------
     [H ] = concentration of hydrogen ions,  moles/liter

     [P ] = concentration of nitrophenolate ions,  moles/liter

     [HP] = concentration of undissociated nitrophenol, moles/liter

     K    = an equilibrium constant for acid dissociation (also called
      a
            an acidity constant)

     The extent to which any acid will donate hydrogen ions to the solution
depends on how many hydrogen ions are in solution (the concentration of
hydrogen ions) and on the strength of the acid.

     The concentration of free hydrogen ions in natural waters can range
             -4      -10
from about 10   to 10    moles per liter.  Hydrogen ion concentrations are
normally expressed in pH units.  In dilute solutions, such as natural
waters, pH is defined as the negative logarithm of the molar hydrogen ion
concentration (pH = -log   [H ]).  For the above two concentrations the pH
values are 4 and 10.
     The strength of an acid is quantified by the equilibrium constant, K .
For very strong acids (those which most readily donate hydrogen ions) the
value of this constant is greater than unity.  Included in this group are
strong acids such as hydrochloric and nitric acid.  Toxic organic acids,
though, are generally weak acids and have K  values between 10   and 10  .
                                           a
K  values are typically expressed in terms of negative base ten logarithms.
When this approach is used the equilibrium constants are called "pK "
(pK  = -log   K ).
   a       10  a

     When the pH of a solution is the same as the pK  value of an acid
(i.e. pH = pK ), 50 percent of the acid will have donated its hydrogen ions
             9
to the solution and will exist as a charged anionic species.  For pH values
greater than the pK  value by one or more units, the acid will have donated
                   3
essentially all of its hydrogen ions to the solution and will exist in the
anionic form (e.g. P ).
                                    55

-------
     The extent to which any base will extract hydrogen ions from solution

depends upon the concentration of hydrogen ions in solution (pH) and on the

strength of the base.  The strength of a base is quantified by an

equilibrium constant, K .   For very strong bases (those that most readily
                       b
extract hydrogen ions from solution) the value of K  is of the order of 1.

Toxic organic bases are generally weak and have K  values between 10   and
  -10                                            b
10   .  In a manner similar to acids, K  is typically expressed in terms of

negative base ten logarithms and is called "pK " (pK  = -log   K ).
                                              b     b       10  b


     Water itself can behave as a weak acid or a weak base:
                     H20 * H+ + OH~   (acidic  behavior)


                     H20 + H+ * H30+   (basic  behavior)
Note that [H ]-[OH~] = K
                        w
where
      [OH  ] = the concentration of hydroxide ion, moles/1
               -14       o
     K     =10   , at 20 C
      w


     pK    =14, at 20°C
       w


     When the pH of a solution equals the pK  of a base, 50 percent of the
                                            b
base has  accepted hydrogen ions and will exist as a charged cationic species.

For pH values greater than one unit above the value of  (pK -pK  ),
                                                          w   b
essentially all of the base will exist  in electrically  neutral form

(e.g. NH  ).  For pH values less than the value of (pK -pK, ) by  1 or more  units

the base  will essentially exist in the  electrically charged cationic form

(e.g. NH*).



     Table 11-12 summarizes the behavior described above for acids and

bases.  Values for pK  and pK  for selected toxic organic acids and bases
                     a       b
and values of pK  are given in Table 11-13.
                w
                                     56

-------
en
                                                        TABLE 11-12




                                   OCCURRENCE OF ACIDS AND BASES IN NEUTRAL AND CHARGED

                                         FORMS AS A FUNCTION OF pH, pK  , AND pK,
                                                                      a        o
Acids
Definition: Hydrogen
Example
HN03
General
HP -

^
pK +2
pK +1
P
pKfl-l
PKa-2
PKa-3
— +~ H + + NO"
Reaction:
•*- H+ + P"
Speciation :
Fraction in
Neutral Form
0.001
0.01
0.09
0.5
0.91
0.99
0.999
ion donors



Fraction in
Ionic Form
0.999
0.99
0.91
0.5
0.09
0.01
0.001
Bases
Definition: Hydrogen ion
Example:
3 4
General Reaction:
B + H+ — »- BH+
Speciation:
Fraction in
pH Neutral Form
pK -pK +3 0.999
pK -pK. +2 0.99
pK _pK +1 0.91
pK -pK 0.5
pK _pK _1 0.09
pKw-pKb-2 0.01
pKw"pl
-------
                               TABLE 11-13
             pK  AND  pK. VALUES FOR SELECTED TOXIC ORGANIC
              a        b

             ACIDS AND BASES AND VALUES OF pK  FOR WATER
                                             w
Acids

Phenol
2-Chlorophenol
2,4-Dichlorophenol
2,4,6-Trichlorophenol
Pentachlorophenol
2-Nitrophenol
4-Nitrophenol
2,4-Dinitrophenol
2,4-Dimethylphenol
4,6-Dinitro-o-cresol
Bases
Benzidine

10.0
8.52
7.85
5.99
4.74
7.21
7.15
4.09
10.6
4.35
pKb b
9.34, 10.43
        Water
Freshwater
   pK
                                                               w
14.63 at 5UC
14.53 at 10°C
14.35 at 15°C
14.17 at 20°C
14.00 at 25°C
13.82 at 30°C
Seawater
14.03 at 5un
13.81 at 10°C
13.60 at 15°C
13.40 at
13.20 at
                                                                   20°C
                                                                   25°C
                                                          13.00 at 30°C
Notes:
  a
    All pK  values from Callahan et al (1979)
          a
    All pKb values from Weast and Astle (1980)
  c  pK   values from Stumm and Morgan (1981) and from Dickson and Riley (1979)
      W
                                    58

-------
     Since toxic organics almost always exist in very low concentrations and
are at best only weak acids or weak bases, they will have little influence,
if any, on the pH values of the water.  The hydrogen ion concentration of
the water will, however, determine whether acids or bases exist in neutral
or ionic forms.

     Values of pH for natural waters can be obtained from the USGS, the
U.S. EPA, and state and local agencies.  Waters with low alkalinities
(e.g. < 50 mg/1 as CaCO , or 1 milliequivalent/liter) are quite susceptible
      ~                3
to changes in pH due to natural processes such as photosynthesis and
respiration and even to relatively small additions of strong acid or base.
Selection of representative pH values for such waters will require more data
than for systems with higher alkalinities where less change  in pH can be
anticipated.
2.3.1.2  Quantifying the Influence of pH on Toxicant Volatilization

     Only electrically neutral species are directly volatile.
Volatilization rate expressions must therefore use as the concentration of
toxicant only that fraction which is electrically neutral (non-ionic).  The
fraction of an acid or base which is in the non-ionic form can be determined
by use of the expressions given below:

     For organic acids:

                         a   = A°- = 	-L_	                    (11-11)

     For organic bases:

                       aBo  = "B~ = 	'r~"—-"—rrrr                 01-12)

where
                                    59

-------
     a   = the decimal  fraction of the organic acid which is in the
      Ao
           electrically neutral (non-ionic)  form
     a   = the decimal  fraction of the organic base which is in the
      Bo
           electrically neutral (non-ionic) form
     A   = the total dissolved concentrations of the toxic organic acid

           (e.g. HP+P ), also called the analytical concentration of A



     B   = the total dissolved concentration of the toxic organic base

           (e.g. BH  + B), also called the analytical concentration of

           B
The rate expressions then become in general form:
     and
                              R   =  k  a   A                         (II-13a)
                                      v  A
                                          o
                              R   =  k  a    B                        (II-13b)
                                      v  B
                                          o
where



     R  = rate of volatilization
     k  = specific rate constants for volatilization
                                      60

-------
                                EXAMPLE 11-2
     2-nitrophenol has been detected in the Alehandra Estuary,  which has a
pH of 8, at concentrations of 20 yg/1  (total dissolved form).   Determine the
volatilization flux on a per unit area basis.  Assume the volatilization
rate constant, k , is 2 cm/hr.
                v

     From Table 11-13, the pK  of 2-nitrophenol is 7.21.  The fraction
present in the electrically neutral (non-ionic) form is:
                            a.   =        l
                                  l  + 10(PH-PKa)

                                = 1  + lo'8-0-7-2
                                = 0.14

From Equation 11-13 the volatilization flux is:
         R  = 2 cm/hr (0.14)  (^^)  (1220J.)  (T?^)  =  56 yg  hr'V2
          v                      '       m*
                            END OF EXAMPLE 11-2
                                   61

-------
2.3.2  Sorption  on  Suspended Sediments
2.3.2.1  Introduction

     Sorption refers to the accumulation of a chemical in the boundary
region of a solid-liquid interface.  Sorption occurs when the net
sorbate-sorbent attraction overcomes the solute-solvent attraction, where
solute and sorbate refer to the sorbing species in solution and sorbed at
the interface, respectively.

     Sorption of chemicals  in the natural environment is significant because
the fates of sorbates and solutes can be significantly different.  Sorbates
are transported along with  sediments, and can be deposited in river or lake
beds to remain indefinitely.  Sorbates are in many ways protected from
transformation processes which would otherwise affect the solute.  For
example:

     •   Microbial degradation rates can be reduced.  Steen e_t aj_. (1978)
         performed tests which showed that sorption of toxicants to
         suspended sediments renders some compounds unavailable for
         biodegradation in  the adsorbed state.

     •   Volatilization is  diminished.  Since volatilization of a
         chemical occurs from the dissolved phase, the sorbate is not
         directly available for volatilization.  Rather, the sorbate
         first desorbs before it volatilizes.  Example II-4 will show
         the  significant influence of sorption on volatilization.

     •   Direct photolysis  of pollutants adsorbed on  suspended particles
         is inhibited in some cases.  Further, suspended solids deposited
         on the bed of a river, lake, or estuary, receive very little
         radiation for photolytic reactions.

     The net  interaction between the surface of a solid  and  sorbate can
result  from a variety of forces, including coulombic  attraction,
Van  der Waals forces, orientation  energy,  induction forces,  hydrogen
                                      62

-------
bonding, and chemical forces (Reinbold €|t aK,  1979).  In the case of many
organic compounds, the solute-solvent interaction is often weak so that even
a weak sorbate-sorbent attraction can result in sorption.  This type of
sorption is referred to as hydrophobia sorption because of the importance of
the weak solute-solvent attraction.  Hydrophobic sorption will be the topic
of much of the following discussion, but it is preceded by brief discussions
of equilibrium isotherms and sorption kinetics.
2.3.2.2  Adsorption Isotherms

     Adsorption isotherms describe the relationship between the amount of
chemical sorbed and the equilibrium solution concentration.  The most
commonly used isotherms are:

     •   Langmuir Adsorption Isotherm.  This equation was originally
         developed to describe adsorption of a gas to a solid surface,
         but has been used to describe solid-liquid sorption.

     •   Freundlich Adsorption Isotherm.  This empirical equation is
         based on surface-free energy and monolayer capacity.

     •   Linear Adsorption Isotherm.  This equation assumes that there
         is a linear relationship between the concentrations of solute
         and sorbate at equilibrium.  It is valid for dilute solutions.

Figure  II-4 shows example comparisons between the three isotherms, and
includes the equations which describe each isotherm.  The quantity X  is the
amount  of  sorbed chemical per mass of sediment, and C,,  is the amount  of
                                                     w
dissolved  chemical per volume of solution.  The remaining variables are
unknown parameters required to define the relationship  between X and  Cw.
The  linear  isotherm has one unknown parameter (K  ), while both the
                                                p
Freundlich  and Langmuir isotherms have two unknown parameters (k ,n and m,b,
respectively).
                                    63

-------
       5000
       4500
       4000
    g  3500

    E

    ^5
    0>


    S»  3000
ra



1  2500


u




I  2000


•a
re
    -=•  1500

    X
       1000 -
       500 -,
                      Linear Isotherm

                        X = kp-Cw
                                                         Freundlich Isotherm


                                                           X = kf-Cw1/n
                0.5    1.0    1.5    2.0    2.5    3.0    3.5    4.0    4.5    5.0


                            Cw (ug dissolved chemical/I! solution)
FIGURE  11-4    ISOTHERMS  FOR ADSORPTION OF A  HYDROPHOBIC  POLLUTANT

                 ON SEDIMENTS
                                       64

-------
     For the purposes of this document, analyses will mostly deal with
dilute aqueous solution in the range where the linear isotherm is generally
valid.  This approach has the advantage of requiring that one unknown
parameter (K ) be evaluated,  rather than two, and of being easier to
            p
manipulate mathematically.  Sectior
predicting the unknown parameter K
            p
manipulate mathematically.  Section 2.3.2.4 will present methods of
2.3.2.3  Kinetics of Adsorption

     Sorption of organic pollutants is often treated as a process which
achieves rapid equilibrium so that expressions of kinetics are not needed.
The equilibrium approach will be used in the remaining chapters of this
document.  However, a brief introduction will be given of sorption kinetics.

     Studies of sorption kinetics are apparently few, with the result that
parameters required in rate expressions are  ill defined and applicable only
under a specific set of conditions.  Under these constraints, kinetics
expressions become less attractive unless the user can determine values of
the rate constants which apply to the specific system being investigated.

     Most typically, kinetics expressions for sorption and desorption are
chosen to be first order.  Specifically,
                           3C
                             W = -k ,(C  —)                       (11-14)
                            3t     sd  w   K
                                           P
expresses the kinetic expression for the solute and

                           9X
                              = -k   (X - K C  )                       (H-15)
                           3t     sd      p w
for the sorbate.  The concentrations X and C  are not necessarily
                                            w
equilibrium concentrations.   In these two equations, the rate parameter k
is assumed to be the same whether adsorption or desorption is occurring.
However, different rates could be used for each process.
                                     65

-------
     Karickhoff (1979) investigated the sorption and desorption of organic
pollutants and found that a very rapid component of adsorption preceded a
much slower component of adsorption, and that first order kinetics were
obeyed during each of the two periods.  For the fast process, the time
constant was found to range from 4 to 30 per hour, while for the slow
process the time constant ranged from 0.06 to 1.5 per hour.  Approximately
half of the sorptive equilibrium was realized within minutes, while the
slower component required days or weeks to complete.  The slower second
period was visualized as diffusive transfer to sorption sites that were
inaccessible directly to the bulk water.  Thus, equilibrium conditions are
more likely to be rapidly attained when the number of easily accessible
surface sites exceeds the amount of available sorbate, e.g. when suspended
sediment concentrations are high.

2.3.2.4  Partition Coefficients for Organic Chemicals Obeying Linear
         Isotherms

     The single unknown parameter, K  , which relates the sorbate and solute
                                    p
for linear isotherms  is called the partition coefficient.  A number of
studies have been completed which develop empirical relationships for
partition coefficients in natural sediments.  Several of these studies will
be summarized here.   Theoretically based methods of estimating partition
coefficients exist, such as a thermodynamic approach described in
Pavlou (1979);  however, these will not be discussed here.

     Karickhoff jat al. (1979) examined the sorption of aromatic hydrocarbons
and chlorinated hydrocarbons on natural sediments.  They found it convenient
to relate the partition coefficient directly to organic carbon content of
the sediments as follows:

                               K  = K  x                              (11-16)
                                p     oc oc
 where
      K    =  partition  coefficient  expressed  on  an  organic  carbon  basis
      oc
                                     66

-------
     x   = mass fraction of organic carbon in sediment.
      oc


These workers were able to expand this relationship to segregate the

influence of particle size as follows:



                      K  = K  [0.2(l-f)xs  + fxf ]                   (H-17)
                       p    oc          oc     oc


where
     f    = mass fraction of fine sediments (d < 50 ym)



     xs  = organic carbon content of coarse sediment fraction
      oc


     x"f  = organic carbon content of fine sediment fraction.
      oc


     Karickhoff et al. (1979) were able to relate K   to the octanol-water
                                                   oc
partition coefficient and to the water solubility by the following

relationships:
                              K   = 0.63 K                           (11-18)
                               oc         ow


where
     K   = octanol-water partition coefficient  (concentration of
      ow
           chemical  in octanol divided by concentration of chemical  in

           water, at equilibrium)



and
                        K   = -0.54  log S  + 0.44                     (11-19)
                         oc              w


where
     S   = water  solubility of  sorbate,  expressed  as  a mole fraction.
      w
                                    67

-------
The water solubilities of the compounds examined ranged from 1 ppb to
1000 ppm.

     Hassett et al.  (1980) found a similar relationship between K   and K
                                                                  oc      ow
for organic energy-related pollutants.  Figure II-5 shows the relationship.
Data from Karickhoff et al.  are included in the plot for comparison.

     Prior to the work of Karickhoff jet _aK, Chiou et jil_.  (1977)
investigated the relationship between octanol-water partitioning and aqueous
solubilities for a wide variety of chemicals including aliphatic and
aromatic hydrocarbons, aromatic acids, organochlorine and organophosphate
pesticides, and polychlorinated biphenyls.  Their results, shown in
Figure II-6, cover more than eight orders of magnitude in solubility
and six orders of magnitude  in the octanol-water partition coefficient.  The
regression equation based on this figure  is:

                                                                     (11-20)
                             log K   = 5.00 - 0.670 log Sw
                                 ow                      w
where
     S  =  solubility,  in ymol/1
      w
     Brown and  Flagg  (1981) have extended the work of Karickhoff _et  aj_.   by
 developing an empirical relationship  between K    and K    for  nine
                                              ow      oc
 chloro-s-triazine  and  dinitroaniline  compounds.   They plotted their  results,
 along with those of Karickhoff ^t  a]^,  as shown  in Figure  II-7.  The  combined
 data set produces  the  following correlation:

                      log K    = 0.937  log K   -  0.006                  (H-21)
                          oc              ow
 The  linear correlation between K    and K    for  the compounds  studied by
                                 ?c     ow
                                 or of uncertainty than  those studied by
 Karickhoff e£ aj_.

     The  previous  paragraphs  have  shown how the partition coefficient K  can
 be predicted for organic  hydrophobic  compounds  which  obey a linear isotherm
 relationship.   First,  K   is  predicted based on either  water  solubility or
                        oc
                                     68

-------
en
o
7



6



5



4



3



2



 I



0
                                        o
                                                                          7
       FIGURE 11-5  RELATIONSHIP BETWEEN KQC AND OCTANOL-WATER PARTITION

                    COEFFICIENT (1C..) OF ENERGY-RELATED ORGANIC  POLLUTANTS
                                  uw

       REFERENCE:   HASSETT EI AL,  (1980)

-------
10
 10
      10
           10
 I     IO   10    10    10
Solubility in Woter (/xmoles/l)
                                       10
                                            10'
FIGURE 11-6  CORRELATION  OF AQUEOUS  SOLUBILITY
              WITH OCTANOL-WATER PARTITION
              COEFFICIENT

REFERENCE:  CHIOU EJ_ AL,   (1977)
                        70

-------
                                            BROWN AND  FLAGG  (1981)
                                            KARICKHOFF ET AL,  (1979)
                                       _L
0  050 100  150 200  250 300  350 400 450  500 550  600 650

                    LOG Kow
 Note:  The actual  error bands for this figure  are probably
       greater than  indicated here  due to error in the
       measurement of K
                      ow
FIGURE 11-7   RELATIONSHIP BETWEEN Knr  AND 1C..  FOR
                                       UL       (JW
               COARSE  SILT
                               71

-------
the octanol-water partition coefficient.   Tables II-5 through II-9 shown

earlier contain K   values for a number of compounds.  Then based on an
                 ow
estimate of organic carbon fraction in the fine and coarse sediments,  K  can
                                                                       p
be estimated from Equation 11-17.
2.3.2.5  Solute and Sorbate Fractions



     The relative amount of pollutant sorbed and dissolved depends on both

the suspended sediment concentration and the partition coefficient, and at

equilibrium is given by:
                                Cw      1
                           °w ~ T.'  = TTiTs"              .             (n-22)
where                                   P
     C  = total dissolved phase concentration
      w


     C  = C  + C
      T    w    S



     CS = XS



     K  = partition coefficient
      P


     S  = suspended sediment concentration, on a part per part basis



     X  = mass of sorbed pollutant per mass of suspended sediment.



Equation 11-22 can be illustrated more vividly by tabulating ranges of K
                                                                        p
and  S values.  Table 11-14 shows this information.  Partition coefficients
                                                   o      4
and suspended sediment concentrations range from 10  to 10 .  For the lowest

value of the partition coefficient nearly all of the pollutant is present in

the dissolved form, regardless of the suspended sediment concentration.

Also, for low suspended sediment concentrations, nearly all of the pollutant

is dissolved, unless the partition coefficient is exiremely large.  When

relatively high partition coefficients and sediment concentrations occur

simultaneously, then most of the pollutant present exists as sorbate.  For
                                    72

-------
                    TABLE 11-14

RELATIONSHIP OF DISSOLVED AND SORBED PHASE POLLUTANT
    CONCENTRATIONS TO  PARTITION COEFFICIENT AND
               SEDIMENT CONCENTRATION
K
P
10°




101




102




103




104





S (ppm)
1
10
100
1000
10000
1
10
100
1000
10000
1
10
100
1000
10000
1
10
100
1000
10000
1

10
100
1000
10000
Cw/CT .
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
1.0
0.9
1.0
1.0
1.0
0.9
0.5
1.0
1.0
0.9
0.5
0.1
1.0

0.9
0.5
0.1
0.0

V
100.
100.
100.
100.
99.
100.
100.
99.9
99.0
90.9
100.
99.9
99.0
90.9
50.
99.9
99.0
90.9
50.
9.1
99.0

90.9
50.
9.1
1.0
If CT = 100 ppb
X =
100.
100.
100.
100.
99.
IxlO3
IxlO3
999.
990.
909.
IxlO4
IxlO4
9.9xl03
9. IxlO3
5xl03
IxlO5
9.9xl04
9. IxlO4
5xl04
9xl03
9.9xl05
5
9.1x10
5xl05
9. IxlO4
9.9xl03

CS =
0.0
0.0
0.0
0.0
1.0
0.0
0.0
0.1
1.0
9.1
0.0
0.1
1.0
9.1
50.
0.1
1.0
9.1
50.
90.9
1.0

9.1
50.
90.9
99.0
                         73

-------
all the cases shown,  X is  high which  indicates that the mass sorbed per unit
mass of sediment present can  be  high  while C  is simultaneously low.
                                EXAMPLE 11-3
     Determine the fraction of benzo(a)pyrene that is dissolved in a system
containing 300 ppm suspended solids.  The suspended sediments are 70 percent
fines (d <50 ym) and the weight fraction of organic carbon is 10 percent of
the fines and 5 percent of the sand fraction.

     From Table II-9, the solubility of benzo(a)pyrene is 0.0038 mg/1, and
                                             6
the octanol-water partition coefficient is 10 .   If, for the moment, the
octanol-water partition coefficient is ignored,  Equation 11-20 can be used
to predict K   based on solubility.  The solubility of 0.0038 mg/1 must be
            ow
converted toy mole/1:
             - (0.0038 mg/1) (ICT  g/.g)  ()  (106

                = 0.015 ymole/1
From Equation 11-20, the predicted octanol-water partition coefficient is:

                log K   = 5.00 - 0.670 log (.015) = 6.22
                     ow
           6.22                                                        6
so K   =10    , which is acceptably close to the tabulated value of 10 .
    ow

     Using the tabulated K , , K   is computed from Equation 11-18:
                          ow   oc
                                      6
                         K   = 0.63 10  = 630,000
                          oc

From Equation 11-17, the partition coefficient becomes:

               K  = 630,000 [0.2 (1-.7) (.05) + 0.7 (.10)]
                P =  46,000
                                    74

-------
     The  suspended  sediment  concentration for the  system  is 300 ppm, or
       -6
 300-10   parts  per  part.   Using  Equation 11-22,  the fraction of

 benzo(a)pyrene  which  is  dissolved  is:



           C.
            w
           CT   1 + 300 • 10"6-46,000
                                      = 0.067 or about  7  percent
 Consequently,  most  of  the  benzo(a)pyrene  is  present  as  sorbate.




	END  OF  EXAMPLE  11-3	
                                   75

-------
2.4  TRANSPORT PROCESSES

2.4.1  Solubility Limits

     The concentration of a compound in a natural  water,  and therefore the
rate of transport by that water, can be limited by its equilibrium
solubility.  The aqueous solubility of organic compounds  ranges widely:

                                                         o
                                 Aqueous Solubility at 25 C
        Compound       (mass which will dissolve in 1 liter of water)

        Sucrose                   2,000,000 milligrams
        Benzene                       2,000 milligrams
        Toxaphene                         2 milligrams
        Chrysene                          0.002 milligrams

     Non-polar compounds have limited solubilities in polar solvents such as
water.  The solubility of toxic organic compounds is generally much lower
than for inorganic salts.  Equilibrium solubilities for toxic organic
compounds  are given in Tables II-5 through II-9.  Solubility increases with
temperature for most organic compounds, typically by a factor of about 3
from 0 C to 30 C.

     Organics are generally less soluble in sea water than in fresh water as
can be seen in the tabulations  below (Rossi and Thomas, 1981):

                          Solubility at 25 C
        Compound      Distilled Hater     Sea Water
Toluene
Acenapthene
Pyrene
507 yg/1
2.41 yg/1
0.13 yg/1
419 yg/1
1.84 yg/1
0.09 yg/1
      In  the  absence of colloids or micelles, the maximum amount of a toxic
organic  substance which can be held  in the water column under equilibrium
conditions is just the aqueous equilibrium solubility S , plus the
equilibrium  amount of solute sorbed  on suspended matter:
                                    76

-------
                     C   = 5  + f  (S )                                  (11-23)
                      T     w    s   w

where C      = total amount of compound  which can be held in a
               natural water at equilibrium conditions, jjg liter

                                                       -1
      S      = equilibrium aqueous solubility, yg liter
       w
      f (S ) = equilibrium amount of sorbate on suspended matter; a
       S  W
              function of S .  f  is the sorption isotherm function.
                           w    s
If a linear sorption isotherm is used, as is commonly the case for trace
constituents (see Section 2.3.2), the above expression becomes:

                       C  
-------
2.4.2  Volatilization

2.4.2.1  Introduction

     Volatilization is defined as the transfer of matter from the dissolved
to the gaseous phase.  A considerable number of toxic substances volatilize
in the natural environment.  Volatilization rates depend on the properties
of the toxicant and on the characteristics of the water body.  If a toxicant
is "highly volatile", then obviously volatilization is an important process
affecting the fate of the toxicant.  However, even for toxicants which are
considerably  less volatile, volatilization cannot always be ignored.  This
is because the fate of a toxicant is governed by a variety of processes.  If
volatilization proceeds as fast as other competing mechanisims, even though
all the rates might be slow, then volatilization will influence the fate of
the toxicant.

     Methods  will be provided in this section to predict the volatilization
rate for toxic organic substances, which volatilize according to the
following relationship:

                  3C     ~kv       JP_         k-   (C  - -P- )           (II
                  3t      Z        K.,          v       K>i|
where
     C  =  concentration  of  toxicant  in  dissolved phase  (concentration
           of  solute)
      k   =  volatilization  rate  constant  in  units  of  length/time
      v
      k"  =  volatilization  rate  constant  in  mixed  water  body  in units  of
      v        -1
           time
      Z   =  mixed  depth  of  water  body

      P   =  partial  pressure  of toxicant  in  atmosphere  above  the
           waterbody being investigated.
                                           78

-------
     K  = Henry's Law constant
      H


For many applications the partial pressure of the compound in the atmosphere

is zero, so that Equation 11-25 simplifies to:


                                3C      *.'  r
                               It  =   ~  v                            (H-26)



     An alternate form of Equation  11-26 is in terms of the total pollutant

concentration, C , and the cite specific volatilization rate constant, k  :


                               3CT
                                 T  _   k    p                         (11-27)
                               3T  "  "kvm  CT                       (      '
where
     a   = fraction of toxicant present in dissolved phase
      w


The following sections will illustrate how to predict the volatilization

rate for toxicants of either low or high volatility.  But first, a brief

discussion of Henry's Law  is required.
2.4.2.2  Henry's Law



     Henry's Law is an expression which relates the concentration of a

chemical dissolved in the aqueous phase to the concentration (or pressure)

of the chemical in the gaseous phase when the two phases are at equilibrium

with each other.  One method of commonly expressing Henry's Law is:



                              P = K C                                 (11-29)
                                   H w
where
     P  = equilibrium partial pressure of pollutant in atmosphere above

          the water, atm
                                     79

-------
     C  = equilibrium concentration of pollutant in the water, mole/m
      w
                                     3
     K  = Henry's Law constant, atm m /mole
      H
Henry's Law in this form is valid for pollutants present in concentrations
up to 0.02 expressed as a mole fraction.   For compounds with molecular
weights greater than 50 g/mole, a mole fraction of 0.02 represents a
concentration of at least 55,000 mg/1.  Typically toxic pollutant levels
in the environment are present at levels  far below this concentration.

      Table 11-15 contains values of  Henry's  Law constants  for  a  number  of
 selected hydrocarbons.   In the table, Henry's  Law constant is  expressed in
 units of atm m /mole.   However,  in the literature Henry's  Law  constant  can
 be defined in numerous ways.   A second,  widely used  method of  defining
 Henry's Law constant is:
                                                                      (11-30)
                                       w
 where
      C  = molar concentration in air,  mole/m
       a

      K  = alternate form of Henry's Law constant,  dimensionless
       H

 Equations 11-29 and 11-30 are related as follows:
V
                            8.2 x
 where
      T = temperature of water,  K.

 This relationship is based on the ideal gas law.  Equation 11-31 is useful
 because of the frequent necessity to convert literature data from one set of
 units to another.
                                      80

-------
                                  TABLE  H-15




              HENRY'S  LAW CONSTANT  FOR SELECTED HYDROCARBONS

Oleflns
and
Acetylenes
Ethene (g)
Propene (g)
1-Butene (9)
1-Pentene (I)
1-Hexene (I)
2-Heptene (t)
1-Octene U)
Propyne (?)
1-Butyne (g)


Cycloalkanes
Branched-Chain
Alkanes
Cycl opentane (i.)
Cyclohexane (i)
Methyl cycl opentane (i)
Kethylcyclohexane (t)
Propyl cycl opentane (£)
Isocutane (y)
Isopentane (i)
2-Methylpentane (t)
2-Kethylhexane (i)
2,2-Dimethylpentane (t)
3-*ethyl heptane (i)
2,2,4-Trimethylpentane (I)
4-Metnyloctane (i)
Polychlorinated
Biphenyls
Aroclor 1242
Aroclor J248
Aroclor 1254
Aroclor 1260




KH
Henrys Law
Constant
(atm-m-'/mole
0.214
0.232
0.268
0.398
0.412
0.418
0.905
0.0110
0.0194





0.187
0.196
0.362
0.428
0.893
1.24
1.364
1.73
3.42
3.15
3.71
3.04
9.936


5.7x10-'
3.5 xlO'1
2.8x10-'
7.1 x 10-'







*v (cm/hr)a
20.
20.
20.
20.
20.
20.
20.
19.8
ZOi





20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
20.


15.6
18.9
18.9
19.6







Aromatics
Benzene (t)
Toluene (1)
Ethyl benzene (l)
o-Xylene U)
I sopropyl benzene (1)
Naphthalene (s)
Biphenyl (s)
Acenaphthene (s)
Fluorene (s)
Anthracene (s)
Phenanthrene (s)


n-Alkane
Methane (9)a
Ethane (g)
Propane (g)
n-Butane (g)
n-Pentane (i)
n-Hexane (t)
n-Heptane (i)
n-Octane (t)
n-Nonane (i)
Decane (t)
Dodecane (£)
Tetradecane (i)


Pesticides
DDT
Lindane
Dieldrin
Aldrin
Endrin
Heptachlor
Chlordane
Toxaphene
h
Henry's Law
Constant
(atm-mVmole
5.49x10-'
6.66x10-'
8.73x10''
5.27x10-'
1.45xlO-2
4.25X10-11
6. 36x10" *
2.28x10"*
2.35x10—
1.65x10"'
1.48x10-'



0.665
0.499
0.707
0.947
1.26
1.85
2.07
3.22
3.29
4.93
7.12
1.14



3.9xlO-5
4.9x10-'
2.0x10"'
1.4xlO-5
4.6x10-'
1.5x10-'
5x10' 5
0.1



kv 'cm/hr)a
19.4
19.5
19.6
19.4
19.8
14.5
16.0
11.7
11.9
18.2
9.6



20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
20.
20.


3.9
0.06
0.02
0.60
0.06
18.
4.8
19.8
These are estimated values based on k, = 20 cm/hr and k = 3000 cm/hr.
                                       81

-------
     Henry's Law constant can be estimated for slightly soluble compounds
(mole fraction ^0.02)  by the following expression:

                                          Ps X MW                     (11-32)
                      K   (atr,ma/mole)  = ____                    (II  32)
where
     P  = saturation vapor pressure of pure compound in Torr
      s
     MW  = molecular weight
     S  = solubility in water in ppm
      w

Tables II-5 through II-9 presented vapor pressure and solubility data for
the organic priority pollutants, which can be used to predict Henry's Law
constant.  Although Equation 11-32 is not valid for highly soluble
chemicals, generally the toxicants of interest here are only slightly
soluble, so that the expression is adequate.  The dimensionless form of
Henry's Law constant is expressable as:
                               16.04  P  x MW
                          '                                          (11-33)
                          H       Sw x T
where all variables have been previously defined.
                                EXAMPLE 11-4
                    Henry's Law Constant for Chloroform

     Calculate  Henry's Law constant  in the two forms expressed by Equations
 11-32  and  11-33.  Chloroform  (also called trichloromethane or CHC1  ) has the
                                                                  O
 following  properties:

     •    vapor  pressure =  150  Torr  (from Table  II-5)

     •    solubility  =  8200 ppm at 20  C  (from Table  II-5)
                                      82

-------
    0   Molecular weight =           12 (carbon)
                                     1 (hydrogen)
                                3 x 35.5 (chlorine)
                               Sum = 119

From Equation 11-32,

                         150x119            -3
                  K  =  	=  2.86 x  10     atm-m3/mole
                    H    760x8200

From Equation 11-33, at 20 C (293 K):

                              16.04x150x119
                        KM  =  	 =  0.12
                          H       8200x293
Henry's constant, expressed as K", had been found experimentally to be 0.12,
the same as predicted here.
                            END OF EXAMPLE II-4
2.4.2.3  Two Film Theory of Volatilization

     When a chemical volatilizes from water, the process can be visualized
as a mass transfer occurring over several distinct steps.  Figure II-8
presents a schematic representation of the process.  The concentration of
the chemical is C in the bulk liquid solution.  As the chemical moves upward
in the bulk solution it moves through a thin "liquid film" where a
concentration gradient develops because the transfer rate is limited by diffusion.
The dissolved chemical then volatilizes and passes through a thin "gas
film", where again transfer may be limited, before reaching the bulk vapor
phase.

     At the interface between the gas and liquid films the concentration in
the liquid (C ) and in the gas (P  , expressed as partial pressure) are
             i                   ci
assumed to be in equilibrium and to obey Henry's Law:
                                    83

-------
        Toxicant  concentration
          Vapor phase
                 Direction of movement

FIGURE  II-3
SCHEMATIC  REPRESENTATION OF VOLATILIZATION
FROM SOLUTION PHASE  TO  LIQUID PHASE
                                84

-------
                           P  . = K C                                  (11-34)
                            ci    H i                                       '


In the absence of net accumulation at the interface the mass flux from one

phase must equal the mass flux from the other, or
                   Fz=f (PC-PC1) =kl.  (C-C.)               (11-3



where
     F   = flux of chemical in z direction
      z


     k   = mass transfer coefficient in the qas phase across "gas film"
      9i


     k   = mass transfer coefficient in the liquid phase across "liquid

           film"



and P , P  ., C, C. are defined in Figure II-8.  Since it is not convenient
     L.   C I      1
to measure the partial pressure and concentration at the interface, it is

worthwhile to develop expressions for bulk transfer coefficients, given by:



                   F  = 1_V£ (p  . p')  - i,   (r   ci                 (11-36)
                    z   RUT  l c    PcJ    kvl  (C - V

where
     k   = overall volatilization rate defined for the gaseous phase



     k   = overall volatilization rate defined for the liquid phase



     S   = saturation concentration of chemical in equilibrium with P
      P                                                              c


     P"  = partial pressure in equilibrium with C
      c


Combining Henry's Law equilibrium expressions with Equations 11-35 and 11-36

the overall volatilization rates become:
                                       85

-------
                           k      R  T    k,.    k  .
                            vg    u     IT    gi
                                                                     (11-37)
and
                                         KHkgi
                                                                     (11-38)
Of the two expressions, normally Equation 11-38 is more useful  for the
purposes of this document because the pollutants being analyzed are in the
aqueous phase.  To simplify terminology Equation 11-38 will be rewritten as:
             or:
                               1    i     R T
                               1  _  1      u
                               kv    kl    KHkg
                              kv   kl    KH kg
(II-39a)
                                                                    (II-39b)
where the second subscripts to each variable have been dropped.  The
volatilization rate, k , is the same as shown earlier in Equation 11-25 and
                      v
depends on k , K , and k .
            g   H       1

     There are two special cases of Equation 11-39, depending on the value
of Henry's Law constant.  They are:
                      k,,  for large  1C  (liquid-phase  limited)
                     _ H g
                          ,  for small  1C (gas-phase limited)
(II-40a)
(II-40b)
To make Equation  11-40 usable, "large" and "small" values of K" have to be
                                                              H
defined.  For cases when the  liquid phase is  limiting the transfer rate,  a
large fraction, R, of the total resistance exists  in the liquid phase, or:
                                                                      (11-41)
                                          kl    KHkg,
                                        86

-------
Similarly when the gas phase is limiting:
                       1      / 1 \     /I     1
                           = R  T-  =  R  T-
(11-42)
Equations 11-41 and 11-42 can be rearranged to express Henry's Law constant
explicity:
                       k     R
                      _L 	  , for liquid-phase limited            (II-43a)
                       kg 1-R

                      _L ilE.   , for gas-phase limited              (II-43b)
                       kg   R
At  this  point  values for R, k  , and k  must be specified.  "Typical" values
of  k   and k  for surface waters are in the range of 20 cm/hr and 3,000
cm/hr, respectively.  For R values of 0.83, 0.90, and 0.95, the phase
limiting values of Henry's  Law constants, converted to units of atm-ru /rcole
 using Equation 11-31,  are as follows:

                    Henry's Constant  (atm-m3/mole)
          J^          L_iquid-phase Limited      Gas-phase Limited
         0.83               7.8 x  10""                3.3 x 10"5
         0.90               1.4 x  10~3                1.8 x 10'5
         0.95                3 x  ID'3                8.4 x 10~6

                                                           -3       3
Hence, for  Henry's Law constants  larger  than  about  1.0 x 10    atm m /mole
most  of  the resistance  to volatilization lies  in the  liquid phase,  and for
                                               -5      3
Henry's  Law constants  less  than about 1.0 x 10   atm m /mole,  most  of the
resistance  lies  in the  gas  phase.  When  either of the two phases controls
the volatilization rate, then  the  simplified  Equation 11-40 can be  used  in
 lieu  of  Equation  11-39.  The data  in the tables presented earlier can be
used  to  predict  Henry's  Law constant and then  to decide whether the gas  or
 liquid phase limits volatilization.

      Based  on  the  two-film  model  there  are two methods which  can be used to
 estimate volatilization  rates.  One approach  is considerably  more simple
 than  the other.   The  simpler approach  is based on the following reasoning.
Using "typical"  values  of k and  k , k   can be estimated based solely on K
                            1       g   v                                    H

                                     87

-------
as the independent variable, where K  is allowed to vary over its potential
                                    H
range of values.  As Table 11-16 shows, K  can vary by at least seven orders
                                         H
of magnitude.  Based on this variability of Henry's Law constant, Table
11-17 presents the associated volatilization rates.  As Henry's Law constant
increases, the volatilization rate approaches 20 cm/hr, the liquid phase
limiting rate.  As Henry's Law constant decreases, so does the
volatilization rate, with the lower limit being zero.

     The second method of predicting k  is based on finding k  and k
                                      v                      g      1
individually, rather than assuming typical values.  The gas-pnase transfer
rate can be found based on the evaporation rate of water as outlined in
Mills (1981).  Mills showed that:
                               kg-700V
where
     k ' = gas transfer rate for water vapor, cm/hr

     V  = wind speed, m/sec

This expression was derived from an empirical relationship shown  in Linsley
et jil_., (1979) for the evaporation of water.  Liss  (1973) conducted
measurements  in an experimental basin and found that:

                               k^ = 1000 V                            (n

where  the units are the  same  in Equation 11-44.   Considering  that the
approaches  used to develop Equations  11-44  and  11-45  are  different, their
agreement is  good.

     The values of kg and kg  are related by penetration theory  (Bird  e_t al_.,
1960)  as follows:

-------
                       TABLE  11-16

       HENRY'S  LAW  CONSTANTS  FOR SELECTED COMPOUNDS
        Compound
Henry's Law Constant (atm-mVmole)
  Vinyl  Chloride

  Carbon Tetrachloride

  Toluene

  Aroclor  1254

  Flourene

  DDT

  Dieldrin
                3.7

             2 x ID'2

            6.7 x ID'3

            2.8 x 10'3

            2.4 x 10-"

            3.9 x lO'5

            2.0 x 10'7
                        TABLE 11-17

       TYPICAL VALUES OF POLLUTANT VOLATILIZATION RATES
                     IN SURFACE WATERS
Ku(atm-m3/mole)
n
10°
lo-1
io-2
ID'3
10-"
io-5
io-6
io-7
1C (dimensionless)
H
41.6
4.2
4.2X10'1
4.2xlO-2
4.2xlO-3
4.2x10'"
4.2xlO-5
4.2xlO-6
k (cm/hr)*
20.
20.
19.7
17.3
7.7
1.2
0.1
0.01
using k  = 3000 cm/hr
      k, = 20 cm/hr
                                89

-------
where
     D   = diffusion coefficient of pollutant in air
      a

     D   = diffusion coefficient of water vapor in air
      wv

Diffusion coefficient data can be found in such references as Perry and
Chilton (1973), or estimated using the Wilke-Chang method, also in Perry and
Chilton.  If an analytical method is used to estimate diffusion coefficients,
note that it is easier to predict the ratio of two diffusion coefficients
than to predict each coefficient individually because some of the required
information cancels out of the ratio, and consequently is not needed at all.
     In many cases  it is acceptable to approximate the ratio of diffusion
coefficients as follows:
                               wv
                              _Da    (laV*                            (H-47)
                              D
where
     MW = molecular weight of pollutant

 Table  11-18  illustrates the difference between calculating the diffusion
 coefficient  ratio  by  using tabulated data from Perry and Chilton  and  by
 using  Equation  11-47.  The percent differences  between the ratios range
from 1 to 27 percent and average 15 percent.  This agreement is acceptable for
 screening purposes.   Combining  Equations 11-46,  11-44,  and  11-47,  the final
 expression  for  k   (in  units of  cm/hr)  is:
                9
(
                                       ^
                                       MW

 This expression is valid  for  rivers,  lakes,  and  estuaries.

      The  liquid phase transfer  coefficient  k  can be  predicted based  on  the
 reaeration  rate,  k ,  for  the  system.   The  relationship proposed by Smith
 et al.  (1981)  is;9
                                       90

-------
                      TABLE  11-18

COMPARISON OF TABULATED AND  PREDICTED VALUES  OF DIFFUSION
           COEFFICIENTS FOR  SELECTED POLLUTANTS

Pollutant
Chlorobenzene
Toluene
Chloroform
Naphthalene
Anthracene
Benzene

Molecular
Weight
113
92
119
128
178
78
Diffusion
Perry & Chil
(cm2/sec)
0.075
0.076
0.091
0.051
0.042
0.077
Coefficient
ton Predicted
(cm2/sec)
0.088
0.097
0.086
0.083
0.070
0.106
Perry & Chvlton
/DV«
w
.58
.59
.64
.48
.44
.59
Predicted:
l°\h
w
.63
.66
.63
.61
.56
.69

Percent
Difference
9
12
1
27
27
17

-------
                          'D  \"
                            W
where
                          \   2
                                  k'   ,   0.5  <  n <  1                  (11-49)
                                   a          ~~   ~~
     D   = diffusion coefficient of pollutant in  water
      w
     Dg  = diffusion coefficient of dissolved oxygen in water

     k"  = surface transfer rate of dissolved oxygen,  expressed in the
      a
           same units as k .

In other chapters of this report, the reaeration rate is presented as k ,
                                                                       a
defined as:
                               k  = k/Z                             ("
                                a    a

where

     Z  = mixed depth of water body

For  rivers the mixed depth is the  total depth, while for estuaries the mixed
depth  is the  total depth only if the  estuary  is well mixed.  Otherwise,  it
is the  depth  to the pycnocline.  Similarly for lakes, the mixed depth can be
less than the total depth, and can be chosen  to be the depth of the
epilimnion.

     The exponent  n varies as a  function of the theorical approach used  to
develop Equation  11-49.  If  film theory is used,  i.e. the film  is considered
to be  a laminar sublayer, then  n = 1.  If penetration or surface renewal
theory is used, n  = 0.5.  Using  experimental  approaches, researchers have
found  n to  vary from 0.5 to  1.0.   Since the movement of water  in natural
water  bodies  is generally turbulent,  the parameter n can be  chosen to  be
0.5.
                                     92

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     Perry and Chilton (1973) provide data and methods to predict the
diffusion coefficient of a pollutant in water.  The Othner-Thakor
relationship, described in Smith jrt al.  (1981) can also be used.  As an
approximate approach, by using the square root of the molecular weights the
following expression results:

                                                                     (H-51)
     A recent study (Rathbun and Tai, 1981) used a tracer technique to
predict the volatilization rates of four priority pollutants from 12
different rivers.  That study provides an opportunity to compare, even if
only to a limited degree, some of the methods presented here against field
results.  Table 11-19 briefly summarizes the results of Rathbun and Tai
(1981).  As shown by the values of Henry's Law constant for the four
pollutants, each pollutant is liquid phase limited, since all Henry's Law
constants exceed 1.0 x 10   atm m /mole.  The study results were unable to
predict differences in volatilization rates for the four pollutants, and
found that the best predictive expression was:
                              k  = 0.655 k'
                               V          a
Based on Equation 11-51 the screening methods predict:
                           k = 0.7kT to  0.8 k'
                            v      ci         a
where the range reflects the variability in molecular weight among the four
pollutants.

     If the default value of 20 cm/hr, suggested earlier in this section
were used as a rough estimate of the volatilization rate for liquid phase
limited pollutants, this value would fall within the observed range of 1.5
to  24 cm/hr.  It appears that the screening methods presented here generate
acceptable estimates of volatilization rates.
                                   93

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                           TABLE H-19

RESULTS OF A STUDY TO DIRECTLY DETERMINE VOLATILIZATION RATES OF
             SEVERAL PRIORITY POLLUTANTS IN RIVERS3

                      Henry's Constant

     Pollutant           (atm-rnVmole)            Molecular Weight

Benzene                  5.5 x 10"3                    H9

Chloroform               2.9 x 10"3                     78

Methylene Chloride       2.7 x 10"3                     85

Toluene                  6.7 x 10"3                     92
Study results showed:  k  = 0.655 k"
Range of values for 12 rivers:   1.5 to 24 cm/hr
Screening method predicts:   k  = 0.7 k"L to 0.8 k_"
          	—.	    v        a         a
aRathbun, R.E.  and D.Y.  Tai.   1981.   Techniques for Determining
 the Volatilization Coefficients of Priority Pollutants in Streams
 Water Research, Volume  15,  pp.  243-250.
                              94

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2.4.2.4  Volatilization Half-Life



     Numerous researchers have in the past calculated the volatilization

half-life of toxicants under controlled laboratory conditions.  The result

of some of this work was shown earlier in Tables II-5 through II-9.

Typically researchers have used the following expression to calculate the

half-life:


                                   0.693Z
where
     t   = half-life (time required for the concentration of the
      }|
           contaminant to decrease by half)



It is important to understand that the volatilization half-life of a

toxicant varies according to the environmental conditions.  Under controlled

laboratory conditions, where the depth of water is extremely small, t  can
                                                                     %
be extremely small.  If the water depth increases by 100 fold, for example,

so does t .
         h


     The volatilization half-life is affected by suspended solids in the

system.  When suspended solids are present, Equation 11-52 should be

modified to:
                                     - (1 + SKJ                     (H-53)
                           %      KM          $

where



     S  = suspended solids concentration



     K  = partition coefficient
      P


The partition coefficient is the ratio of the sorbed pollutant concentration

to the dissolved phase concentration.  A method to predict K  was discussed
                                                            n
earlier in Section 2.3.2.  Since the toxicant which sorbs to the sediments

is not directly available for volatilization, the total flux of volatilizing
                                     95

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particles decreases.   The following example illustrates how sorption can

influence the half-life.
                                EXAMPLE I1-5
     The following data for hexachlorobenzene were obtained from Table 11-8:



     •   solubility = 20  yg/1


                            -5           o
     •   vapor pressure = 10   Torr at 20 C


                6
     •   K  = 10
          ow


Under the conditions reported in the work of Mackay and Leinonen (1975)



     L  = 1 m



     k  = 8 cm/hr = 8 x 10~2 m/hr
Hence
                               0.693 x 1
                          t, = 	2 = 8.7 hours
                            h    8 x ID'2
 Note  that  the half-life  is small even though the vapor pressure is only 10

 Torr.  The results  indicate that the vapor pressure is, by itself, not

 necessarily a good  indicator of the importance of volatilization.



      Now,  consider  the following conditions which might be encountered  in a

 r i ver:
      •    k   (reaeration rate) = 0.5/day
          a
      •    suspended  sediment concentration = 550 ppm
                                   96

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                    4
     0   K  = 5 x 10
          P

     •   depth = 1 m


The expression of volatilization half-life modified to account for the

presence of the suspended solids is:

                             0.693  Z ,         .
From Equation 11-51, the liquid-phase transfer rate for hexachlorobenzene

is:
                 \

              <:ob /
                    x  0.5  x  1 = 0.29 m/day = 0.01 m/hr =  1 cm/hr

Henry's Law constant can be estimated based on Equation 11-32.
Using the data presented earlier
   K.. =
x 285 = 1.9 x 10"" atm-mVmole = 7.8 •  10"3, dimensionless
    H    760 x  .02


Using a  default value of 3,000 cm/hr for k  , the volatilization rate is:
                                          9
So
                              k  =1 cm/hr
The  half-life  becomes
           V
A comparison of half-lives shows that:


     •   t  = 8.7 hours  under  laboratory conditions
                                   97

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     •   t  = 75 days under instream conditions

This example illustrates that half-lives are not always extrapolatable from
one type of system to another due to the combined difference in sorption
effects and volatilization rates.
                            END OF EXAMPLE 11-5
2.4.2.5  Flux of Volatilizing Pollutants

     The preceding sections have provided techniques for predicting
volatilization rates of pollutants.  Obviously, if the volatilization rate
of one pollutant exceeds that of a second pollutant, then the first
pollutant is more volatile than the second.  However, this criterion alone
does not determine whether volatilization is important in a specific
situation.  The volatilization flux is the rate at which mass is transferred
to the gaseous phase from the liquid phase and is given by the following
expression:
                           Flux = k    C - —                         (H-54)
                                           KH
                                = kvC, when P = 0                     (11-55)

where

     C   =  concentration  of pollutant  in water  as  solute

     P   =  partial  pressure of  pollutant in  atmosphere.

Hence  both the  volatilization  rate and  the  dissolved  phase  concentration
have to  be considered  jointly  to predict  the flux being  volatilized.   Table
11-20  illustrates  these  principals for  several  chemicals.   The
volatilization  rates  for these pollutants,  range from a  high  of  20 cm/hr  for
carbon  tetrachloride  to  a low  of 0.02 cm/hr for dieldrin.   Anthracene has a
volatilization  rate constant of 18 cm/hr,  90 percent  as  high  as  the volatile
carbon  tetrachloride.  However, the solubility of anthracene  in  water is
much  lower (0.06 ppm  versus  785 ppm).  Hence if each  of  these two chemicals

                                       98

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                                           TABLE 11-20

         RELATIVE  VOLATILIZATION MASS FLUXES OF SEVERAL CHEMICALS  IN SATURATED  SOLUTIONS
      Chemical
Henry's Law Constant
    (atm-niVmole)
Volatilization Rate   Solubility
 Constant  (cm/hr)         (ppm)
K
                                                                                     ow
Flux Ratio'
Carbon
DDT
Dieldri
Tetrachloride

n
Phenanthrene
2
3
2
1
.3
.9
.0
.5
x
x
X
X
io-2
io-5
10-"
10- 3
20
3
0
9
.
.9
.02
.6
785
.002-. 085
0.2
1.0
400
10"-106
-
29,000

5x10
4
2
1
"-2xl06
x 10b
x IO3
This is the ratio of volatilization  flux of a  saturated  solution  of  carbon  tetrachloride to the
volatilization of the specified  chemical.

-------
were to volatilize from saturated solutions, the flux of carbon
tetrachloride would be 15,000 times as great.  The same type of comparison
can be made for DDT and carbon tetrachloride.  The volatilization rate
constant for DDT is relatively high (about 20 percent that of carbon
tetrachloride), but the solubility is so low that the ratio of
volatilization flux would be about 100,000:1.

     These comparisons have not considered the relative differences in
sorption characteristics of the pollutants.  Since only the solute
volatilizes, the volatilization flux of a pollutant which is mostly sorbed
to suspended material is lower than in the absence of suspended material,
all other factors remaining the same.  Tables 11-5 through 11-9 show the
octanol-water partition coefficient, which provides a measure of relative
importance of sorption for the four pollutants.  Because both DDT and
anthracene have higher octanol-water partition coefficients than does carbon
tetrachloride, the ratio of volatilization of mass fluxes is likely to be
even greater than calculated above for natural systems containing suspended
material.
                                       100

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2.5  TRANSFORMATION PROCESSES
2.5.1  Biodegradation
2.5.1.1  Introduction
     Microorganisms are ubiquitous in the aquatic environment.
Microbes are also very active chemically due to their ability to supply
energy for reactions through normal metabolic processes and to catalyze
reactions through enzymatic activity.  Chemical reactions which proceed very
slowly or not at all in the absence of biota occur at rates up to eleven
orders of magnitude faster in the presence of biological enzymes.  Some of
the reactions catalyzed by microorganisms transform or degrade organic
pollutants.  Frequently, microbial degradation, or biodegradation, is the
most important, if not the only process which can decompose an organic
pollutant in the aquatic environment.

     Although microbial communities catalyze countless reactions, many of
them fall into  a few classes of  important reactions.  Oxidative reactions
make up one very important class of biochemical reactions.  The
hydroxylation of aromatic compounds, such as benzene, is an example of an
oxidative reaction which generates polar compounds from non-polar ones:
                                                    OH
                                Enzyme
               Benzene
                             Catechol
An extremely  important oxidative reaction unique to microbial organisms  is
aromatic ring fission:
          CCOO"
          COO"
Enzyme
Enzyme
                                 Catechol
                                    101

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Microbes also catalyze reductive  reactions.   A notorious example is the
dehydrochlorination of DDT  to  produce DDE:
     ci
               DDT                                     DDE
Enzymes  can  catalyze otherwise slow hydrolytic reactions as well:
              s                                    s
              II                                    u
      (CH30)2— P— S— CHCOOC2H5 - ^^^ - *-  (CH.^ - P — S — CHCOOC^ + C^OH
                   CHCOOC2Hg                              CH2COOH
          MalatMon                            Malathion S-monoacid

      The term "biodegradation" encompasses these and other  biologically
mediated processes which chemically alter a pollutant.  Although  each
reaction causes the  disappearance or primary  degradation of a  compound,
different reactions  affect the toxicity  of a  compound  in markedly different
ways  (Alexander,  1980).

      "Mineralization" refers to the complete  degradation of an organic
compound to inorganic products:

   Toxic Organic Compound  — *-  CO  + Inorganic  Products (e.g.  NOZ,
                                  2                               ^
                                                          P04~>  SO*')
 In many reactions, however, organic products  remain.

      "Detoxication" reactions produce  innocuous  metabolities from a toxic
 substance:

               Toxic Organic Compound  —*-  Innocuous Compounds
                                     102

-------
In "activation" reactions microbes convert an innocuous compound into a
toxic compound:

                  Innocuous Compound    »  Toxic Compound

The "defusing" of potentially hazardous compounds occurs when biota produce
an innocuous compound before the parent compound's harmful form is
generated.

            Potentially Toxic Compound    »  Innocuous Compound

Finally, a toxic compound may be transformed chemically but still retain its
toxicity.  Figure II-9 illustrates some of the above types of reactions as
they occur among the phenoxy herbicides.

     Because of the wide variety of toxicological effects metabolic
transformations may have, evaluating the impact of a compound on the
environment requires a knowledge of the potential products which form.
However, for the purposes of estimating the concentration of a pollutant in
a natural water body, the user may simply consider biodegradation to be a
decay process.  Methods of estimating the rates of biodegradation constitute
the subject matter of the remainder of this section.
2.5.1.2  Rates of Biodegradation in the Environment

The rate at which a compound biodegrades in the aquatic environment depends
on its role in microbial metabolism.  Some organic pollutants serve as
food sources which provide energy and carbon for growth and cell maintenance
when metabolized by a microorganism.  In other cases, microorganisms
transform the pollutant, but are unable to derive energy for growth from the
reaction.  These two metabolic patterns, growth metabolism and cometabolism,
exhibit distinct characteristics and rates of degradation.  Because of the
important differences between these two types of biodegradation, they are
treated separately in the following discussion.
                                   103

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MICROSIAL TRANSFORMATIONS OF TOXIC CHEMICALS
         (Potential  Toxin)
           O(CH2)3COOH
(Less Toxic Substance)
          OH
          Cl
          OCH2CH2OSO3H
                 r-CI
         Cl

    (Potential  Toxin)
                                   Cl
         Cl

       (Toxin)
Source: Alexander (1980)
      FIGURE 11-9   MICROBIAL TRANSFORMATIONS  OF PHENOXY HERBICIDES
                                   104

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2.5.1.2.1  Metabolism of Growth Substances.

     Heterotrophic bacteria degrade certain  organic compounds to provide the
energy and carbon required for their growth.  Many toxic substances function
as growth substrates for bacteria in a manner similar to naturally occurring
organic compounds.  These growth substrates  are identifiable by their
ability to serve as the sole carbon source for a bacterial culture.  The
metabolic transformation of these growth substrates generally results in
relatively complete degradation or mineralization, thus detoxifying toxic
growth substrates.  The detoxifying effect and relatively rapid rates of
growth metabolism imply that potential growth substrates pose1 a lesser
threat to the environment than compounds which cannot be used in this
way (Tiedje, 1980).

     Before the utilization of a compound can begin, the microbial community
must adapt itself to the chemical.  Investigations of biodegradation of a
compound to which the biota have not been recently exposed, both in the field
(Spain ert aJL 1980), and in the laboratory (Shamat and Maier, 1980), have shown
the existence of a lag time (lag phase) of 2 to 50 days before the microbial
community acclimates.  Since the degradation of a growth substrate is
relatively rapid once a microbial population has adapted to it,
Tiedje (1980) has suggested that the primary concern in assessing
biodegradation of such substances should be the conditions and time period
required for adaptation or acclimation.

     The lag time depends on several biological and environmental
constraints.  The primary contraint is the development of a sufficiently
large bacterial population which is capable of utilizing the pollutant as a
growth substrate.  Frequently, specific organisms with specific enzymes are
required to metabolize a pollutant.  The processes of species selection and
enzyme induction  by which a microbial community adapts itself to a pollutant
require  time.  The adaptation  time  is influenced both by prior exposure of
the community to  a pollutant and the  initial numbers of suitable species.
Spain et_ aJL (1980) have demonstrated that prior exposure to a compound
reduces  or eliminates the adaptation period.  Thus, lag times in pristine
environments should be much longer  than in locations which have been chronically
exposed  to a compound.  In addition, Ward and Brock (1976) have shown that  lag time
                                    105

-------
preceding the onset of petroleum degradation depends on the initial  size nf
the bacterial population.   Water with larger microbial  communities should
require relatively shorter times to develop a viable population of
degraders.  High microbial biomass levels are associated with higher BOD
                                                                        5
concentrations.

     The presence of more easily degraded carbon sources may delay the
adaptation of a microbial community to the metabolism of a pollutant.  Ward
and Brock (1976), found that microorganisms in lake water metabolized added
glucose completely before degrading hydrocarbons.  This diauxic pattern may
result in longer lag times.

     A final factor which influences lag time is the concentration of the
pollutant in the water.  There may be concentration thresholds below which
adaptation does not take place.  (For example, no adaptation for metabolism
of 4-nitrophenol occurred at concentrations below about 40 yg/1 (Spain j2t
al . , 1980).  Too high a pollutant concentration, on the other hand, may be
toxic to the microbes (Tabak et a\_., 1981).  The user should be aware of
these possibilities when extremely low or high concentrations are involved.

     Once the microbial community has adapted to the organic pollutant, it
is of interest to know the rate at which biodegradation occurs.  Kinetic
expressions  for compounds used as a growth substrate can be relatively
complicated  since both the substrate and bacterial concentrations change
with time.   The Monod equation has been used to describe the degradation
rate of a compound which serves as a sole carbon source:

                       dC    1  dB   ymax    B •  C
                       dt   Yo           K  + c
                                           s
where
     C    = pollutant concentration
     B    = bacterial concentration
     Y    = biomass produced per unit C consumed
     y    = maximum specific growth rate
      max
     K    = half-saturation constant
      s
                                    106

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     Frequently,  the Monod equation is reduced to a second-order
biodegradation expression by assuming C «K ,  in which case:
                                                                     (.1-57)
where
     k   = second-order biodegradation rate constant
      82
                s
     Although Monod kinetics accurately describe some laboratory results,
they are inapplicable in the environment due to the presence of other carbon
sources.  As a simple alternative, first order kinetics are frequently
applied:

                                  -— = k  • C                      (11-58)
                                    dt    B

where
     k  = first-order biodegradation rate constant.
      B

This first-order expression  is analagous to the equation commonly used for
the decay of BOD  (see Chapter 4). Larson (1981) has shown that first-order
kinetics which  include a  lag phase  (lag time) represent the degradation of
                                                                          6
growth substrates reasonably well at initial bacterial concentration of 10
cells/ml or  less, a condition which is usually met  in the environment.
 2.5.1.2.2  Cometabolism

     Microorganisms  also  degrade compounds which they cannot use as  a
 nutrient or  growth substrate  through  cometabolism.  Cometabolism is  thought
 to  occur when  enzymes  of  low  specificity  alter  a compound  to form products
 which the other  enzymes in the organism cannot  utilize.  The metabolites
 formed  in the  process  are structurally similar  to their parent molecules and
 frequently retain their toxicity.   In some cases, the product of
 Cometabolism can be  used  as nutrients by  other  organisms,  but often  these
 intermediate products  accumulate (Alexander,  1980).
                                    107

-------
     The kinetics of microbial  cometabolism differ  significantly  from  that
of growth metabolism.   Often no lag  occurs  before cometabolism  begins.   The
degradation rates, though,  are  generally slower  than  the  fully  adapted  rates
of growth metabolism (Tiedje,  1980).   Since cometabolism  does not provide
the microbes with any energy,  it has no effect on the population  size.   The
rate of cometabolism,  however,  is directly  proportional to  the  size  of the
microbial population.   Paris et^ aiL  (1981), showed  that a second-order  rate
law described microbially catalyzed  hydrolytic reactions:

                            -£.I«K.B.C                        di-59)

Since the bacterial population, B, is independent  of  the  rate  of
cometabolism, it  is possible to reduce Equation  11-59 to  a first-order law
by making the following substitution:

                              kg = kB2  - B                           (11-60)

     In order to  use literature values of the second-order biodegradation
rate constant in  Equation 11-60, it is necessary to make  an estimate of the
size of the bacterial population.  Since different techniques  of  bacterial
enumeration can yield results which vary over several orders of magnitude,
it  is  important to  use estimates of B based on the same method used to
calculate k   .  Table  11-21 lists bacterial densities which are typical of
            no
lakes  and rivers.   Obviously,  large uncertainties  in environmental rates of
cometabolism  exist  due to the wide range of possible bacterial densities.
Generally,  the user should  make conservative assumptions unless other data,
e.g. a  high BOD,  indicate larger bacterial densities.
 2.5.1.2.3   Summary

      Table 11-22  summarizes  some  of  the major differences between growth
 metabolism and cometabolism.   Although the  exceptions to the generalizations
 about each process  are numerous  and  some  compounds can undergo both
 processes, the distinction between the metabolic  processes can serve  a
 useful function in  a screening method.  The generalization about each
                                   108

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                             TABLE  11-21




                         SIZE  OF TYPICAL BACTERIAL

                       POPULATIONS IN NATURAL WATERS
Water Body Type
Bacterial Numbers (cells/ml)
Ref.

Oligotrophic Lake
Mesotrophic Lake
Eutrophic Lake
Eutrophic Reservoir
Dystrophic Lake

Lake Surficial Sediments
40 Surface Waters
Stream Sediments
Rur River (winter)
50- 300
450- 1,400
2000-12,000
1000-58,000
400- 2,300
Q in
8xlOy - 5xl0lu cells/g dry wt
500-lxlO6
107-108 cells/g
3xl04
a
a
a
a
a

a
b
c
d
References:

       aWetzel (1975).  Enumeration techniques unclear

        Paris et _§_]_.  (1981).  Bacterial enumeration using plate counts.
       ^>
        Herbes & Schwall (1978).  Bacterial enumeration using plate counts.

        Larson et al_. (1981).  Bacterial enumeration using plate counts.
                                   109

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                                                            TABLE  11-22

                             SUMMARY OF THE CHARACTERISTICS OF THE TWO  GENERAL  TYPES  OF
                         BIODEGRADATION:   METABOLISM AND COMETABOLISM  (After Tiedje, 1980)
         Topics
     Metabolism for Growth
          Cometabolism*
Distinguishing characteristics
Degradation  rates

Behavior at  low  pollutant
  concentrations

Acclimation
Relation  of degradation kinetics
  to total  biomass, e.g. decay
  rate =  kg2 • B  • C

Extrapolation
Effect of added carbon
Organism will grow on suf^tance as  sole C
  source.   Generally ultimate degradation.

High rates.

Possible anamalous behavior due to  threshold
  for enzyme induction.

Major effect: lag may be quite  variable or
  lengthy due to low initial  density of
  degraders, and perhaps starvation state
  of organisms in natural  sample.

Likely not  valid, use first-order kinetics.
General:  expect eventual  degradation  in nature.
  Quantitative: difficult to be  precise because of
  growth  kinetics and acclimation  effects, but
  may not be important problem because of
  generally fast rates.
Diauxic  pattern—more easily metabolized
  substrates are used first.
Organism will  not  grow on substance as  sole  C  source.
  Accumulation of  intermediate products likely.

Generally slow rates.

No anomalous behavior, rates are first  order in
  pollutant concentration.

Often no effect; rarely causes induction,  may
  increase tolerance to toxic chemical.
May be valid since  activity of interest is  often
  proportional  to general biomass.
Measure kinetic  parameters accurately:  because
  of the generally  slower rates, extrapolations
  will  be made over longer times, and thus  measured
  parameters  need to be accurate.  Also environ-
  mental  influence  factors, e.g. temperature, pH,
  play  a more important role.

Generally effect is proportional to microbial
  population  unless specific carbon source  happens
  to induce or inhibit activity of interest.
*Alteration of a substrate, for purposes other than growth, e.g. for detoxification

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process suggest the following approaches when the user has some knowledge of
a compound's metabolic pathway:
     •   Cometabolism -
          a)   Find  a  second-order  rate  constant  and  estimate  biomass
              density.   Apply Equations 11-59,60.
          b)   When  a)  is not possible,  assume cometabolism is
              negligible,  i.e. k =0.
                                B
     t   Growth Metabolism
          a)   Find  a  first- or second-order rate constant.
          b)   Estimate a range of lag times as follows:

          For chronically exposed  water bodies,  assume that no lag
          time (t ) occurs.   For water  bodies not recently exposed
          (within 200 days)  proceed  as  follows:

          1.   Estimate lag time using available information.   If no
              information is available  use a range of 2-20 days.
         2.   Assume adaptation occurs as follows:

             a)   Rivers    - at travel  times < t ,  k  =0
                                                L   B
                           - at travel  times > t ,  k  ? 0
                                             -  L   B
             b)   Lakes     - for well mixed lakes,  first determine
                             C at  time  =  t  ,   Ct   due to all
                             processes  except  biodegradation.
Then
                             using  Ct   as  C   solve  for Ct     with  a
                             modified  time,  t ,  (t   =  t-t  ).   (Use
                                             mm     L
                             equations  in  Section 5.6.1)
                           -  for  stratified  lakes  use  only  the
                             volume  through  which  the  inflow passes
                             (e.g. the hypolimnion  volume)  in
                            111

-------
                                 calculating the hydraulic residence
                                 time (T ).   Then proceed as above.
                                        w
                 c)  Estuaries - consider all processes except
                                 biodegradation through that downstream
                                 segment for which T ,  as measured from
                                                    w
                                 the injection point, becomes greater
                                 than t .  Thereafter include
                                 biodegradation.

When no data on which metabolic pathway a compound follows are available,
the user should apply any available kinetic information and allow for the
possibility of a lag phase prior to the onset of degradation.
2.5.1.3  Chemical Properties Influencing Biodeqradation

     The chemical properties of a compound determine whether microbes can
potentially utilize it as a growth substrate or not.  Compounds which serve
as bacterial growth substrates usually decay more rapidly than those which
microbes cometabolize.  Thus, significant differences in the aquatic fate of
pollutants can arise depending on which degradation process takes place.

     Unfortunately, it is not possible at this time to predict whether a
toxic compound is a potential source of energy and carbon solely on the
basis of its chemical structure.  Rather, the biodegradability of a compound
is usually  investigated in laboratory tests (Gilbert and Lee, 1980).
Compounds which are growth substrates should be able to serve as sole carbon
sources for a microbial community.  Compounds which cometabolize should
degrade only in the presence of another carbon source.  A systematic study
of the metabolic pathways of the priority pollutants is desperately needed.

     Table  11-23 contains the results of a preliminary degradation test on
the organic priority pollutants (Tabak jjt a\_., 1981).  Because the
experimental conditions were so favorable for biodegradation, the tests
serve as a  good indicator of a compound's potential biodegradability.  Since
the pollutants were not the sole carbon sources, no conclusions can be
                                 112

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                POTENTIAL BIODEGRADABILITY OF  ORGANIC  POLLUTANTS
                                   IN  AN  AEROBIC  ENVIRONMENT
                                  (After  Tabak  et.  al_.,  1981)
Pesticides

Test Compound
Al drin
Dieldrin
Chlordane
DDT p.p'

DDE p.p'

DOD p.p'

Endosul fan-al pha

Endosul fan-beta
Endosul fan sul fate

PCB-1016
PCB-1221
PCB-1232
PCB-1242

Chloroethanes
1 ,1-Dichloroethane
1 ,2- Dichl oroethane
1,1, 1-T rich! oroethane
1 ,1 , 2 -Trichl oroethane
1 , 1 ,2 ,2-Tetrachl oroethane
HexacMoroethane

Hal ^methanes
Mettiylene chloride

Bromochlorome thane

Carbon tetrachlon de
Chi oroform

0 i chlo rob romome thane
Bromoform
Chlo rod ibromo methane
Tn chlorofl uorome thane
Adaotat i on
Summary
N
N
N
N

N

N

N

N
N

N
D
D
N


A
B
B
C
N
D


D

D

D
A

A
A
N
N
Rate
Summary
0
0
0
0

0

0

0

0
0
PCB's and Related
0
2
2
0
Halogenated Aliphatic

1
1
1
1
0
2


2

2

2
2

1
1
0
0

Test Compound
Endrin
Heptachl or
Heptachlor epoxide
Hexachlorocycl ohexane
ti-BHC-alpha
Hexachlorocyclohexane
B-BHC-beta
Hexachlorocycl ohexane
4>-BHC-delta
Hexachlorocycl ohexane
X-BHC-gamma (lindane)
Acrolein

Compounds
PCB-1248
PCB-1254
PCB-1260
2-Chl orohaphthal ene
Hydrocarbons
Chloroethylenes
1,1-Dichloroethylene
1 ,2-Dichloroethylene-cis
1 .2-Dichloroethylene-trans
Trichloroethylene
Tetrachloroethylene
Chloropropanes
1,2-Di chlo ro propane

Chloropropylenes
1,3-Dichloropropylene

CMorobutadienes
Hexachloro-1 ,3-butadiene
Chi oroperttadienes
Hexachl orocycl open tad iene




Adaptation
Summary
N
N
N
N

N

N

N

D


N
N
N
D


A
B
B
A
A

A


A


D

D




Hate
Summary
0
0
0
0

0

0

0

2


0
D
0
2


2
1
1
1
1

1


1


2

2




Halogenated Ethers
Bis-(2-ch1oroettiyl) ether'
2-Chloroethyl vinyl ether
4-Chlorodi phenyl ether
Results of Tdbok et al.(i981)
conditions, ine test measures
duration = 28 days.
Key to Test Summary
D
D
N
2
2
0
using Bunch and Chambers screening test.
disappearance rather than mineralization of
4-Bromodi phenyl ether
Bis-(2-chloroethoxy) methane
Bis-(2-chloroisporopyl ) ether
Results reflect potential biodegradability
a compound. A domestic sewage innoculum
N
N
D
0
0
2
under favorable
was used. Test

N - Not significantly degraded under conditions of test method.
  D  - Significant degradation with rapid adaption; <7 days.
  D* - Same as D except slower adaptation at higher pollutant concentration.
  A  - Significant degradation with gradual  adaptation, 7-21 days.
  A* - Same as A except no degradation evident at higher pollutant concentration.
  B  - Slow degradation.
  C  - Very slow degradation with  long adaption period required,  >28 days.
  T  - Significant degradation with gradual  adaptation followed by deadaption (toxicity).

Key to Rate Summary
  Very crude estimates of first-order biodegradation rate constants may be made from the  information given in
  0 - No significant degradation rate
           -1
  1 - .05 day"
2 - k
                  -.5 day  ,  use .05 day"
         , .5 day 'l , use .5 day"1
                                                    113

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                                        TABLE  11-23   (continued)
Test Compound
Benzene
Chlorobenzene
1,2-Dichlorobenzene
1,3- Dichloro benzene
1,4- Dichloro benzene
1,2, 4-Trichloro benzene

Phenol
2-Chloro phenol
2,4-Dichloro phenol
2,4,6-Trichloro phenol
Pentachloro phenol
2 ,4 Dlmethylphenol

Dimethyl phthalate
Diethyl phthalate
Di-n-butyl phthalate

Napthalene
Acenapthene
Acenaphthylene
Anthracene
Phenanthrene
Adaptation
Summary
D
D
T
T
T
T

D
D
0
D
A
D

0
D
0

D
D
. D
A
D
Rate
Summar
2
2
1
1
1
1

2
2
2
2
1
2

2
2
2

I
2
2
1
2
Monocyclic Aromatics
y Test Compound
Hexachl orobenzene
Nitrobenzene
Ethyl benzene
Toluene
2,4-Dinitrotoluene
2,6-Dimtrotoleune
Phenolic Compounds
p-Chloro-m-cresol
2-N1tro phenol
4-Nitro phenol
2,4-Dinitro phenol
4,6-Dini tro-o-cresol

Phthalate Esters
Bis-(2-ethyl hexy! ) phthalate
Di-n-octyl phthalate
Butyl benzyl phthalate
Polycyclic Aromatic Hydrocarbons
Fluorene
Fluoranthene
1,2-Benzanthracene
Pyrene
Chrysene
Adaptation
Summary
N
D
D
D
T
T

D
D
D
D
N


A
A
D

A
A*
N
D*
A*
Rate
Sumtna ry
0
2
2
2
1
1

2
2
2
2
0


1
1
2

1
2
0
2
1
Nitroso Amines and Miscellaneous Compounds
Ni trosamines
N-Nitroso-dl-N-
propylamine

N-Nitrosodiphenyl amine



N

D



0

2

Substituted benzenes
Isophorone

1 ,2-Diphenylhydrazine

Acrylonitrile

D

T

D

2

1

2
Results of Tabak et a|.  (1981) using  Bunch and Chambers screening test.  Results reflect  potential biodegradabil ity  under  favorable
conditions.   T~he test measures disappearance rather than mineralization of a compound.  A domestic sewage innoculum  was used.  Test
duration * 28 days.

Key to Test Summary
  N  - Not significantly degraded under  conditions of test  method.
  D  - Significant  degradation with  rapid adaption; < 7 days.
  D* - Same as  D except slower adaptation at higher pollutant  concentration.
  A  - Significant  degradation with  gradual adaptation, 7-21 days.
  A* - Same as  A except no degradation evident at higher pollutant concentration.
  B  - Slow degradation.
  C  - Very slow degradation with long adaption period required;  > 28 days.
  T  - Significant  degradation with  gradual adaptation followed  by deadaption (toxicity).

Key to Rate Summary
  Very crude  estimates of first-order biodegradation rate constants may be made from the  information given In  lab^k el_  <0 .

    0 - No significant degradation rate

    1 - .05 day"   < k   < .5 day" ;  use  .05 day~

    2 - kB > .5 day"*; use .5 day"1
                                                           114

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reached about their metabolic pathways.  Some information on the rates of
adaptation and decay, though, can be extracted from the results.

     The adaptation summary results may be used as follows:

     •   Rapid Adaptation (D) - Use a range of adaptation times from
         zero days upward depending upon conditions described above.

     •   Gradual Adaptation (A) - Use a range of adaptation times from
         7 days to more than 20 depending upon the conditions described
         above.

     The rate summary results represent estimates of the biodegradation rate
constants assuming the compounds decay according to first-order kinetics.
General values presented at the bottom of the table are gross estimates and
should only be used if no better data are available.  The rate constants
should represent an upper limit for biodegradation rates by adapted populations
observed in the environment.

     Table  11-24 contains literature values of biodegradation rate
constants.  Where possible, the likely metabolic pattern has been indicated.
Some of these constants were measured  under environmentally relevant
conditions.   In general, rate constants should be compared with those  in
Table  11-24 before use.
2.5.1.4   Environmental  Influences  on  Biodegradation Rates

      Environmental conditions  strongly  influence  the metabolic  activity of  a
microbial  community.  The  environment affects  the types  of metabolic
reactions  microbes are  able  to carry  out,  the  availability of nutrients for
these reactions,  and  the rates at  which  these  reactions  occur.  The
environmental  variables which  are  responsible  for these  effects are
discussed  in the  following sections.
                                    115

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                      TABLE 11-24




BIODEGRADATION RATE CONSTANTS UNDER AEROBIC CONDITIONS
Cc.npcund
Pesticides
2,4-D Butoxyethyl ester
Malathion
Chlorpropham
Furadan
Atrazine
1 Polychlorinated Blphenyls
Aroclor 1221
Aroclor 1016
Aroclor 1242
Aroclor 1254
Halogenated Ethers
4-Chlorophenyl phenyl ether

Monocyclic Aromatics
Nitrobenzene
2-Chlorotoluene
Phenolic Compounds
Phenol

2-Chlorophenol

2,4-Dlchlorophenol

Pentachlorophenol

2,4-Oimethylphenol
2,4-Dinitrophenol
2,4 ,6-Tri ni trophenol
Phthalate Esters
Dimethyl
Di-ethyl
Dl-n-butyl
Di-n^-octyl
Di-(2-ethylhexyl

Butyl Benzyl
k k
Second-Order First-Order
Rate Constant Rate Constant
(ml cell"' day"1) (I/day)
1.2xlO"5'3 1.3X10"2'1
1.1x10"'° l.lxlO"'(1
6.2X10"10'3 6.2xlO"7(1
2.4x10"' 2.4x10"'''
2.4x10"' 2.4xlO"!'4
.8<2
.2<2
.15<2
.1(2
.011-.01612
3.8<4
.7'2
6.5x10" (3 6.5x10"*
4.'2
6.<2
l.<2
.3
.5<2
.1(4
.1(2
I.'2
I.'2
.2<2
0
1.2x10"' .12(1
• 7.7x10"' 7.7X10"5'1
7.0xlO"7 7.0x10"*''
7.4x10"' 7.4X10"6'1
1.0x10"" l.OxlO"7
2.5xlO"2'4
>.35<4
t
'5 Reference
Half-Life Temperature
(days) («c)
53 20
6.3xl02 20
1.1x10* 20
3 x 10* ?
3 x 10* ?
.9 ?
3.5 ?
4.5 ?
7. ?
43-63 ?
.2 ?
1. 20
1.1x10 ?
.2 20
.1 ?
.7 20
2.3 ?
1.4 20
6 25
7 25
.7 25
.7 20
3.5 20
20
5.6 ?
9.0xlO! ?
1.0x10' ?
9.3x10* ?
6.9x10' ?
28 ?
<2 ?
Compound
Used as a
Growth Substrate? Experimental Conditions Ref.
' Natural surface water sanples
Yes Natural surface water sanples
? Natural surface water samples
7 7
7 7
? Acclimated activated sludge
? Acclimated activated sludge
? Acclimated activated sludge
? Acclimated activated sludge
? River water; Log = 5-13 days
? Activated sludge
Yes Adopted activated sludge, COD decay
? Natural surface water sample
Yes Adapted activated sludge, COD decay
? Polluted river water
Yes Adopted activated sludge
7 Soil suspension
Yes Adapted activated sludge; COD decay
7 Natural lake waters
Yes Unadapted; Nutrient Broth
Yes Adapted; Nutrient Broth
Yes Adapted activated sludge
Yes Adapted activated sludge
No Activated sludge
7 7
? ?
7 7
7 7
7 7
7 River Water
? River Water
a
a
a
b
b
c
c
c
c
c
c
d
e
d
c
d
c
d
c
f
f
d
d
d
g
g
g
g
g
c
c
                        116

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                                                 TABLE   11-24   (continued)
kB2 kB
Second -Order Fi rst-Order
Rate Constant Rate Constant
Compound (ml /cell /day) (I/day)
Polycyclic Aromatic Hydrocarbons
Napnthalene - - H
< 4.X10-
Arthracene - .0025
2.5x10"*
1.5
Benz( a)anthracene - l.xlO
A _ i n~ '
t . X 1U
Benz(a)pyrene - < 3x10
< 3x10" s
Phenanthrene 3.8x10"' 3.8x10"'"
t

Half-Life
(days)

5.0
1.7X101
2.8xl02
2.8xlOs
.5
6.9x10'
large
large
1.8x10*
T
o
Reference
Temperature
rc)

12
12
12
12
?
12
1 7
It
12
12
-j

Compound
Used as a
Growth Substrate7 Experimental Condi tons Pef

Yes Contaminated stream srdiF'ents h
? Pristine strean sediments h
Yes Contaminated stream sediments h
? Pristine stream sedinents h
? Contaminated stroarn c
Yes Contaminated stream secnments h
? Contaminated stream sedirr.ents h
? Pristine stream sediments h
? ? e
Notes'                                                                                   References•




1}   First-order rate  constant computed using Equation 11-60  and B = 103 cells/ml.            a)   Paris et_ al_  (1981)




2}   First-order constant calculated  from percent  disappearance and elapsed time.             b)   Schnoor (1981}




3}   Bacterial enumeration using plate count technique.                                     c}   Callahan ei a_l_.  (1979)




4)   First-order rate  constant computed from reported half-life                              d)   Fitter (1976)




                                                                                        e)   Paris et aj  (1930)




                                                                                        f)   Kirsch and Ctzel (1973)




                                                                                        g)   Wolfe et a_]_  (]9?0)




                                                                                        h)   herbfs & Schwall  (1978)
                                                                     117

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2.5.1.4.1  Temperature

     In general, a molecule must have an energy greater than a threshold or
activation level in order for it to react chemically.  Since increasing the
temperature increases the number of molecules which have this minimum
energy, both biotic and abiotic reactions generally proceed more rapidly at
higher temperatures.  However, the fact  that enzymes catalyze most
biochemical reactions, and that microbial populations can adapt to changes
in ambient temperatures, complicate the temperature dependence of
microbially mediated reactions.

     It  is common practice to represent the temperature dependence of
biodegradation  using the following empirical formula:

                       k (T) = k  (T )  •  0     o                        (11-61)
                        B       B  o     B

where

     k  (T)  = specific biodegradation  rate constant  at  temperature = T
     k  {T ) = specific biodegradation  rate constant  at  temperature = T
       Boo                                       o
     T   = ambient  temperature,  C
                                  o
     T   = reference  temperature,  C
       o
      0  = temperature  coefficient for  biodegradation
       B
     The results  of  Larson et  al_.  (1981) and Ward  and  Brock  (1976)  show that
 the  rates of  nitrilotriocetate  and hydrocarbon  biodegradation  increased
 approximately two-fold over a ten degree temperature range  (0   =  1.072).
 Either this  value  or the  typical  value of  1.047 used for  BOD decay  is
 adequate for  screening purposes.
 2.5.1.4.2  Nutrient Limitation

      Microbes require nutrients such as nitrogen and phosphorus in order to
 metabolize organic substrates.  Several researchers have suggested that
 inorganic nutrient limitation is a significant factor influencing
 biodegradation rates in the aquatic environment (Ward and Brock,  1976;
                                   118

-------
Roubel and Atlas, 1978;  Herbes and Schwall, 1978).  Ward and Brock (1976)
found a high correlation between hydrocarbon degradation rates and
phosphorous concentrations in natural waters.  The data fit a saturation
relationship of the Michael is-Menten type:
where
     k (C  )  = specific biodegradation rate constant at dissolved
      B  p
               inorganic phosphorus concentration, C
                                                    P
     C       - dissolved inorganic phosphorous concentration, ya/1
      P
     k (C *) = non-nutrient limited biodeqradation rate onstant
      B  p
     This relationship should serve as a good indicator of possible
phosphorous limitation of biodegradation in the environment.  Generally
surface waters downstream of domestic sewage treatment plants are not
limited in either nitrogen or phosphorus.  Equation 11-62 should be applied
only when other nutrients such as carbon and nitrogen are not limitina.
2.5.1.3  Sorption of Substrates

     Many organic pollutants adsorb strongly on sediments, (See
Section 2.3.2.  The difference in the physical and chemical environments
between sorbed and dissolved pollutants is likely to influence their
availability to microbial organisms.  Baughman et aj_. (1980) showed that the
dissolved fraction of the compounds studied was available to biota for
degradation while the sorbed fraction was not.  In such cases, the rate of
disappearance of the pollutant is:

                         d  CT
                         ._!  = k  •  C  = a 'k -C                    (H-63)
                         dt      B    w    w  B  T
                                       119

-------
where
     C  = the pollutant concentration in the aqueous phase
      w

     a  = the decimal fraction of the total analytical pollutant
      W
          concentration which is in the aqueous phase (a  = 1 - fraction
          sorbed).

     It is well known, however, that bacteria grow very readily on surfaces
and that increasing available surface area in the form of clays and
sediments can increase rates of microbial metabolism.  If specific
information regarding the effects of sorption on the rates of biodegradation
are not available for a compound, it is best to assume that sorption does
not change this rate.
2.5.1.4.4  Solubility

     Wodzinski and Bertolini (1972) have shown that in the dissolved state,
naphthalene and biphenyl were degradable while in the pure crystalline state
they were not.  Thus, sparingly soluble compounds could degrade slowly for
this reason alone.  The extent to which this phenomenon applies to other
biodegradation reactions has not been established.  The user may assume that
only dissolved and sorbed chemicals are degraded.
2.5.1.4.5  £H

     The hydrogen  ion concentration also influences rates of biodegradation.
Each bacterial  species has a pH range for which it is best suited.  Thus, at
different pH values, different species may exist, or a given species may
metabolize the  pollutant  at different rates.  Hambrick ot_ aJN  (1980) found
that the mineralization rate of naphthalene in oxidizing sediments varied  in
the proportions 1:6:5 at  pH 5, 6.5, and 8.  The same study found that  the
mineralization  rates of octadecane varied  in the proportions 4:5:7  at  the
same three pH's.   Until more general rules for predicting pH effects are
                                   120

-------
available, the user should assume biodegradation rates are independent of pH
in the pH range of 5-9 and decrease outside this range.
2.5.1.4.6  Anoxic Conditions

     As the concentration of dissolved oxygen in natural water is depleted,
metabolic pathways shift.  When the dissolved oxygen concentration drops to
about 1 mg/1, the rate of biodegradation becomes dependent on oxygen
concentration in addition to substrate concentration and the rate of
degradation starts to decrease.  At a dissolved oxygen concentration of
about 0.5 to 1.0 mg/1, nitrate begins to substitute for molecular oxygen as
an oxidant.

     When oxygen is depleted anaerobic metabolism prevails with its
generally lower energy yields and lower growth rates.  Most organic
substances are biodegraded more slowly under anaerobic conditions.  Rate
constants derived for oxygenated systems are no longer appropriate;  their
use may overpredict the  amount of degradation.

     Exceptions do exist to the rule of slower degradation under  anoxic
conditions.  Reactions such as dehydrochlorinations and reductive
dechlorinations lead to much higher degradation rates for many chlorinated
hydrocarbons.  Example compounds include lindane, heptachlor,
pentachlorophenol, and some one and two carbon chlorinated alkanes.
                                  121

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                                EXAMPLE 11-6
                      Blodegradability of Naphthalene

     Evaluate the biodegradability of naphthalene discharged into the
Lepidoptera River by a point source  just upstream from Northvilie's sewage
treatment plant.  Assume the following water quality parameters at the
upstream discharge:

                                  o
     Temperature              = 10 C
     Suspended Sediment       = 10 mg/1
     Inorganic Phosphorus     =  5 yg/1
     Dissolved Oxygen         =  5 mg/1

     First, check the potential biodegradability of naphthalene in
Table 11-23.  The table indicates that naphthalene degrades rapidly,
kB= .5 day  , and that bacteria adapt quickly to it.

     Next, examine Table 11-24 for further information on naphthalene's
biodegradability.  Naphthalene is a potential growth substrate.  In
addition, the data in this table concur with the rapid degradation rates
suggested by Table 11-23.  In sediment, which had been previously exposed to
naphthalene, a biodegradation rate constant of 0.14 day   was measured.
This is close to the rate constant in Table 11-24.  As one would expect for
                                                                     -4    -1
a growth  substrate, degradation rates are much lower, e.g. kg < 4x10  day  ,
in sites  not previously exposed to naphthalene.

     Since  naphthalene  is a growth substrate, estimating the adaptation time
in the Lepidoptera River is a primary  issue.  Because the point source
continuously discharges naphthalene  into the Lepidoptera River, it  is safe
to assume that  the bacterial populations have adapted.

     In  a complete  analysis, the  user  would check  whether the  oxygen is
depleted  from  the  river.   If so,  degradation could  be  neglected  until
dissolved oxygen  levels  exceed  1.0 mg/1  again.
                                    122

-------
     Sorption by suspended sediment could potentially reduce the rate at
which naphthalene biodeqrades.  Table II-9 gives a K   for naphthalene of
                                                    ow
2,300.  Using Equations 11-17 and 11-19 and assuming a suspended sediment
organic carbon content of 2 percent, the partition coefficient is:
                     K  = (.02) (.63) (2,300) = 29
                      P
At the suspended sediment levels in the Lepidoptera River 10 mg/1, Table
11-14 shows that sorption will not significantly reduce water column
concentrations of naphthalene.  Although phosphorus levels are low, assume
carbon is the growth-limiting substrate.

     Finally, the degradation rate is adjusted to the river water
temperature using Equation 11-61.

                                    (10-12)           -1
                   k  = 0.14  • 1.072  '      = 0.12 day
                            END OF EXAMPLE 11-6
                                       123

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2.5.2  Photolysis

2.5.2.1  Introduction

     The sun provides the aquatic environment with a large supply of energy.
Substances which absorb sunlight transform much of its radiant energy into
thermal energy.  But, molecules which absorb sunlight in the ultraviolet and
visible portion of the spectrum may gain sufficient energy to initiate a
chemical reaction.  Plants use very specific photochemical reactions to
provide energy for the synthesis of sugar from carbon dioxide.  In other
photochemical reactions, the absorption of light leads to the decomposition
of a molecule.  The latter type of reaction, known as photolysis, strongly
influences the fate of certain pollutants in the aquatic environment.

     Photolysis  is truly a pollutant decay process since it irreversibly
alters the reacting molecule.  However, the products of the photochemical
decomposition of a toxic compound may still be toxic.  For example,
irradiated 2,4-D esters form 2,4-D acid, a priority pollutant, in aerated
waters  (lepp et _al_., 1975).  Upon irradiation, DDT reacts to form DDE, which
persists  in the  environment  longer than DDT (Tinsley, 1979).  Thus,  even
though  the methods in this section assume that pollutants irreversibly decay
through photolysis, the planner should remember that the decomposition of  a
pollutant does not imply the detoxification of the environment.

     The  rate  at which  a pollutant photolyzes depends on numerous chemical
and  environmental factors.   The light absorption properties and reactivity
of a compound, the light transmission characteristics of natural waters,  and
the  intensity  of solar  radiation  are some of the most important factors
influencing environmental  photolysis.  These factors will be  covered by  the
following discussion.   Understanding these factors facilitates the
computation of rate  constants  and the  identification of  pollutants  likely to
photolyze - the  final  two  topics  of  this  section.
                                    124

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2.5.2.2  Factors Influencing Photolysis in the Aquatic Environment

2.5.2.2.1  Photochemical Reactions

     All chemical reactions which occur at finite rates require the reacting
molecule to gain sufficient energy to become "activated" or form a reactive
intermediate.  In dark or thermal reactions, the thermal energy of the
environment supplies the activation energy.  In photochemical reactions, the
absorption of light provides the activation energy.

     The "activated" molecules in photochemical reactions differ in
important respects from those of thermal reactions.  Thermally activated
molecules usually remain in the normal or "ground" electronic energy state,
whereas photochemically activated molecules exist in higher, "excited"
electronic states.  Because of the excess energy and the alteration of the
chemical bonds of photoactivated molecules, the range of potential reaction
products is much greater than that for thermally activated molecules.

     The mechanism by which photoactivated molecules form and react is
divided into three steps:  1) the absorption of light to produce an
electronically excited molecule, 2) the "primary photochemical processes"
which transform  or deexcite the excited molecule, and 3) the secondary or
"dark" thermal reactions which the intermediates produced in step 2 undergo
(Turro, 1978).

     The mechanism of photochemical reactions provides a convenient structure
for a discussion of the factors which  influence photolysis  in the aquatic
environment.  Environmental factors affecting the absorption of light, step
1, will be considered first.  Then, the factors influencing the fate of
molecules which  become excited by the  absorption of  light,  steps 2 and 3,
are discussed.
                                   125

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2.5.2.2.2  Light Absorption

          "Only that light which is absorbed by a system can produce
     chemical changes  (Grotthaus-Draper Law)."   (Glasstone, 1946)

     As this "first law of photochemistry" implies,  it is necessary to know
the rate at which reacting molecules absorb light in order to determine the
rate of a photochemical reaction in the environment.  The following factors
which influence light absorption in the aquatic environment are discussed
here:  1) molecular absorption of light, 2) solar radiation, and 3) light
attenuation in natural waters.
2.5.2.2.2.1  Molecular Absorption of Light

     Both light and molecules have quantized energies.  Light interacts with
matter as quanta with energies inversely proportional  to their wavelengths.  A
molecule has quantized internal energy states associated with the
configuration of its electrons and the rotation and vibration of its
chemical bonds.  Since a molecule can absorb light only as a whole photon,
light absorption is possible only if the energy of the photon corresponds to
the energy change of an allowed transition between the molecule's internal
energy states.  Consequently, the probability of a photon being absorbed
varies strongly with wavelength of the light in a way that is unique to
every chemical species.

     To  initiate a chemical reaction, the absorbed light must be
sufficiently energetic to cause a change in the absorbing molecule's
electronic structure.  Generally, radiation with wavelengths in the
ultraviolet-visible range, or shorter, has sufficient energy to initiate
photochemical reactions while radiation with wavelengths in the infrared
range, or longer, does not.  Thus, the ultraviolet-visible light absorption
properties of a chemical are of primary interest in photochemistry.
                                  126

-------
     Photochemical reactions in the aquatic environmental depend on the rate
at which molecules in aqueous solution absorb light.  According to Beer's
Law, the rate of light absorption by a single compound (I )  in a
                                                         a
cross-section of solution with infinitesimal thickness (Az)  is proportional
to the concentration of the light absorbing species(C), i.e.:

                    I (z) = I(z) •  2.3 •  c • C •  Az                   (11-64)
                     a

where  I (z) is the intensity of the light at a depth z in the solution and e
is the base 10 molar extinction coefficient,  e reflects the probability of
the light being absorbed by the dissolved molecules and therefore varies
with the wavelength of the incident light as shown in Figure 11-10.
Absorption spectra, such as shown here, contain information necessary to
compute the rate at which pollutants absorb radiation available in the
environment.
2.5.2.2.2.2  Solar Radiation

     The only radiant energy available for absorption by pollutants in the
aquatic environment comes from the sun.  The sun emits radiation of nearly
constant intensity and spectral distribution.  But, gases and particles in
the earth's atmosphere alter the incoming solar radiation through scattering
and absorption.  Scattering of the direct solar beam creates the diffuse or
sky radiation visible at the earth's surface.  Absorption of both diffuse
and direct radiation reduces the intensity of solar radiation reaching the
earth.  Since the strength of absorption and scattering depends strongly on
the wavelength of the light involved, the interaction of sunlight with the
atmosphere alters the spectral distribution of solar radiation as well, as
Figure 11-11 shows.

     The composition of the earth's atmosphere and the geometrical
relationship of the sun and earth change over time causing the solar
radiation  incident upon the earth's surface to vary as well.  A comparison
of the total solar irradiance under clear skies at various times, seasons,
and latitudes (Table 11-25) to the extra-atmospheric solar flux of
2800 langleys/day demonstrates the effects of changes in earth-sun geometry.
                                   127

-------
ULTRAVIOLET ABSORPTION SPECTRUM OF NAPHTHACENE
      106 r
        182     200
 250         300
Wavelength (nm)
400
500
Source: U.V.  Atlas of Organic Compounds.
   FIGURE 11-10    ULTRAVIOLET ABSORPTION SPECTRUM  OF NAPHTHACENE
                                 128

-------
>O —I
                              I—I  I  I—I—I  I—I
                                   1500        2000
                                          a) Spectral distribution of sun's
                                             radiation at edge of outer
                                             atmosphere

                                          b) Spectral distribution of sun's
                                             radiation at earth's surface
                             Wavelength (nm)


    Sources:  (a) Weast and Astle (1980); (b) Moon  (1940).


   FIGURE 11-11   SPECTRAL DISTRIBUTION  OF  SOLAR ENERGY
                    (A)  OUTSIDE THE  EARTH'S ATMOSPHERE,  AND
                    (B)  AT  THE EARTH'S  SURFACE
                                 129

-------
                                                          Table  11-25

                         CALCULATED  SOLAR RADIANT ENERGY FLUX TO A HORIZONTAL SURFACE UNDER A CLEAR SKY
                                                         (langleys/day)
CO
o
Latitude
30°N
40°N
50°N
Time
Of Day
Mean1^
Mid-Day^'
Mean
Mid -Day
Mean
Mid- Day
Spring
680
2100
650
1900
590
1700
Season
Summer
750
2200
740
2100
710
1900
Fall
530
1700
440
1400
330
1000
Winter
440
1400
320
1000
190
650
Annual
Mean
600
1900
540
1600
460
1300
                        1)   Mean  values  represent calculated seasonal means under a clear sky.  These
                            should  represent upper limits for solar radiant energy at sea level.
                            Reference:   Weast and Astle (1980).

                        2)   Mid-Day values represent mid-day flux extended over a 24-hour period.  These
                            assume  an atmospheric turbidity of 0, precipitable water content of 2 cm,
                            and an  atmospheric ozone content of .34 cm NTP.  Reference:  Robinson (1966).

-------
The composition of the atmosphere differs greatly from place to place and is
the most difficult of the factors influencing the total solar flux to
accurately quantify.  Historical records of the solar radiation, such as
shown in Figure 11-12, are the best way to estimate the mean solar energy
flux at a given locale.  However, care should be taken to account for the
influence of riparian vegetation on incoming radiation.  Section 4.4.3
discusses how to approximate the affects of shading.

     Information concerning the variability of the spectral distribution of
solar energy incident upon the earth's surface is not as readily available.
It is known that the  fraction of the solar energy in the ultraviolet region
decreases with increased attenuation of light by the atmosphere.  The
fraction of the energy which is visible remains relatively constant.  For
the purpose of this document, it is sufficiently accurate to assume that the
reduction in UV-visible radiation is proportional to the reduction in the
total flux.
2.5.2.2.2.3  Light Attenuation  in Natural Waters

     Just as the earth's atmosphere reduces the intensity of solar radiation
reaching the earth's surface, natural waters reduce the intensity of
radiation available for absorption by aquatic pollutants.  The first process
which reduces the availability of light in the water column is reflection.
The surface of the water reflects less than 10 percent of solar radiation in
most cases (Zepp and Cline, 1977).  Reflection also alters the solar
spectrum slightly.  A calculated spectral distribution of solar radiation,
expressed in photons, immediately below the surface of a water body is
presented in Table 11-26.

     As solar radiation penetrates deeper into natural waters, it is
absorbed and scattered by particulates, dissolved substances, and water
itself.  Measurements of light attenuation in natural waters have been based
on the decrease of solar irradiance, which includes both collimated and
scattered light.  Lambert's Law expresses the decrease in the irradiance,
I(z), i.e. the total flux incident upon dn element of surface divided by its
area, with depth, z, as follows:
                                     131

-------
OJ
ro
                                     EAN DAILY SOLAR RADIATION  (Langleys),  ANNUA
                                                                                    Ref:  US Dept. Comm.  (1963)
                             FIGURE 11-12    SOLAR  RADIATION IN THE  UNITED STATES

-------
                              Table 11-26

          CALCULATED SOLAR IRRADIANCE IN A WATER BODY JUST BENEATH
                      THE SURFACE, ANNUAL MEAN AT 40°N
Wavelength
(nm)
300
310
320
330
340
350
360
370
380
390
400
410
420
430
440
450
460
470
480
490
500
510
520
550
600
650
700
750
800
Photon Spectral
W(X)C
(10 photons cm" secern1)
,00303
.0388
.113
.181
.211
.226
.241
.268
.294
.366
.526
.692
.712
.688
.814
.917
.927
.959
.983
.930
.949
.962
1.00
1.04
1.07
1.08
1.07
1.03
.988
Irradiance
W!(X)d
14 9ii
(10 photons cm sec!X nm1)
.0303
.388
1.13
1.81
2.11
2.26
2.41
2.68
2.94
3.66
5.26
6.92
7.12
6.88
8.14
9.17
9.27
9.59
9.83
9.30
9.49
9.6?
10.0
52.0
53.5
54.0
53.6
51.5
49.4
 Estimated reference solar flux, I  = 540 langleys/day. D  =1.0

 Centric wavelength of waveband X nm in width,
 for 300 
-------
                          -   d~= K '  I(z)                         (11-65)

where K is the diffuse light attenuation coefficient.  The diffuse
attenuation coefficient can be expressed as a sum of terms accounting for
absorption, a, and backward scattering of light, s  (Smith and Tyler, 1976):
                                                  b
                              K = Da + s                             (11-66)
                                        b
where D is the radiance distribution function.  Usually, s  is small
                                                          b
compared to the absorption term.  The absorption term constitues part of the
beam attenuation coefficient, a, which can be measured in a
spectrophotometer:

                          a = a + s  + s                             (11-67)
                                   b    f

where s  is the forward scattering coefficient of the solution.

     The inclusion of the distribution function, D, in Equation (11-66)
accounts for the difference in mean light pathlength of collimated and
diffuse light.  Perfectly diffuse light has a mean path through an element
of water which is twice as long as that of a beam of light.  The
distribution function, generally increases asymptotically with depth due to
the increasing fraction of the total light which is scattered.  In water
bodies where scattering can be ignored, D has a value of 1.2.  Miller and
Zepp (1979) reported that the mean value of D for six sediment laden waters
was 1.6.

     The diffuse light attenuation coefficient of natural waters differs
greatly due to variations in the types and amounts of particles and
dissolved substances in the water.  Miller and Zepp (1979), Zepp and
Schlotzhauer (1981),  and Smith and Baker (1978) have investigated the
contributions of suspended sediments, dissolved organic carbon, and
chlorophyll pigments to the light attenuation coefficient.  By using
Equation (11-66) to integrate the results of these investigations, and
assuming backscattering to be negligible, Burns ert _al_.  (1981) derived the
following expression to estimate the diffuse light attenuation coefficient:
                                    134

-------
   K = D
                                                     (11-68)
where a
       w
      a
      cfil a
      aDOC
      DOC
a  + (a  •  chl a) + (a    •  DOC) + (a   •  SS'
 w     a       -      DOC            ss
absorptivity of water
absorptivity of chlorophyl1-a pigment
concentration of chlorophyll-^, pigment
absorptivity of dissolved organic carbon
concentration of dissolved organic carbon
absorptivity of suspended sediments
concentration of suspended sediments
Each absorptivity term varies with the wavelength of light, as shown in
Table 11-27.

     Diffuse light attenuation coefficients can also be estimated using
turbidity indicators such as Secchi disc depth.  Empirical studies have
shown that the diffuse light attenuation coefficient is inversely
proportional to the Secchi disc depth, Z
                                        sd
                                K =
                                  _  R
                                    "sd
                                                     (11-69)
The proportionality constant, R, has a value between 1.44 and 1.7 for
visible light, i.e. 400-800 nm.  In the middle ultraviolet portion of the
spectrum, i.e. near 312 nm, R has a value of 9.15 (Zepp, 1980).
2.5.2.2.3  Fate of Excited Molecules

          "Each molecule taking part in a chemical reaction which is a
     direct result of the absorption of light takes up one quantum of
     radiation (Stark-Einstein Law)."   (Glasstone, 1946)

     According to this "second law of photochemistry", the extent to which a
photochemical reaction progresses depends on the number of quanta of light
absorbed.  Each absorbed photon produces an electronically excited molecule
which can undergo numerous processes, including reaction.  Factors which
influence the fraction of excited molecules which undergo reaction,  called
                                  135

-------
                      Table 11-27

     CONTRIBUTIONS TO LIGHT ATTENUATION COEFFICIENT
Waveband
Center
(nm)
300
310
320
330
340
350
360
370
380
390
400
410
420
430
440
450
460
470
480
490
500
510
520
550
600
650
700
750
800
Notes:


a a
w
(m-1)
.141
.105
.0844
.0678
.0561
.0463
.0379
.0300
.0220
.0191
.0171
.0162
.0153
.0144
.0145
.0145
.0156
.0156
.0176
.0196
.0257
.0357
.0477
.0638
.244
.349
.650
2.47
2.07

? Source: Smith and
Source: Smith and
ab
a
[(mg/i)"1
69.*
67.*
63.*
61'*
58.*
55.
55.
51.
46.
42.
41.
39.
38.
35.
32.
31.
28.
26.
24.
22.
20.
18.
16.
10.
6.
8.
3.
2.
0.

Baker (1981)
Baker (1978)
a c
aDOC
m'1] [(mg/1)-1 nT1
6.25
5.41
4.68
4.05
3.50
3.03
2.62
2.26
1.96
1.69
1.47
1.27
1.10
0.949
0.821
0.710
0.614
0.531
0.460
0.398
0.344
0.297
0.257
0.167
0.081
-
-
-
~


Calculated using
a d
ass
] [(mg/1)-1 m-1]
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35
.35


aa = K2/D,
   D = 1.2
  cSource:  Zepp and Schlotzhauer (1981)
  dSource:  Miller and Zepp (1979).   Calculated using ass = KS/D.

Denotes extrapolated values.
                          136

-------
the quantum yield, comes first in the following discussion of the fate of
excited molecules.  Then, the two major classes of enviromental photolysis
reactions, direct and sensitized, are discussed.
2.5.2.2.3.1  The Quantum Yield

     Although all photochemical reactions are initiated by the absorption of
a photon, not every absorbed photon induces a chemical reaction.  Besides
chemical reactions, possible processes which excited molecules may undergo
include the reemission of light through flourescence and phosphorescence,
the internal conversion of the photons' energy into heat, and the excitation
of other molecules, as shown in Figure 11-13.  The fraction of absorbed
photons which cause the desired reaction(s) is termed the quantum yield, $:

                 moles  of  a  given  species  formed  or  destroyed
            <|>  =   	          (11-70)
                 moles  of  photons  absorbed by the system

     The quantum yields for photochemical reactions in the solution phase
exhibit two properties which greatly simplify their use:

     •   The quantum yield  is  less than or equal  to one.

     t   The quantum yield  is  independent of the wavelength of the
         absorbed photons.

Although exceptions to these rules exist, they are  rare for photochemical
reactions  in the aquatic  environment.

     Environmental conditions  influence photolysis  quantum yields.
Molecular  oxygen acts  as  a  quenching agent (see  Figure 11-13) in some
photochemical reactions,  reducing the  quantum yields  (Wolfe ei aj_., 1978).
In other cases,  it has no effect  or may even be  a reactant.   In any case,
rate constant and quantum yield measurements should be performed in water
with oxygen concentrations  representative of environmental conditions.
                                   137

-------
PHOTOCHEMICAL PATHWAYS OF AN EXCITED MOLECULE
                                 A0 + heat
                        Internal
                      conversion
                 hv
                 MHHi
               Absorption
                                       A. + hi»'
                                        0
      Flourescence


  Intersystem crossing

.Quenching
                    Chemical reaction
                                      Chemical reaction
                             AQ — ground state of reactant molecule
                             A* — excited state
                            QQ — ground state of quenching molecule
                            Q* — excited state
     FIGURE  11-13
PHOTOCHEMICAL  PATHWAYS  OF  AN  EXCITED
MOLECULE,    EXCITED MOLECULES  DO  NOT
ALWAYS CHEMICALLY  REACT,
                                     138

-------
     Suspended sediments also influence rates of photolysis.  Not only do
suspended sediments increase light attenuation, but they change the
reactivity of compounds sorbed on them (Miller and Zepp, 1979).  Sorption
may either increase or decrease a compound's reactivity depending on the
reaction it undergoes.  This effect, however, is of secondary importance in
comparison to the increase in light attenuation by the suspended sediments
(Burns et a/L, 1981).  Thus, the effects of sorption will be neglected.

     Chemical speciation also effects rates of photolysis.  Different forms
of an organic acid or base may have different quantum yields, as well as
absorptivities, causing the apparent photolysis rate of the compound to vary
with pH.  The possibility of this should be kept in mind when the pK  of a
                                                                    a
photolyzing compound is 7 _+ 2.  Except where stated otherwise, data
contained herein may be assumed independent of pH over the range of values
observed in natural waters.

     Photochemicaly initiated reactions may show a temperature effect
depending upon the actual mechanisms involved.  General methods for
predicting this effect have yet to be developed.  Users of this screening
manual should assume thermal effects on photolysis to be negligible.

     Quantum yields vary over several orders of magnitude depending on the
nature of the molecule which absorbs light and the nature of the reactions
it undergoes.  The two major classes of photochemical reactions of interest
in the aquatic environment are direct and sensitized photolysis.  A closer
examination of each reaction type follows.
2.5.2.2.3.2  Direct Photolysis

     Direct photolysis occurs when the reacting molecule itself directly
absorbs light.  The excited molecule can undergo various types of reactions,
including fragmentation, reduction, oxidation, hydrolysis, acid-base
reaction, addition, substitution, isomerization, polymerization, etc.
Figure 11-14 shows examples of the reactions undergone by three toxic
substances which directly photolyze.
                                    139

-------
a)
                                            OCH2COR
                            Cl
                                          OCH2COR
b)
                               Sunlight
                                                 +  R - C
c)
Cl          H
 Sunlight
                                       Cl
                               Cl
Cl
 FIGURE
DIRECT  PHOTOCHEMICAL REACTIONS  OF (A) 2,4-D ESTER,
(B) BENZ(A)ANTHRACENE, AND  (c)  PENTACHLOROPHENOL,
                                  140

-------
      The  quantum yield  for  the  direct  photolysis,    ,  of  a  compound  is  a
                                                   d
 constant  defined as  follows:
— 1
 dt/
                            d    dt    ad
where  C  is  the  concentration  of the compound  and  I    is  the rate  at which
                                                   ad
the  compound  absorbs  light.   Table 11-28  lists several disappearance quantum
yields  for  direct  photolysis  of aquatic pollutants.

     By  comparing  molecular absorption  spectra with the  spectral
distribution  of sunlight,  it  is possible  to determine whether or  not a
compound may  directly photolyze.  Benzene, as shown in Figure II-15a, does
not  directly  photolyze because it does  not absorb  light  above 275 nm.
Naphthacene,  shown in Figure  II-15b, does directly photolyze because of  its
strong absorptivity in the  sunlight region of the  spectrum.  Humic acids,
Figure II-15c,  by  virtue of their absorption  of sunlight may initiate
indirect, or  sensitized, photochemical  reactions.
2.5.2.2.3.3  Sensitized Photolysis

     Sunlight can cause the degradation of aquatic pollutants by means other
than direct photolysis.  A light-absorbing molecule can transfer its excess
energy to  an acceptor molecule causing the acceptor to react as if it had
absorbed the radiant energy directly.  This reaction mechanism, known as
photosensitization, contributes to the degradation of aquatic pollutants
when suitable light absorbing substances, or photosensitizers, are present.
2,5-Dimethylfuran is an example of a compound which degrades by sensitized
photolysis.  It does not react when exposed to sunlight in distilled water
but degrades rapidly in waters containing natural humic acids (Zepp ejtal.,
1981a).

     Numerous substances,  including humic acids, titanium dioxide,  and
synthetic organic compounds,  can sensitize photochemical reactions.  But,
most potential sensitizers occur  at such low environmental concentrations
that they have negligible effects on photolysis rates.  Humic acids,  the
naturally occurring by-products of plant matter decay, frequently attain
                                 141

-------
                              Table 11-28
         DISAPPEARANCE QUANTUM YIELDS, d  FOR DIRECT  PHOTOLYSIS
Compound
Polycyclic Aromatic Hydrocarbons
Naphthalene
1-Methyl naphthalene
2-Methyl naphthalene
Phenanthrene
Anthracene
9-Methyl anthracene
9, 10-Dimethyl anthracene
Pyrene
Fluoranthrene

Chrysene
Naphthacene
Benz(a)anthracene
Benz(a)pyrene
2,4-D Esters
Butoxyethyl ester
Methyl ester
Carbaryl
N-Nitrosoatrazine
Trifluralin
DMDE
(jjj Reference

.015
.018
.0053
.010
.0030
.0075
.0040
.0021
(313 nm) .00012
(366 nm) .000002
.0028
.013
.0033
.00089

.056
.031
.0055
.30
.0020
.30

a
a
a
a
a
a
a
a
a
a
a
a
a
a

b
b
c
d
d
d
References:
  aZepp and Schlotzhauer (1979)
  bZepp et al_. (1975)
  Slolfe et al_. (1978)
  dZepp and Cline (1977)
                                   142

-------
CO
           fD
           -S
           n>
           3
           O
           ro
00 to CO
O T3 C
3- fD 3
3  O —i

c-t- "S U3
N  CU 3-
fD »   r+
-s
      : en
       -o
      : fD
10 •   n
    fa »
    (/)
       CO
    o c
    -h -S
       3
    o 

   kjQ jfD
    0)|t-t-

    _i.| Cu
    O |—i

    O
    o -~-
    3 i—
   "O to
    O OD
           CO
           fD
       rc  3
       C  N
       3  ro
       — '•  3
       O  fD

       CD  QJ
       O  3
       _i.  Q.
       Q.
           3
       CO  O)
      -O -O
       fD  3-
       O  rt
          o
          ro
          3
          fD
                                      extinction coefficient  (cm-1 gC//l"
                                                                                        S      8
                                     Solar  Irradiance  (photons/sec'nmt
                  o
                  o

                  m
X   ~T3   O
a:   in   o
•—02
o   -H   TJ
:E   o   o
                       z  N
                       •—  m
                       —I  v
                                           O
                                           m
                                           o
                 o
                 3:
                 T3
                  O   •—
                 m

                 o
                 —l
                 i—i
                 o

                 CO
H   Z   O
m   o   n:


—   no
z   v_x  m
O        V)

33        O
m   co   «—i
O   C=   33
H   td   m
      co   o
                            o
                            m
r~   o   z:   -*
-<   o   m   co
      2:         o
-o   T>   3=-  2
n:   o   co
o   c:   co   o
H   z   o   -n
O   O   33
r~        -o   GO
-<   s:   H   o
N   :r   •—   r~
m   i—i   o   J>


s~^        GO  •—i
CO   O   ~D   33
v~-x   O   m   33
      m   o   >
>   CO   H   C3
                           o   n
                           ~n   m
CD
c
33
m
                                                                                                                                      e, molar extinction coefficient   (cm~'(mole/£)~t)
                                                                                                                                                                                                CO
                                                                                                                                                                                                c
                                                                                                                                       Solar Irradiance  photon s/sec/nm
                                                                                                                                      (, molar extinction coefficient
                                                                                                                                       Solar Irradiance  tphotons/sec/nm)

-------
concentrations of  1-10 mg as carbon per  liter  in  natural systems.  Humic
acids  strongly absorb sunlight with wavelengths shorter than 500 nm,
as  the absorption  coefficients for dissolved organic  carbon, aDQC> in
Table  11-27  indicate.

     The quantum yield for photosensitized reactions,    ,  is defined  in a
manner similar to the quantum yield for direct photolysis:

                                                                   (H-72)

where C is the concentration of the pollutant and I   is the rate of  light
                                                   as
absorption by the sensitizing molecule.  The quantum yield for sensitized
photolysis, however, is  not constant but depends on the pollutant
concentration, such that:

                               4>   = Qs" C                          (11-73)

where Q is a constant.  This is due to the fact that the probability of the
sensitized molecule donating its  energy to a pollutant molecule is
proportional to the concentration of the pollutant molecule.  Published
values of Q are very rare.  Zepp e_t cfl_. (1981b)   report a Q of 19
(mol/1)    for the photosensitized ozidation of 2,5-dimethylfuran.
2.5.2.3  Computing Environmental Photolysis Rates

     The overall rate at which a pollutant photolyzes in the aquatic
environment is the sum of the rates of direct and sensitized photochemical
reactions.  At the low pollutant concentrations observed in the environment,
the rates of both direct and sensitized photolysis are proportional to the
concentration of the pollutant.  Thus, photolysis follows a first-order
rate law:

                            — = -k  • C                            (11-74)
                            dt     P

where
                                   144

-------
     k' = overall photolysis rate constant, day

        = k  + k
           d    s

     k  = direct photolysis rate constant, day
      d

     k  = sensitized photolysis rate constant, day

Due to the complexity of the units for the parameters in the photolysis
section, it is essential that the user employ the specified units in each
equation.  All resulting first-order photolysis rate constants have units of
day  .

     The determination of rate constants for direct and sensitized
photolysis is the subject of the remainder of this section.
Section 2.5.2.3.1 includes a derivation of the equations for k  and k .
Sections 2.5.2.3.2 and 2.5.2.3.3 describe how to calculate these constants
on the basis of near surface rate constants or molecular absorption spectra.
2.5.2.3.1  Derivation of Rate Constant Equations

2.5.2.3.1.1  Direct Photolysis

     The rate at which a compound directly photolyzes is proportional to the
rate at which it absorbs light.  The rate of light absorption by a dissolved
substance in natural waters is (Miller & Zepp, 1979):

                   \
                 J   2.3-j-e(X) • C(z) • D(z)- W(X) -e'K(A) "z dAdz    (H-75)
where
                                               -1    -1
     I   = rate of light absorption, einstein 1   day
      ad
                                        145

-------
     Z   =  mixed  depth  of  water  body, m
     A   =  500  nm
     1

     A   £300  nm
     o
                                       -16        3      -1    -1
     j   =  conversion  factor  =  1.43  x  10   mole-cm  -sec-l   -day
        = base 10 molar extinction  coefficient of  pollutant,
          1  mol   cm
     C  = concentration of pollutant,  mol/1

     D  = radiance distribution  function

                                                        -2    -1   -1
     W  = photon irradiance near the surface,  photons  cm sec nm

     K  = diffuse light attenuation  coefficient  of  the water, m

     The expression for the direct photolysis  rate  constant,  which  can  be
derived from Equations (11-71),  (11-74),  and (11-75)  is:
                                     r         i P'K'Z
                 k.  =  2.3-j-i. -D'/   e-W-ll*	 . dA          (11-76)
                                    /           K-Z
Equation (11-76) incorporates the assumption that C,  K,  and D are
independent of depth.  Thus, it will overpredict photolysis rates if the
pollutant is not distributed evenly throughout the water column.
                                      146

-------
2.5.2.3.1.2  Sensitized Photolysis



     The rate at which a compound decays through sensitized photolysis is

proportional to the rate at which sensitizing molecules absorb light.  The

rate at which sensitizers absorb light in the aquatic environment is:

             Z   X

         1  r   r                                                    (H-77)
   las = IJ   J    J • a  U) • C  (z) • D(z) • W(X) • e "
                                              dAdz
         b        b
A.
                0

where



     I   = rate of light absorption by sensitizers, einstein 1  day
      clS


     a  = base e absorption coefficient of the sensitizer,
      s                _i   _i
          e.g. 1 mg-DOC   cm



     C  = concentration of sensitizer, e.g. mg-DOC/1



     The rate constant for sensitized photolysis of a compound, k ,  is then:
                                                                 s


                                    Al

             ks   =  J'-Cs  '  D  '  Qs'  /  as ' w • ]  "  e      -dA         (n

                                   A            K*Z
                                    o

Equation (11-78) includes the assumptions that GS, K,  and D are independent of
depth and that Q is independent of wavelength
2.5.23.2  Use of Near Surface Rate Constants



     Experimental data for direct photolysis are generally reported as near

surface rate constants, as in Table 11-29.  Near the surface of a water body

(K-z <0.2), the mean irradiance is approximately equal to the surface

irradiance.  This fact permits Equation (11-76) to be simplified to the

following expression which defines the near surface rate constant, k  :
                                                                    do
                                  147

-------
                 Table 11-29



NEAR-SURFACE DIRECT PHOTOLYSIS  RATE  CONSTANTS





























Compound
Polycyclic Aromatic Hydrocarbons
Naphthalene
1 -Methyl naphthalene
2-Methylnaphthalene
Phenanthrene
Anthracene
9-Methyl anthracene
9, 10-Dimethylanthracene
Pyrene
Fluoranthrene
Chrysene
Naphthacene
Benzo(a)pyrene
Benzo( a)anthracene
Carbamate Pesticides
Carbaryl
Propham
Chlorpropham
Phthlate Esters
dimethyl ester
diethyl ester
di-n-butyl ester
di-n-octyl ester
di-(2-ethylhexyl) ester
2,4-D Esters
butoxyethyl ester
methyl ester
Hexachl orocycl opentadi ene
Pentachlorophenol (anion)
3,3 '-dichlorobenzi dine
N-ni trosoatrazine
Trifluralin
DMDE(l,l-bis(p-methylphenyl 1)-
2,2-dichloroethylene)
k l} 2) *3)
do , I i] \
1 °
(day" ) (lanqleys/day) (no) Ref.
9
.23
.76
.31
2.0
22.0
130.0
48.0
24.0
.79
3.8
490.0
31.0
28.0
.32
<.003
<.006
5x10"'
5x10" 3
5x10" '
5xlO"3
5xlO"3
.050
.030
94.
.46
670.
300.
30.
17.
2100
2100
2100
2100
2100
2100
2100
2100
2100
2100
2100
2100
2100
2100
740
740
600
600
600
600
600
420
420
540
600
2000
1800
1800
2200
310 a
312 a
320 a
323 a
360 a
380 &
400 a
330 a
a
320 a
440 a
380 a
340 a
313 b
c
c
d
d
d
d
d
e
e
f
318* f
280-330* f
9
g
g
References:
Notes:
1)
2)
3)
*



Parenthetic comments after name of compound indicate when the form
of the compound undergoing photolysis is something other than the
neutral form.
Estimated Solar Flux - usually high estimates to
photolysis rates.
Wavelength of maximum sunlight absorption.
Indicates the maximum of the absorption spectrum
give conservative

is used.



a) Zepp and Schlotzhauer (1979)
b) Zepp (1978)
c) Wolfe et al_. (1978)
d) Wolfe et a\_. (1980)
e) Zepp et al_. (1979)
f) Callahan e_t aj_. (1979)
g) Zepp and Cline (1977)
                    148

-------
kdo
                                              l
                                    o '  j 'f   e • W * dA           (H-79)
                                           A
                                            0
where

     k   = near-surface direct photolysis rate constant, day
      do

     D   = radiance distribution near the surface (approximate value =
      °   1.2)

     According to Equation  (11-79), the near surface rate constant is
independent of the properties of the water it is measured in, except for the
small variation in D  .  Thus, when the difference in solar irradiance
                    o
between the experimental and environmental conditions is accounted for, the
user can apply a near surface rate constant to other bodies of water using
the following expression:
                  k   -  k    l      D
                   d  "   do'     '
where

     I  = total solar radiation (langleys/day)

     I  = total solar radiation under conditions at which k   was
      o                                                    do
          measured (langleys/day)

     A* = wavelength of maximum light absorption, i.e. wavelength where
          the product e(A)-w(A) is greatest.

     This approximate expression is valid if the following assumptions are
sufficiently accurate:  1) the solar irradiance at a wavelength is a
constant fraction of the total solar irradiance (Park ^t jfL , 1980) and
2) the light attenuation coefficient, K, is constant over the range of
wavelength that the compound absorbs solar radiation at high rates
(Burns et a!., 1981).
                                        149

-------
     Although it is possible to derive a similar expression for sensitized
photolysis, variation in the absorptivity and reactivity of natural  humic
substances make extrapolations based on the concentration of dissolved
organic carbon subject to large errors.  An approach taken by Zepp (1980)
was to correlate the sensitized photolysis rate constant with the absorbance
of a solution at 366nm.  Such an empirical relationship was found for
2,5-dimethylfuran:

                    log k   = .671og a    - 1.15                     (11-81)
                      y  so           366

where
     a      = absorbance of solution at 366nm
      366
     k     = near surface rate constant, day  cm   (I =1 langley/day).
      so                                             o

At present, data on sensitized photolysis are difficult to obtain.  The
planner should be aware of its potential significance even if it is not
possible to estimate rates at this time.
2.5.2.3.3  Evaluation of Rate Constant Integrals

     When both the absorption spectrum, e(A) or a (A), and the quantum
yields,    or Q  , are available, it is possible to evaluate the integrals in
         d     s
Equations 11-76  and  11-78 numerically, as shown below:
                                        s . r -  ts                  (n-83)
                                     i
 where
      i   =  index  of  wavelength  interval
      W  =  W •  AX
                                           150

-------
     The user may obtain information necessary to evauate these expressions
from the following sources:

     •   W - Table 11-26.

     t   K  - Equation (11-68) and Table 11-27 or Equation (11-69).

     •   D  - Assign a value between 1.2 and 2 as follows:  1.2 for
              very clear waters, 1.6 for typical rivers, 2 for
              extremely turbid waters.

     •    e - Spectroscopy reference works, e.g. Stadler  U.V.  Spectra
              or U.V. Atlas of Organic Compounds.

     •     - Literature or Table 11-28.
          d

     •   a  - For reactions sensitized by humic acids, use an_- in
          s
              Table 11-27.
     •   Q  - Literature (rarely available).
                               EXAMPLE II-7
                  Computation of Photolysis Rate Constants

     Compute the mean annual photolysis rate constant for the pesticide
carbaryl in a hypothetical river near Fresno, California.  Use both the
evaluation of integral and near surface rate constant methods described
above.  Assume the following physical and chemical parameters apply to the
river:

          Mean Depth = 2 m
          Suspended Sediments - 10 mg/1
          Humic Acid = 2 mg-DOC/1
          Chlorophyll j. = 0 mg/1
                                    151

-------
     Zepp (1978) reported a quantum yield,  ,,  of .0060 and the following
absorptivities, e, for carbaryl :

    Wavelength (nm)                          Absorptivity (M  cm  ) __
         300                                           918
         310                                           356
         320                                           101
         330                                            11

A.  Near Surface Rate Constant Method

     Table 11-29 contains the following information regarding carbaryl:

                         k  = .32 day
                          d
                         I  = 2100 langleys/day
                         ^ = 313 nm

     According to Figure 11-12, the mean annual solar irradiance at Fresno,
California is 450 langleys/day.

     Assume that the radiance distribution function under reference, D  ,
                                                                      o
and environmental, D, conditions have values of 1.2 and 1.6 respectively.

     To  calculate the light attenuation coefficient at the wavelength of
maximum  light  absorption, 313 nm, we use Equation  (11-68) and the data  in
Table  11-27,  at 310 nm;

         K =  1.6  (.105 + 67«0 + 5.41 • 2 +  .35  • 10) = 23.1m"

     When the water absorbs nearly  all of the  incident radiation,  i.e.  kZ >_
3,  the following  approximation is valid:
                            i    Q-KZ    i
                            1 - e    %  1
                               KZ    % KZ

 This  approximation  can  be  applied  to  Equation  (11-80)  and  Equation  (11-82).
 It  both  simplifies  the  calculations  and  eliminates  the dependence of  the
 rate  constant  on  the  radiance  distribution  function,  D,  in cases where  the
                                    152

-------
 light  attenuation  coefficient is  calculated from D, as in this example.  In
 such  a case,  the  user's  choice of a value of D does not affect the result.

      Using  this approximation in  Equation (11-80),  the mean photolysis rate
 constant  is computed  to  be:
                k ,  =  .32 day
                            -1    450    1.6
1
                                 2100   1.2   23.1 •  2
                   -  2.0 x 10"3 day"1
     This  example  demonstrates  the significant difference,  100 fold in this
 case, which  may  exist  between  near surface and mean photolysis rate
 constants.   The  strong attenuation of light by the river water was the
 primary  cause  of the reduction  in  rates.
B.  Evaluation  of  Integrals

     The absorption data for carbaryl  indicate that we  need  to  concern
ourselves only with light of wavelength 300-330 nm in order  to  determine  a
mean rate constant.

     First, we assume that D has the same value as above,     1.6.   Then,
we compute the light attenuation coefficients using Equation  (11-68)  and
the data in Table 11-27.
A
(nm)
300
310
320
330
D
1.6
1.6
1.6
1.6
h
(irf1)
,141
.105
.0844
.0678
+ (a
V DOC
[(mg/1 TV1]
6.25
5.41
4.68
4.05
DOC/
(mg/1)
2
2
2
2
• (•„ •
[(mg/1 TV1]
.35
.35
.35
.35
(mg/1)
10
10
10
10
                                                                       (m"1)
                                                                      •*.. mimmmmim

                                                                       25.8

                                                                       23.1

                                                                       20.7

                                                                       18.7
                                    153

-------
     Table 11-26 lists the photon spectral irradiance, W, at a reference
total sloar flux, I , of 540 langleys/day.  The local solar flux, as in part
                   o
A, is 450 langleys/day.

     Next, evaluate the sum indicated in Equation (11-82).

     Since KZ  >3 for all wavelengths of interest, use the approximation
discussed in part A.
     X          e             W  x 10"14                          ...
               1   i                  ?                         c-W
    (nm)      (M  cm"1)       (photons/cnT/s)      (K-Z)            K Z
    300        918               .0303          51.6         .539 x 10 14
    310        356               .388           46.2        2.99  x 10 '14
    320        101              1.13            41.4        2.76  x 10 14
    330         11              1.81            37.4         .532 x 10 14
                                                       E = 6.82  x 10
                                                       i
14
     Given that the quantum yield is .006, the mean photolysis rate constant
can be computed using Equation (11-82) and the above information:

      k  = 2.3 • 1.43 x 10"16 • — - .0060 • 1.6 • 6.82 x 1014
       d                        540
         = 1.8 x 10"3 day"1

     The small difference between the rate constants calculated in parts A
and B is due to the difference in the reference solar intensities.  The
assumption made here that the spectral  distribution of solar energy is
independent of intensity is only approximately true.  Consequently, the
greater the discrepancy between the reference and local  solar intensities,
the greater the error in rate constants that can be expected.  When the
local exceeds the reference intensity,  the actual rate constant is probably
higher than the calculated value.  When the reference exceeds the local
intensity, the actual rate constant is  probably lov.'er than calculated.
                             rjD OF  EXAMPLE  11-7 —
                                   154

-------
2.5.3  Hydrolysis

     Some toxic compounds can be altered by direct reaction with water.   The
chemical reaction of a compound with water is called hydrolysis.  Typically
in hydrolysis reactions hydroxide replaces another chemical group.

     An example hydrolysis reaction for a toxic organic compound is given
below:
 Carbaryl
                         H20
Water
                               OH'
             +   H2  NCH3   +   C0:
a-Naphthanol  +  Methyl ami ne + Carbon
                               Dioxide
     Generalized hydrolytic reactions of organic compounds are presented in
Table  11-30.

     Hydrolysis reactions alter the reacting molecules but do not always
produce less noxious products.  For example the more toxic 2,4-D acid is
produced from the hydrolysis of certain 2,4-D esters.  Alternatively the
hydrolysis of carbaryl (shown above) produces less toxic products,
i.e. a-naphthanol  and methylamine.

     Hydrolysis products may  be more or less volatile than the original
compound.  Hydrolysis products which ionize may have essentially zero
volatility depending  upon pH.  Hydrolysis products are generally more
readily biodegraded than the  parent compounds, although there are some
exceptions.

     Hydrolysis reactions are commonly catalyzed by  hydrogen or hydroxide
ions.  This produces  the strong pH  dependence often  observed for hydrolysis
reactions.  Examples  of this  dependency are shown in Figure 11-16, where the
logarithms of reaction rate constants  (k ) are plotted versus pH.  The
                                        H
                                    155

-------
                                    TABLE 11-30



             GENERALIZED HYDROLYTIC REACTIONS OF  ORGANIC COMPOUNDS
REACTANT REACTION CONDITIONS
PRODUCTS

CARBOXYLIC ACID ESTERS ACIDIC, NEUTRAL,
Q BASIC
R-ct
AMIDES ACIDIC, BASIC
R-c(
XN-R'
1
H
CARBAMATES ACIDIC, BASIC
H
R-N
C-O-R'
0
ORGANOPHOSPHATES BASIC (Acioic,
(AND DERIVATES) NEUTRAL)
Q
RO-P— OR
i
OR
HALOGENATED ALKANES NEUTRAL, BASIC
R
i
,C~\
R' R-
CARBOXYLIC ACID + ALCOHOL
o
R-C7 + R'OH
XOH
CARBOXYLIC ACID + AMINE
/ H\
R-cf + A\
XOH ,/ V
AMINE + ALCOHOL + CARBON DIOXIDE
R_N/H R'OH C02
\

PHOSPHATE DIESTER + ALCOHOL
0
RO — P — OH ROH
i
OR
ALCOHOL + HALIDE ION
R _
R'— C— OH X
i
1
R"
SOURCE:   i.J. TINSLEY,  CHEMICAL CONCEPTS IN  POLLUTANT BEHAVIOR,  J. WILEY, NEW YORK  (1979).
                                         156

-------
                                            2    V0-CH2-CH2-0-CH
                                             O  Parathion
                                             0  Carbaryl
                                             O  Chloromethane
                                             A  2.4-D (2-butoxyethyl
                                                ester)
                                    PH
FIGURE  11-16   pH DEPENDENCE OF HYDROLYSIS  RATE CONSTANTS
                                 157

-------
hydrolysis rate of carbaryl can be seen to increase logarithmically with pH.
The rate at pH = 8 is ten times that at pH = 7 and 100 times that at pH = 6.
The hydrolysis rate of parathion is high at low pH values, reaches a minimum
at pH = 6, and then increases with increasing pH.   The hydrolysis rate of
chloromethane shows minimal dependence on pH over the range presented.

     Adsorption can also influence hydrolysis rates.  Adsorption of an
organic molecule protects it from acid or base catalyzed hydrolysis (Wolfe,
1981).  The amount of adsorption can be predicted using the principles
presented in Section 2.3.2.

     Microbially mediated hydrolysis reactions are responsible for the
breakdown of many complex molecules, including natural polymers such as
cellulose.  Microorganisms catalyze hydrolysis reactions in the process of
using organic compounds as energy and/or carbon sources.  In cometabolism
microbes may hydrolyze toxic organic compounds to hasten their removal from
cell protoplasm.  Microbially mediated processes are covered under the
general heading of biodegradation in Section 2.5.1.  Here only abiotic
hydrolysis is treated.

     Abiotic hydrolysis reactions are  represented by rate expressions which
are first order in the concentration of the compound being hydrolyzed:

                         R = — = -k   C                               (11-84)
                             at     H  T
                                              -1    -1
                          ,_. jlvsis. mole  1itet
where R   = the rate of hydrolysis,  mole liter   sec   or
            yg liter   sec
       k    =  specific  hydrolysis  rate constant, sec"1
        H

       C   =  the  dissolved  plus  sorbed  phased  concentration  of  compound  C,
             mole liter     or  yg  liter
      In the literature k   is  typically  defined  as:
                        H
                                  158

-------
                   k  = k  + k  [H ]+ k  [Oh"]                         (11-85)
                    H    n    a        b

     In this document the specific hydrolysis rate constant, k,,, is defined
                                                              h
to include the effects of adsorption:

                                     4-         - \~1
                                                                       (11-86)
    r        /     +         - \i
k  = k  + a  (k  [H ]+ k  [OH ]}
 HLn    w \ a        b      /_
where k     = the neutral hydrolysis rate constant, sec
       n

      a     = the decimal fraction of the total amount of compound C
       w
              which is dissolved (Calculation procedures in Section 2.3.2)

      k     = the acid catalyzed hydrolysis rate constant, liter
       a          -1-1
              mole   sec

      [H 1  = the molar concentration of hydrogen ion, mole liter
      k     = the base catalyzed hydrolysis rate constant, liter
              mole   sec

      [OH ] = the concentration of hydroxide ion, mole liter
               [of] - io(pH-'V  -- io°pH-14)

Equation 11-86 is a convenient definition of k  because specific rates
constants which act on the dissolved and total concentrations do not have to
be used separately.

     Values for the three rate constants k ,  ka, kb for selected compounds
are presented in Table 11-31.  Additional values can be found in the
literature (e.g.  Mabey and Mill, 1978).  The three constants can also be
determined by simple laboratory tests.

     Water body pH values must be obtained for hydrolysis reactions which
are pH dependent (i.e.  those for which  k  4 0 and/or k  ^ 0).  It should be
noted that in poorly buffered waters (alkalinity £50 mg/1 as CaCO ), pH
values may change by 1-2 units daily due to natural processes alone.  In
                                   159

-------
                                     TABLE  11-31

       HYDROLYSIS  RATE  PARAMETERS  AND ESTIMATED  ENVIRONMENTAL
                                 HYDROLYSIS  RATES
Compound
Pesticides
Endnsul fon
Hept-ichlor
C-if baryl
Prophan
Chlorpropham
2,4-D(2-Butoxyethyl ester)
2,4-D(Methyl ester)
Parathion
Phosmet
Dial i for
Malathion
Captan
Atrazine
Methoxychlor
Haloqenated Hydrocarbons
Chloromethane
Bromomethane
Chloroethane
Dlchloromethane
Tr ichloromethane
Brouiodi chl oromethane
D ibromochloromethane
Tri bromome thane
Hexachlorocyclopentadiene
Haloqenated Ethers
Bis{chloromethyl) ether
2-Chloroethyl vinyl ether
Phthalate Esters
Dimethyl ester
Oiethyl ester
Ci-n-butyl ester
Di-n-octyl ester
Di(2-ethylhexyl ) ester
Monocyc'Hc Aromatics
Pentachl orophenol

ka(M"1day"1) k^day'1) kb(M"1day"1)

3.3xl05
7 7 ?
4.3xl05
.66
1.7
1.7 - 2.6xl06
1.5xl06
1.3xl02 3.6xlO"3 2.46xl03
7 ? ?
777
7 77
1.6 4.9xl07
3.4 6.6
2.6xlO"3 31.

2.1xlO"3 .53
3.5xlO"2 12.
l.BxlO"2
2.8xlO"6 1.8xlO"3
6.0
1.4xl03
69.
28.
4.8xlO"2

1.6xl03
3.8xl02

1. - 6.0xl03
1. - 1.9xl03
1. - 9.1xl02
1. - 1.4xl03
1. - 9.6

l.lxlO4 5.8xlO"3 3.3
U n v i ro
Hydro lysi
kH(day"')

3.5xlO"2
.7
4.3xlO"2
6.6xlO"8
1.7xlO"7
.26
.15
3.9xlO"3
2.3
1.2
6.6xlO"2
5.6
6.6
2.6xlO"3

2.1xlO"3
3.5xlO"2
l.BxlO"2
2.8xlO"6
e.cxio"7
1.4x10"°
6.9xlO"6
2.8xlO"6
4.8xlO"2

1.6xl03
3.8xlO"5

6.0xlO"4
1.9xlO"4
9.1xlO"5
1.4xlO"4
9 SxlO"7

6.9xlO"3
nmental
s Rates (pH=7)
todays)

21
1.
16.
l.lxlO7
4.0xl06
2.7
4.6
l.SxlO2
.30
58
11.
.13
.10
2.7xl02

3.4xl02
20.
38.
2.6xl05
I.SxlO6
5.0xl04
l.OxlO5
2.5xl05
14.

4.5xlO"4
I.SxlO4

1.2xl03
3.7xl03
7.6xl03
4.9xl03
7.2xl05

l.OxlO2
Ref.
Temp.

27
30
27
27
27
28
28
7
20
20
20
27
25
25

25
25
25
25
25
25
25
25
25

20
25

30
30
30
30
30

7
Ref.

a
a
b
b
b
c
c
d
e
e
e
f
f
f

f
f
f
f
f
f
f
f
a

a
a

9
9
9
9
9

d
"?" denotes rate parameter not given and not estimable from data in reference
"-" denotes zero or very small rate parameter

References:
*  Callahan e_t al.  (1979)
  Wolfe e_t JKT1978)
5  Zepp et al_. (1975)
a  Park et, a]_. U980)
!  Tinsley 11979)
  Habey and Mill (1978)
9  Wotfe et al.  (1980)
                                              160

-------
 these cases either additional data must be gathered to characterize the

 system's pH regime or conservatively low values of k  must be used.
                                                     H
                                 EXAMPLE 11-8
      A biodegradation rate constant,  k  for the fungicide  Captan has been

 given as 0.5 per day.  Compare this with the abiotic hydrolysis rate

 constant, k , at pH = 8.4, a temperature of 25 C,  and with 90 percent of the

 compound adsorbed on suspended matter.  Values for k ,  k , and k  can be

 found in Table 11-31.
      k   =  0
       a             7-1
      k   =  4.9 x 10  day
       b            -1
      k   =  1.6 day
       n

                        f   /    +         -VI
                    k  = a   k [H ] + k [OH ]  + k
                     HlwVa        b     /I    n
      [OH'] -- !0PH-14 - 108'4-14 . ID'5-6 - 2.51 x 10-6
 thus



      kH =[(1.0-0.9)-(4.9 x 10  x 2.5 x 10~6)1



         = 12.3+ 1.6  = 13.9 day
      x 10  )|  + 1.6


-1
 Comparing k  to k  ,
            H     B
                  13.9

                   A t   = 27.8
 Comparison  of  k   with k  for the above situation shows that the abiotic
               H        B
 hydrolysis  rate  is  about 28 times faster than  the biodegradation rate.

 Biodegradation could  be neglected here with  minimal  effect on  the results.



—	 END OF EXAMPLE  II-8—	
                                   161

-------
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                                  166

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                                 167

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                                  CHAPTER  3
                         WASTE LOADING CALCULATIONS
3.1  INTRODUCTION
     This chapter outlines basic procedures that can be used to generate
estimates of diffuse (nonpoint) and point source loads.  Loading functions
for the following pollutants will be considered for nonpoint sources:

     •   Sediment
     •   Nutrients (phosphorus and nitrogen)
     •   Organic matter
     •   Salinity in irrigation return flow
     •   Toxic organic pollutants
     •   Metals

 Both cultivated  and noncultivated agricultural  land as well as urban areas
 are addressed  in this report.  For agricultural lands, long term sediment
 loads are calculated with the  Universal  Soil Loss Equation  (USLE).   This
 method  has  been  adopted for a  number of  reasons, principal  among them being
 the large data base that exists for the  terms  in the USLE.  The modified
 USLE is presented as a method  for estimating single event conventional
 pollutant loads.  The  loading  of both  nutrients and organic matter  can  be
 quantitatively related to sediment  loading.  Thus,  the discussion of
 nutrients and  organic  matter  logically follows the  sediment loading
 calculations.  These selected  water quality parameters were chosen  for
 inclusion  in  this report  because they  represent commonly  occurring  problems
 of major concern to planners.

      Salinity in irrigation  return  flow  is important  in many areas  in  the
 arid western  states.   Considerable  data  are included  in this report
 especially  for the  Colorado  River  basin  and the irrigated regions  in
 California  (Section  3.2.8).   Procedures  are included  for  determining
 electrical  conductivity  and  sodium adsorption  ratio (SAR).
                                  168

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     For urban areas two procedures are presented;  the URS Urban Water
Quality Management procedure and the SWMM Level One Screening procedure.  In
the former, solids loading rates are first calculated and then the loading
rates of other pollutants are related to them.  Pollutants considered in
this section include BOD, phosphorus, nitrogen, coliforms, and heavy metals.
In the SWMM procedure separate and combined sewers are considered as well as
street sweeping efficiency.  Single event procedures are also provided for
urban areas.

     Next, typical point source pollutant loads for municipal and industrial
discharges are discussed.  Whenever possible, however, local data should
always be used, if available, in lieu of the "typical" loadings given here.

     Within each major section a subsection on toxic organic pollutants is
included.  These sections cover the various ways in which toxicants
accumulate on watershed surfaces and provide procedures to estimate washoff
of toxicants in the sediment and water phases.

     Each of the major divisions on nonpoint source calculations
(agricultural and urban areas) in this chapter is essentially independent of
every other.  Accordingly, they can be used in any order.  Within each
section, the calculations performed can be used in two different ways.
First, the magnitude of loadings can be compared for various alternatives
(e.g., different land use schemes) to ascertain the significance of the
changes.  Second, the loadings can be used in calculations presented in
Chapter 4 to assess the water quality impacts of nonpoint source pollutants
on rivers and streams.  These data can then be used to determine input of
nonpoint source pollutants to impoundments (Chapter 5) and estuaries
(Chapter 6), as appropriate.

     In writing this chapter the following sources have been heavily and
freely drawn upon:  "Loading Functions for Assessment of Water Pollution
from Nonpoint Source (McElroy _et jTL, 1976), "Water Quality Management
Planning for Urban Runoff" (Amy, et aj_., 1974), "Storm Water Management
Model Level I, Prel iminary Screening Procedures" (Heaney, et _al_., 1976),
"Predicting Rainfall Erosion Losses:  A Guide to Conservation Planning"
(Wischmeier and Smith, 1978) and "A Mathematical Model for Estimating
                                       169

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Pesticide Losses in Runoff" (Haith, 1980).  Users should refer to these
references for further details concerning the methodologies.
3.2  NONURBAN NONPOINT SOURCE LOADS

3.2.1  Annual Sediment Loads

     Sediment loading  is  defined  in this report as the quantity of soil
material  that is  eroded and transported into the watercourse.  Sediment
loading  is  dependent on (a) on-site erosion, and (b)  delivery, or the
ability  of  runoff to carry the  eroded material  into  the  receiving waters.

     The sediment loading function  is based on  the mechanisms  of gross
erosion  and sediment delivery.   The Universal  Soil Loss  Equation  (Wischmeier
and Smith,  1965)  has been chosen to predict on-site  surface  (including  sheet
and rill) erosion, for the following  reasons:

      1.   This  equation is applicable  to  a  wide variety  of land uses  and
          climatic conditions.

      2.   Data have been collected nationwide  for  factors included  in
          the equation.

      The sediment loading function has  the form:

                      Y(S)£ =1   [A. -(R-K-L.S.C-P).Sd]               (III-l)

 where
      Y(S)  = sediment  loading from surface erosion,  (tons/year,
              tonnes/year)
       n      =  number  of  subareas  in  the  area
                                   170

-------
    A.    = acreage of subarea i, (acres, ha)

    R     = the rainfall factor, expressing the erosion potential of
            average annual rainfall  in the locality.

    K     = the soil-erodibility factor, commonly expressed in tons
            per acre  per R unit

    L     = the slope-length  factor,  dimensionless ratio

    S     = the slope-steepness factor,  dimensionless  ratio

    C     = the cover factor, dimensionless  ratio

     P      = the erosion  control  practice factor, dimensionless ratio
            and

     S,     = the  sediment delivery  ratio, dimensionless.
      d

     Equation  III-l can be used to  predict  sediment  loading resulting  from
sheet  and rill erosion from cultivated and  non-cultivated  lands.   Parameter
values  for silviculture,  construction, and  mining  are less well  documented
than for agriculture,  however.  The user will thus  find it relatively  easy
to use  Equation III-l  for agriculture, and  substantially more  difficult for
other  sources.  The equation does not predict sediment contributions from
gully  erosion, streambank erosion,  or mass  soil  movement.

     Estimation of surface erosion  should be  made  for each relatively
homogeneous  land-use type.  For a given land-use type, if  90 percent or more
of the area is made up of one soil  type, one  may calculate soil  loss for
each soil type that makes up at least 10 percent of the land use, and  then
obtain  a weighted  average for the entire land-use  area (U.S. Dept.  of
Agriculture,  1974).  There is no limitation on how finely  the watershed can
be broken down into subwatersheds.   This determination should be made  based
on information density, time and monetary restrictions, and level of
accuracy desired in the results.  Figure III-l is  a flow diagram showing the
usage of Equation III-l for predicting annual average sediment loads.
                                  171

-------
tvs
             Local Drainage
              Density Soil
              Texture, and
             Figure m-9,
             or Eq. (HI-2)



Sediment
Delivery
Ratio 84



Land Use Acreage, A,- 's
.
t
Soil Names,
or Soil
Properties
.

Soil Erodibility
Factor K, from
Published Lists
or Nomographs
i



Land Use Types,
Dates of Cropstages,
Canopy, ground
Cover Density
1
Cover Factor C,
from Table HI -2
to HI -5, or Others



-
Types of
Conservation
Practice
•
-
Practice
Factor P,
from
Table m-6
»
n r~ ~~i
r(s)E=£ A| • (R-K • LS -c- p • sd )| 1







Slope Lengths,
and Slope
Gradients
*
Topographic
Factor LS,
from Figure
m-7 to m-8



                                                        Local Rainfall Erosivity
                                                       Factor R from Iso-erodent
                                                       Maps  or by  Calculation
               FIGURE III-l  FLOW DIAGRAM FOR CALCULATING SEDIMENT  LOADING FROM SURFACE EROSION

-------
3.2.1.1  Data Requirements

     The following should be obtained:

     •   total area, and land use acres in the area:  cropland,
         pastureland, and woodland, etc.

     •   soil characteristic information (e.g.  soil texture) for each
         land use.

     •   canopy and ground cover condition for each land use.

     •   good topographic maps

     •   the  type and extent of conservation practices.


3.2.1.2  Determination of LISLE Factors

3.2.1.2.1  The Rainfall Factor (R)

     R is  a  factor expressing the erosion potential of precipitation  in a
locality.  It is  also called index of erosivity, erosion index, etc.   It is
the  summation of  the individual storm products of  the kinetic  energy  of
rainfall  (denoted by E),  and the maximum 30 minute rainfall  intensity
(denoted by  I) for  all significant storms within the period  under
consideration.  The product  El reflects the combined potential of raindrop
impact and runoff turbulence to transport dislodged soil particles  from the
site (Wischmeier  and Smith,  1965).

     Values  of average annual rainfal1-erosivity index, R, are shown  in
Figure  III-2 for  the continental U.S.   and Figure  III-3 for  islands of
Hawaii.  On  these maps,  the  lines  joining points with the  same erosion index
value  are  called  isoerodents.  Points  lying between the indicated
isoerodents  may be  approximated by linear interpolation.
                                   173

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          35
FIGURE 111-2  AVERAGE ANNUAL VALUES OF THE RAINFALL-EROSIVITY FACTOR,  R  (EPA,  1975)

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                              0   5   10 Miles
OAHU
                              KAUAI
                              LANAI
                              MAUI
                              MOLOKAI
                              OAHU
FIGURE  111-3   MEAN ANNUAL VALUES  OF EROSION  INDEX FOR HAWAII  (I'.SAA,, 1974)

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     Interpolation for values of R factors in the mountainous areas,
particularly those west of the 104th meridian may not be appropriate because
of the sporadic rainfall pattern.  Values of the erosion index at specific
areas can be computed from local recording rain gage records with the help
of a rainfall-energy table and the computation procedure presented by
Wischmeier and Smith (1978).

     The USDA has recommended that 350 be the maximum used in the Gulf and
southeastern states, shown in Figure III-2, until further research can
validate values higher than 350.

     In the  northwestern United  States, runoff from snowmelt contributes
significantly to  surface erosion.  The annual  index of R for some portions
of this region is the combined  effect of  rainfall and snowmelt designated by
R  and R  , respectively.  The snowmelt factor  (R  )  is important  in  Areas
  I       j                                       »5
A-l, B-l,  and C on  Figure III-4 (also refer  to Table  III-l).  The map  values
 in the shaded region  of the  Northwest  (see  Figure III-2) represent  values
for  the rainfall  effect  (R  )  only,  and must  be added  with appropriate  R.
                          r                                            b
values to  account for the effect of  runoff  from thaw  and snowmelt.

      Interim procedures  for calculating  annual R  values, which  include both
 R  and R  , for the  northwestern U.S.   are described in  Conservation Agronomy
 Technical  Note No.  32,  USDA/SCS, Portland,  Oregon (1974), and  are  briefly
 presented below.

      The annual  R  factor is obtained  by using as a base the two year, six
 hour rainfall (2-6 rainfall).  Relationships between R   and 2-6 rainfall
 vary to  conform  to specific local climatic characteristics.  These
 relationships are designated as Type I,  Type IA,  and Type II, and are shown
 in Figure III-5.   Specific  areas applicable to these curves are shown in
 Figure III-6.  Type I curve is for the central valley and coastal  mountains
 and valleys of southern California.  Type IA curve applies  to the coastal
 side of the Cascades in Oregon  and Washington, the coastal  side of the
 Sierra Nevada Mountains in northern California, and the coastal regions of
 Alaska.    Type II curve applies  to the remainder of the region.  For 2-6
 rainfall  data, refer to Technical Paper  No. 40, U.S. Department of Commerce,
                                    176

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                                          0    100  200 MILES
FIGURE 111-4  SOIL MOISTURE-SOIL TEMPERATURE REGIMES OF THE
              WESTERN  UNITED  STATES  (U.S.P.A,, 197*0
                              177

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                            TABLE III-l


           APPLICABILITY OF Rp AND Rg FACTORS  IN THE AREAS

    WEST OF THE ROCKY MOUNTAINS (U.S. DEPT.  OF AGRICULTURE,  1974a)
  Areas  (see
  Figure  III-4)


       A-l


       A-2


       A-3


       A-4
       B-l
       B-2
   Typical  Locations


Washington, Idaho, Nevada,
California, western Utah

Cascades, Sierra, Tetons of
Idaho, Wasatch Mountains

West of Cascades, San Joaquin
Valley, west of Sierras

Areas of southern California,
east of Santa Anas, southern
Nevada, intermountain Nevada,
Salt Lake area, Utah

Western Montana, Colorado,
eastern Utah, high elevations
of Arizona

Great plains area of eastern
Montana, Wyoming, Colorado
(includes gently sloping
mesas and upland at lower
elevations of Monticello,
Utah area)

Rainfall during summer is
high; high elevations
xi/


X


X


X
b/
a/  X needed
b/  - not needed
                                  178

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                2.0
      3.0
4.0
2-Year, 6-Hour Rainfall, cm

 5.0   6.0    7.0    8.0   9.0
II.0  12.0
          600 -
                          1.5
                  2.0     2.5     3.0    3.5


                 2-Year, 6-Hour Rainfall,
                                  4.0
                                     4.5
          5.0
FIGURE  111-5  RELATIONSHIPS  BETWEEN ANNUAL AVERAGE  RAINFALL  FROSIVITY  INDEX AND  THE

               ?-YEAR,  6 HOUR RAINFALL  DEPTH FOR  3  RAINFALL TYPES IN WESTERN ?',$,
                '!!  c  n A   107/1)
                . u i O 11' i n i j -L3/ ./
! I



I

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      LEGEND- Storm Distribution
      1   J TYPE IA
           TYPE I
           TYPE
FIGURE  III-6  STORM  DISTRIBUTION  REGIONS  IN  V/ESTERN n,S,
               (U.S.TU,, 1974)
                              180

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Weather Bureau, Washington, D.C. (1961), or other suitable rainfall
frequency analysis reports.

     To obtain the annual  R  factor for a given  location, obtain the average
annual total precipitation by snowfall  (in  inches of water depth)  and
multiply  it by the constant 1.5.

     There  are numerous  sources  of  snowfall data for the  United  States.
Some of the major  sources  are:

     •   The  1941  Yearbook of Agriculture,  USDA, Washington,  D.C.,

     •   "Climates of the  States,"  Water  Information  Center,  Inc., Port
          Washington,  New York  (1974),  and

      •   Data resulting from  the Western  Federal-State-Private
          Cooperative Snow Surveys,  coordinated by  SCS/USDA,
          Portland, Oregon.

      Data on snow density is  necessary to convert  depth of snow to depth of
 meltwater.   Snow at the time  of fall  may have a density as low as 0.01 and
 as high as  0.15  g/ml.  The average snow density for the United States is
 taken  to be 0.10 (Garstka, 1964).  If snowfall  is  recorded as inches of
 precipitation, no conversion  is required.

      The monthly distribution of the erosion index for the 37 states east of
 the Rocky Mountains has been reported in USDA-ARS Agriculture Handbook
 No. 282  (Wischmeier and Smith,  1965).  Average  monthly erosion  index values
 are expressed as percentages of average annual  values and plotted
 cumulatively against time in Appendix A.

      The monthly distribution of erosion index  for the islands of Hawaii
 also has been developed (U.S.  Dept.  of Agriculture, 1974b).  These curves
 are shown in Appendix A.  If monthly or seasonal sediment yields  are
 required the annual R value can be factored using the percentages from these
 figures.
                                     181

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     For the areas west of the Rockies in the continental United States,  the
monthly distribution of erosion index R is the summation of R  and R .
                                                             r      s
Where RS values are not needed, the R and R  curves are the same.

     The R factor in equation III-l can be expressed in metric units
((hundreds of metric tons/ha-cm) multiplied by (maximum 30-minute intensity,
cm/hr)) by multiplying the English R values by 1.735.
3.2.1.2.2  The Soi1-Erodibility Factor (K)

     K factor is a quantitative measure of the rate at which a soil  will
erode, expressed as the soil loss (tons) per acre per unit of R, for a plot
with 9 percent slope, 72.6 ft.  long under continuous cultivated fallow.  K
factors for topsoils, as well as subsoils, for most soil series have been
developed.  Values of K for soils studied thus far vary from 0.12 to 0.70
tons/acre per unit R.  Values can usually be obtained from the regional  or
state offices of the Soil Conservation Service.

     K values of soils can also be predicted from soil properties.   In
Appendix B of this report, two methods are presented from which K values may
be determined for topsoils and subsoils when the governing soil properties
are known.  The factor for conversion of K in English units to metric-tons
per hectare per metric R unit is 1.292 (Wischmeier, 1972).
3.2.1.2.3  The Topographic Factor (IS)

     Soil loss is affected by both length (L)  and steepness of slope (S).
These factors affect the capability of runoff  to detach and transport soil
materi al.

     The slope length factor is the ratio of soil loss from a specific
length of slope to that length (72.6 ft) specified for the K factor in the
USLE.  Slope length is defined as the distance from the point of origin of
overland flow to either of the following:  the point where the slope
decreases to the extent that deposition begins or the point where runoff
                                   182

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enters a well-defined channel.  Slope length can be determined accurately by
on-site inspection of a field, or by measurements from topographic maps.
When the land is terraced, the terrace spacing should be used.

     The slope gradient or percent slope factor is the ratio of soil loss
from a specific percent slope to that slope (9 percent) specified for the K
value in the USLE.  A 9 percent slope has a factor value of 1.  Slope data
may be obtained from topographic maps, engineering or land level surveys,
and other sources.  A widely  used method is to estimate slope from soil
survey maps  in which the  soils have been mapped by slope range.

     The slope length  (L) and slope gradient  (S) are usually combined in the
USLE into a  single dimensionless topographic  factor, LS, which can be
evaluated using a slope-effect chart.

     The slope-effect  chart  in Figure III-7 is designed for the following
areas  shown  in Figure  III-4:  A-l  in Washington, Oregon, and  Idaho;  and all
of  A-3  (U.S.   Dept.  of Agriculture, 1974a).   For  the remainder of the  U.S.,
the slope-effect  chart, Figure  III-8, is to be  used  (U.S.  Dept.   of
Agriculture,  1974a).

      Slope-effect charts  in  Figure  III-7 and  III-8 can  be  used when  uniform
slopes  are  assumed.  The  following  steps are  to  be used for obtaining  LS
values  from these charts:

      1.   Enter the  chart  on  the horizontal  axis  with the  appropriate
          value of slope  length.

      2.   Follow the  vertical line  for that  slope length to where  it
          intersects  the  curve for  the appropriate  percent  slope.

      3.   Read across the  point of  intersection to  the vertical  axis.
          The number  on the vertical  axis  is the LS value.
                                    183

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                       Slope  Length, Meters
           20  30 40  60 80IOO  ISO 200 30O 4OO 60O 8OO
       40.0
       20.0
        10.0
     _J
      -  6.0
     O
     O  4.0
     O
     u_
     a.
     o
        2.0
     0>
     CX  1.0
     o
        0.6

        0.4



        0.2



         O.I
                        (Slope %)
                                  60
                                  , 50
                                  45
                                  '40
                                  •35
                                  •30
                                  25
                                  ,20
                                  18
                                  • 16
                                  •14
                                  • 12
                                  . 10

                                   8
                                  •0.5
            70  100    200    4OO 600  1000   2000
                        Slope  Length, Feet
FIGURE 111-7
SLOPE EFFECT CHART APPLICABLE TO AREAS A-l
IN WASHINGTON, OREGON,  AND IDAHO AND ALL OF
A-3 A^B/ (U,S, DEPT,  OF AGRICULTURE, 1974)
A/ SEE FIGURE  II1-4,
B/ DASHED LINES  ARE  EXTENSIONS OF LS FORMULAE BEYOND VALUES
   TESTED IN STUDIES,
                                184

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  20.0
       3.5    6.0
10
Slope Length,  Meters
 20      40  60    100
200
                                                            400  600
                                    1 '  ' >*
   O.I I*
     10      20      40   60    100     200     400  600  1000    2000
                           Slope Length, Feet

FIGURE 111-8     SLOPE—EFFECT CHART FOR AREAS WHERE  FIGURE  111-7
                 is NOT APPLICABLE A/ (U.S. DEPT. OF  AGRICULTURE)

A/ THE DASHED LINES REPRESENT ESTIMATES FOR SLOPE DIMENSIONS
   BEYOND THE RANGE OF LENGTHS AND STEEPNESSES FOR WHICH DATA
   ARE AVAILABLE,
                                185

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3.2.1.2.4  The Cover Management Factor (C)

     In the USLE, the factor C represents the ratio of soil  qualtity eroded
from land that is cropped or treated under a specified condition to that
which is eroded from clean-tilled fallow under identical  slope and rainfall
conditions.  C ranges in value from near zero for excellent  sod or a
well-developed forest to 1.0 for continuous fallow, construction areas, or
other extensively disturbed soil.

     Values of factor C for croplands are highly variable with planting
dates, type of vegetative cover, seeding method, soil tillage, disposition
of residues, and general management level.  Generalized C values for various
types of crop management systems are  listed in Table  III-2.   The reader is
advised to consult with state conservation agronomists of SCS for
appropriate C values for crops  in the local area.  The reader is also
referred to USDA-ARS Agriculture Handbook No.  537  (Wischmeier and
Smith, 1978) for a  listing  of  approximated C values for various crops  at
each crop  stage, as well as a  working table for derivation of average  C
value  for  periods of crop rotation.

     C values  typical  of permanent  pasture,  range,  and idle  lands,  with
varying  cover  and canopy conditions,  are given  in  Table  III-3.  These  values
were developed  by Wischmeier  (1972).  Wischmeier  (1972)  has  also  estimated C
values for some woodland situations (Table  III-4).

      For urban and  road areas, as  well  as construction sites,  the factor  C
 represents the effect  of  land cover or  treatment  that may be used to protect
 soil  from being eroded. Table III-5 (Water Resources Administration,  1973)
 lists  values  of the C  factors for  various soil  covers and treatments.
 3.2.1.2.5  The Practice Factor (P)

      The factor P accounts for control practices that reduce the erosion
 potential of runoff by their influence on drainage patterns, runoff
 concentration, and runoff velocity.
                                   186

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GENERALIZED VALUES OF THE COVER AND MANAGEMENT FACTOR,  C,
      IN THE 37 STATES EAST OF THE ROCKY MOUNTAINS1

Line , , -\
Clop, rotation, and management
no.

Base value: continuous fallow, tilled up and down slope
CORN
1 C, RdR, fallTP, conv(l)
2 C, RdR, spring TP, conv(l)
3 C, RdL. fall TP, conv(l)
4 C, RdR, we seeding, spring TP, conv (1 )
5 C, RdL, standing, spring TP, conv (1)
6 C, fall shred stalks, spring TP, conv (1 )
7 C(silage)-W(RdL, fall TP) (2)
8 C, RdL, fall chisel, spring disk, 40-30% re (1)
9 C(silagc), W we seeding, no-till pi m c-k W (1 )
10 C(RdL)-W(RdL, spring TP) (2)
1 1 C, fall shred stalks, chisel pi , 40-30% re (1 )
1 2 C-C-C-W-M, RdL, TP for C, disk for W (5)
1 3 C, RdL, strip till row zones, 55-40'7r. re (1 )
14 C-C-C-W-M-M, RdL, TP for C, disk for W (6)
15 C-C-W-M, RdL, TP for C, disk for W (4)
16 C, fall shred, no-till pi , 70-50',; re ( 1 )
1 7 C-C-W-M-M, RdL, TP for C disk tor W (5)
18 C-C-C-W-M, RdL, no-till pi 2d & 3rd C(5)
19 C-C-W-M, RdL, no-till pi 2d C (4)
20 C, no-till pi in e-k wheat, 90-70'/ re ( 1 )
21 C-C-C-W-M-M, no-till pi 2d & 3rd C (6)
22 C-W-M, RdL, TP for C, disk for \V (3)
23 C-C-W-M-M, RdL, no-till pi 2d C(5)
24 C-W-M-M, RdL, TP for C, disk tor W (4)
25 C-W-M-M-M, RdL, TP for C, disk for W (5)
26 C, no-till pi in c-k sod, 95-80% re (1 )
COTTON4
27 Cot, eonv (Western Plains) (1 )
28 Cot, conv (South) (1)
MFADOW
29 Grass & Legume mix
30 Alfalfa, lespedc/.a or Scricia
31 Sweet clover
SORGHUM, GRAIN (Western Plains)4
32 RdL, spring TP, eonv (1)
33 No-till pi in shredded 70-50' < re
Productivity level"
High
Mod.
C value
1.00

0.54
.50
.42
.40
.38
.35
.31
.24
.20
.20
.19
.17
16
14
.12
.11
087
.076
.068
.062
061
.055
051
.039
.032
017

0.42
.34

0.004
020
.025

0 43
11
1.00

0.62
59
.52
49
.48
44
.35
30
24
28
26
.23
24
20
17
18
14
13
11
14
1 1
095
094
074
061
.053

0 49
.40

001



0 53
IK
                            187

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                                           TABLE  111-2  (Continued)
            GENERALIZED  VALUES  OF  THE  COVER AND MANAGEMENT  FACTOR,  C,
              IN  THE  37  STATES EAST  OF  THE  ROCKY MOUNTAINS1-  continued

Line
no.


Crop, rotation, and management

SOYBEANS4
34
35
36
37
WHF.AT
38
39
40
41
42
43
44
45
46
47
48
49
B, RdL, spring TP, conv (1)
C-B, TP annually, conv (2)
B, no-till pi
C-B, no-till pi, fall shred C stalks (2)

W-F, fall TP after W (2)
W-F, stubble mulch, 500 Ibs re (2)
W-F, stubble mulch, 1000 Ibs re (2)
Spring W, RdL, Sept TP, conv (N & S Dak) (1 )
Winter W, RdL. Aug TP, conv (Kans) (1)
Spring W, stubble mulch, 750 Ibs re (1 )
Spring W, stubble mulch, 1250 Ibs re (1)
Winter W, stubble mulch, 750 Ibs re (1 )
Winter W, stubble mulch, 1 250 Ibs re (1 )
W-M, conv (2)
W-M-M, conv (3)
W-M-M-M, conv (4)
Productivity level2
High
Mod.
C value

0.48
.43
.22
.18

0.38
.32
.21
.23
.19
.15
.12
.11
.10
.054
.026
.021

0.54
.51
.28
.22













   1  This table is for illustrative purposes only and is not a complete list of cropping systems or potential practices. Values of C differ
with  rainfall pattern and planting dates. These generalized values show approximately the relative erosion-reducing effectiveness of
various crop systems, but locationally derived C values should be used for conservation planning at the field level. Tables of local
values are available from the Soil Conservation Service.
   2  High level is exemplified by long-term yield averages greater than 75 bu. corn or 3 tons grass-and-legume hay; or cotton manage-
ment that regularly provides good stands and growth.
   3  Numbers in parentheses indicate number of years in the rotation cycle. No. (1) designates a continuous one-crop system.
     Gram sorghum, soybeans, or cotton may be substituted for com in lines 12,14,15, 17-19, 21-25  to estimate Cvalues for sod-
based rotations.
Abbreviations defined:
B    - soybeans
C    - corn
c-k  - chemically killed
conv - conventional
cot  - cotton
F  - fallow
M  - grass & legume hay
pi - plant
W  -wheat
we - winter cover
Ibs re    - pounds of crop residue per acre remaining on surface after new crop seeding
% re     - percentage of soil surface covered by residue mulch after new crop seeding
70-50% re - 70% cover for C values in first column; 50% for second column
RdR     - residues (corn stover, straw, etc.) removed or burned
RdL     - all residues left on field (on surface or incorporated)
TP      - turn plowed (upper 5 or more inches of soil inverted, covering residues)
 Source:    U.S.  EPA,  1975
                                                     188

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                                                          TABLE 111-3
00
                          "C" VALUES FOR PERMANENT PASTURE, RANGELAND, AND IDLE LAND (WISCHMEIER, 1972)-7
Vegetal Canopy
Type and Height , ,
of Raised Canopy-
Column No.
No appreciable canopy

Canopy of tall weeds
or short brush
(0.5 m fall height)



Appreciable brush
or brushes
(2 m fall height)



Canopy-
Cover—' ,,
(%) Type—
2 3
G
W
25 G
W
50 G
W
75 G
W
25 G
w
50 G
W
75 G
W
Cover that Contacts the Surface

0
4
0.45
0.45
0.36
0.36
0.26
0.26
0.17
0.17
0.40
0.40
0.34
0.34
0.28
0.28

20
5
0.20
0.24
0.17
0.20
0.13
0.16
0.10
0.12
0.18
0.22
0.16
0.19
0.14
0.17
Percent
40
6
0.10
0.15
0.09
0.13
0.07
0.11
0.06
0.09
0.09
0.14
0.085
0.13
0.08
0.12
Ground Cover
60
7
0.042
0.090
0.038
0.082
0.035
0.075
0.031
0.067
0.040
0.085
0.038
0.081
0.036
0.077
80
8
0.013
0.043
0.012
0.041
0.012
0.039
0.011
0.038
0.013
0.042
0.012
0.041
0.012
0.040
95-100
9
0.003
0.011
0.003
0.011
0.003
0.011
0.003
0.011
0.003
0.011
0.003
0.011
0.003
0.011
                                                          (continued)

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                                      TABLE 111-3 (Continued)
Vegetal Canopy
Type and Height , ,
of Raised Canopy-
Column No.
Trees but no appreci-
able low brush
(4 m fall height)



Canopy
Cover- ..
(%) Type—
2 3
25 G
W
50 G
W
75 G
W
Cover
that Contacts the
Percent

0
4
0.42
0.42
0.39
0.39
0.36
0.36



0
0
0
0
0
0

20
5
.19
.23
.18
.21
.17
.20



0
0
0
0
0
0

40
6
.10
.14
.09
.14
.09
.13
Surface
Ground Cover



0
0
0
0
0
0

60
7
.041
.087
.040
.085
.039
.083



0
0
0
0
0
0

80
8
.013
.042
.013
.042
.012
.041

95-100
9
0.003
0.011
0.003
0.011
0.003
0.011
a_/  All values shown assume:   (1)  random distribution of mulch or vegetation, and (2) mulch of
      appreciable depth where it exists.
b/  Average fall  height of waterdrops from canopy to soil  surface:   m = meters.
c_/  Portion of total-area surface  that would be hidden from view by canopy in a  vertical
      projection (a bird's-eye view).
d_/  G:   Cover at surface is grass,  grasslike plants, decaying compacted duff, or litter
      at least 5 cm (2 in.) deep.
    W:   Cover at surface is mostly  broadleaf herbaceous plants (as  weeds)  with little
      lateral-root network near the surface and/or undecayed residue.

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                              TABLE 111-4
               'C" VALUES FOR WOODLAND (WISCHMEIER, 1972)
Stand Condition
Well stocked
Medium stocked

Poorly stocked
Tree Canopy
Percent of
Area^-7
100-75
70-40

35-20
Forest
Litter
Percent of
Area^
100-90
85-75

70-40
Undergrowth—
Managed—
Unmanaged—
Managed
Unmanaged
Managed
Unmanaged
"C" Factor
0.001
0.003-0. Oil
0.002-0.004
0.01-0.04
0.003-0.009
0.02-0.09-7
a/  When tree canopy is less than 20%, the area will  be considered as
      grassland or cropland for estimating soil loss.
b/  Forest litter is assumed to be at least 2-in.  deep over the percent
      ground surface area covered.
c/  Undergrowth is defined as shrubs, weeds, grasses,  vines, etc., on
      the surface area not protected by forest litter.  Usually found
      under canopy openings.
d_/  Managed - grazing and fires are controlled.
    Unmanaged - stands that are overgrazed or subjected to repeated
      burning.
e/  For unmanaged woodland with litter cover of less  than 75%,  C values
      should be derived by taking 0.7 of the appropriate values in
      Table III-3.  The factor of 0.7 adjusts for  the  much higher soil
      organic matter on -permanent woodland.
                                  191

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                              TABLE  III-5
                   "C"  VALUES  FOR  CONSTRUCTION  SITES
                (WATER  RESOURCES ADMINISTRATION,  1973)
            Type of Cover
                                C Value
          None (fallow)                             1.00

          Temporary seedings
            First 60 days                           0.40
            After 60 days                           0.05

          Permanent seedings
            First 60 days                           0.40
            After 60 days                           0.05
            After 1 year                           0.01

          Sod (laid immediately)                    0.01

                         Rate of  Application
   Mulch
Hay or straw
Stone or gravel
Chemical mulches
In Metric  Tons   In  Tons
 Per Hectare   Per  Acre
       1/2
         1
     1-1/2
         2

        14
        55
       120
       220
  1/2
    1
1-1/2
    2

   15
   60
  135
  240
C Value

 0.34
 0.20
 0.10
 0.05

 0.80
 0.20
 0.10
 0.05
                      Maximum Allowable
                        Slope Length
                                TO
 20
 30
 40
 50

 15
 80
175
200
 6
 9
12
15

 5
24
53
61
First 90 days
After 90 days
Woodchips







2
4
6
11
18
23
a/
a/
2
4
7
12
20
25
0.50
1 .00
0.80
0.30
0.20
0.10
0.06
0.05
50
50
25
50
75
100
150
200
15
15
8
15
23
30
46
61
a/  As recommended by manufacturer.
                                 192

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     For croplands, control practices refer to contour tillage, cross-slope
farming, and contour strip-cropping.  The practice value P is the ratio of
soil loss from a specified conservation practice to the soil loss occurring
with up-and-downhill tillage, when other conditions remain constant.  Table
III-6 (USEPA, 1975) shows P values currently in common usage.
3.2.1.2.6  Sediment Delivery Ratio ($d)

     The sediment-delivery ratio, in this report,  is defined as the fraction
of the gross erosion which is delivered to some point in the stream system
downstream of the  source  area.  The classical method for determining an
average delivery ratio  is by comparing the magnitude of the sediment yield
at a given point in a watershed (generally at a reservoir or a stream
sediment measuring station), and  the total amount  of erosion.  The
quantities of gross erosion from  sloping uplands are computed by  erosion
prediction equations for  surface  erosion, and estimated by various
procedures for  gullies,  stream channels, and other sources.  The  sedimenb
yield  at a given downstream point is obtained through direct measurements.
Estimates of  the delivery ratio for  some specific  watersheds, particularly
 in the humid  sections of  the country,  can be obtained from the Soil
Conservation  Service, USDA.

     Many delivery-ratio  studies  have  been aimed at finding measurable
 influencing  factors  that  can  be  related  to  sediment-delivery ratio.  A
popular means of developing  such  information  is  by statistical analysis
using  the sediment-delivery  ratio as the dependent variable  and measurable
watershed factors  as  the  independent,  or controlling variables.   Many
physical  and  hydrologic factors may  influence  sediment-delivery ratios.
 Empirical relationships for  delivery ratios  have been  proposed  and  some  are
 presented below.   Estimates  of  sediment  loading  can be  made  through  the  use
 of these  relationships, but  such  estimates  should  be tempered with  judgment
 and  consideration  of other  influencing factors  not included  in  the
 quantitative expressions.  The  user  is encouraged  to consult with local
 experts  and  should use  local  data when available.
                                     193

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                                            TABLE 111-6

                          PRACTICE  FACTORS  (P)  USED  IN  SEDIMENT
                                        LOADING  EQUATION
Practice
Contouring (Pt)
Contour strip cropping (Pst->
R-R-M-M1
R-W-M-M
R-R-W-M
R-W
R-O
Contour listing or ridge planting
(Pel)
Contour terracing (Pj)
No support practice
Land slope (percent)
1.1-2
2.1-7
7.1-12
12.1-18
18.1-24
(1-actor P)
0.60
0.30
0.30
0.45
0.52
0.60
0.30
3 0.6/V^
1.0
0.50
0.25
0.25
0.38
0.44
0.50
0.25
0.5/Vn"
1.0
0.60
0.30
0.30
0.45
0.52
0.60
0.30
0.6 A/T
1.0
0.80
0.40
0.40
0.60
0.70
0.80
0.40
0.8/V^T
1.0
0.90
0.45
0.45
0.68
0.90
0.90
0.45
0.9/VrT
1.0
     R » rowcrop, W * fall-seeded grain, O » spring-seeded grain. M = meadow. The crops are grown in rotation and \o arranged on
 the field that rowcrop strips arc always separated by a meadow or winter-grain strip.
     These Pt values estimate the amount of .soil eroded to the terrace channels and arc used for conservation planning. Tor prediction
 of off-field sediment, the P| values are multiplied by 0.2.
     n = number of approximately equal-length intervals into which the field slope is divided by the terraces. Tillage operations must
 be parallel to the terraces.
Source:    U.S.  EPA,  1975.
                                                      194

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     The MITRE Corporation (1974) reported that the sediment delivery ratio
for construction sites can be approximated by a function of the overland
distance between the construction site and the receiving water:

                                Sd  =  D"°'22                        (HI-2)

where

     D  =  overland distance between the erosion site and the receiving
           water, (ft).

     The above equation was empirically derived from available data.  The
data base for the derivations includes values of D from 0 to 800 ft.  MITRE
suggests that this function should be further tested, particularly in areas
of the Midwest and Central U.S.

     For mining sites, logging roads and fire lanes, sediment delivery ratio
relationships have not yet been established due to lack of systematically
measured data.  It is suggested that the delivery ratio developed by MITRE
and expressed in Equation III-2 be used as the first approximation for these
sites.  This should be verified when appropriate data become available.

     Sediment delivery ratios have been evaluated in many areas of the
country, particularly the eastern half of the United States.  The delivery
ratio usually depicts a general trend in basins that are relatively
homogeneous with respect to soils, land cover, climate, and topography.  The
Soil Conservation Service (1973) analyzed data from stream and reservoir
sediment surveys from widely scattered areas.

     This analysis shows that sediment delivery ratios vary inversely with
"drainage basin size".  It also indicates the effect of soil texture of
upland soil on the sediment delivery ratio.

     The delivery ratio relationships reported by SCS (1973) were used by an
MRI study group in developing delivery ratios for sediment loading to
watercourses.  The result is shown in Figure III-9.  The horizontal scale of
the figure is the reciprocal of drainage density which is defined as the
                                    195

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01
                     IOO
                                                I/Drainage  Density, Kilometers
                                                   i.o                10
                                          100   200     500
                                                                             Silty Clay
                                                                                Predominantly Silt
                       0.02
        1.0                 10
I/Drainage  Density, Miles
100
                                                              SWa
400
                            FIGURE 111-9  SEDIMENT DELIVERY RATIO FOR RELATIVELY  HOMOGENEOUS BASINS
                                          (MLROY, ET  AL,, 1976)

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ratio of total channel-segment lengths (accumulated for all  orders within a
basin) to the basin area.  The reciprocal  of drainage density may be thought
of as an expression of the closeness of spacing of channels, or the average
distance for soil particles to travel from the erosion site  to the receiving
water.  The drainage density is found by dividing the total  length of
perennial streams in the waters and by the area of the watershed.

     The delivery ratio relationship shown in Figure III-9 also takes into
account the effect of soil texture.  For example, if soil texture of upland
soil is essentially silt or clay, the sediment delivery ratio will be higher
than when the soil texture is coarse.

     The following steps are to be used to obtain the delivery ratio (S,)
from Figure III-9.

     1.  Enter the figure on the horizontal axis with the value of the
         reciprocal of drainage density (1/DD).

     2.  Move vertically from the value of 1/DD to where it intersects
         the curve for the appropriate soil texture.

     3.  Read across from the point of intersection to the vertical
         axis.  That number represents the delivery ratio, S,.

     A great range of values of drainage density exists  in the United
States, from 2 km/km2 (3 miles/mile2) for the Appalachian Plateau Province
(Smith, 1950) to 500 km/km2 (800 miles/mile2) in Badlands at Perth Amboy,
New Jersey  (Schumm, 1956).  In general, according to Strahler  (1964), low
drainage density is found in regions of highly resistant or highly permeable
subsoil materials, under dense vegetative cover, and where relief is low.
High drainage density is favored in regions of weak or impermeable
materials,  sparse vegetation, and mountainous relief.

     Some typical values of drainage density for various locales  in the U.S.
are given in Table III-7.  Local drainage density figures may  be  obtained
from agencies such as the U.S. Geological Survey and the Army  Corps of
Engineers.

                                   197

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                              TABLE II1-7

                  TYPICAL VALUES OF DRAINAGE DENSITY
Location
Drainage density
2 2
km/ km mile/mile
Reference
Appalachian Plateau
  Province

Central and eastern
  United States

Dry Areas of the Rocky
  Mountain Region

The Rocky Mountain Region
  (except the above)

Coastal ranges of
  Southern California
Badlands in South Dakota

Badlands in New Jersey
1.9-2.5
  5-10
 31-62
3.0-4.0
Smith (1950)
8.0-16.0     Strahler (1952)
 50-100
5-10
12-25
125-250
183-510
8.0-16
20-40
200-400
310-820
Melton (1957)


Melton (1957)


Smith (1950)
Melton (1957)
Maxwell  (1960)

Smith (1958)

Schumn (1956)
                                 198

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     Measurements of drainage density can be made from a topographic map
with a planimeter and chartometer.  Care must be taken to include all
permanent stream channels to their upper ends by checking in the field or
with aerial photographs to verify topographic maps.  A rapid approximation
method for determining drainage density is suggested by Carlston and
Langbein (1960).
3.2.1.3  Limitations and Accuracy of Sediment Loading Equation

     The USLE predicts  soil  losses from sheet and rill erosion.  It does not
predict sediment from gullies, streambank erosion,  landslides, road ditches,
irrigation, or from wind erosion.  The USLE was developed primarily for
croplands,  and has been chiefly  based upon experimental plot data from the
areas east  of the Rocky Mountains.  The loading function therefore is best
defined for these areas of  use.  For croplands  in the western  United States
and  sources outside agriculture  such as silviculture, construction, and
mining, the factors have not  been systematically developed, which seriously
affects the ease of using the USLE for such sources.

     The USLE was developed primarily as  a means of predicting annual
erosion losses.  Although several methods have  been proposed for using it to
calculate  losses from individual events the MUSLE (Williams, 1975) presented
later in this chapter is recommended.

     The  loading function (Equation III-l) and  supporting data in tables and
figures were designed to predict longterm average loadings for specific
conditions. Sediment loading for a specific year may be substantially
greater or  smaller than the annual averages because of differences in
number, size, and timing of erosive rainstorms, and in other weather
parameters.  Table II of USDA Agriculture Handbook  282 (1965)  contains a
listing of  50, 20, and  5 percent probability values of R factor at 181 key
locations  in the area east  of the Rocky Mountains.  These may  be used for
further characterization of soil-loss hazards.
                                  199

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     Because of year to year variations in climate and management factors,
the average soil loss predicted by the USLE may be different from that
occurring in any given year.  Onstad et _al_.  (1979) evaluated the precision
of the USLE factors.  The results (Table 111-8) show that C is the most
variable parameter followed by K, R, L and S.  When the coefficients of
variation for each parameter where used in an error propagation exercise, it
was found that the coefficient of variation of soil loss prediction was
roughly 107 percent.
                               EXAMPLE III-1<
              Assessing Sediment Loading from Surface Erosion

     The watershed of interest has an area of 830 acres.  It is located in
Parke County, Indiana.  Compute sediment loading from the watershed from
sheet and rill erosion in terms of average annual loading.

Basic Information

     Land use types:
       •  Cropland
       •  Pasture
       •  Woodland

Delivery ratio:  60 percent

     Land information:  (Cropland - 180 acres)
       •  Continuous corn on contours
       •  Conventional tillage, average yield,   40 to 45 bu
       •  Cornstalks are removed after harvest, winter crop seeded
       t  Spring turn plowed
       •  Soil - Fayette silt  loam
       •  Slope - 6 percent
       •  Slope length - 250 ft
                                       200

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ISJ
o
                                                         TABLE  III-8


                                         EROSION EQUATION FACTOR PRECISION ERROR
Factor

Rainfall factor (R)
Soil credibility (K)
Cropping management
factor (C)
Slope steepness (s)
Slope steepness factor (S)
Slope length (1)
Slope length factor (L)
Number
Reps

22 yr
4 to 20 loc.
4 to 20
single plots
3

3

of
Treatments

42 loc.
14 soils

5 rotations
29

6

Range of
means

57-231
0.11-0.41

0.01-1.40
1.0-46.3
0.02-16.1
50-148
1.5-1.6
Coefficient
of Variation
I
34
39

92
4
5
38
19
          Source:   Onstad,  et  al.,  1979

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     Pasture:   (220  acres)
       •  No appreciable  canopy
       •  Cover at  surface  -  grass  and  grass!ike  plants
       •  Percent of surface  or ground  cover  -  80 percent
       •  Soil  - Fayette  silt loam
       •  Slope - 6  percent
       •  Slope length -  200  ft

     Woodland:   (430 acres)
       •  Medium stocked
       •  Percent of area covered by tree canopy - 50 percent
       •  Percent of area covered by litter - 80 percent
       •  Undergrowth - managed
       •  Soil  - Bates silt loam
       •  Slope - 12 percent
       •  Slope length -  150  ft

     Solution:
     Cropland:
         R   =
         K   =
         LS  =
         C   =
         P
         S   =
200 (Figure III-2)
0.37 (USDA-SCS)
1.08 (Figure III-8)
0.49 (Table III-2)
0.50 (Table III-6)
0.60
Calculate average annual loading per acre.
             Y(S)     ,  = 200 x 0.37 x 1.08 x 0.49 x 0.50 x 0.6
              x  'annual
     Pasture:
         R   =
         K   =
         LS  =
         C   =
         P   =
                        =  11.7 tons/acre-year
200
0.37
0.95
0.013 (Table III-3)
1.0
                                        202

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            =  0.60
           Y(S)
               annual
     Woodland:
         R   =
         K   =
         LS  =
         C   =
         P   =
         S   =
      = 200 x 0.37  x  0.95  x  0.013 x 1.0 x 0.6
      - 0.548 tons/acre-year =  1,100 Ib/acre-year
200
0.32
2.75
0.003 (Table III-4)
1.0
0.60
            Y(S)
                annual
        = 200 x 0.32 x 2.75 x 0.003 x 1.0 x 0.60
        = 0.3168 tons/acre-year
Calculations of Gross Loading

     Average annual:
         Cropland - 180 acres x 11.7 tons/acre-year
         Pasture - 220 acres x 0.55 tons/acre-year
         Woodland - 430 acres x 0.32 tons/acre-year
                   Total
                  Y(S)[
= 2114 tons/year
=  121 tons/year
=  138 tons/year

= 2374 tons/year
                            END OF EXAMPLE III-l
3.2.2  Single Event Sediment Loads

     Soil erosion is governed by two processes:   detachment of soil  fines
and transport of soil fines to the receiving water body.   Detachment of soil
fines can be accomplished by erosive rainfall or by shear forces at  the soil
surface created by surface runoff.  One of the shortcomings of the USLE is
that it does not explicitly consider transport nor detachment by runoff.
Williams (1975) modified the USLE by replacing the "R" factor with a "runoff
                                       203

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energy" factor to provide more accurate sediment loss prediction for single
storm events.  In addition this modification eliminates the need for the
sediment delivery ratio.  The form of this modification is

                         Y(S)£ *  95  (Vq  )°-56 KLSCP                   (HI-3)

where
     Y(S)F  = sediment  yield  in tons  per event
     V      = volume of runoff  in  acre-feet  and
     q      = peak  flow rate  in cubic feet per  second

 Other  terms are  as  previously  defined.

      Alternatively the modified  USLE (MUSLE) can be expressed
 in metric units  as
                        Y(S)E  =  11.8 (Vqp)0'56 KLSCP                  (III'

 where
      Y(S)r = sediment yield in tonnes
      V     = volume of runoff (m3)and
      q     = peak runoff rate (m3/sec)

      In order to use MUSLE the terms V and qp must be evaluated.  This  is
 most conveniently accomplished using the Soil Conservation Service  runoff
 curve number method (Mockus, 1972).
  3.2.2.1   Evaluation  of  Total  Storm  Runoff

       The depth  of runoff from the watershed  area is  estimated by the
  following Equation:

                            Q  = (R-0.2S)2/(R+0.8S)                    (III-5)
                                    204

-------
where
     Q  = the depth of runoff from the watershed area (in,  cm)
     R  = the total storm rainfall (in, cm) and
     S  = water retention parameter (in, cm).

     The storm runoff volume can be calculated by
                                       W

where
     V   =  total  storm runoff volume  (acre-ft, m3)
     a   =  a   units conversion, 0.083  English, 100 metric
     A   =  watershed  area  (acres,  ha)
       w
     Q   =  depth  of runoff (in,  cm)

 S,  the  watershed retention parameter,  is  calculated  using

                          s  , (l°°°  .  10)  . a                        (ni-7)

 where
      CN  = the SCS Runoff Curve Number (dimensionless)  and
      a   = 1.0 English, 2.54 metric.

      Runoff curve numbers are dependent upon antecedent soil water
 conditions, the relative permeability of the soil  and vegetation cover and
 management factors.   Table III-9 gives runoff  curve numbers for various
 combinations of the above factors.  The table  is used by first determining
 the hydrologic  soil  group.  Descriptions of each group are located at the
 bottom of the table.  Next, move to the proper row for the crop/management
 scheme.  Within each crop/management scheme a subrow labeled Hydrologic
 Condition is found.   The qualifiers "good", "fair", or "poor" indicate
 relative management conditions.  For instance, under the crop management
 scenario  "small grains",  "contoured",  a  "poor" hydrologic condition would be
 a  poor stand of vegetation with  breakthroughs in the contours both of which
 would  increase  surface runoff.
                                      205

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                                          TABLE  III-9

           RUNOFF CURVE  NUBERS  FOR  HYDROLOGIC  SOIL-COVER  COMPLEXES

              (FOR ANTECEDENT RAINFALL  CONDITION II)
Hydro! ogic
Land Use
or Cover
Fallow
Row crops





Small grain






Close-seeded
legumes or
rotation
meadow


Pasture or
range




Meadow
(permanent)
Woods
(farm woodlots)

Farmsteads
Roads and
Treatment
or Practice
Straight row
Straight row
Straight row
Contoured
Contoured
Terraced
Terraced
Straight row
Straight row
Contoured
Contoured
Terraced
Terraced

Straight row
Straight row
Contoured
Contoured
Terraced
Terraced



Contoured
Contoured
Contoured







Hydrologic
Condition
—
Poor
Good
Poor
Good
Poor
Good
Poor
Good
Poor
Good
Poor
Good

Poor
Good
Poor
Good
Poor
Good
Poor
Fair
Good
Poor
Fair
Good
Good

Poor
Fair
Good
—
—
A
77
72
67
70
65
66
62
65
63
63
61
61
59

66
58
64
55
63 /
51
68
49
39
47
25
6
30

45
36
25
59
74
B
86
81
78
79
75
74
71
76
75
74
73
72
70

77
72
75
69
73
67
79
69
61
67
59
35
58

66
60
55
74
84
Soil Group
C
91
88
85
84
82
80
78
84
83
82
81
79
78
t
85
81
83
78
80
76
86
79
74
81
75
70
71

77
73
70
82
90
D
94
91
89
88
86
82
81
88
87
85
84
82
81

89
85
85
83
83
80
89
84
80
88
83
79
78

83
79
77
86
92
  right-of-v/ay
  (hard  surface)
*Soil  Group                                          Description

    A                Lowest Runoff Potential:  Includes  deep sands with very little silt and clay,
                      also deep, rapidly permeable loess.

    B                Moderately Low Runoff Potential: Mostely sandy soils  less deep than A, and
                      loess less deep or less aggregated  than A, but the group as a whole has above-
                      average infiltration after thorough  wetting.

    C                Moderately High Runoff Potential:   Comprises shallow soils and soils containing
                      considerable clay and colloids, though less than those of group D.   The group
                      has below-average infiltration after presaturation.

    D                Highest Runoff Potential:  Includes  mostly clays of high swelling  per cent, but
                      the group also includes some shallow soils with nearly irperr.eable  subhorizons
                      near the surface.


Source:   Scf~>w3b et ^1.  , 1955
                                           206

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     The intersection of the crop/management/condition row with  the
hydrologic soil group column is the curve number for this watershed.   This
table is, however, for antecedent soil moisture condition II.   To account
for very wet or very dry antecedent conditions the curve number is
multiplied by the appropriate correction found in Table 111-10.
3.2.2.2  Estimation of Peak Storm Runoff

     In order to estimate peak storm runoff a hydrograph shape must be
assumed.  Commonly, a triangular or trapezoidal shape is used.  A
trapezoidal hydrograph is used here.  The equation for the peak runoff rate
is
                                   a A,  R  Q
                             q  = ___w	_                        (IH-8)
                              P  Tr (R-0.2S)
where
     q  = the peak runoff rate  (ft3/sec, m3/sec)
     A  = watershed area (acres, ha)
     R  = total storm rainfall  (in, cm)
     Q  = storm runoff depth  (in, cm)
     Tr = storm duration (hr)
     a  = a units conversion  constant 1.01 English, 0.028 metric.

For  the development of the above equation see  Haith (1980).
                               EXAMPLE  III-2
           Assessing Single  Event Sediment Loads and Storm Runoff

     The 180 acres  (72.8 ha) of cropland  in the previous example will be
considered here.  The USLE parameters are the same.  Assume a 4.5 cm rain
falls  in a 3 hour period in  early June.   The soil hydrologic condition is
good and the soils  are  in hydrologic group A.  This particular storm was
preceded by 4 cm (1.6 in) in the previous five-day period.  Calculate total
storm  runoff and sediment yield.

                                 207

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                      TABLE  111-10
           ANTECEDENT RAINFALL CONDITIONS  AND CURVE

                   NUMBERS (FOR I  =0.2S)
                                 a
Curve Number
    of
Condition II
              Factor to  Convert Curve  Number
                     for Condition  II  to
           Condition  I
       Condition  III
10
20
30
40
50
60
70
80
90
100
Condition
I
0.40
0.45
0.50
0.55
0.62
0.67
0.73
0.79
0.87
1.00
General Description
Optimum soil condition
2.22
1.85
1.67
1.50
1.40
1.30
1.21
1.14
1.07
1.00
5-Day Antecedent Rainfall
in inches
Dormant Growing
Season Season
<0.5 <1.4
    II

   III
 from about lower plastic
 limit to wilting point

Average value for
 annual floods

Heavy rainfall or light
 rainfall and low tem-
 perature within 5 day
 prior to the given storm
0.5-1.1
1.4-2.1
Source:   Schwab et. al.,  1956
                           208

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Solution:

     First the total storm runoff volume will be estimated.   The curve
number from Table III-9 is (row crops, contoured, good, A) 65 since
antecedent rainfall (growing season) is between 1.4 and 2.1  inches the
antecedent condition is II and no correction is needed.  Therefore using
Equation III-7,
                                 Oj  •  2.!
                               -  10   • 2.54 =  13.68
                         \ UJ

 Using Equation  III-5


               Q =[4.5 - 0.2 (13.68)]2/[4.5 + 0.8 (13.68)]
                 = 0.20


 The  storm runoff volume is  (Eqn.   III-6)

                           V = 100 (72.8) (.2)
                             = 1456 m3

 Now  the peak  runoff  is estimated  from Equation  III-8

                      q  = 0.028  (72.8)  (4.5 }_(Q.2Q]_
                           (TTT475  - 0.2  T13.68J]
                         = 0.35 m3/sec

 The  watershed sediment yield  for  the storm  is (Eqn.   III-4)

           Y(S)E  =  11.8 [1456  (.35)]0'56  (.37) (1.08)  (.49)  (.60)
                 =  45.5 tonnes  -  sediment

.	 END  OF  EXAMPLE  111-2-	
                                   209

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3.2.3  NITROGEN LOADING FUNCTION

     While the complex interactions in soil,  air,  water and  plants are
reasonably well understood,  methods for quantifying movements within the
system are still in the research stage.  Methods which are suitable for
general use often oversimplify the problem.  They must be used with
discretion and may be inadequate in certain cases.  For instance, it is not
presently possible to describe leaching processes for soluble forms of
nitrogen in a simplified manner.  The nitrogen loading function assumes that
erosion is the primary N source for cultivated land.  The loading functions
exclude leaching losses, and predict the amount of total nitrogen that is
released to surface waters by runoff and erosion.  For predicting N and P
loads from forested areas see Section 3.2.7.
3.2.3.1  Nitrogen Loading Function for Erosion Loss

     The nitrogen loading due to erosion is computed as:

                 Y(NT)E  =  a •  Y(S)E •  C$(NT)  •  rN                  (III-9)

where
     Y(NT^ = total nitrogen loading due to erosion, (kg/yr or event,
              Ib/year  or  event)
     a      = dimensional constant (10 for metric  units, 20 for English
              units)
     C  (NT) = total nitrogen concentration in soil, g/100 g
       O
     Y(Sl   = sediment loading  from  surface erosion, (MT/year or  event,
              tons/year  or  event)
     r      = nitrogen enrichment ratio

     Available  nitrogen  can  be  obtained by using  a fraction fN which is  the
ratio of available  N  to  total N loss predicted by erosion.  Thus,  the
available  nitrogen  load  is

-------
                            Y(NA)E =  Y(NT)£  .  fN                    (111-10)
3.2.3.2  Evaluation of Parameters in the Nitrogen Loading Function

     In the erosion nitrogen loading function three parameters must be
evaluated.  The value of Y(SL  comes from the USLE or MUSLE depending upon
whether long term or single event-loads are being estimated.

     Values of the nitrogen enrichment ratio r.,  are shown in Table 111-12.
These values range from roughly 2.0 to 5.0.  It is generally higher on sandy
soils and lower on finely divided highly credible soils.  The enrichment
ratio represents the effects of several processes which cause the nitrogen
content of the eroded soil to be higher than the source soil back in the
watershed.  This is mainly due to preferential detachment and transport of
smaller soil particles which have higher N associated with them.

     The  user may want to use a low and a high value for K.  to evaluate a
range of  erosion nitrogen losses.  The enrichment ratio is quite variable
with regard to management practices even for the same soil type.

     The  enrichment ratio also varies from storm to storm and within storms.
Menzel  (1980) found that r., varied  logarithmically with sediment  loss.  His
equation  is

                       In [rN]  =  2.0 + 0.20 ln[Y(S)£]                 (III-11)

where
    Y  is  the sediment  loss  in  (Kg/ha).

     This equation can be used only on a per event basis.

     The  value of  CS(NT)  in the plowed  layer of  soil  is variable  from
location  to  location  and from  season  to season.   Estimates  of native soil
nitrogen  in  the U.S.   indicate a range  between 0.02 and 0.4 percent  (Jenny,
1930).  Parker e_t  at.   (1946)  published a  map showing the nitrogen content
in  the  top 1-ft layer  in the U.S.   (Figure  111-10).   Data in  this figure

                                  211

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        TABLE 111-12



ENRICHMENT RATIOS FOR NITROGEN
Soil

Collington
Sandy Loam



Almena Silt Loam
Fayette silt Loam
Silt loam soils
Conditions Slope
Prevailing Practice
Conservative Practice
Control, Total N 3.5%
Cover crop
Manure
Cover & manure
Total N
Total N 3.0%
Total N 11.0%

rN
1.74
2.08
3.88
4.09
4.28
3.35
5.0
1.34
1.08
2.7
Reference
Stoltenburg &
White (1953)
Knoblauch,
Ko Today and
Brill (1942)


Neal (1944)
Massey, Jackson
& Hays (1953)
Massey & Jackson
                                          (1952)
              212

-------
ro
i—•
CO
                                                                                                     NITROGEN


                                                                                                     Percent N


                                                                                                     Highly Diverse
                                                                                                     Insufficient  Data


                                                                                                     Under 0.05


                                                                                                     0.05-0.09



                                                                                                 I'vfl 0.10-0.19


                                                                                                     0.20 and Over
                    FIGURE  111-10  PERCENTAGE  NITROGEN (N)  IN SURFACE FOOT  OF SOIL (PARKER, EJ_ AL,,  1946)

-------
should be viewed in general terms;  for specific sites, local sources such
as ASCS and SCS Soil Survey should be consulted.

     Precipitation also contributes to the soil nitrogen.  Atmospheric
nitrogen extracted by soil microbes becomes incorporated into soil organic
matter.  Animal manures, crop residues, and other wastes contribute
significant amounts of nitrogen to the soil.  Jenny (1930) expressed the
nitrogen content of the soil in terms of temperature, T, and a humidity
factor, H. Jenny's equation is:
                    CS(NT)  =  0.55/0-081" d-e-0'005")                 (111-12)
 where
      P       =  precipitation, mm/year
      CS(NT)  =  concentration of  soil nitrogen, g/100 g
      T       =  annual  average temperature,  C
      RH     =  relative  humidity,  percent
      SVP.    =  saturated vapor pressure at given  temperature,
               mm  of  Hg

 Equation  111-14 shows the  relation  between SV?t  and T  (Gladstone,  1946).

                     SVPt = 10   [9-2992 -2360/(273 + T)]              (III

      The  solution of Equation  111-12  is  shown graphically  in  Figure  III-ll.
 The value of humidity factor, H,  can  be  determined from Equations  111-13  and
 111-14.  A nomograph solution of  H  is shown  in Figure  111-12.   For given
 values  of precipitation, relative humidity and temperature,  the value  of  H
 can be  quickly and accurately established from Figure  111-12.   For example,
 given P,  = 500 mm/year  (19.7  in/year), RH , = 60  percent,  and
 T.  = 5  t  (41 F),  the value of  H factor can be determined as  follows:   using
 a straight-edge ruler,  align  Pj and RH ^  to intersect  on the  index  line at
 "A" as  shown on the inset  of  Figure 111-12.   Align "a" with  T  on  the
                                   214

-------
     0.01
              100    200     3OO    400     500
                         H. Humidity Factor
600    700
FIGURE III-ll  SOIL NITROGEN vs,  HUMIDITY FACTOR AND TEMPERATURE
                             215

-------
ro
80 -t- 2000
70-
60-
50-
40-
30 i

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8'.8-
0.7-
0.6-
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- •
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-1000 I
- 800
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- 600
-500

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-10

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" " ( 1 - RH/KX))SVPT
F9299- 236°1
SVPT=IOL 273TT]
where


H = Humidity Factor
P = Precipitation, mm/yr
RH = Relative Humidity, Percent
SVPy= Saturated Vapor Pressure at
Given Temperature, mm of Hg
T = Average Temperature, °C


P! S^Q
xT
^s.
RH|
A. Aleti


|HI 1




Midwest Research Institute -
0.4 -1— IU iv



Ti
1 1



8/75

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e
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                                   FIGURE 111-12  NOMOGRAPH  FOR  HUMIDITY  FACTOR,  H

-------
temperature scale to intersect the H scale.  The result on the H scale is
194.

     Data in Figure 111-10 may be used as a check on current data.
Equations 111-12 and 111-13 may be used to calculate nitrogen content of
soil more precisely if necessary data are available for using these
equations.  Again data from State Agricultural Experiment Stations, and SCS
Soil Surveys are much more dependable than the above equations and should be
consulted whenever possible.

     The fraction of available nitrogen (f ) or that nitrogen which can be
directly used by plants is usually considered to be the NH4+ + NOs fraction.
The erosion nitrogen load which consists primarily of organic N bound in
detritus does not necessarily correlate well with the NH4  or NOs  load
especially in areas with  low surface runoff and sediment loss.  Forms of
nutrients on the watershed surface will vary with

     1.  amount  and type  of plant residue  remaining in the field
         (Timmons et aj_., 1970)

     2.  land use (Logan, 1980)

     3.  application of manures and fertilizers (Reddy, 1980) and

     4.  type of tillage  management  (Frere, ejt  aj_., 1980)

It  is  suggested  for screening purposes that the user rely on  total N  load
estimates.
3.2.4   PHOSPHORUS  LOADING  FUNCTION

     Phosphorus  occurs  naturally  in  soil  from  weathering  of  primary
phosphorus-bearing  minerals  in  the parent material.   Additions  of  plant
residues  and  fertilizers by  man enhances  the phosphorus content  of the
surface soil  layer.
                                   217

-------
ro
1—>
CO
                                 \
PHOSPHORIC ACID


 Percent P2®5


     0.0-0.04


     0.05-0.09


     0.10-0.19


     0.20-0.30
                         FIGURE 111-13   PHOSPHORUS CONTENT IN THE TOP 1  FT OF SOIL (PARKER, ET_  AL,, 1946)

-------
     Phosphorus in soils occurs either as organic or inorganic phosphorus
The relative proportion of phosphorus in these two categories varies widely.
Organic phosphorus is generally high in surface soils where organic matter
tends to accumulate.  Inorganic forms are prevalent in subsoils.  Soil
phosphorus is readily immobilized due to its affinity to certain minerals.
In strongly acid soils the formation of iron and aluminum phosphates, and in
alkaline soils, the formation of tricalcium phosphate reduces the
availability of soil phosphorus.  Once it enters a stream, the partioning of
phosphorus between the sediment and solution phases becomes significant in
the nutrition of aquatic microorganisms.

     Phosphorus transport from a given site to a stream can occur either by
erosion or by  leaching.  The predominant mode of transport is via soil
erosion.  The  soil solution usually contains less than 0.1 yg of phosphorus
per milliliter;  the leaching  losses are thus extremely low even in
well-drained soils.  Exceptions are sands and peats which have  little
tendency to react with phosphorus.

     The loading function for  phosphorus is based on the  soil erosion
mechanism.  The loading function is:

                        Y(PT)  - a-Y(S)E.Cs(PT).rp                    (111-15)

where
     Y(PT)  =  total phosphorus  loading,  (kg/year, Ib/year)
     a      =  a dimensional constant  (10 metric, 20 English)
     Y(S)   =  sediment  loading,  (MT/year, tons/year)
     CJPT) =  total phosphorus  concentration  in  soil, g/100 g
     r      =  phosphorus enrichment ratio
 Available  phosphorus  may be  computed  as  in  Equation  III-ll:
                             Y(PA) = Y(PT)-f                         (111-16)
                                  219

-------
where
     Y(PA)  = yield of available phosphorus, (kg/year, Ib/year)
     f      = ratio of available phosphorus to total  phosphorus
3.2.4.1  Evaluation of Parameters in the Phosphorus Loading Function

     As with the nitrogen erosion loading equation two parameters must be
evaluated - the soil concentration of total P and the phosphorus enrichment
ratio.  The sediment load, Y(S) , is known from previous analysis.

     Local sources should be consulted in preference to using the estimates
of CS(PT) in Figure 111-13.  The Soil Conservation Service or agriculture
extension personnel will be the best sources of this information.

     Table 111-13 shows enrichment ratios for phosphorus found in the
literature.  On the whole r  is slightly less than r  having values of about
1.0 to 4.0.  Sharpley (1980) and Menzel (1980) have both used equations of
the form
           ln[r ] = a + b In [Y(S)r]
               P                  h
                                                                    (111-17)
     where
     a = 2.48
     b = 0.27
     a = 2.0
     b = 0.20
(Sharpley, 1980)
and
Menzel (1980)
to predict enrichment ratios for individual storm events.

     As with nitrogen the available to total P ratio varies with soil type,
crop type and management practice.  Users should use total P in subsequent
analyses whenever possible.
                                   220

-------
         TABLE 111-13



ENRICHMENT RATIOS FOR PHOSPHORUS
Soils
Conditions
Slope
Prevailing Practice


Collington

Sandy
Loam

Conservative
Check plot

Cover crop
Manure

Practice
3.5%



Manure & cover crop


Almena silt loam

Fayette silt loam


Dun™ re silt loam



Total P
Available P
Available P

Available P


Available P

Available P
Available P


corn oats 3.0
of a
corn-oats 11.0%
hay-hay
rotation
Wheat) dilute 5-25%
|H2S04
Corn ' sol uble

r
P
1.82

2.03
1.59

1.56
1.47
1.47
3.1
0.99
1.92

2.20


3.74

1.79
3.4
Reference
Stoltenberg &
White (1953)

Knoblauch,
Ko Today &
Brill (1942)


Neal (1941)

Massey, Jackson
& Hays (1953)



Rogers (1941)


Massey & Jackson
                                            1952
                221

-------
     Schuman,  ejt al_.  (1970)  have reported  an  empirical  relation  between
sediment phosphorus (concentration in ppm,  C  (PT)  and  soluble  phosphorus
                                           O
(concentration in ppm,  C (P) )  for Iowa soils.   The relation may be stated
as:
                            CQ(P) = a + b-C$(PT)                    (111-18)
where a and b are regression coefficients.  The reported values of a and b
are 0.018 and 0.047, repectively.  Equation 111-18 shows that the ratio of
solution phosphorus to sediment phosphorus is just under 1 to 20.

     Taylor (1967) suggested that about 10 percent of the total phosphorus
in eroded soil  is ordinarily available for aquatic plant growth.  However,
some values as  high as 20 to 30 percent have been suggested.
 3.2.5   Organic  Matter  Loading  Function

     The loading  function  is:

                         Y(OM)E =  a-Cs(OM).Y(S)E.rOM                  (111-19)

 where
     Y(OM)   = organic  loading, (kg/year,  Ib/year)
     a      = a dimensional  constant (10  metric,  20  English)
     CJ(OM) = organic  matter concentration of soil,  g/100 g
      Y(SL   = sediment loading, (MT/year, tons/year)
      rOM    = enrichment ratio for organic matter in eroded  soil


 3.2.5.1  Evaluation of Parameters in the  Organic Matter Loading Function

      The value of Y(S)E can be obtained from procedures discussed
 previously.  The value of C$(OM) should be obtained preferably from current
 or historical data for a given area, (e.g.  from the extension service).
 For approximate values, CJOM) may be taken as equal to 20 x CS(NT), where


                                    222

-------
       is the total  nitrogen concentration in the soil (Buckman and
Brady, 1969).

     The enrichment ratio for organic matter rQM has a range of 1 to 5 being
higher on sandy soils and lowest on finely divided highly erodible mineral
soil  (McElroy et al_., 1976).  Foster (1980) gives a range of rQM of 1.2 to
4.4.  Frequently it is assumed that rQM is that of the clay enrichment
ratio.   The data of Leonard et §_]_. (1979) show that  this was approximately
the case for four watersheds in the Piedmont region of Georgia.  Enrichment
rations for organic matter found in the literature are shown in
Table 111-14.

      Obviously, the effects  of management  practices can  be pronounced  on
r.  One would expect higher rgM  with practices  such  as residue cover and
slope reduction.  In general, practices which  reduce  runoff velocities and
rainfall detachment probably increase  r.
                                EXAMPLE II1-3
                      Example of Loading Computation for
                     Nitrogen, Phosphorus,  Organic Matter

      The watershed used in Example III-l (Section 3.2.4) for Parke County in
 Indiana will  be used to illustrate the methodology presented in this section
 for computing pollutant loads.  Computation of available nitrogen, available
 phosphorus,  and organic matter annual loads is required:

      The following data, plus soils data,  are required:
           Soil nitrogen content.
           Soil phosphorus content.

      The preferred source of data is local records.  Jenny's equation
 (Equation.  111-12) and Figure 111-13 are alternate sources from which
 general values may be estimated.
                                     223

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                                 TABLE 111-14

               ENRICHMENT RATIOS FOR ORGANIC MATTER IN  SURFACE  RUNOFF
Soil
CoTlington Sandy
Loam




Almena Silt Loam
Conditions Slope
Check plot 3.5%
Cover crop
Manure
Cover + manure
Prevailing Practice
Conservation Practice

Corn oats of a corn 3%
oats-hay-hay rotation
r
Offi
4.13
4.48
4.23
3.97
1.24
1.38
4.7
4.6
Reference
Knoblauch,
Koloday
and Brill
(1942)


S to. 1 ten berg &
White (1953)
Neal (1944)
Massey,
Jackson &
Hays (1953)
 Fayette Silt Loam


 Silt Loam Soils


 Sandy Loam Soils
Corn oats of a corn     11%
oats-hay-hay rotation
Contoured (PI)           2-5%
                        Countoured (P2)           2-4%

                        Terraced w/grassed (P3)   1-2%
                        Waterway

                        Terraced w/grassed (P4)   1-2%
                        Waterway
1.24


1.15


2.6


2.1

2.4


1.9
Massey  & Jackson
(1952)

Leonard,
Langdale &
Fleming(1979)
* Values are averages for 4, 1, 3 and 1 surmier storm(s) respectively for PI.
  P2, P3, P4 watersheds.
                                       224

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Nitrogen Loading

     Using the following data, soil nitrogen content is calculated:

     Average annual temperature = 10°C
     Average annual precipitation = 96.5 cm
     Average annual relative humidity = 70 percent

     Using the nomograph given in Figure 111-12, the value of the H factor
is determined to be 350.  From Figure III-ll, and using H = 350 and
T = 10°C, the value of C_(NT), the soil nitrogen content is estimated to be
0.204 percent or 0.204 g/100 g.  Using Equations III-9 and 111-10 and rN =
2.0,
                         Y(NA)E  =  20-Y(S)E  0.2-2.0
                                =  8-Y(S)E
      The  values  of  area!  sediment yield  as  given  in  Example  III-l  are  shown
 below in  Table  111-15.

 Phosphorus  Loading

      Assuming C  (PT)  =  0.15 g/100 g for  the area  and r  = 1.5,  equation
 111-10 gives


                         Y(PA)E = 20-Y(S)E-0.15.1.5
                                - 4.5 Y(S)£

 Organic Matter Loading

      Using  Equation 111-19, data for CS(OM), Y(S)E,  rQM are needed.

      Assume that the value of CS(OM)/CS(NT) equals 20 and rQM =2.5,
                                     225

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                            TABLE II1-15
       CALCULATED SEDIMENT, NITROGEN, PHOSPHORUS AND ORGANIC
           MATTER LOADS FOR PARKE CO., INDIANA WATERSHED
Land Use
Sediment
   Load (tons/year)
 Total            Total          Organic
Nitrogen	Phosphorus      Matter
Cropland
Pasture
Woodland
  2530
   121
   430
  10.1
   0.5
   1.7
5.7
0.3
1.0
253
 12
 43
Total
  2797
  12.3
7.0
308
                                   226

-------
                     Y(OM)E = 20-2.5-Y(S)E-20-Cs(NT)
                            - IOOO-CS(NT)-Y(S)E
Us
ing Cc-(NT) = 0.2 percent.
                             Y(OM)E =200 Y(S)E
     The values for nitrogen, phosphorus organic matter  loading  are  also
presented  in Table  111-15.
                             END  OF  EXAMPLE  III-3
 3.2.6  Accuracy  of  Nutrient  and  Organic  Matter Loadj_n_g_s__fV_qm_Er_qs_i_on

     The  accuracy  of  a  prediction using  loading functions  depends upon the
 accuracy  in  predicting  sediment  loading, watershed concentration (or
 availability)  of a  pollutant,  and its enrichment  in eroded sediments.

     Predicting  sediment loss  has been and continues to be a problem in Doth
 hand calculation methods and computer models.   Prediction  of sediment loads
 is  generally better for longer periods;   that  is, annual  predictions are
 better than  seasonal  predictions which are better than for single storm
 events.   Storm event sediment  loads are  particularly a problem for hand
 calculation  methods such as  the USLE but the use  of MUSLE improves the
 accuracy.

     Aside from sediment load  prediction, the dynamic surface concentration
 of  nutrient  forms is also difficult to estimate unless computer simulation
 techniques are used.   Frere  et aj_. (1980) have indicated that typical values
 for soil  nitrogen and phosphorus vary from 6 to 10 fold.
                                   227

-------
     Since most enrichment ratios observed for organic matter,  N and P have
values between 1 and 5, their estimation seems the least critical  of the
three parameters of the loading function.

     Total nutrient losses for N and P are among the most accurate for
agricultural watersheds.  This is primarily because most of the N lost is
organic which is bound to fines or is itself detrital.  Similarly, P is
mostly particulate in cultivated watersheds.  The prediction of individual
forms of either N or P is less accurate because of the chemical
transformation which must be considered and is impractical using hand
calculator methods.

     Table 16 shows the percentage of explained variance for several
parameters by regression on suspended solids from several different parts of
the country.  The information is only for regressions which were linear with
respect to both the independent and dependent variables.  As expected, TKN
and Total P are among the highest, with explained variance decreasing for
more weakly adsorbed constituents.
3.2.7  Nitrogen and P hos phor u s L pad i_n_g F r om F or es ted _Wa t e r s hed s

     Because of the orotection of the soil surface afforded by tree canopy
and tree  litter in forested watersheds, the quantity of soil eroded from the
watershed surface  is generally small.  Contrast the two order of magnitude
differences  in sediment loading between cropland and woodland computed  in
Example III-l.  Hence the mechanism by which nutrients are lost from these
watersheds are guite different from those erosion mechanisms which operate
in agricultural watersheds.  For this reason the erosion loading equations
are not recommended for use in forested systems.

     An empirical  procedure is given below for estimating N outputs for
forested  basins based on precipitation input load.  The equation is
                               Y(N)r = A-N   -b                        (111-20)
                                \  /p      pr                          v       /
                                       228

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                              TABLE 111-16


          VARIATION IN CONSTITUENT ACCOUNTED FOR BY REGRESSION
                 ON SUSPENDED SOLIDS (Linear Models Only)
Constituent
                                   Data Base
Explained
Variance
Nutrients

TKN
Total P
NH^-N
NO^-N
Miscellaneous
                               Watkinsville, GA
                               Buffalo Bill, 10
                               Michigan State, MI
                               Honey Creek, OH

                               Watkinsville
                               Honey Creek

                               Watkinsville
                               Buffalo Bill

                               Watkinsville
                               Buffalo Bill
                               Michigan State

                               Buffalo Bill
                               Michigan State
  37.1
  11.1
   2.1
  19.4

  18.7
  67.9

   6.9
   5.6

  18.5
  15.0
   5.8

  13.8
   0.06
BOD
Iron
Buffalo Bill
Honey Creek
32.0
82.8
Source:  Zison, 1980
                                    229

-------
where
     Y(N)p =  the loading of N from a forested watershed (Kg,  Ib)
     A     =  the watershed area (ha, acres)
     N     =  the input precipitation nitrogen load (kg/ha,  Ib/acre)  and
     b     =  an attenuation factor

An alternative form of Equation 111-20 is

                      Y(N)p = A-C(N)pr-Q(Pr)-b-a                    (111-21)

where
     C(N)    =  a typical N concentration in  precipitation (mg/1)
     Q(Pr)   =  the depth of rainfall over the period (in, cm)  and
     a       =  a units conversion factor
             =  0.23  English  units
             =  0.10  metric  units

     Equation 111-21 should be used if local  and reliable N precipitation
concentration data are available.  If not Equation 111-20 can  be used.   The
map in Figure 111-14 or the data in Table 111-17 can be used to estimate N
in this case.

     The attenuation factor 'b' can be estimated using Table 111-18.  On the
average the attenuation factors for N and P are 0.40 and 0.78  respectively.
The attenuation factors are calculated from the data in Likens, et al.,
1977.


3.2.8  Loading Values for Salinity Loads in Irrigation Return  Flow

     Perhaps the most useful method of establishing salinity loads is
through loading values determined for particular regions.  Lists of such
values are presented in Tables 111-19 through 111-23 for subbasins in  the
Colorado River basin, and for irrigated regions in California.

     Studies in the Twin Falls area and the Colorado River basin indicate
that the range of values for salt pickup from irrigated lands  is roughly 1.3
to 22 MT/ha/year (0.5 to 8 tons/acre/year) (Skogerboe and Law,  1971).   These
                                   230

-------
                                  .3kg/ha/yr
                                           .5 kg/ha/yr
                                                                                             2.0 kg/ha/yr
                         '.0 kg/ha/yr
ro
CO
                                                      1.0 kg/ha/yr  1.5 kg/ho/yr   2.0 kg/ha/yr
                                                                                                       1.5 kg/ha/yr
                                  1.0 kg/ha/yr
                                                                                              1.0 kg/ha/yr

                                                                                               |.5kg/ha/yr
FIGURE  1 1 1-
                                      NITROGEN  (NH^-N AND  NO^-N)  IN PRECIPITATION,  (PERSONAL COMMUNICATION
                                      WITH  MRL J.H,  CRAVENS, REGIONAL FORESTER,  U,S,D,A,-FS EASTERN
                                      REGION, 1974)

-------
                                                       TABLE 111-17
                            ATMOSPHERIC CONTRIBUTIONS OF NITROGEN AND PHOSPHORUS  IN  RAINFALL
ro
CO
ro
N Contribution in Kq/ha/yr
N03-N+NH4-N Total N

Northeastern U.S.
Southeastern U.S.
Midwestern U.S.
West/Southwestern U.S.
United States
Low.
5.7
1.5
0.2
1.7
-
High, Low High.
12.1 5.7 12.1
12.3
20.9 1.7 20.9
5.7 9.0 14.6
-
P Contribution in Kg/ha/yr
Inorganic P Total P
Low^ High. _Lqw Hj^Jl
_
_
- - -
- - -
0.18 0.18 0.08 0.80
          Source:  Weiner, et al.  (1976)

-------
                                                       TABLE 111-18


                         NUTRIENT BUDGETS FOR VARIOUS TERRESTRIAL ECOSYSTEMS OF THE WORLD (kg/ha-yr)
ro
CO
co

la&iM Mill, .^lo.pem
Teryei d Uf_ fcostly coniferous and
evergreen forest

Temperate bcnj vegetation
TropJcJl ingioipprm, mostly
evergreen forest
Tempe ra te ncstly angiospern
ana deciduous forest
TCTiueraU mostly coniferous and
evergreen forest

Temperate bog vegetation
Tropical dngtQspenn mostly




MA| ireta.iorpnic (* refers to subsc
JTo water table


Calculated frun Mg inputs and Na
lNVN *"VN
j
"Wrije for $ yr l'J/1-1975
"Calculated fran B9 cm of precipit
"•Trace •

L OL j 1 1 wn

Hubbard Bruoi, U S
Pago Cdtcnront, Australia
Silverstrean. Nc« Zealand
Tiugrannoa Creek. NT. U S
Walter Srdncn. TE . U S
Blue Rjnge Caurn.*nt, Australia
Boundary haters Canje Area, MlN,
U S (24)
Carnation Creek. Vancouver Island,
Canada
Cedar River. WA. U S
Clear Lake, Ontario, Canada (25)
Finland
Western Cascades Range, OR. U S
Rio Negro, Brazil
Kuokket area. Sweden
Cosnocton. OH, U.S. (2!)
Huboard Brook, U.S
S E. U S.
Stlverstream. New Zealand
Ta-ghannocK Creek, NY, U.S.
Walker Branch, TE , U S
Birkenes Watershed, Norway
Canada
Cedar River, HA, L! S.
ELA, Ontario, Canada
Finland
Storsjon, Sweden
Velen. Sweden
(22) 9
Rough Sike Catchment. England
Rio Negro, Brazil








ation times concentration (0 02 mg P/l , lay)

Precipitation
Input

0 036
0 33
0 I
0 07
0 54
0 39
0 14
0 11
0 35
a i
0 14
0 29P
0 2
0 055*
20
2 2.
9 71
a 7
H.SJ
1 1
6 4
6
8 2
5.6
1 15







or et «1 , 1971)
samples
s<~-
PMsphorus
0 019
0 26
0 03
0 ?0
0 0^
0 42
0 (,15
0 05
0 0?
0 09
0 3
0 Q?
0 51P
0 l'
0 041*
nitrogen
4 O1
1 B.
5 61
1 8
0 9
LV
30f
4 79
097









»-,•;-

• 0 OP
«0 07
• 0 2
-0 13
*0 52
-0 03
tO 13
*0 06
-0 2
*Q 12
-0 22
+0 1
+0 014
ti7 5
*0 4
+ 4 1
*6 9
+ 12 3
»0 5
+5 5
+4
+ 7 7
+5 5
+5 2
+0 9










AM.ual
precipitation,
cat

89
130
150
135
96
155
132
70
315
136
90
57
87
200
213
75
89
130
127
135
96
155
134
136
83
5?
67
72
213
200


, Trp, tropical







DOfftfUAt
vegetation

Ac. F, 6
E
N
Ac, Ti. Ts
g. c
Pin
Pin, Pic, &
At), Ts, Th
Ps
Ac, F, Q
Pin, Pic. B
Pin, Pic

Trp
Ca. En, B
L, Pin
Ac, F. B
Q. Pin
N
Ac. Ti. Ts
0, C
B, Pi Pic
's
-in! c, B
'in, c
1 1 11 , C
Bog
Trp


species
amis tone,
Source Likens






G.OIO,/ Aiteao.l,

Jshr^cr Ss •»
n9;; i" .79
S5hrS ' M M 15
S5' 5hr ir s" l.K
Sjhr c 04
I H 93
'gr S!h "
"9r Hsr "c -'5
Is H .it
Igr M9 16
Iqr M' 3ioo
I9r 9 .14

'cr si sh
S M H .SO
H 75
Grand Avg ,
!"»-«V ^ :!?
$?£«„,„ •»
ssr jhr 9r sh 58
S^ c 21
I 15
S 54
I M 14
I9r H9 .33
,gr 9 23
M9 I 07
,gr 9 6S
't
Scr 5si 5sh X
SShr "«r », «
Grand Avg


ejil (1977)






on Fattur |t<}

Avg 77



- 0 78
Avg - M



= 40










-------
IN3
CO
-p.
                                                          TABLE  111-19


                                   SALT  YIELDS  FROM  IRRIGATION • IN GREEN RIVER SUBBASIN  (EPA,  1971)
Average salt yiel
Area
Green River above New Fork River
Big Sandy Creek
Blacks Fork in Lyman area
Hams Fork
Henry's Fork
Yampa River above Steamboat Springs
Yampa River, Steamboat Springs to Craig
Mill Creek
Williams Fork River
Little Sanke above Dixon
Little Sanke, Dixon to Baggs
Ashley Creek
Duchesne River
White River below Meeker
Price River
San Rafael River
(tons/acre/yr)
0.1
5.6
2.4
0.3
4.9
0.2
0.4
0.1
0.3
0.3
0.5
4.2
3.0
2.0
8.5
2.9
(kq/ha/day)
0.6
34.3
14.7
1 .8
30.1
1.2
2.5
6.1
1.8
1.8
3.1
25.8
18.4
12.3
52.2
17.8
d
(Ib/acre/day)
0.5
30.7
13.2
1.6
26.9
1.1
2.2
5.4
1.6
1.6
2.7
23.0
16.4
11.0
46.6
15.9

-------
                                                         TABLE 111-20
                          SALT YIELDS  FROM  IRRIGATION  IN  UPPER  COLORADO MAIN  STREAM SUBBASIN  (EPA,  1971)
GO
en

Area
Main stern above Hot Sulphur Springs
Main stem, Hot Sulphur Springs to
Kremml i ng
Muddy Creek Drainage Area
Brush Creek
Roaring Fork River
Colorado River Valley, Glenwood Springs
to Silt
Colorado River, Silt to Cameo
Grand Valley
Plateau Creek
Gunnison River above Gunnison
Tomichi Creek above Par! in
Tomichi Creek, Parlin to mouth
Uncompahgre above Dallas Creek
Lower Gunnison
Naturita Creek near Norwood

(tons/acre/yr)
0.3
0.9

2.4
0.7
3.5
2.3

3.5
8.0
0.9
0.3
0.3
0.3
4.5
6.7
2.8
Average salt yield
(kg/ha/day)
1.8
5.5

14.7
4.3
21.5
14.1

21.5
49.1
5.5
1 .8
1.8
1.8
27.6
41.1
17.2

(Ib/acre/day)
1.6
4.9

13.2
3.8
19.2
12.6

19.2
43.8
4.9
1.6
1.6
1.6
24.7
36.7
15.3

-------
PO
00
en
                                                            TABLE 111-21


                                  SALT YIELDS FROM IRRIGATION IN SAN JUAN RIVER SUBBASIN (EPA, 1971)
Average salt yield

Fremont River above Torrey, Utah
Fremont River, Torrey to
Hanksville, Utah
Muddy Creek above Hanksville, Utah
San Juan above Carracas
Florida, Los Pinos, Animas drainage
Lower Animas Basin
LaPlata River in Colorado
LaPlate River in New Mexico
(tons/acre/yr)
0.4
5.8

3.1
2.7
0.2
3.5
1.4
0.3
(kg/ha/day)
2.5
35.6

19.0
16.6
1.2
21.5
8.6
1.8
(Ib/acre/day)
2.2
31.8

17.0
14.8
1.1
19.2
7.7
1.6

-------
                                                        TABLE  111-22
                            SALT YIELDS  FROM  IRRIGATION  IN  LOWER  COLORADO RIVER BASIN  (EPA,  1971)
Average salt yield
Area
Virginia River
Colorado River Indian Reservation
Palo Verde Irrigation District
Below Imperial Dam
(Gila and Yuma projects)
(tons/acre/yr) (kg/ha/day)
2.3 14.1
0.5 3.1
2.1 12.9
variable

(Ib/acre/day)
12.6
2.7
11.5
-

ro
CO
                         TABLE 111-23
SALT YIELDS  FROM IRRIGATION  FOR SELECTED AREAS  IN  CALIFORNIA
               (WATER RESOURCES COUNCIL, 1971)
                                                                        Average  salt yield
                             Area
             North coastal
             Central  coastal
             Sacramento
             Delta-Central  Sierra
             San Joaquin
             Tulare
             Colorado Desert
                            (tons/acre/yr)    (kg/ha/day)      (Ib/acre/day)
                                  0.353
                                  0.808
                                  0.707
                                  0.974
                                  0.827
                                  0.768
                                  10.9
 2.2
 5.0
 4.3
 6.0
 5.1
 4.7
67
 1 .9
 4.4
 3.9
 5.3
 4.5
 4.2
60

-------
values are site specific.   An average salt pickup rate might  be  5 MT/ha/year
(2 tons/acre/year).  On a per day basis,  the range becomes 3  to  50 kg/ha/day
(3 to 44 Ib/acre/day), and the average becomes 12 kg/ha/day (11  ]b/acre/day).

     The most common means of expressing  the salinity of  water is its
electrical conductivity.   Conductivity is the inverse of  resistance (ohms)
and is expressed in units of "mhos".

     The salt pick up in  an irrigation water as it is diverted from a river
through a field and returns to the river  can be measured  by the  change in
the conductivity of the water.  The conductivity of the drainage water can
be determined from the conductivity of the irrigation water and  the leaching
fraction (USDA, 1954) by

                              ECdw= ECiw/(LF)                      (111-22)

where    EC,  = drainage water conductivity (umho)
           dw
         EC   = irrigation water conductivity (umho) and
           iw
         LF   = leaching fraction

     The usual range of the leaching fraction is about 0.1 to 0.3.

     The conductivity of the  irrigation water is related almost  linearly to
the concentration  of the salt.  Thus the concentration of salt can be
determined from the conductivity and vice versa.  The general model is

                                   S = aK                           (111-23)

where
      S   is the dissolved solids concentration (mg/1)
      K   is the conductance  (umho) and
      a   is a regression coefficient

The value of a  is  usually  between 0.55 and 0.75 with higher values generally
occurring in waters  having  higher sulfate concentrations  (Hem, 1970).  An
average  value  is  about 0.63.
                                     238

-------
     Another  important  parameter affecting the quality of water for
irrigation is the sodium adsorption ratio (SAR).   This is defined as
                                       [Na]
                              SAR  = ^__=—                       (111-24)
                                   /[Ca  + Mg]
where

    SAR      is the sodium adsorption ratio (meq/1)

    [Ca+Mg]  is the concentration of calcium plus magnesium in  the
              irrigation water (meq/1) and

    [Na]     is the concentration of sodium in the  irrigation water
              (meq/1)

     The  SAR is  a measure of  the sodium  hazard of  irrigation water  to
plants.   Like the EC,  the SAR of  irrigation drainage  water can  be  calculated
knowing the  SAR  of the irrigation  water  and the  leaching  fraction  (Bower,
et  aj[., 1968)  by
                                     SAR.
                              SARdw = ~~                          (111-25)

where
     dw denotes  drainage water  and
     iw denotes  irrigation  water.

This equation assumes  that  no precipitation  or dissolution of  salts occurs
 in  the soil  during  irrigation.
 3.2.9  Toxic  Chemicals in Agricultural  Environment

      The primary group of toxic chemicals that will  be of concern in
 agricultural  or  forested settings will  be the pesticides including
 herbicides,  insecticides, etc.   Metals  and other organic materials may be a
 problem if municipal  sludges or landfills are of concern.  These problems
 will  not be dealt with in this  text however.   In addition the discussion
                                     239

-------
will be limited to those insecticides occurring on the EPA 129 priority
pollutant list.

     While  pesticides may be lost during application, enter the air and be
diffusely redeposited and washed off the land surface, this mechanism will
not  be  as great a pathway for  loss as washoff from the field surface to
which  the pesticide  is  applied.  It will be  assumed  that  the only  sources  of
pesticides  will be  slug applications to  the  surface  in a  short  time period
following which the  pesticide  will disappear at  some first order rate.   It
 is  important that  the  amount of  pesticide  remaining  on the watershed  surface
 be  known  at the time of the storm  event.   Another important  quantity  to  know
 is  the amount of  pesticide  that  is  adsorbed  onto soil materials versus  that
 quantity which is  dissolved in the soil  solution.  This  ratio  greatly
 affects the amount of pesticide  lost in  the  runoff.   Thus for  toxic
 pollutants  three  key processes must  be described in  order to simulate their
 magnitude  in runoff losses:

      •   the rate at which they accumulate or are deposited at the
          watershed  surface

      •   the rate at which they disappear from the  watershed surface
          and

       •  the  ratio  with which they partition themselves  between the
          dissolved  and sorbed phases.
  3.2.9.1  Disappearance of Pesticides  from the  Watershed  Surface

       Pesticides are lost from the watershed  surface after application
  through several important processes:

       1.  leaching
       2.  runoff
       3.  volatilization
       4.  degradation and
       5.  plant uptake
                                     240

-------
     Pesticides which have low water solubilities and are strongly adsorbed
to soil materials are most resistant to leaching.  Chlorinated hydrocarbons
(e.g.  aldrin, chlordane, DDT, endrin, dieldrin, endosulfan, heptachlor,
toxaphene) fall into these categories.  They tend to be adsorbed
hydrophobically and to a greater extent in soils with high organic carbon
contents.  Nonbiological degradation is thought to be a minor mode of loss
for chlorinated hydrocarbons (El Beit, jet aK,  1981) as well as chemical
degradation.  They are degraded biologically however, especially under
anaerobic conditions (Kaufman, 1974).

     Volatilization is apparently one of the major pathways of loss of
organochlorine pesticides from the soil.  Many factors affect volatilization
rates including sorption, concentration, soil water/air flow rate,
temperature, diffusion and physical and chemical properties of the
pesticides.

     The two factors that most affect plant uptake are polarity and water
solubility (Nash, 1974).  Although polar, the chlorinated hydrocarbons are
relatively insoluble in water and plant uptake is probably not a great
mechanism of loss.

     Usually runoff losses are greatest for those pesticides with long half
lives and those which are strongly adsorbed to soil materials.  These
pesticides tend to remain on the surface for long periods of time where they
continue to be lost in eroded sediments.

     Except for the processes of leaching and runoff losses which will be
described mathematically, this methodology for calculating pesticide runoff
losses will assume that the disappearance of pesticide from the soil surface
is first order.  The rate constant k , for this disappearance is the sum of
the rate constants for all the individual processes of volatilization,
degradation, etc.

     The equation which gives the quantity of pesticide in the soil surface
layer (1 cm) is (Haith, 1980):
                                    241

-------
                              Pt = PTexp [-ks (t-i)]                (111-26)

where
     Pf  is the pesticide remaining on day t

      *
     P   is the amount of pesticide in the soil on the day of the last
      T
         rainfall event or pesticide application event

     ks  is the disappearance rate constant

     t   is the number of the day of the runoff event and

     T   is the number of the day of the last runoff event or
         application event.

     If the event on day t  was a rainfall event then

                       P*  -  PT  -  PXT-  (1-R/RT)DT                    (111-27)

 or  if the  event was a pesticide application

                              P* = P   + AP                           (111-28)
                              T    T     T

 The parameters PX  ,  6, R   and D   are  discussed  in section 3.2.9.3.
 Degradation rate coefficients (ks) can be estimated  for most of  the
 chlorinated hydrocarbons on  the priority pollutant  list by choosing a
 representative value from  either  Table 111-24  or Table 111-25.
 3.2.9.2  Partitioning of Pesticides  between Apjj__anjj _Water

      Sorption refers to the removal  of  pesticide  from  solution  by soil
 materials.   Adsorption mechanisms  on clay minerals  include  cationic  and
 anionic exchange,  hydrogen bonding and  Van der  Waals attraction.   Adsorption
 onto organic matter is a result of cation or  anion  exchange,  hydrogen
 bonding, and/or hydrophobic bonding.
                                     242

-------
                         TABLE  111-24



VALUES OF ks  FOR DISSIPATION  OF PESTICIDES  FROM  SOIL  SURFACES
Pesticide

Aldrin
Aldrin
(+dieldrin)
(granules)
Aldrin
Aldrin
Aldrin
Aldrin
Aldrin
Aldrin
Aldrin
Aldrin
Aldrin
Aldrin
Aldrin


Aldrin

Aldrin
Aldrin
Aldrin
Aldrin
(Dieldrin)
Aldrin
(Dieldrin)
Aldrin
(Dieldrin)
Soil
Type pH

Coachella fs

Carrington sil


Ulysses sil
Knox sil
Celeryville muck
Marietta si
Fox fsl
Miami sil
Muck
Carrington sil Nondisked
Carrington sil Disked
Udaipur cl 7.8


Jobner 8.6

Muck
Miami sil
Composite

Carrington sil Nondisked

Carrington sil Disked

Carrington sil Disked

OM conditions
(%)





Fallow
Fallow
Fallow
Fallow
Fallow
Fallow
Fa 1 low
Fallow
Fallow
1.6 Various


.26 Various









Granules
Application
rate
(kg/ha)
20.2

5.6


2.24
2.24
2.24
2.24
2.24
2.24
2.24
4.5
4.5
3.0


3.0

22.4
22.4
22.4

4.5

4.5

5.6
ks
'
0.2406

.0045

< .0032
.0264
.0259
.0014
.0136
.0256
.0258
.0066
.0101
.0136
.0149
x of 19
x of 19
.0165
x of 19
.0061
.0096
.0038

.0006

.0008

.0012
                          (continued)

-------
                                                  TABLE 111-24  (continued)
ro
Pesticide

Aldrin
(Dieldrin)
BHC
BHC
BHC

BHC

BHC alpha
BHC beta
BHC gamma
BHC delta
Chlordane
Chlordane
Chlordane
Chlordane
DDT
DDT
DDT
DDT
DDT
DDT
DDT
DDT
DDT
DDT
DDT
p,p'-DDT
p,p'-DDT
p,p'-DDT

Type


Carrington sil

Udaipur


Jobner si

Berwick si
Berwick si
Berwick si
Berwick si
Berwick si
Composite
Gullatin Valley
Gullatin Valley
si
Coachella fs
Houston c
Pima sic
Pinal gl
Blackwater River
Pollard Mountain
Mosquito Bnk Pod
Route 11
West Oxbow
Beach Mountain
Carrington sil
Carrington sil
Miami sil
Soil
PH




7.8


8.6











>7
>7
>7
<7
<7
<7
<7
<7
<7
Nondisked
Disked


OM conditions
(%)

Spray

1.6 Various


.26 Various

Vegetables
Vegetables
Vegetables
Vegetables


Alfalfa
Alfalfa





Forest
Forest
Forest
Forest
Forest
Forest

Fallow

Application
rate
(kg/ha)



5.0


5.0

7.4 BHC
7.4 BHC
7.4 BHC
7.4 BHC
2.0

2.0
>2
83
22.4



1.12
1.12
1.12
1.12
1.12
1.12
4.5
4.5
11.6
ks


.0017
.0021
.0140

x of 19
.0098
x of 19
.0006
.00015
.00042
.00036
.00072
.0020
.0101
.007
.004
.053
.0060
.0049
.0060
.00015
.000023
.00040
.00014
.00024
.00044
.0024
.0048
.0003
                                                         (continued)

-------
                                                   TABLE 111-24 (continued)
ro
-F>
en
Pesticide

p,p'-DDT

p,p'-DDT
p,p'-DDT
p,p'-DDT
p,p'-DDT
o,p'-DDT
p,p'-DDT
p,p'-DDT
p,p'-DDT
p,p'-DDT
p,p'-DDT
p,p'-DDT
p,p'-DDT
p,p'-DDT
Dieldrin
Dieldrin
Dieldrin
Dieldrin
Dieldrin
Dieldrin
Endosulfan
Endrin
Endrin
Heptachlor
Heptachlor
Heptachlor
Lindane
Lindane
Lindane

Type

Carrington sil

Muck
Miami sil
Berwick si
Composite
Berwick si
Ulysses sil
Knox sil
Celeryville muck
Marietta si
Fox fsl
Miami sil
Muck
Commerce sil
Carrington sil
Carrington sil

Imperial sc
Holtville fsl
Composite
Various
Mhoon sicl
Coachella fs
Composite
Composite
Composite
Imperial sc
Holtville fsl
Composite
Soil
pH

Disked/non-
disked





6.9
6.8
4.9
6.0
7.2
7.1
6.8

Nondisked
Disked

7.8
7.8


6.0




7.8
7.8


OM
(%)







1.8
.8
74.5
2.0
.8
3.6
40.0




1.0
.5


1.2




1.0
.5

Crop or
conditions

Fallow






Fallow
Fallow
Fallow
Fallow
Fallow
Fallow
Fallow

Fallow
Fallow





Sugarcane







Application
rate
(kg/ha)
4.5

11.2
11.2
37 DDT


9.4
9.4
9.4
9.4
9.4
9.4
1.0
24.4
4.5
4.5

20.0
20.0

1.3

5.4



20
20

k

.0002

.0011
.0029
.00016
.0007
.00029
.0008
.0005
.0021
.0014
.0009
.0004
.0009
.0037
.0142
.0187
.0003
.0002
.0001
.0008
.0162
.0110
.2436
.0021
.0025
.0028
.0022
.0026
.0017
                                                          (continued)

-------
                                                 TABLE 111-24 (continued)
en
Pesticide

Lindane
Lindane
Lindane
Lindane
Lindane
Lindane
Lindane
Lindane
Lindane
Lindane
Lindane
Toxaphene
Soil
Type pH

Gila sil 7.7
Miami sil
Muck
Miami sil
Ulysses sil
Knox sil
Celeryville muck
Marietta si
Fox fsl
Miami sil
Muck
Galestown si 6.7

OM conditions
(%)
.6 None



Fallow
None
None
None
None
None
None
5.2 Cotton
Appl ication
rate
(kg/ ha)

11.6
11.2
11.2
1.12
11.2
11.2
11.2
11.2
11.2
11.2
(6x2.7)
ks

2/.0046
.0011
.0014
.0048
.0147
.0264
.0074
.0263
.0264
.0139
3/.0059
.0046
      I/  si  = silt;   s  =  sand;   sh  = shale;   c  = clay;  1 = loam;  f = fine; g = gravelly.



      Source:   Nash,  1980.

-------
                                TABLE  111-25



           DEGRADATION  RATES  COEFFICIENTS  FOR  SELECTED  PESTICIDES
Pesticide
Aldrin

Chlordane
DDT

Dieldrin

Endrin


Heptachlor

Lindane
(Y-BHC)
Conditions
Lab
Field
Field
Lab
Lab (anaerobic)
Lab
Field
Lab (anaerobic)
Field
Field (anaerobic)
Lab
Field
Lab
Lab (anaerobic)
k
s
0.013
0.0023
0.0024
0.00013
0.0035
0.013
0.0023
0.03
0.0015
0.0053
0.011
0.0046
0.0026
0.0046
%cv

100.
104.2
130.8
82.7

100.
53.3



119.6


Half
Life
53
1237
1214
1657
692
53
1237
31
460
130
63
426
266
151
Source:  Rao and Davidson (1980)
                                    247

-------
     Pesticides  can  be broken  down  into  two  categories

     1.   ionic and
     2.   nonionic

If pesticides are ionic they are in general  cationic,  basic or acidic.
Their primary mechanism of sorption is through ion exchange when in their
ionic form.  Chlorinated hydrocarbons are nonionic and their major mechanism
of sorption appears to be hydrophobic bonding.  Therefore their sorption is
highly related to the amount of organic carbon in the soil (Woodard and
Weber, 1974).

     For hydrophobic  sorption the partition coefficient Kj can be most
successfully estimated using the octanol-water partition coefficient and the
following equations (Rao and Davidson, 1980):
                       log KQC =  1.03 log KQW -  0.18                 (111-29)
and
                                    K   •  %OC
                               K, = -flC	                        (111-30)
                                d      100
where
      K     is  the  octanol  - water partition coefficient,
       ow

      K     is  the  organic  carbon partition coefficient
       \J \f

      %OC  is  the  percent  soil  organic  carbon  and

      Kd   is  the  adsorption  partition  coefficient  (cm3/g)

      Values of K   ,  K   and «d are given in  Table  111-26 for some of the
 chlorinated hydrocarbons  on  the priority pollutant list.
                                    248

-------
                        TABLE 111-26

            OCTANOL-WATER PARTITION COEFFICIENTS
                  FOR SELECTED PESTICIDES1
Pesticide
Aldrin
Chlordane
ODD
DDE
DDE n n
P>P
DDT
DDT P.P
Dieldrin
Endrin
Heptachlor
Lindane (y-BHC)
Toxaphene
Kow

2.1E3
1.2E5
7.3E4
4.9E5
3.7E5
1.5E6
4.9E3
1.6E3
7.4E3
6.4E2
1.7E3
Koc Kd
2.8



2.4E5 4.2E4
6.3E2


1.1E3 20.1

'•Kow and Koc from Rao and Davidson, 1980.
 Kd from Pionke and DeAngelis, 1980.
 Kd Lindane from Rao and Davidson, 1980.
                               249

-------
3.2.9.3  Determination of Pesticide Runoff Loss

     To determine the magnitude of runoff loss the quantity of adsorbed and
dissolved pesticide is first determined.  Total pesticide is the sum of the
adsorbed and dissolved fractions

                                Pt = \ + Dt                        (111-31)

The adsorbed quantity A  is given by

                          At =  [I/O  +  9/K.p)] P.                    (111-32)
                           L              d      t
while  the dissolved fraction, D. , is
                                    +  d/e)J P
                                               u

The loss of adsorbed pesticide is
                                       Kdp/e    P                      (111-33)
                                               t  r,                   (111-34)
                                        N '^V\A Aj^*
 and  the  dissolved  pesticide  loss  is

                               PQt =  CQ/I\.]  Dt                        (111-35)

 In the above equations

      A   =  sorbed pesticide loss (Kg/ha,  Ib/ac)

      6   =  available water  capacity of the top  cm of  soil  (difference
             between wilting  point and field capacity)  (dimensionless)

      p   =  soil bulk density (g/cm3)

      P.   =  total  pesticide  concentration (kg/ha, Ib/acre)
                                    250

-------
     D   =  dissolved pesticide concentration (kg/ha, Ib/acre)

     PX  =  sorbed pesticide loss (kg/ha, Ib/acre)

     PQ  =  dissolved pesticide loss (kg/ha, Ib/acre)

     Q   =  total storm runoff depth (in, cm)

     R   =  total storm rainfall depth (in, cm) and

     K .  =  sorption partition coefficient (cm3/g)

     An example problem for determining the runoff losses of a chlorinated
hydrocarbon follows.
                               EXAMPLE III-4
                         Estimation of Lindane Loss
                       From an Agricultural Watershed

     On 5 June an application of 5.0 kg/ha of lindane (Y-BHC) was made to
the corn crop on the watershed in Example  III-l.  There was lindane residue
of 1.0 Kg/ha already in the soil.  On June 8 the rainfall event evaluated in
Example 111-2 occurred.  Runoff from this  storm was 0.20 cm and the total
sedirrent loss was 45.5 metric tons.  The soil is a Fayette Silt Loam (si!)
with  9 = 0.3 and 10 percent organic carbon.  The bulk density is 1.2 g/cm3.
Evaluate the lindane loss in sediment and  water.

Solut ion:

     First the amount of lindane in the surface layer on 8 June, three days
after application, must be estimated.  Using Equation  111-28
                        Pt = 1.0 + 5.0 = 6.0 kg/r
na
                                    251

-------
of lindane on June 5;  Looking over the k  values for lindane in silty loam
soils, values of .0011 to .0164 per day are found.  To simulate worst case,
the smallest disappearance rate will be used.

     From Equation 111-26

                         Pt = 6.0 exp[-0.0011(3)]
                            =5.98 Kg/ha
The dissolved and adsorbed fractions of lindane must be known.  The K
                                                                     ow
according to Rao and Davidson (Table 111-26) is 643.  Using Equation 111-29

                   log Koc = 1.03 [log  (643.)] - 0.18
                           = 2.71
                       KQC = 516.

Using 10 percent soil organic carbon and Equation 111-30,

                          Y  - 516(10)  _ ,.  , cm3
                          Kd     TSO~~ " 51'6 ~~g~

The dissolved and adsorbed portions are
                                + (51.6  •  1.2)/.3)] 5.98
                          6.03 kg/ha
                                +  .3/(51.6  • 1.2))] 5.98
                        = 5.95  Kg/ha


The lindane lost due to  erosion is (Equation 111-34)

                      PXt =  [45. 5/(72. 8-100-1. 2)]5. 95
                          =  0.03 kg/ha

The lindane lost due to  runoff  is (Equation 111-35)

                           PQt  = [0.2/4.5]  0.03
                               = .001  kg/ha
                                    252

-------
The total loss of lindane is the sum of PQt and PXt times the total area or

                       Ptotal =  (0-03 + 0-001)(72.8)
                              =  2.26 kg

It is evident that  lindane travels primarily with sediment and that erosion
control practices would be effective in reducing  lindane  losses.  This will
not be the case for all pesticides but will be true for most chlorinated
hydrocarbons.
                             END  OF  EXAMPLE  III-4
 3.3   URBAN  NONPOINT  SOURCE  LOADS

      From established  urban areas,  stormwater  may pick  up  various  wastes
 ranging  from  settled dust and  ash to  debris  coming directly from man
 himself.  The quantities of solids  from urban  nonpoint  sources  are quite
 significant in quantity.  Fly  ash and dust from industrial  processes  such  as
 steel  mills,  cement  manufacturing,  and certain chemical  processes  are known
 to be profuse.  Dusts  from  the burning of organic fuels  are a significant
 factor,  and solids  in  sizable  quantities also  result from  off-street  mud,
 automotive  exhaust,  organic debris  from tree leaves and  grass trimmings,  and
 discarded  litter.

      In  this  report, the  nonpoint source loading calculation for
 conventional  pollutants follows the procedures contained in a recent  EPA
 study (Heaney, e_t  aJL, 1976).   This procedure  is used for  annual loadings.
 For  storm event loadings, excerpts  from another EPA study  (Amy, et aj_.,
 1974) are utilized.   The  original procedure  has been modified to make it
 more realistic in  terms of  pollutant accumulation.
                                     253

-------
3.3.1  Annual Urban Loads

     The predictive equation in this procedure allows the user to make a
determination of average annual loads of BOD5, suspended solids, volatile
solids, P0i» and Total N as a function of land use, type of sewer system,
precipitation, population density and street sweeping frequency.  The
procedure requires little external data.  The loading equation is

                     *j • ••';

In this equation
     P        =  annual precipitation  (in) -fern)

     e-       =  fraction of urban area  that  is  made  up  of  the
                 following  land uses:
                 1)  Residential
                 2)  Commercial
                 3)  Industrial
                 4)  Other  developed (parks,  cemeteries,  schools,  etc.)

     ex..       =  pollutant  loading factor  (Ib/acre-in,-teg^hjrew)  for
                 land  use  'i'.

     f2.(PD.)  =  population density  functions for land  use 'i1  and

     Y;        =  the street sweeping frequency

      a        =   a units conversion
                  1.0 English units
                  0.442 metric units  and
                       h    '
                       fv \ \ n
      _               ToU<^
       M.       =  the^annual area weighted load of pollutant  'j1
        J             0»>>AMxa£L
                  (lb/acre-yr, kg/ha-yr)
                                     254

-------
Evaluation of Factors In the LoadijTg_£ujictio£

     The value of e. is determined from areal photographs or may come from
talking to local sources such as city planners or engineers.  When better
data are lacking, Table 111-27 may provide some general guidance.

     Values fora— are found in Table 111-28.  Notice that a different set
of a., are used for separate and combined sewer systems.
    ' J

     The population density function is given by the following set of
equations
Residential  (i  = 1)
                      f2(PD.) = 0.142 + 0.218  (PDd)°'54              (111-37)
Commercial  -  Industrial  (i  =  2,3)

                                f2(PDd)  =  1.0                         (111-38)

Other  developed  (i  =  4)

                               f2(PDd)  = 0.142                        (111-39)

      The  population density PD^ must  be obtained  locally.

      The  street  sweeping factor Y  is  evaluated  by the following  equations

                    Y =  N£/20       (0<_N  <_ 20  days)               (111-40)

                          Y  =  1.0     (Ns  >  20 days)                  (111-41)

Where
      N  is the street sweeping interval (days)
                                    255

-------
                              TABLE  I II- 27
                     GENERAL LAND CONSUMPTION  RATES
                          FOR VARIOUS LAND USES
                (AMERICAN  PUBLIC WORKS ASSOCIATION,  1974)
  Land Use
Residential
Commercial
Industrial
Park
                              Land consumption (acres/capita)
 <100,000
Population
  0.1049
  0.0101
  0.0177
  0.0146
 >100,000
Population
  0.0714
  0.0084
  0.0083
  0.0093
 >250,000
Population
  0.0585
  0.0073
  0.0077
  0.0078
                            TABLE III-28
                   POLLUTANT LOADING FACTORS  (a. .)
                                               i»J
Land Use, i

f\ Separate
Areas,


Combined
Areas,

1.
2.
3.
4.
1.
2.
3.
4.
Residential
Commercial
Industrial
Other
Residential
Commercial
Industrial
Other
1.
0.
3.
1.
0.
3.
13.
5.
0.
BOD5
799
20
21
113
29
2
00
467
2. SS
16.
22.
29.
2.
67.
91.
120.
11.
3
2
1
70
2
8
0
1
3.
9.
14.
14.
2.
38.
57.
59.
10.
VS
45
0
3
6
9
9
2
8
4.
0.
0.
0.
0.
0.
0.
0.
0.
P04
0336
0757
0705
00994
139
312
291
0411
5. N
0.131
0.296
0.277
0.0605
0.540
1.22
1.14
0.150
                                   256

-------
     It is evident from Table 111-20 that higher loads for all pollutants
will be generated if combined sewers are specified.  The data of Lager and
Smith (1974) (Tables 111-29, 30) suggest that the ratio of 4.12 for loads
from combined areas to separate areas is good for BOD,-, N, and P (assumed
in the above methodology).  Suspended solids loads on the average appear to
be less from combined areas than separate areas.  Total coliform loadings on
the other hand appear to be over an order of magnitude greater from combined
than from separately sewered areas.  The above trends are also verified by
the data in Tables 111-29, 30, 31 with the exception of total N.
                               EXAMPLE III-5
                 Estimation of Annual Urban Pollutant Loads

     Consider a city of 10,000 acres of which 20 percent is commercial, 10
percent  industrial, 65 percent residential and 5 percent is in other
developed areas.  The residential population density is 10 persons/acre.
Most of  the city has separate sewers but approximately 30 percent of the
residential area still has combined sewers.  The streets are swept every
five days in the commercial and industrial areas and are not swept in the
residential areas.  The mean annual precipitation  is 42 inches.  Determine
the average annual loadings of total nitrogen and  phosphate.

So 1 u t i on :

     The population density function value for the residential area is
(Equation 111-37)
                       fa (Pp)d) = 0.142 + 0.218(10)°-54
                                = .90

The  street sweeping parameter  is  (Equation  111-40)

                               Y  = 5/20 =  .25
                                    257

-------
                                            TABLE II1-29
        COMPARISON OF QUALITY OF STORM  SEWER  DISCHARGES  FOR VARIOUS CITIES'
                               (LAGER  AND SMITH,  1974)
Type of wastewater,
location, year,
Ref. No.
Typical untreated
municipal
Typical treated
•unlclpal
Primary effluent
Secondary effluent
Storm sewer
discharges
Ann Arbor. Mich.,
1965 (2)
Castro Valley,
Calif., 1971-72 (14)

-------
                                             TABLE  111-30
            COMPARISON  OF QUALITY OF  COMBINED   SEWERS  FOR VARIOUS CITIES3,
                                     (LAGER  AND SMITH,  1974)
Type of wastewater,
location, year,
Ref. No.
Typical untreated
municipal
Typical treated
municipal
Primary effluent
Secondary effluent
Selected combined
Atlanta, Ga.,
1969 (31)
Berkeley, Calif.
1968-69 (34)c
Brooklyn, N.Y.,
1972 (8)
Bucyrus, Ohio
1968-69 (35)
Cincinnati, Ohio,
1970 (36)
Des Moines, Iowa,
1968-69 (6)
Detroit, Mich.,
1965 (2)
Kenosha, Wis. ,
1970 (18)
Milwaukee, Wis. ,
1969 (7)
Northampton, U.K. ,
1960-62 (22)
Racine, Wis.,
1971 (18)
Roanoke, Va.,
1969 (12)
Sacramento, Calif.,
1968-69 (37)
BODj, COD DO,
mg/1 mg/1 mg/1
Avg
200
136
25

100
60
180
120
200
115
153
129
55
150
119
115
165
San Francisco, Calif.,
1969-70 (3) 49
Washington, D.C.,
1969 (5)
71
Range Avg Range Avg
100-300 500 250-750 —
70-200 330 165-500 —
15-45 55 25-80

48-540 - — 8.5
18-300 200 20-600 —
86-428 --
11-560 400 13-920 —
80-380 250 190-410 —
29-158 -
74-685 115
464
26-182 177 118-765 —
80-350 	
—
_.
70-328 238 59-513 —
1.5-202 155 17-626
10-470 362 80-1,760 --
^ Total Total Total
conforms, nitrogen, phosphorus,
mg/1 MPN/100 ml mg/1 as N mg/1 as P
Avg
200
80
15

—
100
1,051
470
1,100
295
274
458
244
400
439
78
125
68
622
Range Avg Range
100-350 5xl07 Ixl07-lxl09
40-120 2xl06 5xl06-5xl08
10-30 IxlO3 Ixl02-lxl04

IxlO7
40-150
132-8,759
20-2,440 IxlO7 2xl05-5xl07
500-1 ,800
155-1,166
120-804
2xl06
113-848 — 2xl05-3xl07
200-800
—
7xl07
56-502 5xl06 7xl05-9xl07
4-426 3xl06 2xl04-2xl07
35-2,000 3xl06 4xl05-6xl06
Avg Avg
40 10
35 7.5
30 5.0

1.2b
-
1.2b
13 3.5
-
12.7 11.6
16.3d 4.3
10. 4d 5.9
3-24 0.8b
10C
„
--
__
„
3.5 1.0
a.  Data presented here are for general comparisons only.  Since different sampling methods, number of samples, and other
   procedures were used, the reader should consult the references before using the data for specific planning purposes.
b.  Only orthophosphate.
c.  Infiltrated sanitary sewer overflow.
d.  Only ammonia plus organic nitrogen (total) Kjeldahl).
e.  Only ammonia.
f.  Only fecal.
                                                   259

-------
                              TABLE  III-31
             SUMMARY OF STORMWATER POLLUTANT CONCENTRATIONS
                        (KAISER ENGINEERS, 1969)


Pollutant^
BOD5
COD
S.S.
Total
Total
(as
Total
(as



Coliforms^
Nitrogen
N)
Phosphorus
P)
Stormwater Overflow
Separate
Mean
27
205
608
3xl05
2.3
0.5
Drainage Areas ^
Standard
Deviation
25
118
616
-
1.4
0.4
Concentrations
Combined
Mean
108
284
372
6x1 06
9
2.8
Areas(b)
Standard
Deviation
36
no
275
-
6
2.9
(a)   Summary of 20 cities,  storm sewers  and  unsewered  areas
(b)   Summary of 25 cities,  combined sewer areas
(c)   All  units mg/1  except  coliforms,  MPN/100  ml
(d)   Geometric mean
                                    260

-------
Using Equation 111-36,

                                Residential
%otal  =  42   [o.65 (0.131 -  0.70 + 0.54-  0.30) (.9) (1.0)

                                 Commercial
                         + 0.20  (0.296)(1.0)(0.25)

                                 Industrial
                         + 0.10  (0.277)(1.0)(0.25)

                                   Other
                         + 0.05  (0.06059(0.142)(1.0)1

                              =  7.2  Ib   /acre-yr

                                 Residential
~ii       =  42    [o.65  (0.0336  •  0.70  + 0.139-  0.30) (.9) (1.0)

                                  Commercial
                          +  0.20 (.0757)(1.0)(0.25)

                                  Industrial
                          +  0.10 (0.0705)(1.0)(0.25)

                                    Other
                         + 0.05 (Q.0099)(0.142)(1.0)l

                                1.8 Ib-PO^/acre-yr.

      Assuming the urban nonpoint source flow is untreated, the annual N and
 PO^ loads to the stream are 36 tons - N/year and 9 tons-POt/year.
                             END OF EXAMPLE III-5
                                      261

-------
3.3.2  Estimation of Single Event Pollutant Loads

     Two factors are of primary importance in determining pollutant loads
from urban stormwater events.  First, the accumulation (supply) of materials
on the watershed must be accurately known and second, the capability of the
system to move pollutants from the street surface to the stream must be
estimated.  The system here is a combination of rainfall event
characteristics and watershed characteristics.

     The accumulation of material on the watershed surface is addressed
first.
3.3.2.1  Accumulation of Pollutants on Street Surfaces

     The amount  of material  available to be washed off can  be described  as  a
function of  the  time  since the  latest of these events occurred.   This  time
is  called  the  equivalent days of  accumulation (EDA)  and  is  computed  by

                        EDA  =  (DR - Ds)  (1  -es)  + D$                (111-42)

where
      D  =  days since  last  "significant"  storm event
       R

      D  =  days since  last  street  sweeping  event, and
       O

      e  =  the street  sweeping  efficiency

      According to Amy,  et  al_.,  1974,  a "significant" storm event is one in
 which 0.5  inches falls  within  a period of  one  to five hours.  A storm of
 this size  is considered to remove 90 percent of the surface particulates.

      Typical values for the street sweeping efficiency term, e_, are given
 in Table  111-32.  Notice that the efficiency is reduced for smaller particle
 sizes.  Table 111-33 shows the percent of solids, BOD5, heavy metals  and
 pesticides  associated with different size fractions of debris, dirt and dust
                                     262

-------
ro
cr>
CO
                                                        TABLE 111-32


                                             SUMMARY OF STREET CLEANING METHODS

Type



Hand Cleaning


3 Wheel Mechanical


4 Wheel I'cchanlcil


Vacuum


Air

Flusher


Sweeping Action



Pushbroan


Gutter and
Main Brooms

Cutter and
Main Brooms

Gutter Broom,
Vacuum Pickup Head

Gutter Broom, Air
Pump System
Water Under
Pressure

Effectiveness

Debris
Percent
95-100


95-100


95-100


95-100


95-100

Small



Dirt
Percent
Est. 70


50-65


50-65


60-80


Est. 50-
70
30



Dust
Percent
Est. 45


15-20


15-20


40-70


Est. 30-
60
Overall


Travel
Speed,
mph

Trucks
Needed

15-20


55


55


55

55


Sweeping
Speed,
n.ph

Slow


4-8


4-8


4-10


4-8

12


Total
Cost


High


Medium


Medium


Low


Low

Low


Special
Li nil -
tatlons

Heavy
Traffic

Wet,
Snowy
Streets
Wet,
Snowy
Streets
Less Man-
euvera-
bility
Wet
Streets
Very flat
grades

Potential Problems
Parl'ed
r * i-c
Cars


Minor


Major


Major


Major


Major

No


Pavement
Cond 1 1 1 on


No


Major


Major


Minor


Minor
•
No


Unimproved
c t r Af> f t
j irec u


lio


Not Useablc


Not Usrjble


Not Effec-
tive

Not Effec-
tive
Can't use
If no
drainage
Special
n(J V Ait-*
tagcs

Adapt. to
Special
Heeds
Maneu-
vers
well



Wand cm
Clean
Catch
Basins




              Source:   Tetra Tech,  Inc.,  1978


                        Final Report.   Surface Sanitation  Program for

                                       Newport Bay, California

-------
ro
                                                        TABLE  111-33



                                       REMOVAL  RATES  FOR SELECTED CONTAMINANTS  BY  SIZE
Particle Size
(u)

^2.000
. 840-2,000
240-840
104-240
43-104
<43
Total Removal
Sweeper
Efficiency
(x)
79
64
60
43
20
15

' Total
Size Oistr
(X)
24.4
7.6
24.6
27.6
9.7
3.9

Solids
. Removal
U)
19.3
4.9
14.9
13.3
1.9
0.9
55.2
BOD5
Size Oistr.
(X)
7.4
20.1
15.7
15.2
17.3
24.3

Heavy Metals
Removal
(X)
5.8
13.3
9.4
7.3
3.8
3.4
43.0
Size Oistri.
(X)
14.8
17.8
14.9
33.8
27.8
- .

Removal
(X)
13.9
11.4
9.9
14.5
5.6
- -
55.3
Pesticides

Size Distri. Removal
(X)
0
16
25.8
28.8
31.7
- .

(X)
0
10.2
15.5
12.4
6.3
- -
44.4
               Source:   Sartor,  J.D.  and  G.B. Boyd,  1972.

-------
and their corresponding removal rates assuming the typical efficiencies in
column 2 of the table.

     Multiplication of EDA by the daily loading rate (Ib day  ) gives the
total load of material on the street surfaces.  (Residual loads remaining
through pervious storm or sweeping events are not accounted for in this
approach.)  Notice that the removal of material will only be from street
surfaces by this method.  Material loads from previous areas in the
watershed or nonconnected impervious areas will not be a calculated part of
the  load.  Daily loading rates are calculated from the following procedure.
3.3.2.2  Street Surface Pollutant Loadings

     Data developed in Amy, et a]_.  (1974) include nationwide means of
solids loading rates and pollutant composition of street solids, as well as
a more detailed breakdown of data into major source categories.  Table
111-34 shows data from the URS report which are divided into 13 subsets
among three major source categories including climate, land use, and average
daily traffic.  These data may be different from the means which are given
in the last column of the table, at the 80 percent confidence  level.
Whenever the mean of any parameter (solid loading rates or composition) in
any  subset differs significantly from the mean of the set of all data, that
number may be substituted for the mean of the set of all data.  Table  111-34
also gives the percent standard error of the mean which indicates the  degree
of confidence that may be placed on the mean.
 3.3.2.2.1   Loading  Functions for  Solids

                             Y(S)U  =  L(S)u-Lst                       (111-43)

 where
     Y(S)   =  daily  total  solids  loading,  (kg/day,  Ib/day)
     L(S)   =  daily  solids  loading rates,  (kg/curb-km-day,  Ib/curb-
              mile-day)
                                    265

-------
                                                                   TABLE  II1-34
ro
CTl
cr>
                                              SOLID LOADING  RATES  AND  COMPOSITION — NATIONWIDE MEANS  AND
                                SUBSTITUTIONS OF THE  NATIONWIDE MEANS AT  80%  CONFIDENCE  LEVEL*  (AMY, _EJ AL^ , 1974)


Climate



Land Use




Average Daily
Traffic
No. /day



Category
Northeast
Southeast
Southwest
Northwest
Openspace
Residential
Commercial
Light Industry
Heavy Industry
< 500
500-5,000
5,000-15,000
< 15,000
All data**
Ibs/curb Concentrations in micrograms per gram of dry solid No /gram
Loading BOD, COD OP04 N03 OrgN Cd Cr Cu Fe Pb Mn III Sr Zn TCOLI+ FCOL 1+
291c 5,970c 2.6b 139b 17,700b 870c 363fl 21c 27b 260b 4.4r5c
103fa 29,100b 2,240a 1 ,970a 137b 1 ,370b 21b 28b 7.0i4rf
5Qc 470b 241a 78a 2,520b 57, 15, 5.7Z6,
30 246 34,500. 2,600, 10, 480, 6.8z5f 1.114.
C a D D C a T T

14,000b 82,000b 850b 550c 1 ,800a 93fl 1 ,430b 28b
74c 58,700c 269,000C 2,250C 1 ,580c 6.430a 133b 3,440b 48b 520fa

278b 28,600b 1,160C 570b 8.2Z5g
l,210d 252b 6.9Z4f
9,500c 83,000c 741 d 419fa 18,900a 1 ,060C 17rf 34C 3.4Z5d
18a
82d 357a 3.8Z5a
156 19,900. 140,000, 1,280. 804, 2,950, 3.4. 211 104, 22,000a 1,810 418 35 21 370 2.5S6 1.7E5,
u u u uu D U d a a d d d 3 d CD
                                                                                           -                                 ..
            Freedom >_ 10).  Total number of permitted substitutions = 103.  Percent Standard Error of the Mean  Subscripting Code-  a=0-9 b=10-T9  c=20-29  d=30-39
            e=40-49,  f=50-62.
            +Co1iform counts are expressed in computer notation,  i.e.  /,5=10^.
            ** Average TP04  is 2,930C and NH4 is  2,640C

-------
     L     = street  curb-length (approximately 2.0 x street  length),
      O v
             (curb/km,  curb-miles).
3.3.2.2.2  Loading_Functions for Other Pollutants
                           Y(i)u = a-Y(S)u-C(i)u                    (111-44)
where
     Y(i)  = daily total loading of pollutant i, (kg/day, Ib/day)
             MPN per day for total  col i form and fecal col i form

     a     = conversion factor, 10    (metric and English).
     Y(S)  = daily total  loading of solids,  (kg/day, Ib/day),
         u
             calculated  in Equation 11
      C(i)   = concentration of pollutant  i  in  solids,  (ug/g);  MPN/g for
         u
             total coliform and fecal coliform.
      Equations  111-43 and  111-44, along with  solid  loading values and
compositions  in  Tables  111-21  and 111-22, provide the means to assess daily
average  pollutant  loadings  to  urban  street  surfaces.

      It  is  important  to note that pollutant loadings  so  calculated are
street  surface  loadings rather than  loadings  at  outfalls  to the  receiving
waters.   The  transport  of  storm runoff  in sewers and  removal of  pollutants
in  some  treatment  systems  would reduce  pollutant loads to some extent.   Such
effects  are not  included in loading  factors suggested  in  Table 111-34.   The
use of  catchment basins to remove solids  and  organic  matter, will reduce
pollutant loads  from  streets to receiving waters.
                                    267

-------
3.3.2.2.3  Procedure for Loading Calculations

     Data in Table 111-34 represent two options as well as two levels of
accuracy for a user to assess pollutant loadings from a given urban area.
Application of the "subset" data may result in higher accuracy, but require
more data and more computation effort, than if "nationwide means" are used.

     Option I - In this option the user will use nationwide means presented
in Table 111-21.  Proceed as follows:

     1.  Determine solids loading rate and solids composition from
         tables.

     2.  Determine street length  (include that of primary and secondary
         streets  but  not driveways,  alleys, or parking  lots).

     3.  Calculate daily solids  loading using  (Equation  111-43).

     4.  Calculate daily loading  of  other pollutants  using
         (Equation  111-44).

     Option  II  -  In  this option  the  user will  make  use  of data presented for
 source categories in  Table  111-34.   Steps needed  for  loading  calculations
 are:

      1.  Characterize the  study urban area.   When applicable,  the
         entire area should be divided into  individual  homogeneous
         sections with unique characteristics.   Each  individual  section
          is  then  defined  as a subarea (e.g.,  residential area).

      1.  Determine street  length in  each  subarea.

      3.  Enter the Table 111-34 at the line labeled "All Data."

      4.  Select  a category of climate, land use, or average daily
          traffic, which best applies to an area and move upward  to the
          line of data to the right of the category heading.

                                      268

-------
     5.   Substitute  those  values  available  in  the row selected  for the
         corresponding  values  in  the row labeled  "All  Data."   In
         choosing  the  substitute  loading factors, the following
         priority  sequence of  source categories  is suggested:   (a)
         climate;   (b)  land use;   (c)  average  daily traffic.   The
         climatic  zones of the U.S.   delineated  by the URS are  shown in
         Figure 111-15.  Caution:  it is not permissible to use more
         than one  row  of substitutions at a time, i.e.,  to use  a  BOD
         value for land use and COD for climate  in order to form  a new
         row of loading rate and  composition data.  It is both  proper
         and useful, however,  to  repeat the above process to obtain
         several  new rows  of data to present a range of composition and
         loading  rates.

     6.   Repeat Steps  4 and 5  for all subareas.

     7.   Use equation  111-43 to calculate total  solid loading in  a
         subarea.

     8.   Use solid loading (Step 7), Equation 111-44 and selected
         composition data to calculate total loading of other
         pollutants in a subarea.

     9.   Sum up loadings of subareas to obtain the loading of entire
         study area.

     Option III - In this option, the user will  make use of site  specific
data.

     The recent URS study has  assembled all presently available data on the
rates of accumulation of solids and on the concentrations of various
pollutant constituents in those solids that collect on street surfaces.
These data are probably adequate for most urban planning operations.  The
user, however, may alternatively replace these loading factors by site
specific data to obtain better prediction.
                                    269

-------
                                                   Gr&d
                    (INSUFFICIENT DATA) i    l«Wwauk"
-------
     If site specific data are lacking, users are encouraged to conduct
sampling and analytical programs of their own.  The data from site specific
tests, if handled properly, may be used in analyzing the area's runoff
problems instead of using values given in this report.  This would be
desirable in most instances, especially in areas or under specific
conditions that were not documented in the URS study.

     Recommended procedures for conducting site specific tests are given in
Appendix B of the URS Report (Amy, et al_., 1974).

     With the lack of site specific data, the user may wish to examine the
available published data for source and reliability.  The user is referred
to Appendix A of the URS Report for description of available data sources,
as well as procedures for processing these data.
3.3.2.2.4  Street Length and Land Use Data for Urban Areas

     Street  length data are available from local public works departments or
street departments.  They can also be obtained by measurement of aerial
photographs.

     Survey  statistics for the U.S.  indicate that street surfaces occupy on
the average  about one-sixth of the urban area (Manuel, et aj_., 1968).  The
American Public Works Association (1974) recently developed a regression
relationship between curb length of urban area versus population density.
Data from many cities across the country were used.  The resulting
regression equation is:

                      CL = 413.11 - (352.66)(0.839)PD                (111-45)

where
                  CL = curb length density, ft/acre
                  PD = population density, number/acre
                                     271

-------
     The correlation coefficient for the equation is 0.72.   The  regression
     ! is shown in Figure 111-16.
curve is shown in Figure 111-16
3.3.2.3  Washoff of Pollutants to Receiving Waters

     Once the equivalent load of pollutant on the watershed is known the
next step is to calculate the runoff and solids loading from the storm.

     The storm event  runoff  is found by

                              R = CR • P - DS                       (111-46)

where
     P  = storm precipitation (inches, cm)
     R  = total storm runoff (inches,  cm)
     CR = runoff coefficient and
     OS = depression storage

     The runoff coefficient will be dealt with first.


3.3.2.3.1  Runoff Coefficient

     In order to estimate the runoff coefficient the percent of impervious
watershed area must be known.  If this information is not readily available
the following equation can be used for estimation:
                    I = 9.6 PD   {0-573 - O^L°910  PDd)            (111-47)

where
     I   = percent impervious area and
     PD  = population density (r persons/acre)
                                     272

-------
GROSS POPULATION DENSITY, POP/HECTARE
600

550

500
450
UJ
^ 400
£>
UJ
•^ 350
t—
§ 300
UJ


£ 250

O
Z

^J 200
03

ID
U 150


) 20 40 60 80 ICC 120 140 160 180 200 220 240
11111 i i • • i i i
-
.
,
'*
•
• 	 A 	 , 	 • 	 ~
S*^^ • •
s -^
r *

1
-•/ .
J

• /••• •
-/

/


"/ •
>/*
I

1

100f-~


50

0



—
i i i i ii i i i
797
750

700
650
600
550 £
i—
500 m
3^
450 g
| ,---
r m
LU
400 §
^«
i —
350 ^
Z
LU
300 Q

x
250 o
Z
LU
200 -1
co
&£.
150 3

100


50
n
0 10 20 30 40 50 60 70 80 90 100"
GROSS POPULATION DENSITY, POP/ACRE
FIGURE 111-16  CORRELATION BETWEEN POPULATION  DENSITY  AND CURB
               LENGTH DENSITY,   (AMERICAN  PUBLIC  WORKS ASSOCIA-
               TION, 1975)
                              273

-------
     The  STORM algorithm  for  computing the runoff coefficient is:

                      CR  =  0.15
                                      100
                                 \

where
                                               (m)
    CR = runoff coefficient
    I  = percent impervious area and
    K  = impervious area runoff coefficient based  on  slope  information
         (See Table 35).

                            TABLE  111-35
                   VALUES  OF RUNOFF  COEFFICIENT, k

                  Impervious Surfaces        Approximate k
                Flat (<2%  slope)                 0.80
                Moderate (2 to  7%  slope)         0.85
                Steep (>7% slope)                0.90
3.3.2.3.2  Depression  Storage

     Depression storage  on  the watershed is computed as

              DS  =  0.25  - 0.1875  i~]     English units or        (111-49)
              DS  =  0.63  - 0.48  UQQ-!       metric units            (111-50)

where
     DS = depression storage (inches,  cm)
                                   274

-------
3.3.2.3.3  Solids Removal

     Once the total storm runoff has been computed the percentage of solids
removed from the street  surfaces can be estimated by referring to the graph
in Figure 111-17.  The solids load for the runoff event is

                         Y(S)w = EDA  • Y(S)u  •   (PC)                  (Ill-Si)

when
     Y(S)    is  the load  of  solids removed to the receiving water body
             (Ibs,  kg)

     EDA    is  the equivalent number of days of accumulation

     Y(S)    is  the street  surface  loading rate  (Ib/day,  kg/day)  and

      (PC)    is  the percentage  (expressed  as  a  decimal  fraction)  of
             solids removed during  the  storm  event

      The user should  realize that  the  runoff coefficient and  hence  the
 stream loading  rate  does not incorporate  the effects of losses in  sewers or
 stormwater detention  basins.  For  more accuracy in these complex situations
 the user is directed  toward a more sophisticated urban stormwater  model
 which would require  a hydraulic description  of these structures.
 3.3.2.3.4  Other Pollutants

      As in the street surface loading equation the quantity of other
 pollutants is determined by a product of a concentration factor and the
 loading of solids.  Factors for several conventional pollutants and some
 metals can be found in Table 111-34.

      Smolenyak (1979) developed loading equations for other conventional
 pollutant forms given the suspended solids load.  His coefficients for
 linear and power function models are given in Table 111-36.  These
                                   275

-------
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     o
     e
     -s
     o
     ft)
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    CD
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    JO
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             CO  H
                 33
             >  m
                 m
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—I
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o
                 oo
                 O
                 m
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    o

C? H

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             ID i— >
             n> 3
             3 O
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             n>
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                      70
                      C

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                      o  o o
                      ro  .   «—
                      T3  en no
                             co
                          01
                          (-• O

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                          i_i o

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                                                            Percent  of Contaminat Removal
•vj
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                                                                                                                                            8
                                                                                                                               \

                                                                                                                                \

-------
                              TABLE  111-36



RELATIONSHIPS BETWEEN  TOTAL  SUSPENDED  SOLIDS  (TSS)  AND OTHER POLLUTANTS
Dependent
Variable
BOD
COD
NHj
I « W ""I
3
N02 + NO^
Organic N
Total N
Dissolved PO.-P
Total P04
Total P-P
No. of
Events
76
109
20
20
100
38
14
31
113
28
Linear
R2
.18
.52
.41
.43
.14
.67
.83
.22
.06
.25
(Load = a+b
Req.
a
24
3.4
.065
.007
.011
.072
.0083
.0081
.003
.084
• TSS
Coef.
b
1.7
.19
.0027
.0012
.00077
.0029
.0027
.00014
.00017
.028
Loq-Loq
R2
.42
.73
.18
.54
.57
.83
.75
.65
.65
.68
(Load = aTSSb)
Req. Coef.
a
.39
.92
.022
.0046
.0071
.011
.0075
.0010
.0012
.0041


b
.99
.72
.48
.60
.55
.80
.78
.67
.68
1.2

-------
regressions were performed on combined data from 23 different urban
catchments in various U.S.  cities.
3.3.2.4  Toxic Pollutant Accumulation

     Toxic pollutants  in urban watersheds are introduced by a variety of
activities.  Atmospheric deposition from industrial emissions and vehicular
emissions are primary  sources.  Other sources include spills onto highways
and  loading docks.  Such spills may represent significant  loads of toxicants
because  they generally occur onto  impervious surfaces.

     The discussion of deposition  of toxic  pollutants to urban areas will be
divided  into two  categories

     1.   metals  and
     2.   organic pollutants
 3.3.2.4.1  Deposition of Metals

      The loading of metals to street surfaces is estimated in the same
 manner as for conventional pollutants.   The product of equivalent days of
 accumulation, solids loading rates and  concentration factor for the metals
 in solids (Table 111-34) is used.
                                EXAMPLE III-6
                          Estimation of Lead Washoff
                        Load for a Single Storm Event
      Estimate the amount of lead removed from the street surface of Laurel,
 MD, during a single storm event.  The rainfall depth of the storm is 1.21
 inches.  The population density for Laurel is 13.2 persons acre~  and there
 are 70 curb-miles in the town.  When the storm occurred, it had been eight
 days since the last significant rainfall and four days since the streets had
                                      278

-------
been swept.  (Sweeping efficiency = 0.750) Use a solids supply rate of
103-lb/day curb-mile.

Solution

First determine the percent impervious area using Equation 111-47

           I    =  9.6 (PDd) (0'573 ' °'0392 logi° Pdd)
           PDd  = 13.2 and
           I    = 37.6 percent

Next, compute the runoff coefficient for the area using Equation 111-48

               CR = 0.15 (1 - -L) + 0.85 (^J
               I  = 37.6 and
               CR = 0.41

The depression storage is computed as (Equation 111-49)

                    DS = 0.25 - 0.1875 (1/100)
                    I  = 37.6
                    DS = 0.18

The storm  runoff can now be computed by Equation 111-46 as

                         Q = CR  - P - DS
                           = 0.41 (1.21) - 0.18
                           - 0.32 inches

Now, the supply of solids which  is present on the watershed must be
determined.  Compute the equivalent days of accumulation  (EDA) as  (Equation
111-42)

                     EDA  =  (Dr -  Ds) (1 -  es) + Ds
                         =  (8 - 4)  (1 - 0.75) + 4
                         =  5 days
                                 279

-------
Using a solids loading rate of 103 Ib/curb-mile - day,  Equation 111-43 gives

                    Y(S)  = 103 • (70) = 7210 Ib/day

Equation 111-44 gives the amount of lead deposited per day as a function of
solids
                         Y(i)u =  10"6  (7210)(1370)
                               =  9.9 Ib  -  Pb/day
Since the washoff of lead as opposed to solids is of concern, the Y(S)
becomes Y(i)  in Equation 111-51 and
            w
                           Y(1)w = 5 (9.9)(.75)
                                 = 37.1 Ib - Pb
washed off  in the event.
                            END OF EXAMPLE 111-6
3.3.2.4.2  Deposition  of Organic Pollutants

      Many pollutants  are discharged  into  the atmosphere  and eventually
settle  out directly onto water surfaces,  or onto  the watershed surface where
they  become  available for transport.   Pollutants  occur  in  the atmosphere  as
1)  particulates;   2)  gases;   or 3) dissolved in water vapor.  Eisenreich
ert  al.  (1981)  have suggested  that compounds having  saturation vapor
                      _Q
pressures (P ) of  10   will  primarily be particulate whereas those
             s         .4
compounds with P   >10   will  be primarily in the  vapor  phase.  Cautreels  and
Van Cauwenberghe  (1978) give  distribution coefficients  between the gas  and
particulate  phases for 55 aliphatic  hydrocarbons, PAH's, phthalic  acid
esters, fatty  acid esters, aromatic  acids and  basic compounds.

      Both particulates and gases may settle out onto  receptor surfaces.   For
 particles <0.3 ym in  diameter,  the major  process  is Brownian  diffusion  for
diameters 0.5  to  5 ym inertial  impaction-interception  governs and  for
 diameters >5 ym,  gravitational  settling is dc~n'nent.   For gravitational
 settling, Stokes1 Law may be  used  to predict  the  settling velocity.   Since
 Stokes1 Law is applicable only  to  quiescent redia,  it  should  give  an upper
                                   230

-------
bound for V. (the deposition velocity).  It is stated as

                          Vd aaifg£-(p - Pa}                      (IH-52)

where
     V   = settling velocity (cm/sec)
      d                        _4
     a   = conversion factor (10  )
     g   = acceleration of gravity, 981.46  (cm/sec2)
     y   = viscosity of air, 0.000177  (g/cm-sec) at 50^  (10°C)
     P   = particle density, % 2  (g/cm3)
     Pa  = density of air, 0.001243 (g/cm3) at 50°F (10°C)
     d   = particle diameter (microns)

     For particles   <5  ym  in diameter Stokes Law  is  not applicable and
 experimental  values for  the deposition velocity  should  be used.   Eisenreich
 e_t aj_.   (1981)  suggest  values of V ,  = 0.1  to  0.5 cm/sec for  trace organics.
 Some experimental  values are  shown  in Table  111-37.

     Once the settling  velocity  is  known,  the following procedure can be
 used to  predict the dry deposition  loadings:

                          L = Vd • Cp •  A  • f                       (111-53)

 where
     L    is the load  of the pollutant delivered  to the receptor surface
          as dry deposition  (appropriate mass  units/sec)
      V    is the particle settling  (deposition)  velocity (m/sec)
      C    is the concentration of atmospheric  particulates (mass/m3)
     A    is the projected receptor  ares (m2)
     f    is the fraction (by weight) of the  pollutant in the
          particulates

      Normally,  smaller  size particles are more  chemically and physically
 reactive than larger  particulates,  and therefore pollutants will be
 associated  with these  smaller particles.  Obviously the particle size to
 which  pollutants are  adsorbed affects their  atmospheric residence time and,
 hence,  loadings.  According to  Neff  (1979),  most PAH are associated with
                                    281

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                              TABLE III-37
                 FIELD-MEASURED DRY DEPOSITION VELOCITIES
Compound
  V .
(cm/s)
 Collection
   Surface
PCB
  (Aroclor
  1242, 1254)

PCB
PCB, DDT
  (gas phase)

PCB, DDT

PCB
  (total)

PCB
  (Aroclor
  1016)

PCB
0.5
0.3-3


0.19


1.0

0.14


0.04
Mineral-oil-coated
      plates

Estimated
Estimated

Glycerol-coated
    plates

Glycerin-water,
    Al  pans
0.43
Source:  Eisenreich et al., 1981
                                     282

-------
participates in the 1 to 2 micron range.  Van Vaeck and Cauwenberghe (1978)
have shown that aerosol PAH are associated with particles of median diameter
from 0.7 to 1.4 urn.  In addition, they give the concentrations of 50 trace
organic compounds associated with different size particles.  Higher weight
PAH, alkanes, and carboxylic acids had significant mass fractions associated
with >1 ym diameter particles.
                               EXAMPLE  III-7
                  Dry Atmospheric Deposition of Pollutants
                          Adsorbed to Participates

     Estimate the maximum daily  loading of pyrene to a watershed having an
area of 106m2 overlain by an air mass having a mean daily particulate
concentration of 50 yg/m3.  The  average pyrene content of the participates
is 1.0 x 10   yg-pyrene/yg.  Assume  a deposition velocity of 0.1 cm/sec.

Solution:
Compute  the daily dry deposited  load  of pyrene.
                    L = Vt  • Cp  • A  .  f
                      = 0.001 -OL. • ^^  •  106m2
                              sec     m3
                                                 86400 sec
                       • 1 0 x 10" "   -
                                        yg          day
                      = 4.32 x JLOJ_ ug/day
                                   Ans.
                            •END OF  EXAMPLE  111-7
      Gas  phase  pollutants  may also be deposited directly to the v.'atershed
 surface.   In  this  case  the loading equation is
                                  283

-------
                                 L = V
                                                               (111-54)
  where
            is the dry deposited load (mass/sec)
        , .   is the gas deposition velocity (m/sec) and
L
V
 a
A   is the receptor area (m2)
C   is the ambient concentration of the gas phase pollutant.
                                 EXAMPLE 111-8
                 Dry Atmospheric Deposition of Gaseous Pollutants
                             of Gaseous Pollutants


       Estimate  the annual deposition of toxaphene to a 1 Km  area at
   Stoneville, MS during  1974.  The mean monthly atmospheric concentrations are
   shown  in Table 111-42.  Assume an average deposition velocity of 0.2 cm/sec
   for the entire year.
   Solution:
 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
   .002
   .002
   .002
   .002
   .002
   .002
   .002
   .002
   .002
   .002
   .002
   .002
                               12
                                           A • At
Vd

(m/sec)
C
n
(ng/M3)
A t
n
(M2)
L


 10.9
  9.7
 19.1
 27.7
 44.
 38.
   ,3
   .6
175.0
   .6
   ,6
903.
524.
114.8
 32.9
 12.6
10"
10"
10"
10"
10"
10"
10"
10"
10"
10"
10"
10"
31 x
28 x
31 x
30 x
31 x
30 x
31 x
31 x
30 x
31 x
30 x
31 x
86400
86400
86400
86400
86400
86400
86400
86400
86400
86400
86400
86400
5
4
1
1
2
2
9
4
2
6
1
6
.84
.69
.02
.43
.37
.00
.37
.84
.72
.15
.71
.75
x
x
X
X
X
X
X
X
X
X
X
X
108
108
109
109
109
109
109
1010
1010
109
109
108
                                                                1.01 x 1011
                                                                  ng/year
                                                 or 101.4 q/year   Ans.
                                      284

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     In actual situations the deposition velocity changes with
meteorological conditions especially wind speed.  In general, deposition
velocities diminish as wind speeds decrease.  Further reading on gaseous
pollutant deposition can be found in Murphy et. a_l_.   (1980).
                            •END OF EXAMPLE  III-8
      Precipitation  falling  through  the  atmosphere  tends  to  scavenge
 particulates  and  absorb  gases  so  that  it  contains  a  variety of  substances.
 Because  of  the  volume  of precipitation  which  generally occurs,  it  may
 constitute  a  significant source of  pollutant  loading to  the watershed
 surface.  Load  calculation  for wet  deposition is  shown below:
 where
                              L = 10 • C • P • A
                     (111-55)
      L   is the load of the pollutant delivered to the receptor as wet
          deposition (appropriate mass units/sec)

      C   is the concentration of the pollutant in precipitation
          (mass/liter)

      P   is the precipitation rate (cm/sec)

      A   is the projected receptor area (m2)

      If concentrations of constituents in rainwater are unknown, they can be
 estimated using the ambient vapor phase concentrations of the pollutant and
 the Henry's Law constant for the pollutant.   By assuming equilibrium between
 the gas and water phases, one can write
                         C1V1 +  CgV9  =  CtVt
or
111-56)
                                    285

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                            .hft")
          C,   = 	x^	'                       (IH-57)
           1
where
    Ci  is the concentration  of the pollutant in water  yg/m3
    Vi  is the volume of rainfall m3
    C  is the concentration  in the gas phase (yg/m3)
    V  is the gas phase volume (m3)
    C.  is the total pollutant concentration  yg/m3
     V  is the total volume of the atmosphere (m3) and
     H  is the Henry's Law constant for a particular pollutant.
     Because HV  »VX for almost all of the priority pollutants and V^ V
 the equation reduces to
                                 C
                                                 '  '\j V
g                          -      -  .              g    t
at
                                  1
                                  H                            (111-58)
 Thus for toluene, for instance, if Ct is 1 yg/m3  air

                         r  _  1.0
                         Ll   .27
                            =3.7 yg/m3 water
 For Henry's Law constants on the order of  10"  the equation for Ci  can be
 rewritten as
                                  /W DI
                        r          \  1  q    /
                        cl  =  	w~pT	                     (ni-59)
                              H .  ^.-1 + 1
                                    l pg
 where
      p   is the gas  density
      P!  is the water  vapor density
                                 286

-------
     Wi  is the weight of water vapor in the atmosphere and
     W   is the weight of dry air.

W , Wi, p , and PI can be determined for any temperature and relative
 y       «?
humidity from a standard psychrometric chart.
     Another similar approach to determining wet deposition is the use of
washout rations (Eisenreich et al., 1981).  The wet flux is calculated by
                             F = W.  •  I  . C                         (111-60)
                                   i        a
where
     F    is the wet pollutant flux
     W.   is the washout ratio for pollutant  i
     I    is the precipitation rate  (LT~  ) and
                                                    _3
     C-,   is the ambient pollutant concentration  (ML   )
      Calculated  and observed  valued of W  for  some contaminants are shown  in
                                        i
 Table  II1-38.  Note that  field measured washout  ratios  contain the effect  of
 particulate  scavenging  by rainfall whereas calculated values only consider
 constituents absorbed as gases from the atmosphere.

      In  order  to use the methods  for  determining dry and  wet deposition  and
 gaseous  absorption, the atmospheric concentration of the  pollutant must  be
 known.   For  the  129 priority  substances,  very  little monitoring data  is
 available.   Some scattered  data  are available  such  as that  in  Tables  111-39
 through  42.  For a particular locale, some monitoring will  need to be done
 at  this  stage.
 3.3.2.5  Washoff of Toxic Pollutants

      The amount of organics or metals lost in solids or dissolved phase is
 estimated using the adsorption partition coefficient.  The fractions are
 given by
                                   287

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                        TABLE  111-38
          WASHOUT RATIOS FOR SELECTED TRACE ORGANICS
Compound                  RT/H = W.                      Wfield

Dieldrin                  1.1 x 105                    2-9 x 103
Aldrin                    1.6 x 103
DDT                       5.9 x 102                    2-8 x 10"
HCH                       5 x 10"                      1-5 x 10"
Aroclor                   4 x 101                      1 x 10"
  1242
Aroclor                   6.3                          9 x 10"
  1248
Aroclor                   8.3                          2-9 x 10"
  1254
                          8-35 x 10"
Aroclor                   2.9
  1260
Hexachlorobenzene        '3.7 x 102                    1.5 x 103
Chloroterpenes            3.5 x 10"                    7 x 103-
                                                         3 x 10s
Di-2(ethylhexyl)             —                        1-9 x 10"
  phthalate
Source:  Eisenreich eit aj_., 1981
Note:  H (Henry's law constant) in this table has units of
       1iter-atm/mole.  Essentially W. = -   as defined previously.
                              288

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                                        TABLE  II1-39


           PCB's, DOT'S,  AND  PHTHALATE  ESTERS  IN  THE  GULF  OF  MEXICO ATMOSPHERE*
Sample No. Date
1 3/26-27
2 3/28-29
3 3/29-30
4 3/30-31
5 3/31-4/1
6 4/1-2
7 4/2-3
8 4/3-4
9 4/4-5
10 4/6-7
Average
PCB
0.66
0.37
0.17
0.18
0.13b
0.17
0.23
0.71
0.79
0.35
0.35
Concentration (ng nT
p,p'-ODT p,p'-DDE
0.042
0.078
0.047 (90)
0.020
0.016b
0.022
0.041
0.021
0.044
0.010
0.034
0.116
0.065
0.026
0.018
0.010b
0.009
0.018
0.017
0.180
0.031
0.049
)
DEHP
1.92 (51)
0.72 (67)
1.45 (51)
1.75 (78)
0.53b(-)
1.72 (71)
1.34 (50)
1.80 (25)
1.34 (69)
0.83 (58)
1.16 (57)
DBP
3.71 (68)
0.84 (94)
3.34 (20)a
0.65 (88)
0.75b(-)
1.03 (J5)
0.16C(-)
1.30 (46)
0.80 (66)
0.38C(-)
1.30 (63)
Questionable value, not included in average.

 Vapor phase only

cParticulate only.

 Concentrations  (in ng m" )  are for the total sample.  The numbers in parentheses are the percent
 of the compound measured in the vapor phase only.   Unless otherwise indicated all PCB's, DDT,
 and DDE vapor concentrations are>98S.

Source:  Giam et al., 1980.
                                                289

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                                            TABLE 111-40

  1975 MONTHLY AVERAGE CONCENTRATIONS OF THREE ORGANIC COMPOUNDS AT THREE NEW YORK CITY LOCATIONS
Month
January
February
March
April
May
June
July
August
September
October
November
December
Average
Urban
Suburban
(Sterl ing
Forest, N
Mi
23
85.43
NDA
47.39
53.42
NDA
NDA
NDA
NDA
57.19
98.78
69.53
NDA




•Y.)
TSPM*
crograms/m3
Sector
27 34
59.52
61.21
52.71
70.31
89.38
67.28
74.41
63.51
54.74
73.65
65.69
57.96

65.86



63.71
NDA
56.63
65.72
68.58
67.25
56.97
55.34
51.67
73.64
79.74
NDA





23
4.90
NDA
2.93
3.00
NDA
NDA
NDA
NDA
4.40
2.98
4.15
NDA





DBP*
Sector
27
4.93
8.49
5.03
4.84
3.17
1.99
3.48
5.00
4.79
10.28
5.31
10.99

4.41


1.41
Nanograms/m3
34 23
3.87
NDA
4.33
2.72
2.22
1.80
0.14
1.80
7.38
2.81
5.69
NDA





10.89
NDA
10.91
4.93
NDA
NDA
NDA
NDA
8.81
12.15
13.52
NDA





DEHP*
Sector
27
11.96
15.41
12.30
12.48
14.72
10.06
14.05
15.48
17.93
28.60
23.24
25.30

14.45


2.51
34
18.58
NDA
13.06
13.50
12.23
11.02
8.96
13.58
12.15
22.15
16.76
NDA





BEO*
Mi crograms/m3
Sector
23 27 34
3.87
NDA
1.76
1.88
NDA
NDA
NDA
NDA
1.43
3.98
3.79
NDA





3.08
4.13
2.56
2.96
3.89
2.39
3.84
3.45
3.04
5.24
5.01
5.66

3.21



4.15
NDA
2.54
2.54
2.67
2.06
1.63
1.87
3.26
3.53
3.56
NDA





 TSPM, Total  Suspended Particulate  Matter;  DBP  and  DEHP,  di-Butyl  and  di-(2-Ethylhexyl)  phthalate;  and
 BEO, Benzene Extractable Orgam'cs.

Source:  Bave et al,  1978.

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                              TABLE 111-41
      SEASONAL FLUCTUATIONS IN THE GEOMETRIC MEAN PAH CONCENTRATIONS
                 IN AIR SAMPLES COLLECTED AT 13 STATIONS
                   IN THE LOS ANGELES, CALIFORNIA, AREA
Compound
Pyrene
Fl uoranthene
Benz[a]anthracene
Chrysene
Benzo[e]pyrene
Benzo[a]pyrene
Benzo[b]fl uoranthene
Benzo [i ]f 1 uoranthene
Benzo [k]fl uoranthene
Perylene
Anthanthrene
Benzo [ghi ]peryl ene
Indeno[l ,2,3-cd]pyrene
Coronene
Total PAH measured
1
0-58
0-38
0-30
0-70
1-30
0-77

0-26
0-27
0-22
0-33
3-80
1-79
2-49
13-19
Quarter concentration (ng/m3
2 3
0-23
0-15
0-06
0-26
0-42
0-17
0-24
0-06
0-07

0-08
1-35
0-68
1-13
4-90
0-25
0-24
0-10
0-44
0-62
0-26
0-33
0-12
0-15
0-06
0-14
2-71
1-00
1-66
8-08
)
4
1-24
0-68
0-59
1-57
1-96
1-27
1-30
0-43
0-52
0-22
0-79
8-25
2-64
4.44
25-90
Source:  Neff,  1979
                                    291

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                               TABLE 111-42

                 AVERAGE MONTHLY ATMOSPHERIC LEVELS  OF
               FOUR PESTICIDES AT STONEVILLE, MISSISSIPPI



Endrin (nqm"

January
February
March
April
May
June
July
August
September
October
November
December
Average


January
February
March
April
May
June
July
August
September
October
November
December
Average
1972
1.1
1.1
2.1
3.1
1.0
0.9
5.2
10.1
8.8
4.0
0.5
0.0
3.2

Methvl
0.0
0.0
0.0
0.0
0.0
1.6
61.4
216.9
111.7
1.4
0.0
0.0
32.8
1973
0.1
0.1
0.7
0.7
1.2
3.8
0.7
5.0
8.4
5.0
1.1
0.2
2.3

Parathion
0.0
0.0
0.0
0.0
0.0
22.8
4.5
129.3
791.1
17.1
0.0
0.1
80.4
3
' )
1974
0.2
9.2
0.6
0.5
0.7
0.7
9.3
27.2
18.8
4.3
1.0
0.5
5.3
3
(nonf )
1.0
0.3
0.3
0.6
0.6
0.9
40.9
341.1
167.9
2.0
0.0
0.0
46.3


1972
0.0
13.0
68.0
67.4
32.4
44.2
400.7
1540.0
827.9
97.9
9.3
0.0
258.4


10.8
12.6
32.6
34.1
17.2
16.2
117.3
515.3
378.8
37.6
14.8
6.3
99.5
3
Toxaohene (nqm" )
1973
0.0
0.0
16.8
10.8
46.8
109.9
41.1
268.8
322.6
161.1
0.0
9.9
82.3
3
Total DDT (nqm" )
3.9
4.8
11.1
11.4
18.6
49.5
9.6
25.6
24.6
18.9
11.9
2.4
16.0


1974
10.9
9.7
19.1
27.7
44.3
38.6
175.0
903.6
524.6
114.8
32.9
12.6
159.5


3.0
3.6
7.6
7.7
15.6
12.8
24.3
37.9
19.4
5.1
3.3
2.1
11.9
Source:  Arthur et al, 1976
                                      292

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                                            -]'                      (111-62)
                                         s c!
where
     F   = fraction of dissolved pollutant
     p   - sediment concentration (g/cm3)
     K,  = adsorption partition coefficient (cm3/g) and
      d
     F   = the fraction of sorbed pollutant

     The average sediment concentration p  is determined by dividing the
sediment loss by the total storm runoff

                       Ps  = a  •  Y(S)w /  (Aw • Q)                     (111-63)
                       AW  = watershed area (ha, ac)
when
      p       is  the  suspended sediment concentration  (g/cm3, lb/ft3)
      Y(S)    is  the  sediment  load  (kg, Ib)
      Q       is  the  total  storm runoff depth  (in, cm)
      a       is  a conversion  constant
                    =  10   metric
                    =  2.75 x  10"4  English

      Y(S)   and  Q are  determined by  urban runoff  single  event procedures  in
section  3.3.2.3.
      Tables  111-43  and  111-44  show  the  relative magnitudes of concentrations
 of  metals  and  some  organic pollutants  in wet  and  dry weather flows.  Wet/dry
 ratios   show that the concentration  of  metals  in  nonpoint source runoff is
 from  1  to  10 times  greater than dry  weather flows  in which the contributions
 are primarily  from  point  sources.   Concentrations  of PAH are 100 times
 greater from nonpoint than point  sources.
                                     293

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                                             TABLE 111-43


                 FLOW WEIGHTED MEAN CONCENTRATIONS OF TRACE METALS AND CHLORINATED
                            HYDROCARBONS IN THE LOS ANGELES RIVER ( yg/1)
1971-1972
Constituent
Ag
Cd
Cr
Cu
Hg
Ni
Pb
Zn
*
Fe
Mn
DDT
PCB
Dry Weather Flow
1.4
4.3
84.
21.
0.39
24.
150.
230.
3.8
120.
0.27
1.6
Storm Runoff
2.2
13.
83.
130.
1.0
78.
940.
100.
18.
480.
0.93
2.6
Ratio
Wet/ Dry
1.6
3.0
.99
6.2
2.6
3.2
6.3
.43
4.7
4.0
3.4
1.6
1979-1980
Dry Weather Flow
0.4
6.2
30.
52.
0.25
43.
56.
200.
4.8
130.
0.05
0.21
Storm Runoff
0.8
4.0
100.
87.
0.8
61.
160.
960.
51.
650.
0.33
0.31
Ratio
Wet/ Dry
2.0
0.64
3.3
1.7
3.2
1.4
2.9
4.8
10.6
5.
6.6
1.5
Source:  Coastal Water Research Project Biennial  Report 1979-1980.

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                           TABLE 111-44

  30NCENTRATIONS OF PAH IN MUNICIPAL  UASTEUATER  EFFLUENTS  IN THE GFR
                   (ALL VALUES ARE  IN THE  yG/LITER)
Compound
Fluoranthene
Pyrene
Benz[a]anthracene
Benzo[b]fluoranthene
Benzo[i]fluoranthene
Benzo[k]fluoranthene
Benzo[a]pyrene
Benzo[ghi]perylene
Indeno[l ,2,3-cd]pyrene
Total identified PAH
Total unidentified PAH
Total PAH
Dry Weather
0.352
0.254
0.025
0.039
0.057
0.022
0.001
0.004
0.017
0.771
0.075
0.846
During Heavy Rain
16.350
16.050
10.360
10.790
9.910
1.840
3.840
4.180
4.980
78.300
9.200
87.500
Ratio
Wet/ Dry
46.4
62.2
414.4
276.7
173.9
83.6
3840.0
1045.0
292.9


103.4
Source:   Neff,  1979
                                 295

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                              •EXAMPLE II1-9
                    Washoff of Organic  Urban Pollutants

     Estimate the washoff of pyrene from the street surface of Laurel,  MD
during the storm in Example III-6.   Assume the deposition rate of pyrene
from Example III-7.  Estimate the load  of pyrene in runoff (dissolved)  and
adsorbed to solids.  The KQC for pyrene is approximately 1.2 x 105 and  the
streets solids are 20 percent organic carbon.

Solution:
     From problem III-6
     A        = 1000 ha
      w
     EDA      = 5
     Q        = 0.32 in or 0.81 cm
     Y(S)     = 7210 Ib/day or 3277 kg/day
     Y(pyrene)u = 4.3 x 10s ug/day

The washoff of solids is (Equation  111-51)

     Y(S)U = 5 (3277)(.75)
           = 12289 kg-solids
The mean concentration of solids is (Equation 111-63)

                   p_ =  10"5(12289)(0.81-1000)
                    s
                     = 0.15 kg/m3 or  1.5  x  10"* g/cm
To estimate the K , (partition coefficient) for pyrene Equation 111-30 can be
used
                                =  1.2xl05(20)
                            Kd       100
                                =  24000  cm3/9

Using  Equations  111-61  and  111-62 the dissolved  and  adsorbed pyrene
fractions  are

                      F,, =  [1 + (1.5xlO"'4)(24010.)]"1
                       W
                         -  0.22         and
                                  296

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                      [' *	!	]'
                      L    1.5 x  10'"(24000)  J
                          i-l
         .5 x 10'" (24000)
= 0.78
     The dissolved and adsorbed loads are the product of the above fractions
and the total pyrene load (Equation 111-51)

     Y(pyrene)w  = 5(4.3xl05)(.75)
                 = 1.6xl06 yg

     Y(pyrene)w  = F   1.6xl06
               w = 0.22(1.6xl06)
                 = 3.5x105 yg

      Y(pyrene)w   =  Fg  (1.6xl06)
               5  = 0.78  (1.6 x 106)
                  =  1.25xl06 yg

     Note  that although  the partition coefficient for pyrene is very high,  a
substantial  quantity of  pyrene is  in the dissolved form  (22 percent).  This
is due  to  the very  low mean solids concentration  (only 150 mg/1).  The mean
pyrene  concentration  is  about 0.20 yg/1 which  is  close to dry weather values
in Table  111-46.
                             END  OF  EXAMPLE  III-9
 3.4   POINT  SOURCE  WASTE  LOADS

      The  purpose  of  this section  is  to  discuss  sources of  information
 concerning  point  source  discharges  and  to  provide  a  reasonable  range of
 values for  discharge concentrations  when no  direct source  data  can  be
 located.  When  available,  direct  data concerning  an  existing  or proposed
 discharge is  preferable  to the  use  of the  information  presented here.
                                  297

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3.4.1  Direct Sources of Data

     Before using these guidelines and estimates a planner should exhaust
the sources of actual point source waste loading information available to
him.  The discharger may be the best source of information since many states
require dischargers to maintain a self monitoring program.  Pollutant load
per day and pollutant concentration data are usually included in this
information.  Second, essentially all point source discharges are required
to obtain a discharge permit.  The state or federal agency issuing these
permits will have on file maximum allowable limits for the discharge.  These
limits can be used as an upper bound waste loading rate.  Third, state water
quality or water resource agencies often have conducted sample collection
programs for significant discharges.  Fourth, data for a similar facility
within the  local region  (same activity, same general size) may be used as an
estimate for an  unknown  waste load.   If none of these are available the
following procedure  may  be used.
 3.4.2   Estimation  of  Municipal Waste Loads

     The equation  for estimating  municipal waste  loads  is  shown  below.
 Basically this  method involves computing  an  influent  load  and  reducing  that
 load according  to  removal  efficiency based on  treatment type.  The  equation
 is
                    Y(p)m =
 where
      Y(P)   is the waste load being delivered from the treatment plant
          m
             to the stream (Kg/day)
      Q      is the flow per capita per day
      P      is the population being served by the treatment facility
      C      is the concentration of a particular pollutant in raw
             domestic sewage (yg/1) and
       e     is the removal efficiency based on treatment type.
                                   298

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3.4.2.1 Evaluation of Parameters in the Municipal Waste Loading Equation

     The utilization of domestic water depends on a number of factors.
Among them are:

     •   geographic location
     •   climate
     •   degree of industrialization and
     •   size of community

     A reasonable estimation of water comsumption in different parts of the
country is found in Table 111-45.  Average water consumption per capita by
state and selected municipalities are shown.  The user should note the large
variations in the table.  These rates can be used for the parameter Q  if
more site specific data is unavailable.

     Typical concentrations of conventional wastewater constituents in
untreated domestic wastewater (mg/1)  is shown in Table 111-46.  If the
relative strength of the raw sewage  is unknown,  use of the higher values are
recommended.

     Removal efficiencies vary greatly depending upon the constituent and
upon treatment process.  Typical removal efficiencies are shown in
Table  111-47.

     An example of  the  differences  in  loadings of untreated  and treated
domestic sewage are  shown in Table  111-48.
 3.4.3   Industrial  Waste  Loads

      Industry  is  a source of many  types of  pollutants.  Of the conventional
 pollutants,  they  are  primarily  sources of  BOD,  suspended  solids,  COD,  and
 oil  and grease.   They are also  primary sources  of  toxic organic  pollutants
 and  metals  as  will  be discussed in the next section.
                                  299

-------
co
o
o
                                                            TABLE 111-45




                    WATER WITHDRAWALS  FOR PUBLIC SUPPLIES BY STATES AND BY SELECTED  MUNICIPAL SYSTEMS, 1970
State, city
Alabama:
Birmingham
Alaska:
Anchorage
Arizona:
Phoenix
Arkansas:
Little Rock
California:
Los Angeles
San Francisco
Colorado:
Denver
Connecticut:
Hartford
Delaware
Florida:
Miami
Georgia:
Atlanta
Hawaii :
Honolulu
Idaho
Illinois:
Chicago
Indiana:
Indianapolis
Iowa:
Des Moines
Kansas:
Wichita
Kentucky:
Louisvil le
Louisiana:
Shreveport
L/
capita-d
806
576
1790
769
787
864
503
784
685
686
1424
746
955
541
564
700
617
1208
946
564
746
780
897
772
871
534
508
466
534
587
508
314
655
545
519
gal/
capita-d
213
152
473
203
208
228
133
207
181
181
376
197
252
143
149
85
163
319
250
149
197
206
237
204
230
141
134
123
141
155
134
83
173
144
137
State, city
Maine:
Portland
Maryland:
Baltimore
Massachusetts:
Boston
Michigan:
Detroit
Minnesota:
St. Paul
Mississippi :
Jackson
Missouri :
Kansas City
Montana:
Billings
Nebraska:
Omaha
Nevada:
Las Vegas
New Hampshire
New Jersey:
Elizabeth
New Mexico:
Albuquerque
New York:
New York City
Rochester
North Carolina:
Greensboro
North Dakota:
Fargo
Ohio:
Akron

L/
cap1ta-d
553
580
515
648
530
883
636
671
473
515
507
432
485
587
826
754
636
742
1154
1038
435
526
314
772
746
609
1046
663
644
492
477
515
594
492

gal/
capita-d
146
153
136
171
140
233
168
177
125
136
134
114
128
155
219
199
168
196
305
274
128
139
83
204
197
161
276
175
170
130
126
136
157
130

State, city
Oklahoma:
Tulsa
Oregon:
Portland
Pennsylvania:
Pittsburgh
Rhode Island
South Carolina:
Charleston
South Dakota:
Sioux Falls
Tennessee:
Memphis
Texas:
Dallas
Houston
Utah:
Salt Lake City
Vermont
V i rg i n i a :
Richmond
Washington:
Seattle
West Virginia:
Morgantown
Wisconsin :
Mi Iwaukee
Wyoming:
Chenne
District of Columbia
Puerto Rico
United States*



L/
capita-d
492
595
712
1129
685
485
462
916
652
549
587
488
549
587
610
947
1113
523
553
420
644
1200
1091
568
549
587
659
746
841
799
326
628



gal/
capita-d
130
157
188
298
181
128
122
242
172
145
155
129
145
155
161
250
294
138
146
111
170
317
288
150
145
155
174
197
222
211
86
166



           Note:  L x 0.2642 = gal.
           Source:  Metcalf and Eddy, 1979.

-------
                                TABLE  III-46
                  TYPICAL MUNICIPAL WASTE CONCENTRATIONS
                                                         Concentration ma/1
Constituent
Solids, total
Dissolved, total
Fixed
Volatile
Suspended, total
Fixed
Volatile
Settlable solids, (ml/liter)
Biochemical oxygen demand, 5-day, 20° (BOD5-20°)
Total organic carbon (TOC)
Chemical oxygen demand (COD)
Nitrogen, (total as N)
Organic
Free ammonia
Nitrites
Nitrates
Phosphorus (total as P)
Organic
Inorganic
Chlorides*
Alkalinity (as CaC03)*
Grease
Strong
1,200
850
525
325
350
75
275
20
400
290
1,000
85
35
50
0
0
15
5
10
100
200
150
Medium**
720
500
300
200
220
55
165
10
220
160
500
40
15
25
0
0
8
3
5
50
100
100
Weak
350
250
145
105
100
20
80
5
110
80
250
20
8
12
0
0
4
1
3
30
50
50
 *Values should be increased by amount in carriage water.
**In the absence of other data use medium strength data for planning purposes,
Source:  Metcalf and Eddy, 1979
                                      301

-------
                                   TABLE  III-47

             MUNICIPAL WASTEWATER  TREATMENT SYSTEM PERFORMANCE
Influent: "Raw-Medium Strength Domestic Sewage" see Scheme Number 0 for characteristics.
Effluent Concentrations (ma/1), (% Total Removal Efficiencies*)
Scheme Number** BOD,
o 200(rr)
Raw waste water v '
1 130(35%)
2 40
(80%)
3 25(88%)
4 18
5 18
61 ^
( 94»)
7 2/
COD
50V)
375(252)
125
100(80S)
70(86%)
70(86%)
60(88%)
«(97«
SS PT, (mgP/1) NT, (mgn/1 )
?nn IA An
ZOO(OS) 10(OS) 40(0i)
100(25S) 9(102) 32(202)
30 7.5 26
(85%) (25%) (355)
12(94%) ' 7(30S) 24(40%)
7(95^) ^90%) 22(45%)
7(95S) ^90%) 4(90%)
^gg.Si) ^gox) 3(92%)
^99. 5%) ^gOS) 2(95S)
       *   Efficiencies for wastewater treatment are  for the approximate concentration  range,
          as measured by BOD5, of TOO < BODg S 400,  (mg/1).


       **  Scheme No.  Process

               0      No treatment.
               1      Primary
               2      Primary, plus Activated Sludge (Secondary Treatment)
               3      Primary, Activated Sludge,  plus Polishing Filter (High Efficiency or
                      Super  Secondary)
               4      Primary, Activated Sludge,  Polishing Filter,  plus Phosphorus  Removal
                      and Recarbonation
               5      Primary, Activated Sludge,  Polishing Filter,  Phosphorus Removal, plus
                      Nitrogen Stripping and Recarbcnation
               6      Primary, Activated Sluage,  Poiisning Filter,  Phosphorus Removal, Nitrogen
                      Stripping Recarbonation, plus Pressure Filtration
               7      Primary, Activated Sludge,  Polishing filter,  Pnosphorus Removal, Nitrogen
                      Stripping Recarbonation, Pressure Filtration, plus Activated  Carbon
                      Adsorption
Source:   Meta  Systems,  1973
                                             302

-------
OJ
o
                                                         TABLE 111-48

                POINT  SOURCE LOADINGS OF SIX MAJOR WASTEWATER TREATMENT FACILITIES  IN  ONE NORTH  CAROLINA 208 AREA
FACILITY NAME
Norths ide
Third Fork
New Hope
.Chapel Hill
Walnut Creek
Ilil Isborough
SUB-TOTAL
FLOW
(MGD)
8.4
3.4
3.4
3.8
20.3
0.56
39.9
BOD C
INFLUENT
16,673
7,231
5,473
5,166
64,673
957
100,173
b/day)
EFFLUENT
1,331
993
1,758
824
11,005
383
16,294
S.S.
INFLUENT
13,731
5,189
4,197
5,071
23,702
934
52,824
Ib/day)
EFFLUENT
2,522
2,410
1,361
1,363
7,111
234
15,001
Sludge Production
(Ib/day Dry Solids)
4,300
3,300
318
3,000
6,255

17,173

-------
     Because of the difficulty in characterizing industrial  wastes in
general, the user is advised to get as much data as possible locally.
Water use (flow rate) as well as variety in unit processes will have a
profound effect on pollutant loads.  If local data is unavailable, the
best sources of information on industrial waste characterization  is the
"Effluent Guidelines" series of reports by the U.S. EPA.  A report is
available for each of the EPA point source categories.  These reports
contain typical waste characteristics for various processes within the
point source category as well as process water usage and are listed  in
the references at the end of the chapter.  Effluent limitations are
also given  which can be used as upper bound concentrations  in water
quality assessments.

      In addition to  process  variation,  industries  also  employ various
types of waste reduction measures  in  the plant  and  in plant wash
treatment facilities.   In-plant measures include

      •    recirculation  of  non-contaminated water
      •    segregation of contaminated  and non-contaminated waters
          prior to  treatment
      0    removal  of semidry residues  and
      •    flow reduction

      Eckenfelder (1970) presents information on industrial  waste
 concentrations and loads,  waste reduction  measures and  industrial waste
 treatment.

      Table 111-49 contains some typical pollutant loads which might
 result from the industries shown.  Table 111-50 also presents loads for
 some industries and typical removal efficiencies and expected loads.
 These waste water treatment processes are  representative though not
 exhaustive of techniques which may be used.   Values in  Tables 111-49
 and 111-50 are for comparison only.  They should not be used for load
 projecting in other areas.
                                304

-------
OJ
o
in
                                                             TABLE  III-49


                                       TYPICAL  INDUSTRIAL DISCHARGE POLLUTANT CONCENTRATIONS
r 	
Industry
Primary Metal2
Cu, Brass Rods3
Roofing Materials3
Steel Plate, Wire3
Petroleum (General)2
Oil Production^!)3
Oil Production(#2)3
Oil Production(#3)3
Paper (General)2
Paperboard3
Paper3
Primary Inorganic2
Alky Lead Fluoro
Hydrocarbons3
Inorg. Acids3
Primary Organic2
Caustic Chemicals3
Plant Food3
Flow
Rates ,
mg/1000 Ib1
0.2-1.6
0.04
0.01
0.004
0.005
0.003
0.003
0.001
0.015
0.017
0.024
0.002
0.002
0.004
0.002
0.021
0.001
BOD
lb/1000 Ib
_
0.1
13.6
0.56
1.3
0.57
0.45
0.45
18
19.6
12.6
0.2-3.5
0.39
0.08
U1.9
1.24
0.03
COD
lb/1000 Ib
_
0.5
25.7
2.7
3.7
2.1
1.3
2.9
55
64.8
43
-
0.89
0.52
-
4.9
1.43
TSS
lb/1000 Ib
„
0.02
14.2
5.1
-
0.58
0.86
• 0.65
28
37.9
33.1
5-30
0.15
5.37
_
19.9
0.01
Total N
lb/1000 Ib
32
0.07
0.34
0.04
0.4
0.33
0.16
0.24
-
0.05
0.03
0.03-0.7
0.03
0.04
3-7
1.27
1.17
Total P
lb/1000 Ib
15
-0
-0
0.01
_
0.01
0.01
0.01
-
_
..
0.8-9.0
„
0.02
0.15-0.3
0.3
0.14
Heavy
Metal
lb/1000 Ib
55-242
-
0.13
1.2
0.003
0.05
0.03
0.04
-
-
-
0.05-0.3
..
0.33
0.01-0.02
1.69
0.02
Oil &
Grease
lb/1000 Ib
-
-
0.68
0.12
0.15
0.14
0.09
0.31
-
-
-
0.06-2
0.1
0.06
0.05-0.08
0.24
0.02
               1   Units are million gallons  of pollutant per 1000 Ib. of finished  product


               2   Kaiser Engineers, 1969


               3   Pearson, Storrs, Sellech,  1969

-------
                                                         TABLE 111-50

                         SUMMARY OF CURRENT AND PROJECTED WASTE LOADS IN ONE REGION 208 AREA (BY SIC CODE)
OJ
o
cr>
SIC GROUP
No.
201
202
204
205
208
211
22_
226
251
265
27
28_
32_
35_
36_
379
---
9999

Description
Meat Products
Dairy Products
Grain Mill Prods.
Bakery Prods.
Soft Drinks
Tobacco Man.
Textile Mill
Dyeing & Fin.
Furniture
Paperboard Con.
Print. & Pub.
Chem. & Allied P.
Stone, Clay P.
Machinery.
Elect. Equip.
Transp. Equip.
Non-Manuf.
Mun. W.W.T.P.
TOTALS
CURRENT LOADINGS
BOD
(Ib/day)
Sewer
1,523
973
180
935
330
2,024
2,530
0
0
245
0
64
0
32
659
100
1,374
0
10,469
SS
(Ib/day)
Sewer
1,059
400
50
910
40
1,750
2,173
0
0
150
0
29
0
79
402
100
170
0
7,312
BEST PRACTICABLE WASTE REDUCTION TECHNOLOGY
Description
Anaerobic Lagoon to Stabilization Pond
Anaerobic Digestion & Clarification
Oxidation Ditch & Clarification
Rotating Bio-Filters & Clarification
Fixed Activated Sludge
Activated Sludge (E.A.) & Clarification
Activated Sludge & Alum-Aided Clarif.
Carbon Adsorption & Clarification
—
Screening, Ext. Aeration, Clarification
--
Activated Sludge & Clarification
Stilling Ponds, Water Recycle
Oil & Grease Traps
Ion Exchange (for Plating Process)
Oi 1 & Grease Traps
See Text
Upgrade Six Largest Plants
--
Expected
Reductions
BOD ( %)
90
85
85
85
84
85
85
75
--
35
--
85
30
50
10
50
70
SS(X)
85
90
75
65
65
75
75
60
—
65
--
75
70
65
90
65
90
Varies for
Each Plant
--
PROJECTED LOADINGS
BOD
(lb/aay)
Sewer
152
71
27
140
53
304
380


159

10

16
593
50
412

2,367
SS
(Ib/day)
Sewer
117
40
13
319
14
438
543


53

18

28
40
50
17

1,690

-------
3.4.4  Priority Pollutants in Municipal and Industrial Waste Waters

     The priority pollutants which appear in municipal wastewaters comes
from three main sources

     •   industrial effluents
     •   nonpoint source runoff and
     •   domestic uses

     The proportion from each category will vary from location to  location
as well.  The  types of pollutants  in Table  111-51  are those occurring most
frequently  in  household wastewaters.

     According to  the  data  of Feiler  (1980) of  the 129 priority  substances
only 27 occurred at least 30 percent of  the time in his sampled  treatment
plant  influents (Table  111-52).   Of those  27, eight were metals.   Of the
five most frequently detected,  three were  metals (zinc, copper and
chromium).   The loading of  metals in  the influent  is substantially affected
by the percentage  of industrial  effluent as shown  in Figure  111-18.  The
slope  of  the regression  line is 72.86  yg/1/percent.

     The  mixture of priority substances  found  in municipal  influent will
depend primarily on the mixture of industries  contributing  flow.
Table  111-53 contains  42  of the 129 priority  pollutants categorized by the
 industrial  effluents  in  which  they will  likely be  found.  This  table is
 based  on  screening data provided by U.S. EPA  (Neptune, 1981).  The 42  which
 appear are those which most frequently appeared in the screening data.   The
 intent of the table is not to imply that these chemicals are necessarily the
 most problematic (i.e.  carcinogenic, toxic)  but only that they are the most
 ubiquitous.  Characterization of influent concentrations for these
 pollutants  is not currently possible.  Maximum and minimum values such as
 those shown in Table 111-52 are more typical  of the  available data.  Jf data
 for a particular priority pollutant is necessary  some  sampling of the
 influent and effluent of the treatment plant is recommended.
                                      307

-------
                     TABLE 111-51

  PREDICTED PRIORITY POLLUTANTS IN HOUSEHOLD WASTEWATER


Organ ics_                                 Inorganics

benzene                                  arsenic
phenol                                   cadmium
2,4,6-trichlorophenol                    chromium
2-chlorophenol                           copper
1,2-dichlorobenzene                      lead
1,4-dichlorobenzene                      mercury
1,1,1-trichloroethane                    zinc
naphthalene                              antimony
toluene                                  silver
diethylphthalate
dimethylphthal ate
trichloroethylene
aldrin
dieldrin
 Source:   Hathaway,  1980
                              308

-------
           TABLE 111-52°
OCCURRENCE OF PRIORITY POLLUTANTS
    IN POTW INFLUENT SAMPLES


Parameter
Zinc
Copper
Cyanide
Chromium
Toluene
Tetrachl oroethyl ene
Chloroform
Methylene Chloride
Trichloroethylene
Bis(2-ethylhexyl) phthal
1,1,1-Trichloroe thane
Nickel
Ethylbenzene
Silver
Phenol
Lead
Cadmium
Mercury
Benzene
Di-n-butyl phthalate
Diethyl phthalate
Butyl benzyl phthalate
Number of
Samples
Analyzed
146
146
150
146
152
152
152
152
152
ate 152
152
146
152
146
152
146
146
146
152
152
152
152
1,2-Trans-dichloroethylene 152
Naphthalene
1,1-dichloroethane
1,1-dichloroethylene
1,2-dichlorobenzene
? Only those substances
° Source: Feiler, 1980
^ 11 nl 4- r* ^-C ,.,-,/ 1
152
152
152
152
detached at least

Percent
of Times
Detected
100
100
99
99
98
97
96
95
95
94
91
87
86
84
83
79
71
70
68
63
62
59
58
55
40
35
30
30% of the



c c
Minimum Maximum
23
34
3
8
2
2
1
1
1
2
1
11
1
2
1
16
1
200
1
1
1
2
1
1
1
1
2
time are

7680
1190
2500
2380
500
1100
430
11000
860
390
1600
1930
448
77
380
935
1800
3900
1560
105
33
140
97
150
24
243
440
included.

                  309

-------
     10000
                   i     r
i      i
       8000
       6000
C
O
tO
s_
+->
c
QJ
O
c
o
4000
       2000
                         »      I	L
                                              J	L
                        10
                             20         30


                           % Industrial Flow
                4 0
5 0
     FIGURE  III-13   CORRELATION OF  INFLUENT TOTAL  METALS CONCENTRATION

                     TO PERCENT  INDUSTRIAL FLOW


       Source:  Feiler, 1980
                                  310

-------
                                   TABLE  111-53

                  INDUSTRIAL CATEGORIES AND FREQUENTLY  DETECTED
                          PRIORITY POLLUTANTS BY CATEGORY


Benzene
Carbon tetrachloride
Chlorobenzene
1,2 dichloroethane
1,1,1 trichloroethane
Chloroform
1,1 dichlosoethylene
1,2 trans-dichlosoethylene
2,4 dimethyl phenol
Ethylbenzene
Methylene chloride
Oi ch 1 orobromonethane
Tnchlorof luoromethane
Naphthalene
Pentachlorophenol
Phenol
Bis(2-ethylhexyl) phthalate
Butyl benzyl phthalate
Di-n-butyl phthalate
Di-n-octyl phthalate
Dimethylphthalate
Chrysene
Anthracene
Flourene
Phenanthrene
Pyrene
Tetrachloroethylene
Toluene
Trichloroethylene
Antimony
Arsenic
Beryllium
Cadmium
Chromium
Copper
Cyanide
Lead
Mercury
Nickel
Silver
Thallium
Zinc
& Detergents
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Source:  Neptune, 1980
                                              311

-------
     The evaluation of priority pollutant loads in municipal  wastes is the
same as for conventional parameters.   First, the influent concentration is
estimated and then the removal of the substance is estimated.  Data such as
that found in Table 111-54 can be used to estimate the removal efficiency
for some compounds.

     The data of Table  111-55 give typical concentrations of some priority
pollutants in municipal primary and secondary effluent.
                               -EXAMPLE III-8
                       Estimation of Municipal Waste
                    Treatment Loads of Trichloroethylene

     A municipal waste treatment plant has a mean  influent concentration of
40  ug/1  of  trichloroethylene.  The plant employs a trickling filter for
secondary treatment.  Estimate the daily trichloroethylene effluent load.
The  plant flow rate is 1 mgd.

Solution:

     From Table  111-54 the removal efficiency of trickling filters for
trichloroethylene  (TCE)  is 96 percent.

     Equation  111-64  gives the effluent  load.  Since  the  plant flow rate is
known  the estimate of flow (Q  • P ) is  not necessary.  The flow rate of 1
                              P    P
mgd  (3.8 x  106  I/day) can be  substituted for  (Q   • P  ).

                         Y(TCE)  = 3.8 x 10&  (40)(l-.96)  x 10"9
                               m

                                  =  6 x  10"3  kg-TCE/day
                             END OF  EXAMPLE  111-8
                                     312

-------
                                                        TABLE 111-54


                        REDUCTION  OF  CONVENTIONAL  AND  PRIORITY POLLUTANTS BY POTW TREATMENT PROCESSES
OO
I—'
OJ


Fraction
Conventionals



Organlcs














Meta 1 s








( 1 ) Two Plant


Parameter
BOO
Total Suspended Solids
COD
01 1 and Grease
Benzene
1,1,1 - Tr Ichloroethane
Chloroform
1,2 - Trans-Dlchloroethylene
Ethyl benzene
Methyl ene Chloride
Tetrachloroethylene
Toluene
Tr Ich loroethylene
Phenol
Naphthalene
Bis (2-Ethylhexyl) Phthalate
Butyl Benzyl Phthalate
DI-N-Butyl Phthlate
Dl ethyl Phthlate
Cad ml urn
Chromium
Copper
Cyanide
Lead
Mercury
Nickel
Si Iver
Zinc
data base (3) Seventeen
(2) Three Plant data base (4) One plant

Pr imary
Treatment 1
17
39
13
52
23
47
23
68
25
14
-
-
30
55
0
-
36
99+
II
_
0
24
57
-
-
-
17
27
plant data
data base

Trickling
) niter<2)
93
94
62
69
96
92
60
98
92
47
78
87
96
96
99+
54
97
0
96
74
74
89
81
94
99+
25
95
80
base

Percent Removal
Activated
Sludge(3)
95
94
90
89
95
87
79
57
92
77
82
71
89
13
28
78
48
31
10
92
91
90
71
74
54
60
83
86
(5) Three plant


Activated
Sludge(4)
90
88
80
90
99+
38
11
99+
80
27
-
96
44
99+
99+
40
99+
99+
99+
99+
76
84
53
99+
86
18
99+
83
data base


Tert 1 ary
Treatment (5)
95
98
91
71
99+
99
25
99+
98
92
98
99
99
99
-
60
99+
64
99+
99+
87
88
-
97
86
51
99+
87



-------
                       TABLE III-55
CONCENTRATIONS (MEAN t STANDARD ERROR) OF  EPA  PRIORITY
POLLUTANTS  IN  THE LOS ANGELES  COUNTY JWPCP  EFFLUENTS3

Flow (liters/yr x 10")
PH
General constituents (mg/liter)
Total suspended solids
Oil and grease
Ammonia nitrogen
Nitrate nitrogen
Total (K) nitorgen
Total phosphorus
BOO
COD
Fecal coliform (MPN/lOOml)
Volatile organics (pg/liter)
Benzene
Carbon tetrachloride
Chlorobenzene
1,2-dichloroethane
1,1,1-trichloroethane
Chloroform
Ethyl benzene
Methyl ene chloride
Dichlordifluoromethane
Dichl orobronomethane
Tetrachl oroethyl ene
Toluene
Trichloroethylene
Extractable organics (yg/liter)
Acenaphthene
1,2-dichlorobenzene
1,4-di Chlorobenzene
2,4-dimethylphenol
Bis (2-chloroethoxy) methane
Naphthalene
Nitrobenzene
N-ni trosodiphenyl amine
Phenol
Pentachlorophenol
Bis (2-ethylhexyl) phthalate
Di-n-butyl phthalate
Diethyl phthalate
Dimethyl phthalate
Miscel laneous
Asbestos (lOVliter)
Cyanide tug/liter)
Phenol (mg/liter)
Trace metals (mg/liter}
Antimony
Arsenic
Beryll ium
Cadmium
Chromium
Copper
Mercury
Manganese
Nickel
Lead
Selenium
Si Iver
Thallium
Zinc
Primary
4.71
7.3

131
34
37
NA
49
20
200
460
7.5 x 10s

200 ± 34
12 ±2
12 ±1
<10
130 ± 15
34 ± 0
130 ± 6
24 ± 2
6
<10
54 ± 14
310 ± 24
140 ± 5

<10
<10
<10
14 ± 2
<10

-------
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                                     320

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                                 CHAPTER 4

                             RIVERS AND STREAMS
4.1  INTRODUCTION
     The purpose of this chapter is to present simplified tools which can be
used to predict responses of rivers and streams to the impact of pollutants.
The introductory sections to the chapter should be read prior to solving any
problems in order to become familiar with the topics that will be covered
and the limitations of the formulations presented.

     Rivers throughout this country are subject to a wide spectrum of
geological, biological, climatological , and anthropogenic impacts which
produce a variety of water quality problems.  Approaches which provide
guidance to the solution of these problems, especially ones restricted to
hand calculations, must be limited in scope.  The following guidelines have
been used in selecting topics to be considered in this chapter:  1.  widely
occuring problems, 2.  those amenable to hand calculations, and 3.  those
for which planners can obtain sufficient data.
4.1.1  Scope

     The major problem areas to be considered are:

     •   Carbonaceous (CBOD) and Nitrogenous (NBOD) Biochemical Oxygen
         Demand
     »   Dissolved Oxygen
     •   Temperature (with a discussion of low flow)
     •   Nutrients and Eutrophication Potential
     •   Coliform Organisms
     •   Conservative Constituents
     •   Sedimentation and Suspended Solids
     •   Toxic Substances
                                  321

-------
     Beginning in 1974, the U.S.  Environmental  Protection Agency has  for
several years published the National  Water Quality Inventory which is a
compilation of current water quality conditions and recent trends in  the
nation's rivers and lakes.  Several  of the tables  in that report series are
relevant to this document and are included here.   Table IV-1 illustrates
reference water quality levels used  to define acceptable pollutant limits in
U.S.  waterways.  Table IV-2 shows water quality conditions in eight  major
waterways in the United States, while Table IV-3 summarizes the most  widely
observed water quality problems in the U.S.  These tables will be cited
throughout this chapter.

     Local water quality standards,  when they exist, are preferable to the
general guidelines provided in Table IV-1.  Table  IV-4 shows example
standards for dissolved oxygen and water temperature for the states of
Virginia and Maryland.  Parts of the standards are significantly different
from the reference levels in Table IV-1.  For example the daily average
dissolved oxygen standard for natural trout water  for the state of Virginia
is 7.0 mg/1, while 5.0 mg/1 is recommended for the protection of aquatic
life (Table IV-1).  Thus, when local  standards exist, they should be  used in
lieu of general reference levels.
4.1.2  Significance of Problem Areas

     Oxygen depletion is often the result of excessive CBOD and NBOD
loadings particularly in combination with high temperature and low flow
conditions.  Increased nutrient loadings to streams which produce elevated
ambient concentrations can pose substantial potential  for eutrophication.
The nutrient problem is currently one of the most widespread areas of
concern regarding river water quality.  The health hazards category in Table
IV-3 lists elevated coliform levels as a problem of particular concern in
northeastern and Great Lakes States.  Salinity has been identified as a
major problem in the central and southwestern states.
                                   322

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                            TABLE IV-1


         REFERENCE LEVEL VALUES OF SELECTED WATER QUALITY

          INDICATORS FOR U.S. WATERWAYS (U.S. EPA, 1976)
    Parameter
     Reference Level
Ammonia


Color


Dissolved Oxygen


Dissolved Solids

Fecal Coliforms



Nitrate-N

pH


Phenols

Suspended Solids and
  Turbidity


Total Dissolved Gases
£ 0.02 mg/1 as unionized ammonia
       (for freshwater aquatic life)

£ 75 platinum-cobalt units (for
     water supply)

>_ 5.0 mg/1 (to maintain fish
      populations)

£ 250 mg/1 (for water supply)

log mean £ 200 per ml over 30 days
and 90 percent £ 400 per ml (for
bathing waters)

£ 10 mg/1 (water supply)

between 6.5 and 9.0  (for freshwater
aquatic life)

£ 1 yg/1  (for water supply)

shall not reduce the depth of the
compensation point by more than
10 percent (aquatic life)

£ 110 percent saturation (aquatic
      life)
                                  323

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                                                         TABLE   IV-2
                                         CONDITION OF  EIGHT MAJOR  WATERWAYS  (EPA,1974)
River
Harmful
Substances
Physical
Modification
Eutrophication
Potential
CO
ro
               Mississippi
               Missouri
               Ohio
               Tennessee
                Detroit area
                rivers
               Columbia
Trace metals
present in middle
river

High*, increasing
iron and
manganese
Cyanide  present
but dimishing
Severe gas super
saturation;  some radio-
activity in lower river
High* turbidity and
solids below
Missouri River

High* suspended solids,
turbidity in middle and
lower river

High* suspended solids
in lower river, some
improvements
Suspended solids
improving, local
temperature effects
from discharges

Occasional high*
temperatures
High*, increasing
nutrients but no
algae

High*, increasing
nutrients but no
algae

High* nutrients but
no algae
Small increase in
nutrients but no
algae

Nutrients discharged
to Lake Erie
decreasing
High* nutrients but
no algae, except for
slime growths in
lower river
               Snake
Severe gas super-
saturation, signif-
cant pesticides
Turbidity from
natural  erosion,
agricultural  practices,
reservoir flushing
Nuisance algal
blooms each
summer

-------
                                                     TABLE1 IV-2 (continued)
River
Willamette
Harmful
Substances
Significant sulfite
Physical
Modification
High* turbidity at
Eutrophication
Potential
High* level of
                                    waste  liquor  from
                                    pulp and paper wastes
                             high flow, high
                             temperature in summer
                                      nutrients but
                                      not excessive algae
                  River
GO
ro
                Mississippi
                Missouri
                Ohio
                Tennessee
                Detroit area
                rivers
 Salinity, Acidity,
   and Alkalinity	
               Oxygen
              Depletion
High* salinity, acidity
below major
tributaries
High* dissolved salts
in middle and lower
river

Low* alkalinity
especially in upper
river
                             Health Hazards and
                            Aesthetic Degradation
Acids and chloride
improving despite
large discharges
low,1
          Oxygen-demanding
          loads from large
          cities evident
High* organic loads
from feedlots,
improved near cities

Occasional  low*
dissolved oxygen near
Cincinnati  and Pittsburgh

Low* BOD  and
decreasing  COD in
reservoirs

Low* dissolved oxygen
only at mouths of
area tributaries
Commercial fishing
eliminated in lower
river by phenols,
bacteria near cities

High* bacteria and
viruses present in wet and
dry periods

High* bacteria especially
in high population
areas

High* bacteria in small
areas near cities, low
radionuclides

Phenols decreasing,
bacteria unchanged-
to-higher

-------
                                     TABLE IV-2 (continued)
                      Salinity,  Acidity,                Oxygen                  Health Hazards and
  River	and Alkalinity	Depletion	Aesthetic Degradation

Columbia             Approaches  ideal              Dissolved oxygen            Very low* bacteria
                     for fresh waters              close to saturation

Snake                High* dissolved              Dissolved oxygen            High* bacteria
                     solids from irrigation       close to saturation         below population
                     in middle river                                          centers

Willamette           Low* dissolved mineral       Improved dissolved          High* bacteria, but
                     salts, improved pH           oxygen, no standards        improving
                                                  violations


*High (or low) relative to other rivers,  or relative to other sections of river,  or to
 national reference levels.  Does not  necessarily imply standards  violations or
 dangerous condition.

-------
                                                          TABLE IV-3
co
ro
                                        WATER QUALITY PROBLEM AREAS REPORTED BY STATES*

                                          NUMBER REPORTING PROBLEMS/TOTAL (EPA,1975)

Oxygen
depletion
Eutrophi-
cation
potential
Health
hazards
Salinity,
acidity,
alkalinity
Physical
modification
Harmful
substances
Middle
Atlantic,
Northeast
11/13

11/13


11/13

3/13


7/13

6/13

South
9/9

6/9


8/9

6/9


3/9

6/9

Great
Lakes
6/6

6/6


5/6

2/6


3/6

5/6

Central
6/8

8/8


8/8

6/8


8/8

4/8

Southwest
4/4

2/4


3/4

4/4


3/4

4/4

West
6/6

6/6


5/6

4/6


6/6

2/6

Islands
4/6

4/6


5/6

2/6


5/6

3/6

Total
46/52

43/52


45/52

27/52


35/52

30/52

               * Localized or statewide  problems  discussed  by the  States  in  their reports.

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                                                              TABLE  IV-4
                                                EXAMPLE RIVER WATER  QUALITY STANDARDS
                                                             VIRGINIA
CO
ro
oo
CLASS
III
IV
V
VI
DESCRIPTION
COASTAL AND PIEDMONT
MOUNTAINOUS
PUT AND TAKE TROUT WATERS
NATURAL TROUT WATERS
DISSOLVED
MINIMUM
4,0
4.0
5.0
6.0
OXYGEN
AVERAGE
5.0
5.0
6.Q
7.0
TEMPERATURE,
*TN
5
5
5
5
°F
'MAX
90
37
70
68
MARYLAND
CLASS
I
III
IV
DESCRIPTION
WATER CONTACT, RECREATION
NATURAL TROUT WATERS
RECREATIONAL TROUT WATERS
DISSOLVED OXYGEN*
MINIMUM AVERAGE



4.0 5.0
5.0 6.0
4.0 5.0
TEMPERATURE
MAXIMUM, °F**
90
63
75




                       *THESE VALUES APPLY EXCEPT WHERE LOWER  VALUES OCCUR NATURALLY.

                      **THESE APPLY OUTSIDE  THE MIXING ZONE,  IF  NATURAL  TEMPERATURE OF RECEIVING WATER

                        IS GREATER THAN THE  STANDARD, THEN THAT BECOMES THE  STANDARD.

-------
     Because of their importance, each of the problem areas described will
be addressed in this chapter.  As shown in Table IV-5, many states routinely
measure the parameters associated with these problems.  The total number of
states responding to the survey was 47.  Because of the routine surveys
conducted, data are commonly available for performing hand calculations.
NBOD, though not directly measured, can be found from measurements of
organic and ammonia nitrogen.  Chloride concentration measurements can be
directly converted to salinity.
4.1.3  Applicability to Other Problems

     The tools which are presented in this chapter are designed to address
specific water quality problems.  However, a number of the tools, which are
based on the law of mass conservation, can be directly applied to other
problems with little or no modification.  In the case of temperature
prediction, an energy balance is used (which is analogous to a mass
balance).

     The degree of commonality of source and sinks of a particular pollutant
e.g. a nutrient) or water quality indicator (e.g. dissolved oxygen) is
responsible for the similarities and differences among the specific
equations.  For example, CBOD and NBOD produce a similar general effect
(oxygen depletion), generally have similar sources and sinks, and for
purposes of this study, are assumed to follow first order decay kinetics.
Coliforms, also assumed to decay by first order kinetics, are handled by the
mass-balance approach.  Conservative substances are different from BOD and
coliforms in that they do not decay.  Finally, there are some instances
where a more subjective analysis is indicated, and neither a mass nor energy
balance is presented.

     Once the similarities among water quality parameters are understood,
handling two seemingly different problems can often be accomplished in a
straightforward and similar fashion.  For example, the distribution of toxic
substances that are either conservative or follow a first order decay may be
evaluated using techniques described for conservative substances and
coliforms, respectively.
                                   329

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                              TABLE  JV-5

                       WATER QUALITY PARAMETERS
                COMMONLY MONITORED BY STATES* (EPA,1975)
                                             Number
        Parameter	of States

      Flow                                      47
      Dissolved  oxygen                          47
      Coliform bacteria                         45
      Nitrogen (any  form)                       39
      Phosphorus  (any form)                     35
      PH                                        35
      BOD/COD/TOC                              27
      Water  temperature                         29
      Turbidity                                 26
      Solids  (any type)                         27
      Metals  (any type)                         17
      Chlorides                                 19
      Alkalinity                                15
      Conductivity                              16
      Color                                     11
      Sulfate                                   14
*0nly parameters listed by at least 10 States  and  specified  as  being
part of each State's monitoring program are included.
                                 330

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4.1.4  Sources of Pollutants

     Pollutant loadings originate from three general sources:  point,
nonpoint, and natural.  Each of these can constitute a major hurdle in
meeting the 1983 goals of fishable and swimmable waters.  Specifically,
point sources (30 states), nonpoint sources (37 states), and natural
conditions (21 states) are all major contributors to water quality problems
(EPA, 1975).

     It  is imperative that the capacity to assess impacts of nonpoint
sources  be a part of the hand calculation methodology for rivers.  Table
IV-6 illustrates the importance of nonpoint source nutrient loading for
selected rivers in Iowa.  Up to 96 percent of the annual phosphorus load and
up to 99 percent of the total nitrogen load are from nonpoint sources.
Admittedly, quantification of nonpoint source loads is often difficult.
Nevertheless, simplified nonpoint source terms will be included in some of
the mass-balance formulations.  The methodology supplied in Chapter III  can
be used  to estimate the nonpoint source loading rates.
4.1.5  Assumptions

     In deriving the mass-balance equations, a number of assumptions were
made.  Users should be aware of each assumption so that the tools are not
misapplied.  The most important assumptions are:

     •   The system is at steady-state
     t   Dispersion is small compared to advection (i.e. plug flow is
         assumed)
     •   The river system is vertically and laterally mixed
     •   When pollutants decay, the rates are first order.

     The steady-state assumption means that conditions are not changing with
time, but only as a function of distance along the river.  The time scale
for steady-state generally should be on the order of a week or longer.  For
                                    331

-------
                                                           TABLE  IV-6
                        ANNUAL  PHOSPHORUS AND  NITROGEN LOAD FOR SELECTED IOWA RIVER BASINS  (EPA,1975)
CO
CO
r\>
River
Floyd
Little Sioux
Char i ton
Des Moines
Iowa
Cedar
*0rthophosphate

River
Floyd
Little Sioux
Chariton
Des Moines
Iowa
Cedar
Total
(Ibs/year)
720,207
1,851,632
879,916
5,621,007
1,723,975*
5,099,507


Total
(Ibs/year)
1,705,984
9,609,556
1,585,427
41,334,897
2,075,830
6,804,881
ANNUAL PHOSPHORUS LOAD
Point Sources
(Ibs/year)
29,807
129,088
48,203
586,015
103,445*
1,526,775

ANNUAL NITROGEN LOAD
Point Sources
(Ibs/year)
65,171
85,308
24,795
695,235
91,287
1,552,334
Nonpoint Sources
(Ibs/year)
690,400
1,722,544
831,713
5,034,992
1,620,530*
3,572,732


Nonpoint Sources
(Ibs/year)
1,640,813
9,522,248
1 ,560,632
40,639,662
1,984,543
.5,252,547
Percent of
Total from
Nonpoint Sources
95.9
93.0
94.5
89.6
94.0
70.1


Percent of
Total from
Nonpoint Sources
96.2
99.1
98.4
98.3
95.6
77.2

-------
example, the summer low flow period generally represents a steady-state
situation.  However, storm events, and the dynamic responses of a river to
them, must be considered a transient phenomenon.

     Dispersion effects can usually be neglected when pollutant input into a
river is continuous.  Under these conditions the plug flow assumption is
reasonable because the net dispersive transport is small.  However, when a
slug of pollutant is discharged instantaneously, dispersive transport is
important since high concentration gradients exist around the centroid of
the discharged pollutant.

     The fully-mixed assumption presupposes that concentration gradients
exist only in the direction of flow (longitudinal direction) and not in
either  the vertical or lateral direction.  The final major assumption is
that all decay rates can be approximated by first order kinetics.  This
means that the decay rate of a substance is proportional to the amount
present.  First order decay is traditionally used in CBOD computations, and
occasionally  in nitrogen oxidation.  The oxidation of inorganic nitrogen
actually  proceeds in stages from  ammonia-N to nitrite-N to nitrate-N.
However,  for  purposes of this report, the first order decay rate is
acceptable for NBOD and coliforms, as well as CBOD.  Before applying first
order decay to other substances,  however, care should be taken to determine
the validity  of the assumption.

     For  a few of the analyses which follow, several of  the aforementioned
assumptions are relaxed.  In the  discussion of mixing zones, Section 4.1.9,
partial mixing is discussed for wide rivers.  In the discussion on
toxicants, Section  4.9, the spill  analysis requires that an unsteady-state
situation be  analyzed where the effects of dispersion are included.
4.1.6   Data  Requirements

     Required  in  the  analysis of most water  quality  problems  are  one or more
types  of  data.  For example, stream  velocity (U),  volumetric  flow rate  (Q),
and  stream temperatures  (T) are commonly  needed.   Decay rates,  specific to
the  particular  problem at  hand, are  also  required.
                                   333

-------
     The U.S.  Environmental Protection Agency has published a document
(Zison et^ aj^., 1978) intended to provide water quality modelers with a
comprehensive source of information on rate constants and coefficients.  The
document provides extensive information on both biological and water quality
parameters commonly used in surface water modeling.  The contents of the
document will be useful to the users of this document, who are often faced
with limited information on process rates for the water bodies being
analyzed.

     Stream velocity is the most basic hydraulic parameter needed for the
analyses presented in this chapter.  Ideally, the appropriate stream
velocity is the travel time of neutrally buoyant particles over the reach
being investigated divided by the distance traveled.  Note that this concept
of velocity is different from the velocity determined by:
As defined by Equation IV-1, this concept of velocity exists only at the
point in the river where the cross-sectional area is A.  If the point of
measurement is not typical of the reach being investigated, then neither
will the velocity be typical.  Consequently, should the user predict stream
velocity based on cross-sectional area, a location typical of the river
reach being investigated should be chosen.

     An alternate method of predicting stream velocity, which does not
depend on either flowrate Q or cross-sectional area A is Manning's Equation.
A complete description of the use of this approach is given in many texts on
surface water hydraulics, one of the best being Chow (1959).

     According to Manning's Equation stream velocity under uniform flow
conditions is expressible as:

                            U=L49   sl/2   2/3                      (IV.2)
                                 n          n

where
     n   =  Manning's n
     S   =  slope, ft/ft
                                     334

-------
     R   =  hydraulic radius, ft
      H

Manning's n is the roughness of the stream bed, and can be predicted as
outlined in Chow (1959).  Barnes (1967) provides roughness data for 90
streams in the United States, and includes cross-sectional areas and
photographs of the streams investigated.  The slope can be estimated using
topographic maps to predict elevation changes between two locations, and
then overlying a string over the stream path to predict distance.  The
hydraulic radius (which is the ratio of the cross-sectional area to wetted
perimeter) can be estimated in terms of depth when the stream width is much
greater than the depth.  Specifically,

            /depth, if channel cross-section is rectangular
     V
            v/3 maximum depth, if channel cross-section is parabolic
4.1.7  Selecti on of Season

     It  is reasonable to expect that a particular water quality problem may
be more  severe at one time of the year than another.  Table IV-7 shows that
pollutant levels can depend on season (summer or winter) and flow rate (high
flow or  low flow).  Dissolved oxygen problems, for example, are clearly
associated with summer, low flow conditions.  Consequently, for any
particular pollution problem, users should strive to perform the analysis
under critical conditions.  Where planning is performed with consideration
of the aggravated situation, and where proper abatement action is taken, it
is likely that pollution concentrations will be below problem levels during
other times of the year.  If a problem in fact exists, then it is under
these conditions that it will be most pronounced.

     In  the following sections, hand calculation methods for each problem
area are described with illustrative examples.  Table IV-8 provides a
summary  of the material presented.
                                   335

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                                                            TABLE IV-7
co
CO
                                   MAJOR WATERWAYS:   SEASONAL AND FLOW ANALYSIS,  1968-72  (EPA, 1974)
Parameters

Suspended solids
Turbidity
Color
Ammonia
Nitrite
Nitrate(as N)
Nitrate(as N03)
Nitrite plus nitrate
Organic nitrogen
Total Kjeldahl nitrogen
Total phosphorus
Total phosphate
Dissolved phosphate
Dissolved solids(105°C)
Dissolved solids(180°C)
Chlorides
Sulfates
Al kal ini ty
ph
Dissolved oxygen
BOD5
COD (.025N)
Total coliforms(MFD)*
Total coliforms(MFI)*
Total coliforms(MPN)*
Fecal col iforms(MF)*
Fecal coliforms(MPN)*
Phenol s
Odor
Winter,
High Flow

9
13
11
14
3
12
8
2
3
3
10
8
6
4
3
4
5
6
15
0
11
6
4
8
4
6
4
5
4
Summer,
Low Flow
(number of
5
4
6
3
7
4
3
3
6
5
3
3
3
7
8
15
13
12
4
19
6
5
10
6
2
6
0
0
0
Winter,
Low Flow
reaches exceeding
0
1
3
7
5
8
6
2
0
0
5
5
4
6
6
10
5
10
6
0
8
3
2
2
3
3
1
1
0
Summer,
High Flow
reference
4
7
4
1
1
1
1
1
3
3
2
1
0
3
2
0
5
0
4
9
1
2
5
4
3
4
0
0
0
Dominant
Effect
levels)**
High flow
High flow
High flow
Cold weather
Low flow
Cold weather
Cold weather
Inconclusive
Warm weather
Warm weather
Cold weather
Cold weather
Cold weather
Low flow
Low flow
Low flow
Warm weather, low flow
Low flow
Cold weather, high flow
Warm weather
Cold weather
Cold weather
Warm weather
High flow, warm weather
Inconclusive
Inconclusive
Cold weather
Inconclusive
Inconclusive
                    ['•mbrane filter delayed,  membrane filter  immediate, most  probable number,  membrane filter.


                  '"'. ference  levels are available in Table IV-1.  Thirty  reaches were analyzed during each season.

-------
                                                                                       TABLE  IV-8
                                                       WATER  QUALITY  ANALYSES   FOR  RIVER  SCREENING METHODOLOGY
                                  Water Quality Constituent
    Computational Procedures
                                                                                                                                  Supporting Information Included
                                 Water  temperature
  equilibrium  temperature
  mixing  temperature
  temperature  profile for point sources
                                                                                                                                 shortwave solar radiation
                                                                                                                                 longwave solar radiation
                                                                                                                                 vapor  pressure
                                 Carbonaceous and nitrogenous
                                 biochemical oxygen demand
  BOD profiles  for point sources
  BOD profiles  with benthic sources added
  BOD profiles  with both benthic and nonpoint
  sources  added
graphs, tables, and equations
tor decay rates
                                 Dissolved oxygen
U)
CO
- CB8D-NBOD-DO  profile for point sources
- DO profiles with photosynthetic oxygen
  production and benthic uptake added
- critical  dissolved oxygen conditions
- waste assimilative capacity
reaeration  rates for shallow and
deep streams
saturation  dissolved oxygen levels
corrected  for  temperature, altitude,
salinity
photosynthetic  oxygen production and
benthic uptake  data
tabulated  solutions for critical
dissolved  oxygen levels
                                Nutrients
                                                                        growth limiting nutrient
                                                                        nutrient profiles for point sources
                                                                        nutrient profiles for nonpoint sources
                                                           nitrogen/phosphorus ratios  tor
                                                           growth  1 imitation
                                                           nonpoint source loading rates by
                                                           land  use type
                                Coliform organisms
  coliform  profiles for point sources
  coliform  profiles for nonpoint sources
                                                                                                                               - decay  rates
                                Sediment
                                                                        bed load
                                                                        suspended  load
                                                                        total  load
                                                           median  bed particle sues for
                                                           numerous  rivers
                                                           critical  shear stress
                                                           sediment  transport propensity  factor
                                                           approximate bed load/suspended load
                                                           relationship
                                Toxicants
  toxicant  profiles for point and
  nonpoint  sources
 • mass flux volatilized, advected, and
  transformed
 - spill  analysis of low and high density
  toxicants
 • time required  to desorb toxicant from
  bedded sediments
vnpor pressure,  solubility,octanol -
water portion coefficient for
priotity pollutants
Henry's I dw Constants

-------
4.1.8  River Segmentation

     Although the tools presented in this chapter are of a simplified nature
they can be used to analyze complex river systems (i.e. those which have a
number of different point and nonpoint sources of pollution, tributaries and
withdrawals).  Analysis of these systems is accomplished by dividing the
river into segments.  The basic tenet which must be followed is simply this:
Segments are created so that one of the analytical tools presented in this
chapter can be used to predict the pollutant concentration profile within
the segment.

     Analyses of river systems normally begin at a segment where the
boundary conditions are known, and proceed sequentially downstream.  Thus
the results found for one segment are used as the upstream boundary
condition for the next segment.  Based on the tools in this chapter, the
following rules should be followed when segmenting:

     1.  Point sources of pollutants enter the river just above the
         upstream boundary of a segment.  Tributaries are treated as
         point sources.

     2.  Nonpoint sources enter a river throughout the length of a
         segment.

     3.  Pollutant concentrations at the upstream end of segments are
         obtained by mixing the pollutant concentration in the river
         with the contribution of the point source at that location  (if
         one exists).  The location where mixing occurs is called a
         mixing zone.

     4.  Generally constant hydraulic variables  (e.g. depth and
         velocity) are used throughout a segment.  If there is a
         gradual change  in the hydraulic variables over distance, an
         average value can be used.  If there is  an abrupt change in
         the variable, such as a velocity change  caused by a
         significant deepening of the channel, then a new segment can
         be  created  at this boundary.
                                    338

-------
     5.  Decay rates, reaeration rates, and other rate coefficients
         remain constant within a segment.  If rate coefficients are
         known to change significantly from one location to another in
         a river, then different segments should be created.  This rule
         is consistent with rule (4), since rate coefficients are often
         functions of hydraulic variables.
                                EXAMPLE IV-1
     Figure IV-la shows a stretch of the James River, located in Virginia.
On the stretch of the river shown, there is a tributary (Falling Creek), a
sewage treatment plant (STP), and a nonpoint source of runoff
(agricultural).  Segment the river between locations A and B in order to
determine the profile of a pollutant which is discharged from each of the
three sources.

     First, it should be noted that often there is more than one way to
segment the river to successfully solve the problem.  The most obvious
method will be illustrated here.  Figure IV-lb shows the proposed solution.
There are two mixing zones - the first around the treatment plant and the
second around the tributary which is treated as a point source.  The first
segment is located from below the first mixing zone to above the second
mixing zone, and has a nonpoint source discharging throughout the length of
the segment, consistent with rule (2).  The second segment is located below
the second mixing zone and continues downstream to location B, which is the
end of the nonpoint source.  If Falling Creek had not been present, a single
segment and a single mixing zone would have been sufficient to analyze the
problem.
                            END OF EXAMPLE IV-1
     A second, more comprehensive example will illustrate a number of points
about segmentation not covered in the previous example.  One of these points
is that the segmentation scheme used can vary depending on the pollutant
being analyzed.
                                  339

-------
                                          JAMES RIVER
                                                  > B
                   AGRICULTURAL RUNOFF
           (a) River Segment Being Analyzed
        (b) Proposed Segmentation  Scheme

FIGURE IV-1    ILLUSTRATION  OF RIVER SEGMENTATION
                PROCEDURE ON  THE JAMES RIVER,
                           340

-------
                                EXAMPLE IV-2
     Segment the river shown in Figure IV-2 beginning at location A and
continuing to location B in order to determine the instream BOD
distribution.  How would the segmentation differ when predicting the
dissolved oxygen profile?

     Both point and nonpoint sources discharge to the river in Figure IV-2.
Several flows are diverted, and the river width changes over parts of the
reach being investigated.  Each of the rules stated earlier will be utilized
to segment the river system.  Figure IV-3 shows one solution to the problem.
Depending on the distances between the various sources of pollutants, which
are not given in the problem, it might be possible to combine some of the
segments.  The reservoir is assumed to be analyzed using the methods in
Chapter 5, and so is not segmented.

     Mixing zones are included around the four point sources:  the food
processing plant, the tributary, the sewage treatment plant, and the pulp
mill.  In segments 9 and 11 there appear to be a number of point sources and
diversions.  Strictly speaking, segments 9 and 11 do not follow the rules
presented earlier, which require mixing zones around each point source.
However, the point sources and sinks within segments 9 and 11 are assumed to
represent equivalent nonpoint sources, which act over the length of each
segment.  This approach can obviously simplify the analysis of complex river
systems by decreasing the number of segments analyzed.  However, the
analysis is more approximate because the nonpoint source is assumed to be
uniformly distributed throughout the segment.  Example IV-5 presented later
shows a specific application of the concept of an equivalent nonpoint
source.

     In segment 2 the presence of the small dam is assumed not to influence
the BOD profile, so that its presence does not require a mixing zone.
However if the dissolved oxygen profile were being calculated, segment 2
would be divided into two segments, with a mixing zone around the dam.  This
division is required because the dissolved oxygen concentration can rapidly
                                   341

-------
          J
            SMALL DAM
                          n
                     AGRICULTURE
                                                            (CONT.)
      VJIOENS)
                               ATTACHED
                                ALGAE
                                             (CON'T)
       RESERVOIR
                        n
                       DIVERTED FLOWS
FIGURE IV-2
HYPOTHETICAL  RIVER  HAVING  A VARIETY OF
POLLUTANT SOURCES AND SINKS,
              342

-------
                             SMALL DAM
                                   i
                                                           I
1
^G
E

©
1 | •
*'*!* /^\
1 ©
MIXING
7nwct;
\t
H
\
1
' i
I J
' J
k J
AGRICULTURE
1 — >- 	 t-r
t J | (CONT.)
i'®"!' r

/T\ Z°NE
                                                            (CON'T.)
                                      DIVERTED FLOWS
FIGURE  IV-3   RIVER  SEGMENTATION FOR BOD  DISTRIBUTION,
                              343

-------
change (almost instantaneously) as the water flows over the dam.  The
dissolved oxygen concentration just below the dam should be used as the
upstream boundary conditions for the next segment.  The specific information
required to accomplish this is discussed later in Section 4.3.

     A second difference in segmenting for dissolved oxygen occurs in
Segment 8.  The presence of the attached algae is assumed not to influence
the BOD profile, but the algae are internal sources of oxygen.  Thus segment
8 would be subdivided at the upstream location of the attached algal growth.
                            END OF EXAMPLE IV-2
4.1.9  Mixing Zones

     A mixing zone, as used in this document, is nothing more than a short
reach of a river where a point source and river water mix.  It is often
assumed, for both simple and more complex approaches (e.g. QUAL-II computer
model), that mixing is instantaneous and complete across the entire width of
the channel.  With several exceptions, such an approach is used in this
document.

     Assuming complete mixing, the concentration of a pollutant in a river
after mixing is:
                                 C Q  + C Q
                             r    u u    wxw
                                   Q+Q                            (IV-3a)
                                                                      (iv-3b)
                                   Qw + Qu
where
     C   =  concentration of pollutant in river following mixing, mg/1
     C,, =  concentration in point source, mg/1
      w
     C   =  concentration in river above point source, mg/1
     Q    =   discharge  rate of  point source, ft  /sec
      W
     Qu  =   flow  rate  of  river above  point of discharge,  ft3/sec
     W    =   pollutant  mass emission rate, Ibs/day
                                   344

-------
The concentration C is the pollutant level in the mixing zones shown in the
earlier Figures IV-1 and IV-3.  These concentrations become the upstream
boundary conditions for the adjacent downstream segment.

     Although it is convenient to assume that complete mixing occurs, this
assumption may be inaccurate for wide rivers, depending on the
characteristics of the point source outfall and diffuser.  Figure IV-4
illustrates such a case.  The river is wide enough so that the wastewater is
initially mixed with only a fraction of the total river flow.  As the
pollutant-riverwater mixture is transported downstream mixing continues
until the pollutant is completely mixed across the channel.

     The initial pollutant concentration at the point of discharge is
                                 Y
                          c   =   W  Qu  Cu * Qw Cw                      (IV-4)
                                    QW + tf Qu
where
     V
     jj-  =  fractional distance across river where initial mixing occurs.

and all other variables have been previously defined.

     The significance of incomplete initial mixing is that pollutant
concentrations can be initially much higher than if complete mixing occurs.
For example, if the upstream contribution of the pollutant is negligible
(C = 0) and if the fraction of river flow which initially mixes is far
                                  Y
greater than the wastewater flow (~ Q »Q ), then

                                r  =  — r                             fIV-5)
                                L     Y Ccm                           U   '

where

     C    =  concentration of pollutant if there is incomplete initial
             mixing

     Ccm  =  concentration of pollutant if there is complete initial
             mixing
                                   345

-------
  I I I I I I I I I I I I I I II I I I I I I I I I 11 I I I I 11 I I I I I I I I  I I I I I
CONTAMINATED '.
                       UNCONTAMINATED
             •;.-CONTAMINATED .

                                               T
                                                     W
                                                             U
  I I I I II I I l\l I I I I I I I I I I I I I I I I I I I I I I
LJ I I 1 I I I I II III
FIGURE  IV-4    POLLUTANT DISCHARGE WHERE INITIAL MIXING
               OCCURS A FRACTIONAL DISTANCE ACROSS THE
               RIVER,
                           346

-------
If Y/W = 0.1,  then the pollutant concentration following  incomplete mixing
is 10 times higher than if complete mixing were to occur.

     The distance L  to complete mixing (see Figure IV-4)  can be estimated
(as an upper limit) by the following expression:

                              L   =  0.4 W2 U                         (IV_6)
where
     L   =  distance below point source where complete mixing occurs
     W   =  width of river
     U   =  river velocity
     e   =  lateral diffusion coefficient

Values of the lateral diffusion coefficient can be estimated from the data
given in Table IV-9.  Also, the following predictive formula can be used:

                     ,0.1-0.2, for a straight rectangular flume
             4-       1
               f   =  <0.25, for irrigation channels                   (IV-7)
                     ^0.4-0.8, many natural channels
where
     D   =  mean depth of flow
     u*  =  friction velocity  =   VgDS
     S   =  slope of channel

The actual distance L  is probably less than that calculated from Equation
IV-6 because of secondary mixing, river curvature, and initial momentum of
the discharge.  It is also sensitive to river width.
4.1.10  Hater  and Pollutant Balances

     Many  river  systems  are hydrologically complex.  Flow patterns are
influenced by  tributaries, nonpoint sources of runoff, flow withdrawals, as
well as point  sources  of  pollution.   If the planner  intends to perform water
quality analyses on a  basin wide scale, it is probably prudent that a water
                                   347

-------
                                                        TABLE IV-9
                                     EXPERIMENTAL MEASUREMENTS OF TRANSVERSE MIXING IN
                                       OPEN CHANNELS WITH CURVES AND IRREGULAR SIDES
co
-P>
CO
Channel
Missouri River near
Blair, Nebraska
Laboratory







Laboratory model
of the Ussel River
IJssel River

Mackenzie River
from Fort Simpson
to Norman Wells

Missouri River
downstream of
Cooper Nuclear
station, Nebraska
Potomac River;
29 km reach below
the Dickerson
Power Plant
Channel
geometry
Meandering river

Smooth sides and
bottom; 0.15 m
long groins on
both sides
Smooth sides and
bottom; 0.5 m
long groins on
both sides
Groins on sides
and gentle curvature
Groins on sides
and gentle curvature
Generally straight
alignment or slight
curvature; numerous
island and sand bars
Reach includes one
90° and one 180°
bend

Gently meandering
river with up to
60° bends

Channel
width,
W
(m)
200

2.2



2.2



1.22

69.5

1240



210-270



350



Mean depth
of flow,
d
(m)
2.7

0.097



0.097



0.9

4.0

6.7



4



0.73-1.74



Mean
velocity,
(m/s)
1.75

0.11



0.11



0.13

0.96

1.77



5.4



0.29-0.58



Shear
velocity,
u*
(m/s)
0.074

-



-



0.0078

0.075

0.152



0.08



0.033-0.051



Transverse
mixing
coefficient
(m2/sec)
0.12

-



-



.

-

0.67



1.1







Et
Du*
0.6

0.36-0.49



0.3-0.4



0.45-0.77

0.51

3.4



3.4



0.52-0.65



                  from:  Fischer, H.B., E.J. List, R.C.Y. Kob, J. Imberger, and N.H. Brooks, 1979.
                         Mixing in Inland and oastal Waters.  Adademic Press, New York.

-------
budget be first completed.  A water budget is a statement that

          jjf  = £  Inflows  - £ Outflows  =  0, for steady-state    (IV-8)
where
     S  =  storage in the river channel

For the steady-state situations, which are examined here, the water budget
simply states that inflows to the system equal outflows from the system.  A
water budget thus provides a method of determining whether the major flow
contributions have been accurately assessed or not.  If a large imbalance in
the water budget exists, accurate evaluation of the major sources of
pollutant might be difficult to achieve.  An accurate water balance helps to
minimize the possibility of inaccurate assessment of pollutant concentra-
tion.  It does not eliminate the possibility.

Once a water balance has been completed, then a pollutant balance of a
conservative pollutant can be developed based on the following relationship:
in
                      Flux  = £  Flux
                              out
                         ,at steady-state
(IV-9)
where the fluxes are the rates of entry and loss of the pollutant into and
out of the system, respectively.  One of the following two expressions can
be used to predict the mass loading rates:
                               M  =  5.38 C Q
                                                   (IV-10)
where
     M  =  mass loading rate, Ibs/day
     C  =  concentration, mg/1
     Q  =  flow rate, ft3/sec
and
                               M  =  86.4 C Q
                                                   (IV-11)
where
     M  =  mass  loading rate, kgs/day
     Q  =  flow  rate, m3/sec
                                   349

-------
When nutrient and water balances are developed, the following considerations
should be kept in mind:

     1.  In most instances it is probably not possible to develop water
         or nutrient balances where inflows and outflows balance to
         within less than 10 percent of each other.

     2.  The system's upstream boundary must be included in the balance
         as a source and the downstream boundary as a loss.

     3.  All sources and losses should be mutually exclusive of each
         other.

     4.  Choose system boundaries to coincide with locations of gaging
         stations when possible.

     5.  Try to use comparable periods of record of data.  This will
         help to minimize the impacts of trends which could be present
         in one record but not in another.

     6.  It is typically easier to develop water and mass balances on
         an annual basis, although balances can be developed for each
         season of the year.  However, if the system is not at steady
         state, inflows and outflows should not balance.

     Table  IV-10 shows a suggested method of tabulating the results of water
and pollutant balances.  Total nitrogen (TN) and total phosphorus (TP) are
the pollutants.  All flow rates and loading rates are tabulated
individually.  Once total loading rates have been tabulated, the percent
contribution from each source can be determined.  Percent contributions help
to determine the relative importances of each source as a contributor to
pollution,  and can provide a method to prioritize pollution abatement
efforts.
                                     350

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                         TABLE IV-10



SUGGESTED CONFIGURATION FOR WATER AND NUTRIENT  BALANCE  TABLE
SOURCES
- UPSTREAM
- TRIBUTARIES
- IRRIGATION
RETURNS
- MUNICIPAL
- INDUSTRIAL
TOTAL
LOSSES
- DOWNSTREAM
- DIVERSIONS
i
TOTAL
SOURCES-LOSSES nnn
X JLUU
LOSSES
FLOW RATE












LOADING RATE
TN %
























TP %
























                              351

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                                EXAMPLE IV-3
Figure IV-5 shows a hypothetical  river which has three tributaries,  a
nonpoint source of runoff, and two diversions.   Develop a water balance for
this system.  The known flow rates are
          Identification Number              Flow rate (cfs)

                   1                             2000
                   2                             4000
                   3                             1200
                   4                              200
                   5                              800
                   6                             1000
                   7                             2000
                   8                             6000

The flowrates at locations 1,2,3, and 5 are assumed to comprise the inflow
rates to the system.  The total inflows are:
          Identification Number                  Inflows
                   1                             2000 cfs
                   2                             4000 cfs
                   3                             1200 cfs
                   5                              800 cfs
                 Total                           8000 cfs
The inflow from gage 4 is not needed because gage 5 is located further
downstream on the same tributary.  The outflows consist of diversions 6 and
7 and the downstream outflow past gage 8:
                                   352

-------
FIGURE IV-5   ILLUSTRATION OF WATER BALANCE
                         353

-------
          Identification Number                  Outflows
                   6                             1000 cfs
                   7                             2000 cfs
                   8                             6000 cfs
                                                 9000 cfs
     The inflows and outflows differ by 1000 cfs.  There are several reasons
for the imbalance.  One, the flow rate past each gage is not measured
perfectly, but differs by some degree from the actual flow rate.  Two, the
gage at location 5 does not catch all of the nonpoint source runoff, so
there is an additional inflow to the system which has not be quantified.
Three, depending on the size of the reservoir, direct precipitation and
-evaporation might be significant.
                            END OF EXAMPLE IV-3
     The following example  illustrates both a water and nutrient balance,
 and  is based on work performed by Tetra Tech on the Snake River  in  Idaho
 (Mills and  Desvoigne, 1978).
                                EXAMPLE  IV-4
      Develop  annual water  and  phosphorus  balances for water year  1976  for
 the  Snake  River  from  Heise,  Idaho,  to  below American Falls Reservoir,  a
 distance of 150  miles.   A  sketch  is shown in  Figure  IV-6.  Estimate  the
 phosphorus retention  coefficient  for American Falls  Reservoir.  The
 retention  coefficient is defined  as:

                      R   ^  Flux Input - Flux Output
                       p          Flux Input

 The  required  data are shown  below.

      •   Surface area of American Falls  Reservoir  =  56,600  acres
      •   Evaporation  rate  in this part of United States  =  33
          inches/year
                                     354

-------
 Snake  River
 near Heise
      RM861
    Henry's Fork
     near Rexburg
                               Blackfoot River
                                near Blackfoot
                               (include  bypass canal
                                         Portneuf  River at  Pocatello
                                               American Falls  Reservoir
                                                  Snake River  at Neeley
                                                            RM713
FIGURE  IV-6
SKETCH  OF SNAKE  RIVER FROM HEISE  TO NEELEY,
IDAHO,
                               355

-------
     •   Precipitation = 11 inches/year
     •   Ground water inflow into Snake River:  500 cfs
     •   Ground water inflow into American Falls Reservoir:   2,100 cfs.

The total phosphorus concentrations were generated during the study of Mills
and Desvoigne (1978) and are provided here:

              Source                             mg/1
              In rainwater                       0.03
              Snake River near Heise             0.05
              Henrys Fork                        0.11
              Blackfoot River                    0.26
              Portneuf River                     0.68
              Groundwater inflow                 0.23
              Snake River near Neeley            0.08

     The surface inflow rates are gaged by the U.S.  Geological Survey and
are reported in the U.S.  Geological Survey Water Data Report for Idaho
(1976).  An example of how the information is tabulated  in these reports is
shown  in Figure IV-7.  From an entry in the Table, the mean flow rate for
water  year 1976 is 8549 cfs at USGS 30307500, near Heise.  Rather than
showing  the remaining tabulations from the USGS report the flow rates from
water  year 1976 will simply be tabulated, as  contained in the report.

                       Source                        Flow rate
              Blackfoot River                          453 cfs
              Henrys Fork                            3,235 cfs
              Portneuf River                           412 cfs
              USGS  13059500 (diversion)          2,333,700 ac-ft/yr
              USGS  13069000 (diversion)            800,900 ac-ft/yr

Based  on this  information the water and total phosphorus balances are
calculated and  shown  in Table IV-11.   The  flow  rates are all converted to
units  of cfs.   This  requires converting the precipitation, evaporation,  and
diversions to  these  units.  A precipitation rate of  11 inches  per year is
equivalent to  71 cfs:
                                   356

-------
LOCATION. --Lat 43°36'45", long 111°39'33", in SE
-------
                        TABLE  IV-11
SOLUTION TO SNAKE RIVER WATER AND PHOSPHORUS BALANCE PROBLEM
Sources
Snake River at Heise
Blackfoot River
Henrys Fork
Portneuf River
Ground water inflow into
Snake River
Ground water inflow into
American Falls Reservoir
Precipitation on American
Falls Reservoir
Losses
USGS 13059500
USGS 13069000
Snake River at Neeley
Evaporation
2-f Losses
Flow
Rate (cfs)
8,549
453
3,235
412
500
2,100
71
15,320
Flow
Rate (cfs)
3,214.
1,103
11,360.
215.
15,892.
TP Loading (Ibs/day)
2,300.
1,915.
634.
1,510.
619.
2,600.
11.
9,589.
TP Loading (Ibs/dav)
865
415
4,890
_
6,170
r r. /Losses-Sources\ inn _ ,al
                     Losses
                             358

-------
             11 f 12 x 56600 x 43560 f 366 :- 24 f 3600 - 71 cfs

The diverted flow in ac-ft/yr is converted to cfs as shown:

          USGS 13059500:  2333700 x 43560 - 366 * 24 T 3600 = 3214

The percent difference between inflow rates and outflow rates is 4 percent.

     Based on these flow rates, and the concentrations of total phosphorus
presented earlier, the sources and losses of total phosphorus can be
tabulated.  For example, the mass flux of total phosphorus flowing past
Heise can be calculated using Equation IV-10:

                 M  =  5.38 x 8549 x 0.05  =  2300 Ibs/day

Continuing in this manner, the sources and losses are as tabulated in Table
IV-11.  The large imbalance is caused by retention at American Falls
Reservoir.  The phosphorus loading to the reservoir is:

                     9589 - 865 - 415  =  8309 Ibs/day

Since the phosphorus leaving the reservoir is 4890 Ibs/day, the retention
coefficient is:

                                          890
                                    8309
American Falls Reservoir retains a significant quantity of the phosphorus
which enters the reservoir and consequently tends to keep phosphorus levels
in the Snake River below the dam depressed compared with what they would
otherwise be.
                            END OF EXAMPLE IV-4-
                                    359

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4.1.11  Hand Held Calculator Programs

     It has become apparent that, after applying the river screening
techniques contained in the original manual (Zison e_t a]_., 1977) to real
systems, a substantial savings of both time and effort could be realized by
programming the major computational sequences.  To this end, these
algorithms have been programmed on the Texas  Instrument TI-59 calculator and
are available upon request in a document prepared by Tetra Tech
(Mills erb _al_., 1979)*.  To date the algorithms contained in Mills eit  a 1.
(1979) predict:

     •   equilibrium temperature
     •   longitudinal instream temperature distribution
     0   mixing temperatures
     •   BOD profiles for point and nonpoint  sources
     •   reaeration rates
     •   dissolved oxygen profiles
     •   waste assimilative capacity and critical dissolved oxygen
         levels
     •   coliform profiles for point and nonpoint sources
     •   bed material sediment transport

     For each program contained in the document the following information  is
provided for the user:

     t   a detailed set of user instructions,
     0   a program listing, and
     0   a sample input/output sequence.

An example set of users instruction  is shown  in Figure  IV-8.  The first 6
steps are for data entry  and the  seventh is for calculation of  the  required
information.
* Attention:  W.B. Mills
  Tetra Tech, Inc.
  3746 Mt. Diablo Blvd., Suite 300
  Lafayette, California 94549
                                    360

-------
  IICLE	

  PI-.OGHAf.1MER	DATE

  Partitioning (Op 17; JL6_Q.J> .Oj Library Module	
                                     FAGe_J	OF J	
                     .Printer .OptlOnaLClrcsI
                                 PROGRAM DESCRIPTION
    Program:  Critical  Dissolved Oxygen Calculations
    This program calculates the critical  dissolved oxygen deficit  downstream  from a
    point source of pollution.  It also calculates the travel time to the critical
    deficit.
    Note that if the travel time turns out to be negative, then the critical  deficit
    occurs at the point where pollution enters the stream.
  SSTEPI
                                  USER INSTRUCTIONS
                     PROCEDURE
  I 1  | Enter program -  see listing following
       these instructions
       Enter reaeration rate at 20°C, k
       (I/day)
'a 20
       Enter deoxygenation rate at 20°C,  k
       (I/day)
   'd20
       Enter BOD concentration  in stream just
       below source of pollution, L  (mg/S.)
       Enter dissolved oxygen  deficit in  stream
       just below source of pollution,  D   (mg/1)

       Enter stream temperature, T (°C)
   7  i Calculate and display:
        - reaeration rate at stream temperature,
          ka (I/day)

        - deoxygenation rate at stream
          temperature,  k. (I/day)

        - travel time to critical deficit,
          tc (days)
        - critical deficit, D  (mg/S.)
program j D

ka20
kd20
Lo
Do
T
I






R/S
R/S
R/S
R/S
R/S
R/S
R/S
R/S
R/S

\










1







1
1



FIGURE   IV-8   EXAMPLE  SET  OF  USER'S  INSTRUCTIONS
                     FOR  HAND HELD  CALCULATOR  PROGRAMS
                                   361

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4.2  CARBONACEOUS AND NITROGENOUS OXYGEN DEMAND

4.2.1  Introduction

     Many wastes discharged into waterways contain biologically oxidizable
materials that exert an oxygen demand on waterway resources.  This
biochemical oxygen demand (BOD) can be subdivided into carbonaceous  (CBOD)
and nitrogenous (NBOD) components.  Table IV-12 illustrates typical
concentrations of NBOD and CBOD in untreated municipal waste.

     CBOD represents the amount of oxygen required by bacteria to stabilize
organic matter under aerobic conditions.  The reaction can be approximated
by

          C.H.OtNc +  n +  -   -  c 0, -* nCO, +  ? -   c\ H,O + cNH,
This reaction assumes that the available organic matter is completely
oxidized.  Bacteria, however, might not be able to completely oxidize  all of
the available organic matter.  Equation IV-13 does illustrate that oxidation
of the nitrogen is not included as part of CBOD.  The reduced nitrogen  is
oxidized to nitrate in a two step process as follows:

                   2NH, + 30, ^l!^ 2NOl- + 2H+ +  2H,0             ( IV-13)
                               b&eleru

                                    nitral^-forminc                         / T., •% n \
                   2NOz~ + O, + 2H+ -- + 2NOr + 2H+             ( IV-14)
                                      bacteria
Based on Equations IV-13 and IV-14 the NBOD is

           NBOD = 4.571 lOrg-NJ  +  [NH^  -  N| I  + 1.14 |NO~ - N|     (IV-15)

Typically the nitrite concentration is negligible so that

                            NBOD  =  4.57 (TON)                       (IV-16)

where TON represents total oxidizable nitrogen, the sum of organic and
ammonia nitrogen.  A typical value of TON from Table IV-12 is 20+28   =  48
mg-N/1, which corresponds to an NBOD of 220 mg/1.
                                    362

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                             TABLE  IV-12


                   MUNICIPAL WASTE CHARACTERISTICS
                   BEFORE TREATMENT (THOMANN, 1972)
Variable
Average Daily Flow
Solids
Total
Total Volatile
Total Dissolved
Total Suspended
Volatile Suspended
Settleable
BOD
Carbonaceous (5 day)
Carbonaceous (ultimate)
Nitrogenous*
Ni trogen
Total
Organic
Ammonia
Nitrite + Nitrate
Phosphate
Total
Ortho
Poly
Col i forms
Total mi
Fecal mi
Unit
gal/cap/day

mg/1
mg/1
mg/1
mg/1
mg/1
mg/1

mg/1
mg/1
mg/1

mg/1 N
mg/1 N
mg/1 N
mg/1 N

mg/1 PO^
mg/1 PO^
mg/1 PO

11 ion org./lOO ml
11 ion org./lOO ml
Approx.
Averaqe
125

800
400
500
300
130
150

180
220
220

50
20
28
2

20
10
10

30
4
Normal
Range
100-200

450-1200
250-800
300-800
100-400
80-200
-

100-450
120-580
-

15-100
5-35
10-60
0-6

10-50
5-25
5-25

2-50
0.3-17
*Ultimate, Nitrogenous oxygen demand, exclusive of CBOD.
                                  363

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     Typically in the bottle determination  of  CBOD  and  NBOD,  the
carbonaceous demand precedes the nitrogenous demand  by  5  to  10  days,  as
shown in Figure IV-9.  This had led workers to believe  that  nitrification
can be ignored in river environments below  a source  of  pollution  up to  a
distance corresponding to a travel  time of  five to  ten  days.  Such  an
assumption might be invalid for several reasons.  Given that  there  are
numerous sources of pollution along many rivers a viable  population of
nitrifying bacteria may already be  present  within the water  column.   Second,
nitrifers can grow attached to the  bottom substrate.  Consequently,
significant numbers can exist just  below the discharge  location and
nitrification can proceed immediately.   Nitrification by  attached bacteria
is more likely to be of significance in relatively  shallow,  wide  rivers,
which have stable bottom substrate  (Mills,  1976).
                                           urve for combined demand
                                          (Carbonaceous plus nitrification)
                                  Curve for carbonaceous demand at 20°C
     FIGURE  IV-9    THE  BOD  CURVE,   (A)  CURVE FOR OXIDATION OF
                      CARBONACEOUS  MATTER,    (B) CURVE  SHOWING
                      INFLUENCE  OF  NITRIFICATION,
     CBOD is a commonly measured characteristic of waste water.   The CBOD
used in the formulations presented below is the ultimate CBOD.   Often CBOD
is expressed as CBOD5, the oxygen utilized in a 5 day test.   The
relationship between ultimate (CBODL) and 5-day CBOD can be  approximated by:
                               CBODL -
CBOD
OT5ET
                                  364

-------
This relationship assumes a decay rate of 0.23/day,  and may be different for
effluents from advanced wastewater treatment plants.

     The mass balance equation used in the CBOD analysis is exactly
analogous to the NBOD equation.  The first order decay rate assumption for
NBOD stabilization is necessary to maintain this analogy, and is sufficient
for hand calculations.

     Nitrification (the process by which ammonia is oxidized to nitrite, and
nitrite to nitrate) is pH dependent with an optimum range of 8.0 to 8.5
(Wild, 1971).  If the pH of the river is below 7.0, nitrification is not
likely to be important.
4.2.2  BOD Decay Rate

     The decay rate for CBOD will be denoted by kL and for NBOD by k^.
Typical values of both kL and kN lie between 0.1 and 0.6/day, with 0.3/day
being typical,  k. values can, however, exceed the range given here.  Values
of  1 to 3/day have been computed for shallow streams (Thomann, 1972).  A
figure to be presented shortly will show how k, depends on depth.  The
following discussion will be directed  toward kL, but in general will also
apply to kN.

     The disappearance of BOD from  a river  is  a reflection of both settling
and biochemical oxidation,  as shown in Figure  IV-10.  Biochemical oxidation
can consist of  instream oxidation (kjL) as  well as absorption by attached
organisms  (k4L).  The total oxidation  rate  then, is k , where

                                 k,  = kx + k4
                                  d

The total  loss  rate k   is


                                 "L-V1"

where  k3  reflects  settling  losses.
                                   365

-------
        FLOW
                     Sedimentation
                                      Ax\
          K4L
           ww
                                          <
r
KiL- Instream
     deoxygenation
           L- ULTIMATE B.O.D.
Absorption by
attached organisms
       FIGURE  IV-10
MECHANISMS OF  BOD  REMOVAL
FROM RIVERS
Settling of BOD is generally more prevalent just below a sewage discharge
where the discharged material may contain a large suspended  fraction.   As
this material is transported downstream the settling component becomes less
important and the reaction rate k  approaches the oxidation  rate k ,.   In
this chapter, the settling component will not be explicitly  considered.
Neglecting settling will tend to cause estimated instream BOD levels  to be
somewhat higher than they actually might be along certain portions of a
river.  It should be noted that if instream BOD data are used to determine
k  (one such method will be explained in Figure IV-12) then  the effect of
settling is automatically included in k .
Figure IV-11 illustrates the dependence of k.  on river depth.  The highest
deoxygenation rates occur in shallow streams with stable, rocky beds,
reflecting the significance of attached biological organisms.  Appendix C
contains observed and predicted values of k.  for various natural streams.

The decay coefficients k  and kN are both temperature dependent and this
dependence can be estimated by:
                               = k20 1.047
                                          (T-20)
                                           (IV-17)
                                   366

-------
   10.0
   1.0
o
o
o
CVJ
O

   0.05
                                            Stable, Rocky Bed
                                            Moderate Treatment
                                            Some Ammonia
MEAN
                                             Unstable, Sandy Channel
                                             Highly Treated Effluent
                                             with Nitrification
                                           10.0
                       100.0
       DEPTH (FT.)
 FIGURE IV-11     DEOXYGENATION COEFFICIENT AS A  FUNCTION OF
                   DEPTH,  (AFTER HYDROSCIENCE, 1971)
                                   367

-------
where

     kon  =  k,  at 20°C
      20
     k   =  k  at T°C
     T   =  water temperature,  C
Numerous methods for computing k  from observed data are available
(Nemerow, 1974).  One method entails the use of a semi-log plot.  The
stretch of river containing the data to be plotted must have a constant
stream area and flow rate, and the BOD loading must be from a point source
located at a position that will be called x = 0.  Plotting the log of BOD
concentration versus distance generally produces a straight line with slope
of -k /U.  An example is shown in Figure IV-12.  Either CBOD5 or CBOD.  can
be plotted as the ordinate.  The slope should be converted from base 10
logarithms as given in the semi-log plot to base e logarithms as needed in
the formulations used in this chapter.  The conversion is made by
multiplying the value for log base 10 by 2.303.

Wright and McDonnell (1979) have more recently developed an expression for
instream BOD decay rate based on the flow rate of the river.  The expression
is:

                                   i  klab  if Q>800 cfs             (IV-18a)
                      kj  '^YJ  =
                                     10'3  if Q<800 cfs             (IV-18b)
This expression is particularly attractive because the only hydraulic
variable required is flow rate.  Other predictive techniques and rate data
from rivers around the country are contained in Zison et al.  (1978).
                                  368

-------
   10.0
                -Slope x U
                    0.017* ,4Miles
                    Miles' *  Day
                0.16/Day
o
      | DISTANCE (MILES)

      INPUT
FIGURE  IV-12     EXAMPLE  OF  COMPUTATION OF KJ_ FROM STREAM
                 DATA  (FROM  HYDROSCIENCE,  1971)
                           369

-------
 4.2.3   Mass  Balance of  BOD
      The  general mass-balance equation for BOD in rivers is

                          If  (QL) - kL L + Lr 
-------
     For any particular reach of a river under investigation the  stream
cross-sectional  area can  be  expressed  by:

                        /A, -A  \
             A  =  AQ +           x  =  AQ + AAx                     (iv-21)
where

                      A       XL

     A   =  stream cross-sectional area at upstream end of the reach
     Af  =  stream cross-sectional area at downstrean end of reach
     x   =  distance downstream from beginning of reach
     x.   =  length of reach

The cross-sectional area  need not  be measured directly, but can be
computed from:
     The cross-sectional area change  can  reflect a change in
stream velocity, perhaps due to a bed slope increase or decrease.
The length of the reach under investigation, x,  , is measured in river
miles along the river's centerline.   If use of  a constant stream area
is assumed,  then Aft = 0 and A = AQ throughout the reach.

4.2.4  Typical  Solutions

     Ca_s_e_]_:  The only source  of  CBOD occurs  as a  point  source  at
     x = 0.  The CBOD  distribution  is then  expressed  by:
                                                                      (IV-22)
 where         .
      i    -   A
       L   "    Uo
                                  371

-------
     U   =  stream velocity at x =  0
      o
     L   =  ultimate BOD at the upstream end  of the reach
      o
     L   =  ultimate BOD at a distance x downstream
The other terms have previously beer, defined.   The initial  CBOD,  L ,
must reflect both CBOD upstream of the reach as well  as that contributed
by the point source in question.   It is given by:
                         L.O  + W/5.38
                  L   =                                             (IV-23)
where
     W  =  mass rate of discharge of CBOD, Ib/day
     Q  =  upstream river flow, cfs
     Qw =  waste flow rate, cfs
     L  =  upstream CBOD concentration, mg/1

     Ca_se_2:   For a point source of CBOD at x =  0 and a  distributed
     mass influx of CBOD (with no associated flow) entering the river
     throughout the reach, the solution is
                                                                    (IV-24)
 where
      L  , = mass rate of CBOD entering the reach per unit
       rd
            volume of river water, mg/1/day


     Case 3:   A  distributed  flow  enters the river carrying CBOD
     and  a point source  of  CBOD exists  at  x -  0.  The  flow rate
     Q at a distance  x is:

                           Qf - Qo
                  Q = Q   +  —	  x = Q  +  Anx
                  M   ^o     x,           o    Q
                                  372

-------
where
      The  BOD  distribution  is  given  by  (the  river  cross-sectional  area
      is assumed  constant  throughout the  reach):

 where        k,  A  + An
     r    -    L   0    U
     El   •   —^-

     L    =   concentration of CBOD  entering  the  river in  the  distributed
             flow, mg/1

     Case 3 can also be usea TO  esTaolish the effect a  purely
     diluting inflow (i.e.  L  =0)  would  have on the CBOD distribution.

      Case  4:   For  a point  source at x = 0, a distributed source
      with  associated  inflow, and a mass flux with no associated
      flow  (constant river  cross-sectional area), the solution is

 where
                 k  A  +
            E  = _^-- --- .   , as in Case 3.
              I       AQ

 4.2.5  Othe r__S i_mp1 i fyijig Procedures

      The formulations represented by Equations IV- 22 through IV-26 offer
 a range of options for examining BOD distribution  in rivers.
 However, there are additional methods of estimating instream concen-
 trations and determining whether or not significant BOD levels  exist.
                                    373

-------
 Perhaps  the simplest  method  is  assuming  that  BOD  does  not  decay.  An
 upper limit of the instream  concentration  at  any  point can  then be
 determined by incorporating  all  known  sources,  and  using the methods
 presented in Section  4.7.   If the  computed  instream concentrations are
 below a  threshold  pollution  level,  then  there is  no need to apply
 Equations IV-22 through IV-26 because  the  inclusion of a decay  rate will
 only  lower the concentrations.

       It may  also  be feasible,  as a first estimate,  to combine  the CBOD
 and NBOD equations into one, and use that equation  to estimate  the
 distribution of the total oxygen-demanding material.  To  do this, all
 source terms must include both  CBOD and NBOD.  One  decay coeffi-
 cient is used for both CBOD and NBOD decay.  The larger decay  coeffi-
 cient of the two should be used since  that will produce the larger
 oxygen  deficit.
      In deciding which of Equations IV-22 through IV-26 to use for any
 analysis, the purpose of the analysis as well  as data availability
 should be considered.  If the main purpose is  to estimate  differences
 in stream concentrations caused by various levels of abatement at a
 sewage treatment plant, the diffuse sources of BOD need not be
 considered.  The resulting concentration difference can be expressed
 as:
            AL =
                    AL  exp
                      o   p
                    AL
                             •-J
                               L
(V +
A
                        (!V-27a)
                        (IV-27b)
where 'L is the change in BOD concentration due to a change,  f-L  ,  in
 the  initial concentration.   Equation  IV- 27A should be used for a Case 1
or Case 2 situation, and Equation IV-27B for Case 3 or Case 4.  If an
estimate of the absolute level of BOD is desired, however,  then  the
appropriate expression including the nonpoint sources should be
utilized.  It should be noted that if the diffuse sources of BOD are
                                 374

-------
         large then the improvement of instream BOD concentrations  by point
         source control will be relatively minor.   In that case the planner
         should focus on nonpoint source control.
                                       EXAMPLE IV-5
Mixing
 Zone
                          Ejrti mati ng  BOD  Distribution  in  a _Rvve_r

               Suppose the user wants to  calculate  the BOD  distribution  in the river
          shown below in Figure IV-13.  There are nine point sources contributing
y0=i.ifPs
BOD= mg/l 1
Q = 300cfs 1
1 t
\
1
™\i
I ^S
1 /^
I vi>
n


/ 75 Ml. \
t


K


/2\
(4)




t
/fr
&


®
1



50 Ml.
\ Q = 200cfs
\BOD = lmg/l

tti
©®i
i/
/
r Mixing
Zone
i
'y >
» A\ /
       FIGURE  IV-13      HYPOTHETICAL BOD WASTE LOADINGS IN  A RIVER
          BOD  in  the  stretch of river under consideration.   The  ninth source is
          assumed to  be a tributary, and contributes  substantially more flow than
          the  other eight.  Begin hy dividing the  river  into  reaches.  The
          first reach  (I) should include the first 75 miles  in which there is
          one  point source of BOD at the upstream  end (source (1)).  Equation IV-22
                                            375

-------
is applicable to that reach.  Now, there are several choices available
regarding the division of the river between sources (2) and (8).   One
choice is to divide the 50 miles into mini-reaches similar to reach I,
and reapply Equation IV-22 seven more times.  A second alternative is
to group adjacent point sources into fewer and larger sources, thereby
requiring fewer applications of Equation IV-22.  A third alternative  is
to assume that sources (2) through (8) comprise one continuous distrib-
uted source, the total pollutant loading of this equivalent source being
equal to the sum of the individual loads.   For this representation to be
valid the sources should be both evenly spread spatially and be dis-
charging comparable loads.  The third alternative will be examined here,
and reach II will consist of the 50 miles  following reach I.  Equation
IV-25 will  be used to analyze reach II.  Reach III then, will begin just
downstream from the tributary (source (9)).

     For reach I, Equation IV-22 is first solved.  Suppose the follow-
ing characteristics of waste source (1) are known:

     Q  =   20 MGD  =  1.55  (20) cfs = 31 cfs
     W  =   5000  Ib. BOD5/day

Recall  that
                0
 W must  be in  Ib.  BOD  ultimate/day:
                     -5-QPl  =   7353  ib.  BOD, /day
                      . bo                 L
                                  376

-------
Then
                   (1) (300) + 7353/5.38
                        300 + 31
=  5.0 mg/1
The decay coefficient is estimated from Figure IV-H as 0.4/day.   No
correction will be made for temperature.  Equation IV-22 can
now be expressed as (for constant cross-sectional area):
              L  =  5

where x is the downstream distance in feet.  Note the correction
needed to convert the decay coefficient from units of I/day to I/sec

     The results of the above equation for selected distances down-
stream can be expressed as follows:
x (miles)
0
30
60
75
L (mg/1)
5.0
2.6
1.3
0.9
     For reach II, sources (2) through (8) are assumed to contribute
the followinc loading.

                          BOD = 8000 Ib/day
                            Q = 120 MGD = 186 cfs

The flow distribution, Q, in reach II is then:
                     0    X.
                                           186
                                 377

-------
where x i.s  in  miles  (from 0 to 50).   L ,  the  average BOD.  concentration

in the incoming  flow  is:
                .  = 8COO Ib/day    _l_ms/l	  _  8 Q    ,,
                Lr     120 MGD    X 8.34 Ib/day    B'U mg/'
If the average  depth in reach II is assumed  to  be  5 feet, then:




                kL  = .3/day



Finally, E,  is  computed:
                r    -   LQ    Q    A  -  o  .  331
                El   ~     A      '  Ao " UQ  ~  1.1
                            (0.3)(301)

                                               =  2  5
                               186
                             (50)(5280)
Then,  using  L  from  the 75 mile point of Reach  I  as  LQ:
                  -3,-
                                 378

-------
In tabulated form:
x (mi )
0
20
40
50
Q (cfs)
331
405
480
517
L (mg/1)
0.9
1.8
2.3
2.5
Note that the BOD concentration is increasing within this reach.
   For reach III, only enough information is given to compute the
initial  concentration, utilizing weighted values  for  the  ROD  at the end
of reach II and that entering through the tributary (source (9)).
   =  200JJ) + 517J2.JQ.  =
o         200 +517
                                                   „
                                                 mg/l
                           END OF EXAMPLE IV-5
4.2.6   Interpretation of Results

     The most frequent  use of BOD data  in river water quality
analyses involves  their relationship with the dissolved oxygen
balance.  This relationship will be discussed more fully in Section
4.3.  At this point  it  is sufficient to say that it  is necessary to
predict the BOD distribution in a river in order to  compute dissolved
oxygen  concentrations.

     When a river  receives a heavy load of organic matter, the normal
processes of self  purification result  in a series of zones of decreas-
ingly severe conditions succeeding one  another downstream.  Each zone
contains characteristic animals and plants (Neir.erow, 1974).  A sapro-
bicity  system (saprobicity is a measure of biodegradable organic
matter) has been developed that relates BOD concentrations in streams
                                379

-------
to the degree of pollution there.  Correlations have been found, for
example, among BOD concentrations, coliform bacteria, and dissolved
oxygen in rivers (Sladecek, 1965).  Sladecek (1969)  has assigned 5-day
BOD values of 5 mg/1  to mildly polluted  conditions and  10  mg/1  to  sub-
stantial pollution.

     Sources of drinking water are subject to restraints on the maximum
allowable BOD that can be contained in raw water and still qualify as
a drinking water source.  Further, the degree of treatment of the raw
water is dependent on  the concentrations of certain constituents, such
as BOD.  One reference (NEC, 1975) has stated that water having a 5-day
BOD over 4 mg/1, in combination with high levels of other constituents,
represents a poor source of domestic water supply.

     As  discussed  above, BOD  in  a  river can come from a number  of
sources, both point and nonpoint.  Although BOD reduction from  point
source might be easier to accomplish  than from nonpoint sources,
there  is no guarantee  that BOD levels will be substantially lowered.
4.3  DISSOLVED OXYGEN

4.3.1.  In t roduc_ti_on_

      Historically dissolved oxygen has been and continues to be the
single most frequently used indicator of v-ater quality in streams and
rivers.   Figure IV-14 shows the seasonal variability of dissolved
oxygen in 22 major waterways throughout the country (EPA, 1974) from
1968 to 1972.   Invariably the levels observed from June to October
are lower than those observed in January to March.   This is due
primarily to the influence of temperature on the dissolved oxygen
levels.   Due to the effect of temperature,  surrmer is the most critical
season in terns of organic pollutant assimilation in rivers.
                                  380

-------
                                    300 SEASONAL
                                               Greater
                                                Than
Reach
Hudson
De 1 aware
Susquehanna
Potonac
AlabaiTia
Upper Ohio
diddle Ohio
Lower Ohio
Upper Tennessee
Lower Tennessee
Upper Missouri
Middle Missouri
Lower ilissoun
Upper Mississippi
Mississippi near Minneapolis
Middle Mississippi
Lower Mississippi
Upper Arkansas
Lower Arkansas
Upper Red
Lower Ked
Brazos
Rio Grande
Upper Colorado
Lower Colorado
Sacramento
Col umbi a
Snake
Wi 1 1 amette
Yukon
Boston Harbor
Chicago Area-Tributaries
Chicago Area-Lake ,-iichigan
Detroit Area-Tributaries
Detroit Area-Rivers
Nuofer 0.00 1.75 3.50 5.25 7.00 8.75 10.50 12.50 14. (
Stations
19
17
21
Ib
10
8
59
29
6
24
?3
9
4
3
17
12
4
4
4
3
5
4
4
2
5
4
17
12
12
7
8
9
14
11
5
6
6
7
4
1
6
5
7
b
14
9
8
!
21
11
18
15
?8
23
7
16
65
11
9
7
7
b6
1 i 1
•JLf
1*
tie
•1*




	 %L
*T




tit
1*
_.,, %L
•P





.,£-.. Mean 15th
KEY: ^^^ Percent! le
x^ Mean
Jfin-Mnr -.- . - ^TB ... . .... ...
Mean 85th.^-'- —
Percentile
.
^r
ale
•p
1 I I
T T I
tic
1* 	 	 	
	 « 	
--* 	

	 • 	
"• 	
	 •--





	 * 	


A. i
^r



	 •• 	
>b
.
"~^~~
*
	 • 	





	 •-
	 , 	
"*
III
FIGURE IV-14
VARIABILITY OF DISSOLVED  OXYGEN BY SEASON FOR
22 MAJOR WATERWAYS,  1968-72  (EPA,  1974)
                             381

-------
      The dissolved oxygen calculations presented below range in
complexity from a simple CBOD-DO relationship to a more general  dis-
solved oxygen mass balance including CBOD,  NBOD, photosynthesis,
respiration, and benthic demands.   It should be stressed, however,
that the results calculated from any of the relationships provide
estimates only since each procedure incorporates various assumptions
that might not be  fully met.  For example, waste loading inflows are
assumed to remain  constant  in quality and quantity over  time.   In
reality loadings probably vary over time.  Furthermore the choice
of system parameters involves a certain degree  of judgment.  However,
for any given situation, the planner can establish an envelope  of
possible outcomes  by different realistic choices of system parameters,
4.3.2  Dissolved Oxygen Mass-B_alance_

      The general dissolved oxygen mass-balance equation that will be
utilized here is given by:

                        -kl-kN + k  (C  C]   S  +PR           (IV-28)
   5F =   = -   A 3x        LL   V    a (  s Lj   bb   P R           V      '

where the new symbols introduced are:
   C   =  dissolved oxygen concentration, mg/1
   k   =  reaeration coefficient, I/day
    a
   C   =  saturation value cf dissolved oxygen, mg/1
   Sb  =  benthic oxygen demand, mg/1/day
   P   =  rate  of oxygen production due to photosynthesis, nig/I/day
   R   =  rate  of oxygen consumption due to algal respiration,
          mg/l/day

Stated in words, Equation  IV-24 expresses the  following relationship:
                                 382

-------
At steady state, the rate of addition of dissolved oxygen to a river
due to reaeration and photosynthesis equals the depletion rate caused
by the net advective flow, carbonaceous oxidation, nitrogenous oxidation,
benthic demands, and algal respiration.

Commonly, the dissolved oxygen mass-balance equation is expressed in
terms of the deficit, D, which is the difference between the saturation
and actual concentrations.

4.3.3  Reaeration Rate

      The atmosphere acts as  the major source for replenishing the
dissolved oxygen resources of rivers.  Reaeration tends to equili-
brate the dissolved oxygen concentration in a  river  with its saturation
value.  Most commonly,  the dissolved oxygen concentration is below
saturation and there is a net influx of oxygen into  the river from the
atmosphere.   On occasion, due to the production of dissolved oxygen  by
algae, rivers or streams can  become supersaturated,  in which case there
is a net loss of oxygen to the atmosphere.

      A number of expressions for the  reaeration  coefficient,  k  ,  have
                                                              a
 been  developed.   Several are presented here.   O'Connor's formulation
(Thomann, 1972) states that:

                       k   =  (DL  U)     at 20°C                         (IV-29)
                              H3/2
 where
       D,  =  oxygen  diffusivity  =  0.000081  ft2/hr  at  20°C
       H   =  stream  depth  in  ft
       U  =  stream  velocity  in  ft/sec
                                 383

-------
Expressed in English units,

                              ,V2
                   k  = 12.9 U "•  at 20UC                            (IV-30)
                        — H3/2
The above formula was verified on streams and rivers ranging in average
depth from 1  foot to 30 feet with velocities ranging from 0.5 to 1.6  fps.
Its use should be limited to streams where the reaeration coefficient
is less than  12/day.  Figure IV-15 illustrates how kfl changes with depth
and velocity  according  to  this  relationship.

     For shallow (0.4 - 2.4 feet), fast moving streams the following
expression developed by Owens (Thomann, 1972) is preferable, as the
experimental  work to develop this expression was done almost exclusively on
shallow streams:

                         k  - 21.6  U°'67  at 20°C
                          a       —1V85                            (IV-31)
                                    n
where U is in ft/sec and H in feet.  A graphical representation of Equation
IV-31 is shown in Figure IV-16.

     Covar (1976) showed that there were certain combinations of river
depths and velocities where a formula developed by Churchill
(Churchill et al_., 1962) is more accurate than either the O'Connor or Owens
formulations.  The Churchill expression is:

              ka  =  11.6U0'969 H'1-673  per day  at 20°C            (IV-32)

The regions of validity, and the predicted values, for the three
formulations are shown  in Figure  IV-17.

     Recent studies  have suggested that the  Owens expression overestimates
the reaeration rate  for particularly shallow streams  (e.g., less than a foot
in depth).  Under these circumstances the Tsivoglou-Wallace method
(Tsivoglou and Wallace, 1978) is more accurate.  The  expression is:
                                  384

-------
  10.0
   o
o
o
O
CO


!5
 O
Ld

O
UJ
o
o
o
01
UJ
<
LU
cr
   0.10
   0.01
       0.3

       DEPTH (FT.)
                  1.0
                                          Rapid Turbulent
                                          1.0-2.0 FPS

                                          Moderate
                                          0.5-1.0 FPS

                                          Slow Stagnant
                                         "0.1-0.5 FPS
                  J_L
10.0
                                                               100.0
FIGURE IV- 15
                 REAERATION COEFFICIENT AS A FUNCTION OF DEPTH

                 (FROM HYDROSCIENCE,  1971)
                               385

-------
   40
   10
o
o
O
(M
1
V-Stream Velocity (ft/sec)
                 j	i	i   i   i   i  i
                                                          V=I.O
                                                          V»0.5
                                                          V=0.l
       O.I

      DEPTH (FT.)
                                                 4.0
    FIGURE IV-16  R.EAERATION COEFFICIENT  FOR  SHALLOW STREAMS,

                  OWEN'S  FORMULATION
                                386

-------
G)
                                     3e«/l
'It.)
-~f.
o
s
s
\
c
TS

i
u
^.

s
•^
c
i
\
A.
1
D
h
^
p
o>
-<,

K
                                               o

-------
           ka (I/day)
            a
                                         -0
7776. US, @ 25°C, Q < 10 cfs            (IV-33a)
4665.6 US, @ 25°C, 10 < 0 < 3000 cfs    (IV-33h)
                            2592. US, & 25°C, Q > 3000 cfs          (IV-^c.
where
     S  =  stream slope, ft/ft
Table IV-13 compares predictions of Tsivoglou-Wallace with observed values
for several small streams in Wisconsin.  The agreement is good.
                                EXAMPLE IV-6
                       Prediction of Reaeration Rates

     In September, 1969, a study was conducted to determine the reaeration
rate coefficients on the Patuxent River in Maryland during the low flow
period.  The study was carried out on a seven mile stretch of the river
below Laurel, Maryland.  The stream was divided into seven segments, and the
reaeration rate determined for each segment.   A portion of the results are
shown in the Table IV-14.  Using the hydraulic data in the table predict the
reaeration rates using the methods of Tsivoglou-Wallace and of Covar.

     Since the method of calculating the reaeration for each reach  is the
same, an example calculation will be shown for the first reach only.  Based
on a velocity of 0.39 ft/sec and a slope of 0.0013 ft/ft, the
Tsivoglou-Wallace method predicts a reaeration rate of

              k   =  7776 x 0.39 x 0.0013  -   3.9/day at 25°C
               a

Equation IV-33a is used since Q<10 cfs.

     Using Figure IV-17 and a river depth of  0.8 feet reveals that the Owens
formula is applicable.  Applying Equation IV-31 shows that
                             n  ^qo .ev
                   k   = 21.6  ^^	  =  17.4/day  at  20°C
                    a         0.81'85
                                    388

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                            TABLE IV-13
               COMPARISON OF PREDICTED AND OBSERVED

          REAERATION RATES ON SMALL STREAMS IN WISCONSIN*



Stream
Black Earth
Creek
Mud Creek
tributary
Dodge Branch
Isabel! e Creek
Madison effluent
channel
Mill Creek
Honey Creek
West Branch
Sugar River
Koshkonong Creek
Badger Mill
Creek


Observed k
(I/day at 25°C)
8.46
10.7
33.1
14.
2.06
3.31
18.4
42.5
6.09
7.98
Predicted
k Using
Tsivoglou's
Method
(1/da.y at 25°C)
7.8
4.2
34.6
-
4.1
2.2
27.4
36.4
4.8
9.1
*Grant, R.S., 1976.  Reaeration-Coefficient Measurements of 10 Small
 Streams in Wisconsin Using Radioactive Tracers...  with a Section on
 the Energy-Dissipation Model.  U.S. Geological Survey.  Water Resources
 Investigations, 76-96.
                                   389

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                                                       TABLE IV-14
                                            TYPICAL  HYDRAULIC PROPERTIES

                                          PATUXENT RIVER (SEPTEMBER,  1969)
Reach
1-2
2-3
3-4
4-5
5-6
6-7
Flow
cfs
9.8
9.8
9.8
19.5
19.5
19.5
Length
ft
5,400
4,200
7,200
8,400
6,600
4,800
Velocity
ft/sec
0.39
0.22
0.35
0.35
0.25
0.37
Depth
ft
0.80
1.00
1.00
1.10
1.10
1.00
Slope
ft/ft
.0013
.0011
.0014
.0018
.0013
.0013
Reaerution Rate (I/day)
Observed
(25°C)
3.9
2.7
3.3
3.5
2.4
4.8
Tsi vogl ou-VJal lace
(25°C)






Covd r
(20JC)






GO
UD
O

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The results for all the reaches are tabulated below.
                          Reaeration Rate (I/day)
       Reach
        1-2
        2-3
        3-4
        4-5
        5-6
        6-7

The predictions using the Tsivoglou-Wallace method  are good for all reaches,
while the method of Owens predict values two to three times too large, and
provides evidence that Owens method probably should  not be applied to
extremely shallow rivers.
Observed
(25°C)
3.9
2.7
3.3
3.5
2.4
4.8
Tsivoglou -Wai lace
(25°C)
3.9
1.9
3.8
2.9
1.5
2.2
                            END OF EXAMPLE IV-6
     Temperature changes  affect the reaeration rate,  and the relationship
can be  approximated by:

                          (kJ   =  (k )    1.024(T-20)               (IV-34)
                           3 T       a 20
where
      (k  )    is the reaeration coefficient at T °C.
       a T
In addition  to temperature,  substantial suspended  sediment concentrations
can appreciably  alter the  reaeration rate in streams  (Alonso ejt _al_., 1975).
As an  approximation, k   decreases by 9 percent per  1,000 ppm increase in
                      3
suspended sediment up to a 4,000 ppm load.  Beyond  that, concentration data
are not  available to assess  the response of k  .   It  is  suggested that a 40
                                             a
percent  decrease be used for higher suspended  sediment  loads.  Rivers with
high  suspended sediment  loads are generally found  in  the western central
                                    391

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states.  Measured values of k  for various streams and rivers are included
                             a
in Appendix C.
4.3.4  Effect of Dams on Reaeration

     Many rivers or streams have small to moderate sized dams crossing them
in one or more places.  Reaeration occurs as the water flows over the dam.
Based on experimental data (Gameson eit aJL , 1958), and later verified with
field data (Barrett et al_ 1960), the following relationship for reaeration
over dams has been developed:
b(1 *0.046T)H]°
                                                             a

where
     D   =  dissolved oxygen deficit above dam, mg/1
     D.   =  dissolved oxygen deficit below dam, mg/1
     T   =  temperature, °C
     H   =  height through which the water falls, ft
     a   =  1.25 in clear to slightly polluted water:  1.00 in polluted
            water
     b   =  1.00 for weir with free fall:  1.3 for step weirs or
            cascades

     An alternate equation developed from data on the Mohawk River and Barge
Canal in New York State (Mastropietro, 1968) is as follows:

                            Da - Db = 0.037H Da                      (IV-36)

Equation IV-36 is valid for dams up to fifteen feet high and for
temperatures in the range of 20° to 25 C.

     In handling the problem of a dam, a new reach can be started just below
the dam.  Da can be calculated as the value that occurs at the end of the
upstream reach.  The new deficit Db, which will become the deficit at the
beginning of the next reach, is calculated using either of the above two
formulas.
                                   392

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4.3.5  Dissolved Oxygen Saturation

     The rate at which atmospheric reaeration occurs depends not only on k^,
but also on the difference between the saturation concentration GS and the
actual concentration C.  The saturation value of dissolved oxygen is a
function of temperature, salinity, and barometric pressure.  The effect of
salinity becomes important in esuarine systems, and to a lesser degree in
rivers where high irrigation return flow can lead to substantial salinity
values.  Table  IV-15 depicts the relationship between oxygen saturation and
chlorinity.  The expression relating salinity and chlorinity concentration
is:

            Salinity (°/   ) = 0.03 + 0.001805 chlorinity (mg/1)      (IV-37)

where
     °/oo represents parts per thousand.

     The temperature dependence  (at zero salinity)  can be  expressed  as:

              C  -  14.65 - 0.41022T + 0.00791T2 - 0.00007774T3       (IV-38)
                s

where  T  is  in °C.   This relationship  is also found  in Table  IV-15 for  zero
chloride concentration.

     Barometric  pressure affects  C$ as follows:


                           cs'  =  cs  V-TGO^P;/                      dv-39)
                                            027E\
                                     /     .
                                     V  "
where
     C   =
      s
            water, mg/1
      C    =   saturation  value  at  sea  level,  at  the  temperature  of  the
      s
     C '  =  corrected value at the altitude of the river, mg/1
     P.   =  barometric pressure at altitude, mm Hg
                                    393

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                   TABLE IV-15
SOLUBILITY OF OXYGEN IN WATER (STANDARD METHODS,  1971)
Temp.
in
°C
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
Chloride Concentration
0
5,000
10,000
in Water - mg/1
15,000
20,000
Di fference
per 100 mg
Chloride
Dissolved Oxygen - mg/1
14.6
14.2
13.8
13.5
13.1
12.8
12.5
12.2
11.9
11.6
11 .3
11.1
10.8
10.6
10.4
10.2
10.0
9.7
9.5
9.4
9.2
9.0
8.8
8.7
8.5
8.4
8.2
8.1
7.9
7.8
7.6
7.5
7.4
7.3
7.2
7.1
13.8
13.4
13.1
12.7
12.4
12.1
11.8
11.5
11.2
11.0
10.7
10.5
10.3
10.1
9.9
9.7
9.5
9.3
9.1
8.9
8.7
8.6
8.4
8.3
8.1
8.0
7.8
7.7
7.5
7.4
7.3





13.0
12.6
12.3
12.0
11.7
11.4
11.1
10.9
10.6
10.4
10.1
9.9
9.7
9.5
9.3
9.1
9.0
8.8
8.6
8.5
8.3
8.1
8.0
7.9
7.7
7.6
7.4
7.3
7.1
7.0
6.9





12.1
11.8
11.5
11.2
11.0
10.7
10.5
10.2
10.0
9.8
9.6
9.4
9.2
9.0
8.8
8.6
8.5
8.3
8.2
8.0
7.9
7.7
7.6
7.4
7.3
7.2
7.0
6.9
6.8
6.6
6.5





11.3
11 .0
10.8
10.5
10.3
10.0
9.8
9.6
9.4
9.2
9.0
8.8
8.6
8.5
8.3
8.1
8.0
7.8
7.7
7.6
7.4
7.3
7.1
7.0
6.9
6.7
6.6
6.5
6.4
6.3
6.1





0.017
0.016
0.015
0.015
0.014
0.014
0.014
0.013
0.013
0.012
0.012
0.011
0.011
o.on
0.010
0.010
0.010
0.010
0.009
0.009
0.009
0.009
0.008
0.008
0.008
0.008
0.008
0.008
0 . 008
0.008
0.008





                          394

-------
     P   =  saturation vapor pressure of water at the river
            temperature, mm Hg
     E   =  elevation, feet

Table IV-16 illustrates the variability of dissolved oxygen saturation with
altitude and temperature.  The significant effect of altitude is apparent
and should not be neglected.  For example, at a temperature of 20 C, the
saturation value decreases from 9.2 mg/1 to 7.2 mg/1 as the altitude
increases from sea level to 6000 feet, the approximate elevation of Lake
Tahoe and the Truckee River in California and Nevada.
4.3.6  DO-BOD Interactions
     A widely used dissolved oxygen predictive equation is the
Streeter-Phelps relationship which predicts the dissolved oxygen
concentration downstream from a point source of BOD.  Assuming a constant
river cross-sectional area, the dissolved oxygen deficit  (C -C) can be
expressed as:
D -
D exp
-k
. u

J ka-kL
where
D
L
                                       exp
            reaeration coefficient,  I/day
            initial deficit  (at x =  0), mg/1
            deficit at x, mg/1
            initial BOD  (at  x  = 0),  mg/1
            BOD decay coefficient,  I/day
                                              - exp
(IV-40)
L  and D  are found by  proportioning  BOD  and  DO  deficit  concentrations  just
upstream of the waste discharge with  the  influx  from  the discharge  itself.
As presented earlier  in  the  BOD section,  LQ  is given  by:
                            W/5.38 + L  Q
                            	 u  u
                               Q,., + Q,,
                                                                      (IV-41)
                                   395

-------
          TABLE IV-16
  DISSOLVED OXYGEN SATURATION
VERSUS TEMPERATURE AND ALTITUDE
Temperature
0
5
10
15
20
25
30
35
ALTITUDE (ft)
0
14.6
12.8
11.3
10.2
9.2
8.4
7.6
7.1
2,000
13.6
11.9
10.5
9.5
8.5
7.8
7.1
6.6
4,000
12.5
11.0
9.7
8.8
7.9
7.2
6.5
6.1
6,000
11.5
10.1
8.9
8.0
7.2
6.6
6.0
5.6
8,000
10.5
9.2
8.1
7.3
6.6
6.0
5.4
5.1
              396

-------
where
     W   -  discharge rate of BOD, Ib/day
     L   -  concentration of BOD  in the river upstream of the waste
      u
            discharge, mg/1
     Qu  =  river flow rate upstream of discharge, cfs
     Qw  =  flow rate of waste discharge, cfs
     Qw + Qu =  flow rate of river in the reach under consideration,
            cfs
W in Equation IV-41 should be expressed in terms of ultimate BOD, and not
5-day BOD.

     The  initial deficit is found from:
                   D   =C
                   0    s
                                             Q  + Q
                                             y    4
                                                          IV-42)
where
      w
concentration of dissolved oxygen in the waste, mg/1
concentration of dissolved oxygen upstream of the waste
discharge, mg/1
dissolved oxygen deficit in waste, mg/1
dissolved oxygen deficit upstream, mg/1
In cases where information is lacking, D  can normally be assumed to be in
the range 1-2 mg/1.
     If NBOD is to be considered as well as CBOD, Equation IV-40 can be
modified as follows:
                               L_K|         / ~~ KI  X \        / ~ K
                         -  4-
                        U
       D =  DQ  exp
                     -k   x
                      a
                  __-.
                  k  -k.
                   a   L
                            exp
                          N
                               r    / -kN x \
                               [exp ( --jj-j  -
                                                exp
                                                          IV-43)
If the decay coefficient of NBOD is approximately equal to that of CBOD,
Equation IV-40 can be utilized instead of the more complicated Equation
                                    397

-------
IV-43.   In  this case, L  in Equation  IV-40  is  replaced by the sum of L   and
4.3.7  Dissolved Oxygen Calculations

     Calculation of dissolved oxygen in rivers  can proceed as shown in
Figure IV-19.   The planner needs to estimate  the waste loading scheme for
the prototype,  whether it be for a 20 year  projection or for current
conditions.   The river system can then be divided into reaches and by
repeated use  of Equation IV-40, dissolved oxygen calculations can be
performed for each reach, starting from a known boundary condition and
proceeding downstream.  All data and calculations should be succinctly and
clearly recorded to minimize errors.

     The dissolved oxygen profile downstream  from a waste discharge
characteristically has a shape shown in Figure  IV-18.  If the reach is
          o
          q
          ci
                    -Waste Inlet
              0              TC(XC)
                TIME (DISTANCE)
       FIGURE  IV-18
CHARACTERISTIC  DISSOLVED OXYGEN
PROFILE DOWNSTREAM FROM A  POINT
SOURCE OF  POLLUTION
                                   398

-------
   Determine projected waste loading

  scenario  (source/sink distribution)
   Criteria Met for

  Hand  Calculations
                       Divide river into reaches
Nj,
/
Determine temperature independent
parameters for each reach:
u, Q, d, A (as needed)
\,
/
Determine reaction rates at 20° C:
k , k, , k , SD (as needed)
a I n D
for each reach
\
/
\,
NO
/
Use Computer
Model
                  | Incorporate temperature corrections |
                       Determine C  for each reach
                      Calculate conditions at x=o

                     (upstream end of present reach)
\
 Perform and record

desired calculations
FIGURE  IV-19    FLOW  PROCESS  OF  SOLUTION TO DISSOLVED  OXYGEN
                   PROBLEM  IN RIVERS
                                      399

-------
long enough, the dissolved oxygen deficit will increase to some maximum
value, D , at a distance x  (termed the critical distance).  D  is called
        L.                 L*                                   L-
the critical deficit.  Within any reach there will always be a minimum
dissolved oxygen value that occurs, but it may not be the critical deficit,
which is defined as the minimum point on a dissolved oxygen sag.  The
difference between the minimum and critical values should be kept in mind.
As one example of the difference between the values, a reach may have a
dissolved oxygen profile where concentrations are monotonically decreasing
throughout the reach.  The minimum DO will then occur at the downstream end
of the reach, but this will NOT be the critical DO value, since DO is still
decreasing in the downstream direction.
     The travel time to the critical deficit is given by:
                                    k
                           1
                        k -k.
                         a   L
     /    D (k -k, )
 a   /-,     o  a  L
k,    I1  ~   k.  L
 L   \       L  o
                                                                      (IV-44)
The distance downstream can be computed by knowing the travel time and flow
velocity:
                                   = U •  t
                                 (IV-45)
The critical deficit can be found from:
                            L k.  \
                             o L \
                                                         -k
                                                                      (IV-46)
     The formulas for the critical dissolved oxygen deficit are not really
applicable  in the special case when ka = kL.  However, these special cases
can readily be handled in one of two ways.  First a small change can be made
in either k  or k, so that k, and k,  are approximately equal.  Or  second,
            a      L          d      L
the following expression can be used to predict critical travel time:
                                   400

-------
                             T   -     I I     —
                             1. _  ~  7—- I 1  — i
                                                                     (IV-47)
                                           uo /
Then, the critical deficit is given by
                     D   =  exp
                                                                      IV-48)
Equation IV-48 is valid for all k /k.  values, and is not limited to cases
                                 a  L
where k /k.  = 1.
       a  L

     Solutions to both Equations IV-46 and IV-44 are presented in Tables
IV-17 and IV-18, respectively.  There exist practical limitations to the
solutions of both equations, governed by the conditions that the solutions
be both positive and real.  If in solving Equation IV-44 t  is negative, the
                                                          L*
minimum dissolved oxygen concentration actually occurs at the point of
discharge, and concentrations increase immediately below the discharge.

     Tables IV-17 and IV-18 are particularly useful for computing the waste
assimilative capacity of a river.  Waste assimilative capacity (WAC), as
defined here, is the amount of BOD that can be discharged into a river
without causing the minimum dissolved oxygen level to fall below a specified
value.  In constructing Tables IV-17 and IV-18 extra detail was incorporated
for DO/LQ values between 0.0 and 0.5.  This is necessary because most
practical problems fall within this range.

     The following steps show how to use Table IV-17.

     1.  Find the reaeration rate (ka) and the BOD decay rate (kL) for
         the river being investigated.

     2.  Find the BOD concentration in the river just below the point
         of mixing (L0).

     3.  Find the dissolved oxygen deficit at this location
         (D0 = Cs - C).
                                   401

-------
UJ     CO
_i     a:
ca     uu
        (X)

        UJ
           o
          _1
          •»_
           (_>
j><:
-^.
   (V
-*a
                                                                  o  —  —
                                                       to  r--  ;o  CO  O"1  Q  O  •—
                                             GO  ON  01  o  ~-  ^-
                                                       „-  tO  <^1

                                                                                                                          O  —  f"  O

                                                                                                                          to  r-  oo  -3-  -—  co
                                                                                                                                            .—  O  CC
                                                                                                                                                                                                                      o  o  cr
                                                                                                                                                                                                                   o  o  o  —  —
                                                                                                                                                                                                               O  (—  —  i—
                                                                                                                                                                                                                                                             CM
                                                                                                                                                                                                                                                             CD
                                                                                                                                    o     o
                                                                                                                                                                                                                        o    c

-------

CQ       t>O
<:       ID
t—       oo
          o:
          LU
                             J*

                                n:
                             j*:
                                                                             r—   o   o   en  co
                                                                         ,—   i—   oocnccccr---^
                 O  i-O   O
                 <—  o   o

                                                                                                             cn  TT  cc
CO  LT!  '—  CO   ^T
—  .—  ^-  o   o
                     o   ^c   cxi   co  KJ-  o
                     o   en   en   c.:  cc  cc
                                                                                     O  --  -=3-
                                                                                                 —  en  ic
                                                ooocn
                                                CO  CO  CO

                                                                                                                                                                                                                                                    .M  O

                                                                                                                                                                                                                                                       CTl  f^-   ufl   CM   C~>
                                                                                                                                                                                                                                               -   O  CO

                                                                                                                                                                                                                                               o  en  cc
                                                                                                                                                                                                                                               o  en  cc
                                                                                                                                                                                                                                               =  oc5c3o----r-^-

                                                                                                                                                                                                                                               oooooooooc
                                                                                                                                                                                                                                                                                                      CO
                                                                                                                                                                                                                                                                                                      o
                                                                                                                                         o     o
                                                                                                                                                                                                                                                        o     o

-------
     4.  Compute k /k.  and D /L  .

     5.  Using the ratios ka/kL  and D0/l_0, find DC/L0 where  Dc  is  the
         critical deficit.

     6.  Finally, calculate DC =  (DC/LQ) LQ, and Cmin = Cs - DC.

To use Table  IV-18 complete these steps:

     1.-4.  Repeat steps 1 through 3 above.

     5.     Using the ratios k /k, and D /L  , find k t  .
                              a  L      U  U        a L

     6.     Calculate t   =  (k t )/ka.
                       C       a C   a
4.3.8  General Dissolved Oxygen Deficit Equation

     The most general dissolved oxygen mass-balance formulation to be
presented in this chapter is as follows:
where
/ Lrd) [ /A
M rd ) \Fvn |
n !c I exP '
\ N / [
+ D0 exP (
°
^ Ao
^-ja
^ AM
                                              f(x))  -
                                              - exp
                                                )
                                                           ^1 f (x))
                                                                (IV'49)
P
R
S
            oxygen production rate due to photosynthesis, mg/l/day
            oxygen utilization rate due to respiration, mg/l/day
            benthic demand of oxygen, mg/l/day
                                   404

-------
The distance function f(x) expresses the cross-sectional area relationship
throughout the reach.  The area can increase or decrease linearly or remain
constant.  The general form of the relationship is:

                      f(x)  = AQx  + AA  x2/2 , AA = A^A^
                                                  "
                                                    XL
where
     Af  =  area at x = XL
     A   =  area at x = 0
     x.   =  length of reach
For a reach of constant cross-sectional area, Aft = 0.

     In developing Equation  IV-49 the following relationship for CBOD was
used (as originally presented in the BOD section):
                                                                      (IV-22)
An analogous expression for NBOD was also used.

     In Equation IV-49, the distributed sources and sinks (P, R, Sg, L  .,
Nrd) are all mass fluxes, and no volumetric flow rate is associated with any
of these sources and sinks of dissolved oxygen.


4.3.9  Photosynthesis _and Resp i rat ion

     The difficulty of accurately assessing the impact of photosynthesis and
respiration on the dissolved oxygen resources of streams is not readily
apparent from the single terms appearing in Equation IV-49.  Of concern are
both free floating and attached algae, as well as aquatic plants.  The
extent to which algae impact the dissolved oxygen resources of a river is
dependent on many factors, such as turbidity, which can decrease light
transmittance through the water column.  Additionally, the photosynthetic
rate constantly changes in response to variations in sunlight intensity and
is not truly constant as implied by Equation IV-49.  Hence if algal activity
                                  405

-------
is known to be a significant factor affecting the dissolved oxygen  balance,
the use of a computer model is recommended in order to accurately assess
such influences.  For example, in the Truckee River in California and
Nevada, the diurnal variation of dissolved oxygen has exhibited a range of
from 150 percent saturation during the daylight hours to 50 percent
saturation at night due to algal photosynthesis and respiration,
respectively.  At the most, hand calculations can give estimates  of net
dissolved oxygen production rates that then can be compared to the  other
source/sink terms in Equation IV-28.   From this comparison the significance
of each can be estimated.

     Table IV-19 presents some observed values of photosynthetic  oxygen
production rates.  As shown in the table dissolved oxygen production is
expressed in units of rate per unit area (gm/m -day).  To convert to units
of concentration per unit time, the algal production rate must be divided by
river depth:

                                P = {-J-                                (IV-50)

where
     P  =  production rate of dissolved oxygen, gm/m2-day
     H  =  average river depth, meters
     P  =  production rate of dissolved oxygen, mg/l-day

P can now be directly compared to other terms in Equation IV-28.

     By using a regression equation developed by Erdmann (1979a,  1979b), the
production rate of dissolved oxygen,  P, can be determined directly if the
diurnal variation of dissolved oxygen is known.  When water temperature is
fairly constant throughout the day, the photosynthetic oxygen production
rate becomes
                                 P  =  2ADO                          (IV-51)

where
     ADO  =  difference between the daily maximum dissolved oxygen
             concentration and the daily minimum dissolved oxygen
             concentration, mg/1
                                  406

-------
                             TABLE IV-19
       SOME AVERAGE VALUES OF GROSS PHOTOSYNTHETIC PRODUCTION OF
  DISSOLVED OXYGEN (AFTER THOMANN, 1972 AND THOMAS AND O'CONNELL, 1966)
     Water Type
Aver.Gross Production
    (qrams/m -day)
Average Respiration
    (gm/m -day)	
Truckee River - Bottom
attached algae

Tidal Creek - Diatom Bloom
(62-109-106 diatoms/1)

Delaware Estuary - summer

Duwamish River estuary -
Seattle, Washington

Neuse River System -
North Carolina

River Ivel

North Carolina Streams

Laboratory Streams
          3-7

        0.5-2.0


        0.3-2.4


        3.2-17.6

          9.8

        3.4-4.0
                                 11.4
      6.7-15.4

       21.5

      2.4-2.9
Since Equation  IV-51  is  based on regression analysis,  the units  are  not
consistent.


     The importance of  a constant water temperature is illustrated by Figure
IV-20.  This figure shows the hourly variation of dissolved  oxygen over a 24
                                   407

-------
                                       80*
rn


<
 i

CD
CO
co
O
m
a
X


m
2:

<
>


>
—\
I—I
O
m
;o
CO
          O
          O
          O
          O
          8
          0
        Z _,.
        O oo

        §8
        CO
          ro
          6
          O
          O
          0
          O
          co
          O
          O
          O
                        oo
                                    DISSOLVED OXYGEN MG/L


                                   co         O          it
                                       \
                                              \

                                        /
O
C
33

m

CD
                                       \
                                 1   \
                               CO 33
                             O   >
                             -   §
                                             \
                                                          '

                                                             \
                                                                O

                                                              "\i
                                                              1 m
                                                               \
                                                              m


-------
hour period for Wyman Creek in California and for the  Ivel River in England.
Both exhibit  large diurnal dissolved oxygen variations, although the reasons
differ.   In curve A  (Ivel River) the dissolved oxygen  level gradually
increases from 0600  hr to 1800 hr, and then decreases over the next 12
hours.  The cause of the changing dissolved oxygen levels is a net
photosynthetic oxygen production during the daylight hours, and a net
comsumption during evening and night.  Curve B is almost a mirror image of
curve A since the minimum dissolved oxygen levels occur during daylight
hours and the maximum during nighttime.  The variations exhibited by curve B
are principally caused by a changing water temperature.  During the day this
creek absorbs considerable solar radiation causing the water temperature to
rise and the dissolved oxygen saturation level to decrease.  At night the
creek cools off and the dissolved oxygen saturation level increases.  Curve
B then is free from the influence of photosynthetic effects, so it would be
erroneous to apply Equation IV-51.  Erdmann (1979a, 1797b) and
Kelly et jf[.  (1975) provide more sophisticated methods to predict P when
both photosynthetic and temperature effects occur concurrently.  Example
IV-7 illustrates the utility of Equation IV-51.
                                EXAMPLE IV-7
            Prediction of Photosynthetic Oxygen Production Rate

     On Mechums River near Charlottesville, Virginia, Kelly ejt al_.  (1975'
collected the following data:
       Time of Day                  Stream                  Dissolved
 (hours after midnight^        Temperature,  °C            Oxvaen (mq/£)
           0-0                      23.3                       7.6
           0-5                      23.3                       7.6
           1-0                      23.4                       7 6
           1.5                      23.4                       7.5
           2-0                      23.5                       7 4
           2-5                      23.5                       7 2
           3.0                      23.5                       7.3
           3-5                      23.5                       7 3
           4-0                      23.4                       7 3
                                 409

-------
      Time  ot  Uay                  Stream                  Dissolved
(hours after midnight)         Temperature, "C:           Oxy_2_en_l!53L?J-

          4.5                      23.4                      7.3
          5 0                      23.3                      7.3
          5.5                      23.2                      7.3
          6.0                      23.1                      7.3
          6.5                      23.0                      7.3
          7.0                      22.9                      7.4
          7.5                      22.8                      7.4
          8.0                      22.7                      7.5
          8.5                      22.7                      7.6
          9.0                      22.7                      7.7
          9.5                      22.7                      7.8
         10.0                      22.8                      8.0
         10.5                      23.0                      8.1
         11.0                      23.2                      8.4
         11.5                      23.5                      8.5
         12.0                      23.6                      8.7
         12.5                      24.3                      8.9
         13.0                      24.8                      9.0
         13.5                      25.3                      9.1
         14.0                      25.5                      9.2
         14.5                      25.5                      9.3
         15.0                      25.9                      9.2
         15.5                      26.1                      9.2
         16.0                      26.1                      9.2
         16.5                      26.1                      9.1
         17.0                      26.1                      9.0
         17.5                      25.8                      8.9
         18.0                      25.8                      8.8
         18.5                      25.5                      8.6
         19.0                      25.3                      8.5
         19.5                      25.1                      8.3
         20.0                      24.8                     .8.2
         20.5                      24.5                      8.0
         21.0                      24.2                      8.0
         21.5                      24.0                      7.9
         22.0                      23.8                      7.6
         22.5                      23.7                      7.7
         23.0                      23.6                      7.7
         23.5                      23.6                      7.6
         24.0                      23.5                      7.5

       Using a sophisticated analysis, Kelly et a]_.  found the daily mean

  photosynthetic oxygen production to be 4.40 mg/1.  Using the data shown

  above and Equation  IV-51  estimate the daily photosynthetic oxygen
  production,  P (mg/l/day).


       The  minimum dissolved  oxygen is  7.2 mg/1, which occurs at 0230.  The

  maximum dissolved oxygen  is  9.3 mg/1  which  occurs at 1430.  Hence:
                                    410

-------
                    P = 2ADO = 2(9.3-7.2) = 4.2 mg/l/day

This compares very well with the value found by Kelly et aJL  using a more
sophisticated analysis, even though the stream temperature varies by a few
degrees during the day.  Probably one reason for the good agreement is that
the maximum and minimum values occur about 12 hours apart, which the method
assumes they do.
                            END OF EXAMPLE IV-7
     Values of photosynthetic respiration vary widely, ranging from 0.5
gm/m2/day to greater than 20 gm/m2/day.  One suggested relationship between
respiration and chlorophyll a is given as (Thomann, 1972):

                 R(mg/l/day) = 0.024  (chlorophyll  aj  (yg/1)         (IV-52)

where
     1 pg/1 = 10"3 mg/1

Chlorophyl a. concentration is most commonly expressed in terms of ug/1.


4.3.10  Benthic Demand

     In addition to oxygen utilization by respiration of attached algae,
benthic deposits of organic material and attached bacterial growth can
utilize dissolved oxygen.  Table IV-20 illustrates some uptake rates.  As
with photosynthesis, the uptake rates are expressed in gm/m2-day.  To use
these values in Equations IV-28 or IV-49, division by stream depth (in
meters) is necessary.  Temperature effects can be approximated by
                                              T_?n
                               =  (S  )    1.065'-^                   (IV_53)
                             T      b  20
                                   411

-------
                                 TABLE  IV-20
                 AVERAGE VALUES  OF  OXYGEN UPTAKE RATES OF
                   RIVER BOTTOMS (AFTER  THOMANN, 1972)
Bottom Type and
Sphaerotilus - (
Municipal Sewage
Outfall Vicinity
Location
10 gm dry wt/M2)
Sludge -
Municipal Sewage Sludge -
"Aged" Downstream of Outfall
Cellulosic Fiber
Estuarine mud
Sandy bottom
Mineral soils
SI udge



2
Uptake (gms 02/m -day)
@ 20°C
Range
-
2-10.0
1-2
4-10
1-2
0.2-1.0
0.05-0.1
Approximate
Average
7
4
1 .5
7
1.5
0.5
0.07
     The areal  extent of significant oxygen demanding benthic materials is
often limited to the region just below the outfall  vicinity.   Although the
oxygen demand may be great over a short distance,  it may be insignificant
over larger distances.  The response of rivers to  areally limited benthic
deposits is generally to move the critical deficit  upstream,  but not to
lower its value significantly.

     Zison e^t jil_ (1978) contains significantly more data and  further
discussion of benthic oxygen demand in rivers.  Additionally  Butts and Evans
(1978) conducted extensive studies of sediment oxygen demand  on 20 streams
in Illinois.  They found that benthic oxygen demand could be  predicted as:
                                   412

-------
                       =  0.15T + 0.3D  + 0.11 logN - 0.56           (IV-54)
where
     Sg  =  benthic oxygen demand, g/m2-day
     T   =  water temperature, °C
     Ds  =  depth of sediment, inches
     N   =  number of macroinvertebrates per m
2
They found that N typically ranged from 10,000 to 1,000,000.  Within this
range the sum of the last two terms is between ±0.1, and is negligible
compared to the first two terms.  Under these conditions Equation IV-54
simplifies to

                            SB  =  0.15T + 0.3DC                     (IV-55)
                             D                 b

The depths of sediment found during the study of Butts and Evans (1978)
ranged from 1 to 17 inches.  Consequently Equation  IV-55 is applicable to
streams which have fairly significant benthic oxygen demands.  For cleaner
streams Equation IV-55 probably overestimates the benthic oxygen demand.
4.3.11  Simplifying Procedures in Dissolved Oxygen Calculations

     Using Equation IV-49 might be untenable for several reasons, such as
lack of available data, or because of the voluminous calculations required
to apply  it to a large number of reaches.  Several suggestions are offered
here that should simplify analysis of dissolved oxygen problems.

     Since the general scope of this section is to facilitate the
determination of existing or potential problem areas, the analysis should
proceed from the simple to the more complicated approach.  It may be
adequate  to analyze the dissolved oxygen response to the most severe
loadings  first, neglecting those of secondary importance.  If such an
analysis  clearly indicates dissolved oxygen problems, then the inclusion of
any other pollutant discharges would only reinforce that conclusion.  More
rigorous  procedures (e.g. a computer model) could then be employed to
perform a detailed analysis.
                                    413

-------
     Suppose the improvement of dissolved oxygen levels due to decreased
loading from a point source is of interest.   This is a common situation
since it relates to the design of waste loading abatement schemes.   Such
improvement can be estimated by:
          AD =
                   exp
                          k x
                           a
                                              exp
where
Al_
AD
                       - exp   -/  f(x)
                             V Ao       >
             the change in the initial BOD, mg/1
             change in deficit in response to ALQ
                                                                     (IV-56)
Equation IV-56 was formulated from Equation IV-49 assuming that LQ and DQ
are the only changes of significance.

     Many rivers have a large number of point sources.  Although this is not
necessarily a complicating factor, a detailed analysis might be too time
consuming for hand calculations.  There are several possible alternatives to
deal with this situation in order to reduce the number of reaches to be
analyzed.  The first, already mentioned, is to consider only the significant
pollutant sources.  Second, as was illustrated in Example IV-5, a number of
uniformly distributed point sources can be considered as a single
distributed source.  Third, combining several adjacent point sources is also
possible, if the length of the reach under consideration is long relative to
the distance of separation between the point sources.  Analogously, a
distributed source can be approximated as a point source, contributing the
same waste loading and located at the center of the distributed source.

     It may be that the planner wants only to determine the critical
dissolved oxygen concentration in each of a series of reaches.  In this case
no more than two values of dissolved oxygen per reach need be calculated.
Figure IV-21 shows the solution process to be followed.
                                   414

-------
                           Go to next
                           reach
                                                  Determine  k  and k,
                                                           a      L
                                                  for each reach
                                                     Begin  reach
                                                     calculations!
Find D ,L
     o'  o
(at x = o)


Find D at
x = x.
.7
\
/
V
/
\




Find D
at xc

D =DC
at
X = 0

^YES 1
\
/YES ,
\
                                                   Find tc,  xc = Utc
                                                    Find D at x.
                                                       D = D
FIGURE  IV-21   FLOW PROCESS  IN  REACH BY  REACH SOLUTION  TO
                CRITICAL DISSOLVED OXYGEN VALUES
                               415

-------
     One final note on dissolved oxygen evaluations should be made here.  It
may be that if the planner is interested primarily in locating dissolved
oxygen problems, he need not perform any computations.  This is especially
likely where dissolved oxygen data are available at various locations on the
river.  Plotting dissolved oxygen time trends may reveal when, as well as
where, annual dissolved oxygen minima occur.
                                EXAMPLE IV-8
                Determining River Assimilative Capacity from
                           Tables IV-17 and IV-18

     Suppose the user wants to determine waste assimilative capacity (WAC)
for a river reach that has the following characteristics:

               critical dissolved oxygen concentration = 5.0 mg/1
               (user establishes this)
               initial deficit = 1.0 mg/1
               average velocity = 0.5 fps
               average depth = 4 feet
               chloride concentration = 0
               temperature range = 10°C to 35°C

First, kg and kL need to be found.  From Figure IV-17, ka (20°) = 0.8/day,
and from Figure IV-11, k,  = 0.4/day.  At any other temperature then, kaand
k. can be found from the temperature relationships previously developed:

                          k    =  (k )    1.0241-20                   (IV-34)
                          a        a 20
                          k,   =  (k, )    1.0471"20                   (IV-17)
                          L        L 20
Using Table IV-15 the dissolved oxygen saturation concentration within the
temperature range of interest  can be found.  This information can be then
compiled into Table  IV-21 shown below.
                                   416

-------
                                TABLE IV-21
                COMPILATION OF  INFORMATION  IN EXAMPLE IV-8
T
(°0
10
15
20
25
30
35
Cs
(mg/1)
11.3
10.2
9.2
8.4
7.6
7.1
C
(mg/1)
5.0
5.0
5.0
5.0
5.0
5.0
D
(mg/1)
6.3
5.2
4.2
3.4
2.6
2.1
D /D
o c
0.16
0.19
0.24
0.29
0.38-
0.48
VkL
2.5
2.2
2.0
1.8
1.6
1.4
Using the values of DQ/DC and ka/kL, LQ can be found, which in this case is
the WAC.

     Procedure

     1.  Table IV-21 is entered at the appropriate ka/k,L column.  This
         is 2.5 at 10°C.

     2.  Next, the entry within the ka/kL column in Table IV-17 is
         found such that
                            Dc/Lo
D,
                                              0.16
     Since the left-most column of Table IV-17 is DQ/L0 and the entries are
D /L , the ratio of these values is calculated until that ratio equals 0.16.

For example,  try DO/LQ = 0.05.   Then DC/LQ = 0.23 and
                            0.05  =  0.22 >0.16,  too big
                            0.23
                                  417

-------
               try DQ/LO = 0.04.   Then  DC/|_O  -  0.23 and

                             n'oo   =  .17,  close  enough
    then  p^  -  .23,  or  L   =
                                       fi
                                   o   .23
                                            =   27.4  mg/1
                                               —
 The results are tabulated below for the temperature range  10°C  to  35°C.
T(°C)
10
15
20
25
30
35
WAC (mg/1)
27.4
20.0
15.0
11 .3
7.6
5.4
D /L
0 0
0.04
0.05
0.07
0.09
0.13
0.19
L  is directly related to the loading rate of BOD,  as  expressed
earlier in Equation IV-41:
WAC = (Lo)
                     critical
                                     +W
                                       critica1/5.38
                                      Q   +  Q
                                      x     M
From equation  IV-41 the critical waste loading W can be found.  If
desired, this  procedure can be repeated for different river flow rates,
and WAC and W  ._  ,  found for the various flows.   To do  this,  diff-
             cntical
erent average  depths and velocities will be needed.  Generally this
analysis is most apolicable to minimum flow conditions, as
this is the most critical situation, but higher flows may be of interest
to assess the  benefits of flow augmentation decisions.  Novotny and
                                 418

-------
Krenkel (1975) have used a 20 year, 3-day low flow in analyzing the
Holston River in Tennessee.  For further discussion of low flow cal-
culations refer to Section 4.4.6.

     In interpreting the results of this example the user should be
looking more at trends rather than particular results.  For example,
notice how the WAC decreases with  increasing temperature.  For every
10° increase the WAC is approximately halved.  A similar relationship
between WAC and flow rate could also be determined.

     Finally, using Table IV-18, the travel time t  can be determined
to the point of critical deficit.   The appropriate DQ/LO and ka/kL
values are used to find t .  Table IV-22 illustrates these results.

                             TABLE  IV-22
                    CRITICAL TRAVEL TIME RESULTS
T(°C)
10
15
20
25
30
35
ka/kL
2.5
2.2
2.0
1.8
1.6
1.4
VLo
0.04
.05
.07
.09
.13
.19
t k
c a
1.4
1.3
1.2
1.13
1.0
0.9
ka
.63
.71
.8
.9
1.0
1.1
todays)
2.2
1.8
1.5
1.2
1.0
0.8
                        END OF EXAMPLE  IV-8
                                  419

-------
                                EXAMPLE  IV-9
              Critical Deficit Calculations  for Multiple Reaches

         Suppose  the  critical deficit in each of the three reaches  of  the
    river illustrated  in Figure IV-22 is to be determined.  The conditions
    upstream  of the first discharae are:
               T = 27UC
               Q = 600 cfs
               U = 0.4 fps
                          depth = 5.0 feet
                          Du = 1 mg/1
                          Lu = 2 mg/1
   Using these data, along with the  solution  process  outlined in
   Figure IV-21, the following  procedure can  be used:
        1.  Determine ka, kL for  each  reach.   For  this example it will
   be assumed that the average  depth,  velocity, and  temperature remain
   relatively constant over the three  reaches, so  that k  and k,  are
                                                       a      L
   also the same.
               .Mixing
 Du=lmg/l
 Qu=600cfs
             f
Zone
                            I2MI.
             B.O.D.L=40mg/l
             Q=50MGD
Mixing
 Zone
                                   4MI.
                              B.O.D.L=50mg/l
                              Q=60MGD
          B.O.D.L=20mg/l
          Q = IOMGD
FIGURE  IV-22
    HYPOTHETICAL RIVER USED  IN  EXAMPLE  IV-9
                                   420

-------
                   k   (20)  = 0.5,  (from Figure IV-l?)
                   a
                   kL  (20)  = 0.35, (from Figure IV-11)

 Using  the  temperature correction:
                   k   (27) = 0.60, (from Equation IV-34)
                   a
                  ''KL  (27) = 0.48, (from Equation IV-17)

The  saturation dissolved oxygen concentration at 27°C and 0%0 salinity
is (from Table IV-15) 8.1 mg/1.
     2.   For the first reach, calculate L  and D .
                                         o      o
            L   =  (2)(600)+(40) (50) H.55)    . _,    ._
             0          600 +(50)(1.55)      ~ 6'35 mg/1
     For lack of better information about the dissolved oxygen
characteristics of the waste, it can be assumed that D  = D  = 1 mg/1.
The location of the critical deficit can now be calculated
using Table  IV-18, or Equation IV-45•   In this example Table IV-18 will
be used.  To use that table, the following ratios are needed:

                    DO/LQ = 1/6.35 = 0.16
and
                    k /k,  - 0.60/0.48  - 1.3
                     ct  L

From Table IV-18,  katc -  .92 or

                    tc =  .92/0.6  =1.53 days

              x    _  (0.4)  (1.53)  (3600)  (24)     ..  .   „
              xc	5280"	   =   10.0  miles
                               421

-------
Since x  < 12, the critical  deficit actually  exists,  and  is located  10
miles downstream.   From Table IV-17  D   can  be found  by  entering  it with
                                     v*
the same ratios used in Table IV-18.   The result  is:

                    ~ =  .38  +  Dr = 2^_ mg/1
                     o            C

      3.   Before the critical conditions in reach 2 can be calculated,
 the  conditions at  the  upstream end of that reach must be established.
 The  conditions at  the  downstream end of reach 1 are

            D  = 2.3 mg/1, from Equation IV-40
            L  = 2.6 mg/1  from Equation IV-42
 The conditions  at  the  upstream end of reach 2 are  thus:

                    .(2^)  (677)+(60)  (K55) =
                                              «.Jt> mg/i
 D  =2.3 can be used for lack  of  better  information on the dissolved
  o
 oxygen concentration in  the  effluent  to  reach 2.  For use in
 Table IV-18, it is found that
                        VLo  =  "
 So
           k t =  .76
           t   =  .76/0.6  =1.3 days
            \s
           x   =  8.3  miles
                                 422

-------
 Since reach 2 is only 4.0 miles long, the critical deficit is not
 reached.  Instead the maximum deficit will occur at the downstream
 end of reach 2, where:

                   D = 3_._3_rnq/1_, Equation  IV-40
                   JL_=_.6,?_2 JiS/1, Equation IV-22
      4.  For the beginning of reach 3, LQ and D  must be found.

                 I    -   (20)00)0.55) +(770.5)  (6.22)
                 Lo  --  770.5     --- --- -=6.5mg/l
 For DQ, it can be assumed that GW = 5.0 mg/1.  From Equation IV-41,
 then
       n  - R i     _(8.1 - 3.3)  (770.5)+(5.0)(10)  (1.55), . -    ,
        o " °-'       ~        770.5 + 15.5~              •3"3 mg/l
 The calculations of critical conditions can now be made for
 this reach, as for the previous two.
                          END OF EXAMPLE IV-9
 4.4  TEMPERATURE

 4.4.1   Introduction^

      The biota comprising an established aquatic ecosystem generally
respond negatively to significant abnormal temperature fluctuations.
Anthropogenic modifications of rivers and streams can alter the thermal
regime, most often by elevating the maximum and mean water temperatures,
Repercussions of elevated temperatures are manifested through a shift
                                  423

-------
in the ecological balance and in the water quality of rivers.  For
example, there is a progression in the predominance of algal species
from diatoms to green algae to blue-green algae as water temperature
increases through a specific range.  Thermal discharges can increase
the ambient temperature enough to alter the predominant species to
the undesirable blue-green algae.  Increased metabolic activity of
aquatic organisms, such as fish, also accompanies elevated tempera-
ture.  If the increase is high enough, the results can be lethal.  Much
data are available today (e.g., Committee on Water Quality Criteria,
1972) which specify lethal  threshold  temperatures  for aquatic organisms.

      Water quality may be  adversely  affected  through  decreased
solubility of dissolved oxygen  and  increased biochemical  reaction
rates.   Adequate  dissolved  oxygen  levels,  particularly at elevated
temperatures,  are critical  because  of the  increased  metabolic acti-
vity.  Yet, as previously discussed the saturation concentration
of dissolved oxygen diminishes  with rising temperature.    Worse still,
is the concurrent low flow condition which is associated, in many
parts of the country, with the warm summer months.  For example, in
a study of 30 river reaches in the U.S. (EPA, 1974), 20 had lower
flows in the summer months than in the winter.  This situation
further reduces assimilative capacity and usually results in the
most critical dissolved oxygen levels over the year.

     Man can alter the thermal regime of rivers by removing  trees,
changing the flow regime, and by increasing thermal discharges.
Diversions of water from a river can reduce the water depth, and
increase the mean and diurnal fluctuation of stream temperature.

      In  Long  Island,  modification  of the  natural  environment of streams
 has  increased  average stream  temperatures during  the  summertime by
 as much  as  9  to  14 F  (Pluhowski,  1968';.   Concurrent temperature
 differences  of as  much  as  14  to  18°F !etueen  sites  on the same stream
 were observed on dtys of high solar radiation.   A principal factor
 involved in these occurrences was the removal of vegetation along the
 banks of the streams, permitting  significantly greater penetration of
 solar radiation.  Other contributing factors cited by Pluhowski
                                 424

-------
included increased  stormwater runoff, a reduction in the amount of
groundwater inflow,  and the introduction of ponds  and lakes.

 4.4.2
      If  a  body of water at a  given  initial  temperature is exposed
 to  a  set of constant meteorological conditions,  it will tend to
 approach some other temperature asymptotically.   It may warm
 by  gaining heat or cool by losing heat.  Theoretically, after a
 long  period of time the temperature will become  constant and
 the net  heat transfer will be zero.  This final  temperature has been
 called the equilibrium temperature, E.  At  equilibrium, the heat
 gained by absorbing solar radiation and long-wave radiation from the
 atmosphere will exactly balance the heat lost  by  back radiation,
 evaporation, and conduction.
      These heat fluxes are illustrated  in Figure  IV- 23  which also
 shows typical ranges for the  fluxes.  Some  of  these terms (Hs>Ha>Hsr>
 H   )  are independent of water temperature,  while  the remainder
 (H, ,H ,H  ) are dependent upon water temperature.  At equilibrium then,
 H   (net  transfer) equals zero, or

              Hs - Hsr + Ha - Har ' Hbr ' Hc ' He = °               (IV'

      In  actuality, the water  temperature rarely  equals the equilibrium
 temperature because the equilibrium temperature  itself is constantly
 changing wit.i the "ocal meteorological  conditions.  The equili-
 brium temperature will rise during  the  day  when  solar radiation is
 greatest,  and fall to a minimum at  night when  solar radiation is absent.

       A daily average equilibrium  temperature may be computed using a
 number  of factors deluding  daily  average  values of radiation, temp-
 erature, wind speed, and vapor pressure.   The daily average value will
 reach a maximum in midsummer and a minimum in midwinter.  Since the
  actual  water  temperature  always  tends  to approach,  but does not  reach
  the  equilibrium  temperature,  it  will  usually  be less  than equilibrium
                                   425

-------
    H   =  Shortwave solar radiation  (400-2800 BTU ft"2 day "*)
       H  = Long wave atmospheric radiation  (2400-3200 BTU ft~2 day"1)
       a
           i
       =Long wave back radiation (2400-3600  BTU ft"2 day"1)
       He =  Evaporative heat loss (2000-8000  BTU ft"2 day"1)
            = Conductive heat loss or gain  (-320-+400 BTU ft"2 day"1)
              .. = Reflected solar (40-200 BTU  ft"2 day"1)
                                                          ?     i
              AHar = AtmosPheric reflection  (70-120 BTU ft   day" )
         NET RATE  AT  WHICH HEAT CROSSES WATER SURFACE
["
     = (H
                   sr
He)  BTU ft"2  day"1
     Absorbed Radiation  (HR)           Temperature  Dependent Terms
     Independent of  Water Temperature
                                      Hbr~ (Ts  +  460)4
                                      Hc ~ (Ts  -  Ta)
                                      He ~ W(es - ea)
  FIGURE  IV-23
                MECHANISMS  OF HEAT TRANSFER ACROSS  A
                WATER  SURFACE (PARKER AND  KRENKEL,  1969)
in the spring when  temperatures are rising, and greater than  equilibrium
in the fall  when  temperatures are dropping.  During a 24 hour period,
the equilibrium temperature usually rises above the actual  water temperature
during the day and  falls  below the water temperature at night, forcing  the
water temperature to  follow a diurnal cycle.
                                 426

-------
      The amplitude of  the actual diurnal water temperature cycle is
 generally dampened significantly in comparison to the amplitude of
 the equilibrium  temperature cycle due to the large heat capacity of
 water.  A thermal  discharge into a water body will  usually increase
 the actual  daily amplitude because of the water temperature dependent
 terms in Equation  IV-57.  This situation is  illustrated in the following
 example  (Edinger, et al., 1968).  Figure IV-24 illustrates a flow through
 cooling  pond  into which a thermal  effluent is  discharged (at Station B).
                              Sta.
                        Sta.G.
                     ,   430
               Sta E  /  ACRES
             Sta. D.
                           Sta.C
         FIGURE IV-24
SCHEMATIC  OF SITE No,  3
COOLING LAKE (FROM  EDINGER,
ET AL,, 1968)
Temperature observations were recorded  at  Stations  B  through H at four-
hour periods for one week.   The findings are depicted  in  Figure  IV-25.
                                  427

-------
        120
                7/18    7/19  '   7/20    7/21    7/22    7/23    7/24
             DAY (4 HOUR PERIODS)
     FIGURE  IV-25
OBSERVED  TEMPERATURES,  SITE No,  3,
JULY 18 - JULY  24,  1965  (EDINGER,
ET AL,, 1968)
The highest temperatures  and largest diurnal temperature  variables are
recorded at Station  B.  The peak temperature at Station B occurs just
after noon, corresponding to the peak loading  from the plant.   At  Station
C the peak temperature  is at 1800 hours,  indicating the lag in flow time
from Stations  B to C.   The peak temperatures at the remaining  stations are
more influenced by meteorological conditions,  and less by the thermal
discharge.  The relationship of the  observed  temperatures to  the
equilibrium temperature over a  24-hour period  is shown in Figure IV-26 .
Note the amplitude of the equilibrium temperature E  (33°F amplitude).
The average equilibrium temperature, E,  is  approximately 91  F.
A progression  from Station  B to Station  H indicates  that the  daily
water temperature tends to  approach  the  average  equilibrium  temperature.
                                428

-------
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-------
           0.05E2    HR - 1801    K -
                                 15.7    [e   -  C(B) + 0.26T 1  /
                                726TB)   L 3                -I  UV'58
where
      E     =   equilibrium temperature,  F
      K     =   thermal exchange coefficient, BID/ ft2/day/°F
      Hp    =   net incoming short (H   ) and long (H  ) wave radiation
      i»             o              S D             an
              BTU/ftVday
      T     =   air temperature, °F
      a
      e,    =   water vapor pressure of ambient air at air temperature,
      a
B    =   proportionality coefficient,  mmHg/°F
              mmHg
              prop
     C(B) =   value dependent on B, mmHg

The thermal exchange coefficient K is expressible as:

              K = 15.7 + (0.26+B) f(u)                           (IV- 59)

where f(u) is a function of wind speed.  Different relationships for
f(u) have been developed.  For purposes of hand calculations, the
following relationship will be used:

                     f(u) - 11. 4u                                (IV-60)

where u is the daily average  wind speed in mph.

     To calculate E using Equation  IV- 58 an iterative procedure is
needed,  since K,  B,  and C(B)  depend  on E.   The following steps outline
a  solution procedure.

     1.   Data needed to start the procedure include:
         T ,  relative  humidity,  wind  speed,  and net shortwave
          d
         solar radiation.  Figure IV-27  illustrates daily average
         solar radiation  reaching the continental  United States
                                 430

-------
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Atlantic Ocean

-------
     for  the  months  July  and  August.   It  is  during  these
     months that  stream temperatures  usually reach  their
     annual maxima.    These values  do  not account for  the
     albedo of  water (the percent of  incoming  solar radiation
     that is  reflected),  but  since  this is  small, it can be
     ignored.   Because of the variability caused by
     topography,  vegetative cover,  and other factors,
     local sources of  information should  be  used when  possible
     for  solar  radiation  values.
2.  Calculate HD = H   + H   (BTU/ft2/day).   If Figure IV-27
               r\    sn    an                                „
    is utilized for H$n, convert from langleys/day to BTU/ft /day
    by multiplying by 3.7.  H   can be estimated from Table IV-23
                             ci n
    by knowing the air temperature and the cloud cover fraction
    (0.1 to 1.0).
3.  Determine e= from Table IV-24 by entering with T  and
               a                                    a
    relative humidity.

4.  Choose an  initial value for  E.  The air  temperature  T
                                                         a
    can be the first guess.

5.  Enter Table IV-25 for B and C(B) at E (°F).

6.  Knowing u, f(u), and B, calculate K from Equation
    IV-59.

7.  From Equation IV-58 make the next estimate of E (E   }
                                                    * new'
    by evaluating the right hand side of that equation
    (call  this result F(E)).
                            432

-------
                                                         TABLE IV-23
                                          NET LONG WAVE ATMOSPHERIC RADIATION,  H
                                                                                 an
co
CO
Cloud
Cover
.1

.2

.3

.4

.5

.6

.7

.8

.9

1.0

Tempera-
ture
(°F)
35
65
35
65
35
65
35
65
35
65
35
65
35
65
35
65
35
65
35
65
Han
(BTU/Sq.
Ft/ Day)
1685
2400
1694
2412
1708
2432
1728
2461
1754
2497
1785
2542
1822
2595
1865
2656
1914
2725
1968
2803
Tempera-
ture
(°F)
40
70
40
70
40
70
40
70
40
70
40
70
40
70
40
70
40
70
40
70
H
an
(BTU/Sq.
Ft/Day)
1790
2540
1799
2553
1814
2575
1835
2605
1863
2644
1896
2691
1936
2747
1981
2812
2033
2885
2091
2967
Tempera-
ture
(°F)
45
75
45
75
45
75
45
75
45
75
45
75
45
75
45
75
45
75
45
75
Han
(BTU/Sq.
Ft/Day)
1900
2688
1910
2701
1926
2724
1949
2756
1978
2797
2013
2847
2055
2907
2103
2975
2158
3053
2220
3139
Tempera-
ture
(°F)
50
80
50
80
50
80
50
80
50
80
50
80
50
80
50
80
50
80
50
80
Han
(BTU/Sq.
Ft/ Day)
2016
2842
2026
2857
2043
2881
2067
2914
2098
2958
2136
3011
2180
3074
2232
3146
2290
3228
2355
3320
Tempera-
ture
(°F)
55
85
55
85
55
85
55
85
55
85
55
85
55
85
55
85
55
85
55
85
Han
(BTU/Sq.
Ft/Day)
2138
3004
2149
3019
2167
3045
2192
3080
2225
3126
2265
3182
2312
3249
2366
3325
2428
3412
2497
3509
Tempera-
ture
(°F)
60
90
60
90
60
90
60
90
60
90
60
90
60
90
60
90
60
90
60
90
H
an
(BTU/Sq.
Ft/ Day)
2266
3173
2277
3190
2296
3216
2323
3254
2358
3303
2400
3362
2450
3432
2508
3513
2573
3604
2646
3707

-------
                                                    TABLE IV-24
                         WATER  VAPOR  PRESSURE  (mmHg)  VERSUS  AIR  TEMPERATURE,  T ,  AND RELATIVE HUMIDITY
                                                                              a
CO
-P*
Ta
<°F)
35
40
45
50
55
60
65
70
75
80
85
90
95
100
es*
(mmHg)
5.2
6.3
7.6
9.1
11.0
13.1
15.6
18.6
22.0
26.0
30.5
35.8
41.8
48.7

0.1
0.5
0.6
0.8
0.9
1.1
1.3
1.6
1.9
2.2
2.6
3.1
3.6
4.2
4.9

0.2
1.0
1.3
1.5
1.8
2.2
2.6
3.1
3.7
4.4
5.2
6.1
7.2
8.4
9.7

0.3
1.6
1.9
2.3
2.7
3.3
3.9
4.7
5.6
6.6
7.8
9.2
10.7
12.5
14.6
R E L
0.4
2.1
2.5
3.0
3.6
4.4
5.2
6.2
7.4
8.8
10.4
12.2
14.3
16.7
19.5
A T I V E
0.5
2.6
3.2
3.8
4.6
5.5
6.6
7.8
9.3
11.0
13.0
15.3
17.9
20.9
24.4
H U M I
0.6
3.1
3.8
4.6
5.5
6.6
7.9
9.4
11.2
13.2
15.6
18.3
21.5
25.1
29.2
D I T Y
0.7
3.6
4.4
5.3
6.4
7.7
9.2
10.9
13.0
15.4
18.2
21.4
25.1
29.3
34.1

0.8
4.2
5.0
6.1
7.3
8.8
10.5
12.5
14.9
17.6
20.8
24.4
28.6
33.4
39.0

0.9
4.7
5.7
6.8
8.2
9.9
11.8
14.0
16.7
19.8
23.4
27.5
32.2
37.6
43.8

1.0
5.2
6.3
7.6
9.1
11.0
13.1
15.6
18.6
22.0
26.0
30.5
35.8
41.8
48.7
          * e  = saturated vapor pressure

-------
             TABLE IV-25
B AND C(B) AS FUNCTIONS OF TEMPERATURE
Temperature
(°F)
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
B
(mmHq/ F)
.286
.296
.306
.317
.328
.340
.352
.365
.378
.391
.405
.419
.433
.448
.464
.479
.496
.512
.529
.547
.564
.583
.601
.620
.640
C(B)
(mmHg)
-5.5
-4.5
-4.1
-4.2
-4.6
-5.4
-6.3
-7.5
-8.7
-10.0
-11.2
-12.5
-13.6
-14.7
-15.8
-16.7
-17.6
-18.3
-19.0
-19.6
-20.1
-20.7
-21.2
-21.7
-22.3
Temperature
(°F)
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
B
(mmHg/0F)
.660
.680
.701
.722
.743
.765
.787
.810
.833
.857
.881
.905
.930
.955
.980
1 .006
1 .033
1.060
1.087
1.114
1.142
1.171
1.200
1.229
1.259
C(B)
(mmHg)
-22.9
-23.6
-24.4
-25.4
-26.5
-27.8
-29.3
-31.0
-33.0
-35.1
-37.6
-40.3
-43.2
-46.4
-49.7
-53.3
-57.1
-61 .0
-64.9
-68.9
-72.9
-76.7
-80.4
-83.8
-86.8
                         95
1 .289
-89.3
                   435

-------
       8.   The next  estimate of E is:

                            Enew=0.3E+0.7F(E)
           (Note:  this  choice  of E     brings  about  a more
            rapid  convergence to  the answer  than would use
            of E alone).
       9-   If  lE-  EUlF,  then  E   ,  , = E    .
              1        '     '       actual    new
           If  |E    - -E  >1  F,  return to step 5 with EnQi and
                new
                                                   new
           repeat the  procedure  until the convergence criterion
           is met, namely,  Eactufl1 = Enew.

      Instantaneous, daily  average, v.-eekly  average,  or even  longer
 term  average equilibrium temperature, F, can  be calculated  by
 usina mean meteorological  conditions over  the  period of  interest
 and following  the solution procedure just outlined.  Cal-
 culating the daily average E under the most crucial
 annual meteorological conditions (usually occurring in July or
 August) yields the highest temperature about which that water body
. tends to  naturally oscillate.  The repercussions of man's activities
 in terms of altering E can thus be estimated  and analyzed  for potential
 impact.
                               EXAMPLE IV-10
                  Calculation of Equilibrium Temperature

      On Long Island,  New York,  studies done by Pluhowski  (1968)  have
 indicated that shading of streams by a natural vegetative canopy
 can drastically affect the shortwave solar radiation reaching those
 streams.  The results of some of his findings are presented in
 Table IV-26.  In the  summer, when leaves are on the trees, the
 actual  solar radiation reaching the Connetquot River can  be as low
 as 29%  of that reaching unobstructed sites at nearby Mineola or
 Brookhaven.
                                    436

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                                                       TABLE IV-26


                                             SUMMARY OF SOLAR-RADIATION DATA
                                 FOR MIMEOLA, BROQKHAVEN, AND THE CONNETQUOT RIVER SITES
GO
Mean-Daily Solar Radiation in Langleys:
for the Indicated Periods

Solar
Site
(1)
1
2
3
1

2
3
1
2
3
1
2
3
1




Jan.
Jan.
Jan.
Apr.
Apr.
Apr.
Apr.
June
June
June
Aug.
Aug.
Aug.
Nov.


Dates
(2)
30, 31
28, 29
25, 26
21-23,
16-18,
19, 20
24-26,
9-11,
7, 8,
12-14,
26-28,
22-24,
29, 30
28, 29




, 1967
, 1967
, 1967
1967
1968
, 1967
1967
1967
1967
1967
1967
1967
, 1967
, 1967


Mineola
(3)
235
148
135
466
452
436
408
600
664
527
275
277
504
204


Brookhaven
(4)
244
130
135
464
502
386
411
599
671
523
260
328
484
-
Connetquot
River
Estimated
(5)
240
137
135
465
502
429
410
599
669
525
266
308
492
204
Connetquot
River
Observed
(6)
148
96
104
343
389
384
401
254
531
443
78
162
338
86
Ratio=
Connetquot River
Observed
Connetquot
River
Unobstructed
(7)
0.62
.70
.77
.74
.77
.90
.98
.42
.79
.84
.29
.53
.69
.42
              Note 1  - Radiation data  in  column  5  are  estimated  unobstructed  horizon  values  for  Connetquot River
                       based on data  from Mineola  and  Brookhaven (cols.  3,4).

              Note 2  - Solar site 1  is  typically heavily  forested,  solar site  2  is  moderately  to heavily forested,
                       and solar site  3 is moderately  forested.

-------
     Suppose the user is interested in predicting how the  removal  of
the riparian vegetative cover might effect E.   Consider the  period
22-24 August, 1967, when the Connetquot River  received 162 langleys/
day of a possible 308 langleys/day of whortwave solar radiation.
Representative meteorological  conditions at this time were:


                    T  * 65°F
                     a
                    u  = 2 mph
                    cloud cover fraction = 0.5
                    relative humidity = 80%

     The steps in solving for E are as follows:

        1.   Data have been gathered,  as previously listed.

        2.   H$n = 162 (3.7)  =  600  BTU/ft2/day.   This value
            assumes that the vegetative canopy blocks 47%  of the
            solar radiation.  From Table IV-23, H   is
            (.5 cloud cover  at 65°F)  2497 BTU/ ft /day.  Thus,
                  HR  =  2497  +  600  -  3097  BTU/ ft2/day.
        3.   At 80% relative  humidity  and  an  air  temperature
            of 65°F,  e   =12.5  mmHg   from Table  IV-24.
                     a

        4.   As an  initial  guess of  E,  assume E-,  =  65°F,
            the air temperature.

        5.   From Table  IV-25, B =  .56,  C(B)  =  -20.1

        6.   K = 15.7  +  (.26  + .56)  (11.4)  (2)  =  34.4
                               438

-------
          7.   F(E1 )  = -0.05(65)2   3098-1801    34.4-15.7
                          34.4        34.4     34.41. 26+. 56)

              X [l2.5 + 20.1  + .26(65)1  - -6.1  + 37.7 + 33.0 = 64.6

          8.   E  -  .3(65)  + .7(64.6)  = 64.7
          9.   Since |E2-E1  <1°F
       Now suppose the user wants to find E for no reduction in H   due
  to shading.   Steps 1 through 9 again are repeated, using H   =
                        r\                                   J M
  308(3.7) - 1140 BTU/ft /day, with otherwise the same meteorological
  conditions.   Without detailing the calculations here, it is found that
  F = 73.7°, a 9°F increase.
      It is evident  then  that  altering  the  solar  radiation  penetrating
 to the stream can significantly  change  E.   Even  more  severe  cases  of
 repression of shortwave  radiation  (as  noted by the  71%  reduction on
 26-28 August, 1967, Table  IV-26) are possible, exemplifying  the
 large differences which  may be observed.
                            END OF EXAMPLE IV-10
     The approach illustrated in Example  IV-10  for  predicting  equilibrium
temperature is obviously time consuming,  and  has  been  programmed  for  hand
held calculators in  Mills eta/U (1979)  .  A simplified  approach  is  also
available for predicting equilibrium temperature  (Brady £t ji^., 1969)  and  is
described below.  The predictions are usually within 3°F  or  less  of those
found by the more complicated approach.
     The data required for the simpler approach  are:
     t   T,, dewpoint temperature (°F)
     •   U, mean daily wind speed (mph),  and
     •   Hsn, net incoming shortwave radiation  (Btu/ft2/day)
                                 439

-------
Short wave solar radiation data were previously  shown  in  Figure  IV-27.   The
climatic atlas  (U.S. Department of Commerce,  1968)  contains  compilations of
dewpoint temperature and windspeed.  Figures  IV-28  and IV-29 show these data
for the months  of July  and August.  Figures  IV-27 through IV-29  provide the
user with all the data  needed to predict  equilibrium temperature using
Brady et^ a! 's approach.

     To find the equilibrium^temperature  the  following equations are applied
sequentially:
         COMPUTE ONCE
                                F(U)  -  70 + 0.7 U2
       ITERATE OVER
       THESE EQUATIONS
                                      (IV-61)

                                      (IV-62)

B     =  0,255 - 0.0085T + 0.000204T2    (IV-63)

K     =  15.7 + (B + .26) F(U)         (IV-64)

Ei+l  =  TD + Hs ' K                   (IV-65)
The wind speed function f(U) is found once from Equation  IV-61.   The
dewpoint temperature (Td) is a convenient starting choice as  an  initial
guess of the equilibrium temperature.  T can then be calculated  from
Equation IV-62;  B from Equation IV-63;  K from Equation  IV-64;   and  finally
a new equilibrium temperature (E-j+i) from Equation IV-65.   If
                     °
                                                                  and  E-+1
differ by more than 1F, return to Equation IV-62 with Ei+1 and repeat  the
procedure until convergence is attained (usually within 2 or 3 cycles).
                                     440

-------
     504Q
JULY
                                                          55
                                                           65
                                                      •75
                          AUGUST
                                                  75--75
FIGURE IV-28  MEAN  DEWPOI&T TEMPERATURE (°F) THROUGHOUT  THE
              UNITED  STATES FOR JULY AND AUGUST  (U,S,  DEPART-
              MENT  OF COMMERCE, 1968)
                              441

-------
                           JULY
                          AUGUST
FIGURE IV-29  MEAN DAILY WIND SPEEDS (MPH) THROUGHOUT THE
              UNITED STATES FOR JULY AND AUGUST (U,S, DEPARTMENT
              OF COMMERCE, 1968)
                              442

-------
                               EXAMPLE IV-11
             Equilibrium Temperature using Simplified Approach

     Determine the average daily surface water equilibrium temperature for
Little Rock, Arkansas during the month of August.  Based on Figures IV-27
through IV-29 the following data are found:

     Td  =  68°F
     U   =  7 mph
     Hsn =  (525)(3.7) = 1943 Btu/ft2/day

Assume as a first guess That E = Td = 68°F

then
     f(U)  =  70 + .7 (7)2 = 104.
     T     =  (Td + Td)/2 = 68°
     B     =  .62
     K     =  15.7 + (.62 + .26) (104) = 107.
     E     =  68 + 1943/107 = 86°F

For the second interation

     T  =  (86 + 68)/2 = 77
     B  =  0.81
     K  =  127
     E  =  83.3°F

At the end of a third interation E = 83.7 F, so convergence has been
attained by three interations.
                                    443

-------
     As a comparison, the equilibrium temperature will also be calculated
using the longer approach.  The required data are:
     Tg   =  80°F
     T,   =  68°F
Hsn  =  1943
          =  7.
          =  19
     sky cover  =  0.5 (from climatic atlas)

A summary of the procedure is:

     1.  Han  =  2958
         HR   =  1943 + 2958 = 4901

     2.  Since Td  =  68°, e  = 17.4

     3.  Choose E  =  T   =  80°F
                       a

     4.  B     =  .881
         C(B)  =  -37.6

     5.  f(U)  =  70 + 0.7 (7)2  = 104
         K     =  15.7 + (0.26 + .881) (104) = 134

     6.  F(E)  =  79.3

     7.  E  =  .3(80)+ .7 (79.3) = 80°F, after one pass.

Since the starting guess of 80°F is virtually identical with the calculated
value at step 7, a second interation is not required.  The two procedures
predict equilibrium temperatures which differ by about 4°F.
                            END OF EXAMPLE IV-11
     To estimate the effects of shading, the incoming solar radiation should
be calculated first assuming no shading, but otherwise using existing
meteorological conditions for the time of the year of interest.  The effects
                                    444

-------
of shading should be superimposed upon this result as a percent reduction.
The following (Pluhowski, 1968) can serve as guidelines in estimating solar
radiation reduction:

     •   0-25 percent reduction:  shading generally restricted to early
         morning and late afternoon

     •   25-50 percent reduction:  some sunshine penetration in morning
         and evening.  Considerable sunshine between 1000 and 1400
         hours.

     •   50-75 percent reduction:  very little sunshine penetration  in
         morning or  late afternoon.  Some sunshine between 1000 and
         1400 hours.

     t   Greater than 75 percent reduction:  very little penetration
         even at noon.
4.4.4  Screening of Thermal Discharges

4.4.4.1   Introduction

     This  section presents a  set of procedures which can be used to
determine  whether the thermal discharge  at a proposed power plant  site or
the discharge from the expansion of an existing site is  likely to  violate
thermal standards.  Procedures are presented to test for contravention of
the following types of standards:

     •    The AT Criterion:  The increase  in temperature  of water
          passing through the  condenser must not exceed a specified
          maximum.

     •    The Maximum Discharge Temperature Criterion:  The temperature
          of the heated effluent must  not  exceed a  specified maximum.
                                   445

-------
     •   The Thermal  Block Criterion:   The cross-sectional  area of a
         river occupied by temperatures greater than a specified value
         must not exceed a specified percentage of the total area.

     •   The Surface Area Criterion:  The surface area covered by
         isotherms exceeding a specified temperature increment (above
         ambient) must not exceed a specified maximum.

Actual values associated with the above standards vary by political
jurisdiction.  Accordingly, regulations must be consulted.

     The thermal discharge screening procedures are designed to address the
following questions:

     •   Is the power plant, as proposed, acceptable at the candidate
         location?

     t   What is the largest power plant that can be placed at the
         candidate location?  Equivalently, can an existing power plant
         at the candidate location be expanded?

     The methods do not analyze interactions among multiple powerplants on
the same river.  Such an analysis can be rather more complex.  A report by
Tetra Tech  (1978) addresses that question.

     The methods developed to evaluate instream thermal criteria use heat
balance equations assuming a steady-state, well mixed system at low flow.
The power plants are assumed to employ once through cooling, as shown in
Figure IV-30.
                                  446

-------
Intake Channel — —— -»*

^
WR
X,
-^
A
t
Qo/^
Qr 	 ^
,
Ti
1

Power _ _ A_
Plant T0=Tj+AT

t
^___ ___ Outlet
*~~~ Channel
Skimmer Wall 1


1
River |A


                                   PLAN VIEW

         FIGURE  IV-30      IDEALIZATION OF  A RUN-OF-THE-RIVER
                              POWER  PLANT
     The selection of well  mixed  conditions  appears to be justified.
Studies by Stefan and Gulliver  (1978)  on  the Mississippi and Missouri Rivers
have dealt with the lateral  mixing  of  thermal plumes which were released at
the shoreline and were not  initially well mixed across the river.  The
investigators found that over a short  distance, thermal losses were
negligible and that the well mixed  isotherm  (the isotherm that would result
were the plume initially well mixed laterally and vertically) eventually
extended across nearly the  entire width of the river, albeit at some
distance downstream.   This  indicates that if the thermal block criterion is
not met for the well  mixed  case,  it is not likely to be met for the
shoreline discharge either.  A  similar conclusion can be reached regarding
the surface area constraint.  Thus, at this  level of analysis, it is not
necessary to consider the consequence  of  incomplete lateral or vertical
mixing adjacent to the shoreline  discharge.

     One simplification which can be used at the option of the user for the
surface area calculation should be  mentioned.  Surface water that is
undisturbed by anthropogenic influences (in  a thermal sense) approaches the
equilibrium temperature. This  temperature is dictated by natural
meteorological conditions.   Surface water temperature in rivers, especially
during steady low-flow periods, can be near  equilibrium.  In calculating the
                                    447

-------
surface area occupied by isotherms exceeding a specified temperature it is
necessary to know the equilibrium temperature.  However, since the procedure
for calculating equilibrium temperature is fairly complicated, considerable
savings in computational effort can be obtained by assuming the ambient
water is at its equilibrium temperature.

     Some circumstances, in addition to anthropogenic influences, tend to
produce ambient temperatures different from equilibrium.  For example,

     •   Locally, large quantities of groundwater may discharge into
         the river.

     •   Hypolimnionic releases from large reservoirs may occur nearby.

     •   Snow melt may supply a substantial amount of inflow.

As a result of the first two influences, the stream water temperature may be
lower than equilibrium since the source of the water comprising the stream
flow has been shielded from the heating effect of solar radiation.  Snow
melt, although not likely to influence the river's thermal regime during the
late summer, can be important through spring and into early summer in areas
where high-mountain snowpack exists over most, or all, of the year.

     The screening procedure that follows assumes the river water, once it
has been heated by the thermal plume, is above equilibrium.  This means that
the water temperature will  then decrease in the downstream direction, which
is generally, but not always, true.

     Table IV-27 shows the data needed to apply the thermal screening
methods.  The symbols are defined in the table and suggested default values
are given for variables where appropriate.  The variables are introduced in
the table in the order they occur in the screening procedure.
                                     448

-------
                           TABLE  IV-27

          DATA NEEDED FOR  THERMAL DISCHARGE SCREENING
 Variable
          Term Definition
Default Value
   Mwe
AT,
  max!
AT
  max2
  maxmin
 Capacity  of power  plant  in
 megawatts electric (bus  bar)

 Percent of total energy  pro-
 duced  that goes to electricity
 production

 Percent of total energy  produced
 that is dissipated through the
 cooling water

 River-flow rate above power
 plant  (nr/s)

 Mass density of water
 (kg/mi)

 Specific  heat of water
 (Btu/DF-kg)

 Temperature rise in the  river
 cross  section that constitutes
 a thermal  block (°F)

 Maximum legal allowable  tempera-
 ture rise  across the condenser (°F)

 Maximum allowable  temperature
 rise across the condenser such
 that T  <  (T )     (°F)
      e    v e'max  v  '

Temperature of heated effluent (°F)

Maximum legal allowable tempera-
ture of heated effluent  (°F)

The lesser of ATm  , and

«»»*  <°F>
            The maximum  allowable flow rate
            through the  cooling system
             (m3/s)
                                                 new  fossil fuel
                                                 plants:38
                                                 nuclear plants:32

                                                 new  fossil fuel
                                                 plants:48
                                                 nuclear plants:68
    1000


    2.2


    5



   20
                                           .25Q,
                        449

-------
                   TABLE IV-27 (continued)
Variable
                  Term Definition
                                      Default Value
  AT



   V


   d


   E

   K
sa
  A
   sa
   W
   ra
The isotherm defining the boundary
of the surface area for which legal
limits have been established (°F)

Mean velocity of the river
(ra/s)

Mean hydraulic depth of river in
reach under consideration (m)

Equilibrium temperature l°F)

Surface thermal transfer coeffi-
cient (Btu/d • °F • m2)

         Surface area of river down to AT
         isotherm (m2)

         Legal maximum surface area limit
         which can be covered by the AT
         and greater isotherms (m2)

         Average surface width of river
         down to AT,, isotherm (m)
                   Sa

         River temperature just above where
         a tributary joins the mainstern
             Temperature of tributary (°F)

             Flow rate of tributary  (m^/s)

             Air Temperature (°F)
Relative
humidity
    sn
   an
         Wind speed at 7 meters above
         surface (m/s)

         Net shortwave solar radiation
         (Btu/m2 • d)

         Net long wave solar radiation
         (Btu/m2 • d)
                             450

-------
4.4.4.2  Evaluating the Thermal Block Criterion

     The initial temperature elevation that results when the thermal plume
becomes well mixed with the river water is given as:

                              T                                      (IV-66)

                        = J_ . !c MW   . J_ .  3.414 x  106            (IV-67)
                          Qr   epMWe   PCp    —mt
where
     ATwm  =  temperature elevation of the initially well mixed
              isotherm ( F)
     Q     =  flowrate of cooling water (m3/s)
     AT    =  Te - Tr (°F)
     T£    =  temperature of heated effluent (°F)
     Tr    =  temperature of river water upstream of power plant (°F)

All other terms are defined in Table IV-27.  To find AT  , Equation IV-67 is
                                                       wm
solved.  If ATwm is less than the thermal  block temperature increment
(ATtb), the thermal block criterion is not contravened.  Otherwise, it is.
4.4.4.3  Acceptability of the Temperature Rise Across the Condenser
         and of the Temperature of the Heated Effluent

     Whether these criteria are met or not depends on a number of factors,
such as the cooling water flow rate.  Since the cooling water flow rate can
be designed to be within a specified range, it is determined here whether a
feasible range exists such that the two above mentioned criteria are met.

     The minimum acceptable flow rate such that both temperature criteria do
not exceed their standards is as follows:

              m \      6c   MU«         1         3.414  x  106
              
-------
where
     (Q )  .   =  minimum flow rate such that the two temperature
       p mm
                 criteria are not exceeded (m3/s)
By evaluating Equation IV-68 the minimum cooling water flow can be
determined.
     As an example of how AT     .   is chosen, suppose the following
                            maxnnn
conditions exist:
     •   The maximum legal temperature rise across the condenser is
         20°F.

     •   The maximum legal temperature of the heated effluent is 86°F.

     t   The ambient river temperature is 74 F.

From these conditions, ATmax2   (the allowable temperature increase across
the condenser such that the temperature of the effluent does not exceed the
legal maximum) = 86°F - 74°F = 12°F.  So AT.   = minimum (20°F, 12°F) =
                                           11 id AIM III
12°F.  12°F must be chosen, then, as the maximal temperature rise across the
condenser.
     Once Equation  IV-68 has been solved, the ratio of cooling water to
river flow should be checked so that the value is within acceptable limits.
Equation IV-66 can  be rewritten as:

                                  Q«   AT
                                  JB. =   wm                          (IV-69)
                                  Qr    AT

Since AT    has been calculated from Equation IV-67 and AT has been
         wm
calculated as AT     . , the flow rate fraction can be calculated from
Equation IV-69.  If this fraction exceeds a certain percent (e.g. 25 percent
or some  user defined value), then the cooling water flow rate is too large
to be acceptable.   If the flow rate fraction is not excessive, the actual
flow rate can be chosen so that:
                                     452

-------
                           (Q )m.n ±Q  ± (Qp)max                    (IV-70)

where
     (Q )max  =  maximum allowable cooling water flow rate (m3/s)


4.4.4.4  Evaluating the Surface Area Constraint

     The evaluation of this criterion may require the user to perform
considerably more calculations than for any of the other prescreening
criteria.  The two major complicating factors that are encountered are:
1.  determining the river equilibrium temperature, and 2.  evaluating the
effects of tributaries.

     If it is the case that ATwm does not exceed ATsa the surface area
criterion will not be contravened and no calculations have to be performed.
If ATwm exceeds ATsa, the criterion might be exceeded.  In this case it is
necessary to determine the distance from the location of the thermal
discharge to the downstream location of the AT$a isotherm.  This distance is
given by:
                          -pC  Vd      /T   -  E\
                   x   = —^__ in   ( T   _  E 1  24-  3600            (IV-71)
                                     \  wm    /
where
     Tsa  =  ATsa + Tr
      wm  ~    wm    r

Section 4.4.3 discusses procedures for predicting K and E.  Once K and E are
found,  xsa can be determined from Equation IV-71.  If one or more tributaries
exist with the distance x,. then x „ should be recalculated as discussed
                         sa        sa
in Section 4.4.4.5.

      The surface area included within this  reach is:

                                 A = xsa ' W                          (IV-72)
                                   453

-------
where
     A  =  surface area of the river from the point of thermal
           discharge to x   (m2)
     W  =  average river width in this reach (m)

If A < A   then the surface area criterion is not contravened.  Otherwise,
        sa
it is.
4.4.4.5  Evaluating the Effects of a Tributary in Mitigating Temperature
         Within a Thermal Plume

     Tributaries, when they join a river subjected to the influences of a
thermal plume, generally act to reduce the elevated river temperature.  They
may therefore prevent the surface area constraint from being exceeded when
it otherwise would.

     Equation IV-71 assumes no tributaries exist throughout the reach
defined by x  .  If it is found that x   > x, (x . is defined below under
             S cl                         S a     L    L
Equation IV-73) then it is necessary to examine the impact of the tributary
flow on the surface area constraint.  This is done by computing the water
temperature (°F) just above the location where the tributary joins the
mainstream using the following equation:
                    =  (Twm " E) exP (^C"Vd ~*ll • 360o)
                Tra

where
     T    =  river temperature just upstream of tributary ( F)
      1T3
     x    =  distance from power plant discharge to tributary (m)

After the river has mixed with the tributary the new river temperature ( F)
is given by:

                          (r\     - TraQr + TtQt                    (IV-74)
                          V rl new     0+0,.
                                     454

-------
where
     T.   =  temperature of the tributary (  F)
     Qt  =  flow rate of tributary (m3/s)

If

                               I     <  AT   + T                       (IV-7b)
                              •i  new —   sa    ra                     v

then this location marks the downstream  location of the ATga isotherm and
the surface area A can be calculated using the distance x$a as the distance
down to the tributary, xt.  Otherwise the ATsa isotherm is located further
downstream.  In this case Equation IV-71 is reapplied (first making
appropriate adjustments to V and d) where the initial temperature is
(Tr)new (which was Twm in Equation IV-71) and the final temperature is still
T ,.  The distance xpa is determined by  adding this additional distance to
 S a                 S a
xt-
4.4.4.6  Determining Whether the Thermal Block or the Surface Area
         Constraint is the More Limiting

     One of these two constraints may cause a greater limitation on power
plant size than the other.  If ATtb < AT$a the thermal block constraint will
be more limiting, and there is no need to continue with the analysis in this
part.  If, however, ATtb > ATsa, the surface area constraint may be more
limiting.  To determine if it is, find ATwm (call it ATwmsa) using the
following equation:

                         I  '     \       I      "KXsa       \
           ATwmsa = E  +   Tsa - E    exP   ,X-Vd^-24T3600   " Tr   (IV-76)
                         \        /       \   P              /
where

                                T$a  - AT   + T                       (IV-77)

and
                                        A
                                  x    =  -ii                          (IV-78)
                                   455

-------
If a tributary exists in the reach delineated by x  , recompute x   as
                                                  S3             S d
outlined in Section 4.4.4.5.



     If ATwmsg < ATtb, the surface area constraint  is more restrictive, so

set ATwm =   ATwmsa-  Otherwise set ATwm = ATtb.
4.4.4.7  Determining the Maximum Plant Capacity


     The maximum power plant capacity can be determined based upon the

maximum well mixed temperature elevation and the river flow rate.  It is

given by:
                    )max = e  ' pCo ' (VT)max -    —          (IV'79)
                     max   ec     p     p   max ^414 x 1Q6


                         = -£ • pC  -AT  Q  • ---- 360°             (IV-80)
                           6c     P     ™r   3.4.4 x  10*

By using Equation IV-80 and the maximum allowable AT  , the maximum capacity
                                                    Will
can be found.
4.4.4.8  Readjusting the Maximum Cooling Water Flow Rate


     If the minimum acceptable flow rate is greater than the maximum

allowable, the power plant size must be reduced.  To do this, set
where

     Qp       =  actual cooling water flow rate (m3/s)

     (Q )max  =  maximum allowable cooling water flow rate (m3/s)


AT   is recalculated by:
  WIN
(Note:  the surface area and thermal  block constraints are still  met and
need not be recomputed.)
                                  456

-------
                          AT   = AT     .    Rmax                    (iv-82)
                            wm     maxmin
where
     AT     .  is the same AT calculated earlier.
       maxim n
                               EXAMPLE IV-12
           Estimating AT Across a Power Plant Heat Exchange Unit

     Suppose the user wants to determine AT for the Hartford Electric Light
Company's South Meadow Steam Electric Power Plant (a fossil fuel plant)
located on the Connecticut River.  Data available are (Jones et aj_. , 1975):

          capacity ................... 217 MW
          cooling water flow rate  ........... 341 ftVsec
          waste heat discharged to cooling water .... 422 MW

Since the waste heat being dissipated through the cooling water is known, AT
can be calculated directly using that value in conjunction with the known
flow rate.  Assume, however, that the waste heat being discharged is not
known.  It can be estimated from the plant capacity as follows.  First,
assume the plant efficiency is 33 percent.  The rate at which fuel is burned
when at capacity is then:

                                  =  658 MW
If 10 percent of the total energy is lost up the stacks, then approximately
58 percent is dissipated through the cooling water, or

                            658 (.58)  =  382 MW

Compared with the known 422 MW of heat discharged to the cooling water, the
above calculation would underestimate AT.
                                    457

-------
     AT is calculated by

        AT    thermal  loading  rate  to  coolin£j^aj^-jjjrg3awa.tts.
                       ft  4i/n/in6  BTU   Vl  hr
                                   hr73600
where
     YC   =62.4 BTU/ft3/°F
     Q0   =  flow rate, ftVsec


Substituting the appropriate values into the above equation, it is found
that (using the known thermal loading to the cooling water):
                            >  (3.414)  (106)/3600  _
                                          L - .  -
                   AT  -
                   AT
Equation IV-83 is not feasible to use when the thermal loading rate to the
cooling water is unknown.  As an alternative approach, the following
expression can be employed:
                   AT = -_L . _^. Mue .   '  . J.tiH x  ID               (TV-84}
                        Qo   ep       PCp        3600-              (IV84)

where
     e   =  percent of total energy produced that is transmitted as

            electricity.  For new fossil fuel plants:  38 percent:  for
            nuclear plants:  32 percent.


     e_  =  percent of total energy produced that is dissipated through
       \f
            cooling water.  For new fossil fuel plants:  48 percent;
            for nuclear plants:  68 percent


     MWe =  capacity of power plant in megawatts electric


Equation IV-84 predicts that AT is


                 1  . 58  .017    '  . 3 • 414    10   _   -17 cor
                341   32       62.4       3600
                                   458

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AT is only about 1°F less than predicted by Equation IV-83.

	END OF EXAMPLE IV-12	
4.4.5  Longitudinal Temperature Variation

     If the temperature at a particular location in a river is known,  the
steady-state temperature distribution downstream from that point can be
estimated by:
                          T  -  E         /-.061 •  Kx \                  /TW oc^
                          =!	V = exo  I	r^-rn	                   (Iv-85)
where
     T   =  temperature at x = 0, °F
      m                                                             .
     T   =  stream temperature at a distance x, where x is measured in
            miles
     E   =  equilibrium temperature,  F
     K   =  thermal transfer coefficient, BTU/ft2/day/°F
     U   =  stream velocity, ft/sec
     d   =  stream depth, feet
     p   =  water density, lb/ft3
     Cp  =  heat capacity of water, BTU/lb/°F  (pCp = 62.4 BTU/ftV°F)

     An important fact is revealed upon inspection of Equation IV-85.
Suppose that a thermal discharge heats the ambient water to a temperature
Tm, but Tm is less than the instantaneous equilibrium temperature E.  In
that instance the stream temperature will continue to rise exponentially
downstream, approaching E.  The rate at which T approaches E is dependent on
the thermal transfer coefficient, as well as stream velocity and depth.
Equation IV-66 is graphically illustrated in Figure IV-31.
                                    459

-------
                          r -
                              Kx
                             pcpdU
FIGURE IV-31     DOWNSTREAM TEMPERATURE  PROFILE  FOR  COMPLETELY
                 MIXED STREAM., T-E/T -E  vs,  r  (FROM  EDINGER,
                 1965)
                           460

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                               EXAMPLE IV-13
                            Use of Figure IV-31

     Suppose an average daily thermal transfer coefficient, K, of 200
BTU/ft2/day has been calculated.  The river of interest has an initial
temperature "excess" (i.e. Tm-E>0).  How far downstream will that excess be
50 percent of the original?  Other stream data:

     U    =    .5 fps
     d    =   4   feet
     pC   =  62.4 BTU/ft3/°F

From Figure IV-31, r is to be found such that
                                 V  E
The correct r equals 0.68.  Solving for x in terms of r it is found:
                     roC  dU    (0.68)  (62.4)  (4)  (.5)(24)(3600)
                x =
                                             200
                  =  3.6  x  104  feet  =  6.9 miles

The associated travel time is T = U>-XlQ_  x   I   hr = 2o.4  hours
                                      .b       jouU
                            END OF EXAMPLE IV-13
4.4.6  Diurnal Temperature Variation

     Although it is beyond the scope of this report to analyze diurnal
stream temperature variations, a few brief statements should be made.
Diurnal stream temperature variations on Long Island, New York, were
mentioned in Section 4.4.1.  Documentation of large diurnal temperature
variations is not limited to New York.  For example, studies in Oregon
(Brown, 1969), Hawaii (Hathaway, 1978) and California (Mills, 1979)  have
revealed that solar radiation entering shallow streams and rivers produces a
                                   461

-------
significant difference between maximum and minimum daily temperatures.
Figure IV-32 shows one such example on the Santa Ana River near Mentone,
California (Mills, 1979).  The water temperature varied by 17°F over a
period of 24 hours.  One significant effect of the temperature variation is
its effect on dissolved oxygen levels.  Figure IV-33 shows the measured
dissolved oxygen concentrations and predicted saturation levels over the
same time period at the same location on the Santa Ana River.  The dissolved
oxygen concentrations ranged from a high of 9.2 mg/1 to a low of 8.0 mg/1.
The variations were caused predominantly by the temperature changes.  This
illustrates several points.

     •   Temperature data concomitant with dissolved oxygen data might
         be needed to properly interpret the cause of dissolved oxygen
         variations in shallow rivers receiving large amounts of solar
         radiation.

     t   Removing riparian vegetation around shallow rivers tends to
         increase the daily maximum temperature and decrease the daily
         minimum temperature.

     •   Impacts on the dissolved oxygen levels and indigenous biota
         can be significant.
4.4.7 Low Flow and Temperature

     Evidence has previously been cited in this chapter to show that in many
parts of the country high temperature conditions are concomitant with low
flow.  The planner needs to be able to quantify better the nebulous term
"low flow" to fruitfully use this concept as a planning tool.   For example,
suppose a decision is made based on the low flow condition of  this year.
What are the chances that this low flow will be exceeded in the future?  If
they are high, then any decision (e.g. at particular level of  waste
abatement at a sewage treatment plant) based on the observed conditions
could have unexpected deleterious results at a future time.  It is paramount
then, to predict how often flow will fall below a specified rate.
                                  462

-------
o
Ul
CC
cc
Ui
a.
5
HI
h-
90


85

80


75

70


65

60

55


50
1
— I 	 I 	 1 	 I
KEY
                                            Air Temperature
                                            Water Temperature
      1040
      6/19
                                            _L
                                                _L
          1440
1840
2240
                   0240
                   6/20
TIME OF DAY (Military Time)
                                                    0640
                                                        1040
 FIGURE IV-32
             MEASURED  AIR AND WATER TEMPERATURES FOR
             THE SANTA ANA RIVER  NEAR MENTONE, CALIFORNIA,
             IN JUNE 1979,
                              463

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    10.0

    9.8

    9.6

    9.4

    9.2
     KEY
     Observed DO
     Saturation, Cs
      1040     1440      1840      2240     0240
      6/1f                                6/20
                       TIME OF DAY (Military Time)
                                   0640
1040
FIGURE  IV-33
MEASURED  DISSOLVED OXYGEN  CONCENTRATION
AND PREDICTED SATURATION  CONCENTRATION  FOR
THE SANTA ANA RIVER NEAR  MENTONE, CALIFORNIA,
IN JUNE 1979,
                             464

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     Two measures or indices of low flow that have been found useful  are
flow duration and low-flow frequency.  Although it is beyond the scope of
this report to explain in detail how to develop these measures, examples of
each will be presented that explain their utility.  The majority of the
material in this section is from Cragwall (1966) who provides a discussion
on low flow, and cites additional references.  Many texts on engineering
hydrology (e.g. Linsley et al_., 1958) also discuss low flow.  Figure IV-34
shows a flow duration curve for the Hatchie River at Bolivar, Tennessee.
The vertical axis is the daily discharge and the horizontal is the percent
of time a flow is equaled or exceeded.  For example, 95 percent of the time
from 1930-58 the flow exceeded 177 cfs.  It can also be assumed that this
flow (177 cfs) will probably be exceeded 95 percent of the time in other
years.  Thus this concept offers one means by which to quantify "low flow".

     A second concept is the low flow frequency curve, illustrated in Figure
IV-35.  This depicts the relationship between discharge and recurrence
interval of different duration flows.  For example the 7 day mean flow of
100 cfs can be expected to occur once each 19 years.  Stated another way,
since probability is the reciprocal of recurrence interval, in any one year
there is about a 5 percent probability that a seven day mean flow of less
than 100 cfs will occur.  A commonly used flow for analyses is the 7 day
mean flow at a recurrence interval of 10 years, or 7Qio.
4.4.8  Interrelationships Between Temperature Prediction Tools

     The three major temperature prediction tools presented in Section 4.4
are:

     *   water temperature alterations caused by a power plant
     •   equilibrium temperature
     •   longitudinal river temperature profile

Figure IV-36 shows three river temperature profiles which illustrate how
these tools can be used jointly.  Curve A represents a temperature profile
of a river where a power plant is located a distance D below some reference
point.  The temperature on the river above the power plant is T2  which is
                                    465

-------
                                              DAILY DISCHARGE (cfs)
cn
                         CD
                         cr
                         73
                         m
                      m
<-> z
?3
>  (—)
cn  cr
2:  73
>  <
r~  m
                      h-1 >
                      
                         73

-------
    10000
                                           120 Day
                                           60 Day
                                           30 Day
  a
                                                    100
        RECURRENCE INTERVAL (YEARS)
FIGURE IV-35
FREQUENCY  OF LOWEST MEAN DISCHARGES OF
INDICATED  DURATION, HATCHIE RIVER AT
BOLIVAR, TENN, (FROM CRAGWALL,  1966)
                        467

-------
  Stream
Temperature
                    A (Power plant present)
                         B (Release from hypolimmon)
                   D
                                    DISTANCE
             FIGURE  IV-36    THREE RIVER TEMPERATURE PROFILES
                                   468

-------
slightly below the equilibrium temperature.   Due to the thermal  discharge
from the power plant, the river's temperature is increased to "!\,  above the
equilibrium temperature.  Below the mixing zone area, the water  temperature
gradually decreases toward equilibrium, as the excess heat is dissipated
into the atmosphere.

     Curve B illustrates the temperature profile of a river whose  water
comes predominantly from the hypolimnion of a reservoir.  While  in the
reservoir the water is insolated from the solar radiation, so the
temperature is below the equilibrium temperature.  As the water  is withdrawn
from the reservoir and begins to flow downstream, its temperature  increases
due to solar radiation and atmospheric heating.  The temperature tends to
approach the same equilibrium temperature (the two rivers are assumed to be
in the same geographic area).

     Curve C shows the temperature profile of river B which now has a power
plant, similar to the one on river A, discharging into it.  If the flow
rates of the two rivers are the same, so is the initial temperature increase
(i.e.  T3 - Ti = TV T2).  However, the temperature of the river continues
to increase, in contrast to profile A, because T3 is less than E.   This
illustrates an unusual, but entirely possible, situation where river
temperature continues to increase below a thermal discharge.
4.5  NUTRIENTS AND EUTROPHICATION POTENTIAL

4.5.1   Introduction

     Within the past decade the elements most often responsible for
accelerating eutrophication - nitrogen and phosphorus - have shown generally
increasing levels in rivers (EPA, 1974).  Median concentrations increased in
the period from 1968 to 1972 over the period from 1963 to 1967 in 82 percent
of the  reaches sampled for total phosphorus, 74 percent for nitrate, and 56
percent for total phosphate.
                                     469

-------
     These increasing concentrations afford more favorable conditions for
eutrophication, although many rivers with high nutrient levels do not have
algal blooms.  Algal growth can be inhibited in numerous ways.  For example,
turbidity can decrease light transmittance through water and effectively
stop growth.  Decreasing turbidity could, however, have a deleterious side
effect of promoting excessive algal growth, unless stream nutrient levels
are concurrently decreased.  High water velocity can also prevent algae from
reaching bloom proportions before they are carried out of the river system.
The eutrophication problem, then, is transferred to the water body into
which the river empties.
4.5.2  Basic Theory

     Stumm and Morgan (1970) have proposed a representation for the
stoichiometry of algal growth:


           106CO  + 16NO"  + HPO 2" + 122H 0 + 18H+( + trace
                2        3       **         2
                                              elements; energy)
                                                                     (IV-86)
                         K   H   0   N  P I  + 138 0
                         '106263110161'         2
                          algal  protoplasm


where P and R represent photosynthesis and respiration, respectively.
Observe that in the algal protoplasm the ratio of C:N:P is

                     C:N:P = 106:16:1, by atomic ratios              (IV-87)

                      C:N:P = 41:7:1, by weight ratios               (IV-88)
                                    470

-------
      From the above two equations  it  can  be  inferred that only  small
 amounts  of phosphorus  are needed to support  algal  growth  in  relation
 to the amounts of carbon and nitrogen required.   If phosphorus  is  not
 present  in the amount  required for algal  growth  then algal  production
 will  be  curtailed, regardless of how  much of the other nutrients  is
 available.  Phosphorus is then termed growth limiting.   It is possible
 for other elements, particularly nitrogen, and occasionally  carbon or
 trace metals, to be growth limiting as well  (Stumm and Sturnm-Zol linger,
 1972).

      Nitrogen uptake by algae is generally in the nitrate form  if
 nitrate  is available.   However,  different types  of fresh  water  algae
 can utilize either organic nitrogen or inorganic nitrogen in the form  of
 ammonia, depending on  what is available (Stumrn and Stumm-Zoll inger,
 1972).  Algae typically require  phosphorus in an inorganic form,
 usually  as orthophosphate ion (Kormondy,  1969).

       Some indication  of whether nitrogen or  phosphorus is growth
  limiting  may  be made  by  determining  the weight  ratio of  the appro-
  priate  forms  of nitrogen  and  phosphorus found in  a  river, and
  comparing that with the  stoichiometric ratio required for growth.
  This  gives an  idea  regarding  the nutrient on which  control efforts
  should  focus.  Specifically,  let
                                         ]                           (IV-89)
where
     [TN]     =  concentration of total  nitrogen in river,  mg-N/1
     [OPCL-P] =  concentration of orthophosphate,  mg-P/1


If R>10, phosphorus is more likely to limit than N.
If R<5,  nitrogen is more likely limiting than P.
If 5
-------
 Since the N:P ratio in algal  biomass  can vary from species  to  species,
 this makes the determination  of the limiting nutrient somewhat uncer-
 tain, and leads to the indeterminate  range of 5
-------
   For example, algae utilize nutrients, die, and settle to the bottom.
   Although  there  is a recycling of algal cell-bound nutrients, the
   settling  rate may surpass the rate of recycling.  Assuming total
   nitrogen  and total phosphorus to be conservative should give an
   estimate  of the upper limit of the instream concentrations of these
   nutrients.

       The  instream concentration of total nitrogen (TN) or total
   phosphorus (TP) resulting from a point discharge is (formulas will be
   presented for TN only; those for TP are exactly analogous):
                                                                    (IV_90a)
  or
                                   S. 38                             (I
                          Qu + Qw


 where
      TNu = instream TN upstream of discharge.  mg-N/1
      TNw = concentration  of TN  in  point  discharge,  mg-N/1
      Qu   = flow  in  river  upstream  of  point  discharge, cfs
      Qw   =  flow  rate of point discharge, cfs
      TNQ  -  resulting instream TN concentration, mg-N/1
     wp   =  loading rate of point source, Ib/day

The expression for TNQ is given by either Equation  IV-9iA or IV-91B
The appropriate form to use will  depend on the form of the available
data.
                               473

-------
     To determine the instream concentration of total nitrogen due to a
distributed discharge, use:

                                    j X
                       TN  =  TNQ + -5-  (TNr - TNQ)                 (IV-91a)
or

                                 TN Q
                                                                    (IV-915)
                                   Q      5.38 Q
where
     TN   =  TN entering with the distributed flow, mg-N/1
     TNQ  =  instream TN at x = 0, mg-N/1
     x    =  distance downstream from the point source discharge
     Q    =  stream flow rate at x, cfs
     Q    =  stream flow rate at x = 0, cfs
     Ag   =  incremental flow increase per unit distance, cfs/mile
     w    =  mass flux of TN entering the stream through the
             distributed source, Ib/day/mile

     The choice of whether to use Equation IV-91a of IV-91b depends on the
available data.  Based on the approach detailed in Chapter III, the mass
flux of nutrient entering the stream (in units of Ib/day/mile) can be
generated.  When this approach is used, then Equation IV-91b is applicable.

     To use Equation IV-91a the concentration of pollutant from the nonpoint
source has to be known.  This can be accomplished using the approach of
Omernik (1977).  Nonpoint source nitrogen and phosphorus concentrations are
predicted as fractions of land use type or based on color coded maps if land
use categories are not known.  The data used to predict nitrogen and
phosphorus concentrations were generated in a National Eutrophication Survey
(NES) program wherein a nationwide network of 928 nonpoint-source watersheds
were monitored.  This method accounts for only the nonpoint source
contribution.  Consequently, if point source exist within the watershed,
their contributions must be included as well in order to accurately predict
instream concentrations.
                                   474

-------
     Table IV-29 summarizes the predictive formulas developed by Omernik for
total phosphorus, orthophosphorus, total nitrogen, and inorganic nitrogen.
The formulas are regionalized by eastern, central, and western United
States.  Agricultural, urban, and forested lands comprise the independent
variables in the formulas.

     Omernik's analysis of the NES data indicates that:

     1.  Streams draining agricultural watersheds had considerably
         higher nutrient concentrations than those draining forested
         watersheds.

     2.  Nutrient concentrations were generally directly proportional
         to the percent of the land in agriculture and inversely
         proportional to the percent of land in forest.

     3.  Mean concentrations of total phosphorus and total nitrogen
         were nearly  nine times greater in streams draining
         agricultural lands than  in streams draining forested lands.

     4.  Mean phosphorus concentrations in streams draining forested
         watersheds  in the west were generally twice as high  as those
         in the east.

     5.  Total and  inorganic nitrogen in  streams draining agricultural
         watersheds were considerably higher in the heart of  the corn
         belt than  elsewhere.

     As  an  alternative to the equations shown in Table IV-29, Omernik
provides three colored maps of nonpoint source related concentrations of
nutrients in streams.  They can be used where detailed information necessary
for more accurate prediction is unavailable.
                                    475

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                               TABLE IV-29

  REGIONAL  STREAM NUTRIENT  CONCENTRATION  PREDICTIVE MODELS
 Nutrient Form    Model,  Correlation Coefficient and Multiplicative Standard
    Region        Error


 Total  phosphorus

 East      Log1Q (PCONC)  =  -1.8364 + 0.00971 (% agric +  %  urb)

                          r = 0.74, f = 1.85

 Central   Log1£) (PCONC)  =-1.5697 + 0.00811 (% agric * % urb) -0.002312 (X for)

                          r = 0.70, f = 2.05

 West      Log^ (PCONC)  =-1.1504 + 0.00460 (%agric + %urb) -0.00632 (% for)

                        r = 0.70, f = 1.91

 Orthophosphorus

 East      L°9io (°PCONC) = -2-2219 + 0.00934 (% agric + % urb)

                          r = 0.73, f = 1.86

 Central   Log]Q (OPCONC) = -2.0815 + 0.00868 (% agric + % urb)

                          r = 0.63, f = 2.05

 West      Log10 (OPCONC) = -1.5513 + 0.00510 (% agric + % urb) -0.00476 (% for)

                          r = 0.64, f = 1.91

 Total  nitrogen

 East      Log]0 (NCONC)  =  -0.08557 + 0.00716 (% agric + % urb) -0.00227 (% for)

                          r = 0.85, f = 1.51

 Central   Log]Q (NCONC)  =  -0.01609 + 0.00399 (% agric + % urb) -0.00306 (% for)

                          r = 0.77, f = 1.50

 West      L°9io (NCONC)  =  -0.03665 + 0.00425 (% agric + X urb) -0.00376 (% for)

                          r = 0.61, f = 1.75
East      Log1Q (1IICONC) =-0.3479  + 0.00858 (% agric + % urb)  -0.00584 (% for)

                         r = 0.84, f = 1.93

Central    Log.. (INCONC) = -0.5219 + 0.00482 (~ agric + % urb) -0.00572 (% for)

                          r = 0.71,f = 2.06

West      Lo9in UNCONC> = -°-6339 ^ 0.00789 (% agric + X urb) -0.00657 (% for)

                          r = 0.65, f = 2.45
From:   Omernik  (1977)


                                 476

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4.5.4  Nutrient Accounting System

     It may be desirable to determine the impact of each nutrient source on
the total instream concentration in order to distinguish among the major
sources.  An accounting procedure utilizing Equations IV-90 and IV-91 can be
developed to do this.  The following steps outline the procedure.

     1.  Segment River.  Divide the river into major segments.  These
         segment divisions may reflect waste loading distributions or
         another convenient division scheme chosen at the discretion of
         the planner.  The segments are not necessarily the same as the
         reaches that have previously been discussed (see Section 4.1).
         The delineation of reaches as described earlier is based upon
         lengths of river having uniform hydraulic conditions.
         Segments, as used here, are purely a convenient subdivision of
         the river.

     2.  Quantify and Locate Sources of Nutrients.  The quantification
         of point, nonpoint, and natural sources on the mainstem and
         tributaries should be accomplished using1 the best available
         data.  Tabulation can be performed for each different season
         to reflect the discharge pattern characteristic of each
         season.  The quantification should include total nitrogen and
         total phosphorus.  Tabulate data in terms of average daily
         input (Ib/day).  Characterize the location of the nutrient
         sources by river mile.  For nonpoint sources characterize by
         river mile at both the beginning and end of the source.

     3.  Perform Mass-Balance.  Sum the known sources to determine the
         total nutrient loading to each segment.  Then make the
         following comparisons:

         a.   Compare the total loading with the nutrient input from the
             mainstem at the upstream end of the segment.  This direct
             comparison permits an assessment of the collective impact
             of the nutrient sources entering a segment and the
             upstream contribution of the mainstem.
                                     477

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         b.  Perform an intersource comparison to ascertain the
             relative impact of each nutrient source.  Express the
             results for each source as a percent of the total loading.

     When a tributary has a high percent contribution steps 1 through 3
can be repeated for the tributary itself to track the sources of the
nutrients.

     Apply Equations IV-90 and IV-91 to each reach within the segment
to determine the instream nutrient concentration throughout the
segment.  Once this is done this step can be repeated for the next
reach.

     By applying this analysis one can determine the relative impact of
any discharge, determined jointly by the flux of the nutrient and the
discharge location.  Section 4.1.10 provided a detailed example problem
which illustrates the procedure.  A brief example also follows.
                             EXAMPLE IV-14
                 Computing Total Nitrogen Distribution

     This example illustrates the use of Equations IV-90b and IV-91b in
calculating the total nitrogen distribution in a river.  Suppose the
user has been able to estimate the point and nonpoint loading of total
nitrogen in a river as shown in Table IV-30.
                                   478

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                                 TABLE IV-30
                  TOTAL  NITROGEN  DISTRIBUTION IN A RIVER IN
                RESPONSE TO  POINT AND NON-POINT SOURCE LOADING
Reach
Number
1

2

3

4

River
Mile-
Point
0
9.99
10.0
14.99
15.0
20.99
21.0
26.0
TN
Added*
(Ibs/day)
400 L
500 D
0
700 D
800 L
650 D
0
900 D
TN
Cumul ati ve
(Ibs/day)
400
900
900
1,600
2,400
3,050
3,050
3,950
Q
Cumulative
(cfs)
300
400
400
600
700
900
900
1 ,000
TN Concen-
tration
(mg-N/1)
0.25
0.42
0.42
0.50
0.64
0.62
0.62
0.73
   *"L"  indicates a localized  or  point  source.   "D" indicates a diffuse
    or non-point source whose range  of  input is  over the entire reach.
If these loading rates  are  estimated over a year, then the flow rates
used should also be average annual flows.  To compute the concentration
at mile 0,  Equation IV-90b  can  be used:

                            (0)(Qu) ,  400
                    TN
                                 300_
                                 1.55
       0.25 mg-N/1
where the following conversions  were  used:


                          1 MGD = 1.55 cfs
                          1 mg/l = 8.34 Ib/MG


To determine the concentration at milepoint 9.99, use Equation IV-91b:
                                       500
                 TN  =  (0.25)  300
__
8". 34
400
1.55
- 0.42 mg-N/1
                                   479

-------
Note that wx in Equation IV-91 is the 500 Ib/day shown in Table IV-30.  By
reapplying these two basic equations for each reach the user can work
downstream through the four reaches.  Also note that the total nitrogen
concentration has decreased slightly through reach 3, even though more TN
has been added.  This is because the incoming flow has served to lower the
concentration by dilution.
                            END OF EXAMPLE IV-14
4.6  TOTAL COLIFORM BACTERIA

4.6.1  Introduction

     Total coliform bacteria are considered an indicator of the presence of
pathogenic organisms, and as such relate to the potential for public health
problems.  Allowable levels of total coliform bacteria in rivers vary from
state to state and according to the water use description characterizing the
particular river segment.  For example, in Montana (Montana State Dept.  of
Health and Environmental Sciences, 1973) the raw water supply may not have
more than an average of 50 MPN/100 ml* total coliforms if it is to be used
as a potable water supply following simple disinfection.  In water suitable
for bathing, swimming and recreation, as well as growth and marginal
propagation of salmonid fishes, an average of 1,000 MPN/100 ml is allowable.

     Concentrations of total coliforms vary with the season of the year.
Often the heaviest loadings occur during the summer months, but this impact
is somewhat offset due to the more rapid die-off at higher temperatures and
more intense solar radiation.  In the Willamette River (Figure IV-37), for
example, the highest counts of 1971-72 were actually observed from November
through May (EPA, 1974).

     Treated municipal sewage comprises a major source of coliform
pollution.  Urban stormwater runoff can also be significant, especially
 *MPN  means  "Most  Probable  Number".   Coliform  organisms  are  not  counted
  individually,  but  their densities  are  statistically  determined and  the
  results  stated as  MPN/100 ml.
                                    480

-------
         SEASONAL RIVER PROFILES
               WILLAMETTE RIVER
               Total  Conforms
100,000
I
§ 10,000
L.
O)
•»
o 100
«*-
"o
o
_ 10
K
'(

100,000
E
o
2 10,000
0.
CO
E
o
±: 100
o
o 10
1
JUN. TO OCT. 1972

\ A / /\ ^Xl OREGON
A/\/ / \ / SIANUAHU?
A/I / /^^\V ^ A
vr^
V \
1 1 1 1 I 1 1 1 1 J
) 20 40 60 80 100 120 140 160 180 200
River Miles
NOV. TO MAY 1971 /I972
/\
-- x" — '" \ A

1 \ \ 	 \/ ^
OREGON \ ^ ~-\ ^«^
STANDARD -* ^-^

1 1 1 1 1 1 1 1 1 1
                                     LEGEND:
                                             MEDIAN
                                             85%
      0  20  40  60  80 100 120 140  160 180 200
                  River   Miles

FIGURE IV-37  TOTAL COLIFORM PROFILES FOR
             THE WILLAMETTE RIVER (EPA, 1974)
                     481

-------
through combined sewer outflows.   Rural  storm water runoff transports
significant fecal contamination from livestock pastures,  poultry and pig
feeding pens, and feedlots.   Wildlife both within refuges and in the wilds
can contribute as well.  For guidance in the interpretation of preliminary
coliform analyses, Table IV-31 can be used.

                                TABLE IV-31

                    TOTAL COLIFORM ANALYSIS (EPA, 1976)
If the Calculated
Concentration is:
Less than 100/100 ml
Less than 1 ,000/100 ml
More than 1,000/100 ml
More than 10,000/100 ml
Probabil ity of
a Col iform Problem
Improbable
Possible
Probable
Highly Probable
4.6.2  Mass Balance for Total Col iforms

     The mass balance equations applicable to total coliform organisms are
exactly analogous to Equations IV-18, IV-21, and IV-23A and IV-23B, since
first order decay is used for both.  For purposes of hand computations, the
following decay coefficient is acceptable:

                          kt  = 1.0 + 0.02  (T-20)                    (IV-92)

where
     ktc  =  decay coefficient for total col iforms, I/day
     T    =  water temperature,  °C

Those equations with the widest applicability are listed below.  For a point
source of col iforms:
                                   482

-------
                 TC  -  TCQ exp
                                -J'
                                  tc
A
                                     (IV-93)
For both  point  and  distributed  sources  of  coliforms:
                       TC
                     _ r—  +   ITC   -
                                                   •tc
     For  a  change  in  coliform  concentration  due  to  a  point  source
modification:
                                     (IV-94)
                 ATC -
                          ATC  exp
                          ATC
"J tc   /ft
V  (*•'
                                       •tc
                                    (IV-95a)

                                    (IV-95b)
where
     TC  =  total coliform concentration, MPN/100 ml
     TC  =  initial total coliform concentration, MPN/100 ml
      'tc "   u:
     TC  =  total coliform level in distributed flow, MPN/100 ml
      'tc
     Because of the potential variability in coliform loadings, seasonal
analyses may be warranted.  Typically the summer months are of primary
concern because loadings often increase during this time period and water
contact recreation is at its maximum.  Major storm events may also be of
interest, because of the large coliform loading that may be associated with
them.
                                   483

-------
                              EXAMPLE  IV-15
               Estimating  the  Change  in  Total  Coliform Levels
                   in  Response to  a Waste  Loading  Change

     Compare the change in total  coliform levels,  ATC,  produced by a
change ATCQ at a given location in a  river.   Further,  determine how this
change is affected by a distributed flow entering  the  river.   Relevant
data for the river are as  follows:
     UQ  =  Ifps
     T   =  20°C
     Q   =  500 cfs
     Q   =  800 cfs
     x   =  10 miles
     kt  =  1.0/day at 20°C

First the computations will be performed assuming no distributed flow.
Equation IV-95A is then applicable.  Computing the exponent jt x (at a flow
distance of 10 miles):

                    J* x       (1.0)  (10)  (5280)   _  n ,n
                      tc    =    (24)  (3600)  (1)    '  U-b"
So

                        ATC
                        ATCQ
                               =  exp (-.611) = 0.54
 or
                              ATC =0.54 ATCQ
 For  example  if  ATC   =  -1,000 MPN/100 ml then ATC  = -540 MPN/100 ml  (negative
 ATC   indicates  that  the  coliform  level has decreased from what it previously
 was).
                                   484

-------
     Now suppose the  distributed flow of 300 cfs is included in the
computation.   Then,

                 F     -   ktc Ao * AQ
                 tC   "      AQ

                 Ao    =   VUo = 500/1 = 50° ft2

                 AQ    =  TOTWO-)   =  °-0057 ft2/sec
                 F     _      (1.0)  (500)
                 tc     I24j (3600 P(0. 0057)

                      =  2.02

Then

                          _        2'02 . 0  39
                       O   "  \8ooy     ~ u-jy

or

                             ATC   =  0.39 ^TCQ

For  ATCQ  = 1,000 MPN/100 ml,  ATC = -390  MPN/1 00  ml.

Note that this  decrease  is 150 MPN/100 ml  less than if no  distributed flow
existed.

     To  determine the absolute total coliform level,  simply add  to the
original  level  the resulting change caused by the  waste loading
modification.
ATC_  _   SOO
ATC   "
         END  OF  EXAMPLE  IV-15
               485

-------
4.7  CONSERVATIVE CONSTITUENTS

4.7.1  Introduction

     Conservative constituents are those which are not reactive and remain
either in solution or in suspension.  They are advected through the water
column at the velocity of the river with no loss of mass.  The analysis of
nutrients, already discussed in this report, was performed assuming they
acted conservatively.  Other substances, such as salinity, can also be
considered as conservative.  Chapter 3 contains information on salinity in
irrigation return flow for many rivers with salinity problems.


4.7.2  Mass  Balance  for  Conservative Constituents

      Two simple mass balance equations are sufficient  for analyzing
 conservative constituents.   The first  relates the  instream concentration  due
 to a point  source  loading:
                                  SO  + W/5.38
                              S =   u "   + '	                       (IV-96)

 where
      S   -  resulting pollutant  concentration,  mg/1
      S   =  upstream concentration, mg/1
      Q   =  upstream flow rate,  cfs
      Q   =  point source flow rate, cfs
      W   =  loading rate of pollutants, Ib/day

 When a distributed flow is present along some length of the river, then the
 distribution of the conservative pollutant is given by:
                                  S  0
                                                                      (IV-97)
                                         5.38C)

 where
      w    =   distributed  loading rate,  Ib/day/mi
      x    =   distance  downstream, miles
                                    486

-------
     S   =  initial concentration (at x = 0), mg/1
S  in Equation IV-97 is identical with S in Equation IV-93.
                               •EXAMPLE IV-16-
                Calculating Salinity Distribution in a River

     Salinity problems are receiving increased attention in the western
United States, particularly relating to the economic issues in the Colorado
River Basin and international compacts with Mexico.  In the Colorado River
high salinity levels in the lower reaches adversely affect nearly twelve
million people and approximately one million acres of fertile irrigated
farmland (Bessler and Maletic, 1975).  The salinity now averages
approximately 865 mg/1 at Imperial Dam and is projected to be 1,160 mg/1 or
more by the year 2000, unless firm control actions are taken.

     Consider the river shown in Figure IV-38.  Predict the salinity
distribution based on the inflows and withdrawals shown.  Assume the data
are averaged over a period of a year.  These data, along with the salinity
concentrations at different river mileposts are shown in Table IV-32.

To calculate S (salinity at milepoint 100) use Equation IV-96:

                                   6
                  S  =   ^      J^xT0)n. 55/8. 34)  _
                                 2000               ido Tig/l
At milepost 199.9, Equation IV-97 is appropriate and S is given by:

                     6)(2pO_0)  x (4xl06)(1.55
                     50~0(T~            5000
                 . (186)(2pO_0)  x  (4xl06)(1.55/8.34)
                 ~~~  ~~                       = ^J mg'  '
                                    487

-------
         Q = 3000cfs             Q = 5000cfs
         W=4xl06lb/day          W = 25xl06lb/day      0 - 25OOcfs
                                                                   \
  -— "— ^— •"^•-•—••^— - — •> ---- *— J— J-J- J -- j --- -*"»---»-T»««|f lp1l»«M J
      ^               \              /              Tiff!
      Q = l500cfs           *              0-SOOOcfs      I   »  1  I  I
      W-PvlfAh/rtm/        ^              U-3UUUCTS      Q=2000cfs
      W-2xlO°lb/day         Q=,000cfs      W=8xloP|b/day   W = 20xlo6|b/day
0	100     200     300      400     500  	600      700  750
i         i         i         r       ~i—     i~~     i         ii
                            RIVER MILES
 FIGURE  IV-38     SALINITY  DISTRIBUTION IN A  HYPOTHETICAL RIVER
     At milepoint 280, 1,000  cfs of  flow leaves the mainstem (perhaps  for
 irrigation purposes).   The concentration of salinity in this flow is the
 same as that in the mainstem.   So  the mass rate of withdrawal  is


                 W - ~Y~  (223 x 1000) = -1.2xl06 Ib/day

     A negative sign is used  to signify a withdrawal.   Completing the
 remainder of the table is  solely a matter of reapplying these  basic concepts,
 4.8  SEDIMENTATION

 4.8.1  Introduction
                        END OF  EXAMPLE IV-16
     One of the more  difficult classes of hydraulic engineering problems
 associated with rivers  involves the erosion,  transportation, and deposition
 of sediment.  Sedimentation  is important economically, particularly relating
 to filling of reservoirs  and harbors, and to  maintaining channel
                                488

-------
                             TABLE IV-32

            SALINITY DISTRIBUTION IN A HYPOTHETICAL RIVER

Reach
Number
1

2

3

4

5

6

7

8

9

10

River
Mile
Point
0
99.9
100
199.9
200
279.9
280
359.9
360
449.9
450
499.9
500
524.9
525
599.9
600
649.9
650
750
Sal inity
Added*
(Ibs/day)
0
0 c
2x10^
4x10°
0
0
-1.2x10°
0
0
25x10°
0
0 c
8 106
0
-7.9xlOb
0
-4.7x10°
0
0 ,
20x10°





L
D


L


D


L

L

L


D
Sal inity
Cumulative
(Ibs/day)
0
0 c
2x10^
6x10°
6x10°
6x10° ,
4.8x10°
4.8x10°
4.8x10°
29.8x10°
29.8x10°
29.8x10°
37.8x10°
37.8x10°
29.9x10°
29.9x10°
25.2x10°
25.2x10°
25.2x10°
45.2x10°
Q
Cumulative
(cfs)
500
500
2000
5000
5000
5000
4000
4000
4000
9000
9000
9000
12000
12000
9500
9500
8000
8000
8000
10000
Salinity
Concentration
(mg/1 )
0
0
186
223
223
223
223
223
223
615
615
615
585
585
585
585
585
585
585
840
*'L'  indicates a localized or point source at the milepoint shown  in
 the same row.

 'D'  indicates a diffuse or non-point source ending at the milepoint
 shown in the same row and beginning at the milepoint in the above row.
                                489

-------
navigability and stability.   Table IV-2,  located  in  Section  4.1,  documents
some suspended solids problems encountered in  eight  major  U.S.  waterways.

     The sediment load carried in a river can  be  divided into two
components:  the bed material load and the wash load.   The bed material  load
is composed of those solid particles represented  in  the bed.  The transport
of this material is accomplished both along the bed  (bed load) and suspended
within the water (suspended load).  Although there is  no sharp demarcation
delineating bed load from suspended load, many researchers have developed
individual expressions for each transport component.  The total bed material
load is the sum of the bed load and the suspended load.  Other researchers
have developed a unified theory from which the total bed material load can
be predicted from a single expression.

     The wash load  is usually produced through land erosion, rather than
channel scour.  Wash  load is composed of grain sizes finer  than found in the
bed material.   It readily remains  in  suspension and is washed out of the
river without being deposited.  A  definite relationship between the
hydraulic  properties  of a river and the wash  load capacity  apparently does
not exist, making  it  difficult to  advance  an  analytical method for washload
prediction  (Graf,  1971).  Not all  the erodible material entering  a stream  is
transported as  wash  load, but a  large portion may become  part of  the bed
material  and  be  transported  as bed material load.

      Figure  IV-39  provides  a graphical  illustration of the  difference
between wash  load  and bed material load.   For a  particular  flow  condition  in
a particular  river,  the river has  the capacity to transport a  certain
quantity  of  sediment  (q  ) which  generally decreases as particle  size
increases.  At  some large particle size  the river cannot  exert enough force
to transport  particles of that  size or  larger.   This  situation would occur
at some point to the  right  of point D on curve COD.  This same river might
be supplied with sediment  at a  rate AOB,  which  is unrelated to transport
capacity.

      To  the left of point  0 the river is transporting all the material  of
 that  size range being supplied  to it.  Sediment  having diameters less  than
 d* are classified as wash  load,  because the amount  being transported  is
                                   490

-------
   CD
   d
   73
   m
   UD
O  *-<
-n  o
73  Z
o
2  dd
• -  m
                       SEDIMENT TRANSPORT CAPABILITY OF FLOW
o
r~
o
   m
   m
O  CO
o  a:

oo i —
-i  o
>  >
-i  a
m
z  a
t—4
<  CO
m  m
73  O
H  >
•<  H
>.  m
CO >
*--J |—

(-D
          N
          m
O)
rn
g

^
m
o
r~
m
                                 SEDIMENT SUPPLY  RATE

-------
supply limited,  and  not  transport limited.  To the right of point 0,
supply exceeds  transport capacity.  The amount given by the curve OD is
transported,  and the difference in OB and OD is deposited in the stream  bed.
The methods to  be presented  in the following sections are generally
concerned with  predicting  curve OD (i.e.  the bed material load), although
Section 4.8.2 does provide a  brief description of how to estimate long-term
sediment supply rates.

     As a guide in evaluating whether a river is carrying a significant
quantity of suspended sediment, Table IV-33 can be consulted.  100 mg/1  is
the delineation between  a  potential and probable problem.  In a table
previously introduced (Table  IV-1), a reference level of 80 mg/1 was set for
protection of aquatic life.

                             TABLE IV-33

          RELATIONSHIP OF  TOTAL SUSPENDED SEDIMENT CONCENTRATION
                  TO PROBLEM POTENTIAL  (AFTER EPA, 1976)
            If Calculated                    Probability of
          Concentration is:                    a Problem
          Less than 10 mg/1                    Improbable
          Less than 100 mg/1                   Potential
          More than 100 mg/1       	  Probable
 4.8.2  Long-Term Sediment Loading from Runoff

      The procedures outlined  in Chapter   3  will  permit  an  assessment
 of the sediment loading  to a  river on a long-term basis.  When  using
 those procedures care should  be taken to  incorporate  the entire
 drainage area of the watershed.  As an estimate,  the  loading  can  be
 assumed conservative (i.e. all sediment that comes into  the river will
 be washed out of the river over an extended time  period).   Under  that
 assumption  the  procedure outlined  in  Section  4.7 can be utilized for an
 estimate of average yearly suspended  solids concentrations  at locations
 throughout  the  river system.   This  result should be interpreted as
                                   492

-------
an indicator of the  impact of  the  runoff  on  sediment loads  within  a
river and not as actual  suspended  solids  concentrations.   Not all  of
the incoming sediment will be  transported as suspended load since  a
large fraction can be transported  as  bed  load.   The transport process
is generally of an intermittent  nature  with  higher concentrations
occurring during periods of  high flow.

     Care should be  taken not  to apply  the conservative assumption at
points on a river where  that assumption is clearly violated, such  as
at reservoirs which  can  be efficient  sediment traps.  An example for
the computation of sediment  loading to  rivers has been considered  in
Chapter  3.
4.8.3  Bed Material Load

     As previously mentioned, the estimation  of  bed  material transport
poses a difficult problem, and is an area where  there  is  no  consensus
regarding the best predictive relationship to use.   Numerous bed
material load relationships (Task Committee on Preparation of Sedimen-
tation Manual, 1971) have been developed over the  past century, some
requiring considerably more input data than others.   In this report
the  DuBoys relationship (Task Committee on Preparation of Sedimentation
Manual, 1971) will be used in part because of its  simplicity.  The
relationship,which is restricted to uniform flow in  alluvial channels,
is:
                   gb = *ao (TQ - TC)                               (IV-98)

where
     gb   -   bed  load,  Ib/sec/ft  of  width  of  river
     '!'     =   coefficient depending on  grain size, ft /lb/sec
                                          p
     T     -   yRu  S,  bed shear  stress,  Ib/ft
     o         n
     Y     =   specific weight of water, Ib/ft
     Ru    =   river hydraulic  radius,  ft
     H
                                 493

-------
     S    =   slope of stream,  ft/ft

     ic    =   critical shear  stress, lb/ft2

The values of Y and r  can be  expressed as functions of the median
size (by  weight) of the bed  sediment (den)-   These relationships  are
expressed graphically in Figure  IV-40.   To aid  in determining d™
Table IV -34  is presented to  show the size range of sediment and each
associated class name.  If the class name of the predominant sediment
type comprising a stream bed  is  known,  then the sediment size (in mm)
can be  estimated.  Appendix C also contains
rivers  and  streams.
                                           ™
                                             data for numerous
     Once d5Q is  estimated, then
                                  and  TC can easily be  evaluated,
leaving only  TQ to compute.   A summary of hydraulic radii  (the  ratio
of cross-sectional area to wetted  perimeter) for different channel
                                                       200
                      .2     .4   .6 .8 I      2     4
                  MEDIAN SIZE OF BED SEDIMENT, d.
                                 (MM)
          FIGURE  IV-40
                             * AND TC FOR DUBOYS RELATIONSHIP
                             AS FUNCTIONS OF MEDIAN  SIZE OF
                             BED  SEDIMENT (TASK COMMITTEE ON
                             PREPARATION  OF SEDIMENTATION
                             MANUAL,  1971)
                               494

-------
                  TABLE  IV-34

SEDIMENT GRADE SCALE (TASK COMMITTEE  ON  PREPARATION
          OF SEDIMENTATION MANUAL,  1971)
Class Name
Very large boulders
Large boulders
Medium boulders
Small boulders
Large cobbles
Small cobbles
Very coarse gravel
Coarse gravel
Medium gravel
Fine gravel
Very fine gravel
Very coarse sand
Coarse sand
Medium sand
Find sand
Very fine sand
Coarse silt
Medium silt
Fine si 1 1
Very fine silt
Coarse clay
Medium clay
Fine clay
Very fine clay

Size
Mil 1 imeters











2-1
1-1/2
1/2-1/4
1/4-1/8
1/8-1/16
1/16-1/32
1/32-1/64
1/64-1/128
1/128-1/256
1/256-1/512
1/512-1/024
i /1 024-1/2048
1/2048-1/4096
4096-2048
2048-1024
1024-512
512-256
246-128
128-64
64-32
32-16
16-8
8-4
4-2
2.000-1 .000
1.000-0.500
0.500-0.250
0.250-0.125
0.125-0.062
0.062-0.031
0.031-0.016
0.016-0.008
0.008-0.004
0.004-0.0020
0.0020-0.0010
0.0010-0.0005
0.0005-0.00024
P Approximate Sieve Mesh
ange Openings Per Inch
United States
Microns Inches Tyler Standard
160-80
80-40
40-20
20-10
10-5
5-2.5
2.5 -1.3
1.3 -0.6
0.6 -0.3 2-1/2
0.3 -0.16 5 5
0.16-0.08 9 10
2000-1000 16 18
1000-500 32 35
500-250 60 60
250-125 115 120
125-62 250 230
62-31
31-16
16-8
8-4
4-2
2-1
1-0.5
0.5-0.24

-------
geometries is shown in Figure IV-41.   For very wide, shallow channels,
the hydraulic radius approximately equals the depth of flow.   Many
river cross-sections can be approximated by a parabolic section.   To
calculate "c" in the relationship for hydraulic radius of a parabolic
section, refer to Table IV-35.

     If the bed slope is unknown it can be estimated by using a
topographic map and finding contour lines approximately five hundred
feet above and below the point on the river where the measurement is
to be made.  Dividing this elevation difference by the horizontal
distance over which the difference is measured, produces the slope.
                            TABLE IV-35
      COMPUTING D/T FOR DETERMINING THE HYDRAULIC RADIUS OF
              A PARABOLIC SECTION (FROM KING, 1954)
*
D
T
.0
.1
.2
.3
.4
.5
.6
.7
.8
.9

.00
.667
.650
.607
.554
.500
.451
.408
.370
.338
.311
*D
T C

.01
.667
.646
.602
.548
.495
.446
.404
.367
.335
.308



.02
.666
.643
.597
.543
.490
.442
.400
.364
.333
.306



.03
.665
.639
.592
.537
.485
.437
.396
.360
.330
.303



.04
.664
.635
.586
.532
.480
.433
.392
.357
.327
.301



.05
.662
.631
.581
.526
.475
.428
.388
.354
.324
.298



.06
.660
.626
.575
.521
.470
.424
.385
.351
.321
.296



.07
.658
.622
.570
.516
.465
.420
.381
.348
.319
.294



.08
.656
.617
.564
.510
.460
.416
.377
.344
.316
.291



.09
.653
.612
.559
.505
.455
.412
.374
.341
.313
.289


                                  496

-------
CHANNEL SLOPE
                                  HYDRAULIC RADIUS
    f
    1
    Trapezoidal
                   3
                     e

	Q-±_zxLJL__  x = D/b, z = e/D

1  + 2 x Vl + x2

         T   \
    f
    Rectangular
                                              bD
                                             b + 2D
    Triangular
                                                    z = e/D
         T
    Parabolic
                                             n
                                            cu
                                                  (for c, see
                                                  Table IV-29)
FIGURE IV-^1     HYDRAULIC RADII FOR DIFFERENT CHANNEL  SHAPES
                 (FROM KING, 1954)
                             497

-------
      Adequate methods that are within the scope of this  report and
 which would  provide a straightforward estimation of suspended sediment
 discharge  presently do not exist.  Most relationships  require a known
 reference  level concentration at some depth within the river to predict
 the concentration at another depth (Morris and Wiggert,  1972).  To
 determine the suspended sediment load, then, a summation of contributions
 at each depth must be made.  Since these formulas apply to one grain
 size this procedure should be repeated for all grain sizes present.
 Einstein (Graf,  1971) has developed a method for computing suspended
 sediment discharge that does not require knowledge of a reference concen-
 tration, but it  is an advanced approach.  For this report the contri-
 bution of the suspended load will  be estimated from the bed material
 load by the  relationship given in Table IV-36.   The relationship in
 Table IV-36  is valid  for graded  channels (by graded is  meant  that the
 slope is stable over  time,  being neither steepened nor  flattened by
 flow or other influence).


                             TABLE  IV-36
               RELATIONSHIP BETWEEN WIDTH TO DEPTH RATIO
               OF A GRADED STREAM AND THE SUSPENDED AND
               BED LOAD DISCHARGE (AFTER FENWICK, 1969)
Suspended
Load % of Total
Bed Material Load
85-100
65-85
30-65
Bed Load % of
Total Bed
Material Load
0-15
15-35
35-70
Width-
Depth
Ratio
7
7-25
25
Once the width  to  depth ratio for the stream in question  is  determined,
the suspended load can then be approximated after first computing the
bed material load, and then using Table IV-36.
                                 498

-------
     Once the suspended load discharge is estimated the average
concentration at a section can be computed by:
                       4il.6xl04                               (IV-99a)
 or                    g
                 Css - -^1.6 x 104                               (IV-99b)
 where
      C   = average suspended solids concentration,  mg/1
      G   = suspended solids discharge,  Ib/sec
      Q   = flow rate,  cfs
      g   -- suspended solids discharge per unit width, Ib/sec/ft
      q   = flow rate per unit width, cfs/ft
     The procedures discussed in this section can be summarized as follows

     1.  Determine the bed load discharge g  (Ib/sec/ft) using Equation
         IV-98.  The required input data are channel slope, hydraulic
         radius (see Figure IV-41), and the median sediment size, d™
         (see Appendix C).  Once d   has been estimated the unknown
                                  bu
         parameters T  and ¥ can be found from Figure IV-40.
     2.  Multiply g,  by the river width to find the total bed load
         discharge.

     3.  Determine the width/depth ratio.

     4.  Use  Table IV-36  to determine  the suspended  load.

     5.  To determine the suspended  sediment  concentration use  Equation
         IV-99.
                                     499

-------
     6.  Compare the suspended sediment concentration against the data
         in Table IV-33 to find out if a problem potentially exists.

     7.  The total bed material load is sum of the total bed load
         (step 2) and the total suspended load (step 4).

     The user may be primarily concerned with the total bed material load
rather than either bed load or suspended load individually.  Total bed
material load can be directly calculated using a number of predictive
formulas.  The method of Yang (1976) based on unit stream power is presented
here.  Yang's method has been verified for the following parameter ranges:

     t   median bed size from 0.16 mm to 1.0 mm
     •   channel depth 0.2 ft to 49.9 ft
     •   water temperature from 0°C to 29.4°C
     •   stream velocity from 1.23 fps to 7.82 fps
     •   flow rate from 2.7 cfs to 470,000 cfs
     •   slope from 0.0000428 to 0.00188
     t   total sediment concentration (excluding wash load) from 2.8
         ppm to 2,440 ppm

     The input data are the same as for the DuBoy's method, with the
addition of water temperature.  The predictive formula, however, is
considerably more complicated, so the method has been programmed on a hand
held calculator and the program is included.  The predictive expression is:

    log Ct = 5.435 - 0.286 log ^ - 0.457  log ^

           + (1.799 - 0.409 log ^ - 0.314  log  ^)  log (— -  -^-)  (IV-100)

where
     C.  =  total sediment concentration in parts per million by weight
     D   =  median sieve diameter
     S   =  water surface slope or energy slope
     U*  =  shear velocity
     U   =  average water velocity
     Ucr =  Critica1  average water velocity at incipient motion
                                    500

-------
     v   =  kinematic viscosity
     w   =  terminal fall velocity


The term -^- can be calculated as
          w
            Ucr         2 5                          U D
                                   + 0.66 when 1.2 < ^  < 70      (IV-101)
                                      .         .
                         ) - 0.06                     v
and
cr
w              ' " —  v
                              = 2.05 when 70 <                      (IV-102)
     Figure IV-42 shows the required user instructions to execute the
program on a TI-59.  Figure IV-43 contains the program listing and a sample
input/output.  This program was written by Colorado State University (1979).
                               EXAMPLE IV-17
                      Estimation of Bed Material Load


     Table IV-37 shows characteristics of the Colorado River at Taylor's

Ferry, California, and of the Niobrara River near Cody, Nebraska.  Suppose

one desires to calculate the bed load for the Colorado River at this

location for flow ranges of 8-35 cfs/ft.  The following data will be used:


                         d^Q =   0.33 mm

                         Y    =   62.4 lb/ft3,  at 60°F

                         S    -   0.000217 ft/ft


Using Figure IV-40 one finds


                                 V    -   64

                                 T    -   0.019
                                     501

-------
TITLE.
                  .PAGE	i_OF.
PROGRAMMER.
                  .DATE.
Partitioning (Op 17) I 4, 6, 0. 6, Ol  Library Module.
                                       .Printer  Optional Cards 1
                                PROGRAM DESCRIPTION
 Program:  Yang's Sediment Transport Equation
                                 USER INSTRUCTIONS
STEP
1
2
3
4

5
6
7

PROCEDURE
Ift2\
Enter kinematic viscosity, vlj=-l
Enter slope SQ (ft/ft)
Enter median sediment diameter, d (ft)
Enter flow velocity, U (r^r )
sec
Enter flow depth, Y (ft)
Compute sediment concentration (ppm)
To input new data, repeat steps 1
through 6.
ENTER
V
So
ds
U

Y



PRESS
A
B
C
0

E
2nd








A'











DISPLAY
V
So
ds
U

Y
Ct


FIGURE IV-42
USER  INSTRUCTIONS  FOR YANG'S SEDIMENT  TRANSPORT
EQUATION,
                                      502

-------
Procram Listina:
000
001
002
003
004
005
006
007
003
009
0 1 0
Oil
012
013
014
015
016
01?
01 S
019
020
021
022
023.
024
025
026
02^
0 2 3
029
030
03 1
032
0 3 3
034
035
036
037
0 3 S
o r '-•
0 4 0
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0-2
0 4 '•
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76
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060
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063
064
065
066
067
063
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070
071
072
073
074
075
076
077
078
079
080
081
082
083
034
085
086
087
083
039
090
091
092
093
094
095
096
097
093
099
100

34
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109
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117
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119
120
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122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
133
139
140
141
142
143
144
145
146
147
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149
150

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172
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192
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S
 FIGURE  IV-43
PROGRAM LISTING  AND  SAMPLE INPUT/OUTPUT FOR
YANG'S SEDIMENT  TRANSPORT EQUATION
                            503

-------
Program Listing (continued):
201
202
203
20-1
205
206
207
208
209
210
211
212
213
214
215
216
217
213
219
220
221
2^2
223
224
225
226
227
22'-'
229
230
231
232
233
23-i
235
236
237
233
239
240
241
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243
24*
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24"
24 5
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28
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65
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23
54
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LDG
STD
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LDG
>
>
INV
251
252
253
254
                        28 LDG
                        98 flDV
                        99 PRT
                        92 RTN
Sample Input:
V
sn
0
d
s
U
Y
» .0000111
- .0017

- .000623

= 2.89
= 0.51
                                            Output.-
                                            Ct « 2117.066395
                  FIGURE  IV-43   (CONTINUED)
                              504

-------
                            TABLE IV-37
        CHARACTERISTICS OF THE COLORADO AND NIOBRARA RIVERS
   (TASK COMMITTEE ON PREPARATION OF SEDIMENTATION MANUAL, 1971)
             Data
Depth range, ft
Range in q, in cubic feet per
second per foot of width
Mean width, in feet
                                                   Stream
    Colorado
     River
(Taylor's  Ferryj
      4-12
      8-35
   350
                                                          Niobrara
                                                           River
                                                        (Cody, Neb.)
                                                          0.7-1.3

                                                          1.7-5
                                                         110
Slope,  in feet per foot
   Minimum value
   Maximum value
   Value used in calculations
                                           0.000147
                                           0.000333
                                           0.000217
                      0.00116
                      0.00126
                      0.00129
Water temperature, in degrees
Fahrenheit
Minimum value
Maximum value
Value used in calculations
Geometric mean*
in mil 1
d
d

d

d

Mean

35'

50'
f I~ 3
65
r\ t~\ 9
90
si

imeters
in mill
in mil 1

in mill

in mill

ze, d ,
m
sediment size,

imeters
imeters

imeters

imeters

in millimeters

48
81
60

0.
0.
0.

0.

0.

0.



320
287
330

378

530

396

33
86
60

0.
0.
0.

0.

0.

0.



283
233
277

335

530

342

The  geometric  mean  of  a  set of values X,
                  ihus the
 geometric  mean of  the  values 1, 2, 3, and 4 is (1x2x3x4) '  = 2.213.
 Compare with  arithmetic mean of 2.5.
                               505

-------
All that remains is the computation of the hydraulic radius.   Since the
width is much greater than the depth,  assume R  = D.
                                              H

                               4 ft at q - 8 cfs/ft
                               12 ft at q = 35 cfs/ft

Using Equation IV-98 it is found that  the bed load is

                           0.12  Ib/sec/ft  at  q  =  8  cfs/ft
                   gb
                          ' 1.5 Ib/sec/ft at q =  35  cfs/ft

The actual bed material load  observed at Taylor's Ferry has been compared
with the DuBoys prediction for a range of flow rates (Task  Committee on
Preparation of Sedimentation  Manual, 1971).   This relationship is shown in
Figure IV-44 (The DuBoys curve in Figure IV-44 does  not quite match the
calculations in this example  because slightly different data were used).
Observe that the DuBoys relationship overpredicts the bed material  load for
nearly all flow ranges.  This pattern is repeated for the Niobrara  River
(Figure IV-45).  This suggests that the bed  material load estimated by the
DuBoys relationship will in general exceed the actual bed material  load.
This is further substantiated by other work  (Stall et _al_.,  1958).  The more
accurate predictions of bed material load occur  under high  flow conditions,
which is generally when the prediction of bed material load is most
important.
                                   506

-------
                      COLORADO RIVER
                      AT TAYLORS FERRY
o i.uu —
g 0.80-
- 0.60-
£ 0.40-
LJ
g 0.20-
X
On in
U. 1 \J
(S) 0.08—
Q 006-

z °-04~~
UJ
1 002-
Q
QJ
co n ni




Duboys/
/-





o





1 1
1
s£
/025.  Referring to Table  IV-36, the  suspended load
should be between 30 and 65  percent of the  bed material load.   Assume
it is on the lower end of the scale, about  40%.  Then  the suspended
load  is
              3ss
0.08 Ib/sec/ft at q  = 8 cfs/ft

     Ib/scc/ft at q  - 35 cfs/ft
                      i  n
                                507

-------
 or
                    'ss
160 mg/1 at q - 8 cfs/ft
440 mg/1 at q - 35 cfs/ft
                         NIOBRARA RIVER
                         04  0.8    2   468 10
                          ' 0.6  I
                          WATER DISCHARGE (cfs/ft)
           FIGURE IV-
   SEDIMENT DISCHARGE  AS A FUNCTION
   OF I.'ATER DISCHARGE  FOR THE
   NIOBRARA RIVER AT CODY,
   NEBRASKA (TASK COMMITTEE ON
   PREPARATION  OF SEDIMENTATION
   MANUAL,  1971)
from  Equation IV-99.  These concentrations  indicate that suspended sediment
concentrations are excessively high throughout the range of flows normally
encountered at Taylor's Ferry.  Data on suspended sediment concentrations
have  been gathered at Taylor's Ferry (U.S.  Bureau of Reclamation, 1958).
The averages of 30 measurements taken there are as follows:
                                  508

-------
                    Q   =  7350 cfs (or q - 21  cfs/ft)
                    Css  =  132 mg/1
                    Observed range of suspended sediment
                    concentration:   40-277 mg/1

     The method of  Yang  predicts total concentrations of 40 to 80 mg/1,
which is within but  toward  the lower end of the observated data.  The method
of DuBoy's predicts  concentration  between 160  and 440 mg/1 which is toward,
and beyond, the upper end of observation.  These results illustrate the
possible variability of  predictions between different approaches, and are
not necessarily atypical.
                            END OF EXAMPLE IV-17
4.9  TOXIC SUBSTANCES

4.9.1  Methods of Entry of Toxic Pollutants into Rivers

     Although Chapter 3 discussed both point and nonpoint sources of
pollutants, the major pollutant source categories are summarized in Table
IV-38 to indicate how these scenarios differentially govern a pollutant's
fate.  For simplicity, fate is analyzed in terms of volatilization and
sorption since these processes are important for a wide number of toxic
organic chemicals.  These processes govern whether a pollutant remains in
the water column and whether the pollutant is transported as solute or
sorbate.  If the effects of these processes are known, even if only
qualitatively, then the influence of processes such as photolysis and
biodegradation can be better predicted.  For example, if a pollutant is
sorbed to suspended and bedded sediments, it is more protected from
photolytic reactions than when it is dissolved in the water column.

     A common mode of pollutant entry is by a continuous discharge, either
from a municipal or industrial source.  As mixing of the effluent and river
water occurs, partitioning begins.  The sorbate is transported with the
                                      509

-------
                             TABLE IV-38

     METHODS OF INTRODUCTION OF TOXIC ORGANIC COMPOUNDS INTO RIVERS,
             AND FATE IN TERMS OF VOLATILIZATION AND SORPTION
        Pathway
           Fate
Continuous input
- solute transported and volatilized
- sorbate transported with suspended solids
  and with bed load

- sorbed to immobile sediments
- buried by sorption and net deposition
Cessation of continuous
input
  desorbed from immobile sediments

  solute transported and volatilized
  resorbed to suspended sediments

  contaminated sediments resuspended
  portion remains buried
Washoff from land
application
Accidental releases
(e.g. spills)
Leaching
- transport of a major portion of pollutant
  may be governed by first large storm event

- transported as solute and sorbate

- settles and accumulates on bed

- buried

- subsequently resuspended


- If s.g. >1, pollutant settles on streambed

- Volatilization may be unimportant
  --reentrained back into stream and sorbed
    on suspended solids
  --pollutant can be slowly transported along
    bottom
  --diffused into bedded sediments

- If s.g. <1, pollutant tends to remain on
  surface and be transported at speed of
  surface current
  --volatilization can be important
  --gradually dissolved and sorbed
  --dispersion attenuates peak concentrations
  —wind speed and direction influential


- slow movement (years) of solute from dump
  or disposal site to stream

- continues for years after cleanup of
  dump
                                  510

-------
suspended sediments, and can interact with the bed load and immobile bedded
sediments.  Depending on the rate of exchange of the sorbate with the bedded
sediments and on the net sediment deposition rate, some of the sorbate can
gradually become buried in the bedded sediments.

     If a continuous input ceases, the water column initially tends to clean
itself of the pollutant as uncontaminated upstream water replaces
contaminated river water downstream from the former source of pollution.
However, pollutant from the contaminated bottom sediments can desorb back
into the water column at low concentrations and the river bed becomes an
internal source of pollutant.  The desorption period can last a long period
of time, depending on the amount of pollutant contained in the bottom
sediments.  Section 4.9.3.4 discusses this phenomenon in detail.

     Periodic nonpoint sources, such as washoff after an agricultural
application, is another pathway of pollutant entry into rivers.  The mass of
pollutant transported tends to be governed by the timing of the first storm
event following application together with the degradation and volatilization
processes operative during the interim period.

     Accidental releases of pollutants, even through infrequent events, can
be important.  Exceptionally high concentrations of pollutants can result
from spills and the total mass supplied almost  instantaneously can be the
equivalent of a continuous release lasting for many days.  For example, in
1973 a chloroform spill on the Mississippi River resulted in about
800,000 kg (1,750,000 Ibs) of chloroform being released over a period of
several hours (Thibodeaux, 1977).  Based on the background concentration of
chloroform in the river (5 ppb), the release was equivalent to a continuous
supply of chloroform released at background rates for a period of 300 days.

     Many chemicals in their pure or nearly pure form have specific
gravities significantly different from unity.  Because of this, and their
often limited solubility in water, it is a mistake to believe that all
spilled pollutants travel with the speed of the river, have infinite
dissolution capability, and disperse accordingly.  High density pollutants
can sink to the river bed and become slowly reentrained back into the water
column   while  simultaneously diffusing and sorbing into the bedded
                                    511

-------
sediments.  Depending on the rate of dissolution  of the  spilled  pollutant,
as well as the significance of the sorption and  diffusion  processes,  the
spilled pollutant may remain in the riverine system for  either an extended
or brief period of time.

     In contrast to high density pollutants, pollutants  with specific
gravities less than unity tend to at least partially remain on or near the
water's surface while undergoing dissolution.  For these pollutants,
volatilization and photolysis can be extremely important.   As the pollutant
is dissolved in the water column and moves downstream, dispersion becomes
important in attenuating the peak concentration.

     Pollutants which leach from a surface or subsurface disposal site may
eventually reach a river.  Although the mass input rate  may be low, the
source can be continuous and last for years, even after  cleanup of the site.

     The sequence of instream events following the initiation and then the
cessation of point sources of toxicants further illustrates the role that
sorption plays in governing fate of sorbates.  Figure IV-46 illustrates the
two situations.  Figure IV-46a shows the pollutant distributions below a
point source at two distinct times (ti and t2 where t2>  ti) following
initiation of the point source.  As the toxicant is discharged the water
column concentration (the sum of the dissolved and sorbed phases) abruptly
increases at the mixing location.  As the pollutant travels downstream, the
sorbate tends to partially desorb onto the formerly uncontaminated bottom
sediments.  Additionally there may be a net exchange between the bedded
sediments and water column sediments, even if there is no net deposition.
As a result of these processes, the water column concentration tends to
decrease in the downstream direction.  It may take a period of time greater
than t\ for the effects of the discharge to reach a distance D*.  Depending
on the distance, and on the rate of accumulation of the toxicant in the
bottom sediments, as well as on other factors, the time required for the
water column concentration to be noticeably elevated at  D* could greatly
exceed the travel time of the river over the distance.
                                    512

-------
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-------
     After the discharge of the toxicant has continued for a period of time,
the net exchange with the bedded sediment may diminish, so that the toxicant
concentration becomes constant over some distance both in the water column
and in the sediments.  This situation is illustrated by the solid curve in
Figure IV-46b.  Suppose at this time the input of the pollutant ceases.  The
water column concentration just below the point source tends to abruptly
approach zero.  As this happens, desorption of the toxicant from the bedded
sediment can occur, tending to replenish pollutant levels in the water
column, but to a lower level.   Gradually, the pollutant can be desorbed from
the bedded sediments at a given location so that the bottom sediments are
naturally cleansed, from the upstream to the downstream direction.   This
process can take many years and low levels of pollutant in the water column
can be detected throughout this period.   More discussion of this phenomenon
is provided later in Section 4.9.3 and Example IV-18.
4.9.2  Vertical Distributionof Sorbate within Rivers

     Even though most of the analytical tools presented later in Section
4.9.3 assume that, for simplicity,  suspended solids concentrations are
uniformly distributed throughout the water column,  in reality this is not
true.  The vertical distribution of solids depends  both on particle and
river characteristics.  Heavier particles (those with the greater settling
velocities) are transported closer  to the stream bottom while the lighter
particles are more uniformly distributed.  This observation is significant
because pollutants which sorb to the particles also exhibit a non-uniform
vertical distribution.  Pollutants  which do not sorb tend to become
uniformly distributed vertically, regardless of the sediment distribution.
By understanding this, the user can better interpret instream pollutant
data, particularly if the pollutant tends to reside as sorbate.  It may be
that a single pollutant sample is not sufficient to accurately characterize
the pollutant distribution, and in  fact could be misleading in terms of the
total burden of the pollutant carried within the water column.  Depth
integrated samples might be necessary to gain an accurate knowledge of the
pollutant's distribution.
                                   514

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     Figure  IV-47 shows the vertical distribution of suspended solids in an
equilibrium  condition.  The parameter shown in the figure is defined:
                                       Vs                            (IV-103)
where
     V  = settling velocity of suspended solids
     K  = von Karman's constant  (^0.4)
     U* = shear velocity = (g Ru S)°-5 , ft/sec
                               n
     g  = acceleration due to gravity, 32.? ft/sec2
     Ru = hydraulic radius of river,  ft
      n
     S  = slope, dimensionless.

Very small values of z represent clay-sized particles, while larger values
represent first silt, and then sand.   Figure IV-47  illustrates that clay
particles tend to be uniformly distributed vertically  (50 percent  in the top
half of the water column).  About 75  percent of silt and over 95 percent of
the sand particles (typically) reside in the bottom half of the water
column.  This suggests that in rivers  where the suspended sediments are silt
and sand, the sorbed pollutant distribution will be vertically skewed.  If
the suspended material is predominantly clay the sorbed pollutant
distribution will be uniform.  Since  pollutants tend to sorb to sand to a
lesser degree than to silt and clay,  the vertical distribution of  sorbed
pollutant will not be as skewed  as the suspended sediment distribution.

     Figures IV-48 through IV-49 show  the fraction of pollutant present as
solute (C/Ct) versus relative depth for families of z values and K Sa
values.  Sa is the suspended sediment  concentration a small distance above
the bottom.  For K Sa values less than 0.1, the sorbate concentration is
generally negligible compared to the  solute concentration regardless of the
depth or the nature of the suspended material.  For larger K Sa values, the
sorbate level can be important, depending of the nature of the suspended
material.   For extremely large K Sa values, the sorbate concentration will
greatly exceed the solute concentration, at least near the river bed.
                                     515

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                INCREASED SETTLING
                VELOCITY
    0.001
            RELATIVE SEDIMENT CONCENTRATION  S/Sa


FIGURE  IV-47   VERTICAL  EQUILIBRIUM DISTRIBUTION OF

                SUSPENDED SOLIDS IN A  RIVER
                             516

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      Based  on  the  hydraulic  characteristics of the river, characteristics of
 the material being transported  in  suspension, and the partition coefficient
 of the  pollutant,  predictions can  be made of the pollutant's distribution in
 the water column.  To  use  Figures  IV-48  and IV-49 requires knowledge of Sa,
 the suspended  solids concentration  at  a  distance n = a  above the bottom
 (where  typically a = 0.05, or 5  percent  of the river's  depth).  The
 equilibrium expression for suspended sediments, which is found in numerous
 sediment transport texts  (e.g. Graf, 1971) can be rearranged to express Sa
 as:

                           Sa = S("' (¥  I??)'                  (IV-104)

 where
      n  =   relative depth  above  bottom

 To use  this equation the suspended  solids concentration must be known at one
 depth in the water column.   Typically, a depth averaged suspended solids
 concentration might be readily available.  Under these  circumstances Sa can
 be estimated as:
                                 s
                            Sa = —1   ' ^a /                     (IV-105)
                                  /   l~~) c'n
where                             a

     S = depth average suspended sediment concentration.

The denominator of Equation IV-105 can be integrated numerically by one of
many available solution techniques (e.g. see Carnahan et_ _a]_., 1969).  For
the case when a  = 0.05 the relationship between Sa and S is given below:

                           z = 0.2—»-Sa = 1.8 S
                           z - 0.6—*-Sa = 4.4 S
                           z = 1.0—*-Sa = 8.2 S                   (IV-106)
                           z = 2.0—*-Sa = 17 S
                           z = 5.0—»-Sa = 20 S
                                     519

-------
Based on a knowledge of S, Sa can be estimated from Equation IV-106,  and in
turn can be used in Figures IV-48 and IV-49.

     Typically there is a segregation of particle sizes found in suspension
compared with these found in the bed load, and in the immobile bed
materials.  Based on these differences,  the following can be hypothesized:
                                Xs > Xbl
where
     X   = sorbed pollutant concentration on suspended materials, mass
           pollutant/mass sediment

     Xbi = sorbed pollutant concentration on bed load, mass
           pollutant/mass sediment

     X,-m = sorbed pollutant concentration on immovable sediment, mass
           pollutant/mass sediment.

Investigations carried out by Miles (1976) appear to support this
relationship.  Miles collected insecticide residues on stream sediments and
in the water column.  Results of the DDT analysis of Big Creek,  Norfolk
County, Ontario, 1973 (DDT was banned in 1970)  are as follows:
                      Concentration of DDT on Sediments
                   (rna_ss_ of pollutants/mass  of sediments
                     suspended  sediments  110 ppb = X
                     bed  load               76 ppb = X, ,
                     immovable  bed         26 ppb = X.
                                                      im

Miles (1976) also found that DDT transported in the dissolved phase ranged
from 10 to 92 percent of the total transported  in the water column.  This
finding is consistent with the results in Table 11-14 which shows that the
percent of pollutant transported in the dissolved phase can be  high even for
pollutants such as DDT as long as the suspended solids concentration is not
extremely high.
                                    520

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     Contaminant data collected in bedded sediments can be very
illuminating.  Although in a screening approach it is not anticipated the
user will go to the field to collect sediment core samples, some data might
be available.  Depending on the quantity of data available the following
types of information might be determinable:

     •   The spatial extent of contaminated sediments, and pollutant
         concentrations in the sediments

     •   The depth of contaminated sediment

     •   The quantity of toxicant contained in the sediment

     0   A time history of pollution levels to determine whether they
         are increasing or decreasing

     •   The probable sources of the pollutant, based on the location
         and quantity of contaminated sediments.

Although extensive sampling is required to accurately determine all of the
above items, such programs have been successfully accomplished.  For
example, an extensive sediment sampling program was conducted in the Hudson
River in New York to determine the sources of PCBs in the contaminated
sediments, and the degree of contamination (Turk, 1979).
4.9.3  Transport and Transformation Expressions for Toxicants in Rivers

     The tools presented in this section can be used to predict instream
concentrations of toxicants for a variety of different situations.
Specifically, the following scenarios are addressed:

     •   mixing zone analysis,

     •   continuous point source discharges,
                                    521

-------
     t   continuous nonpoint source discharges,

     •   desorption from bedded sediments,

     •   spills  and instantaneous release of soluble chemicals,  and

     •   spills  of high density chemicals which sink to the river bed.

     In contrast to many conventional organic pollutants which degrade into
innocuous substances, many toxicants are transformed to other chemicals
which can be as  harmful or more harmful than the original.  Consequently,
when toxicants are continuously discharged into a river, in addition to
predicting the concentration profile, it is useful to also determine:

     •   the pollutant's advection rate past a specified location,

     •   the pollutant's volatilization rate over a specified reach,
         and

     •   the pollutant's rate of transformation to other species over a
         specified reach.

The toxicant's fate is thus segregated into the processes of advection,
volatilization,  and transformation.

     In the following three sections on mixing zones, point sources, and
nonpoint sources, the user will find there are different methods of
approaching the problems.  One way to simplify the analysis is to first
assume toxicants act conservatively.  The user can then perform a first
level analysis to find out whether criteria are violated.  If they are not,
then a detailed analysis is really not required if the objective is to
determine criteria compliance.   If violations are predicted,  a more detailed
analysis of these "hot spots" can be performed by considering the various
processes affecting the toxicant in  the river.   This approach requires more
work, but by judiciously applying the tools available,  the analyses can be
expedited.
                                  522

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4.9.3.1  Mixing Zone Expressions

     Section IV-4.1.9 presented earlier delineated one- and two-dimensional
mixing zone expressions for conventional pollutants.  The one-dimensional
expressions need to be extended in order to differentiate between solute and
sorbate.  To do this, the following expressions for pollutant concentration
and the suspended solids concentrations are needed:
                             S  =   U   "    W  "-                      (IV-107)
                           r   = Cut Qu + Cwt Qw                     (IV-108)
                            to       Du + QW
where

     S  , C f = concentration of suspended solids and concentration of
               sum of solute and sorbate in the river above the
               location of mixing, respectively

     S  , C 4. = concentration of suspended solids and concentration of
      w   wt
               sum of solute and sorbate in the wastewater,
               respectively.

     S, C   = concentration of suspended solids and concentration of
               sum of solute and sorbate in the river following mixing,
               respectively.

The dissolved phase concentration, C, of the pollutant  at the completion of
mixing  is given by:

                                r -     to                           (IV-109)
                                L " 1 + k   S
                                         P
where
                                     523

-------
     C    and S are found from the two previous expressions.
      to

The concentration of the solute following mixing depends on characteristics
of the waste source, the river's flow rate, and the suspended solids
concentration in the river and waste source.  The solute concentration might
also change after mixing with a tributary of very high suspended solids
concentration (high SJ, even if it contains no additional pollutant
(Cwt=0).

     Equation IV-108 is particularly useful because it predicts the total
instream concentration of toxicant following initial mixing.  This is often
the critical test in establishing whether or not water quality standards are
violated by a point source.

     In cases where initial mixing is incomplete (that is the waste is
initially diluted with a fraction of the total river flow), the
two-dimensional  mixing equation shown earlier as Equation IV-4 will more
accurately predict C tQ.  Then Equation IV-109 can be used to find the solute
concentration.

     When there are numerous discharges of the same toxicant, analysis
becomes more complicated.  The most straightforward method of handling this
situation is to sequentially apply Equation IV-108 to the series of
discharges to find the concentration as a function of distance downstream.
If the solute concentration is needed, then sequential application of
Equations IV-108 and IV-109 is required.

     The analysis of multiple point sources can be simplified in one of two
ways.   One, the sources can be transformed to an equivalent nonpoint source
by assuming that the toxicant input is uniformly distributed between the
series of point sources.  This approach is discussed in Section 4.9.3.3.
Two,  a series of closely grouped point sources can be handled as an
equivalent point source.  The equivalent point source has a flow rate equal
to the sum of the flow rates from the individual plants,  or:
                                      524

-------
                               Q  =  £  Q  .                        (IV-110)
                                w   /r',  xwi

where
     Q .  = flow rate from i;th treatment plant
      W1
     n   = number of treatment plants being grouped

     The total pollutant load can be expressed in one of two ways.  If the
concentrations in the wastewater are known then the total loading is:

                             C   Q  =  £  C .  Q .                     (IV-111)
                             u  xi.i    *—'   un  xun                     *      '
                             W  ^W    .~,   Wl
where
     C .  = concentration of toxicant in effluent of ith plant
      wi                                              —

If the mass emission rates are known instead then:

                               C  Q  =  £ M.                       (IV-112)
                                w  w   £j^
                                        5.38
where
     M- = mass emission rate of toxicant from ith plant is Ibs/day.

The conversion factor 5.38 converts mass emission rate in Ibs/day to flow
units in cfs and concentration units in mg/1 (ppm).

     The grouping procedure described above has been applied by the
U.S. Environmental Protection Agency (1981) to a case study in Indiana to
evaluate the economic impact of toxicant standards.  Numbers of point
sources were grouped together using a procedure called cluster analysis.
The cluster analysis added the loadings of major and minor industrial
dischargers within a ten-mile radius of each other.  Ten clusters were
identified and few violations occurred within them once the best available
technology was attained.
                                     525

-------
     For certain applications the object of using a mixing zone equation is
to directly find the maximum allowable concentration in the discharge so
that the receiving water criteria are not violated.  Under these
circumstances Equation IV-108 can be rewritten as:
                                   (Q   + Q )
                               CTC  ~^Q     ' when Cut
                                        w
where
     (C .)    = maximum allowable concentration of the toxicant in the
       wt max
                waste discharge so that the water quality criterion is
                met under critical conditions.
      C.      = water quality criterion for the toxicant

      Q       = critical river flow rate (e.g. 7Qio)

Equation IV-113b is applicable when the concentration of the toxicant is
zero upstream of the discharge point.
4.9.3.2  Point Source Discharges

     For point sources of toxicants, the pollutant interactions depicted in
Figure IV-50 are simulated.  While transformation of toxicants is generally
more complex than this, in many instances these interactions are sufficient
to analyze the instream processes affecting not only point source discharges
but also nonpoint source discharges, and instantaneous releases of soluble
pollutants.  Figure IV-50 reveals that:

     •   The solute only is assumed to volatilize.
                                     526

-------
  V
FIGURE IV-50   INSTREAM TRANSFORMATION PROCESSES
               ANALYZED FOR TOXICANTS,
                   527

-------
     •   First order transformation processes degrade only the solute.

     •   Adsorption and desorption are assumed to occur at rates much
         faster than other processes.

     •   No interactions with the bottom sediments occur (this is
         analyzed in later sections).

Based on these interactions, the concentration profile below a point source
of toxicant is expressible as:
where
     C   = concentration of dissolved phase of the toxicant at a
           distance x below the point source

     C   = concentration of the dissolved phase of the toxicant at
           x = 0 (after the point source discharge has mixed with the
           river water)

     k '  = k /D
      v     v

     D   = water depth

     k.  = individual first order decay rates which are transforming
           the toxicant (other than volatilization)

     P   = partial pressure of the toxicant in the atmosphere above the
           river,

and the remaining variables have previously been defined.  Typically the
partial pressure is zero, so that Equation IV-114 simplifies to:
                                     528

-------
C = CQ exp
The  initial dissolved phase concentration is given by:
where
                                 C  =
                                      1 + V
                                                                    (IV-115)
                                                                    (IV-116)
     C    was defined by Equation IV-108
      to
The total pollutant concentration, C. , at any location is:

                             Ct = C (1 + K S) ,
                                             (IV-117)
The  sorbed phase concentration expressed as mass per unit volume of water
is:
                               cs = ct  - c  .
                                             (IV-118)
and the sorbed phase concentration expressed as mass per unit mass of
sediment is:
                                  X -  K C
                                       P
                                             (IV-119)
     The most direct application of Equation IV-114 or IV-115, plus
Equations IV-117 through IV-119 is to find the instream concentration as a
function of distance below the point source.  There are, however, other uses
of the expressions.  Consider Equation IV-115, for example.  The ratio C/CQ
can be directly calculated as a function of distance.  Thus the fractional
dissolved phase concentration can be calculated without ever knowing the
initial concentration C .  This approach has the advantage of requiring less
data.  Similarly, the fractional concentration can be calculated for any
specified distance, such as the end of a reach.  Or, the distance x can be
found so that the fractional concentration is some specified number, which
may relate to an acceptable level of toxicant.  The length of river
subjected to unacceptable levels can then be found.
                                    529

-------
     The user might additionally want to know the distribution of pollutant
fluxes in terms of advection (Mg),  volatilization (My),  and transformation
(NL).  Expressions for these are presented for the case  of P = 0.  These
formulae allow the user to predict  the fluxes associated with the point
source discharge where volatilization is not altered by  a background
concentration in the atmosphere.  Under these conditions:

                              ft = Ma + MV + ftt                      (IV-120)

Equation IV-120 states that the rate of entry of the toxicant into the river
(M) equals the rate of advection of that toxicant past some location x ,
plus the rate of volatilization across the water surface between the
discharge location and some other specified location plus the rate of
transformation of the toxicant to other substances within the water column
between the same two locations.  By knowing expressions  for each of M , M ,
and M. the user knows the major processes controlling the toxicant's fate
within any reach of river.

     The mass flux advected past a  location x  is given  by:

                      Ma =  (Qu + Qw) C +  (Qu  +  Qj  Cs              (IV-121)

where the concentrations C and C  are evaluated at x = x .  The
volatilization mass flux is given by:
Mv = Ac kv Cc
U (1 + K S)
                                                        P
where
l~e*p  rOlTTTr
                                                         <  xi
                                                         S) Xs I
                                            (IV-122)
     A  = cross-sectional area of river
      c

and all other terms have previously been defined.  In some cases the user
might have an estimate of the average dissolved phase concentration, C,
within the reach under consideration.  Under these circumstances the
volatilization flux is simply:
                                    530

-------
                 ky C
                                                                    (IV-123)
where
     A  = surface area of the reach under investigation.
      o
The transformation mass flux is expressible as:
      Mt • Ac
U (1 +
              1-exp
                                                k;
U (1 + KpS)   s
                                              (IV-124)
Since the sum of Equations IV-121, IV-122, and IV-124 equals the mass
emission rate of the toxicant, Equation IV-120 can be used to double check
the fluxes calculated.
4.9.3.3  Nonpoint Source Discharge

     This section parallels the previous section on point source discharges
by presenting expressions for the steady-state concentration profile, and
for mass fluxes.  In addition to applying this methodology to a nonpoint
source, another and possibly more useful application is to express a series
of point sources as an equivalent nonpoint source.  The equivalent nonpoint
source discharge rate is simply the sum of the discharge rates of the
pollutant from all the point sources.  This approach is not as accurate as
analyzing each point source individually but is much faster depending on the
number of point sources.  For example, suppose a river segment has ten
separate point sources located within 50 miles of each other.  The most
rigorous analysis would consist of considering each point source
individually, where mixing zone and point source equations are applied
sequentially ten times each.  This obviously is a great deal of work for a
hand calculation approach.  By considering these point sources as a single
equivalent nonpoint source, a single equation application is sufficient to
analyze the problem.  Example IV-5 shown earlier in the BOD section
illustrates this procedure.
                                     531

-------
     The solute  concentration in a river  resulting from a steady nonpoint
source of toxicant  is:


                    '•**(°.*fc)(^)*
where
           1 + K S
     k   = —J—P—  m
         = k2 + k;
          = total concentration of toxicant  in nonpoint source
     m
             xi
     Qf   =  river flow rate at end  of  nonpoint source
     Q0   =  river flow rate at beginning of nonpoint source
     x-|   =  length of nonpoint source.

Equations  IV-117 through IV-119 can be  used to find Ct,  Cs, and  X,
respectively.

     In a  manner similar to point source discharges, Equation  IV-120 which
expresses  the mass balance between  toxicant inflow rate  to the river and
loss rate  by advection, volatilization, and transformation, is valid.  The
appropriate  expressions are (when P = 0):
                    =   (Q0+mx)C   +   (Q0+mx) CkpS  , at =  x$
                        ••—•*** - !_,. •**      ... ,—	^ '— —
                       solute          sorbate
                    transport        transport
                                   532

-------
for the advective flux.  For the volatilization flux
                                                                    (IV-127)
For the transformation flux:
                                                                    dV-128)
As a first cut analysis, the user might want to assume that the toxicants
act conservatively.  If criteria are not violated under these circumstances,
then criteria will not be violated if decay or transformation processes are
included.
4.9.3.4  Desorption of Toxicant from a River Bed

     Because many toxicants are transported as sorbate rather than as
solute, a significant fraction of the pollutant which enters a riverine
system can ultimately be deposited in the bedded sediments.  If the toxicant
is resistant to degradation processes it can remain in the sediments for
extended periods of time.  During this time, the toxicant can slowly be
desorbed back into the water column or scoured into suspension.
     Figure IV-46 shown earlier illustrated an idealization of the process
of desorption of a toxicant from bedded sediments.  The process can be
described as follows.  Supposed the average concentration of the pollutant
in the bedded sediment is X  when the analysis begins (called t = 0).  The
concentration X, at any later time is estimated from mass balance
considerations as:
                        X   =
                                      for x  > k
(IV-129)
                                      otherwise
                                     533

-------
where
     X  = concentration of pollutant in bed at some time t = 0
     M  = mass of contaminated  sediment per unit  area of river  bed,
          g/cmz
     U  = stream velocity, cm/sec
     6  = equivalent depth of water in sediment M , cm
     K  = partition coefficient

Equation IV-129 reveals that desorption can be interpreted as a frontal
phenomenon where desorption is completed at one location before progressing
downstream.  Based on this interpretation, an effective removal velocity of
the front is:

                                 Ue  -  {Li-                       (iv-130)
                                          S  P
The time T. required to desorb the toxicant over any specified distance is:

                                 Td  =  XL/Ue                          (IV
where
     x  = length of contaminated river segment

During the period of desorption the average concentration in the water
column is:
                         C  =
-2- for x> U t                       (IV-132)
KpD
0   , otherwise                      (IV-133)
     To use Equations IV-129 through IV-133,  estimates for XQ,  M$, and 5 are
required.  If both the mass of contaminated sediment per unit area of river
bed (M ) and the mass of toxicant in the sediments are known, then XQ can be
determined.  Conversely, if both XQ and the total  mass of toxicant in the
sediments are known, then M  can be calculated.
                                    534

-------
     In lieu of having data on M  and 6, these quantities can be estimated
based on the depth of contaminated sediments by using Table IV-39.   In
addition to the depth, the percent solids by weight must be estimated.  This
parameter generally increases with depths and can be chosen as 50 percent,
unless better data are available.  The data in Table IV-39 were derived from
the following two equations:
                                      Dc
                                                 -^                  (IV-134)
and
                           6   -   ~S    C}^n(                    (IV-135)
where
     MS = mass of contaminated sediment, g/m2
     6  = equivalent water depth, mm
     S  = specific gravity of solids
     D  = depth of contamination, mm

In cases where the depth of contamination exceeds 100 mm the equations can
be used in lieu of Table IV-39.

     The Hudson River in New York State provides an illustration of an
extreme case of PCB contamination (Turk, 1980).  Between 1951 and 1977 PCBs
were discharged from point sources near Fort Edward and Hudson Falls, about
80 km (50 mi) above Albany, New York.  Figure IV-51 shows the general
vicinity.

     During this time period the mass emission rate of PCBs decreased from
15 kg/day (33 Ibs/day) to less than 1 g/day (0.002 Ibs/day).  PCB
concentration in the bottom materials range from about 200 yg/g near Fort
Edward to about 4 yg/g near Waterford, about 70 km (43 mi) downstream.  In
1975 the New York State Department of Environmental Conservation began a
study to determine the source of contamination.  At that time they estimated
that the total mass of PCBs in the bottom sediments was 225,000 kg
(500,000 Ibs).
                                     535

-------
                    TABLE IV-39
MASS OF CONTAMINATED SEDIMENTS AND EQUIVALENT WATER
   DEPTH AS A FUNCTION OF DEPTH OF CONTAMINATION
Depth (mm) Percent Solids by Weight
1 20
50
80
5 20
50
80
10 20
50
80
20 20
50
80
50 20
50
80
100 20
50
80
Ms (g/cm2)
0.02
0.06
0.11
0.11
0.30
0.55
0.23
0.60
1.1
0.45
1.2
2.2
1.1
3.0
5.5
2.3
6.0
11.0
6 (mm)
0.9
0.6
0.3
4.5
3.0
1.4
9.1
6.0
2.7
18.
12.
5.5
45.
30.
14.
91.
60.
27.
                          536

-------
                              Hudson
                             i. Falls

                               Fort
                               Edward
N
     0   5   10   15 KILOMETERS
FIGURE  IV-51   LOCATION MAP  OF  HUDSON  RIVER,
                NEW  YORK,
                   537

-------
     It has been found that PCBs are being naturally desorbed from the river
bed under moderate and low flow conditions.  The estimated transport rates
are:

     •   at Glen Falls     =  0.0 kg/day (above discharge)
     •   at Schuylersville =  4.0 kg/day
     •   at Stillwater     =  5.0 kg/day
     •   at Waterford      =  4.0 kg/day (70 km downstream)

It is interesting to note that these transport rates are approximately 30
percent as high as the original point source mass emission rates.  At a
desorption rate of about 4 kg/day, the river between Glen Falls and
Waterford would be rid of PCBs in about 150 years.

     Turk (1980) found that flood events transport large quantities of PCBs,
although this transport mechanism is only operative periodically.  Turk
estimated that due to the combined removal rates of PCBs during high flow
periods (by scour) and during low flow periods (by desorption), the
residence time of PCBs above Waterford would be about one century.
                              •EXAMPLE IV-18
For discharges of 600 m3/sec or less, it has been found that the Hudson
River bed provides 4 kg/day of PCBs to the water column at locations between
Schuylersville and Waterford, New York.   Determine the PCB concentration in
the water column at the following two flow rates:

                              a.  600 mVsec
                              b.   50 m3/sec.

Compare these concentrations to the freshwater criterion of 0.001 yg/1
promulgated in the "Red Book".

     Since the mass emission rate and river flow rate are known,
Equation IV-11 can be rearranged to yield the total instream concentration:
                                         M
                                 Ct  = 86".~4Q
                                    538

-------
where
                         M  = mass  loading,  kg/day
                    C.  = concentration of pollutant,  ppm
                     L
                           Q  = flow rate, m3/sec
For the problem at hand,
                                M = 4 kg/day
                           Q = 50 and 600 m3/sec
For Q = 600 m3/sec,

                     4
                            =  °-08 x  10"3
               - 0.08 iig/1, or  80  times the Red Book criterion

For Q = 50 rnVsec,

           CT s 86.Tx~50  =  °'9  X  10"3  Ppm
              = 0.9 yg/1, or  900 times  the criterion


     As a second part to the problem estimate the time required to remove
the PCBs in the sediment by desorption (ignoring scour), assuming the
desorption rate of 4 kg/day is not  known.   Base the calculations  on Table
IV-39 or Equations IV-130 and IV-131.  Use the following data:

     •   depth of contaminated sediment = 600 mm

     •   river velocity = 1 fps

     •   partition coefficient :  103 to 10"

Because the depth of contamination  exceeds the maximum value tabulated in
Table IV-39, Equations IV-134 and IV-135 are used instead.   Assuming
S  = 1.5 and P = 80,
                                     539

-------
1 1.5
\
                                               -  65 9/cm2
                             10 1  1.5      80
                               \
                          -  1.5  x  600
                          ---
         /      \
         (100-80)
         V  80  / _ 1Cn mm _ 1C
         100-80\  " 16° m ~ IB cm
1 + 1
                                      /100-80\
                                   .5  (   80  j
The effective transport velocity is:
                 Ue = eH-lf* = '25 X ^ U   f°r KP ' 10'
and
                               - -25x10- u   forKp=103

The time required for desorption over  the  70  km  (43 mi) reach  is:

            T = .253x"lO->0x 1 Sec ' 29°

and
                         T = 29 years  for K  = 103

Probably the biggest unknown in this problem  is  K  .   Based on  a range of K
from 103 to 104, the time of desorption  ranges from 29 to 290  years, within
the range predicted from observed desorption  rates.

- END OF EXAMPLE IV-18 -
4.9.3.5  Instantaneous Releases of Low Density Toxicajrts

     Many toxicants have specific gravities  less  than  or  equal  to  unity.
Should a toxicant less dense than water be  spilled  in  its pure  form,  the
toxicant can ride atop the water body for a  period  of  time, while  (perhaps)
being rapidly volatilized and photolyzed as  it becomes entrained and
dissolved in the river.
                                     540

-------
     Analysis of releases of low density pollutants is complicated and, in
many cases, beyond the scope of hand calculation analyses.  Often spills of
toxicants occur over a part of the river, so the resultant movement is
three-dimensional because the toxicant spreads laterally, longitudinally,
and vertically due to turbulence and advection.  Buoyant spreading and
mixing can further complicate the dispersal process.

     Toxicant spills can occur in numerous ways.  In one instance the
toxicant may be discharged directly onto the surface of the river, and
depending on the rate of mixing with ambient water a significant portion
could volatilize directly from the pure phase.  On the other hand submerged
spills may result in the chemical becoming mixed with river water before it
reaches the water's surface.  Under these circumstances volatilization
fluxes will not be as great.

     When a chemical is spilled in pure form, the time required for the
chemical to mix with the river water depends, in addition to other factors,
on the solubility of the chemical.  Some chemicals may be highly soluble in
water (essentially infinitely soluble) while others may have a very low
solubility.  Figure IV-52 illustrates these two different situations.

     Figure IV-52a shows the case of a toxicant of infinite solubility.  The
toxicant maintains its pure state (mole fraction equals unity) for some
distance away from the spill site, and then the mole fraction gradually
begins to decrease as the chemical mixes with water.  Figure IV-52b
illustrates the same basic situation, except that the toxicant has a finite
solubility.  In this case there will be a rapid drop between the mole
fraction of the pure toxicant (unity) and the mole fraction at solubility
(much less than unity).   For the pure phase toxicant shown in Figure IV-52b
to become mixed in water at concentrations at or below the solubility limit
might require a substantial amount of water.

     Based on the discussions in the previous paragraphs, tools for analyses
of the following will  be presented:
                                   541

-------
           1.0
MOLE
FRACTION    0.1
          0.01


           0.0
MOLE
FRACTION
               PURE
               CHEMICAL
                          (a)
 1.0

 0.1



0.01


o.o
               PURE
               CHEMICAL
              Solubility
                                 INFINITE SOLUBILITY
                                FINITE SOLUBILITY
                Distance from Spill Centerline
                          (b)
 FIGURE  IV-52    HYPOTHETICAL CONCENTRATION DISTRIBUTIONS
                  OF FINITELY SOLUBLE AND  INFINITELY
                  SOLUBLE  TOXICANTS,
                              542

-------
     •   Volatilization mass flux from a pure toxicant contained within
         a fixed area.

     •   The fate of a highly soluble toxicant which mixes
         instantaneously with the river water.

     •   The fate of a low solubility toxicant which mixes with a
         finite volume of river water.

Toxicants which exist in the gas phase under atmospheric pressure and
typical natural temperatures are excluded from analysis here, even though
they might be transported as a liquid under high pressure (e.g. liquified
chlorine).  If a tank transporting such a chemical were to rupture under
water, the chemical would boil and most of the gas would rapidly escape into
the atmosphere.  Some of the gas would however become dissolved in the river
water during ascent of the bubbles.
4.9.3.5.1  Volatilization of Toxicant in Pure State

     This section will present a method to predict the volatilization mass
flux rate of a pure chemical, and the time required to volatilize a known
amount of the chemical which occupies a specific area of river surface.  The
volatilization flux rate is given by:

                                     MW   k   • P   • MW
                                                                     IV-136
                                    _   _ __ _
                              RUT           82.136  T
where

     F  = volatilization mass flux, g/cm2/hr
     P  = saturation vapor pressure of
     MW = molecular weight of toxicant
P  = saturation vapor pressure of pure liquid toxicant, atm
     T  = temperature of ambient water, K
     k  = gas phase transfer coefficient, cm/hr.
                                     543

-------
The expression for the gas  phase  transfer  coefficient was shown earlier in
Equation 11-46.  A suggested  default  value is  3000 cm/hr.  The saturation
vapor pressure of a number  of toxicants  were shown earlier in Tables  II-5
through II-9.   Weast (1969)  also contains extensive data.

     Based on the amount of pure  toxicant  (M)  contained within a  spill area
(A), the time required to volatilize  the chemical  is:

                              * - icnrnnr                        {IV-137)

where

     t = time, hr
     M = mass, kilograms
     A = area, m2

This expression is limited  to situations where the spill  area A  is  of
constant size over the period of  volatilization so it  is  not applicable to
unconfined spills where the area  could change  rapidly  with time.


4.9.3.5.2  Analysis of Chemicals  Which Instantaneously_M ix

     Depending on the mass  of spilled toxicant and its solubility,  the
spilled toxicant may rapidly attain concentrations in  the water  column below
solubility.  Under these circumstance, Equation IV-138 presented  below can
be used.  The analysis below assumes  that  Henry's  Law  is  valid  (e.g.  the
mole fraction of dissolved  chemical is much less than  1.0) which  is
reasonable for many toxicants only moments after a spill.

     It is worthwhile to calculate the volume  of water required  for a mass  M
of spilled chemical to be diluted to  its solubility  limit.   This  can  provide
a rough idea as to whether  mixing is  likely to be  "instantaneous" or  not.
Suppose that a mass M of spilled  chemical  has  a solubility C$.   The volume
of water needed to be mixed with  the  pure  chemical so  that the  solubility
limit is achieved is:
                                    544

-------
                                V  =  -A-                           (IV-138)
                                 0     Cs
where
     M  = mass of spill , kg
     C  = solubility, mg/1
     V  = volume of water, m3

     The concentration profile resulting from an instantaneous spill (and
assuming concentrations at or below the solubility limit are rapidly
attained) is expressed by:
                                                                    ( IV-139)
where
     C  = dissolved phase concentration
     k  =
      e    1 + KpS
             M
     M  = total mass released

and the remaining variables have been previously defined.  In most instances
the user would like to predict the maximum concentrations remaining in the
river for different elapsed times following the spill, given by the peaks in
Figure IV-53.  Under such conditions, and assuming P = 0, Equation IV-139
simplifies to:
                                    L)         f I  4- \
                                                                    (IV-140)
     The various components of the mass balance at time t  follow (for
P = 0).
                Mass of dissolved pollutants  Mp (t = t )_
                         MD(t  =  ts)  = MD exp (-kets)
                                     545

-------
tn
                                                        CD
                                                        c:
                                                        33
                                                        m
                                                    o  -<
                                                    O  -D
                                                    >  o
                                                    H  H
                                                    •—  X
                                                    o  m
                                                        O
                                                    -n  >
                                                    o  r-
o  --
s:  v>
—  H
z  ^3
CD  •— •
    &
>  cr

oo .-
-D  O
                                                        o
                                                        X
                                                        I—«
                                                        o
                                                        o
                                                        c:
                                                        C/)
o

en
                 o



                 CD
                 CD
                 CQ
                                                                     CQ
                                                                     CO
                                                                     •o
                                                                         Cn

                                                                         °
                                                                         8
                                                                                             Concentration^ (PPB)

                                                                                     Cn         O         oi          O

                                                              8
                                                              |

                                                              co
                                          8
                                                                                    ro
                                                                                    o
                                                                                    o
                                                                                    CD
                                                                                    en

-------
                  Mass of  sorbed po Hut ants  Mg (t = tg )  :

                           Ms = KpS MD exp(-kets)                   (IV-142)

           Mass  of pollutant which has volatil ized  M .  (t = t^ )  :
           „ - , . ---- — _        .
                      Mv 
-------
4.9.3.6  Spill Analysis of High Density Toxicants

     Spills of hazardous chemicals have been of concern for quite a number
of years, and interest will increase as the quantity and variety of
toxicants transported increase.  In past years the primary emphasis has been
on analysis and containment of oil spills.  This has probably been for a
number of reasons:

     •   Large quantities of oil are transported, and are therefore
         subject to more frequent spills.

     •   The environmental consequences of an oil spill can be severe
         and visually offensive.

     •   Oil floats, so oil spills are easy to detect and monitor.

     In contrast to oil, many hazardous chemicals have specific gravities
greater than one, so that in their pure form, they tend to sink in water.
Table IV-40 lists some such chemicals.  Chlorine, although it may be
transported under pressure as a liquid, is a gas under atmospheric
conditions.  Even so, if a liquid chlorine barge were involved in an
accident on a river some of the chlorine could become dissolved in the water
since the solubility of chlorine in water is 50,000 mg/1, although most
would probably gasify and form a toxic cloud.

     The chemicals shown in Table IV-40 are generally either slightly
soluble (10 to 10,000 ppm) or soluble (10,000 to 1,000,000 ppm).   In any
case the solubility levels generally exceed or greatly exceed proposed water
quality criteria.  Thus if a mass of chemical were spilled into a river,  it
is to be expected that concentrations near the chemical's solubility limit
could be detected in the immediate vicinity of the spill.  As the chemical
is dissolved and travels downstream, it could eventually become mixed over
the channel cross-section and expose all organisms living within  the water
column (and perhaps those living in the bedded sediments as well) to its
effects.  With increasing distance the concentrations of the toxicant will
decrease to reflect the additional mixing afforded by the flow of the entire
river, plus dispersion, degradation, and volatilization processes.
                                      548

-------
                          TABLE  IV-40
WATER-SOLUBLE,  HIGH DENSITY  (p>l),  IMMISCIBLE CHEMICALS
Species
Acetic acid
Acetic anhydride
Acetophenone
Aniline
Benzaldehyde
Benzyl alcohol
Bromine
Carbon disulfide
Carbon tetrachloride
Chlorine (liquid)
Chloroform
Chloropthalene
Dichloroethane
Ethyl bromide
Ethyl ene bromide
Furfural
Glycerol
Hydrogen peroxide
Mercury
Naphthalene
Nitrobenzene
Phenol
Phenylhydrazine
Phosphorus trichloride
Trichloroethane
N-Propyl bromide
Quinol ine
Tetrachloroethane
Waterb
Density
in air
(g/cm3)
1.06
1.087
1.03
1.022
1.04
1.043
2.93
1.26
1.595
3.2
1.5

1.256
1.431
2.18
1.159
1.26
1.46
13.54
1.15
1.205
1.071
1.097
1.5
1.325
1.353
1.095
1.60
1.00
Solubility a
in water Interfacial Tension (dynes/cm)
(mg/1) Air Water Vapor
50,000 68.0,no ,, o
JU " C 1 . o^rjo
500,000 - - 32.720c
5,550 - - 39.8200
34,000 44.0 - 42.92QO
1,000 40.04 15.51200
46,000 39.02QO 4.7522 50 39.02C)0
41.700 41.520<> - 41.52QO
2,200 - 48.362Qo
500 - 45200 26.952[)0
50,000 - - 18-420°
5,000 27.142QO 32.82QO
40.74200
9,000 23-4350
10,600 - 31.2200 24.1520o
4,300 - 36.542[)0 38.3720o
83,100 43.5,no - 43.5,no
C\J C\J
63.4180
50,000 - - 76-liQ 2°
.0005 470 37520°
"5H ?P C 9Q Q
JU tti.tt^jo ~ ^o.B.|270
1900 43.92QO - 43-920°
67,000 40.92()0 - 40.02()0
46.12QO
50,000 - - 29.12QO
10 22H40
2,500 - - 19-652()0
60,000 45.02QO
3,000 36.322 50 -
N.A. 73.05]go N.A. 72
 In air, water, and its  own vapor.  Temperature is  °C.

 Under pressure.

 Mercury and v/ater data  included  for reference.

From:  Thibodcau* (1979)
                                   549

-------
     A technique is presented here to estimate the concentration which can
exist in the water column and the duration of the elevated levels following
a spill.  In particular tools are presented to predict:

     t   The concentration of toxicant in the water column at the
         downstream end of the spill.

     •   The concentration of the toxicant after it has become
         completely mixed with the entire river.

     •   The time required to dissolve the spilled toxicant.

     •   The amount of toxicant remaining sorbed to the bottom
         sediments and in the pore water following dissolution.

It is, of course, more accurate but more costly to measure concentrations
directly rather than predicting them.  However, since the toxicant is
"somewhere" on the river bottom,  and might not be immobile, detecting the
location of the toxicant will take time.  By estimating the dissolution time
of the spill, it can be determined if it is feasible to even  set up and
carry out a sampling program.

     The tools delineated above are useful not only to analyze spills which
have occurred, but also for answering hypothetical questions  which relate to
the consequence of spills based on river traffic, sizes of containers, kinds
of toxicants being transported, and characteristics of the rivers.  Based on
this information the user can evaluate possible "spill scenarios" to predict
impacts before they occur.  Such information would be useful  to  formulate
post-spill  responses.   In situations where a spill of a toxicant would
produce extreme consequences, provisions could be made to mitigate the
consequences before they occur.
                                     550

-------
4.9.3.6.1  Description of Spill Process

     Spills which contaminate rivers can be the result of a variety of
accidents:  leaking barges, broken pipelines, highway accidents, and
clandestine dumping.  The scope here is limited to those situations where
the toxicant has been deposited on the bottom of the river.  This situation
is most likely to result from an accident on or under the water's surface.
Figure IV-54 conceptualizes what might happen when a barge carrying a high
density pollutant ruptures.

     Depending on the volume of contaminant, the size of the hole, among
other factors, the toxicant might issue from the barge as a continuous jet.
However, because the volumetric flow rate of the jet is probably small, and
perhaps even intermittent, the toxicant probably breaks up into drops of
various sizes as it falls through the water column.  Some of the finest
drops might never reach the stream bed, but rather be transported in
suspension within the water column, and gradually dissolve.  The majority of
the toxicant may settle on the river bed and form drops, globs, or pools
(using the terminology of Thibodeaux, 1979).  The drop size depends on the
intrafacial tension and density differences between the toxicant and the
water (Hu and Kintner, 1955).  Pools tend to form in the valleys of sand
waves, and occur when large drops or globs coalese.  Thibodeaux (1980)
provides techniques to estimate the residence time of drops, globs, and
pools.  For the simplified analyses here the spill is assumed to be in the
shape of a continuous pool.
                                       551

-------
                                                             Barge
      River bottom.
      sand dune-
                          "Water column
                          -velocity profile
                            Medium  drops
                                          .Fine drops
/i me UIU^ION        .... -.
I          *       ".'.'".
V         ."-• •-••.-••• •••.-.•  •
v   .  •-. -  —.•—..• •
 A .-.•-....•;•:  . .-• •••
,-•••••:•••••:.'  r».**
      crest and valleys.     ——
Large drops
                 W//////77fr/7//77W/7/7v7777////////y/7777Zw
Envelope of zone of contamination/     Droplet     Droplet-glob     Pool
                                                           zone
                                      zone
                                                  zone
   FIGURE IV-54    ILLUSTRATION  OF  HYPOTHETICAL  SPILL  INCIDENT
                      (FROM THIBODEAUX,  1979),
4.9.3.6.2  Fate  of  Pollutant Following Settling

     Once the  toxicant  has  settled on the river bed its fate is governed  by
numerous processes.   Depending  on  the texture of the bottom materials
(e.g. sands, cobbles, boulders), the density of the toxicant, and  its
interfacial tension,  the  toxicant  could settle in deep depressions, and
dissolution would be  slowed.

     Many pollutants  have large partition coefficients so that sorption to
bottom sediments is significant.   The characteristics of the sediments
affect the partition  coefficient,  but in many cases sorption can compete
with dissolution as a major  process  controlling the pollutant's fate.
Although transformation processes  other than sorption and dissolution are
operative the moment  the  toxicant  enters the water, they are not considered
here.
                                      552

-------
     In September 1974 an electrical transformer being loaded onto a barge
fell into the Duwamish Waterway in the State of Washington (Thibodeaux,
1980).  260 gallons of Aroclor 1242, a PCB mixture of specific gravity 1.4,
were spilled into the river.  Divers observed that pools of free PCB on the
bottom moved back and forth with the tide.  Pools of PCBs were removed from
the bottom using suction dredges, and a second stage operation involved a
high solids dredge.  Probably due to its low solubility (0.2 ppb) and high
sorption characteristics, much of the PCB was recovered (from 210 to
240 gallons).
4.9.3.6.3  Predictive Tools

     It is hypothesized that a toxicant spill contaminates an area of width
W  and length L , where the length is measured in the flow direction.  The
toxicant which reaches the river bed is assumed to be highly concentrated,
and its dissolution is controlled by a thin layer immediately above where
molecular diffusion limits the vertical flux of the pollutant.  Above this
layer the toxicant is rapidly entrained into the river.  There are several
expressions available to determine the thickness of the diffusion layer
(e.g. Novotny, 1969 and Mills, 1976).  The expression developed by Mills
will be used here, because the required information is easier to attain
while the two approaches appear to give comparable results.  The expression
is:
                              11.6 • 1.49 v R,  V6
                         6  = 	_	_J!	                  (IV-147)
                          "         vg (Jn
where

     6, = thickness of diffusive sublayer
     v  = dynamic viscosity of water
     R,  = hydraulic radius of the river
     U  = river velocity
     n  = Manning's coefficient
                                     553

-------
Just downstream from the spill  zone,  but  before  complete mixing with the
river, the concentration of the toxicant  in  the  water  column  is:
                     CL = (CQ-CS) exp  ^-^JLj +  cs               (IV-148)
where
     C   = background concentration of chemical
     C   = solubility of chemical  in water
     D   = diffusion coefficient of chemical  in  water
      cw
     H   = water depth
     U   = river velocity
The concentration at the location of complete  mixing  is

                        CWM = CLT+ co(1  -Ir1                  {IV-149)
where
     W  = spill width
     W  = river width
The time T.  required to dissolve the chemical  is:

                                Td = r-Ju-                         (IV-150)

where
     M  = total amount of pollutant  which  is  dissolved  (an  amount  less
          than or equal to the amount spilled).

     As the spilled toxicant dissolves in  the flowing river water,  it
concurrently diffuses into the immobile bedded sediments, where  a  portion  is
sorbed onto the sediments.  Consequently,  some residual  toxicant will remain
in the bottom sediments following the initial dissolution phase.  The
residual will then slowly diffuse and desorb  back  out  into  the river,
although diffusion deeper into the sediments  can  also occur because of  the
concentration gradient.  The time required for the residual toxicant to
                                     554

-------
naturally desorb and diffuse back into the water column can greatly exceed
the original period of dissolution.

     The quantity of toxicant which resides in the sediments following the
initial dissolution period can be predicted as follows.  It is assumed that
the dissolution and downward diffusion/sorption proceed independently until
all the spilled toxicant has been removed.  The time t can be found such
that this statement is true.  From a practical standpoint, the user can
simply determine the time required for complete dissolution, and then find
the total mass which would have diffused/sorbed into the bottom sediments
during this period.  Since this approach accounts for more toxicant than was
originally present, the time period should be decreased by the fractional
amount of toxicant created.  If the amount of excess toxicant is no more
than 15 percent of the total amount spilled, then a time adjustment is not
required.

     Based on the processes of sorption and diffusion the vertical profile
of dissolved chemical in the river bed at time t following the appearance of
the toxicant on the bottom is given by:

                          C - Cb
                          C  -C
                           s  L
where
     C    = concentration of dissolved chemical in the pore water, in
            units of mass of dissolved chemical per unit volume of pore
            water

     C^   = background concentration of chemical in pore water

     Cs   = solubility of chemical in water

     z    = vertical distance,  measured downward from the
            sediment-water interface
                                      555

-------
     De   = effective molcular diffusion coefficient
     PS   = density of sediments
     Kp   = partition coefficient
     n    = porosity of porous medium

     From Equation IV-151, the total mass of pollutant found in the
sediments at time t is:
                                 /•/      \
                                            ndV                     (IV-152a)

                                           :sjdz                   (IV-152b)

where

     AC = spill area
          concentrati
          volume of pore water
     C  = concentration of pollutant sorbed to sediments,  per unit
C  can be related to C by:

                             Cs = CPskp  (ITj                     (IV-153)

Combining Equations IV-151, IV-152 and IV-153 the total  mass in the sediment
is:
                  MT = 0.563nCs  l + pk          AV4             (iV-154)
                               •EXAMPLE IV-19-
     The following is an excerpt from Chemical Engineering Volume 80,
September 3, 1973, as reported in Thibodeaux  (1979).
                                   556

-------
              "Approximately 1.75 x 106 Ibs of chloroform were released
         from a barge that sank near Baton Rouge, Louisiana, and the
         chemical began flowing down the Mississippi River toward the
         Gulf of Mexico.  Although state health officials did not push
         the panic button, noting that they did not anticipate too much
         trouble from the accident, the U.S. Coast Guard warned
         downriver communities to keep a close surveillance on their
         water supply systems, particularly if intakes were close to
         the river bottom (chloroform is heavier than water).11

Based on the low flow conditions and the time history of the chloroform
concentration much of the chloroform (of specific gravity 1.5) was initially
deposited on the river bed.   Determine the fate of the chloroform during the
first few days following the spill.  The following processes are considered:

     •   dissolution into the main body of the water,

     •   diffusion and sorption into the bottom sediments,

     •   volatilization into the atmosphere, and

     •   sorption to suspended sediments.

     Since chloroform is highly volatile and does not have a strong tendency
to sorb to solids, volatilization is an important process controlling its
fate, while sorption is not.  The following analysis substantiates this
statement.

     The data pertinent to the spill are (Thibodeaux, 1979;  Neely
et al_., 1976):

     •   river flow rate = 7590 m3/sec (268,000 cfs)

     •   width of river = 1220 m = 4000 ft
                                    557

-------
     0   river velocity = 56.3 cm/sec = 1.85 ft/sec

     •   water depth = 11 m = 36.3 ft

     •   diffusion coefficient of chloroform in water = 1x10 " cmVsec

     •   length of spill zone = 180 m = 590 ft

     •   background chloroform concentration = 5 ppb

     Using a Manning's n of 0.03, the diffusion layer thickness is:

   .. _ 11.6 x  1.49 x  .915  x  10~5   / — M/R          ,              -2
   6 '                 ~   -- " X  36  7  =             =
                                                                    -
                                                              '8  X  10
The average concentration of chloroform in the water just below the spill
zone during the period of dissolution is:

       C  = (5  x  10-3  - 8200) exp— A
                                                                8200
                                   2.8 x 10~2 x  11.  x  56. 3
          =  850 ppb
In order to estimate the time required to dissolve the chloroform the
average width of the spill zone is required.   The width is estimated to be
256 ft (78 m) (Thibodeaux, 1981).

Based on these data the dissolution time is:

            T  _     .0.9 x 1.75 x_ 106               _.  ,
            'd ~ 5738 ~x .850 x T. 85 x" 156 T 3^3 = ^ days

The factor 0.9 is used in  the above expression because about 10 percent of
the spill dissolved before ever reaching the  bottom (Neely et_ aj_. ,  1976).

     The amount of chloroform which diffused  and sorbed into the sediments
during this time period (20 days)  will  be estimated.   The porosity of the
sandy bottom is approximately 0.35, and the partition coefficient is assumed
to be 1.0.  This is a realistic value  based on K   =  93 (see Table  II-5).
The total mass contained i-i the sediments after 20 days is:

-------
   MTota, -  .35  (180 x 78) (W.6S x 1 x
                                                                    .35
          x  10-2-3  x (5-4.437) ~6000 kg
6000 kg is less than 2 percent of the total mass which reaches the bottom
(715,000 kg).  Based on this result, it is not likely that the dissolution
period is markedly affected by diffusion of the chloroform into the bottom
sediments.  Because of the vertical concentration gradient that has been
established in the sediment profile, some of the chloroform will temporarily
continue to diffuse downward after the dissolution period.  Hence
concentrations in the water column due to desorption of the chloroform and
upward diffusion back into the water column are not likely to be high
compared to those observed during the initial dissolution period.

     Following the chloroform spill, chloroform concentrations were measured
at several locations in the Mississippi River below the spill.  Figure
IV-55a shows the time history of the chloroform concentration at a location
16.3 miles below the spill   for the first 60 hours following the spill.  A
more compressed time scale is shown in Figure IV-55b and illustrates how the
concentrations varied for 20 days following the spill.  The peak
concentration passes very rapidly (on the order of 1 day) and the maximum
observed concentration is about 365 ppb.   At this location, the chloroform
is approximately well-mixed with the river at this point (Neely et _a1.,
1976).

     Based on Figure IV-55b the total amount of chloroform passing the
location can be estimated as follows:

                           Mass = /CQdt = Q/ Cdt
=/CQdt = Q/"
The right-most integral is simply the area under the concentration-time
curve in Figure IV-555.  Without showing the calculations, the total mass of
chloroform (above background) which passes the location 16.3 miles below the
spill is about 300,000 kg.  Since the total amount of chloroform spilled was
about 800,000 kg, more than half of the chloroform was unaccounted for.  It
is unlikely,  as earlier calculations showed, that diffusion and sorption
                                   559

-------
   350
   300
I 250

c
o



i 200

-------
  400
  300
o

5
Q.


-------
into the bottom sediment was significant.   Volatilization could be important
arid will be discussed shortly.

     The observed results shown in Figure IV-55a are compared against those
predicted in this example.  A concentration of 850 ppb was predicted just
below the spill site;  the maximum shown in Figure IV-55a is 365 ppb.  It is
expected, for several reasons,  that the concentrations 16.3 miles below the
spill site will be less than at the spill  site.  First it is probable that
additional dilution occurred as the chloroform was transported to the
sampling site.  An estimate of  the dilution can be attained by multiplying
the river width by the spill width, or:
                                4000   _  ,,
                                 260   "
The well-mixed concentration becomes:

                                 850
                                         ,n   ,
                                      =  60 ppb
Comparing this to Figure IV-55a, it is noted that this value approximates
the average concentration following an elapsed time of about 20 hours, but
misses the peak during the first 20 hours.  There may be a number of factors
responsible for this behavior, and one of the most important will be
examined here.  During the spill of chloroform, it was estimated that about
10 percent, or 80,000 kg were transported downstream directly without ever
reaching the river bottom.  The travel time to the sampling site is:

                             16.3 mi     - _  ,
                                      =  13  hours
Figure IV-55a shows that this coincides with the arrival of the peak at mile
16.3.  The peak concentration can be estimated using Equation IV-140
presented earlier.  The diffusion coefficient is approximately 210 m 2/sec
(McQuivey _ejt aj_. ,  1976) for the lower Mississippi River.  The predicted peak
in concentration at mile 16.3 is:

                    80000 x 103
           C =  ------ — - — - — ----- = 520 ppb
               2 x 4000 x 36.3 x (.3048)2 Vn-210-3600- 13
                                   562

-------
This concentration is somewhat higher than the maximum 365 ppb observed, but
this is to be expected since Equation IV-140 assumes the mass is input
instantaneously, while in reality about 8 hours elapsed.  Further if the
concentration due to the dissolved portion of the spill is calculated at 20
hours, a concentration of 15 ppb is obtained.  This illustrates that the
mass due to initial dissolution has almost passed the sampling location, and
the remaining contribution to the elevated concentrations measured is due
largely to dissolution of chloroform which has settled on the river bottom.
It appears that there are two basic phenomena which account for the measured
concentration-time profile:  an initial period of dissolution of chloroform
(less than 1 day) before it settles to the bottom, and a subsequent period
(10 to 15 days) of dissolution of settled chloroform.

     The absence of an adequate mass balance between the amount of
chloroform which entered the river as a result of the spill and the amount
which passed a location 16.3 mi below the spill has not been addressed.
Volatilzation losses could be one reason for the imbalance.

     Equation IV-123 can be used to estimate the volatilization losses.
Since the chloroform was initially deposited on the bottom of the river,
during a portion of the travel distance it was not in contact with the
atmosphere, and so volatilization could not occur.  The approximate travel
time for vertical mixing to occur is (Fischer et a_l_., 1979):
                                 L =

where

     H  = water depth
     e  = vertical diffusivity

Choosing an ez value of 50 cm2/sec, based on Fischer e_t aJL (1979) and a
depth of 11 m, the travel time required to effect vertical mixing is

                                         hr = 2.7  hrs
                                    563

-------
Based on a velocity of 1.85 ft/sec,  the travel  distance  is  about  3.3 miles.
Hence the pollutant is in contact with the atmosphere  for  about 13 miles.

     Since only the dissolved phase  of chloroform volatilizes, the fraction
of the total chloroform as solute will be estimated using  Equation IV-109:

                                 c-c
                                    __
                                    Hkp,S
The partition coefficient K  was estimated as 1.0.   The sediment
                           P
concentration is about 400 ppm.   Hence:
                      c    .         i            =1.0
                     Ct      1 + 1 x 400 +  10~6

Thus, essentially all the chloroform  is  dissolved  and  is  available  for
volatilization.

     Henry's Law constant for chloroform can be  found  based  on  the  data  in
Table II-5:

     •   vapor pressure = 150 Torr

     •   solubility in water =  8200 ppm

     •   molecular weight = 118.

Henry's Law constant is:
                             = 3 v in
                                     -3
                  760 x 8200            mole

From Table 11-15 a typical  volatilization  rate  is  about  17  cm/hr.

     The average chloroform concentrations for  the 13  miles above  the  data
collection point are:

     200 ppb for 1 day
      40 ppb for the next  9 days
      10 ppb for the next  9 days
                                     564

-------
The total amount of chloroform volatilized is (using Equation IV-109):
   Ik   C.  A  At
     v   i   c
   =  0.17 x 24 x 1200 x 21 x 103(200 +  40 x  9 + 10 x 9 -5 x 19)x 103
   =  5.8 x  107  = 58000 kg
              g
Hence,  all  of the unaccounted for chloroform  (about 480,000 kg) could not
have volatilized within 13 miles.

     Over 50 percent of the chloroform still  remains unaccounted for.  It is
possible that other transformation processes  were operative.  The
enviromental fate of chloroform in terms of photolysis, hydrolysis,
oxidation,  and biological degradation was reviewed in Callahan et_ a]_., 1979.
It was concluded that these processes are of  minor importance compared to
volatilization and so are probably not significant here.

     It  is possible that the samples of chloroform shown in Figure IV-55b
were not cross-sectional averages.  The chloroform concentration could have
been weighted toward the stream bottom or toward one side.  A dye study
performed by McQuivey (1976) on the lower Mississippi River showed that
50 miles were required before complete mixing was attained, while the
sampling was conducted 16.3 miles below the spill.  Even though chloroform
does not sorb strongly, there is a possibility that the suspended solids and
bed load concentration near the bottom of the river were high enough  to
cause substantial sorption.  Based on the evidence there is a distinct
possibility that some of the "missing" chloroform was actually advected past
the sampling locations without being detected.
                            •END OF EXAMPLE IV-19'
                                     565

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